Planetary gearbox is a critical component for many mechanical systems. It is essential to monitor the planetary gearbox health and performance in order to maintain the whole machine works well. The methodology of mechanical fault diagnosis is increasingly intelligent with the extensive application of deep learning. However, the cross-domain issue caused by varying working conditions becomes an enormous encumbrance to fault diagnosis based on deep learning. In this paper, in order to fully excavate potentialities of deep neural network architectures, a novel generative adversarial learning method was introduced for a completely new fault diagnosis based on a deep convolution neural network. In addition, the intelligent fault diagnostic scheme for planetary gearbox under varying speed conditions was developed. After that, some experiments on measured vibration signals of planetary gearbox were conducted to verify the validity and efficiency of the fault diagnostic scheme. The results showed that the proposed method enhanced the capability of the intelligent diagnosis for planetary gear faults under varying speed conditions. Planetary Gearbox (PG) is widely used in different sorts of machinery, owing to its compact structure, large transmission ratio, strong load capacity, and high efficiency, such as helicopters, wind turbines and robots in manufacturing systems. The vital role that the planetary gearbox plays in a mechanical system makes its fault diagnosis become really significant. Most researchers use the vibration signal of the machine to diagnose its health status. However, the information inside the vibration signal is intricate and masked by many noise components. Lei and Feng built mathematical vibration models to show the multi-frequency components inside the signal and their experiments validated the fact that the planetary gearbox vibration signal was complicated for fault diagnosis ,2. So, fWhile various methods have been developed for the fault diagnosis of planetary gearboxes, the intelligent fault diagnosis method is more and more widely utilized to tackle complicated mechanical diagnosis problems due to its adaptive learning mechanism, strong fault tolerance and high non-linear regression ability ,5. CombiIn recent years, Deep Learning (DL) has been attracting growing attention from various fields. The deep model hierarchical structures make DL capable of learning intrinsic representations of raw complex data, which provide the foundation for its popular application in visual recognition and natural language processing ,11,12,13As for the DL-based fault diagnoses, they have tremendous ability of feature extraction and state recognition in different domains if there are sufficient various data for training. However, it is a notoriously slippery task to get enough labeled data in various domains for diagnosis model training to overcome the problem of cross-domain, especially in the practical engineering field. In this paper, Generative Adversarial Network (GAN) is introduced for training the fault diagnosis model to fully exploit the potentialities of the intelligent diagnostic scheme without enough experimental data. The GAN-enhanced CNN is constructed for intelligent fault diagnosis of PG. Through theoretical design and experimental verification, the methodology is better for the PG fault diagnosis under varying working conditions than normal CNN. The rest of the paper is organized as follows. The generative adversarial learning architecture is described in G takes a random noise vector z as an input and outputs a series of signal fakeX = G(z), which simulates the vibration signal of PG. The discriminator D receives either a real vibration signal or a generated fake signal from the generator as input and outputs of a probability distribution P(S | X) = D(X) over possible signal sources. The discriminator is trained to minimize the log-likelihood loss function Ls that forces it to assign to the correct source:GAN framework is introduced for intelligent fault diagnosis model training, which consists of two neural networks trained in opposition to one another. The generator z. The Auxiliary Classifier GAN (ACGAN) framework is adopted as shown in In addition, the generator in GAN is trained to minimize the quadratic term in Equation (1). However, the fault status and the working conditions have important influences in the formation of PG vibration signals. The fault class and working condition are employed as inputs independent of c ∼ cp and working condition label, w ∼ wp in addition to the noise z. G uses all of these to generate vibration signals fakeX = G. The discriminator gives both a probability distribution over sources and a probability distribution over the labels, such as P(S | X), P(C | X) and P(W | X). The loss function has three parts: the log-likelihood of the correct source, SL of Equation (1); the log-likelihood of the correct fault class, CL of Equation (2); and the log-likelihood of working condition, WL of Equation (3).Every generated sample has a corresponding fault class label, D is trained to minimize SL + CL + WL while G is trained to minimize CL + WL − SL. This ACGAN frameworks can learn a representation for z that is independent of the fault class label and working condition.In the ACGAN scheme, z vectors to the same output x, which is assigned a high probability of being real by the discriminator. The common view of mode collapse and instability in GAN training is that it is caused by the supports of real and model distributions being disjoint or lying on low-dimensional manifolds, and the generator cannot get useful gradients to learn [x is the gradient against real data x. This works as a small perturbation of real data, which is to constrain its gradients in the ambient data space and is likely to lie off the data-manifold. In the training process, the instance noise δ of dN is input to the discriminator with real data. The loss functions for discriminator D and generator G can be synthesized asL(D) is the loss function of the discriminator, and L(G) is the loss function of the generator; Sλ, Cλ, Wλ, and Rλ are the coefficients of each loss in the synthesized loss function, which are selected as 1, 3, 5, and 0.5 in the later experiments.Mode collapse is a vital issue to consider when training and implementing the GAN framework. The training is said to result in mode collapse if the generator ends up mapping multiple to learn . A novelto learn .LR =Ex∼A deep CNN architecture is always composed of several convolution blocks to enhance the feature representation ability of CNN. A convolution block is normally composed of convolution layers, activation layers, pooling layers, and so on. According to the extracted features by convolution block, some activated fully connected layers and soft-max function follow afterward, acting as a classifier. The convolution layer performs the convolution operation on the input signal to produce an output to the next layer. Because the vibration signal is a one-dimensional time series, the convolution kernel vector with size Because the bias effect will be counteracted in the next batch normalization layer, the bias parameters in the convolution formula are omitted. By mean of accumulation and abbreviation, the characteristics in multiple frequency bands can be represented in only one feature map, so the number of network parameters is reduced dramatically and the CNN architecture can be made deeper.The vibration signal of PG is unstable because of the variable working conditions. Batch Normalization (BN) is designed to re-scale the input feature map to reduce the shift of internal covariance. The transformation of the BN layer isf is adopted after the convolution layer. The activation output is defined asFor increasing the nonlinear properties of the final decision function without affecting the receptive fields of the convolution layer, nonlinear activation function Rectified Linear Units (ReLU) is often preferred to the other activation functions in CNN. ReLU activation function applies the non-saturating activation function to the input features. The employed ReLU activation function isz is taken as the latent space for the generator. The side information includes fault class and working condition information. The fault class is one-hot encoded into a 64 × 1-dimensional vector c. Here, the rotation speed working condition is just considered according to the real data samples in our experiments. Binary encoding is used to encode the attribute of rotation speed as a 64 × 1-dimensional vector w. The vector z, c and w are connected together into a 256 × 1-dimensional vector, which is input into the generator. The input vector is extended into 512 dimensions through the fully connected layer at first. Then, 10 convolution blocks are utilized to modulate the input signal into different pattern signals. After that, four deconvolution blocks are used to up-sample the adequately modulated signal into a 8192 × 1-dimensional fake signal.A 128-dimensional random noise vector As shown in The PG vibration signals or fake signals are input to the discriminator of fault diagnosis. As shown in The vibration signals for validation of GAN-enhanced CNN were collected from the planetary gearbox fault diagnosis test rig shown in The raw vibration signals of the planetary gearbox were sampled with a sampling frequency of 12,000 Hz. For three health states of a normal gearbox, gearbox with a tooth clipped planet gear, and gearbox with a surface worn planet gear, the vibration signals were collected under five speed conditions, and in total, 15 segments of vibration signals were obtained. About 10,000 pieces of data sets with 8192 data points were made in each segment through sliding window. The working frequency details of the vibration signals are shown in At the beginning of the experiment of PG vibration signal generation, the WC-D were treated as the target domain for the uncertain various speed conditions, and the rest of the four kinds of test data sets  composed the source domain data as the training data sets. After the training of GAN-enhanced CNN with the test data sets in the source domain, the generator could generate the vibration signals of normal gearbox, gearbox with tooth clipped planet gear, and gearbox with surface worn planet gear under various rotation speed conditions. The comparisons of real vibration signals and generated vibration signals of different state gearboxes in source domains were made at first. For representation of generated vibration signals and real vibration signals in source domains, In The comparisons of real vibration signals and generated vibration signals of different state gearboxes in the target domain of WC-D are shown as After training of GAN-enhanced CNN with the test data sets in source domain, not only can the generator produce the vibration signals, but also the discriminator can classify the fault of PG. In the experiments, the fault classification accuracy of a batch of generated vibration signals was applied as evaluation criterion. In the experiment of the fault diagnosis in the target domain, the train sets are used to train the neural network model, and validation sets are used to evaluate the training quality. In verification of the GAN-enhanced CNN fault diagnosis ability in the target domain under various speed conditions, the four kinds of working conditions from the total five conditions were selected as source domains, and the other one was treated as the target domain. For comparison, at first the experimental data sets in the source domains of WC-A, WC-B, WC-C, and WC-E were utilized as training data for the CNN, and then the generated data in all the domains and the experimental data in source domains were employed for training the GAN-enhanced CNN. In order to reveal the detail of the differences between the CNN and the GAN-enhanced CNN, 100 data sets in the target domain of WC-D were tested at the end of each training epoch that was up to 20,000. The comparison of cross-domain fault diagnosis performance of CNN and GAN-enhanced CNN is shown in Then the other experiment was conducted in order to validate further how the GAN enhanced CNN model performed in different target domains under various speed conditions. When the neural network model has been trained to have satisfying performance on validation sets, it can be used in the diagnosing stage. The data sets in four kinds of speed conditions from the total five conditions were chosen as training data, and the data sets in the other one condition were employed as the target domain data sets that were used in the diagnosing stage. The result accuracies of GAN-enhanced CNN and normal CNN in the target domain are shown in The varying working conditions cause feature distribution changing of the vibration signal in the time domain and frequency domain, which will provoke the trouble of the cross-domain for intelligent fault diagnosis. The fault diagnosis of PG under varying working conditions is hard and tedious. We proposed an intelligent diagnostic scheme based on GAN-enhanced CNN to address the problem. The GAN architecture is designed combining the fault classes and working conditions of PG. The deep neural network model of the generator can simulate the dynamic model of PG and can generate the vibration signals of PG in different fault states under varying working conditions after generative adversarial learning. In addition, the CNN model of the discriminator is trained by the measured vibration signals in the source domain and enhanced by the generated vibration signals of the generator in the target domain. The cross-domain fault diagnosis accuracy of GAN-enhanced CNN under varying working conditions is as much as 99.5% in the experiments. The results prove that the cross-domain accuracy of GAN-enhanced CNN is 15.22% on average, and up to 30.9% higher than that of the normal CNN in the experiments. It is verified that the GAN-enhanced CNN can be utilized to diagnose the fault states of PG under varying working conditions with much accuracy. We will keep researching the fault diagnostic scheme that can measure the deviation between source domain and target domain and cross-domain intelligent fault diagnosis with only a few labeled training examples.


Due to long propagation distance and high sensitivity to a variety of damages, ultrasonic guided wave technologies have been widely applied in the damage detection or health monitoring of pipe networks and large plate-like structures. However, there are two important problems to be solved when applying this technology; namely, the large scanning time required for monitoring large-scaled structures and the serious crosstalk between the actuation and receiving signals, especially when monitoring hot-spot regions. Therefore, this study mainly designed key parts, such as the matrix switcher and attenuation circuit. The single-actuation and multiple-simultaneous-reception (SAMSR) mechanism based on an analog switching matrix and a low noise charge amplifier circuit was designed and integrated with the SPI control bus to shorten the scanning time. Moreover, a two-stage attenuation circuit with an interlocking isolation structure is presented to effectively isolate the receiving signals from the actuation signals to obtain ultra-low crosstalk even under a high voltage actuation source. In this study, the designed matrix switcher and other components were integrated into the developed ultrasonic guided wave monitoring system. Several experiments were conducted on a stiffened composite structure to illustrate the effectivity of the developed SAMSR ultrasonic guided wave system by comparing the signals collected with those from a commercial ultrasonic guided wave system. As an efficient and flexible online/offline damage inspection and diagnosis method, ultrasonic guided wave technology has already been widely applied in the damage inspection of engineering structures such as pipes, railways, plate-like structures and connected structures ,2,3. GenThe hardware system of ultrasonic guided waves is the connecting and processing center of piezoelectric sensor networks and damage diagnosis algorithms. The system’s core function is to excite the piezoelectric sensor to generate ultrasonic guided waves in the structure and collect and process the guided wave signal perceived by the other sensors. The hardware system of ultrasonic guided waves includes, mainly, a signal generator, a signal collector, a sensor network and a matrix switcher. The switcher is used to connect these three components. In recent years, many research institutes and companies have developed some ultrasonic guided wave monitoring systems, and conducted preliminary application verification. For example, the US company ACELLENT has developed the commercial ultrasonic guided wave detector ScanGenie III, which adopts pitch- catch data scanning mode  and can support the input of up to 128 channels in the sensor array. Yuan Shenfang et al.  designedCrosstalk mainly occurs in active ultrasonic guided wave detection systems, especially in systems where actuation and acquisition sensor networks are shared. The higher the actuation signal voltage, the more obvious the crosstalk phenomenon is. In the application of some high viscoelastic materials, such as composite materials, it is often a requirement to generate ultrasonic guided wave signals with high signal to noise ratios (SNRs) brought by sufficient vibration of PZT sensors with high actuation voltage. Generally, actuation voltage with maximum amplitude within ±70 V is often selected ,10,11. FIn addition, as the monitoring area increases, the number of sensor networks will increase rapidly, as do the times of actuating and acquitting in a damage scan cycle. However, in the scanning process, to ensure that the signals between the primary and secondary actuation do not affect each other, each actuation must wait for the complete disappearance of echo ultrasonic guided waves generated by the former actuation. Therefore, when collecting a large number of sensor channels in the traditional pitch-catch data acquisition mode, the scanning cycle is long, and thus the overall monitoring efficiency may be affected by environmental changes . In fact(1)Ultrasonic guided wave signals with ultra-low crosstalk can be obtained even under high voltage actuation;(2)The damage detection efficiency is increased effectively by a SAMSR operation mode;(3)The effect of crosstalk is minimized as much as possible to realize the precise damage location of a hot-spot;(4)The large-scaled structures can be monitored by the developed system due to its strong scalability. The attenuators at all levels are controlled by the same control signal from the attenuation design of interlocking isolation structures. When the attenuation series increase, the switching time would not increase correspondingly. Theoretically, the analog switch matrix based on SPI control bus structures can realize the expansion of any multichannel sensor network and the synchronous acquisition of any multichannel.Aiming at the application demand of ultrasonic guided wave technology based on piezoelectric sensor networks in structural health monitoring, this paper designs an active SAMSR ultrasonic guided wave monitoring system with ultra-low crosstalk, and focuses on the design of the matrix switcher and other core components. These key components mainly include a 64-channel and single-actuation and multiple-simultaneous-reception analog switch matrix based on SPI  control bus and the four-channel low noise charge amplifier circuit, and a two-stage attenuation circuit and a six-layer shielding circuit board based on the interlock isolation structure, where the actuation is shielded by ground envelope and highly isolated from the received signal. Moreover, the designed matrix switcher and other core components are integrated into the developed ultrasonic guided wave system; the signals collected by the system and those of commercial use ultrasonic guided wave system are compared and analyzed; and the damage location experiment of hot-spot areas is also carried out in this paper. The major advantages of this system are listed as follows:An ultrasonic guided wave active monitoring system is commonly composed of a sensor network; signal actuation and acquisition hardware; and signal control and processing software . The eleUltrasonic guided wave active monitoring technology uses a PZT sensor mounted on the surface of the structure being tested to actuate ultrasonic guided waves, and then the wave’s signal is transmitted within the structure and finally received by other sensors. If the ultrasonic guided wave interacts with the damage during the propagation, the received ultrasonic guided wave then contains damage information which can be obtained by comparing it with the ultrasonic guided wave when the structure is not damaged . TherefoFocused on the crosstalk encountered and the SAMSR operation mode, this paper analyzes mainly, the reasons behind it and its design basis.In the ultrasonic guided wave monitoring system, in order to reduce the number of sensors, the actuation and acquisition sensors basically share the same set and they are switched by a matrix switcher. Effective isolation can be achieved by a semiconductor switching device at low voltage, and crosstalk signals can be suppressed . HoweverWhen the actuation and acquisition system are completely separated in the design of hardware system, there is no current loop between the actuation and acquisition signal, so the crosstalk problem can indeed be solved. However, because sensors cannot be shared, the number of sensors would then be multiplied, which increases the complexity of the system. If sensors are to be shared, the key of the system lies in the design of matrix switcher; i.e., how to achieve effective isolation between actuation and reception.The traditional SASR operation mode is displayed in As can be seen from the SASR signal sampling process, when PZT 1 is first actuated as the actuation source, all the other PZTs will receive ultrasonic guided wave signals simultaneously. If signals from multiple sensors can be collected into the system at the same time, the number of actuation and delay times can be greatly reduced, thereby reducing scanning time. Therefore, this paper designs a SAMSR operation mode; i.e., when the same five PZTs are used as the actuation source separately, the whole damage scan cycle requires only five rounds of actuation and delay. The core problem of this design also lies in the design of matrix switcher to make it possible that any sensor can be switched to actuation source, and the other four sensors can be switched to acquisition channels, and the four channels can sample synchronously.The overall design of the active SAMSR ultrasonic guided wave with ultra-low crosstalk system is displayed in Each sensor channel of the matrix switcher is designed with a two-stage attenuator to highly isolate the actuation from the reception channels. The primary attenuator is composed of a high speed SPDT (single pole double throw) reed relay. An SPDT reed relay has a set of mechanical inter-block with NO  contacts and NC  contacts. The switching time of it is generally less than 2 ms, and the reed relay contacts are protected by inert gas, preventing them from oxidizing and giving them long contact life. As shown in A four-channel 64 × 1 multiplexers is designed for the ultrasonic guided wave reception channels of the matrix switcher, forming an analog switching matrix. In the design of the primary attenuator, the sensors are connected to reception channel by default; therefore, except for the actuation sensor, all the other sensors are connected with the 64 × 1 multiplexer of each reception channel by default. The STM32 controller on the matrix switcher connects all channel multiplexers in series through the SPI control bus, forming a daisy-chain control structure, which allows any four sensors to be selected as the reception sensor and makes the extension of more simultaneous reception channels more convenient. Because the ultrasonic guided wave signal acquired by the sensor is a very weak charge signal and the output impedance is high, a charge amplifier is designed on each reception channel.9 GOhm. The secondary attenuator adopts an SPST reed relay of the CRR05 series; the maximum switching time of it is less than 0.6 ms; and the isolation resistance is up to 1014 Ohm. As the control signals of the primary and secondary attenuator are connected in parallel, the overall switching time is less than 1.5ms. In the scanning process, the delay of milliseconds between the two excitation signals is also required to wait for the echo to disappear, so the reed relays switching speed would not affect the damage scanning cycle. The drive signal of the reed relay is provided by two relay driver chips ADG732 (32 to 1) directly, which constitutes a multiple selector (64 to 1). STM32 controller outputs a 6-bit address bus, controlling the decoder and realizing 6–64 address decoding. The analog switch matrixes of the collection channels are composed of 32 pieces of ADG738 analog multiplexers with low resistance in series, which is controlled by the SPI bus of STM32 to achieve four-channel 64–4 multiplexers. By controlling the four-channel multiplexers and taking any four sensors except the actuation as the collection sources, the four channels’ ultrasonic guided wave signals could be received synchronously and output to the independent low noise charge amplifier circuit.This paper takes the sensor input of 64-channel as an example to achieve the SAMSR operation mode with the frequency of the actuation signal ranging from 50 to 700 kHz and an voltage amplitude in the range of ±70 V. Feasibility verification was carried out and the circuit schematic diagram is shown in Since the principle of damage detection and location for an ultrasonic guided wave system is to compare the changes of signals before and after the damage, the noise and phase shifts of acquired signals will have a great impact on the damage detected accuracy. The received signal of the PZT is a weak charge signal, which needs to be amplified by the charge amplifier before it can be accurately collected by the data acquisition system. In this paper, according to the performance requirement of 1M bandwidth acquisition signal, OPA132 chips are adopted to design the primary power amplifier circuit and the primary voltage amplifier circuit (as shown in p-p of the power supply noise under 4.4 mV. As displayed in the diagram of p-p) is suppressed under 6mv, as shown in the diagram of In order to prevent the acquisition signal from generating different phase shifts at different frequencies, which would affect the repeatability and accuracy of damage detected accuracy, no hardware filtering is set in the signal collection channel; the phase-shift-free Savitzky-Golay algorithm is used in the software for filtering instead. In terms of hardware, the Π filter and the LDO (low dropout regulator) filter are used, which puts the VTo reduce the crosstalk between the actuation signal and the reception signal in the PCB routing, the matrix switch PCB adopts a six-layer structure in which devices are mounted on the top and bottom layer, and the high voltage actuation signal is mainly routed in the bottom layer, and it is surrounded by ground envelope and shielded by a layer of GND. The 64-channel PZT signals are routed in layers 1 to 4, and each adjacent channel is distributed in different layers. The layered design ensures the shielding and isolation between different signals, and each signal is shielded by GND, which ensures that each signal is transmitted independently and is not disturbed by electromagnetic interference. As shown in Based on the PXI platform of NI, this paper designs and builds an ultrasonic guided wave detecting system into which a SAMSR ultra-low crosstalk matrix switcher is integrated. Simulated damage location and identification experiments were carried out on the hot-spot areas of composite materials. The experimental platform is displayed in The composite material board is 450 × 450 × 3 mm in size, with a T-shaped stiffener (height 40 mm) and a thickness of 1.7 mm, which is glued to the main board to simulate the glued connection structure of hot-spot areas ,20. The Under the same experimental conditions, the ScanGenie III ultrasonic guided wave detector produced by ACELLENT and the proposed system in this paper are used for the crosstalk test of the system respectively. The frequency of the actuation signal center is set at 250 kHz, and different actuation and reception sensors are selected. The acquired signals are shown in Since the damage location of the ultrasonic guided wave system is based on the comparative analysis of the signals before and after the damage, the repeatability of the signals collected by the system is very important. Displayed in Error is calculated by standard mean square error. The system developed in this paper and ScanGenie III are tested with the actuation center frequency as 50–700 kHz. The results are shown in Firstly, the experimental plate is scanned at a frequency of 50–700 kHz, and the frequency that maximizes the effective signal amplitude is obtained; i.e., the resonance frequency of PZT and composite material plate. At this frequency, the acquisition signal has the highest SNR. After frequency scan, the resonance frequency in this experiment obtained is about 300 kHz. Therefore, five peak modulated sine waves with a central frequency of 300 kHz are taken as the actuation signal to collect the baseline signal and damage signal respectively. The baseline signal is the signal acquired from all paths under the condition of no damage, and the damage signal is the signal of all the measured paths after the simulated damage when an absorbing adhesive (size Φ25 mm) is placed on the glued connection structure of the surface under testing with the same actuation of the reference signal. The elliptic weighting algorithm ,22 is us(1)A two-stage attenuating circuit with an interlocking isolation structure is designed to achieve high isolation between actuation and acquisition signals. Under high voltage (±70 V) actuation, ultrasonic guided wave signals with ultra-low crosstalk can also be obtained.(2)This design supports the input of an up to 64-channel sensor array and adopts the mode of single-actuation and four-simultaneous-reception. In this system, any sensor can be used as the actuation source and the other four as the reception source, which effectively improves the acquisition efficiency.(3)The system has been verified on composite materials of hot-spot areas, for which the effect of crosstalk is almost eliminated and the accurate damage location is achieved.(4)This design has strong expansibility and can be applied to higher actuation voltage and large-scaled area monitoring.This paper designed and developed an active SAMSR ultrasonic guided wave monitoring system with ultra-low crosstalk. In this system, the core part, i.e., the 64 × 4 ultra-low crosstalk matrix switcher, was developed and integrated with 4-channel charge amplifiers with low noise and phase shift. The SAMSR operation mode and 64 channel of PZTs input are supported in the developed system. A simulated damage location experiment was carried out on composite materials with hot-spot regions; good results were obtained. The matrix switcher is designed to verify the effect of the design scheme proposed in this paper. By optimizing the selection of chip devices further, higher integration can be achieved. The main contributions of the system include:


Digital Image Correlation (DIC) provides measurements without disturbing the specimen, which is a major advantage over contact methods. Additionally, DIC techniques provide full-field maps of response quantities like strains and displacements, unlike traditional methods that are limited to a local investigation. In this work, an experimental application of DIC is presented to investigate a problem of relevant interest in the civil engineering field, namely the interface behavior between externally bonded fabric reinforced cementitious mortar (FRCM) sheets and concrete substrate. This represents a widespread strengthening technique of existing reinforced concrete structures, but its effectiveness is strongly related to the bond behavior between composite fabric and underlying concrete. To investigate this phenomenon, a set of notched concrete beams are realized, reinforced with FRCM sheets on the bottom face, subsequently cured in different environmental conditions (humidity and temperature) and finally tested up to failure under three-point bending. Mechanical tests are carried out vis-à-vis DIC measurements using two distinct cameras simultaneously, one focused on the concrete front face and another focused on the FRCM-concrete interface. This experimental setup makes it possible to interpret the mechanical behavior and failure mode of the specimens not only from a traditional macroscopic viewpoint but also under a local perspective concerning the evolution of the strain distribution at the FRCM-concrete interface obtained by DIC in the pre- and postcracking phase. Digital Image Correlation (DIC) is a noncontact measurement technique that is increasingly used in several engineering fields. DIC techniques provide full-field maps of response quantities like strains and displacements, which represent a more complete set of information than local measurements obtainable by traditional approaches. On the one hand, there are required (preliminary) operations of DIC such as the need to apply a stochastic pattern (sprayed pattern) to the surface of the material, which might not always be possible. On the other hand, there are many advantages of DIC, such as the relatively simple experimental setup, the adjustable spatial and temporal resolutions, the possibility of examining specimens with different dimensions and involved materials, and the adaptability to different loading rates ranging from quasistatic to dynamic . What isSome of the most interesting applications of DIC include the investigation of the mechanical behavior of concrete structures. Indeed, concrete is a heterogeneous material characterized by a complex fracture behavior, which is difficult to be analyzed with conventional contact measurement approaches like local strain gauges. Moreover, analyzing the failure process of concrete structures is challenging because cracks exhibit micrometric dimensions, are broadly diffused on the material, and rapidly evolve in the internal microstructure. In this regard, DIC proves to be a reliable full-field measurement approach, as demonstrated by the good results reported in previous studies. Choi et al.  were amoOf particular relevance to this research work, DIC can be usefully employed to investigate the interface behavior between externally bonded composite systems and concrete substrate, which represents a widespread strengthening technique for retrofitting existing concrete structures. The oldest and most popular strategy consists of externally bonding fiber-reinforced polymer (FRP)  sheets oAs a more recent alternative, fabric reinforced cementitious mortar (FRCM) sheets represent the natural evolution of FRP systems in which an inorganic (cement-based) matrix is used in place of an epoxy matrix ,19. The In the literature, FRCM-concrete bond behavior was generally investigated by single-lap shear tests wherein the load is directly applied to the strengthening system. Instead, in this paper the bond behavior is analyzed by an alternative notched beam test setup in accordance with ASTM D7958/D7958M standards . In the Experimental three-point bending tests on concrete notched beams with externally bonded PBO-FRCM sheets are conducted for specimens subject to different environmental conditions (humidity and temperature), in order to assess whether these factors influence the bond behavior .Mechanical tests are performed vis-à-vis DIC measurements using two distinct cameras simultaneously, one focused on the concrete front face and another focused on the FRCM-concrete interface. This experimental setup makes it possible to interpret the mechanical behavior and failure mode of the specimens not only from a traditional macroscopic viewpoint but also under a local perspective concerning the evolution of the strain distribution at the FRCM-concrete interface obtained by DIC.Along such research line, in this paper an experimental application of DIC for the investigation of PBO FRCM-concrete interface bond behavior is documented. The novel contributions of this experimental work in comparison to other studies are summarized as follows:Prismatic concrete beams are prepared using an ordinary Portland cement. The characterization of the concrete properties is made in terms of compressive strength and flexural strength, evaluated on standard specimens at 28 days in accordance with UNI EN 12390-3:2009 and UNI EN 12390-5: 2002 standards, respectively. The mean compressive strength of six standard cubes of 150 mm side is 47 MPa, with a coefficient of variation (CoV) of 9%; the mean flexural strength of six prismatic specimens is 6 MPa, with a CoV of 1.92%. The FRCM is made of PBO mesh embedded in a cement-based mortar. The PBO bidirectional woven has an unbalanced configuration in the two directions, with fiber density higher in the main direction compared to the lateral direction, as shown in Prismatic concrete beams with nominal dimensions 150 × 150 × 500 mm are casted in preformed formworks, demolded after 24 h, and wrapped with a wet cloth to prevent water evaporation during the next 28 days, as shown in DIC is a nondestructive and noncontact optical measurement technique widely used to investigate the distribution of strains and displacements of different structures . This meM + 1) × (2M + 1) pixels, where M is a positive integer number and other than 0. The subset size is critical to DIC accuracy, so it should be properly selected according to the actual random intensity distributions of the speckle patterns [P, centered in a reference facet, moves to the new position P’0 within the deformed facet. This displacement and the consequent strain are estimated using a cross-correlation (CC) or sum-squared difference (SSD) correlation algorithm, which identifies the similarity between the reference and the deformed facet. From a mathematical point of view, this involves searching for the peak of the distribution of the correlation coefficients. Specifically, the location of the target subset is identified, once the maximum or the minimum correlation coefficient has been found, depending on the used correlation criterion. Instead, the strain field can be obtained by numerical differentiation.The fundamentals of the DIC measurement process  are illupatterns . As the The registration and computation algorithms aim to ensure the best correlation between the interrogated facets. However, to achieve this goal, it is necessary to pursue a balanced compromise between spatial resolution, pattern speckle quality and computation time . In factThree-point bending tests are performed according to ASTM D7958/D7958M standards , using afour specimens are cured in air at laboratory environmental conditions for 31 days (temperature 23 °C ± 2 °C and relative humidity 65–75%);four specimens are placed in a curing tank for 31 days, with their bottom face  immersed in water (relative humidity 100%) at a controlled temperature of 30 °C;four specimens are placed in a curing tank for 31 days, with their bottom face  immersed in water (relative humidity 100%) at a controlled temperature of 50 °C.The tests comprise different environmental conditioning of the specimens. After the application of the externally bonded PBO-FRCM sheet, three curing conditions are considered see :four speThe goal of this investigation is to ascertain the influence of the environmental factors in the FRCM-concrete interface bond behavior. Apart from the laboratory conditions, two serviceability conditions are considered. The first conditioning temperature (30 °C) can be meant as a service temperature that is frequently experienced in summer seasons, while the second conditioning temperature (50 °C) can represent an ultimate limit state condition that is hardly exceeded in ordinary conditions.The use of correct lens and of high-resolution images plays a crucial role in the correct evaluation of the response and is essential for obtaining reliable results. For this reason, an appropriate DIC test setup has been conceived in this experimental campaign to ensure the highest resolution and a correct measurement ,67.Two reflex cameras, models Nikon D3100 and Nikon D300s, are used in this work, called camera 1 and camera 2 in The synchronization of the acquisition is carried out by connecting a trigger port of the mechanical test equipment with a remote control for the two cameras. The rate of acquisition is set as one photo every 6 s, until the specimen failure. Depending on the lens models used in the two cameras, it is necessary to adopt different focal values, as listed in The set of digital images was elaborated using the DIC software GOM Correlate 2020 .The results of the three-point bending tests on the notched concrete beams with externally bonded PBO-FRCM sheets are illustrated here in terms of load-deflection curves. The graphs in All the recorded curves show an initial elastic branch, in which the behavior of both concrete and FRCM composite system is linear. A clear peak is observed at a deflection equal to approximately 0.5 mm for all the specimens. Thereafter, a decrease of load occurs according to a typical trend of a concrete beam structure. The second part of all curves exhibits a local maximum and a slow nonlinear reduction of the measured load. This curve can be interpreted from a mechanical point of view, by also critically considering alternative single-lap shear tests available in the literature for the same material . The peaFor all the beams, the complete failure is related to the PBO mesh debonding from the mortar matrix. As shown in Considering the reasonably good agreement between the four repetitions of beams for each curing class, only some representative results among the tested specimens are selected and discussed concerning DIC test results. As said above, the two cameras allow the examination of two distinct regions of interest of the beams, namely concrete front face above the notch (camera 2) and FRCM-concrete interface (camera 1). In The DIC-processed images of the longitudinal strains refer to different stages of the loading application, which are identified by a set of characteristic points A-F in the relevant load-deflection curve (the point S represents a “starting point” close to the origin). The branch S-A denotes a linear elastic behavior of both concrete and FRCM. This is corroborated by the corresponding DIC strain distributions shown for the two regions of interest. Specifically, point A highlights the incipient cracking of concrete, while point B denotes the incipient cracking of mortar, with the concrete above the notch already partially cracked. By further increasing the load from point A to point B leads to the attainment of the tensile strength above the notch and, consequently, the neutral axis depth moves from the area close to the notch tip up to the loading point. This leads to the formation of a main crack above the notch, with a resulting tortuous pattern up to the top compressed fiber of the concrete beam (point B) and complete reduction of concrete contribution to the element strength, with the crack width gradually increasing (point C). The whole process is visible in terms of strain distribution between point A and point C obtained by camera 2 . ConcurrIn the initial beam behavior, the beam contribution and the FRCM contribution are mutually interacting. Once the concrete cracking and mortar cracking occur, the FRCM contribution prevails. In the interfacial bond behavior, the concrete is completely cracked, as shown in the DIC images. The load level C corresponds to the attainment of the mortar cracking. Once the critical deflection of point C (around 0.5 mm) is exceeded, a clear softening branch is observed from point C to point D, which is related to the residual tensile stress of concrete observed in the range of narrow crack widths ,70. ThisIt is worth noting that the characterization of the bond behavior at the FRCM-concrete interface is assisted by the DIC images, which allow a clearer interpretation of the mechanical behavior of the notched concrete beam, especially in the precracking phase. More specifically, the DIC-processed images explain the interaction of the two parallel resisting contributions in the specimens and the stress transfer mechanism with the increase of the vertical deflection of the beam. By inspection of the images related to the camera 1, it can be seen that the DIC strain maps are very useful to anticipate the incipient crack initiation of both concrete and mortar matrix under service conditions and the subsequent initiation and development of PBO mesh sliding from mortar matrix. To clarify this aspect and to investigate the effect of the different curing conditions of the samples, some DIC images aimed at capturing the occurrence of incipient crack and crack development are reported in Finally, In conclusion, as demonstrated by these outcomes, the DIC technique can be used to assess the bond behavior at the FRCM-concrete interface or to determine the status of the interfacial properties after an exceptional event , which could be useful to plan local repair interventions and, in general, for structural health monitoring purposes. After a first initial stage in which an almost zero displacement is observed, once the concrete beam has started its cracking then the notch opening grows linearly with the deflection. It is interesting to observe that the opening of the notch proceeds with an almost linear trend. Consequently, it is not significantly affected by the cracking of the mortar matrix and by the progressive debonding of PBO.Any slippage of the concrete beam with respect to the FRCM would highlight a limited adhesion capacity of the mortar matrix to the concrete substrate. This paper has presented an experimental campaign focused on the characterization of the interfacial bond behavior between externally bonded PBO-FRCM sheets and concrete substrate, assisted by DIC. The FRCM-concrete interface bond behavior is investigated via DIC technique by using two cameras simultaneously, one focused on the concrete area above the notch and another focused on the FRCM-concrete interface. Three-point bending test on notched concrete beams in accordance with ASTM D7958/D7958M standards are carried out. Prior to testing, the specimens were subjected to different environmental conditions (humidity and temperature), in order to assess whether, and to what extent, these factors influence the bond behavior.Twelve specimens have been analyzed, and the qualitative trends of the load-deflection curves are quite similar and are marginally affected by the curing conditions. This demonstrates that the performance of the FRCM system is not negatively affected by temperature increase, at least for the relatively short duration of the thermal treatment and temperature range involved in this experimental campaign .After the attainment of cracking in concrete (above the notch) and in FRCM mortar (at the interface), the subsequent branches of the load-deflection curve are related to the stress transfer mechanism at the FRCM-concrete interface and resemble the typical stress-global slip curve observed in alternative single-lap shear tests available in the literature for the same material. For all the beams, the failure mode is ascribed to the PBO mesh debonding from the mortar matrix.DIC images of the longitudinal strains have facilitated the interpretation of the mechanical behavior of the specimens and have better explained the interaction of the two parallel resisting systems (concrete and FRCM composite), something that is impossible to capture by the observation of the mere load-deflection curves. These images have revealed that the temperature condition applied to the bottom part of the specimen has slightly altered the stress transfer mechanism with the increase of the vertical deflection of the beam in the precracking phase and has generated a premature cracking of concrete above the notch.By inspection of the DIC images it is clearly seen that the curing conditions affect the mechanical behavior of the specimen in the precracking phase only. On the contrary, after cracking of mortar takes place, the elongation of the PBO mesh increases until subsequent debonding from the mortar matrix, and this phenomenon is almost comparable in the two curing conditions, which is also confirmed by the qualitative agreement of the load-deflection curves observed for the two classes of specimens.The main results of this research work are summarized as follows:


We appreciate the comments made by Konerding  and are First, our assumption for the scale level of the satisfaction ratings draws from a well-known conceptual framework: the 3-factor model of customer satisfaction -6. This Statistical Analysis), and the approach using the log-log regression model to estimate elasticities is well established in the literature of econometric models of demand [Second, the methodological assumptions to empirically identify the 3-factor model of customer satisfaction are clearly spelled out in our methods section (see our paper , subsectf demand . ElasticThird, in our work , we emphFourth, we provide a robustness check in our paper  to show Taken together, we are thankful for the fruitful discussion concerning our main approach, which has led us to clearly spell out the assumptions under which our results are valid, and to emphasize the robustness check that supports the validity of our main approach. We advise researchers to bear these assumptions in mind when interpreting our results and especially when adopting our main approach to empirically identify nonlinear slopes from rating data.


Propagation delays of GNSS signals caused by the ionosphere can range up to several meters in zenith direction and need to be corrected. Geodetic receivers observing at two or more frequencies allow the mitigation of the ionospheric effects by forming linear combinations. However, single frequency users depend on external information. The ionosphere delay model Regiomontan developed at TU Wien is a regional ionospheric delay model providing high accuracy information with a latency of only a few hours. The model is based on dual-frequency phase observations of a regional network operated by EPOSA (Echtzeit Positionierung Austria) and partners. The corrections cover a geographical extent for receiver positions within Austria and are provided in the standardized IONEX format. The performance of Regiomontan as well as its application in Precise Point Positioning (PPP) were tested with our in-house PPP software raPPPid using the so-called uncombined model with ionospheric constraint. Various tests, e.g., analyzing the coordinate convergence behavior or the difference between estimated and modeled ionospheric delay, proving the high level of accuracy provided with Regiomontan. We conclude that Regiomontan performs at a similar level of accuracy as IGS final TEC maps, but with explicitly reduced latency. The upper part of the atmosphere ranging from approximately 60 to 2000 km  is reRegarding signals in the microwave band, the ionosphere is a dispersive medium. Thus, the ionosphere refraction can be mitigated using a linear combination (LC) of two or more observables of the same type , but at different frequencies see . HoweverA simple model for correcting about 50% of the ionosphere refraction is the Klobuchar model . The modThe approach of the NeQuick model ,6, whichHoque et al.  addresseMost commonly used ionosphere delay models consider only the first-order term of the propagation delay. However, there are numerous studies that investigate the impact of the higher order terms of the ionospheric delay e.g., ,12). Alr. Alr12])Ionosphere delay models can also be derived from Precise Point Positioning (PPP) algorithms utilizing the ionosphere-free LC. Rovira-Garcia et al.  calculatIn a very recent study, Li et al.  presenteThe Regiomontan model presented in this paper aims to provide a high precision ionosphere delay information for single-frequency users with a latency as short as possible and independent from PPP. Regiomontan was developed at TU Wien as part of the correspondent project funded by the Austrian Research Promotion Agency (Österreichische Forschungsförderungsgesellschaft (FFG)) ,18. AfteTo demonstrate the performance of Regiomontan, we present its application in PPP in comparison to ionosphere models of the highest quality and the ionosphere free linear combination. PPP is one of the most promising processing techniques for GNSS data and was firstly proposed by Zumberge et al. . The cooAn introduction to the theoretical background of ionospheric delay estimation is given in f is the frequency of the electromagnetic wave, and s. The constant 2 and a height of the slant signal path [16 electrons/m2.When considering only the first-order term, the relation between electron density and ionosphere refraction can be expressed as e.g., ,30,31): can be written as:The ionosphere is a dispersive medium for microwave signals, as Equation  indicateConversely, the ionospheric delay can be estimated by forming the geometry-free LC for code observations Equation ), and fuEquation .(4)P4=PR the mean Earth radius, H the height of the single layer, and The highest electron density occurs in the so-called F2 layer with a peak density height ranging from 250 to 500 km . Thus, aThe global behavior of the ionosphere can then be expressed by a spherical harmonics (SH) expansion of the VTEC . EvaluatVTEC . The IGSVTEC .The SLM forms the theoretical basis of the Regiomontan model. The The center of the Taylor expansion ongitude . The IPPd orbits . The stad orbits  and partTo estimate the model parameters Equation ), the VTEquation ) is formEquation  is elimiEquation ) is estiThe obtained ionospheric delay Equation  and, subEquation .IGS products are employed to account for satellite Differential Code Biases Equation . The staEquation  for the  the IGS  and the t of one day, bundling all observations of the interval Based on Equation , the RegThe results of the parameter estimation for 1 December 2019, day of year , accurate observation models, and sophisticated algorithms, which all are applied on the observation of a single GNSS receiver. In that way a coordinate accuracy at the dm to cm level for the float solution and at the cm to mm level for the fixed solution can be achieved. Normally, a Kalman filter is used to estimate the coordinates and additional parameters. PPP is an absolute positioning method and in contrary to relative positioning methods  no nearby reference station or network are needed. On the other hand, PPP has a non-negligible convergence time, and, to make PPP more competitive against other high-precision GNSS positioning techniques, scientific research focuses on diminishing convergence periods. As the classical PPP approach using the ionosphere-free linear combination (IF LC) is limited in that regard, the uncombined model based on the raw GNSS observation equations has become quite trendy in the last few years.The classical PPP approach uses observations on two frequencies to build the IF LC which removes the first-order ionospheric delay. As terms of higher order of the ionosphere can be neglected for PPP, the ionospheric delay is completely eliminated from the mathematical model. Therefore, in this formulation, no information about the ionospheric delay can be obtained or be introduced from, e.g., an ionosphere model such as Regiomontan. Building the IF LC increases the observation noise, which elongates the coordinate convergence time  and is nb also contain constant hardware biases and are estimated as real valued numbers therefore. To solve the ambiguities to their integer values, these hardware biases have to be considered for the satellites and the receiver for which different approaches exist [Equations  and 10)10) show bination . In compes exist . Thanks es exist .The so-called uncombined model applies the raw GNSS observation (Equations  and 3)))3)). Theable way . It woulable way  when satEquations  and 13)13) presequations  and 10)Pi and phThrough adding modeled ionospheric delays to each satellite on the first frequency as ionospheric pseudo-observations to the observation model (Equation ), we gett is the time since the start of the solution and t. At the initial epoch of the solution, the ionospheric pseudo-observations are weighted with variance A crucial point when using ionospheric pseudo-observations is their observation variance and weighting in the Kalman filter. If the ionospheric pseudo-observations are weighted too high, the estimated ionospheric delay will be dragged too much to the ionosphere model and its imperfection (“over constraining”). However, also too low weights (“under constraining”) will degrade convergence . FollowiEquation  is used.found in  where thIn our work, the ionospheric delay is calculated from the Regiomontan model, which is provided in the IONEX format . The valIn a first step, Regiomontan was validated by applying model delays to carrier-smoothed pseudo-range observations Equation ) is stroIn this section, the Regiomontan and for comparison also other high-quality ionosphere models are introduced as background models in our uncombined PPP process. Therefore, the final global ionosphere models (GIM) of the International GNSS Service (IGS) and the Center of Orbit Determination in Europe (CODE) were chosen. The coordinates of the different PPP solutions were assessed in terms of convergence time and accuracy. Additionally the difference between the estimated and modeled ionospheric delays was studied and the values of the estimated receiver DCBs were investigated.Regiomontan is an ionospheric model calculated from regional GNSS data and therefore only stations in Austria were chosen for testing. The EUREF stations GRAZ, PFA3, LINZ, SBG2, and TRF2 and two one-month periods in June and December 2019 were selected to cover seasonal different ionospheric conditions. Be aware that the EUREF station GRAZ, which is used here, is different from station GRAZ of the EPOSA network, which was used for the calculation of the Regiomontan model. The PPP calculations were performed with our in-house software raPPPid, which is part of the Vienna VLBI and Satellite Software (VieVS PPP). For the uncombined model with ionospheric constrained ionospheric pseudo-observations from Regiomontan (REGIO), the final IGS GIM or the final CODE GIM was used. To make a fair comparison with the IF LC, only two frequencies were processed also in this PPP model. As described in Convergence is defined as the point in time when the difference to the true coordinates is under a certain threshold and stays there for the remaining convergence period. As expected, the uncombined model with Regiomontan, IGS or CODE as ionospheric background shows better convergence than the IF LC, especially in the first minutes of PPP processing and the difference vanishes over time. This is a result of the higher noise of the IF LC and the use of an ionosphere background model. Comparing the different ionosphere constraints, Regiomontan performs slightly worse than the IGS model and the CODE model shows the best convergence behavior. A difference between the solutions with various ionospheric constraints can mainly be found in the first 5 min. The number of converged solution becomes increasingly similar over time as the ionosphere estimation of the PPP solution gets more reliable and more independent of the ionospheric pseudo-observations used in the first epochs and additionally the constraint is released through the increase of the variance of the ionospheric pseudo-observations.The above findings were confirmed when looking at the coordinate accuracy. To assess the coordinate accuracy, the mean of the 3D position error of all convergence periods for specific points in time after reset is presented in The difference between the modeled and estimated ionospheric delay of all processed epochs is shown in The estimated receiver DCBs of the station GRAZ are shown in the upper part of To give an idea which PPP results can be achieved for single-frequency GPS observations as soon as the Regiomontan model is available (early morning of the next day The Regiomontan model presented in this paper is a regional ionospheric delay model approximating the SLM in a Taylor expansion of degree two. The parameters are calculated using the geometry-free LC of code-leveled phase observations and the model corrections are distributed in the IONEX format. Processing a regional network leads to a comparably low computational effort and, thus, Regiomontan is provided with a latency of only a few hours.A first validation of Regiomontan was performed by forming range residuals between corrected The PPP tests showed that the use of Regiomontan as ionospheric background model leads to much better PPP results than the IF LC in terms of convergence and the same accuracy is achieved after convergence. We also expect that successful integer ambiguity resolution should be accelerated with Regiomontan in our further research. In the PPP solution, Regiomontan performs nearly as good as the final ionosphere models from IGS and CODE, as shown through analyzing the coordinate convergence behavior, the coordinate accuracy, and the difference between estimated and modeled ionospheric delay. No seasonal dependency was found. The shown consistency between the estimated receiver DCBs in the PPP solution and the estimated values from CODE provides another way of validation of the Regiomontan model. With more tests and novel ideas on the weighting of the ionospheric pseudo-observations, the PPP results with the uncombined model with ionospheric constraint may improve in future.


In this paper, AISI 316L stainless steel part is obtained by laser metal deposition additive manufacturing method. The microstructure of the part was observed and analyzed by an optical microscope. The tensile mechanical properties and residual stress distribution of the part were tested by tensile test and the contour method. The results show that the bulk structure is mainly columnar crystal and equiaxed crystal, and the latter layer of laser metal deposition will form a remelted zone and heat-affected zone in the former deposition zone. Tensile test results show that the tensile strength of tensile specimens parallel to laser scanning direction and perpendicular to laser scanning direction is basically the same, but the elongation of the specimens perpendicular to the laser scanning direction is relatively better. The main reason is the different distribution characteristics of columnar crystals and equiaxed crystals in the two directions. Relatively large deformation occurs on the cut surface of the specimen after low-speed wire cut. The residual stress test results indicate that tensile stress is formed in the upper part and it reaches 315 MPa at the top surface. And compressive stress is formed at the part/substrate interface and the substrate. Additive manufacturing (AM), as an emerging manufacturing technology, has been widely used in aerospace , medicalAdditive manufacturing process consists of a group of modern manufacturing technologies that are used to produce three-dimensional prototypes from CAD representations , 8. For In addition, due to the complex thermal effects in the additive manufacturing process, the residual stress distribution in the part is complicated. The residual stress of the part may exceed the yield strength of the alloy, affecting corrosion resistance, fracture toughness, crack propagation behavior, and fatigue performance , 16. MukIn this paper, AISI 316L stainless steel parts were fabricated by LMD. The microstructures and tensile properties parallel to and perpendicular to the laser scanning direction were observed and tested. Fracture modes were analyzed, and residual stress distribution of the components was measured by the contour method.μm and 75 μm and had a good degree of sphericity that enabled a smooth powder feeding flow. The substrate was an AISI 1045 medium carbon steel plate with a composition listed in Z-axis direction, which agrees with the height of each layer of the alloy. The finished alloy serves as a new substrate to carry the new alloy.AISI 316L alloy powder obtained by gas atomisation was used in this study. The morphology of the powder is shown in After the completion of LMD build, the microstructures of the deposits at different locations were examined after mechanical grinding/polishing and etching by using aqua regia reagent. An optical microscope (OM) was used to observe the microstructure. It is known that an additive manufactured component exhibits anisotropic mechanical properties; therefore, in this study, tensile tests were conducted on specimens taken along both longitudinal and transverse directions. μm. The acquired contour point clouds from two opposite surfaces were subsequently processed by averaging and bivariate spline fitting to generate a smooth surface and eliminate measurement errors. The representative profile of deformed cutting surface is shown in The longitudinal residual stress distribution in the LMD part was analyzed using the contour method , 23. At Y-axis, when the compressive stress on the path L5 is the largest, the tensile stress on the path L4 is the smallest. Along the path L4, the tensile stress on both sides is the largest, about 100 MPa, and gradually decreases toward the middle, and it is compressive stress in the middle portion. The compressive stress on both sides of the path L5 is the smallest, about -180 MPa, and the compressive stress in the middle region is the largest, which can reach -375 MPa.The microstructure results show that the LMD 316L parts are mainly composed of columnar crystals and equiaxed crystals. The microstructure distributions perpendicular and parallel to the laser scanning direction are different, resulting in differences of tensile properties in the two directions. The sample elongation of the specimens perpendicular to the laser scanning direction is 3% higher than that in the parallel direction, and the tensile strengths in the two directions are almost the same. The contour stress measurement results show that the tensile stress is observed at the upper side and then changes gradually to compressive stress at the bottom in the LMD part. The maximum tensile stress and compressive stress are 320 MPa and -375 MPa, respectively.


The enlargement of the cracks outside the permitted dimension is one of the main causes for the reduction of service life of Reinforced Concrete (RC) structures. Cracks can develop due to many causes such as dynamic or static load. When tensile stress exceeds the tensile strength of RC, cracks appear. Traditional techniques have limitations in early stage damage detection and localisation, especially on large-scale structures. The ultrasonic Coda Wave Interferometry (CWI) method using diffuse waves is one of the most promising methods to detect subtle changes in heterogeneous materials, such as concrete. In this paper, the assessment of the CWI method applied for multiple cracks opening detection on two specimens based on four-point bending test is presented. Both beams were monitored using a limited number of embedded Ultrasonic (US) transducers as well as other transducers and techniques , LVDT sensors, strain gauges, and Fiber Optics Sensor (FOS)). Results show that strain change and crack formation are successfully and efficiently detected by CWI method even earlier than by the other techniques. The CWI technique using embedded US transducers is undoubtedly a feasible, efficient, and promising method for long-term monitoring on real infrastructure. Infrastructure is the foundation for economic development of the society of a country. Along with population growth, a rising rate of urbanization, and more communication between different regions, the demand for more infrastructure increases . RC is the most widely used material in the construction industry due to its durability, rapid construction, and low maintenance cost. The combination gives the advantage of using two materials as a composite material (RC); concrete has a strong compressive strength and steel has a high tensile strength. This allows almost unlimited range of uses of RC in infrastructure . UsuallyStructural Health monitoring (SHM) is playing an increasing role in infrastructure management. SHM refers to permanent monitoring using installed sensors, including processing and interpretation in terms of structure health. The Non-Destructive Testing (NDT) technique is the highest quality assurance tool which allows the assessment of quality and condition of structure with out damaging the original structure. A wide variety of NDT methods have been developed and used for decades in the manufacturing industry and in the civil engineering domain, for example, ground penetrating radar ,3,4, lasThe sonic method is one of the most reliable and commonly used methods among all NDT techniques because of the direct relationship of wave velocity and the physical and mechanical properties of the material. Acoustic Emission (AE) is an efficient passive method to detect impending damage in concrete by analysing the wave generated by a sudden release of energy from the material under investigation. The application of AE used in infrastructure is described in ,13,14. HThe paper is organised starting with the theory of the CWI method presented in Traditionally, sonic methods or vibration measurements for Structural Health Monitoring (SHM) are performed below 20 kHz; the wavelength is larger than or of the order of the macroscopic size of the structure . Thus, iThe features extracted by the CWI method are relative velocity change (dV/V) and correlation coefficient (CC). In this method, the velocity change is considered to be dilation or compression in time by a factor g method . First, proposed . In the proposed . Damage proposed . In thisThe ultrasonic sensor used in these experiments is ‘SO807’ which is a hollow piezoceramic US transducer designed by Acoustic Control Systems, Ltd. exclusively for BAM. It can be easily installed in the structure during the construction before casting ,29. MoreAmplifier to amplify the input signal of transmitterPre-amplifier with analog filter to improve the signal recorded by receiverDigital-analog data acquisition module to convert signalMultiplexer with 20 channels to switch between different combinations of transducersPC with control software and data storageThe data acquisition system  allows cTwo similar RC specimens were designed to perform four-point bending tests at BAM and NEOSTRAIN. The dimension of the beams is 290 cm × 20 cm × 40 cm (length × width × height). The beam at BAM  was reinEOSTRAIN  was reinMultiple sensoring techniques are applied in the two bending test. The details of the techniques are listed in A limited number of US transducers was attached on the stirrups and installed inside both beams before casting. Two vibrating wire strain gauges and two rebar stress meters were installed in the beam at NEOSTRAIN to measure the strain variation in the beam and the rebar. As the quantity and position of all the cracks were not predictable, only four LVDT sensors were glued on the back surface of the beam at BAM to measure the Crack Opening Displacement (COD) for a few cracks on the surface and to double verify the FOS measurement. Strain changes and crack width inside the beam were also measured by FOS. Although FOS technique was not applied at NEOSTRAIN, DIC technique which covered the whole beam still provided a roughly COD and propagation map. Position and spacing between all the transducers are shown in A step-wise loading procedure was performed for the test at BAM due to the low measurement frequency of the interrogator of FOS technique. In total, 64 load steps were performed. The load increased 5 kN/min and remained stable for one minute until 20 kN. For the following steps, the load increases 1 kN/min and remained stable for one more minute until reaching 80 kN as shown in At the end of the test, fourteen cracks appeared at the beam at BAM and eight cracks occurred in the beam at NEOSTRAIN. The locations of the cracks are presented in The deflections of two beams during the four-point bending test are shown in The stress-strain relationship can distinguish between different stages of the crack opening: the uncracked stage, the crack formation stage and the stabilised cracking phase . Figure The corresponding load to the moment when cracks enter different phases are listed in xx and receiver yy during the initial stage of the beam at NEOSTRAIN are plotted in As an example, signals measured by transducer combinations CC and dV/V of all the transducer combinations calculated by all the different CWI methods are presented in Unusual behaviors of transducer 04 were detected. The CC and dV/V of all the transducer combinations related to transducer 04 varied too much compared to other combinations which were located in the symmetrical positions of the beam. Signals recorded by inearity  at arouninearity , while bat 47 kN  by all tAs shown in According to the results of both experiments, the CWI method shows a high sensitivity to stress change in the structure. In the uncracked phase, when the tensile stress increases, relative velocity decreases linearly. When cracks started to form, the linearity was broken.In a real case, the exact locations of cracks are normally unpredictable, thus LDVT sensors were used only as an auxiliary tool. The DIC technique is easy to implement; however, to compare with FOS, the measuring range and accuracy are relatively low. The LVDT and DIC results proved the reliability of the FOS measurement. The crack opening and location are determined by FOS technique. The first crack(s) opening was detected at 37 kN by transducer combination The FOS technique was not used in this experiment. Nonetheless, the DIC technique provided a rough COD measurement and clear cracks map. CC and dV/V of all transducer combinations varied suddenly at 18 kN due to a misoperation during the load procedure. This proves again the high sensitivity of CWI method to stress variation. A change was detected by CC and dV/V of transducer combination e others .In this study, three CWI algorithms show their feasibility and reliability. Each of them has both advantages and disadvantages. The standard CWI method requires the shortest processing time as it stretched only once the first reference signal. It shows the continuous variation compared to the initial state. However, when cracks appear and the damage in the structure reaches a certain level, it is hard to extract information from both CC and dV/V. Thus, the auto reference CWI method is proposed when the velocity change reached a threshold and a new reference is chosen. This method reduces the dV/V variation range and provides a clearer view. The step-wise CWI method needs a heavier processing procedure as the reference changes all the time; therefore, all the signals need to be stretched. To accelerate the calculation, a lower resolution could be chosen to calculate dV/V as the change between two adjacent signals are not that big. Nonetheless, step-wise CWI shows the clearest and most precise local variation. The dV/V could be accumulated to observe the global variation, relative to the beginning of experiment. The unusual sudden changes observed by standard or auto reference CWI are successfully eliminated. This is the so-called accumulated CWI.The CWI method shows a very high sensitivity to detect stress changes in the specimens. The increasing bending tensile stress leads to a decrease in relative velocity change. Its capability to detect early stage damage in reinforced concrete is also proven. CWI detects cracks earlier than all the other standard traditional sensors, even though the cracks are not in the direct path area between two transducers. This shows the independence of CWI technique from the location of the structural flaw. Although CWI technique could not detect the quantity and location of all the cracks as precisely as FOS and DIC do, an approximate location and damage level of crack(s) can be still inferred in a very early stage. Moreover, as compared with FOS technique, the cost of data acquisition system is significantly lower and the embedded US transducers have higher damage resistance than FOS. The two specimens were monitored by limited numbers of US transducers continuously during the whole bending test. In practical applications, the authors suggest that the use of only two US transducers is enough to monitor a three-meter beam. Due to the easy installation of SO807 transducer and the small size of the US data, which allows remote monitoring, CWI method combined with embedded US transducers will definitely have a bright future for long-term monitoring in SHM.


The location of an acoustic emission (AE) source is crucial for predicting and controlling potential hazards. In this paper, a novel weighted linear least squares location method for AE sources without measuring wave velocity is proposed. First, the governing equations of each sensor are established according to the sensor coordinates and arrival times. Second, a mean reference equation is established by taking the mean of the squared governing equations. Third, the system of linear equations can be obtained based on the mean reference equation, and their residuals are estimated to obtain their weights. Finally, the AE source coordinate is obtained by weighting the linear equations and inserting the parameter constraint. The AE location method is verified by a pencil lead break experiment, and the results show that the locating accuracy of the proposed method is significantly higher than that of traditional methods. Furthermore, the simulation test proves that the proposed method also has a better performance (location accuracy and stability) than the traditional methods under any given scale of arrival errors. Acoustic emission (AE) location technology is an important nondestructive testing method that is widely used in many applications, including underground tunnels, deep mining, environmental acoustics, and the petrochemical and aerospace industries ,6,7,8,9.To date, numerous methods have been proposed to locate AE sources, including the maximum likelihood method , IngladaIn recent years, considerable efforts have been made to develop AE location methods without measuring wave velocity ,32. Das To further improve the location accuracy, a weighted linear least squares solution of AE source location without measuring wave velocity is proposed. In this method, the mean reference equation is first established to linearize the governing equations. Then, the residuals are estimated to weigh these linear equations. Finally, the location result considering the parameter constraint is obtained by introducing an orthogonal projection matrix. The pencil lead break experiment and simulation analysis are combined to verify its effectiveness and accuracy.The method addressed here determines the location of an AE source with sensor coordinates and arrival times. Let ined see . If the Our goal is to determine the AE source using these M of these equations to obtain the average reference equation:To linearize the governing Equation (2), the traditional methods always choose one of the sensors as the reference sensor. However, the selection of the reference sensor always leads to a biased location result . To reduM linear equations:Subtracting Equation (3) from squared Equation (2) to obtain In the presence of arrival noise, the equation residuals are added to Equation (4) and expressed in matrix form as:V and K, denoted by A.Without considering the constraint in Equation (3) and the residual estimation, the least square solutions of the intermediate variables , denoted by D. However, the ordinary least solution in Equation (7) is not optimal; the estimation of the equation residuals and the constraint among parameters x, y, z, V, and K will be further exploited to improve the location accuracy.The least square solution of AE source coordinate When Equation (1) is used to express The first term is the Gaussian random vector and its mean value  is a constant . TherefoHowever, the parameter V, denoted by B in different weights; After determining the covariance matrix A at different weights.The weighted least square solution of the intermediate variable V can be obtained:Substituting Equations (13) and (14) into the constraint of Equation (3), the cubic equation of variable V in closed form, denoted by By solving the cubic equations, the variable v can be further obtained by:Moreover, the optimal average wave velocity The whole procedure of the new method is shown in A pencil lead break experiment was performed on a monitoring system with a 200 × 179 × 84 mm granite block to verify the feasibility of the proposed method, as shown in Before locating an AE source, the arrival times should be determined first. Because the power of the P wave is far higher than that of environmental noise, there will be a significant take-off at the corresponding waveform with the P wave arriving. The corresponding time of the first take-off point is generally determined as the time of arrival. The arrival errors significantly affected the location accuracy ,52. Due As shown in In this paper, a weighted linear least squares location method for an AE source without measuring wave velocity is proposed. First, the mean reference equation is established by transforming the governing equations for all the sensors, which are used to obtain the system of the linear equations. Second, the ordinary least squares solutions are obtained by solving this linear system and are used to estimate the equation residuals. Third, the equation residuals are transformed into weights to obtain the weighted least squares solutions in terms of velocity squared. Finally, the optimal positioning result is obtained by combining the weighted least square solution with the parameter constraint. The proposed method highlights the following advantages: (1) the influence of the measurement error of the average wave velocity on the location accuracy is eliminated; (2) the equation residuals are estimated to obtain the weights, and a better location result is obtained; (3) the selection of the reference sensor is avoided, and the biasness caused by the reference sensor is reduced; (4) the AE source coordinate and the intermediate variables are separately solved by orthogonal projection, lowering their mutual influence; (5) the closed-form solution of the AE source coordinate is obtained, avoiding the compute-intensive work and nonconvergence. The pencil lead break experiment verifies that a more stable and accurate location result can be gained by the proposed method compared with the traditional methods. The simulation results indicate that the new method always has a better location performance than the traditional methods under different error scales, whether the AE source is inside the sensor array or not. Actually, with the increase in the error scales, the average absolute distance errors of the inside AE source are always smaller and increase more slowly than those of the outside AE source. Herein, the sensor array is suggested to surround the monitored area as much as possible.The proposed method is not limited by the type of transmitted wave. As long as the arrival time of the transmitted wave and the coordinates of the sensor are determined, the location of the source can be obtained. However, there is still a limitation because the basic assumption of this method is that the propagation path of the AE signal from the source to the sensor is a straight line, while the actual propagation path is commonly complicated. Therefore, future research should be carried out to address this limitation.