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Sensors Applied to Nondestructive Testing and Structural Health Monitoring

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A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Physical Sensors".

Deadline for manuscript submissions: closed (31 December 2021) | Viewed by 49335

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Special Issue Editors

Dr. Marco Laracca

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Department of Electrical and Information Engineering, University of Cassino and Southern Lazio, Via G. Di Biasio, 43-03043 Cassino, Italy
Interests: nondestructive testing; eddy current testing; ultrasounds; sensor realization; sensor characterization; power quality measurements; traceability in metrology; vehicle speed measurements
Special Issues, Collections and Topics in MDPI journals

Dr. Leandro Maio

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Guest Editor

Department of Materials, The University of Manchester, Manchester, UK
Interests: nondestructive evaluation; structural health monitoring; ultrasonic de-icing; signal processing; mechanical testing; low velocity impacts; adhesive bonding; stress analysis; fiber-reinforced composites; digital image correlation
Special Issues, Collections and Topics in MDPI journals

Dr. Vittorio Memmolo

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Guest Editor

Department of Industrial Engineering, University of Naples “Federico II”, Via Claudio 21, 80125 Naples, Italy
Interests: structural health monitoring; nondestructive testing; load monitoring; smart structures; ultrasounds and material testing
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Nondestructive testing and evaluation (NDT&E) is one of the most critical aspects in many fields. In fact, today, with the aim to guarantee the safety for both persons and components, a wide range of NDT procedures ensure that not a single manufactured component reaches service without first passing a series of stringent tests. New studies in this field have a strategic and essential role in order to reduce the NDT costs and improve the test performance. As a natural evolution of NDT procedures, structural health monitoring (SHM) has been developing fast, with the aim to reduce maintenance costs and limit design constraints. Continuous monitoring of both components and structures ensures high levels of safety, reducing the number of inspections as well.

This Special Issue focuses on fostering improvements and new developments of technology in areas related to novel techniques and approaches for characterization and real-time monitoring of components and structures in a variety of application fields (automotive, nuclear, petrochemical, archeology, cultural heritage, aerospace, and so on). We would like to invite original research articles as well as review articles that contain theoretical, analytical, and experimental investigations covering all aspects of NDT&E and SHM.

Dr. Marco Laracca
Dr. Leandro Maio
Dr. Vittorio Memmolo
Guest Editors

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Keywords

Sensors and transducers for NDT/SHM
Advanced techniques for NDT/SHM measurements
Smart sensors for NDT/SHM
Methods and systems for designing, optimizing, and characterizing NDT instruments and devices
Data processing and advanced techniques for NDT and SHM measurements
Reliability of NDT/SHM
New SHM methodologies and damage assessment criteria
Methods and devices to optimize the performance of existing NDT techniques
Artificial intelligence in the data analysis and damage prediction

Published Papers (14 papers)

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Research

19 pages, 7421 KiB

Open AccessArticle

Assessment of Damage in Composite Pressure Vessels Using Guided Waves

by Vittorio Memmolo, Leandro Maio and Fabrizio Ricci

Sensors 2022, 22(14), 5182; https://0-doi-org.brum.beds.ac.uk/10.3390/s22145182 - 11 Jul 2022

Cited by 2 | Viewed by 1665

Abstract

This paper deals with guided wave-based structural health monitoring of composite overwrapped pressure vessels adopted for space application. Indeed, they are well suited for this scope thanks to their improved performance compared with metallic tanks. However, they are characterized by a complex damage mechanics and suffer from impact induced damage, e.g., due to space debris. After reviewing the limited progress in this specific application, the paper thoroughly covers all the steps needed to design and verify guided wave structural health monitoring system, including methodology, digital modelling, reliability, and noise estimation for a correct decision-making process in a virtual environment. In particular, propagation characteristics of the fundamental anti-symmetric mode are derived experimentally on a real specimen to validate a variety of finite element models useful to investigate wave interaction with damage. Different signal processing techniques are demonstrated sensitive to defect and linearly dependent upon damage severity, showing promising reliability. Those features can be implemented in a probability-based diagnostic imaging in order to detect and localized impact induce damage. A multi-parameter approach is achieved by metrics fusion demonstrating increased capability in damage detection with promising implication in enhancing probability of detection. Full article

(This article belongs to the Special Issue Sensors Applied to Nondestructive Testing and Structural Health Monitoring)

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18 pages, 24339 KiB

Open AccessArticle

Copula-Based Uncertainty Quantification (Copula-UQ) for Multi-Sensor Data in Structural Health Monitoring

by He-Qing Mu, Han-Teng Liu and Ji-Hui Shen

Sensors 2020, 20(19), 5692; https://0-doi-org.brum.beds.ac.uk/10.3390/s20195692 - 06 Oct 2020

Cited by 5 | Viewed by 2069

Abstract

The problem of uncertainty quantification (UQ) for multi-sensor data is one of the main concerns in structural health monitoring (SHM). One important task is multivariate joint probability density function (PDF) modelling. Copula-based statistical inference has attracted significant attention due to the fact that it decouples inferences on the univariate marginal PDF of each random variable and the statistical dependence structure (called copula) among the random variables. This paper proposes the Copula-UQ, composing multivariate joint PDF modelling, inference on model class selection and parameter identification, and probabilistic prediction using incomplete information, for multi-sensor data measured from a SHM system. Multivariate joint PDF is modeled based on the univariate marginal PDFs and the copula. Inference is made by combing the idea of the inference functions for margins and the maximum likelihood estimate. Prediction on the PDF of the target variable, using the complete (from normal sensors) or incomplete information (due to missing data caused by sensor fault issue) of the predictor variable, are made based on the multivariate joint PDF. One example using simulated data and one example using temperature data of a multi-sensor of a monitored bridge are presented to illustrate the capability of the Copula-UQ in joint PDF modelling and target variable prediction. Full article

(This article belongs to the Special Issue Sensors Applied to Nondestructive Testing and Structural Health Monitoring)

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24 pages, 8129 KiB

Open AccessArticle

Monitoring the Structural Health of Glass Fibre-Reinforced Hybrid Laminates Using Novel Piezoceramic Film

by René Schmidt, Alexander Graf, Ricardo Decker, Michael Heinrich, Verena Kräusel, Lothar Kroll and Wolfram Hardt

Sensors 2020, 20(18), 5428; https://0-doi-org.brum.beds.ac.uk/10.3390/s20185428 - 22 Sep 2020

Cited by 3 | Viewed by 2446

Abstract

This work investigates a new generation structural health monitoring (SHM) system for fibre metal laminates (FML) based on an embedded thermoplastic film with compounded piezoceramics, termed piezo-active fibre metal laminate (PFML). The PFML is manufactured using near-series processes and its potential as a passive SHM system is being investigated. A commercial Polyvinylidene fluoride (PVDF) sensor film is used for comparative evaluation of the sensor signals. Furthermore, thermoset and thermoplastic-based FML are equipped with the sensor films and evaluated. For this purpose, static and dynamic three-point bending tests are carried out and the data are recorded. The data obtained from the sensors and the testing machine are compared with the type and time of damage by means of intelligent signal processing. By using a smart sensor system, further investigations are planned which the differentiation between various failure modes, e.g., delamination or fibre breakage. Full article

(This article belongs to the Special Issue Sensors Applied to Nondestructive Testing and Structural Health Monitoring)

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25 pages, 7786 KiB

Open AccessArticle

Artificial Intelligence-Based Bolt Loosening Diagnosis Using Deep Learning Algorithms for Laser Ultrasonic Wave Propagation Data

by Dai Quoc Tran, Ju-Won Kim, Kassahun Demissie Tola, Wonkyu Kim and Seunghee Park

Sensors 2020, 20(18), 5329; https://0-doi-org.brum.beds.ac.uk/10.3390/s20185329 - 17 Sep 2020

Cited by 26 | Viewed by 4131

Abstract

The application of deep learning (DL) algorithms to non-destructive evaluation (NDE) is now becoming one of the most attractive topics in this field. As a contribution to such research, this study aims to investigate the application of DL algorithms for detecting and estimating the looseness in bolted joints using a laser ultrasonic technique. This research was conducted based on a hypothesis regarding the relationship between the true contact area of the bolt head-plate and the guided wave energy lost while the ultrasonic waves pass through it. First, a Q-switched Nd:YAG pulsed laser and an acoustic emission sensor were used as exciting and sensing ultrasonic signals, respectively. Then, a 3D full-field ultrasonic data set was created using an ultrasonic wave propagation imaging (UWPI) process, after which several signal processing techniques were applied to generate the processed data. By using a deep convolutional neural network (DCNN) with a VGG-like architecture based regression model, the estimated error was calculated to compare the performance of a DCNN on different processed data set. The proposed approach was also compared with a K-nearest neighbor, support vector regression, and deep artificial neural network for regression to demonstrate its robustness. Consequently, it was found that the proposed approach shows potential for the incorporation of laser-generated ultrasound and DL algorithms. In addition, the signal processing technique has been shown to have an important impact on the DL performance for automatic looseness estimation. Full article

(This article belongs to the Special Issue Sensors Applied to Nondestructive Testing and Structural Health Monitoring)

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17 pages, 4249 KiB

Open AccessArticle

Evaluation of Bonding Quality with Advanced Nondestructive Testing (NDT) and Data Fusion

by Bengisu Yilmaz, Abdoulaye Ba, Elena Jasiuniene, Huu-Kien Bui and Gérard Berthiau

Sensors 2020, 20(18), 5127; https://0-doi-org.brum.beds.ac.uk/10.3390/s20185127 - 08 Sep 2020

Cited by 21 | Viewed by 4678

Abstract

This work aims to compare quantitatively different nondestructive testing (NDT) techniques and data fusion features for the evaluation of adhesive bonding quality. Adhesively bonded composite-epoxy single-lap joints have been investigated with advanced ultrasonic nondestructive testing and induction thermography. Bonded structures with artificial debonding defects in three different case studies have been investigated: debonding with release film inclusion, debonding with brass film-large, debonding with brass film-small. After completing preprocessing of the data for data fusion, the feature matrices, depending on the interface reflection peak-to-peak amplitude and the principal component analysis, have been extracted from ultrasonic and thermography inspection results, respectively. The obtained feature matrices have been used as the source in basic (average, difference, weighted average, Hadamard product) and statistical (Dempster–Shafer rule of combination) data fusion algorithms. The defect detection performances of advanced nondestructive testing techniques, in addition to data fusion algorithms have been evaluated quantitatively by receiver operating characteristics. In conclusion, it is shown that data fusion can increase the detectability of artificial debonding in single-lap joints. Full article

(This article belongs to the Special Issue Sensors Applied to Nondestructive Testing and Structural Health Monitoring)

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25 pages, 16013 KiB

Open AccessArticle

Experimental Investigation on Choosing a Proper Sensor System for Guided Waves to Check the Integrity of Seven-Wire Steel Strands

by Edison Z.Y. Hou, Javad Rostami, Kim Ming Ng and Peter W. Tse

Sensors 2020, 20(18), 5025; https://0-doi-org.brum.beds.ac.uk/10.3390/s20185025 - 04 Sep 2020

Cited by 3 | Viewed by 2734

Abstract

Multiple wire twisted steel strands are commonly used to hoist elevators, concrete structures, etc. Due to frequent and long-time usage, the steel strands are subjected to corrosion, overloads, and aging, making strands may fail unexpectedly. Hence, the health monitoring of steel strands becomes more important to avoid the sudden collapse of hoisting structures. Guided waves (GW) inspection methods have become favorable in recent years due to its long-distance transmission and stability of evaluation in the area of structural health monitoring (SHM) and Non-Destructive Testing (NDT). Many researchers have reported different GW methods to detect different types of defects that occurred in steel strands. However, researchers rarely carry out comparative studies to investigate the effectiveness of each method or system in monitoring the health state of steel strands. This article reports some vital observations revealed from conducting experiments by using contact and noncontact methods, which include three different popular types of GW sensors and methods during their applications in surface-type defect detection. The proper selection of sensors systems has been identified through the present study. The result of the present study is believed to be useful guidance for selecting appropriate GW methods and sensor systems to monitor the integrity of the steel strand and thereby ensure the safety of the hoisted structures. Full article

(This article belongs to the Special Issue Sensors Applied to Nondestructive Testing and Structural Health Monitoring)

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23 pages, 9172 KiB

Open AccessArticle

Wireless Ultrasound Surgical System with Enhanced Power and Amplitude Performances

by Jungsuk Kim, Kiheum You, Sun-Ho Choe and Hojong Choi

Sensors 2020, 20(15), 4165; https://0-doi-org.brum.beds.ac.uk/10.3390/s20154165 - 27 Jul 2020

Cited by 22 | Viewed by 3225

Abstract

A wireless ultrasound surgical system (WUSS) with battery modules requires efficient power consumption with appropriate cutting effects during surgical operations. Effective cutting performances of the ultrasound transducer (UT) should be produced for ultrasound surgical knives for effective hemostasis performance and efficient dissection time. Therefore, we implemented a custom-made UT with piezoelectric material and re-poling process, which is applied to enhance the battery power consumption and output amplitude performances of the WUSS. After the re-poling process of the UT, the quality factor increased from 1231.1 to 2418 to minimize the unwanted heat generation. To support this UT, we also developed a custom-made generator with a transformer and developed 2nd harmonic termination circuit, control microcontroller with an advanced reduced instruction set computer machine (ARM) controller, and battery management system modules to produce effective WUSS performances. The generator with a matching circuit in the WUSS showed a peak-to-peak output voltage and current amplitude of 166 V and 1.12 A, respectively, at the resonant frequency. The performance with non-contact optical vibrators was also measured. In the experimental data, the developed WUSS reduced power consumption by 3.6% and increased the amplitude by 20% compared to those of the commercial WUSS. Therefore, the improved WUSS performances could be beneficial for hemostatic performance and dissection time during surgical operation because of the developed UT with a piezoelectric material and re-poling process. Full article

(This article belongs to the Special Issue Sensors Applied to Nondestructive Testing and Structural Health Monitoring)

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19 pages, 9707 KiB

Open AccessArticle

A Kalman Filter-Based Method for Diagnosing the Structural Condition of Medium- and Small-Span Beam Bridges during Brief Traffic Interruptions

by Qingfei Gao, Xiang Wang and Yang Liu

Sensors 2020, 20(15), 4130; https://0-doi-org.brum.beds.ac.uk/10.3390/s20154130 - 24 Jul 2020

Cited by 1 | Viewed by 2396

Abstract

Load tests are a popular way to diagnose the structural condition of bridges, however, such tests usually interrupt traffic for many hours. To address this issue, a Kalman filter-based method is proposed to diagnose the structural condition of medium- and small-span beam bridges by using the acceleration responses obtained from the bridge during a brief traffic interruption. First, a condition diagnosis feature based on the Kalman filter innovation (i.e., the optimal difference between the filter predictions and measured responses) is presented. Second, a condition diagnosis index, which is the energy ratio between the innovation and the measured acceleration, is generated by calculating the null space of the Hankel matrix consisting of condition diagnosis features. Then, on the basis of the novel detection, a method is used to diagnose the structural condition of a bridge during a brief traffic interruption. Finally, the validity and dependability of the proposed method is demonstrated through experimental tests with a model bridge and field tests on an actual bridge. Using the proposed method, the long-time interruption of traffic flow and the reliance on finite element model are effective avoided during the process of condition diagnosis of bridges. Full article

(This article belongs to the Special Issue Sensors Applied to Nondestructive Testing and Structural Health Monitoring)

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12 pages, 3367 KiB

Open AccessArticle

Effectiveness of Non-Local Means Algorithm with an Industrial 3 MeV LINAC High-Energy X-ray System for Non-Destructive Testing

by Kyuseok Kim, Jaegu Choi and Youngjin Lee

Sensors 2020, 20(9), 2634; https://0-doi-org.brum.beds.ac.uk/10.3390/s20092634 - 05 May 2020

Cited by 11 | Viewed by 3376

Abstract

Industrial high-energy X-ray imaging systems are widely used for non-destructive testing (NDT) to detect defects in the internal structure of objects. Research on X-ray image noise reduction techniques using image processing has been widely conducted with the aim of improving the detection of defects in objects. In this paper, we propose a non-local means (NLM) denoising algorithm to improve the quality of images obtained using an industrial 3 MeV high-energy X-ray imaging system. We acquired X-ray images using various castings and assessed the performance visually and by obtaining the intensity profile, contrast-to-noise ratio, coefficient of variation, and normalized noise power spectrum. Overall, the quality of images processed by the proposed NLM algorithm is superior to those processed by existing algorithms for the acquired casting images. In conclusion, the NLM denoising algorithm offers an efficient and competitive approach to overcome the noise problem in high-energy X-ray imaging systems, and we expect the accompanying image processing software to facilitate and improve image restoration. Full article

(This article belongs to the Special Issue Sensors Applied to Nondestructive Testing and Structural Health Monitoring)

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22 pages, 14196 KiB

Open AccessArticle

Nondestructive Testing of the Miter Gates Using Various Measurement Methods

by Mikolaj Binczyk, Przemyslaw Kalitowski, Jakub Szulwic and Pawel Tysiac

Sensors 2020, 20(6), 1749; https://0-doi-org.brum.beds.ac.uk/10.3390/s20061749 - 21 Mar 2020

Cited by 10 | Viewed by 2782

Abstract

When any problems related to civil engineering structures appear, identifying the issue through the usage of only one measuring method is difficult. Therefore, comprehensive tests are required to identify the main source. The strains and displacement measurements, as well as modal identification, are widely used in the nondestructive testing of structures. However, measurements are usually carried out at several points and confirm or exclude only one of many potential causes of the problem. The main aim of this paper is to identify the causes of miter gates’ excessive vibration. The research includes displacement measurements using a tachometer and a laser scanner, acceleration measurements connected with modal analysis, and calculations with the finite element method (FEM) model. The numerical model underwent verification regarding test results. Particular attention was paid to evaluate the practical use of a laser scanner for diagnosing miter gates. Unlike classical methods, it measures many points. The analysis eliminated a number of potential causes of excessive vibration and highlighted the field of excessive deformation. The identified anomaly could be associated with bearings’ misalignment after closing the door. This construction part should be subjected to further research using classical methods. The laser scanning has been proven to be a method that can only generally present the deformation of the structure. Full article

(This article belongs to the Special Issue Sensors Applied to Nondestructive Testing and Structural Health Monitoring)

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20 pages, 7617 KiB

Open AccessArticle

Ambient Effect Filtering Using NLPCA-SVR in High-Rise Buildings

by Xijun Ye, Yingfeng Wu, Liwen Zhang, Liu Mei and Yunlai Zhou

Sensors 2020, 20(4), 1143; https://0-doi-org.brum.beds.ac.uk/10.3390/s20041143 - 19 Feb 2020

Cited by 3 | Viewed by 1994

Abstract

The modal frequencies of a structure are affected by continuous changes in ambient factors, such as temperature, wind speed etc. This study incorporates nonlinear principal component analysis (NLPCA) with support vector regression (SVR) to build a mathematical model to reflect the correlation between ambient factors and modal frequencies. NLPCA is first used to eliminate the high correlation among different ambient factors and extract the nonlinear principal components. The extracted nonlinear principal components are input into the SVR model for training and predicting. The proposed method is verified by the measured data provided in the Guangzhou New TV Tower (GNTVT) Benchmark. The grid search method (GSM), genetic algorithm (GA) and fruit fly optimization algorithm (FOA) are applied to determine the optimal hyperparameters for the SVR model. The optimized result of FOA is most suitable for the NLPCA-SVR model. As evaluated by the hypothesis test and goodness-of-fit test, the results show that the proposed method has a high generalization performance and the correlation between the ambient factor and modal frequency can be strongly reflected. The proposed method can effectively eliminate the effects of ambient factors on modal frequencies. Full article

(This article belongs to the Special Issue Sensors Applied to Nondestructive Testing and Structural Health Monitoring)

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16 pages, 22269 KiB

Open AccessArticle

Beam Damage Detection Under a Moving Load Using Random Decrement Technique and Savitzky–Golay Filter

by Hadi Kordestani, Chunwei Zhang and Mahdi Shadabfar

Sensors 2020, 20(1), 243; https://0-doi-org.brum.beds.ac.uk/10.3390/s20010243 - 31 Dec 2019

Cited by 57 | Viewed by 3505

Abstract

In this paper, a two-stage time-domain output-only damage detection method is proposed with a new energy-based damage index. In the first stage, the random decrement technique (RDT) is employed to calculate the random decrement signatures (RDSs) from the acceleration responses of a simply supported beam subjected to a moving load. The RDSs are then filtered using the Savitzky–Golay filter (SGF) in the second stage. Next, the filtered RDSs are processed by the proposed energy-based damage index to locate and quantify the intensity of the possible damage. Finally, by fitting a Gaussian curve to the damage index resulted from the non-damage conditions, the whole process is systematically implemented as a baseline-free method. The proposed method is numerically verified using a simply supported beam under moving sprung mass with different velocities and damage scenarios. The results show that the proposed method can accurately estimate the damage location/quantification from the acceleration data without any prior knowledge of either input load or damage characteristics. Additionally, the proposed method is neither sensitive to noise nor velocity variation, which makes it ideal when obtaining a constant velocity is difficult. Full article

(This article belongs to the Special Issue Sensors Applied to Nondestructive Testing and Structural Health Monitoring)

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13 pages, 4646 KiB

Open AccessArticle

Detecting Debonding between Steel Beam and Reinforcing CFRP Plate Using Active Sensing with Removable PZT-Based Transducers

by Jian Jiang, Jinwei Jiang, Xiaowei Deng and Zifeng Deng

Sensors 2020, 20(1), 41; https://0-doi-org.brum.beds.ac.uk/10.3390/s20010041 - 19 Dec 2019

Cited by 14 | Viewed by 3247

Abstract

Carbon fiber reinforced polymer (CFRP) plates are widely used to retrofit or reinforce steel structures, and the debonding damage between the steel structure and the CFRP plate is a typical failure in strengthening steel structures. This paper proposes a new approach to detecting debonding between a steel beam and a reinforcing CFRP plate by using removable lead zirconate titanate (PZT)-based transducers and active sensing. The removable PZT-based transducers are used to implement the active sensing approach, in which one transducer, as an actuator, is used to generate stress wave, and another transducer, as a sensor, is used to detect the stress wave that propagates across the bonding between the steel beam and the reinforcing CFRP plate. The bonding condition significantly influences the received sensor signal, and a wavelet-packet-based energy index (WPEI) is used to quantify the energy of the received signal to evaluate the severity of debonding between the steel beam and the reinforcing CFRP plate. To validate the proposed approach, experimental studies were performed, and two removable PZT-based transducers were designed and fabricated to detect the debonding between a steel beam and the reinforcing CRFP plate. The experimental results demonstrate the feasibility of the proposed method in detecting the debonding between a steel beam and the reinforcing CFRP plate using removable PZT-based transducers. Full article

(This article belongs to the Special Issue Sensors Applied to Nondestructive Testing and Structural Health Monitoring)

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27 pages, 10932 KiB

Open AccessArticle

Automatic Management and Monitoring of Bridge Lifting: A Method of Changing Engineering in Real-Time

by Yao Min Fang, Tien Yin Chou, Thanh Van Hoang and Bing Jean Lee

Sensors 2019, 19(23), 5293; https://0-doi-org.brum.beds.ac.uk/10.3390/s19235293 - 01 Dec 2019

Cited by 1 | Viewed by 10157

Abstract

In recent years, owing to the increase of extreme climate events due to global climate change, the foundational erosion of old bridges has become increasingly serious. When typhoons have approached, bridge foundations have been broken due to the insufficient bearing capacity of the bridge column. The bridge bottoming method involves rebuilding the lower structure while keeping the bridge surface open, and transferring the load of the bridge temporarily to the temporary support frame to remove the bridge base or damaged part with insufficient strength. This is followed by replacing the removed bridge base with a new bridge foundation that meets the requirements of flood and earthquake resistance. Meanwhile, monitoring plans should be coordinated during construction using the bottoming method to ensure the safety of the bridge. In the case of this study, the No. 3 line Wuxi Bridge had a maximum bridge age of 40 years, where the maximum exposed length of the foundation was up to 7.5 m, resulting in insufficient flood and earthquake resistance. Consequently, a reconstruction plan was carried out on this bridge. This study took the reconstruction of Wuxi Bridge as the object and established a finite element model using the SAP 2000 computer software based on the secondary reconstruction design of the Wuxi Bridge. The domestic bridge design specification was used as the basis for the static and dynamic analyses of the Wuxi Bridge model. As a result of the analysis, the management value of the monitoring instrument during construction was determined. The calculated management values were compared with the monitoring data during the construction period to determine the rationality of the management values and to explore changes in the behavior of the old bridges and temporary support bridges. Full article

(This article belongs to the Special Issue Sensors Applied to Nondestructive Testing and Structural Health Monitoring)

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