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Sensor and Sensing Technologies for Structural Health Monitoring and Non-Destructive Testing

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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 July 2023) | Viewed by 39335

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Special Issue Editors

Prof. Dr. Victor Giurgiutiu

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Guest Editor

Department of Mechanical Engineering, University of South Carolina, Columbia, SC, USA
Interests: structural health monitoring; damage detection; sensor design; guided wave; scatter cube; non-axisymmetric guided waves
Special Issues, Collections and Topics in MDPI journals

Dr. Hanfei Mei

E-Mail Website
Guest Editor

Department of Mechanical Engineering, University of South Carolina, Columbia, SC, USA
Interests: composite modeling; nondestructive evaluation; structural health monitoring; ultrasonic guided waves; finite element modeling
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

With recent advancements in sensor technology, Structural Health Monitoring (SHM) and Nondestructive Evaluation (NDE) systems have been developed and implemented in various civil structures, such as bridges, buildings, tunnels, power plants, and dams. Many advanced types of sensors, from wired to wireless, have been developed to continuously monitor structural conditions through real-time data collection.

With the remarkable progress that has been made following SHM and NDE developments, considerable work remains to be carried out, such as refining theoretical analysis and calibration against well-planned experiments, developing novel sensors for industrial and commercial applications, addressing the operational and environmental variations to deploy SHM and NDE techniques for in-service structures, developing signal analysis methods to achieve a probability of detection, and developing novel imaging algorithms to quantify the damage detection. Papers on topics include, but are not limited to, one or several of the following aspects, which will be considered for publication:

guided wave actuation and detection;
novel signal processing methods;
imaging algorithms for damage quantification;
damage detection in composite structures;
fiber optic sensors;
accelerometer for structural health monitoring;
vibrating wire sensors;
strain gauges in structural health monitoring;
acoustic emission sensors;
linear variable differential transformers (LVDTs);
temperature sensors

Prof. Dr. Victor Giurgiutiu
Dr. Hanfei Mei
Guest Editors

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Related Special Issue

Sensor and Sensing Technologies for Structural Health Monitoring and Non-destructive Testing—2nd Edition in Sensors

Published Papers (14 papers)

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Research

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16 pages, 6918 KiB

Open AccessArticle

Progress in Evaluation of Deep Artificial Defects from Sweep-Frequency Eddy-Current Testing Signals

by Milan Smetana, Daniela Gombarska and Zuzana Psenakova

Sensors 2023, 23(13), 6085; https://doi.org/10.3390/s23136085 - 1 Jul 2023

Viewed by 958

Abstract

The article discusses the practical application of the method of electromagnetic non-destructive investigation of austenitic materials. To identify and evaluate deep artificial defects, the sweep-frequency eddy current method with harmonic excitation is used. The objects of interest are the surface electric-discharged machined notches, with a defined geometry, fabricated in a plate with a thickness of 30 mm. An innovative eddy current probe with a separate excitation and detection circuit is used for the investigation. The achieved results clearly demonstrate the robustness and potential of the method, especially for deep defects in thick material. By using the fifth probe in connection with the frequency sweeping of eddy currents, it is possible to reliably detect artificial defects up to 24 ± 0.5 mm deep by using low-frequency excitation signals. An important fact is that the measuring probe does not have to be placed directly above the examined defect. The experimental results achieved are presented and discussed in this paper. The conducted study can serve, for example, as an input database of defect signals with a defined geometry to increase the convergence of learning networks and for the prediction of the geometry of real (fatigue and stress-corrosion) defects. Full article

(This article belongs to the Special Issue Sensor and Sensing Technologies for Structural Health Monitoring and Non-Destructive Testing)

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19 pages, 2563 KiB

Open AccessArticle

A Joint Extraction System Based on Conditional Layer Normalization for Health Monitoring

by Binbin Shi, Rongli Fan, Lijuan Zhang, Jie Huang, Neal Xiong, Athanasios Vasilakos, Jian Wan and Lei Zhang

Sensors 2023, 23(10), 4812; https://doi.org/10.3390/s23104812 - 16 May 2023

Viewed by 1218

Abstract

Natural language processing (NLP) technology has played a pivotal role in health monitoring as an important artificial intelligence method. As a key technology in NLP, relation triplet extraction is closely related to the performance of health monitoring. In this paper, a novel model is proposed for joint extraction of entities and relations, combining conditional layer normalization with the talking-head attention mechanism to strengthen the interaction between entity recognition and relation extraction. In addition, the proposed model utilizes position information to enhance the extraction accuracy of overlapping triplets. Experiments on the Baidu2019 and CHIP2020 datasets demonstrate that the proposed model can effectively extract overlapping triplets, which leads to significant performance improvements compared with baselines. Full article

(This article belongs to the Special Issue Sensor and Sensing Technologies for Structural Health Monitoring and Non-Destructive Testing)

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11 pages, 3466 KiB

Open AccessArticle

Wave Dispersion Behavior in Quasi-Solid State Concrete Hydration

by Yin Chao Wu, Sanggoo Kang, Yeongseok Jeong, Dafnik Saril Kumar David and Suyun Ham

Sensors 2023, 23(8), 3947; https://doi.org/10.3390/s23083947 - 13 Apr 2023

Cited by 1 | Viewed by 991

Abstract

This paper aims to investigate wave dispersion behavior in the quasi-solid state of concrete to better understand microstructure hydration interactions. The quasi-solid state refers to the consistency of the mixture between the initial liquid–solid stage and the hardened stage, where the concrete has not yet fully solidified but still exhibits viscous behavior. The study seeks to enable a more accurate evaluation of the optimal time for the quasi-liquid product of concrete using both contact and noncontact sensors, as current set time measurement approaches based on group velocity may not provide a comprehensive understanding of the hydration phenomenon. To achieve this goal, the wave dispersion behavior of P-wave and surface wave with transducers and sensors is studied. The dispersion behavior with different concrete mixtures and the phase velocity comparison of dispersion behavior are investigated. The analytical solutions are used to validate the measured data. The laboratory test specimen with w/c = 0.5 was subjected to an impulse in a frequency range of 40 kHz to 150 kHz. The results demonstrate that the P-wave results exhibit well-fitted waveform trends with analytical solutions, showing a maximum phase velocity when the impulse frequency is at 50 kHz. The surface wave phase velocity shows distinct patterns at different scanning times, which is attributed to the effect of the microstructure on the wave dispersion behavior. This investigation delivers profound knowledge of hydration and quality control in the quasi-solid state of concrete with wave dispersion behavior, providing a new approach for determining the optimal time of the quasi-liquid product. The criteria and methods developed in this paper can be applied to optimal timing for additive manufacturing of concrete material for 3D printers by utilizing sensors. Full article

(This article belongs to the Special Issue Sensor and Sensing Technologies for Structural Health Monitoring and Non-Destructive Testing)

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14 pages, 8984 KiB

Open AccessArticle

An Analytical Antenna Modeling of Electromagnetic Wave Propagation in Inhomogeneous Media Using FDTD: A Comprehensive Study

by Dafnik Saril Kumar David, Yeongseok Jeong, Yin Chao Wu and Suyun Ham

Sensors 2023, 23(8), 3896; https://doi.org/10.3390/s23083896 - 11 Apr 2023

Cited by 3 | Viewed by 1827

Abstract

This paper discusses the challenges in characterizing electromagnetic (EM) waves propagating through inhomogeneous media, such as reinforced cement concrete and hot mix asphalt. Understanding the EM properties of materials, including their dielectric constant, conductivity, and magnetic permeability, is crucial to analyzing the behavior of these waves. The focus of this study is to develop a numerical model for EM antennas using the finite difference time domain (FDTD) method, and to gain a deeper understanding of various EM wave phenomena. Additionally, we verify the accuracy of our model by comparing its results with experimental data. We analyze several antenna models with different materials, including the absorber, high-density polyethylene and perfect electrical conductors, to obtain an analytical signal response that is verified against the experimental response. Furthermore, we model the inhomogeneous mixture of randomly distributed aggregates and voids within a medium. We verify the practicality and reliability of our inhomogeneous models using experimental radar responses on an inhomogeneous medium. Full article

(This article belongs to the Special Issue Sensor and Sensing Technologies for Structural Health Monitoring and Non-Destructive Testing)

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14 pages, 3513 KiB

Open AccessArticle

Towards Enhanced Eddy Current Testing Array Probes Scalability for Powder Bed Fusion Layer-Wise Imaging

by André Barrancos, Rodolfo L. Batalha and Luís S. Rosado

Sensors 2023, 23(5), 2711; https://doi.org/10.3390/s23052711 - 1 Mar 2023

Cited by 2 | Viewed by 2002

Abstract

This work presents a new eddy current testing array probe and readout electronics that target the layer-wise quality control in powder bed fusion metal additive manufacturing. The proposed design approach brings important benefits to the sensors’ number scalability, exploring alternative sensor elements and minimalist signal generation and demodulation. Small-sized, commercially available surface-mounted technology coils were evaluated as an alternative to usually employed magneto-resistive sensors, demonstrating low cost, design flexibility, and easy integration with the readout electronics. Strategies to minimize the readout electronics were proposed, considering the specific characteristics of the sensors’ signals. An adjustable single phase coherent demodulation scheme is proposed as an alternative to traditional in-phase and quadrature demodulation provided that the signals under measurement showed minimal phase variations. A simplified amplification and demodulation frontend using discrete components was employed together with offset removal, vector amplification, and digitalization implemented within the microcontrollers’ advanced mixed signal peripherals. An array probe with 16 sensor coils and a 5 mm pitch was materialized together with non-multiplexed digital readout electronics, allowing for a sensor frequency of up to 1.5 MHz and digitalization with 12 bits resolution, as well as a 10 kHz sampling rate. Full article

(This article belongs to the Special Issue Sensor and Sensing Technologies for Structural Health Monitoring and Non-Destructive Testing)

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18 pages, 8714 KiB

Open AccessArticle

Temperature Compensation for Reusable Piezo Configuration for Condition Monitoring of Metallic Structures: EMI Approach

by Sushmita Baral, Prateek Negi, Sailesh Adhikari and Suresh Bhalla

Sensors 2023, 23(3), 1587; https://doi.org/10.3390/s23031587 - 1 Feb 2023

Cited by 4 | Viewed by 1757

Abstract

This paper presents a novel algorithm for compensating the changes in conductance signatures of a piezo sensor due to the temperature variation employed in condition monitoring using the electro-mechanical impedance (EMI) approach. It is crucial to consider the changes in an EMI signature due to temperature before using it for comparison with the baseline signature. The shifts in the signature due to temperature can be misinterpreted as damages to the structure, which might also result in a false alarm. In the present study, the compensation values are calculated based on experiments on piezo sensors both in a free boundary condition and in a bonded condition on a metallic host structure. The values were further validated experimentally for damage detection on a large 2D steel plate structure. The variation in first natural frequency values for the unbonded piezo sensor at different temperatures has been used to develop the compensation algorithms. Whereas, in the case of the bonded sensor, the shift in structural peaks has been used. The developed compensation relations showed promising results in damage detection. Lastly, a finite element-based study has also been performed, supporting the experimental findings. The outcome of this study will aid in the compensation of the signatures in the structure due to temperature variation in the conductance signature. Full article

(This article belongs to the Special Issue Sensor and Sensing Technologies for Structural Health Monitoring and Non-Destructive Testing)

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26 pages, 10431 KiB

Open AccessArticle

Optimal Transducer Placement for Deep Learning-Based Non-Destructive Evaluation

by Ji-Yun Kim and Je-Heon Han

Sensors 2023, 23(3), 1349; https://doi.org/10.3390/s23031349 - 25 Jan 2023

Cited by 2 | Viewed by 1456

Abstract

In this study, the Convolution Neural Network (CNN) algorithm is applied for non-destructive evaluation of aluminum panels. A method of classifying the locations of defects is proposed by exciting an aluminum panel to generate ultrasonic Lamb waves, measuring data with a sensor array, and then deep learning the characteristics of 2D imaged, reflected waves from defects. For the purpose of a better performance, the optimal excitation location and sensor locations are investigated. To ensure the robustness of the training model and extract the feature effectively, experimental data are collected by slightly changing the excitation frequency and shifting the location of the defect. The high classification accuracy for each defect location can be achieved. It is found that the proposed algorithm is also successfully applied even when a bar is attached to the panel. Full article

(This article belongs to the Special Issue Sensor and Sensing Technologies for Structural Health Monitoring and Non-Destructive Testing)

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15 pages, 9076 KiB

Open AccessArticle

Simulation of Layer Thickness Measurement in Thin Multi-Layered Material by Variable-Focus Laser Ultrasonic Testing

by Jinxing Qiu, Zhengying Li, Cuixiang Pei and Guoqiang Luo

Sensors 2023, 23(2), 694; https://doi.org/10.3390/s23020694 - 7 Jan 2023

Viewed by 2085

Abstract

Thin multi-layered materials are widely used in key structures of many high technology industries. To ensure the quality and safety of structures, layer thickness measurement by non-destructive testing (NDT) techniques is essential. In this paper, a novel approach for the measurement of each layer’s thickness in thin multi-layered material is proposed by using ring-shaped laser generated focused ultrasonic bulk waves. The proposed method uses a ring-shaped laser with a variable radius to generate shear waves with variable focus inside the structure. By analyzing the signal characteristics at the ring center when the laser radius varies from zero to maximum, the direct measurement of layer thickness can be realized, considering that only when the focal depth and the layer thickness satisfy the specific relationship, the reflected shear waves converge and form a peak at the ring center. This straightforward approach can increase the pulse-echo SNR and prevent the processing of aliasing signals, and therefore provides higher efficiency and accuracy for the layer thickness measurement. In order to investigate the feasibility of this method, finite element simulations were conducted to simulate the ring-shaped laser generated ultrasonic waves in multi-layered structure in detail. Following the principle of the proposed method, the layer thickness of a bi-layer and 3-layer structure were respectively measured using simulation data. The results confirm that the proposed method can accurately and efficiently measure the layer thickness of thin multi-layered material. Full article

(This article belongs to the Special Issue Sensor and Sensing Technologies for Structural Health Monitoring and Non-Destructive Testing)

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17 pages, 5004 KiB

Open AccessArticle

Crack Growth Monitoring with Structure-Bonded Thin and Flexible Coils

by Catalin Mandache, Richard Desnoyers and Yan Bombardier

Sensors 2022, 22(24), 9958; https://doi.org/10.3390/s22249958 - 17 Dec 2022

Viewed by 1374

Abstract

Structural health monitoring with thin and flexible eddy-current coils is proposed for in situ detection and monitoring of fatigue cracks in metallic aircraft structures, providing a promising means of crack sizing. This approach is seen as an efficient replacement to periodic inspections, as it brings economic and safety benefits. As such, printed-circuit-board eddy-current coils are viable for in situ crack monitoring for multi-layer, electrically conductive structures. They are minimally invasive and could be attached to or embedded into the evaluated structure. This work focuses on the monitoring of fatigue crack growth from a fastener hole with structure-bonded, thin, and flexible spiral coils. Numerical simulations were used for optimization of the driving frequency and selection of crack-sensitive coil parameters. The article also demonstrates the fatigue crack detection capabilities using spiral coils attached to a 7075-T6 aluminum coupon. Full article

(This article belongs to the Special Issue Sensor and Sensing Technologies for Structural Health Monitoring and Non-Destructive Testing)

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25 pages, 9613 KiB

Open AccessArticle

Identification of Nonlinear Soil Properties from Downhole Array Data Using a Bayesian Model Updating Approach

by Farid Ghahari, Fariba Abazarsa, Hamed Ebrahimian, Wenyang Zhang, Pedro Arduino and Ertugrul Taciroglu

Sensors 2022, 22(24), 9848; https://doi.org/10.3390/s22249848 - 14 Dec 2022

Cited by 1 | Viewed by 1729

Abstract

An accurate seismic response simulation of civil structures requires accounting for the nonlinear soil response behavior. This, in turn, requires understanding the nonlinear material behavior of in situ soils under earthquake excitations. System identification methods applied to data recorded during earthquakes provide an opportunity to identify the nonlinear material properties of in situ soils. In this study, we use a Bayesian inference framework for nonlinear model updating to estimate the nonlinear soil properties from recorded downhole array data. For this purpose, a one-dimensional finite element model of the geotechnical site with nonlinear soil material constitutive model is updated to estimate the parameters of the soil model as well as the input excitations, including incident, bedrock, or within motions. The seismic inversion method is first verified by using several synthetic case studies. It is then validated by using measurements from a centrifuge test and with data recorded at the Lotung experimental site in Taiwan. The site inversion method is then applied to the Benicia–Martinez geotechnical array in California, using the seismic data recorded during the 2014 South Napa earthquake. The results show the promising application of the proposed seismic inversion approach using Bayesian model updating to identify the nonlinear material parameters of in situ soil by using recorded downhole array data. Full article

(This article belongs to the Special Issue Sensor and Sensing Technologies for Structural Health Monitoring and Non-Destructive Testing)

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18 pages, 10276 KiB

Open AccessArticle

Acoustic Emission Source Characterisation during Fatigue Crack Growth in Al 2024-T3 Specimens

by Xinyue Yao, Benjamin Steven Vien, Chris Davies and Wing Kong Chiu

Sensors 2022, 22(22), 8796; https://doi.org/10.3390/s22228796 - 14 Nov 2022

Cited by 2 | Viewed by 1408

Abstract

While acoustic emission (AE) testing can be used as a valuable technique in structural health monitoring and non-destructive testing, little research has been conducted to establish its sources, particularly in 2024-T3 aluminium alloys. The major contribution of this work is that it provides a method to obtain a better linear relationship of count rate with crack growth rate based on waveform. This paper aims to characterise AE sources by synchronising the AE waveforms with load levels and then to propose possible dominant frequency ranges. The AE waveforms during fatigue crack growth in edge-notched 2024-T3 aluminium specimens, from an initial crack length of 10 mm to 70 mm, were collected at two different load ratios R = 0.125 and 0.5. At the same time, the crack growth rate was determined using thermal imaging and associated control software. The AE waveforms obtained were processed using the fast Fourier transform. It was shown that a significantly higher AE count rate was recorded at R = 0.125 compared to R = 0.5 when the maximum load was kept the same. This means that the R-ratio would affect the total amount of AE activities collected. It was also found that the dominant frequency range of the AE waveforms directly related to crack growth was 152–487 kHz, and the ranges due to crack closure were likely to be 310 kHz–316 kHz and 500–700 kHz. Based on the proposed frequency ranges, waveform selection was conducted and a better linear relationship between count rate and crack growth rate was observed. This study provides a better understanding of the AE sources and waveforms for future structural health monitoring applications. Full article

(This article belongs to the Special Issue Sensor and Sensing Technologies for Structural Health Monitoring and Non-Destructive Testing)

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24 pages, 11891 KiB

Open AccessArticle

Smartphone Application for Structural Health Monitoring of Bridges

by Eloi Figueiredo, Ionut Moldovan, Pedro Alves, Hugo Rebelo and Laura Souza

Sensors 2022, 22(21), 8483; https://doi.org/10.3390/s22218483 - 4 Nov 2022

Cited by 10 | Viewed by 2865

Abstract

The broad availability and low cost of smartphones have justified their use for structural health monitoring (SHM) of bridges. This paper presents a smartphone application called App4SHM, as a customized SHM process for damage detection. App4SHM interrogates the phone’s internal accelerometer to measure accelerations, estimates the natural frequencies, and compares them with a reference data set through a machine learning algorithm properly trained to detect damage in almost real time. The application is tested on data sets from a laboratory beam structure and two twin post-tensioned concrete bridges. The results show that App4SHM retrieves the natural frequencies with reliable precision and performs accurate damage detection, promising to be a low-cost solution for long-term SHM. It can also be used in the context of scheduled bridge inspections or to assess bridges’ condition after catastrophic events. Full article

(This article belongs to the Special Issue Sensor and Sensing Technologies for Structural Health Monitoring and Non-Destructive Testing)

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15 pages, 5190 KiB

Open AccessArticle

A Novel and Non-Invasive Approach to Evaluating Soil Moisture without Soil Disturbances: Contactless Ultrasonic System

by Dong Kook Woo, Wonseok Do, Jinyoung Hong and Hajin Choi

Sensors 2022, 22(19), 7450; https://doi.org/10.3390/s22197450 - 30 Sep 2022

Cited by 1 | Viewed by 2407

Abstract

Soil moisture has been considered a key variable in governing the terrestrial ecosystem. However, it is challenging to preserve indigenous soil characteristics using conventional soil moisture monitoring methods that require maximum soil contacts. To overcome this issue, we developed a non-destructive method of evaluating soil moisture using a contactless ultrasonic system. This system was designed to measure leaky Rayleigh waves at the air–soil joint-half space. The influences of soil moisture on leaky Rayleigh waves were explored under sand, silt, and clay in a controlled experimental design. Our results showed that there were strong relationships between the energy and amplitude of leaky Rayleigh waves and soil moisture for all three soil cases. These results can be explained by reduced soil strengths during evaporation processes for coarse soil particles as opposed to fine soil particles. To evaluate soil moisture based on the dynamic parameters and wave properties obtained from the observed leaky Rayleigh waves, we used the random forest model. The accuracy of predicted soil moisture was exceptional for test data sets under all soil types (R

^{2}

≥ 0.98, RMSE ≤ 0.0089 m

^{3}

^{- 3}

). That is, our study demonstrated that the leaky Rayleigh waves had great potential to continuously assess soil moisture variations without soil disturbances. Full article

(This article belongs to the Special Issue Sensor and Sensing Technologies for Structural Health Monitoring and Non-Destructive Testing)

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Review

Jump to: Research

83 pages, 1450 KiB

Open AccessReview

A Systematic Review of Advanced Sensor Technologies for Non-Destructive Testing and Structural Health Monitoring

by Sahar Hassani and Ulrike Dackermann

Sensors 2023, 23(4), 2204; https://doi.org/10.3390/s23042204 - 15 Feb 2023

Cited by 44 | Viewed by 15488

Abstract

This paper reviews recent advances in sensor technologies for non-destructive testing (NDT) and structural health monitoring (SHM) of civil structures. The article is motivated by the rapid developments in sensor technologies and data analytics leading to ever-advancing systems for assessing and monitoring structures. Conventional and advanced sensor technologies are systematically reviewed and evaluated in the context of providing input parameters for NDT and SHM systems and for their suitability to determine the health state of structures. The presented sensing technologies and monitoring systems are selected based on their capabilities, reliability, maturity, affordability, popularity, ease of use, resilience, and innovation. A significant focus is placed on evaluating the selected technologies and associated data analytics, highlighting limitations, advantages, and disadvantages. The paper presents sensing techniques such as fiber optics, laser vibrometry, acoustic emission, ultrasonics, thermography, drones, microelectromechanical systems (MEMS), magnetostrictive sensors, and next-generation technologies. Full article

(This article belongs to the Special Issue Sensor and Sensing Technologies for Structural Health Monitoring and Non-Destructive Testing)

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