Special Issue "Structural Health Monitoring & Nondestructive Testing"

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Materials".

Deadline for manuscript submissions: 30 October 2021.

Special Issue Editors

Prof. Dr. Xavier Maldague
E-Mail Website
Guest Editor
Faculty of Science and Engineering, Department of Electrical and Computer Engineering, Université Laval, Québec, Canada
Interests: infrared thermography; NonDestructive Evaluation (NDE) techniques and vision / digital systems for industrial inspection
Special Issues and Collections in MDPI journals
Prof. Valérie Kaftandjian-Doudet
E-Mail Website
Guest Editor
Laboratoire Vibrations et Acoustique, INSA-Lyon, Bâtiment St-Exupéry, Villeurbanne, France
Interests: X-ray imaging, tomography, multi-energy, data fusion, defect detection and classification
Prof. Ahmad Osman
E-Mail Website
Guest Editor
htw Saar University of Applied Sciences, Fraunhofer Institute for Nondestructive Testing IZFP, Saarbruecken, Germany
Interests: NDE techniques, pattern recognition for industrial image processing
Dr. Bastien Chapuis
E-Mail Website
Guest Editor
CEA LIST, NDE Department, Digiteo Saclay, France
Interests: structural health monitoring, guided waves, piezoelectric transducers, optical fibers, probability of detection
Prof. dr. ir. Gunther Steenackers
E-Mail Website
Guest Editor
Faculty of Applied Engineering, Department of Electromechanics, University of Antwerp, Antwerp, Belgium
Interests: infrared thermography; non-destructive testing, medical thermography, finite element modeling., hyperspectral imaging
Dr. Hai Zhang
E-Mail
Guest Editor
Department of Mechanical and Industrial Engineering, University of Toronto and Department of Electrical and Computer Engineering, Université Laval, Canada
Interests: Non-destructive Evbaluation, Infrared thermography, Terahertz Spectroscopy, Photo-thermal coherence tomography, Composite materials

Special Issue Information

Dear Colleagues,

The aim of the International Symposium on Structural Health Monitoring and Nondestructive Testing is to provide an overview of the latest breakthroughs in SHM and NDT and their interactions with various industrial sectors. Thanks to the success of the 2nd (2018, Saarbrücken, Germany) and of the 1st (2013, Lyon, France) symposia, it was decided to hold a third event with oral presentations, poster session and an industrial exhibition in Québec City, Canada on 14 and 15 of May 2020. SHM-NDT 2020 will be held back-to-back with the Annual General Meeting of the initiative, see www.ondutycanada.ca. Cross-fertilization between the two events is highly encouraged.

The Symposium is organized by Université Laval in partnership with the Canadian Institute for NonDestructive Evaluation (CINDE), the German Society for Nondestructive Testing (DGZfP e.V.), the French Society for Nondestructive Testing (Cofrend), INSA-Lyon, Fraunhofer IZFP, Fraunhofer EZRT.

This joint Special Issue is expected to select excellent papers in and out SHM-NDT 2020 in the following topics, but not limited to:

1) Structural health monitoring;
2) NDT sensors, detectors and sources: ultrasound, acoustical emission, X-ray, thermography, eddy currents, EMAT etc;
3) Modeling and simulation;
4) Reliability, probability of detection;
5) Sensor data fusion;
6) Reconstruction techniques;
7) Defect detection & localization methods;
8) Signal and image processing.

All papers (in and out SHM-NDT 2020) must be submitted by the deadline (see above). All selected and peer-reviewed papers will be organized as in a dedicated book with an ISBN number.

Prof. Xavier Maldague
Prof. Valérie Kaftandjian-Doudet
Prof. Ahmad Osman
Dr. Bastien Chapuis
Prof. dr. ir. Gunther Steenackers
Dr. Hai Zhang
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Applied Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2000 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Structural health monitoring
  • NDT sensors, detectors and sources: ultrasound, acoustical emission, X-ray, thermography, eddy currents, EMAT etc
  • Modeling and simulation
  • Reliability, probability of detection
  • Sensor data fusion
  • Reconstruction techniques
  • Defect detection & localisation methods
  • Signal and image processing…

Published Papers (16 papers)

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Research

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Article
Capability of Advanced Ultrasonic Inspection Technologies for Hydraulic Turbine Runners
Appl. Sci. 2021, 11(10), 4681; https://doi.org/10.3390/app11104681 - 20 May 2021
Viewed by 341
Abstract
This paper presents the results of a project aimed at evaluating the performance of ultrasonic techniques for detecting flaws in Francis turbine runners. This work is the first phase of a more ambitious program aimed at improving the reliability of inspection of critical [...] Read more.
This paper presents the results of a project aimed at evaluating the performance of ultrasonic techniques for detecting flaws in Francis turbine runners. This work is the first phase of a more ambitious program aimed at improving the reliability of inspection of critical areas in turbine runners. Francis runners may be utilized to supply power during peak periods, which means that they experience additional load stress associated with start and stop sequences. Inspection during manufacturing is then of paramount importance to remove as much as feasible all flaw initiation sites before the heat treatment. This phase one objective is to collect initial data on a simplified mock-up and then to compare the experimental ultrasonic data with the results of simulations performed by CIVA, a computer simulation package. The area of interest is the region with the highest stress between the blade and the web. A welded T-joint coupon made of UNS S41500 was manufactured to represent this high-stress area. During the FCAW welding process, ceramic beads were embedded in the weld to create discontinuities whose size is in the critical range to initiate a crack. Inspection of the material was carried out by various nondestructive testing (NDT) methods namely conventional pulse-echo, phased array, total focusing method (TFM). With these results, detection rates were obtained in order to compare the effectiveness of each method. Full article
(This article belongs to the Special Issue Structural Health Monitoring & Nondestructive Testing)
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Article
Long-Term Numerical Analysis of Subsurface Delamination Detection in Concrete Slabs via Infrared Thermography
Appl. Sci. 2021, 11(10), 4323; https://doi.org/10.3390/app11104323 - 11 May 2021
Viewed by 292
Abstract
One of the concerns about the use of passive Infrared Thermography (IRT) for structural health monitoring (SHM) is the determination of a favorable period to conduct the inspections. This paper investigates the use of numerical simulations to find appropriate periods for IRT-based detection [...] Read more.
One of the concerns about the use of passive Infrared Thermography (IRT) for structural health monitoring (SHM) is the determination of a favorable period to conduct the inspections. This paper investigates the use of numerical simulations to find appropriate periods for IRT-based detection of subsurface damages in concrete bridge slabs under passive heating along a 1 year of time span. A model was built using the Finite Element Method (FEM) and calibrated using the results of a set of thermographic field inspections on a concrete slab sample. The results showed that the numerical simulation properly reproduced the experimental thermographic measurements of the concrete structure under passive heating, allowing the analysis to be extended for a longer testing period. The long-term FEM results demonstrated that the months of spring and summer are the most suitable for passive IRT inspections in this study, with around 17% more detections compared to the autumn and winter periods in Brazil. By enhancing the possibility of using FEM beyond the design stage, we demonstrate that this computation tool can provide support to long-term SHM. Full article
(This article belongs to the Special Issue Structural Health Monitoring & Nondestructive Testing)
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Article
Locally Optimal Subsampling Strategies for Full Matrix Capture Measurements in Pipe Inspection
Appl. Sci. 2021, 11(9), 4291; https://doi.org/10.3390/app11094291 - 10 May 2021
Viewed by 291
Abstract
In ultrasonic non-destructive testing, array and matrix transducers are being employed for applications that require in-field steerability or which benefit from a higher number of insonification angles. Having many transmit channels, on the other hand, increases the measurement time and renders the use [...] Read more.
In ultrasonic non-destructive testing, array and matrix transducers are being employed for applications that require in-field steerability or which benefit from a higher number of insonification angles. Having many transmit channels, on the other hand, increases the measurement time and renders the use of array transducers unfeasible for many applications. In the literature, methods for reducing the number of required channels compared to the full matrix capture scheme have been proposed. Conventionally, these are based on choosing the aperture that is as wide as possible. In this publication, we investigate a scenario from the field of pipe inspection, where cracks have to be detected in specific areas near the weld. Consequently, the width of the aperture has to be chosen according to the region of interest at hand. On the basis of ray-tracing simulations which incorporate a model of the transducer directivity and beam spread at the interface, we derive application specific measures of the energy distribution over the array configuration for given regions of interest. These are used to determine feasible subsampling schemes. For the given scenario, the validity/quality of the derived subsampling schemes are compared on the basis of reconstructions using the conventional total focusing method as well as sparsity driven-reconstructions using the Fast Iterative Shrinkage-Thresholding Algorithm. The results can be used to effectively improve the measurement time for the given application without notable loss in defect detectability. Full article
(This article belongs to the Special Issue Structural Health Monitoring & Nondestructive Testing)
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Article
Cavity Detection in Steel-Pipe Culverts Using Infrared Thermography
Appl. Sci. 2021, 11(9), 4051; https://doi.org/10.3390/app11094051 - 29 Apr 2021
Viewed by 354
Abstract
Finding efficient and less expensive techniques for different aspects of culvert inspection is in great demand. This study assesses the potential of infrared thermography (IRT) to detect the presence of cavities in the soil around a culvert, specifically for cavities adjacent to the [...] Read more.
Finding efficient and less expensive techniques for different aspects of culvert inspection is in great demand. This study assesses the potential of infrared thermography (IRT) to detect the presence of cavities in the soil around a culvert, specifically for cavities adjacent to the pipe of galvanized culverts. To identify cavities, we analyze thermograms, generated via long pulse thermography, using absolute thermal contrast, principal components thermography, and a statistical approach along with a combination of different pre- and post-processing algorithms. Using several experiments, we evaluate the performance of IRT for accomplishing the given task. Empirical results show a promising future for the application of this approach in culvert inspection. The size and location of cavities are among the aspects that can be extracted from analyzing thermograms. The key finding of this research is that the proposed approach can provide useful information about a certain type of problem around a culvert pipe which may indicate the early stage of the cavity formation. Becoming aware of this process in earlier stages will certainly help to prevent any costly incidents later. Full article
(This article belongs to the Special Issue Structural Health Monitoring & Nondestructive Testing)
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Article
Numerical Simulation and Experimental Study of Capacitive Imaging Technique as a Nondestructive Testing Method
Appl. Sci. 2021, 11(9), 3804; https://doi.org/10.3390/app11093804 - 22 Apr 2021
Viewed by 384
Abstract
It was recently demonstrated that a coplanar capacitive sensor could be applied to the evaluation of materials without the disadvantages associated with the other techniques. This technique effectively detects changes in the dielectric properties of the materials due to, for instance, imperfections or [...] Read more.
It was recently demonstrated that a coplanar capacitive sensor could be applied to the evaluation of materials without the disadvantages associated with the other techniques. This technique effectively detects changes in the dielectric properties of the materials due to, for instance, imperfections or variations in the internal structure, by moving a set of simple electrodes on the surface of the specimen. An AC voltage is applied to one or more electrodes and signals are detected by others. This is a promising inspection method for imaging the interior structure of the numerous materials, without the necessity to be in contact with the surface of the sample. In this paper, finite element (FE) modeling was employed to simulate the electric field distribution from a coplanar capacitive sensor and the way it interacts with a nonconducting sample. Physical experiments with a prototype capacitive sensor were also performed on a Plexiglas sample with subsurface defects, to assess the imaging performance of the sensor. A good qualitative agreement was observed between the numerical simulation and experimental result. Full article
(This article belongs to the Special Issue Structural Health Monitoring & Nondestructive Testing)
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Article
SPAER: Sparse Deep Convolutional Autoencoder Model to Extract Low Dimensional Imaging Biomarkers for Early Detection of Breast Cancer Using Dynamic Thermography
Appl. Sci. 2021, 11(7), 3248; https://doi.org/10.3390/app11073248 - 05 Apr 2021
Viewed by 438
Abstract
Early diagnosis of breast cancer unequivocally improves the survival rate of patients and is crucial for disease treatment. With the current developments in infrared imaging, breast screening using dynamic thermography seems to be a great complementary method for clinical breast examination (CBE) prior [...] Read more.
Early diagnosis of breast cancer unequivocally improves the survival rate of patients and is crucial for disease treatment. With the current developments in infrared imaging, breast screening using dynamic thermography seems to be a great complementary method for clinical breast examination (CBE) prior to mammography. In this study, we propose a sparse deep convolutional autoencoder model named SPAER to extract low-dimensional deep thermomics to aid breast cancer diagnosis. The model receives multichannel, low-rank, approximated thermal bases as input images. SPAER provides a solution for high-dimensional deep learning features and selects the predominant basis matrix using matrix factorization techniques. The model has been evaluated using five state-of-the-art matrix factorization methods and 208 thermal breast cancer screening cases. The best accuracy was for non-negative matrix factorization (NMF)-SPAER + Clinical and NMF-SPAER for maintaining thermal heterogeneity, leading to finding symptomatic cases with accuracies of 78.2% (74.3–82.5%) and 77.7% (70.9–82.1%), respectively. SPAER showed significant robustness when tested for additive Gaussian noise cases (3–20% noise), evaluated by the signal-to-noise ratio (SNR). The results suggest high performance of SPAER for preserveing thermal heterogeneity, and it can be used as a noninvasive in vivo tool aiding CBE in the early detection of breast cancer. Full article
(This article belongs to the Special Issue Structural Health Monitoring & Nondestructive Testing)
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Article
A Drone-Enabled Approach for Gas Leak Detection Using Optical Flow Analysis
Appl. Sci. 2021, 11(4), 1412; https://doi.org/10.3390/app11041412 - 04 Feb 2021
Viewed by 604
Abstract
The recent development of gas imaging technologies has raised a growing interest for various applications. Gas imaging can significantly enhance functional safety by early detection of hazardous gas leaks. Moreover, optical gas imaging technologies can be used to identify possible gas leakages and [...] Read more.
The recent development of gas imaging technologies has raised a growing interest for various applications. Gas imaging can significantly enhance functional safety by early detection of hazardous gas leaks. Moreover, optical gas imaging technologies can be used to identify possible gas leakages and to investigate the amount of gas emission in industrial sites, which is essential, primarily based on current efforts to decrease greenhouse gas emissions all around the world. Therefore, exploring the solutions for automating the inspection process can persuade industries for more regular tests and monitoring. One of the main challenges in gas imaging is the proximity condition required for data to be more reliable for analysis. Therefore, the use of unmanned aerial vehicles can be very advantageous as they can provide significant access due to their maneuver capabilities. Despite the advantages of using drones, their movements and sudden motions during hovering can diminish data usability. In this paper, we propose a method for gas leak detection and visually-enhancement of gas emanation involving stabilization and gas leak detection steps. In addition, a comparative analysis of candidate stabilization techniques is conducted to find the most suitable technique for the drone-based application. Moreover, the system is evaluated using three experiments respectively on an isolated environment, a real scenario, and a drone-based inspection. Full article
(This article belongs to the Special Issue Structural Health Monitoring & Nondestructive Testing)
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Article
Analysis of Eddy-Current Probe Signals in Steam Generator U-Bend Tubes Using the Finite Element Method
Appl. Sci. 2021, 11(2), 696; https://doi.org/10.3390/app11020696 - 13 Jan 2021
Viewed by 448
Abstract
To ensure the integrity and safety of steam generator tubes in nuclear power plants, eddy-current testing is periodically employed. Because steam generators are equipped with thousands of thin-walled tubes, the eddy current is tested using a bobbin probe that can be used at [...] Read more.
To ensure the integrity and safety of steam generator tubes in nuclear power plants, eddy-current testing is periodically employed. Because steam generators are equipped with thousands of thin-walled tubes, the eddy current is tested using a bobbin probe that can be used at high speed. Steam generator heat pipes in nuclear power plants have different sizes and shapes depending on their row number. In particular, heat pipes in the first row are located inside the steam generator and are of the U-bend type because the radius of the curved pipe is the smallest. A steam generator heat pipe has a thickness of about 1 mm, so a geometrical cross-sectional area change may occur due to residual stress when manufacturing the curved pipe. It is difficult to determine an exact shape because the change in cross-sectional area generated during the manufacturing process varies depending on the position of the pipe and the distortion rate. During eddy-current testing (ECT), to ensure the integrity and safety of the steam generator tubes, the shape change of the bend may cause a noise signal, making it difficult to evaluate defects in the pipe. However, the noise signals generated in this situation are difficult to analyze in a real measurement environment, and difficult to verify by producing a mock-up, which complicates distinguishing a noise signal from a defective signal. To solve this problem, various noise signals were obtained using the electromagnetic analysis method of COMSOL Multiphysics, a commercial program based on numerical analysis of the finite element method, to simulate the environment, including the change in cross-sectional area of the heat pipe. When compared to the actual measurement signal, the accuracy of the simulations improved, and various types of noise signals were detected, which may be helpful for accurate evaluations of defects during actual inspections. Full article
(This article belongs to the Special Issue Structural Health Monitoring & Nondestructive Testing)
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Article
A Method of Defect Depth Estimation for Simulated Infrared Thermography Data with Deep Learning
Appl. Sci. 2020, 10(19), 6819; https://doi.org/10.3390/app10196819 - 29 Sep 2020
Cited by 5 | Viewed by 825
Abstract
Infrared thermography has already been proven to be a significant method in non-destructive evaluation since it gives information with immediacy, rapidity, and low cost. However, the thorniest issue for the wider application of IRT is quantification. In this work, we proposed a specific [...] Read more.
Infrared thermography has already been proven to be a significant method in non-destructive evaluation since it gives information with immediacy, rapidity, and low cost. However, the thorniest issue for the wider application of IRT is quantification. In this work, we proposed a specific depth quantifying technique by employing the Gated Recurrent Units (GRUs) in composite material samples via pulsed thermography (PT). Finite Element Method (FEM) modeling provides the economic examination of the response pulsed thermography. In this work, Carbon Fiber Reinforced Polymer (CFRP) specimens embedded with flat bottom holes are stimulated by a FEM modeling (COMSOL) with precisely controlled depth and geometrics of the defects. The GRU model automatically quantified the depth of defects presented in the stimulated CFRP material. The proposed method evaluated the accuracy and performance of synthetic CFRP data from FEM for defect depth predictions. Full article
(This article belongs to the Special Issue Structural Health Monitoring & Nondestructive Testing)
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Article
Investigation on the Formation Mechanism of Crack Indications and the Influences of Related Parameters in Magnetic Particle Inspection
Appl. Sci. 2020, 10(19), 6805; https://doi.org/10.3390/app10196805 - 28 Sep 2020
Viewed by 656
Abstract
The recent rapid development of industrial cameras and machine learning has brought new vitality to the very traditional flaw detection method, namely, magnetic particle inspection (MPI). To fully develop automatic fluorescent MPI technology, two main issues need to be solved urgently—the lack of [...] Read more.
The recent rapid development of industrial cameras and machine learning has brought new vitality to the very traditional flaw detection method, namely, magnetic particle inspection (MPI). To fully develop automatic fluorescent MPI technology, two main issues need to be solved urgently—the lack of theoretical analysis on the formation of the crack indications, and quantitative characterization methods to determine the crack indications. Here, we carry out a theoretical analysis and an experimental approach to address these issues. Theoretical models of the acting force of the leakage magnetic field were established. Subsequently, the impacts of different magnetic field strengths (1000–9000 A/m) and magnetic particle concentrations (0.5–30 mL/L) on the adsorption critical distance were analyzed. The models were solved by numerical calculations in MATLAB. In addition, a single variable control experiment was conducted to study the effects of crack images. In order to determine the quality of the crack image, three characteristic parameters were investigated, such as indication gray scale, background gray scale, and contrast ratio, were provided. The theoretical magnetic particle concentration range provided a guidance value for automated fluorescent MPI. Experimental results revealed that the optimal magnetic particle concentration was 3–4 mL/L, and, under this condition, the contrast between the crack indications and the background of crack images was obvious. Full article
(This article belongs to the Special Issue Structural Health Monitoring & Nondestructive Testing)
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Article
Adaptive Sensor Array Error Calibration Based Impact Localization on Composite Structure
Appl. Sci. 2020, 10(11), 4042; https://doi.org/10.3390/app10114042 - 11 Jun 2020
Cited by 1 | Viewed by 632
Abstract
Gains and phases delay induced by sensor position error would significantly degrade the performance of high-resolution two-dimensional multiple signal classification (2D-MUSIC) algorithm, which resulting in low positioning estimation accuracy and poor imaging. In this study, adaptive piezoelectric sensor array calibration based method is [...] Read more.
Gains and phases delay induced by sensor position error would significantly degrade the performance of high-resolution two-dimensional multiple signal classification (2D-MUSIC) algorithm, which resulting in low positioning estimation accuracy and poor imaging. In this study, adaptive piezoelectric sensor array calibration based method is proposed for impact localization on composite structure. First, observed signal vector from the sensor array is represented by error calibration matrix with unknown gains and phases, and then it used to construct the cost function including sensor array parameters. Second, a 2D-MUSIC algorithm based on linear attenuation calibration is applied for estimating the initial estimate of impact location. Finally, substituting the initial estimate, the cost function is minimized by adaptive iterative to calculate the sensor array error parameters and the exact location of the impact source. Both finite element method (FEM) simulation and experimental results on carbon-fiber composite panel demonstrate the validity and effectiveness of the proposed method. Full article
(This article belongs to the Special Issue Structural Health Monitoring & Nondestructive Testing)
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Article
Optimisation of a Heat Source for Infrared Thermography Measurements: Comparison to Mehler Engineering + Service-Heater
Appl. Sci. 2020, 10(4), 1285; https://doi.org/10.3390/app10041285 - 14 Feb 2020
Cited by 1 | Viewed by 550
Abstract
Using an optimised heating source in active thermography can facilitate the processing of measurement results. By designing a custom heat source for dynamic line scan thermography, we reduced the excitation power needed to heat the sample and decreased the unwanted side effects originating [...] Read more.
Using an optimised heating source in active thermography can facilitate the processing of measurement results. By designing a custom heat source for dynamic line scan thermography, we reduced the excitation power needed to heat the sample and decreased the unwanted side effects originating of a wide-range heating source. The design started from a regular halogen tube lamp and a reflector is composed to provide the desired heating power in a narrow band. The reflector shape is optimised using ray-tracing software to concentrate the electromagnetic radiation along with the heat in a slim line. A comparison between the optimised heat source and a commercially available line-heater is performed. The width of the heated region from the Mehler Engineering + Service-heater is larger than prescribed in the datasheet. The optimised line heater has several advantages over the comercially available heat source. Full article
(This article belongs to the Special Issue Structural Health Monitoring & Nondestructive Testing)
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Article
Validation of Acoustic Emission Waveform Entropy as a Damage Identification Feature
Appl. Sci. 2019, 9(19), 4070; https://doi.org/10.3390/app9194070 - 29 Sep 2019
Cited by 1 | Viewed by 689
Abstract
The increase in the market for supersized LNG (liquefied natural gas) vessels, with double wall cargo tanks, has led to concerns regarding their safe operation. If both the primary and secondary wall of the cargo tank fail simultaneously, the hull of the vessel [...] Read more.
The increase in the market for supersized LNG (liquefied natural gas) vessels, with double wall cargo tanks, has led to concerns regarding their safe operation. If both the primary and secondary wall of the cargo tank fail simultaneously, the hull of the vessel can be exposed to the LNG. This has the potential to cause brittle failure of the hull structure. This study presents a new acoustic emission (AE) technique approach that can be implemented for monitoring the structural condition of the cargo containment. The new technique approach is based on a feature of the AE waveform, calculated using quadratic Renyi’s entropy. The presented technique is capable of providing information regarding critical damage so that appropriate maintenance can be carried out to avoid failure. The new AE technique is based on an AE feature that is independent of acquisition settings (e.g., threshold and timing), unlike many traditional AE features. The effectiveness of the proposed feature was evaluated by comparison with traditional AE features under ideal conditions for a range of varying acquisition settings. Unlike the traditional feature, the new feature demonstrated no variance with variation of the acquisition settings and was effective in capturing the collective information in the waveform. The proposed AE feature was validated through tensile and fatigue testing on standard specimens of austenitic stainless steel (material of the primary wall). The results suggest that the proposed AE feature is sensitive in identifying the critical damages irrespective of some data acquisition settings. Full article
(This article belongs to the Special Issue Structural Health Monitoring & Nondestructive Testing)
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Article
Prediction of Concrete Strength with P-, S-, R-Wave Velocities by Support Vector Machine (SVM) and Artificial Neural Network (ANN)
Appl. Sci. 2019, 9(19), 4053; https://doi.org/10.3390/app9194053 - 27 Sep 2019
Cited by 12 | Viewed by 1200
Abstract
Mechanical waves, such as ultrasonic waves, have shown promise for use in non-destructive methods used in the evaluation of concrete properties, such as strength and elasticity. However, accurate estimation of the concrete compressive strength is difficult if only the pressure waves (P-waves) are [...] Read more.
Mechanical waves, such as ultrasonic waves, have shown promise for use in non-destructive methods used in the evaluation of concrete properties, such as strength and elasticity. However, accurate estimation of the concrete compressive strength is difficult if only the pressure waves (P-waves) are considered, which is common in non-destructive methods. P-waves cannot reflect various factors such as the types of aggregates and cement, the fine aggregate modulus, and the interfacial transition zone, influencing the concrete strength. In this study, shear waves (S-waves) and Rayleigh waves (R-waves) were additionally used to obtain a more accurate prediction of the concrete strength. The velocities of three types of mechanical waves were measured by recent ultrasonic testing methods. Two machine learning models—a support vector machine (SVM) and an artificial neural network (ANN)—were developed within the MATLAB programming environment. Both models were successfully used to model the relationship between the mechanical wave velocities and the concrete compressive strength. The machine learning model that included the P-, S-, and R-wave velocities was more accurate than the model that included only the P-wave velocity. Full article
(This article belongs to the Special Issue Structural Health Monitoring & Nondestructive Testing)
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Review

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Review
Independent Component Analysis Applied on Pulsed Thermographic Data for Carbon Fiber Reinforced Plastic Inspection: A Comparative Study
Appl. Sci. 2021, 11(10), 4377; https://doi.org/10.3390/app11104377 - 12 May 2021
Viewed by 230
Abstract
Dimensional reduction methods have significantly improved the simplification of Pulsed Thermography (PT) data while improving the accuracy of the results. Such approaches reduce the quantity of data to analyze and improve the contrast of the main defects in the samples contributed to their [...] Read more.
Dimensional reduction methods have significantly improved the simplification of Pulsed Thermography (PT) data while improving the accuracy of the results. Such approaches reduce the quantity of data to analyze and improve the contrast of the main defects in the samples contributed to their popularity. Many works have been proposed in the literature mainly based on improving the Principal Component Thermography (PCT). Recently the Independent Component Analysis (ICA) has been a topic of attention. Many different approaches have been proposed in the literature to solve the ICA. In this paper, we investigated several recent ICA methods and evaluated their influence on PT data compared with the state-of-the-art methods. We conducted our evaluation on reference CFRP samples with known defects. We found that ICA outperform PCT for small and deep defects. For other defects ICA results are often not far from the results obtained by PCT. However, the frequency of acquisition and the ICA methods have a great influence on the results. Full article
(This article belongs to the Special Issue Structural Health Monitoring & Nondestructive Testing)
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Other

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Letter
The Use of Non-Destructive Testing (NDT) to Detect Bed Joint Reinforcement in AAC Masonry
Appl. Sci. 2020, 10(13), 4645; https://doi.org/10.3390/app10134645 - 05 Jul 2020
Cited by 1 | Viewed by 621
Abstract
Detecting non-metallic reinforcement made of FRP (Fibre Reinforced Polymers) can be problematic, particularly at the stage of work inspection and constructional evaluation. In contrast to steel reinforcement, detecting non-metallic reinforcement is difficult using NDT (Non-Destructive Testing) techniques. These difficulties mainly arise from considerably [...] Read more.
Detecting non-metallic reinforcement made of FRP (Fibre Reinforced Polymers) can be problematic, particularly at the stage of work inspection and constructional evaluation. In contrast to steel reinforcement, detecting non-metallic reinforcement is difficult using NDT (Non-Destructive Testing) techniques. These difficulties mainly arise from considerably lower density, radiation resistance or electromagnetic impedance and cross-section of rebars when compared to steel reinforcement. Specific problems with the reinforcement detection are experienced in masonry structures, in which reinforcement is laid in bed joints. Measurements are made on a masonry face in the plane perpendicular to the reinforcement plane, and not the parallel one compared to reinforced concrete structures. Thus, the interpretation of results obtained from NDT can be complicated due to many physical phenomena occurring during tests, methods of presenting measurements and their accuracy. This paper compares different testing techniques used to detect non-metallic reinforcement in the masonry wall made of autoclaved aerated concrete (AAC). For the purpose of the tests, fibreglass and basalt meshes, traditional steel trusses and steel wire meshes were placed in bed joints of the masonry wall. An ultrasonic tomography and GPR (Ground-Penetrating Radar) scanner operating within a broad range of frequencies were used for the tests. We also used the electromagnetic device to detect metal meshes. As expected, the tests confirmed problems with detecting the non-metallic reinforcement. Only the radar method was effective in detecting the non-metallic method, whereas other methods failed. The electromagnetic method detected only the steel reinforcement in the masonry. Full article
(This article belongs to the Special Issue Structural Health Monitoring & Nondestructive Testing)
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