Special Issue "Structural Health Monitoring & Nondestructive Testing 2020"

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

Deadline for manuscript submissions: 30 November 2020.

Special Issue Editors

Prof. Xavier Maldague
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
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
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
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
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

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 1800 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 (5 papers)

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Open AccessArticle
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
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 2020)
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Open AccessFeature PaperArticle
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
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 2020)
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Open AccessArticle
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
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 2020)
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Open AccessArticle
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 5
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 2020)
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Open AccessLetter
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
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 2020)
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