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Advanced Sensors in Nondestructive Testing and Structural Health Monitoring
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Advanced Sensors in Nondestructive Testing and Structural Health Monitoring

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

Deadline for manuscript submissions: closed (25 August 2024) | Viewed by 6112

Special Issue Editor

Dr. Miguel A. Machado

E-Mail Website
Guest Editor
Department of Mechanical and Industrial Engineering, NOVA School of Science and Technology, Universidade NOVA de Lisboa, Lisboa, Portugal
Interests: non-destructive testing; eddy currents; thermography; sensors; structural health monitoring

Special Issue Information

Dear Colleagues,

Advanced sensors play a crucial role in enhancing the accuracy, reliability, and efficiency of Nondestructive Testing (NDT) and Structural Health Monitoring (SHM). Traditional methods are often time-consuming, subjective, and may be inadequate to detect hidden defects or early signs of damage. In contrast, advanced sensors enable real-time, remote, and nonintrusive monitoring, allowing for early detection of structural issues and facilitating proactive maintenance and repair strategies. Collecting and analyzing data from advanced sensors provides valuable insights into the structural health and performance of critical assets such as bridges, pipelines, aircraft, and buildings.

The scope of this Special Issue encompasses various technologies used in advanced sensors, including but not limited to optical fibers, piezoelectric materials, wireless sensor networks, ultrasound, electromagnetic waves, and smart materials. We invite submissions that explore the design, development, simulation, and validation of advanced sensors. Additionally, we encourage researchers to share their work on practical applications of advanced sensors in SHM, including case studies that demonstrate their effectiveness in real-world scenarios. Both reviews and original research articles are welcome, contributing to the advancement of knowledge and implementation in this field.

Authors are encouraged to address topics such as: Topics include, but are not limited to, the following:

  • Design and simulation of advanced sensors;
  • Case studies and practical applications showcasing the use of advanced sensors in SHM;
  • Integration of advanced sensor technologies into existing NDT and SHM frameworks;
  • Data analysis and interpretation methods for extracting valuable insights from sensor data;
  • Proactive maintenance and repair strategies enabled by advanced sensor monitoring.

Dr. Miguel A. Machado
Guest Editor

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 submissions that pass pre-check are 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. Sensors 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 2600 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

  • advanced sensors
  • Nondestructive Testing (NDT)
  • Structural Health Monitoring (SHM)
  • sensor technologies
  • smart materials
  • numerical simulation
  • remote monitoring
  • proactive maintenance
  • structural integrity
  • real-time monitoring
  • wireless sensor networks
  • terahertz Inspection
  • eddy currents
  • ultrasounds
  • thermography

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Published Papers (6 papers)

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Research

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19 pages, 5558 KiB  
Article
Convolution Neural Network Development for Identifying Damage in Vibrating Pylons with Mass Attachments
by George D. Manolis and Georgios I. Dadoulis
Sensors 2024, 24(19), 6255; https://doi.org/10.3390/s24196255 (registering DOI) - 27 Sep 2024
Abstract
A convolution neural network (CNN) is developed in this work to detect damage in pylons by measuring their vibratory response. More specifically, damage detection through testing relies on the development of damage-sensitive indicators, which are then used to reach a decision regarding the [...] Read more.
A convolution neural network (CNN) is developed in this work to detect damage in pylons by measuring their vibratory response. More specifically, damage detection through testing relies on the development of damage-sensitive indicators, which are then used to reach a decision regarding the existence/absence of damage, provided they have been retrieved from at least two distinct structural states. Damage indicators, however, exhibit a relatively low sensitivity regarding the onset of structural damage, further exacerbated by the low amplitude response to a variety of environmentally induced loads. To this end, a mathematical model is developed to interpret the experimental data recovered from a fixed-base pylon with a top mass attachment to transverse motion. Damage is introduced in the mathematical model in the form of springs corresponding to the cracking of the beam’s lower end. Families of numerically generated acceleration records are produced at select stations along the beam’s height, which are then used for training a CNN. Once trained, it is used to identify damage from acceleration records produced from a series of experiments. Difficulties faced by CNN in correctly identifying the presence/absence of damage in the pylon are discussed, and steps taken to improve the quality of the results are proposed. Full article
(This article belongs to the Special Issue Advanced Sensors in Nondestructive Testing and Structural Health Monitoring)
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15 pages, 5914 KiB  
Communication
Shear Wave Velocity Determination of a Complex Field Site Using Improved Nondestructive SASW Testing
by Gunwoong Kim and Sungmoon Hwang
Sensors 2024, 24(10), 3231; https://doi.org/10.3390/s24103231 - 19 May 2024
Cited by 1 | Viewed by 783
Abstract
The nondestructive spectral analysis of surface waves (SASW) technique determines the shear wave velocities along the wide wavelength range using Rayleigh-type surface waves that propagate along pairs of receivers on the surface. The typical configuration of source-receivers consists of a vertical source and [...] Read more.
The nondestructive spectral analysis of surface waves (SASW) technique determines the shear wave velocities along the wide wavelength range using Rayleigh-type surface waves that propagate along pairs of receivers on the surface. The typical configuration of source-receivers consists of a vertical source and three vertical receivers arranged in a linear array. While this approach allows for effective site characterization, laterally variable sites are often challenging to characterize. In addition, in a traditional SASW test configuration system, where sources are placed in one direction, the data are collected more on one side, which can cause an imbalance in the interpretation of the data. Data interpretation issues can be resolved by moving the source to opposite ends of the original array and relocating receivers to perform a second complete set of tests. Consequently, two different Vs profiles can be provided with only a small amount of additional time at sites where lateral variability exists. Furthermore, the testing procedure can be modified to enhance the site characterization during data collection. The advantages of performing SASW testing in both directions are discussed using a real case study. Full article
(This article belongs to the Special Issue Advanced Sensors in Nondestructive Testing and Structural Health Monitoring)
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18 pages, 37636 KiB  
Article
Transversal Displacement Detection of an Arched Bridge with a Multimonostatic Multiple-Input Multiple-Output Radar
by Lorenzo Pagnini, Lapo Miccinesi, Alessandra Beni and Massimiliano Pieraccini
Sensors 2024, 24(6), 1839; https://doi.org/10.3390/s24061839 - 13 Mar 2024
Cited by 1 | Viewed by 790
Abstract
Interferometric radars are widely used for monitoring civil structures. Bridges are critical structures that need to be constantly monitored for the safety of the users. In this work, a frequency-modulated continuous wave (FMCW) multiple-input multiple-output (MIMO) radar was used for monitoring an arched [...] Read more.
Interferometric radars are widely used for monitoring civil structures. Bridges are critical structures that need to be constantly monitored for the safety of the users. In this work, a frequency-modulated continuous wave (FMCW) multiple-input multiple-output (MIMO) radar was used for monitoring an arched bridge in Catanzaro, Italy. Two measurements were carried out; a first standard measurement was made in a monostatic configuration, while a subsequent measurement was carried out in a multimonostatic configuration in order to retrieve the components of the deck displacement. A method that is able to predict the measurement uncertainty as a function of the multimonostatic geometry is provided, thereby aiming to facilitate the operators in the choice of the proper experimental setup. The multimonostatic measurement revealed a displacement along the horizontal direction that was four times higher than the one along the vertical direction, while the values reported in the literature correspond to a ratio of at most around 0.2. This is the first time that such a large ratio detected by radar has been reported; at any rate, it is compatible with the arched structure of this specific bridge. This case study highlights the importance of techniques that are able to retrieve at least two components of the displacement. Full article
(This article belongs to the Special Issue Advanced Sensors in Nondestructive Testing and Structural Health Monitoring)
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12 pages, 6335 KiB  
Article
Quantitative Detection Technology for Geometric Deformation of Pipelines Based on LiDAR
by Min Zhao, Zehao Fang, Ning Ding, Nan Li, Tengfei Su and Huihuan Qian
Sensors 2023, 23(24), 9761; https://doi.org/10.3390/s23249761 - 11 Dec 2023
Viewed by 1100
Abstract
This paper introduces a novel method for enhancing underground pipeline inspection, specifically addressing limitations associated with traditional closed-circuit television (CCTV) systems. These systems, commonly used for capturing visual data of sewer system deformations, heavily rely on subjective human expertise, leading to limited accuracy [...] Read more.
This paper introduces a novel method for enhancing underground pipeline inspection, specifically addressing limitations associated with traditional closed-circuit television (CCTV) systems. These systems, commonly used for capturing visual data of sewer system deformations, heavily rely on subjective human expertise, leading to limited accuracy in detection. Furthermore, their inability to perform quantitative analyses of deformation extent hampers overall inspection effectiveness. Our proposed method leverages laser point cloud data and employs a 3D scanner for objective detection of geometric deformations in underground pipe corridors. By utilizing this approach, we enable a quantitative assessment of blockage levels, offering a significant improvement over traditional CCTV-based methods. The key advantages of our method lie in its objectivity and quantification capabilities, ultimately enhancing detection reliability, accuracy, and overall inspection efficiency. Full article
(This article belongs to the Special Issue Advanced Sensors in Nondestructive Testing and Structural Health Monitoring)
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19 pages, 7944 KiB  
Article
Damage Monitoring of Braided Composites Using CNT Yarn Sensor Based on Artificial Fish Swarm Algorithm
by Hongxia Wang, Yungang Jia, Minrui Jia, Xiaoyuan Pei and Zhenkai Wan
Sensors 2023, 23(16), 7067; https://doi.org/10.3390/s23167067 - 10 Aug 2023
Cited by 1 | Viewed by 1042
Abstract
This study aims to enable intelligent structural health monitoring of internal damage in aerospace structural components, providing a crucial means of assuring safety and reliability in the aerospace field. To address the limitations and assumptions of traditional monitoring methods, carbon nanotube (CNT) yarn [...] Read more.
This study aims to enable intelligent structural health monitoring of internal damage in aerospace structural components, providing a crucial means of assuring safety and reliability in the aerospace field. To address the limitations and assumptions of traditional monitoring methods, carbon nanotube (CNT) yarn sensors are used as key elements. These sensors are woven with carbon fiber yarns using a three-dimensional six-way braiding process and cured with resin composites. To optimize the sensor configuration, an artificial fish swarm algorithm (AFSA) is introduced, simulating the foraging behavior of fish to determine the best position and number of CNT yarn sensors. Experimental simulations are conducted on 3D braided composites of varying sizes, including penetration hole damage, line damage, and folded wire-mounted damage, to analyze the changes in the resistance data of carbon nanosensors within the damaged material. The results demonstrate that the optimized configuration of CNT yarn sensors based on AFSA is suitable for damage monitoring in 3D woven composites. The experimental positioning errors range from 0.224 to 0.510 mm, with all error values being less than 1 mm, thus achieving minimum sensor coverage for a maximum area. This result not only effectively reduces the cost of the monitoring system, but also improves the accuracy and reliability of the monitoring process. Full article
(This article belongs to the Special Issue Advanced Sensors in Nondestructive Testing and Structural Health Monitoring)
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Review

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43 pages, 6234 KiB  
Review
Eddy Currents Probe Design for NDT Applications: A Review
by Miguel A. Machado
Sensors 2024, 24(17), 5819; https://doi.org/10.3390/s24175819 - 7 Sep 2024
Abstract
Eddy current testing (ECT) is a crucial non-destructive testing (NDT) technique extensively used across various industries to detect surface and sub-surface defects in conductive materials. This review explores the latest advancements and methodologies in the design of eddy current probes, emphasizing their application [...] Read more.
Eddy current testing (ECT) is a crucial non-destructive testing (NDT) technique extensively used across various industries to detect surface and sub-surface defects in conductive materials. This review explores the latest advancements and methodologies in the design of eddy current probes, emphasizing their application in diverse industrial contexts such as aerospace, automotive, energy, and electronics. It explores the fundamental principles of ECT, examining how eddy currents interact with material defects to provide valuable insights into material integrity. The integration of numerical simulations, particularly through the Finite Element Method (FEM), has emerged as a transformative approach, enabling the precise modeling of electromagnetic interactions and optimizing probe configurations. Innovative probe designs, including multiple coil configurations, have significantly enhanced defect detection capabilities. Despite these advancements, challenges remain, particularly in calibration and sensitivity to environmental conditions. This comprehensive overview highlights the evolving landscape of ECT probe design, aiming to provide researchers and practitioners with a detailed understanding of current trends in this dynamic field. Full article
(This article belongs to the Special Issue Advanced Sensors in Nondestructive Testing and Structural Health Monitoring)
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