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Advances in Imaging-Based NDT Methods
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Advances in Imaging-Based NDT Methods

A special issue of NDT (ISSN 2813-477X).

Deadline for manuscript submissions: closed (30 July 2024) | Viewed by 2119

Special Issue Editor

Dr. Ravibabu Mulaveesala

E-Mail Website
Guest Editor
Centre for Sensors, Instrumentation and Cyber Physical System Engineering (SeNSE) Indian Institute of Technology Delhi, New Delhi 110016, India
Interests: non-destructive testing and evaluation; sub-surface sensing and imaging; industrial vision and automation; infrared/thermal wave imaging; structural health monitoring; bio-medical imaging

Special Issue Information

Dear Colleagues,

This Special Issue's focus is on the advancements of imaging based non-destructive testing and evaluation (NDT&E) methods for inspection of various metals, semiconductors, composites and biomaterials. The main focus is given to widely used non-destructive testing and evaluation methodologies and associated data processing schemes for inspection of various industrial and biomaterials.

Topics of interest

This Special Issue on NDT&E focuses on both laboratory and field applications, including but not limited to the following:

  • ultrasonic testing
  • radiographic testing
  • thermographic testing
  • optical testing
  • eddy current testing
  • magnetic particle inspection
  • liquid penetrant examination
  • signal/image/video processing techniques for improving the sensitivity and resolution for visualization of surface/subsurface/volumetric defects.
  • non-destructive testing/non-invasive inspection of biomaterials
  • data fusion for NDT&E

Dr. Ravibabu Mulaveesala
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. NDT is an international peer-reviewed open access quarterly 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 1000 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

  • nondestructive testing
  • nondestructive evaluation
  • ultrasonics
  • radiography
  • thermography
  • optical techniques
  • signal and umage processing for NDT&E
  • data fusion

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Further information on MDPI's Special Issue polices can be found here.

Published Papers (2 papers)

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Research

17 pages, 2432 KiB  
Article
Non-Destructive Estimation of Paper Fiber Using Macro Images: A Comparative Evaluation of Network Architectures and Patch Sizes for Patch-Based Classification
by Naoki Kamiya, Kosuke Ashino, Yasuhiro Sakai, Yexin Zhou, Yoichi Ohyanagi and Koji Shibazaki
NDT 2024, 2(4), 487-503; https://doi.org/10.3390/ndt2040030 - 7 Nov 2024
Viewed by 428
Abstract
Over the years, research in the field of cultural heritage preservation and document analysis has exponentially grown. In this study, we propose an advanced approach for non-destructive estimation of paper fibers using macro images. Expanding on studies that implemented EfficientNet-B0, we explore the [...] Read more.
Over the years, research in the field of cultural heritage preservation and document analysis has exponentially grown. In this study, we propose an advanced approach for non-destructive estimation of paper fibers using macro images. Expanding on studies that implemented EfficientNet-B0, we explore the effectiveness of six other deep learning networks, including DenseNet-201, DarkNet-53, Inception-v3, Xception, Inception-ResNet-v2, and NASNet-Large, in conjunction with enlarged patch sizes. We experimentally classified three types of paper fibers, namely, kozo, mitsumata, and gampi. During the experiments, patch sizes of 500, 750, and 1000 pixels were evaluated and their impact on classification accuracy was analyzed. The experiments demonstrated that Inception-ResNet-v2 with 1000-pixel patches achieved the highest patch classification accuracy of 82.7%, whereas Xception with 750-pixel patches exhibited the best macro-image-based fiber estimation performance at 84.9%. Additionally, we assessed the efficacy of the method for images containing text, observing consistent improvements in the case of larger patch sizes. However, limitations exist in background patch availability for text-heavy images. This comprehensive evaluation of network architectures and patch sizes can significantly advance the field of non-destructive paper analysis, offering valuable insights into future developments in historical document examination and conservation science. Full article
(This article belongs to the Special Issue Advances in Imaging-Based NDT Methods)
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11 pages, 11529 KiB  
Article
Novel Statistical Analysis Schemes for Frequency-Modulated Thermal Wave Imaging for Inspection of Ship Hull Materials
by Ishant Singh, Vanita Arora, Prabhu Babu and Ravibabu Mulaveesala
NDT 2024, 2(4), 445-455; https://doi.org/10.3390/ndt2040027 - 15 Oct 2024
Viewed by 658
Abstract
In the field of thermal non-destructive testing and evaluation (TNDT&E), active thermography gained popularity due to its fast wide-area monitoring and remote inspection capability to assess materials without compromising their future usability. Among the various active thermographic methods, pulse compression-favorable frequency-modulated thermal wave [...] Read more.
In the field of thermal non-destructive testing and evaluation (TNDT&E), active thermography gained popularity due to its fast wide-area monitoring and remote inspection capability to assess materials without compromising their future usability. Among the various active thermographic methods, pulse compression-favorable frequency-modulated thermal wave imaging stands out for its enhanced detectability and depth resolution. In this study, an experimental investigation has been carried out on a hardened steel sample used in the ship building industry with a flat-bottom-hole-simulated defect using the frequency-modulated thermal wave imaging (FMTWI) technique. The defect detection capabilities of FMTWI have been investigated from various statistical post-processing approaches and compared by taking the signal-to-noise ratio (SNR) as a figure of merit. Among various adopted statistical post-processing techniques, pulse compression has been carried out using different methods, namely the offset removal with polynomial curve fitting and principal component analysis (PCA), which is an unsupervised learning approach for data reduction and offset removal with median centering for data standardization. The performance of these techniques was assessed through experimental investigations on hardened steel specimens used in ship building to provide valuable insights into their effectiveness in defect detection capabilities. Full article
(This article belongs to the Special Issue Advances in Imaging-Based NDT Methods)
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