Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
5.3
2.5
Journals
Applied Sciences
Special Issues
The Advances and Applications of Non-destructive Evaluation
applsci-logo
Submit to Applied Sciences Review for Applied Sciences Propose a Special Issue

Journal Menu

► Journal Menu

Journal Browser

► Journal Browser
share announcement

The Advances and Applications of Non-destructive Evaluation

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

Deadline for manuscript submissions: closed (20 October 2024) | Viewed by 2217

Special Issue Editor

Prof. Dr. Xiaofeng Liu

E-Mail Website
Guest Editor
College of Mechanical Engineering, Chongqing University, Chongqing 400044, China
Interests: condition monitoring; fault diagnosis; fault prediction; signal processing; structural health monitoring; structural damage detection

Special Issue Information

Dear Colleagues,

With the continuous development of science and technology, non-destructive evaluation has become the basic technology of structure management and maintenance in the field of industrial production. It plays an important role in ensuring the safe and reliable service of structure, improving the efficiency of management and maintenance, and generating economic benefits.

In this Special Issue, we are aiming to collate studies on all aspects surrounding “The Advances and Applications of Non-destructive Evaluation”. It will be dedicated to new perspectives on topics ranging from nonlinear acoustics and ultrasonic waves to Lamb wave detection, acoustic emission testing, X-ray radiography, magnetic particle testing, and eddy-current testing. It will also highlight advancements in non-destructive detection technology, structural health monitoring, pattern recognition, deep learning models, artificial intelligence, statistical mathematics, signal processing, and data analytics. This Special Issue aims to bridge the gap between theory and real-world implementation. Any original, unpublished work is welcome. If you have an interest in this topic, please let us know.

Prof. Dr. Xiaofeng Liu
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. 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 2400 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

  • non-destructive testing
  • ultrasonic detection
  • structural health monitoring
  • artificial intelligence
  • signal processing
  • data analytics
  • damage location
  • damage quantification

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • e-Book format: Special Issues with more than 10 articles can be published as dedicated e-books, ensuring wide and rapid dissemination.

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

Published Papers (2 papers)

Download All Papers
Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Research

18 pages, 8574 KiB  
Article
Neural Network-Based Evaluation of Hardness in Cold-Rolled Austenitic Stainless Steel Under Various Heat Treatment Conditions
by Milan Smetana, Michal Gala, Daniela Gombarska and Peter Klco
Appl. Sci. 2025, 15(3), 1352; https://doi.org/10.3390/app15031352 - 28 Jan 2025
Viewed by 720
Abstract
This study introduces an innovative, non-contact method for classifying the hardness of austenitic stainless steels (grade AISI 304) based on their intrinsic magnetic fields. Utilizing a 3 × 3 matrix sensor system, this research captures weak magnetic fields to produce precise 2D magnetic [...] Read more.
This study introduces an innovative, non-contact method for classifying the hardness of austenitic stainless steels (grade AISI 304) based on their intrinsic magnetic fields. Utilizing a 3 × 3 matrix sensor system, this research captures weak magnetic fields to produce precise 2D magnetic field maps of the samples. A key advancement is the application of a modified GoogleNet convolutional neural network, optimized with the stochastic gradient descent with momentum algorithm, which achieves exceptional classification accuracy, ranging from 95% to 100%, and median accuracies of 97.5% to 99%. This method stands out by revealing a novel correlation between annealing temperature and magnetic field strength, particularly a pronounced decline in magnetic properties at temperatures near 1000 °C. This observation underscores the sensitivity of magnetic profiles to heat treatments, offering a groundbreaking approach to material characterization. By enabling reliable, efficient, and fully automated hardness evaluation based on magnetic signatures, this work has the potential to transform materials engineering and manufacturing, setting a new benchmark for non-destructive material analysis techniques. Full article
(This article belongs to the Special Issue The Advances and Applications of Non-destructive Evaluation)
►▼ Show Figures

Figure 1

21 pages, 32088 KiB  
Article
Development and Validation of Concept of Innovative Method of Computer-Aided Monitoring and Diagnostics of Machine Components
by Krzysztof Herbuś, Andrzej Dymarek, Piotr Ociepka, Tomasz Dzitkowski, Cezary Grabowik, Kamil Szewerda, Katarzyna Białas and Zbigniew Monica
Appl. Sci. 2024, 14(21), 10056; https://doi.org/10.3390/app142110056 - 4 Nov 2024
Viewed by 1175
Abstract
The monitoring and diagnostic system has been suggested as a non-destructive diagnostic method. The structure and operation of the suggested system can be described by the concept of digital shadow (DS). One of the main DS subsystems is a set of sensors properly [...] Read more.
The monitoring and diagnostic system has been suggested as a non-destructive diagnostic method. The structure and operation of the suggested system can be described by the concept of digital shadow (DS). One of the main DS subsystems is a set of sensors properly placed on the monitored object and coupled with a discrete data processing model created in Matlab/Simulink. The discrete model, as another important DS subsystem of the monitored facility, transfers information about its technical condition to the operator based on data recorded by the sensor system. The digital monitoring model processes the recorded data in the form of the object’s response to actions caused by its operating conditions. This work formalized a mathematical model determining the coupling of the digital model with the sensors placed on the monitored object. The formulated method using DS, due to its sensitivity, enables the detection of the damage in the object at an early stage. The tests allowed for detecting the regularities enabling the determination of the area of damage to the shaft and its size. Full article
(This article belongs to the Special Issue The Advances and Applications of Non-destructive Evaluation)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-2
Back to TopTop