Advances in Industrial and Research Applications of Acoustic Emission Testing

A special issue of Acoustics (ISSN 2624-599X).

Deadline for manuscript submissions: 21 June 2024 | Viewed by 3235

Special Issue Editor

Department of Applied Mechanics, Faculty of Mechanical Engineering, VŠB-Technical University of Ostrava, Ostrava 70833, Czech Republic
Interests: lamb waves; guided electromagnetic wave propagation

Special Issue Information

Dear Colleagues, 

The Special Issue Advances in Industrial and Research Applications of Acoustic Emission Testing invites original research articles to present to the expert community the latest findings and developments in various industrial and research areas which incorporate acoustic emission testing (AET). The AET is a modern nondestructive test method often used in structural health monitoring assessment of metallic and composite pressure vessels, bridges, dams or even offshore applications. The high sensitivity of the measuring chain together with the optionally graded complexity of signal processing predetermines the given method for wide application, mainly in the field of research. It is therefore not surprising that the AET method is widely used for research purposes in the aerospace or chemical industry, physics of condensed matter, geology or even biology and biomechanics. 

This Special issue welcomes publications from the following fields: 

  • Case studies of in situ implementation of AET method;
  • Composites and their mechanical behavior characterization using the AET method;
  • Operational measurements of pressure equipment and structural parts;
  • Structural health monitoring methodology;
  • Grading criteria assessment methodology;
  • Numerical simulations of wave propagation phenomena in conjunction with the AET method;
  • Source location problematics.

Dr. Michal Šofer
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. Acoustics 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 1600 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

  • machine learning
  • source location
  • in-service inspection
  • structure health monitoring
  • signal processing

Published Papers (2 papers)

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Research

15 pages, 1583 KiB  
Article
Matched Filter for Acoustic Emission Monitoring in Noisy Environments: Application to Wire Break Detection
by Alexander Lange, Ronghua Xu, Max Kaeding, Steffen Marx and Joern Ostermann
Acoustics 2024, 6(1), 204-218; https://doi.org/10.3390/acoustics6010011 - 20 Feb 2024
Viewed by 819
Abstract
Regular inspections of important civil infrastructures are mandatory to ensure structural safety and reliability. Until today, these inspections are primarily conducted manually, which has several deficiencies. In context of prestressed concrete structures, steel tendons can be susceptible to stress corrosion cracking, which may [...] Read more.
Regular inspections of important civil infrastructures are mandatory to ensure structural safety and reliability. Until today, these inspections are primarily conducted manually, which has several deficiencies. In context of prestressed concrete structures, steel tendons can be susceptible to stress corrosion cracking, which may result in breakage of individual wires that is visually not observable. Recent research therefore suggests Acoustic Emission Monitoring for wire break detection in prestressed concrete structures. However, in noisy environments, such as wind turbines, conventional acoustic emission detection based on user-defined amplitude thresholds may not be suitable. Thus, we propose the use of matched filters for acoustic emission detection in noisy environments and apply the proposed method to the task of wire break detection in post-tensioned wind turbine towers. Based on manually conducted wire breaks and rebound hammer tests on a large-scale test frame, we employ a brute-force search for the most suitable query signal of a wire break event and a rebound hammer impact, respectively. Then, we evaluate the signal detection performance on more than 500 other wire break signals and approximately one week of continuous acoustic emission recordings in an operating wind turbine. For a signal-to-noise ratio of 0 dB, the matched filter approach shows an improvement in AUC by up to 0.78 for both, the wire break and the rebound hammer query signal, compared to state-of-the-art amplitude-based detection. Even for the unscaled wire break measurements originally recorded at the 12 m large laboratory test frame, the improvement in AUC still lies between 0.01 and 0.25 depending on the wind turbine noise recordings considered for evaluation. Matched filters may therefore be a promising alternative to amplitude-based detection algorithms and deserve particular consideration with regard to Acoustic Emission Monitoring, especially in noisy environments or when sparse senor networks are required. Full article
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32 pages, 11361 KiB  
Article
Investigating the Detection Capability of Acoustic Emission Monitoring to Identify Imperfections Produced by the Metal Active Gas (MAG) Welding Process
by James Marcus Griffin, Steven Jones, Bama Perumal and Carl Perrin
Acoustics 2023, 5(3), 714-745; https://doi.org/10.3390/acoustics5030043 - 20 Jul 2023
Viewed by 1698
Abstract
Welding inspection is a critical process that can be severely time-consuming, resulting in productivity delays, especially when destructive or invasive processes are required. This paper defines the novel approach to investigate the physical correlation between common imperfections found in arc welding and the [...] Read more.
Welding inspection is a critical process that can be severely time-consuming, resulting in productivity delays, especially when destructive or invasive processes are required. This paper defines the novel approach to investigate the physical correlation between common imperfections found in arc welding and the propensity to determine these through the identification of signatures using acoustic emission sensors. Through a set of experiments engineered to induce prominent imperfections (cracks and other anomalies) using a popular welding process and the use of AE technology (both airborne and contact), it provides confirmation that the verification of physical anomalies can indeed be identified through variations in obtained noise frequency signatures. This in situ information provides signals during and after solidification to inform operators of the deposit/HAZ integrity to support the advanced warning of unwanted anomalies and of whether the weld/fabrication process should be halted to undertake rework before completing the fabrication. Experimentation was carried out based on an acceptable set of parameters where extracted data from the sensors were recorded, analysed, and compared with the resultant microstructure. This may allow signal phenomena to be captured and catalogued for future use in referencing against known anomalies. Full article
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