State of the Art in the Field of Machine and System Testing to Assist in the Diagnosis and Prognosis of Failures

A special issue of Machines (ISSN 2075-1702). This special issue belongs to the section "Machines Testing and Maintenance".

Deadline for manuscript submissions: 15 October 2024 | Viewed by 1088

Special Issue Editor


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Guest Editor
PRISME, University of Orléans, EA 4229, 45072 Orléans, France
Interests: remaining useful life estimation

Special Issue Information

Dear Colleagues,

The increasing complexity of industrial processes, the continued goal of achieving higher profits, and increasingly demanding production constraints call for the implementation of a proactive and sustainable maintenance policy. Adapting maintenance policies that integrate the concepts and obligations of so-called sustainable development is a real challenge for companies. This can concern proactive maintenance operations aimed at providing balance between the social, environmental, and economic dimensions. Such a policy requires the introduction of substantial upstream analysis and the establishment of tools to validate process performance continuity. Consequently, and in an Industry 4.0 context, being able to anticipate a system breakdown based on its estimated degradation, while proposing a time window for a maintenance intervention has become essential. The aim is to avoid a failure with a particularly significant impact. The approaches and methods of Prognostics and Health Management (P.H.M) provide many answers.

This Special Issue looks at the current methods and tools available to meet the needs of P.H.M.

Dr. Pascal Vrignat
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. Machines is an international peer-reviewed open access monthly 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

  • sustainable manufacturing
  • maintenance policies
  • prognostics and health management
  • industry 4.0
  • prognosis
  • diagnosis
  • case studies

Published Papers (1 paper)

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Research

15 pages, 4244 KiB  
Article
Improved Synchronous Sampling and Its Application in High-Speed Railway Bearing Damage Detection
by Kun Wang, Yukun Huang, Baoqiang Zhang, Huageng Luo, Xiang Yu, Dawei Chen and Zhiqiang Zhang
Machines 2024, 12(2), 101; https://doi.org/10.3390/machines12020101 - 01 Feb 2024
Viewed by 825
Abstract
Synchronous analysis is one of the most effective and practical techniques in rotating machinery diagnostics, especially in cases with variable speed operations. A modern analog-to-digital convertor (ADC) usually digitizes an analog signal to an equal time interval data series. Synchronous resampling converts the [...] Read more.
Synchronous analysis is one of the most effective and practical techniques in rotating machinery diagnostics, especially in cases with variable speed operations. A modern analog-to-digital convertor (ADC) usually digitizes an analog signal to an equal time interval data series. Synchronous resampling converts the data series from an equal time interval data series to an equal shaft rotation angle interval data series. This conversion is usually achieved in the digital domain with the aid of shaft speed information, through either direct measurement or identification from a measured vibration signal, which is a time-consuming process. In order to improve the computational efficiency as well as the data processing accuracy, in this paper, a fast synchronous time-point calculation method based on an inverse function interpolation procedure is proposed. By identifying the inverse function of the instantaneous phase with respect to time, the calculation process of synchronous time points is optimized, which results in improved calculation efficiency and accuracy. These advantages are demonstrated by numerical simulations as well as experimental verifications. The numerical simulation results show that the proposed method can improve calculation speed by about five times. The synchronous analysis based on the proposed method was applied to a bearing fault detection in a high-speed rail carriage, which demonstrated the advantages of the proposed algorithm in improving the signal-to-noise ratio (SNR) for bearing damage feature extraction. Full article
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