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http://hdl.handle.net/10397/94104
| Title: | Vibration signal-based early fault prognosis : status quo and applications | Authors: | Lv, Y Zhao, W Zhao, Z Li, W Ng, KKH |
Issue Date: | Apr-2022 | Source: | Advanced engineering informatics, Apr. 2022, v. 52, 101609 | Abstract: | To implement Prognostics and Health Management (PHM) for industrial systems, it is paramount to conduct early fault prognosis on the systems to ensure the stability and reliability during their entire lifecycles. Investigations on early fault prognosis have been actively carried out, but there is a lack of systematic analysis and summary of the developed methods. To bridge the gap, in this paper, the relevant methods are comprehensively reviewed from the aspects of signal processing and fault identification. Furthermore, the applications of the methods are systematically described. In the end, to further facilitate researchers and practitioners, statistical and comparative analysis of the reviewed methods are given, and future development directions are outlined. | Keywords: | Deep learning Early fault prognosis Signal processing Vibration signal analysis |
Publisher: | Elsevier | Journal: | Advanced engineering informatics | EISSN: | 1474-0346 | DOI: | 10.1016/j.aei.2022.101609 | Rights: | © 2022 Elsevier Ltd. All rights reserved. © 2022. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/. The following publication Lv, Y., Zhao, W., Zhao, Z., Li, W., & Ng, K. K. H. (2022). Vibration signal-based early fault prognosis: Status quo and applications. Advanced Engineering Informatics, 52, 101609 is available at https://dx.doi.org/10.1016/j.aei.2022.101609. |
| Appears in Collections: | Journal/Magazine Article |
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| File | Description | Size | Format | |
|---|---|---|---|---|
| Lv_Vibration_Signal-based_Prognosis.pdf | Pre-Published version | 1.23 MB | Adobe PDF | View/Open |
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