Searching for just a few words should be enough to get started. If you need to make more complex queries, use the tips below to guide you.
Issue title: Special Section: Advances in intelligent computing for diagnostics, prognostics, and system health management
Guest editors: Chuan Li and José Valente de Oliveira
Article type: Research Article
Authors: Jin, Yaqianga | Liu, Zhilianga; * | Peng, Dandana | Kang, Jinlonga | Ding, Jianmingb
Affiliations: [a] School of Mechanical and Electrical Engineering, University of Electronic Science and Technology of China, Chengdu, China | [b] State Key Laboratory of Traction Power, Southwest Jiaotong University, Chengdu, China
Correspondence: [*] Corresponding author. Zhiliang Liu, School of Mechanical and Electrical Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China. Tel.: +86 13438832072; E-mail: Zhiliang_Liu@uestc.edu.cn.
Abstract: Local defects of rotating machinery give rise to periodic impulses in vibration. To acquire this fault information, many diagnostic methods have been reported in the past decades. Among them, the envelope spectrum analysis is usually used as the final diagnostic tool; however, its success highly depends on the correct informative frequency band selection. The key problem is how to find the correct centre frequency and its related bandwidth associated to the fault. In this paper, a novel method is proposed for selection of the optimal frequency band parameters. This method improves the informative frequency band selection performance with two aspects. One is that it incorporates the normal data as a health reference, and the other is that an objective indicator that could fuse multidimensional information is proposed. An optimal frequency band can be obtained through this algorithm, and fault mode is then determined via comparing the squared envelope spectrum between the test and normal signals. At the end of this paper, the proposed method is validated on two diagnosis cases and is compared with two of the other diagnostic methods: the conventional envelope analysis and the kurtogram. Though comparison of the results, the validity and superiority of the proposed method have been proven.
Keywords: Frequency band selection, classification, health reference, envelope analysis, fault diagnosis
DOI: 10.3233/JIFS-169528
Journal: Journal of Intelligent & Fuzzy Systems, vol. 34, no. 6, pp. 3487-3498, 2018
IOS Press, Inc.
6751 Tepper Drive
Clifton, VA 20124
USA
Tel: +1 703 830 6300
Fax: +1 703 830 2300
sales@iospress.com
For editorial issues, like the status of your submitted paper or proposals, write to editorial@iospress.nl
IOS Press
Nieuwe Hemweg 6B
1013 BG Amsterdam
The Netherlands
Tel: +31 20 688 3355
Fax: +31 20 687 0091
info@iospress.nl
For editorial issues, permissions, book requests, submissions and proceedings, contact the Amsterdam office info@iospress.nl
Inspirees International (China Office)
Ciyunsi Beili 207(CapitaLand), Bld 1, 7-901
100025, Beijing
China
Free service line: 400 661 8717
Fax: +86 10 8446 7947
china@iospress.cn
For editorial issues, like the status of your submitted paper or proposals, write to editorial@iospress.nl
如果您在出版方面需要帮助或有任何建, 件至: editorial@iospress.nl