Fault Detection of High-Speed Train Wheelset Bearing Based on Impulse-Envelope Manifold
A novel fault detection method employing the impulse-envelope manifold is proposed in this paper which is based on the combination of convolution sparse representation (CSR) and Hilbert transform manifold learning. The impulses with different sparse characteristics are extracted by the CSR with diff...
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Format: | Article |
Language: | English |
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Wiley
2017-01-01
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Series: | Shock and Vibration |
Online Access: | http://dx.doi.org/10.1155/2017/2104720 |
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author | Zhe Zhuang Jianming Ding Andy C. Tan Ying Shi Jianhui Lin |
author_facet | Zhe Zhuang Jianming Ding Andy C. Tan Ying Shi Jianhui Lin |
author_sort | Zhe Zhuang |
collection | DOAJ |
description | A novel fault detection method employing the impulse-envelope manifold is proposed in this paper which is based on the combination of convolution sparse representation (CSR) and Hilbert transform manifold learning. The impulses with different sparse characteristics are extracted by the CSR with different penalty parameters. The impulse-envelope space is constructed through Hilbert transform on the extracted impulses. The manifold based on impulse-envelope space (impulse-envelope manifold) is executed to learn the low-dimensionality intrinsic envelope of vibration signals for fault detection. The analyzed results based on simulations, experimental tests, and practical applications show that (1) the impulse-envelope manifold with both isometric mapping (Isomap) and locally linear coordination (LLC) can be successfully used to extract the intrinsic envelope of the impulses where local tangent space analysis (LTSA) fails to perform and (2) the impulse-envelope manifold with Isomap outperforms those with LLC in terms of strengthening envelopes and the number of extracted harmonics. The proposed impulse-envelope manifold with Isomap is superior in extracting the intrinsic envelope, strengthening the amplitude of intrinsic envelope spectra, and enlarging the harmonic number of fault-characteristic frequency. The proposed technique is highly suitable for extracting intrinsic envelopes for bearing fault detection. |
format | Article |
id | doaj-art-b278eba4b8db44f5b7a9f7e3eb3b9f1a |
institution | Kabale University |
issn | 1070-9622 1875-9203 |
language | English |
publishDate | 2017-01-01 |
publisher | Wiley |
record_format | Article |
series | Shock and Vibration |
spelling | doaj-art-b278eba4b8db44f5b7a9f7e3eb3b9f1a2025-02-03T00:59:13ZengWileyShock and Vibration1070-96221875-92032017-01-01201710.1155/2017/21047202104720Fault Detection of High-Speed Train Wheelset Bearing Based on Impulse-Envelope ManifoldZhe Zhuang0Jianming Ding1Andy C. Tan2Ying Shi3Jianhui Lin4State Key Laboratory of Traction Power, Southwest Jiaotong University, Chengdu 610031, ChinaState Key Laboratory of Traction Power, Southwest Jiaotong University, Chengdu 610031, ChinaLKC Faculty of Engineering and Science, Universiti Tunku Abdul Rahman, 43000 Kajang, MalaysiaState Key Laboratory of Traction Power, Southwest Jiaotong University, Chengdu 610031, ChinaState Key Laboratory of Traction Power, Southwest Jiaotong University, Chengdu 610031, ChinaA novel fault detection method employing the impulse-envelope manifold is proposed in this paper which is based on the combination of convolution sparse representation (CSR) and Hilbert transform manifold learning. The impulses with different sparse characteristics are extracted by the CSR with different penalty parameters. The impulse-envelope space is constructed through Hilbert transform on the extracted impulses. The manifold based on impulse-envelope space (impulse-envelope manifold) is executed to learn the low-dimensionality intrinsic envelope of vibration signals for fault detection. The analyzed results based on simulations, experimental tests, and practical applications show that (1) the impulse-envelope manifold with both isometric mapping (Isomap) and locally linear coordination (LLC) can be successfully used to extract the intrinsic envelope of the impulses where local tangent space analysis (LTSA) fails to perform and (2) the impulse-envelope manifold with Isomap outperforms those with LLC in terms of strengthening envelopes and the number of extracted harmonics. The proposed impulse-envelope manifold with Isomap is superior in extracting the intrinsic envelope, strengthening the amplitude of intrinsic envelope spectra, and enlarging the harmonic number of fault-characteristic frequency. The proposed technique is highly suitable for extracting intrinsic envelopes for bearing fault detection.http://dx.doi.org/10.1155/2017/2104720 |
spellingShingle | Zhe Zhuang Jianming Ding Andy C. Tan Ying Shi Jianhui Lin Fault Detection of High-Speed Train Wheelset Bearing Based on Impulse-Envelope Manifold Shock and Vibration |
title | Fault Detection of High-Speed Train Wheelset Bearing Based on Impulse-Envelope Manifold |
title_full | Fault Detection of High-Speed Train Wheelset Bearing Based on Impulse-Envelope Manifold |
title_fullStr | Fault Detection of High-Speed Train Wheelset Bearing Based on Impulse-Envelope Manifold |
title_full_unstemmed | Fault Detection of High-Speed Train Wheelset Bearing Based on Impulse-Envelope Manifold |
title_short | Fault Detection of High-Speed Train Wheelset Bearing Based on Impulse-Envelope Manifold |
title_sort | fault detection of high speed train wheelset bearing based on impulse envelope manifold |
url | http://dx.doi.org/10.1155/2017/2104720 |
work_keys_str_mv | AT zhezhuang faultdetectionofhighspeedtrainwheelsetbearingbasedonimpulseenvelopemanifold AT jianmingding faultdetectionofhighspeedtrainwheelsetbearingbasedonimpulseenvelopemanifold AT andyctan faultdetectionofhighspeedtrainwheelsetbearingbasedonimpulseenvelopemanifold AT yingshi faultdetectionofhighspeedtrainwheelsetbearingbasedonimpulseenvelopemanifold AT jianhuilin faultdetectionofhighspeedtrainwheelsetbearingbasedonimpulseenvelopemanifold |