Subway Gearbox Fault Diagnosis Algorithm Based on Adaptive Spline Impact Suppression
In the signal processing of real subway vehicles, impacts between wheelsets and rail joint gaps have significant negative effects on the spectrum. This introduces great difficulties for the fault diagnosis of gearboxes. To solve this problem, this paper proposes an adaptive time-domain signal segmen...
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-05-01
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| Series: | Entropy |
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| Online Access: | https://www.mdpi.com/1099-4300/23/6/660 |
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| author | Zhongshuo Hu Jianwei Yang Dechen Yao Jinhai Wang Yongliang Bai |
| author_facet | Zhongshuo Hu Jianwei Yang Dechen Yao Jinhai Wang Yongliang Bai |
| author_sort | Zhongshuo Hu |
| collection | DOAJ |
| description | In the signal processing of real subway vehicles, impacts between wheelsets and rail joint gaps have significant negative effects on the spectrum. This introduces great difficulties for the fault diagnosis of gearboxes. To solve this problem, this paper proposes an adaptive time-domain signal segmentation method that envelopes the original signal using a cubic spline interpolation. The peak values of the rail joint gap impacts are extracted to realize the adaptive segmentation of gearbox fault signals when the vehicle was moving at a uniform speed. A long-time and unsteady signal affected by wheel–rail impacts is segmented into multiple short-term, steady-state signals, which can suppress the high amplitude of the shock response signal. Finally, on this basis, multiple short-term sample signals are analyzed by time- and frequency-domain analyses and compared with the nonfaulty results. The results showed that the method can efficiently suppress the high-amplitude components of subway gearbox vibration signals and effectively extract the characteristics of weak faults due to uniform wear of the gearbox in the time and frequency domains. This provides reference value for the gearbox fault diagnosis in engineering practice. |
| first_indexed | 2024-03-10T11:05:32Z |
| format | Article |
| id | doaj.art-84cbee41cd56432ea3a9784207188795 |
| institution | Directory Open Access Journal |
| issn | 1099-4300 |
| language | English |
| last_indexed | 2024-03-10T11:05:32Z |
| publishDate | 2021-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Entropy |
| spelling | doaj.art-84cbee41cd56432ea3a97842071887952023-11-21T21:13:20ZengMDPI AGEntropy1099-43002021-05-0123666010.3390/e23060660Subway Gearbox Fault Diagnosis Algorithm Based on Adaptive Spline Impact SuppressionZhongshuo Hu0Jianwei Yang1Dechen Yao2Jinhai Wang3Yongliang Bai4School of Mechanical-Electronic and Vehicle Engineering, Beijing University of Civil Engineering and Architecture, Beijing 100044, ChinaSchool of Mechanical-Electronic and Vehicle Engineering, Beijing University of Civil Engineering and Architecture, Beijing 100044, ChinaSchool of Mechanical-Electronic and Vehicle Engineering, Beijing University of Civil Engineering and Architecture, Beijing 100044, ChinaSchool of Mechanical-Electronic and Vehicle Engineering, Beijing University of Civil Engineering and Architecture, Beijing 100044, ChinaBeijing Key Laboratory of Performance Guarantee on Urban Rail Transit Vehicles, Beijing University of Civil Engineering and Architecture, Beijing 100044, ChinaIn the signal processing of real subway vehicles, impacts between wheelsets and rail joint gaps have significant negative effects on the spectrum. This introduces great difficulties for the fault diagnosis of gearboxes. To solve this problem, this paper proposes an adaptive time-domain signal segmentation method that envelopes the original signal using a cubic spline interpolation. The peak values of the rail joint gap impacts are extracted to realize the adaptive segmentation of gearbox fault signals when the vehicle was moving at a uniform speed. A long-time and unsteady signal affected by wheel–rail impacts is segmented into multiple short-term, steady-state signals, which can suppress the high amplitude of the shock response signal. Finally, on this basis, multiple short-term sample signals are analyzed by time- and frequency-domain analyses and compared with the nonfaulty results. The results showed that the method can efficiently suppress the high-amplitude components of subway gearbox vibration signals and effectively extract the characteristics of weak faults due to uniform wear of the gearbox in the time and frequency domains. This provides reference value for the gearbox fault diagnosis in engineering practice.https://www.mdpi.com/1099-4300/23/6/660gearboxsignal interceptionpeak extractioncubic spline interpolation envelope |
| spellingShingle | Zhongshuo Hu Jianwei Yang Dechen Yao Jinhai Wang Yongliang Bai Subway Gearbox Fault Diagnosis Algorithm Based on Adaptive Spline Impact Suppression Entropy gearbox signal interception peak extraction cubic spline interpolation envelope |
| title | Subway Gearbox Fault Diagnosis Algorithm Based on Adaptive Spline Impact Suppression |
| title_full | Subway Gearbox Fault Diagnosis Algorithm Based on Adaptive Spline Impact Suppression |
| title_fullStr | Subway Gearbox Fault Diagnosis Algorithm Based on Adaptive Spline Impact Suppression |
| title_full_unstemmed | Subway Gearbox Fault Diagnosis Algorithm Based on Adaptive Spline Impact Suppression |
| title_short | Subway Gearbox Fault Diagnosis Algorithm Based on Adaptive Spline Impact Suppression |
| title_sort | subway gearbox fault diagnosis algorithm based on adaptive spline impact suppression |
| topic | gearbox signal interception peak extraction cubic spline interpolation envelope |
| url | https://www.mdpi.com/1099-4300/23/6/660 |
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