Locomotive Gear Fault Diagnosis Based on Wavelet Bispectrum of Motor Current
The motor current signature analysis (MCSA) provides a nondestructive method for gear fault detection. The motor current in the faulty gear system not only involves the frequency information related to the fault but also the electric supply frequency and gear meshing-related frequency, which not onl...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2021-01-01
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| Series: | Shock and Vibration |
| Online Access: | http://dx.doi.org/10.1155/2021/5554777 |
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| _version_ | 1832548718075707392 |
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| author | Mingming Zhang Jiangtian Yang Zhang Zhang |
| author_facet | Mingming Zhang Jiangtian Yang Zhang Zhang |
| author_sort | Mingming Zhang |
| collection | DOAJ |
| description | The motor current signature analysis (MCSA) provides a nondestructive method for gear fault detection. The motor current in the faulty gear system not only involves the frequency information related to the fault but also the electric supply frequency and gear meshing-related frequency, which not only contaminates the fault characteristics but also increases the difficulty of fault extraction. To extract the fault characteristic frequency effectively, an innovative method based on the wavelet bispectrum (WB) is proposed. Bispectrum is an effective tool for identifying the fault-related quadratic phase coupling (QPC). However, it requires a large amount of data averaging, which is not suitable for short data analysis. In this paper, the wavelet bispectrum is introduced to motor current analysis and the problem of QPC extraction under variable speed conditions is preliminarily solved. Furthermore, a fault diagnostic approach for locomotive gears using the wavelet bispectrum and wavelet bispectral entropy is suggested. The presented method was effectively applied to the locomotive online running operations, and faults of the drive gear were successfully diagnosed. |
| format | Article |
| id | doaj-art-f71560de4c614f5d8b01e6293c3667b1 |
| institution | Kabale University |
| issn | 1070-9622 1875-9203 |
| language | English |
| publishDate | 2021-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Shock and Vibration |
| spelling | doaj-art-f71560de4c614f5d8b01e6293c3667b12025-02-03T06:13:18ZengWileyShock and Vibration1070-96221875-92032021-01-01202110.1155/2021/55547775554777Locomotive Gear Fault Diagnosis Based on Wavelet Bispectrum of Motor CurrentMingming Zhang0Jiangtian Yang1Zhang Zhang2School of Mechanical,Electronic and Control Engineering, Beijing Jiaotong University, Beijing 100044, ChinaSchool of Mechanical,Electronic and Control Engineering, Beijing Jiaotong University, Beijing 100044, ChinaSchool of Mechanical,Electronic and Control Engineering, Beijing Jiaotong University, Beijing 100044, ChinaThe motor current signature analysis (MCSA) provides a nondestructive method for gear fault detection. The motor current in the faulty gear system not only involves the frequency information related to the fault but also the electric supply frequency and gear meshing-related frequency, which not only contaminates the fault characteristics but also increases the difficulty of fault extraction. To extract the fault characteristic frequency effectively, an innovative method based on the wavelet bispectrum (WB) is proposed. Bispectrum is an effective tool for identifying the fault-related quadratic phase coupling (QPC). However, it requires a large amount of data averaging, which is not suitable for short data analysis. In this paper, the wavelet bispectrum is introduced to motor current analysis and the problem of QPC extraction under variable speed conditions is preliminarily solved. Furthermore, a fault diagnostic approach for locomotive gears using the wavelet bispectrum and wavelet bispectral entropy is suggested. The presented method was effectively applied to the locomotive online running operations, and faults of the drive gear were successfully diagnosed.http://dx.doi.org/10.1155/2021/5554777 |
| spellingShingle | Mingming Zhang Jiangtian Yang Zhang Zhang Locomotive Gear Fault Diagnosis Based on Wavelet Bispectrum of Motor Current Shock and Vibration |
| title | Locomotive Gear Fault Diagnosis Based on Wavelet Bispectrum of Motor Current |
| title_full | Locomotive Gear Fault Diagnosis Based on Wavelet Bispectrum of Motor Current |
| title_fullStr | Locomotive Gear Fault Diagnosis Based on Wavelet Bispectrum of Motor Current |
| title_full_unstemmed | Locomotive Gear Fault Diagnosis Based on Wavelet Bispectrum of Motor Current |
| title_short | Locomotive Gear Fault Diagnosis Based on Wavelet Bispectrum of Motor Current |
| title_sort | locomotive gear fault diagnosis based on wavelet bispectrum of motor current |
| url | http://dx.doi.org/10.1155/2021/5554777 |
| work_keys_str_mv | AT mingmingzhang locomotivegearfaultdiagnosisbasedonwaveletbispectrumofmotorcurrent AT jiangtianyang locomotivegearfaultdiagnosisbasedonwaveletbispectrumofmotorcurrent AT zhangzhang locomotivegearfaultdiagnosisbasedonwaveletbispectrumofmotorcurrent |