A Fault Diagnosis Method for Out-of-Round Faults of Metro Vehicle Wheels with Strong Noise
Detection of out-of round (OOR) faults of metro vehicle wheels is very important to improve stationarity and stability in metro vehicles and avoid accidents caused by OOR faults. Diagnosis of OOR faults demands extracting useful information accurately from mass of vibration signals with poor signal-...
Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2021-01-01
|
| Series: | Shock and Vibration |
| Online Access: | http://dx.doi.org/10.1155/2021/9257622 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1832549155158884352 |
|---|---|
| author | Haifeng Huang Heli Wang Weijiu Zhang Weijie Gu |
| author_facet | Haifeng Huang Heli Wang Weijiu Zhang Weijie Gu |
| author_sort | Haifeng Huang |
| collection | DOAJ |
| description | Detection of out-of round (OOR) faults of metro vehicle wheels is very important to improve stationarity and stability in metro vehicles and avoid accidents caused by OOR faults. Diagnosis of OOR faults demands extracting useful information accurately from mass of vibration signals with poor signal-to-noise ratio (SNR) of metro vehicle wheels for complex running condition. In this paper, we proposed a diagnosis method on OOR faults of metro vehicle wheels combined with variational mode decomposition (VMD), kernel principal component analysis (KPCA), and deep belief network (DBN) to diagnose the OOR faults of metro wheels. Vibration signals of China metro vehicle wheels collected while the metro vehicle is running are used to train the diagnosis model and adjust parameters of DBN and KPCA based on testing accuracy. The different dimensions of KPCA, epoch number, and node number of DBN are compared, and the better parameters of diagnosis model based on vibration signals are concluded in this paper. The generalization of the diagnosis model is checked nine times by testing the calculation of each group of parameters and using an error declining process. The mean accuracy of diagnosis model proposed in this paper is 0.9136, and the diagnosis model presented in this paper is very significant to detect OOR faults online. |
| format | Article |
| id | doaj-art-3d5e34cf48564684a109ccb0076d8bd3 |
| 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-3d5e34cf48564684a109ccb0076d8bd32025-02-03T06:12:05ZengWileyShock and Vibration1070-96221875-92032021-01-01202110.1155/2021/92576229257622A Fault Diagnosis Method for Out-of-Round Faults of Metro Vehicle Wheels with Strong NoiseHaifeng Huang0Heli Wang1Weijiu Zhang2Weijie Gu3School of Mechanical Engineering, Southwest Jiaotong University, Chengdu 610031, ChinaPatent Examination Cooperation Sichuan Center of the Patent Office, China National Intellectual Property Administration, Chengdu 610213, ChinaWuhan Metro Operation Co., Ltd., Qiaokou District, Wuhan 430000, ChinaSchool of Mechanical Engineering, Southwest Jiaotong University, Chengdu 610031, ChinaDetection of out-of round (OOR) faults of metro vehicle wheels is very important to improve stationarity and stability in metro vehicles and avoid accidents caused by OOR faults. Diagnosis of OOR faults demands extracting useful information accurately from mass of vibration signals with poor signal-to-noise ratio (SNR) of metro vehicle wheels for complex running condition. In this paper, we proposed a diagnosis method on OOR faults of metro vehicle wheels combined with variational mode decomposition (VMD), kernel principal component analysis (KPCA), and deep belief network (DBN) to diagnose the OOR faults of metro wheels. Vibration signals of China metro vehicle wheels collected while the metro vehicle is running are used to train the diagnosis model and adjust parameters of DBN and KPCA based on testing accuracy. The different dimensions of KPCA, epoch number, and node number of DBN are compared, and the better parameters of diagnosis model based on vibration signals are concluded in this paper. The generalization of the diagnosis model is checked nine times by testing the calculation of each group of parameters and using an error declining process. The mean accuracy of diagnosis model proposed in this paper is 0.9136, and the diagnosis model presented in this paper is very significant to detect OOR faults online.http://dx.doi.org/10.1155/2021/9257622 |
| spellingShingle | Haifeng Huang Heli Wang Weijiu Zhang Weijie Gu A Fault Diagnosis Method for Out-of-Round Faults of Metro Vehicle Wheels with Strong Noise Shock and Vibration |
| title | A Fault Diagnosis Method for Out-of-Round Faults of Metro Vehicle Wheels with Strong Noise |
| title_full | A Fault Diagnosis Method for Out-of-Round Faults of Metro Vehicle Wheels with Strong Noise |
| title_fullStr | A Fault Diagnosis Method for Out-of-Round Faults of Metro Vehicle Wheels with Strong Noise |
| title_full_unstemmed | A Fault Diagnosis Method for Out-of-Round Faults of Metro Vehicle Wheels with Strong Noise |
| title_short | A Fault Diagnosis Method for Out-of-Round Faults of Metro Vehicle Wheels with Strong Noise |
| title_sort | fault diagnosis method for out of round faults of metro vehicle wheels with strong noise |
| url | http://dx.doi.org/10.1155/2021/9257622 |
| work_keys_str_mv | AT haifenghuang afaultdiagnosismethodforoutofroundfaultsofmetrovehiclewheelswithstrongnoise AT heliwang afaultdiagnosismethodforoutofroundfaultsofmetrovehiclewheelswithstrongnoise AT weijiuzhang afaultdiagnosismethodforoutofroundfaultsofmetrovehiclewheelswithstrongnoise AT weijiegu afaultdiagnosismethodforoutofroundfaultsofmetrovehiclewheelswithstrongnoise AT haifenghuang faultdiagnosismethodforoutofroundfaultsofmetrovehiclewheelswithstrongnoise AT heliwang faultdiagnosismethodforoutofroundfaultsofmetrovehiclewheelswithstrongnoise AT weijiuzhang faultdiagnosismethodforoutofroundfaultsofmetrovehiclewheelswithstrongnoise AT weijiegu faultdiagnosismethodforoutofroundfaultsofmetrovehiclewheelswithstrongnoise |