Wheelset-Bearing Fault Detection Using Adaptive Convolution Sparse Representation
Wheelset bearings are crucial mechanical components of high-speed trains. Wheelset-bearing fault detection is of great significance to ensure the safety of high-speed train service. Convolution sparse representations (CSRs) provide an excellent framework for extracting impulse responses induced by b...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Wiley
2019-01-01
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| Series: | Shock and Vibration |
| Online Access: | http://dx.doi.org/10.1155/2019/7198693 |
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| _version_ | 1832551788438355968 |
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| author | Jianming Ding Zhaoheng Zhang Yanli Yin |
| author_facet | Jianming Ding Zhaoheng Zhang Yanli Yin |
| author_sort | Jianming Ding |
| collection | DOAJ |
| description | Wheelset bearings are crucial mechanical components of high-speed trains. Wheelset-bearing fault detection is of great significance to ensure the safety of high-speed train service. Convolution sparse representations (CSRs) provide an excellent framework for extracting impulse responses induced by bearing faults. However, the performance of CSR on extracting impulse responses is fairly sensitive to inappropriate selection of method-related parameters, and a convolution model for representing the impulse responses has not been discussed. In view of these two unsolved problems, a convolutional representation model of the impulse response series is developed. A novel fault detection method, named adaptive CSR (ACSR), is then proposed based on combinations of CSR and methods for estimating three parameters related to CSR. Finally, the effectiveness of the proposed ACSR method is validated via simulation, bench testing, and a real-life running test employing a high-speed train. |
| format | Article |
| id | doaj-art-1c6cb4fbfd724c99a6f19b1e02906296 |
| institution | Kabale University |
| issn | 1070-9622 1875-9203 |
| language | English |
| publishDate | 2019-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Shock and Vibration |
| spelling | doaj-art-1c6cb4fbfd724c99a6f19b1e029062962025-02-03T06:00:33ZengWileyShock and Vibration1070-96221875-92032019-01-01201910.1155/2019/71986937198693Wheelset-Bearing Fault Detection Using Adaptive Convolution Sparse RepresentationJianming Ding0Zhaoheng Zhang1Yanli Yin2The State Key Laboratory of Mechanical Transmissions, Chongqing University, Chongqing 400044, ChinaThe State Key Laboratory of Traction Power, Southwest Jiaotong University, Chengdu 610031, ChinaSchool of Mechatronics & Vehicle Engineering, Chongqing University, Chongqing 40074, ChinaWheelset bearings are crucial mechanical components of high-speed trains. Wheelset-bearing fault detection is of great significance to ensure the safety of high-speed train service. Convolution sparse representations (CSRs) provide an excellent framework for extracting impulse responses induced by bearing faults. However, the performance of CSR on extracting impulse responses is fairly sensitive to inappropriate selection of method-related parameters, and a convolution model for representing the impulse responses has not been discussed. In view of these two unsolved problems, a convolutional representation model of the impulse response series is developed. A novel fault detection method, named adaptive CSR (ACSR), is then proposed based on combinations of CSR and methods for estimating three parameters related to CSR. Finally, the effectiveness of the proposed ACSR method is validated via simulation, bench testing, and a real-life running test employing a high-speed train.http://dx.doi.org/10.1155/2019/7198693 |
| spellingShingle | Jianming Ding Zhaoheng Zhang Yanli Yin Wheelset-Bearing Fault Detection Using Adaptive Convolution Sparse Representation Shock and Vibration |
| title | Wheelset-Bearing Fault Detection Using Adaptive Convolution Sparse Representation |
| title_full | Wheelset-Bearing Fault Detection Using Adaptive Convolution Sparse Representation |
| title_fullStr | Wheelset-Bearing Fault Detection Using Adaptive Convolution Sparse Representation |
| title_full_unstemmed | Wheelset-Bearing Fault Detection Using Adaptive Convolution Sparse Representation |
| title_short | Wheelset-Bearing Fault Detection Using Adaptive Convolution Sparse Representation |
| title_sort | wheelset bearing fault detection using adaptive convolution sparse representation |
| url | http://dx.doi.org/10.1155/2019/7198693 |
| work_keys_str_mv | AT jianmingding wheelsetbearingfaultdetectionusingadaptiveconvolutionsparserepresentation AT zhaohengzhang wheelsetbearingfaultdetectionusingadaptiveconvolutionsparserepresentation AT yanliyin wheelsetbearingfaultdetectionusingadaptiveconvolutionsparserepresentation |