Fault Diagnosis of Bearings with Adjusted Vibration Spectrum Images
In order to diagnose bearing faults under different operating state and limited sample condition, a fault diagnosis method based on adjusted spectrum image of vibration signal is proposed in this paper. Firstly, the Davies–Bouldin index (DBI) is employed to select a proper capture focus (CF) and ima...
Saved in:
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2018-01-01
|
| Series: | Shock and Vibration |
| Online Access: | http://dx.doi.org/10.1155/2018/6981760 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1832558013476503552 |
|---|---|
| author | Mingquan Qiu Wei Li Zhencai Zhu Fan Jiang Gongbo Zhou |
| author_facet | Mingquan Qiu Wei Li Zhencai Zhu Fan Jiang Gongbo Zhou |
| author_sort | Mingquan Qiu |
| collection | DOAJ |
| description | In order to diagnose bearing faults under different operating state and limited sample condition, a fault diagnosis method based on adjusted spectrum image of vibration signal is proposed in this paper. Firstly, the Davies–Bouldin index (DBI) is employed to select a proper capture focus (CF) and image size, and the spectrum of vibration signal is computed via fast Fourier transformation (FFT) and adjusted according to the average rotating speed. Then, the spectrum is plotted and captured as a two-dimensional (2D) image with the optimized CF and image size. Two-dimensional principal component analysis (2DPCA) is used to reduce the dimension of images, and finally a nearest neighbour method is applied to classify the faults of bearings. Two experiments are carried out to validate the effectiveness of the proposed method. Besides, a further investigation on the effect of spectrum frequency resolution is conducted and a recommended selection method of frequency resolution is given based on the experimental performances. In our method, the training samples could be from only one operating condition, while the testing samples are from all possible operation conditions. All experiment results have demonstrated that the proposed method could achieve high classification accuracy even with very limited training samples. |
| format | Article |
| id | doaj-art-10d03e194886493999fb361143692c41 |
| institution | Kabale University |
| issn | 1070-9622 1875-9203 |
| language | English |
| publishDate | 2018-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Shock and Vibration |
| spelling | doaj-art-10d03e194886493999fb361143692c412025-02-03T01:33:20ZengWileyShock and Vibration1070-96221875-92032018-01-01201810.1155/2018/69817606981760Fault Diagnosis of Bearings with Adjusted Vibration Spectrum ImagesMingquan Qiu0Wei Li1Zhencai Zhu2Fan Jiang3Gongbo Zhou4School of Mechatronic Engineering, China University of Mining and Technology, Xuzhou 221116, ChinaSchool of Mechatronic Engineering, China University of Mining and Technology, Xuzhou 221116, ChinaSchool of Mechatronic Engineering, China University of Mining and Technology, Xuzhou 221116, ChinaSchool of Mechatronic Engineering, China University of Mining and Technology, Xuzhou 221116, ChinaSchool of Mechatronic Engineering, China University of Mining and Technology, Xuzhou 221116, ChinaIn order to diagnose bearing faults under different operating state and limited sample condition, a fault diagnosis method based on adjusted spectrum image of vibration signal is proposed in this paper. Firstly, the Davies–Bouldin index (DBI) is employed to select a proper capture focus (CF) and image size, and the spectrum of vibration signal is computed via fast Fourier transformation (FFT) and adjusted according to the average rotating speed. Then, the spectrum is plotted and captured as a two-dimensional (2D) image with the optimized CF and image size. Two-dimensional principal component analysis (2DPCA) is used to reduce the dimension of images, and finally a nearest neighbour method is applied to classify the faults of bearings. Two experiments are carried out to validate the effectiveness of the proposed method. Besides, a further investigation on the effect of spectrum frequency resolution is conducted and a recommended selection method of frequency resolution is given based on the experimental performances. In our method, the training samples could be from only one operating condition, while the testing samples are from all possible operation conditions. All experiment results have demonstrated that the proposed method could achieve high classification accuracy even with very limited training samples.http://dx.doi.org/10.1155/2018/6981760 |
| spellingShingle | Mingquan Qiu Wei Li Zhencai Zhu Fan Jiang Gongbo Zhou Fault Diagnosis of Bearings with Adjusted Vibration Spectrum Images Shock and Vibration |
| title | Fault Diagnosis of Bearings with Adjusted Vibration Spectrum Images |
| title_full | Fault Diagnosis of Bearings with Adjusted Vibration Spectrum Images |
| title_fullStr | Fault Diagnosis of Bearings with Adjusted Vibration Spectrum Images |
| title_full_unstemmed | Fault Diagnosis of Bearings with Adjusted Vibration Spectrum Images |
| title_short | Fault Diagnosis of Bearings with Adjusted Vibration Spectrum Images |
| title_sort | fault diagnosis of bearings with adjusted vibration spectrum images |
| url | http://dx.doi.org/10.1155/2018/6981760 |
| work_keys_str_mv | AT mingquanqiu faultdiagnosisofbearingswithadjustedvibrationspectrumimages AT weili faultdiagnosisofbearingswithadjustedvibrationspectrumimages AT zhencaizhu faultdiagnosisofbearingswithadjustedvibrationspectrumimages AT fanjiang faultdiagnosisofbearingswithadjustedvibrationspectrumimages AT gongbozhou faultdiagnosisofbearingswithadjustedvibrationspectrumimages |