Feature Frequency Extraction Method based on SAS Noise Reduction and Spectral Kurtosis
A fault feature extraction method for rolling bearings based on sparse assisted smoothing (SAS) noise reduction and spectral kurtosis (SK) is proposed. Firstly, the simulation signal is de-noised by sparse assisted smoothing (SAS), and the performance of SAS de-noising and low-pass filtering is eval...
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| Format: | Article |
| Language: | zho |
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Editorial Office of Journal of Mechanical Transmission
2019-12-01
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| Series: | Jixie chuandong |
| Subjects: | |
| Online Access: | http://www.jxcd.net.cn/thesisDetails#10.16578/j.issn.1004.2539.2019.12.020 |
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| author | Xiao Lingjun Lü Yong Yuan Rui |
| author_facet | Xiao Lingjun Lü Yong Yuan Rui |
| author_sort | Xiao Lingjun |
| collection | DOAJ |
| description | A fault feature extraction method for rolling bearings based on sparse assisted smoothing (SAS) noise reduction and spectral kurtosis (SK) is proposed. Firstly, the simulation signal is de-noised by sparse assisted smoothing (SAS), and the performance of SAS de-noising and low-pass filtering is evaluated by RMSE index. Then, SAS de-noising and spectral kurtosis method are applied to fault diagnosis of rolling bearings, and clear characteristic frequency is extracted. Then the kurtosis index is used to compare the proposed method with the wavelet de-noising and EMD methods. The advantages of the proposed method in feature extraction are verified. The effectiveness of the proposed method is verified by simulation and data experiments. |
| format | Article |
| id | doaj-art-d7bdced504744f6eaaab8d7aab668d97 |
| institution | Kabale University |
| issn | 1004-2539 |
| language | zho |
| publishDate | 2019-12-01 |
| publisher | Editorial Office of Journal of Mechanical Transmission |
| record_format | Article |
| series | Jixie chuandong |
| spelling | doaj-art-d7bdced504744f6eaaab8d7aab668d972025-01-10T14:46:08ZzhoEditorial Office of Journal of Mechanical TransmissionJixie chuandong1004-25392019-12-014310911531612925Feature Frequency Extraction Method based on SAS Noise Reduction and Spectral KurtosisXiao LingjunLü YongYuan RuiA fault feature extraction method for rolling bearings based on sparse assisted smoothing (SAS) noise reduction and spectral kurtosis (SK) is proposed. Firstly, the simulation signal is de-noised by sparse assisted smoothing (SAS), and the performance of SAS de-noising and low-pass filtering is evaluated by RMSE index. Then, SAS de-noising and spectral kurtosis method are applied to fault diagnosis of rolling bearings, and clear characteristic frequency is extracted. Then the kurtosis index is used to compare the proposed method with the wavelet de-noising and EMD methods. The advantages of the proposed method in feature extraction are verified. The effectiveness of the proposed method is verified by simulation and data experiments.http://www.jxcd.net.cn/thesisDetails#10.16578/j.issn.1004.2539.2019.12.020Sparse assisted smoothing |
| spellingShingle | Xiao Lingjun Lü Yong Yuan Rui Feature Frequency Extraction Method based on SAS Noise Reduction and Spectral Kurtosis Jixie chuandong Sparse assisted smoothing |
| title | Feature Frequency Extraction Method based on SAS Noise Reduction and Spectral Kurtosis |
| title_full | Feature Frequency Extraction Method based on SAS Noise Reduction and Spectral Kurtosis |
| title_fullStr | Feature Frequency Extraction Method based on SAS Noise Reduction and Spectral Kurtosis |
| title_full_unstemmed | Feature Frequency Extraction Method based on SAS Noise Reduction and Spectral Kurtosis |
| title_short | Feature Frequency Extraction Method based on SAS Noise Reduction and Spectral Kurtosis |
| title_sort | feature frequency extraction method based on sas noise reduction and spectral kurtosis |
| topic | Sparse assisted smoothing |
| url | http://www.jxcd.net.cn/thesisDetails#10.16578/j.issn.1004.2539.2019.12.020 |
| work_keys_str_mv | AT xiaolingjun featurefrequencyextractionmethodbasedonsasnoisereductionandspectralkurtosis AT luyong featurefrequencyextractionmethodbasedonsasnoisereductionandspectralkurtosis AT yuanrui featurefrequencyextractionmethodbasedonsasnoisereductionandspectralkurtosis |