An Approach of Intelligent Compound Fault Diagnosis of Rolling Bearing based on MWT and CNN
An approach to intelligent compound fault diagnosis of rolling bearing using multi- wavelet transform（ MWT） and convolution neural network（ CNN） was proposed. According to this approach,the vibration signals of rolling bearing are analyzed by using MWT of removed post processing,and the correspondin...
Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | zho |
| Published: |
Editorial Office of Journal of Mechanical Transmission
2016-01-01
|
| Series: | Jixie chuandong |
| Subjects: | |
| Online Access: | http://www.jxcd.net.cn/thesisDetails#10.16578/j.issn.1004.2539.2016.12.031 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1841548089625673728 |
|---|---|
| author | Han Tao Yuan Jianhu Tang Jian An Lizhou |
| author_facet | Han Tao Yuan Jianhu Tang Jian An Lizhou |
| author_sort | Han Tao |
| collection | DOAJ |
| description | An approach to intelligent compound fault diagnosis of rolling bearing using multi- wavelet transform（ MWT） and convolution neural network（ CNN） was proposed. According to this approach,the vibration signals of rolling bearing are analyzed by using MWT of removed post processing,and the corresponding multi- wavelet coefficient branches are obtained. Then,all the multi- wavelet coefficient branches are used to form feature maps,and a multiple CNN classifiers is developed to identify the compound fault of rolling bearing.The tests for the proposed method are accomplished based on artificial bearing fault data sets,and the method is optimized,the vibration signals are analyzed by using MWT,the obtained multi- wavelet coefficient matrix is used to form feature map,and CNN is developed to make a comparative experimental study. The experimental results indicates that this method could effectively identify the compound fault of rolling bearing,and the improved method could effectively improve the fault recognition rate and reduce the training cost. |
| format | Article |
| id | doaj-art-c14df9f61f234ceea8a60d331da8f7d9 |
| institution | Kabale University |
| issn | 1004-2539 |
| language | zho |
| publishDate | 2016-01-01 |
| publisher | Editorial Office of Journal of Mechanical Transmission |
| record_format | Article |
| series | Jixie chuandong |
| spelling | doaj-art-c14df9f61f234ceea8a60d331da8f7d92025-01-10T14:14:33ZzhoEditorial Office of Journal of Mechanical TransmissionJixie chuandong1004-25392016-01-014013914329927759An Approach of Intelligent Compound Fault Diagnosis of Rolling Bearing based on MWT and CNNHan TaoYuan JianhuTang JianAn LizhouAn approach to intelligent compound fault diagnosis of rolling bearing using multi- wavelet transform（ MWT） and convolution neural network（ CNN） was proposed. According to this approach,the vibration signals of rolling bearing are analyzed by using MWT of removed post processing,and the corresponding multi- wavelet coefficient branches are obtained. Then,all the multi- wavelet coefficient branches are used to form feature maps,and a multiple CNN classifiers is developed to identify the compound fault of rolling bearing.The tests for the proposed method are accomplished based on artificial bearing fault data sets,and the method is optimized,the vibration signals are analyzed by using MWT,the obtained multi- wavelet coefficient matrix is used to form feature map,and CNN is developed to make a comparative experimental study. The experimental results indicates that this method could effectively identify the compound fault of rolling bearing,and the improved method could effectively improve the fault recognition rate and reduce the training cost.http://www.jxcd.net.cn/thesisDetails#10.16578/j.issn.1004.2539.2016.12.031Rolling bearingIntelligent compound fault diagnosisMulti-wavelet transform（MWT）Convolution neural network（CNN） |
| spellingShingle | Han Tao Yuan Jianhu Tang Jian An Lizhou An Approach of Intelligent Compound Fault Diagnosis of Rolling Bearing based on MWT and CNN Jixie chuandong Rolling bearing Intelligent compound fault diagnosis Multi-wavelet transform（MWT） Convolution neural network（CNN） |
| title | An Approach of Intelligent Compound Fault Diagnosis of Rolling Bearing based on MWT and CNN |
| title_full | An Approach of Intelligent Compound Fault Diagnosis of Rolling Bearing based on MWT and CNN |
| title_fullStr | An Approach of Intelligent Compound Fault Diagnosis of Rolling Bearing based on MWT and CNN |
| title_full_unstemmed | An Approach of Intelligent Compound Fault Diagnosis of Rolling Bearing based on MWT and CNN |
| title_short | An Approach of Intelligent Compound Fault Diagnosis of Rolling Bearing based on MWT and CNN |
| title_sort | approach of intelligent compound fault diagnosis of rolling bearing based on mwt and cnn |
| topic | Rolling bearing Intelligent compound fault diagnosis Multi-wavelet transform（MWT） Convolution neural network（CNN） |
| url | http://www.jxcd.net.cn/thesisDetails#10.16578/j.issn.1004.2539.2016.12.031 |
| work_keys_str_mv | AT hantao anapproachofintelligentcompoundfaultdiagnosisofrollingbearingbasedonmwtandcnn AT yuanjianhu anapproachofintelligentcompoundfaultdiagnosisofrollingbearingbasedonmwtandcnn AT tangjian anapproachofintelligentcompoundfaultdiagnosisofrollingbearingbasedonmwtandcnn AT anlizhou anapproachofintelligentcompoundfaultdiagnosisofrollingbearingbasedonmwtandcnn AT hantao approachofintelligentcompoundfaultdiagnosisofrollingbearingbasedonmwtandcnn AT yuanjianhu approachofintelligentcompoundfaultdiagnosisofrollingbearingbasedonmwtandcnn AT tangjian approachofintelligentcompoundfaultdiagnosisofrollingbearingbasedonmwtandcnn AT anlizhou approachofintelligentcompoundfaultdiagnosisofrollingbearingbasedonmwtandcnn |