Research of Wavelet Neural Network State Degradation Prediction of Rolling Bearing New Time Domain Index
Aiming at lower accuracy of classification for signal feature extraction of rolling bearing,firstly,some time domain indexes for online simple rapid discrimination are selected. The sensitivity of time domain index of fault is analyzed based on size of bearing fatigue damage and number of local dama...
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| Format: | Article |
| Language: | zho |
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Editorial Office of Journal of Mechanical Transmission
2016-01-01
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| Series: | Jixie chuandong |
| Subjects: | |
| Online Access: | http://www.jxcd.net.cn/thesisDetails#10.16578/j.issn.1004.2539.2016.06.008 |
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| _version_ | 1841547905750532096 |
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| author | Li Wenfeng Xu Aiqiang Sun Jijie Fan Fuqin |
| author_facet | Li Wenfeng Xu Aiqiang Sun Jijie Fan Fuqin |
| author_sort | Li Wenfeng |
| collection | DOAJ |
| description | Aiming at lower accuracy of classification for signal feature extraction of rolling bearing,firstly,some time domain indexes for online simple rapid discrimination are selected. The sensitivity of time domain index of fault is analyzed based on size of bearing fatigue damage and number of local damage. Secondly,based on the traditional time domain index,two more sensitive time domain index ‘TALAF ’and ‘THIKAT ’is searched. Lastly,the data set including two new indicators are trained and tested based on wavelet neural network which has a good real-time. The training and testing results for the traditional time domain indexes kurtosis and BP neural network are compared with results of the data. The simulation results show that TALAF and THIKAT can effectively improve the accuracy of prediction index state bearing. |
| format | Article |
| id | doaj-art-285ae81324d44bff939130f4de8dc035 |
| 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-285ae81324d44bff939130f4de8dc0352025-01-10T14:16:58ZzhoEditorial Office of Journal of Mechanical TransmissionJixie chuandong1004-25392016-01-0140364129924192Research of Wavelet Neural Network State Degradation Prediction of Rolling Bearing New Time Domain IndexLi WenfengXu AiqiangSun JijieFan FuqinAiming at lower accuracy of classification for signal feature extraction of rolling bearing,firstly,some time domain indexes for online simple rapid discrimination are selected. The sensitivity of time domain index of fault is analyzed based on size of bearing fatigue damage and number of local damage. Secondly,based on the traditional time domain index,two more sensitive time domain index ‘TALAF ’and ‘THIKAT ’is searched. Lastly,the data set including two new indicators are trained and tested based on wavelet neural network which has a good real-time. The training and testing results for the traditional time domain indexes kurtosis and BP neural network are compared with results of the data. The simulation results show that TALAF and THIKAT can effectively improve the accuracy of prediction index state bearing.http://www.jxcd.net.cn/thesisDetails#10.16578/j.issn.1004.2539.2016.06.008Rolling bearingTime domain indexWavelet neural networkFault prediction |
| spellingShingle | Li Wenfeng Xu Aiqiang Sun Jijie Fan Fuqin Research of Wavelet Neural Network State Degradation Prediction of Rolling Bearing New Time Domain Index Jixie chuandong Rolling bearing Time domain index Wavelet neural network Fault prediction |
| title | Research of Wavelet Neural Network State Degradation Prediction of Rolling Bearing New Time Domain Index |
| title_full | Research of Wavelet Neural Network State Degradation Prediction of Rolling Bearing New Time Domain Index |
| title_fullStr | Research of Wavelet Neural Network State Degradation Prediction of Rolling Bearing New Time Domain Index |
| title_full_unstemmed | Research of Wavelet Neural Network State Degradation Prediction of Rolling Bearing New Time Domain Index |
| title_short | Research of Wavelet Neural Network State Degradation Prediction of Rolling Bearing New Time Domain Index |
| title_sort | research of wavelet neural network state degradation prediction of rolling bearing new time domain index |
| topic | Rolling bearing Time domain index Wavelet neural network Fault prediction |
| url | http://www.jxcd.net.cn/thesisDetails#10.16578/j.issn.1004.2539.2016.06.008 |
| work_keys_str_mv | AT liwenfeng researchofwaveletneuralnetworkstatedegradationpredictionofrollingbearingnewtimedomainindex AT xuaiqiang researchofwaveletneuralnetworkstatedegradationpredictionofrollingbearingnewtimedomainindex AT sunjijie researchofwaveletneuralnetworkstatedegradationpredictionofrollingbearingnewtimedomainindex AT fanfuqin researchofwaveletneuralnetworkstatedegradationpredictionofrollingbearingnewtimedomainindex |