Fault Diagnosis Method of Planetary Gearbox based on Wavelet Time-frequency Diagram and Convolutional Neural Network
Difficulties are always encountered when distinguish the fault types in the planetary gearbox diagnosis. A new fault diagnosis method with implementation of wavelet time-frequency diagram and convolutional neural network is proposed. At first，the continuous wavelet transform is used on the original...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | zho |
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Editorial Office of Journal of Mechanical Transmission
2022-01-01
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| Series: | Jixie chuandong |
| Subjects: | |
| Online Access: | http://www.jxcd.net.cn/thesisDetails#10.16578/j.issn.1004.2539.2022.01.022 |
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| author | Jianhua Zhou Pan Zheng Shuaixing Wang Shijing Wu Xiaosun Wang |
| author_facet | Jianhua Zhou Pan Zheng Shuaixing Wang Shijing Wu Xiaosun Wang |
| author_sort | Jianhua Zhou |
| collection | DOAJ |
| description | Difficulties are always encountered when distinguish the fault types in the planetary gearbox diagnosis. A new fault diagnosis method with implementation of wavelet time-frequency diagram and convolutional neural network is proposed. At first，the continuous wavelet transform is used on the original signal to obtain the wavelet time-frequency diagrams. Secondly，the wavelet time-frequency diagrams are processed and compressed，the processed wavelet time-frequency diagrams are input into the convolutional neural network to classify and identify. Finally，the wavelet basis function and convolution neural network parameters are adjusted in order to get an ideal diagnosis model. Experimental results show that the proposed method has better diagnostic accuracy and robustness than the BP neural network when the speed of training set data and test set data is different. This approach provides a reference for planetary gearbox fault diagnosis. |
| format | Article |
| id | doaj-art-a119c75d4db24005bd532dcc91ce74ac |
| institution | Kabale University |
| issn | 1004-2539 |
| language | zho |
| publishDate | 2022-01-01 |
| publisher | Editorial Office of Journal of Mechanical Transmission |
| record_format | Article |
| series | Jixie chuandong |
| spelling | doaj-art-a119c75d4db24005bd532dcc91ce74ac2025-01-10T13:57:35ZzhoEditorial Office of Journal of Mechanical TransmissionJixie chuandong1004-25392022-01-014615616330473234Fault Diagnosis Method of Planetary Gearbox based on Wavelet Time-frequency Diagram and Convolutional Neural NetworkJianhua ZhouPan ZhengShuaixing WangShijing WuXiaosun WangDifficulties are always encountered when distinguish the fault types in the planetary gearbox diagnosis. A new fault diagnosis method with implementation of wavelet time-frequency diagram and convolutional neural network is proposed. At first，the continuous wavelet transform is used on the original signal to obtain the wavelet time-frequency diagrams. Secondly，the wavelet time-frequency diagrams are processed and compressed，the processed wavelet time-frequency diagrams are input into the convolutional neural network to classify and identify. Finally，the wavelet basis function and convolution neural network parameters are adjusted in order to get an ideal diagnosis model. Experimental results show that the proposed method has better diagnostic accuracy and robustness than the BP neural network when the speed of training set data and test set data is different. This approach provides a reference for planetary gearbox fault diagnosis.http://www.jxcd.net.cn/thesisDetails#10.16578/j.issn.1004.2539.2022.01.022Planetary gearbox fault diagnosisContinuous wavelet transformWavelet time-frequency diagramConvolutional neural network |
| spellingShingle | Jianhua Zhou Pan Zheng Shuaixing Wang Shijing Wu Xiaosun Wang Fault Diagnosis Method of Planetary Gearbox based on Wavelet Time-frequency Diagram and Convolutional Neural Network Jixie chuandong Planetary gearbox fault diagnosis Continuous wavelet transform Wavelet time-frequency diagram Convolutional neural network |
| title | Fault Diagnosis Method of Planetary Gearbox based on Wavelet Time-frequency Diagram and Convolutional Neural Network |
| title_full | Fault Diagnosis Method of Planetary Gearbox based on Wavelet Time-frequency Diagram and Convolutional Neural Network |
| title_fullStr | Fault Diagnosis Method of Planetary Gearbox based on Wavelet Time-frequency Diagram and Convolutional Neural Network |
| title_full_unstemmed | Fault Diagnosis Method of Planetary Gearbox based on Wavelet Time-frequency Diagram and Convolutional Neural Network |
| title_short | Fault Diagnosis Method of Planetary Gearbox based on Wavelet Time-frequency Diagram and Convolutional Neural Network |
| title_sort | fault diagnosis method of planetary gearbox based on wavelet time frequency diagram and convolutional neural network |
| topic | Planetary gearbox fault diagnosis Continuous wavelet transform Wavelet time-frequency diagram Convolutional neural network |
| url | http://www.jxcd.net.cn/thesisDetails#10.16578/j.issn.1004.2539.2022.01.022 |
| work_keys_str_mv | AT jianhuazhou faultdiagnosismethodofplanetarygearboxbasedonwavelettimefrequencydiagramandconvolutionalneuralnetwork AT panzheng faultdiagnosismethodofplanetarygearboxbasedonwavelettimefrequencydiagramandconvolutionalneuralnetwork AT shuaixingwang faultdiagnosismethodofplanetarygearboxbasedonwavelettimefrequencydiagramandconvolutionalneuralnetwork AT shijingwu faultdiagnosismethodofplanetarygearboxbasedonwavelettimefrequencydiagramandconvolutionalneuralnetwork AT xiaosunwang faultdiagnosismethodofplanetarygearboxbasedonwavelettimefrequencydiagramandconvolutionalneuralnetwork |