A Fault Diagnosis Method for Planetary Gearboxes Based on IFMD
The vibration signal from the planetary gearbox exhibits nonlinear and impulsive characteristics amidst strong noise, impeding the effective extraction of fault information and compromising the accuracy of fault diagnosis. To address this challenge, a fault diagnosis method rooted in feature mode de...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2024-01-01
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| Series: | Shock and Vibration |
| Online Access: | http://dx.doi.org/10.1155/2024/2140227 |
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| _version_ | 1841561426818236416 |
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| author | Fengfeng Bie Xueping Ding Qianqian Li Yuting Zhang Xinyue Huang |
| author_facet | Fengfeng Bie Xueping Ding Qianqian Li Yuting Zhang Xinyue Huang |
| author_sort | Fengfeng Bie |
| collection | DOAJ |
| description | The vibration signal from the planetary gearbox exhibits nonlinear and impulsive characteristics amidst strong noise, impeding the effective extraction of fault information and compromising the accuracy of fault diagnosis. To address this challenge, a fault diagnosis method rooted in feature mode decomposition (FMD) is proposed. Initially, the critical parameters (modal number n and filter length L) of FMD are optimized using an improved genetic algorithm (IGA), and the refined FMD is employed to decompose the vibration signals from the planetary gearbox. Subsequently, a convolutional neural network integrated with the support vector machine model (CNN-SVM) is established, leveraging the convolutional neural network for feature extraction. Ultimately, SVM iteratively optimized by the particle swarm optimization (PSO) algorithm, serves as the classification technique. Simulation and experiment results demonstrate the effectiveness of this method in extracting and identifying fault information within planetary gearboxes. |
| format | Article |
| id | doaj-art-9227d4ce03464f5e8a8f45a6af16862f |
| institution | Kabale University |
| issn | 1875-9203 |
| language | English |
| publishDate | 2024-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Shock and Vibration |
| spelling | doaj-art-9227d4ce03464f5e8a8f45a6af16862f2025-01-03T01:41:03ZengWileyShock and Vibration1875-92032024-01-01202410.1155/2024/2140227A Fault Diagnosis Method for Planetary Gearboxes Based on IFMDFengfeng Bie0Xueping Ding1Qianqian Li2Yuting Zhang3Xinyue Huang4School of Mechanical Engineering and Rail TransitSchool of Mechanical Engineering and Rail TransitSchool of Mechanical Engineering and Rail TransitSchool of Mechanical Engineering and Rail TransitSchool of Mechanical Engineering and Rail TransitThe vibration signal from the planetary gearbox exhibits nonlinear and impulsive characteristics amidst strong noise, impeding the effective extraction of fault information and compromising the accuracy of fault diagnosis. To address this challenge, a fault diagnosis method rooted in feature mode decomposition (FMD) is proposed. Initially, the critical parameters (modal number n and filter length L) of FMD are optimized using an improved genetic algorithm (IGA), and the refined FMD is employed to decompose the vibration signals from the planetary gearbox. Subsequently, a convolutional neural network integrated with the support vector machine model (CNN-SVM) is established, leveraging the convolutional neural network for feature extraction. Ultimately, SVM iteratively optimized by the particle swarm optimization (PSO) algorithm, serves as the classification technique. Simulation and experiment results demonstrate the effectiveness of this method in extracting and identifying fault information within planetary gearboxes.http://dx.doi.org/10.1155/2024/2140227 |
| spellingShingle | Fengfeng Bie Xueping Ding Qianqian Li Yuting Zhang Xinyue Huang A Fault Diagnosis Method for Planetary Gearboxes Based on IFMD Shock and Vibration |
| title | A Fault Diagnosis Method for Planetary Gearboxes Based on IFMD |
| title_full | A Fault Diagnosis Method for Planetary Gearboxes Based on IFMD |
| title_fullStr | A Fault Diagnosis Method for Planetary Gearboxes Based on IFMD |
| title_full_unstemmed | A Fault Diagnosis Method for Planetary Gearboxes Based on IFMD |
| title_short | A Fault Diagnosis Method for Planetary Gearboxes Based on IFMD |
| title_sort | fault diagnosis method for planetary gearboxes based on ifmd |
| url | http://dx.doi.org/10.1155/2024/2140227 |
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