Fault diagnosis of planetary gearboxes based on feature fusion and ResNet
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TN10;TH165 + . 3

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    Abstract:

    Aiming at the coupling of vibration signals and inaccurate fault diagnosis of planetary gearbox, a fault diagnosis method of planetary gearbox based on feature fusion and ResNet is proposed. Firstly, the collected analog fault vibration signals such as planetary gear crack, wear, sun gear broken tooth and composite fault are decomposed by MEEMD and VMD to screen and determine the effective components respectively. Then, the selected effective features are fused and classified by using traditional CNN network and ResNet. The results show that the ResNet has higher classification accuracy, up to more than 95%. Finally, the classification accuracy of data before and after feature fusion is compared by using ResNet. The accuracy before fusion was only 91. 16%, which was lower than 97. 18% of after fusion. Thus, this method is very effective for coupling vibration signal processing and fault diagnosis of planetary gearbox.

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  • Received:
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  • Online: March 06,2023
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