Abstract detail

369 / 2021-07-19 17:27:11
Gearbox Fault Diagnosis based on KHA-VMD-CNN
Gearbox fault diagnosis,,Variational modal decomposition,,Convolutional neural network,,Fault pattern recognition
Special Sessions > Fault Diagnosis of Gears
Draft Paper Accepted
Rujiang Hao / Shijiazhuang Tiedao University
Abstract: Aiming at the complex vibration signals in a gearbox and the difficulty in extracting fault features at the early stage of fault, a gearbox fault feature extraction and fault pattern recognition method based on adaptive Variational Mode Decomposition (VMD) and Convolutional Neural Network (CNN) was proposed in this paper. Firstly, the vibration signals of the gearbox were decomposed using VMD optimized by Krill Herd Algorithm (KHA). Then, the effective modal components are selected by kurtosis criterion for reconstruction. Finally, the reconstructed signal is used as the input of CNN for fault modal identification. The experimental results show that the proposed method is more accurate than the traditional fault pattern identification method.

 

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Important Dates

Abstract Submission Deadline:

 31st March 2021 15th April 2021

Extended Deadline: 1st Aug. 2022

 

Abstract Acceptance:

30th April  2021 Rollover

 

Full Paper Submission Deadline:

30th June 2021  14th July 2021

Extended Deadline: 15th Aug. 2022 

 

Notification of Acceptance:

15th August 2021 1st Sept. 2021

1st Sept. 2022

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