Fault Diagnosis of Rolling Bearing Based on Tunable Q-Factor Wavelet Transform and Convolutional Neural Network

Fault Diagnosis of Rolling Bearing Based on Tunable Q-Factor Wavelet Transform and Convolutional Neural Network

Rolling bearing plays an important role in rotary machines and industrial processes. Effective fault diagnosis technology for rolling bearing directly affects the life and operator safety of the devices. In this paper, a fault diagnosis method based on tunable-Q wavelet transform (TQWT) and convolut...

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Bibliographic Details
Main Authors: Liqun Hou, Zijing Li
Format: Article
Language:English
Published: International Association of Online Engineering (IAOE) 2020-02-01
Series:International Journal of Online and Biomedical Engineering
Subjects:
fault diagnosis
tunable q-factor wavelet transform
convolutional neural network
rolling bearing
Online Access:https://online-journals.org/index.php/i-joe/article/view/11953

Internet

https://online-journals.org/index.php/i-joe/article/view/11953

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