A Fault Detection Method Based on Bearing Dynamics with Multi-frequency Sinusoidal Signal

Xiaohong Li1; Zhicheng Li2; Zaiyue Yang1

10.23919/CCC55666.2022.9901612

2022

41st Chinese Control Conference (CCC)

1934-1768

978-1-6654-8256-1

2022 41st Chinese Control Conference (CCC)

3126-3131

25-27 July 2022

Hefei, China

345 E 47TH ST, NEW YORK, NY 10017 USA

IEEE

Bearing is a common and important component in the industry, and it is crucial to detect and diagnose its working condition. According to the characteristic the motion process of the bearing that is a periodic nonlinear system with sinusoidal input, a bearing fault detection method based on the nonlinear system with multi-frequency sinusoidal input is proposed. Through the dynamics modeling of the motion for the bearing, it is found that its input and output have the characteristics of almost periodic function. Using the periodogram-based asymptotic local fault detection method, the fault detection problem is transformed into a hypothesis test problem, and a threshold is obtained by the given confidence and the degree of freedom of a specific frequency matrix. The method can effectively and quickly monitor the early minor faults in strong noise environment. The realization and performance of this bearing detection method are illustrated by the simulated vibration signal of the bearing.

Bearing dynamics model fault detection sinusoidal signal statistical methods

第一

英语

CPCI-S

National Key Research and Development Program of China[2019YFB1705401] ; Natural Science Foundation of China["61873118","61903179"] ; Science, Technology and Innovation Commission of Shenzhen Municipality["ZDSYS20200811143601004","RCBS20200714114918137"]

Automation & Control Systems

Automation & Control Systems

WOS:000932071603042

IEEE

1.Department of Mechanical and Energy Engineering, Shenzhen Key Laboratory of Biomimetic Robotics and Intelligent Systems, Guangdong Provincial Key Laboratory of Human-Augmentation and Rehabilitation Robotics in Universities, Southern University of Science and Technology, Shenzhen, China
2.Academy for Advanced Interdisciplinary Studies, Southern University of Science and Technology, Shenzhen, P. R. China

Xiaohong Li,Zhicheng Li,Zaiyue Yang. A Fault Detection Method Based on Bearing Dynamics with Multi-frequency Sinusoidal Signal[C]. 345 E 47TH ST, NEW YORK, NY 10017 USA:IEEE,2022:3126-3131.