Extraction and enhancement of unknown bearing fault feature in the strong noise under variable speed condition

Author(s):  
Jianhua Yang ◽  
Chengjin Wu ◽  
zhen Shan ◽  
Houguang Liu ◽  
Chen Yang
Author(s):  
Xuzhu Zhuang ◽  
Chen Yang ◽  
Jianhua Yang ◽  
Chengjin Wu ◽  
Zhen Shan ◽  
...  

The fault characteristic of rolling bearings under variable speed condition is a typical non-stationary stochastic signal. It is difficult to extract due to the interference of strong background noise makes the applicability of traditional noise reduction methods less. In this paper, an aperiodic stochastic resonance (ASR) method is proposed to study the fault diagnosis of rolling bearings under variable speed conditions. Based on numerical simulation, the effect of noise intensity and damping coefficient on the ASR of the second-order underdamped system is discussed, and an appropriate damping coefficient is found to reach the optimal ASR. The proposed method enhances the fault characteristic information of bearing fault simulation signal. Corresponding to rising-stationary and the stationary-declining running conditions, the method is verified by both simulated and experimental signals. It provides reference for fault diagnosis under variable speed condition.


2013 ◽  
Vol 791-793 ◽  
pp. 790-794
Author(s):  
Shi Shun Zhu ◽  
Jing Li ◽  
Sun Yan ◽  
Su Jun Luo

Vehicle-mounted shaft generator system with constant frequency and voltage under variable speed condition can adapt to a large speed range of working condition while the vehicle is moving. Its key technologies are a process of rectification-inversion and a composite staggered parallel DC converter. Test research shows that electrical performance of the shaft generator system meets the first kind electric power plant requirements according to GJB 5785-2006 of China, which indicates that the shaft generator system can provide uninterrupted high quality electric power to current general on-board electrical equipment on vehicles under all speed conditions.


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