Application of Adaptive Mono-Stable Stochastic Resonance Based on Cuckoo Search for Incipient Fault Diagnosis of Rolling Element Bearings

Author(s):  
Jianshe Kang ◽  
Kuo Chi ◽  
Xupeng Die ◽  
Zhenya Wu ◽  
Xiaobo Su
2015 ◽  
Vol 39 (3) ◽  
pp. 593-603
Author(s):  
Xinghui Zhang ◽  
Jianshe Kang ◽  
Hongzhi Teng ◽  
Jianmin Zhao

Gear and bearing faults are the main causes of gearbox failure. Till now, incipient fault diagnosis of these two components has been a problem and needs further research. In this context, it is found that Lucy–Richardson deconvolution (LRD) proved to be an excellent tool to enhance fault diagnosis in rolling element bearings and gears. LRD’s good identification capabilities of fault frequencies are presented which outperform envelope analysis. This is very critical for early fault diagnosis. The case studies were carried out to evaluate the effectiveness of the proposed method. The results of simulated and experimental studies show that LRD is efficient in alleviating the negative effect of noise and transmission path. The results of simulation and experimental tests demonstrated outperformance of LRD compared to classical envelope analysis for fault diagnosis in rolling element bearings and gears, especially when it is applied to the processing of signals with strong background noise.


2019 ◽  
Vol 96 (3) ◽  
pp. 2069-2085 ◽  
Author(s):  
Z. H. Lai ◽  
J. S. Liu ◽  
H. T. Zhang ◽  
C. L. Zhang ◽  
J. W. Zhang ◽  
...  

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