MECHANICAL FAULT DIAGNOSIS BASED ON A NEW TIME-FREQUENCY DISTRIBUTION

2003 ◽  
Vol 39 (07) ◽  
pp. 150 ◽  
Author(s):  
Xinqing Wang
1995 ◽  
Vol 14 (4) ◽  
pp. 539-553
Author(s):  
Soo -Chang Pei ◽  
Er -Jung Tsai

Author(s):  
Jian Xu ◽  
Shuiguang Tong ◽  
Feiyun Cong ◽  
Yidong Zhang

There are still some remaining issues for time–frequency distribution application in rolling bearing fault diagnosis, such as noise suppression and resolution improvement. In this paper, we proposed a novel time–frequency correlation matching and reconstruction method to enhance the ability of rolling bearing fault identification. Firstly, we use the optimal simulated bearing fault signal to obtain the matching template through time–frequency distribution. Then, correlation matching operation is conducted between the obtained matching template and the original time–frequency distribution of analyzed signal. Finally, the original time–frequency distribution is reconstructed with the correlation coefficients and matching template using the template reconstruction algorithm. The reconstructed time–frequency distribution has inherited the capability of matching template in noise suppression, and can reveal the fault impulses of interest in a unified scale. The effectiveness of the proposed method has been proved by experimental result.


Author(s):  
Zhinong Li ◽  
Ming Zhu ◽  
Fulei Chu ◽  
Xuping He

Based on the deficiency of fixed-kernel in the traditional time–frequency distribution, which is lack of adaptability, a new adaptive kernel function, which is named as the adaptive radial sinc kernel, is proposed according to design criteria of adaptive optimal kernel. The definition and algorithm of radial sinc kernel are given, and the proposed method is compared with the tradition time–frequency distribution. The simulation results show that the proposed method is superior to the traditional fixed-kernel functions, such as Wigner–Ville distribution, Choi–Williams distribution, cone-kernel distribution and continuous wavelet transform. The adaptive radial sinc kernel can overcome the deficiency of fixed-kernel function in traditional time–frequency distribution, adopt the optimizing method to filter the cross-terms adaptively according to the signal distribution, obtain good time–frequency resolution and has extensive adaptability for an arbitrary signal. Finally, the proposed method has been applied to the fault diagnosis of rolling bearing, and the experiment result shows that the proposed method is very effective.


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