New Method for Fault Diagnosis Based on Dempster-shafer Theory

2013 ◽  
Vol 12 (10) ◽  
pp. 2069-2072
Author(s):  
Hong Zhan ◽  
Jiwen Tan
2014 ◽  
Vol 1030-1032 ◽  
pp. 1764-1768 ◽  
Author(s):  
Wei Xiao Xu ◽  
Ji Wen Tan ◽  
Hong Zhan

Aiming at the existing defects of evidence dempster-shafer theory (DST) in dealing with high conflict evidence, we proposed a new method to improve DST. By introducing concept of fuzzy consistent matrix, calculate the weights of factors, and put different sources of evidence into distinguish, and finally cast more than one vote to prevent the phenomenon, the average convergence of evidence. What’s more, the improved DST new method is applied to the rolling bearing fault diagnosis of CNC machine workbench .The test results show that the improved new synthetic formula increases the accuracy of fault diagnosis Ball, the conflict of evidence synthesis results better, to achieve better results.


2015 ◽  
Vol 26 (10) ◽  
pp. 105402 ◽  
Author(s):  
Jie Liu ◽  
Xi Lu ◽  
Yunpeng Li ◽  
Xiaowu Chen ◽  
Yong Deng

Measurement ◽  
2020 ◽  
Vol 165 ◽  
pp. 108129 ◽  
Author(s):  
Xiancheng Ji ◽  
Yan Ren ◽  
Hesheng Tang ◽  
Chong Shi ◽  
Jiawei Xiang

2021 ◽  
Author(s):  
Ias Sri Wahyuni ◽  
Rachid Sabre

In this article, we give a new method of multi-focus fusion images based on Dempster-Shafer theory using local variability (DST-LV). Indeed, the method takes into account the variability of observations of neighbouring pixels at the point studied. At each pixel, the method exploits the quadratic distance between the value of the pixel I (x, y) of the point studied and the value of all pixels which belong to its neighbourhood. Local variability is used to determine the mass function. In this work, two classes of Dempster-Shafer theory are considered: the fuzzy part and the focused part. We show that our method gives the significant and better result by comparing it to other methods.


Author(s):  
C.L. Henderson ◽  
J.M. Soden

Abstract A new method of signature analysis is presented and explained. This method of signature analysis can be based on either experiential knowledge of failure analysis, observed data, or a combination of both. The method can also be used on low numbers of failures or even single failures. It uses the Dempster-Shafer theory to calculate failure mechanism confidence. The model is developed in the paper and an example is given for its use.


2016 ◽  
Vol 346-347 ◽  
pp. 302-317 ◽  
Author(s):  
Kok Chin Chai ◽  
Kai Meng Tay ◽  
Chee Peng Lim

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