Research on hydraulic control system fault diagnosis method based on rough set theory

Author(s):  
Rao Hong ◽  
He Yudong ◽  
Chen Lian
2012 ◽  
Vol 170-173 ◽  
pp. 3644-3648
Author(s):  
Chun Fei Yuan ◽  
Jing Cai ◽  
Yi Ming Xu

Modern fault diagnosis system always is a dynamic, flexible and uncertain complicated system, so many fault diagnosis methods are not effective to determine fault causes. Considering that abundant of fault diagnosis cases have been accumulated in daily maintenance work, a fault diagnosis method based on case-based reasoning (CBR) and rough set theory is proposed. Rough set theory is employed to process reduction on attributes and the weighting coefficient of case description attributes. This method makes full use of the advantage of" let the data speak". At last the method is testified by an example, and the result shows it is feasible and effective.


2014 ◽  
Vol 631-632 ◽  
pp. 175-179
Author(s):  
Si Jie Yang ◽  
Jing Hui Li ◽  
Xiao Ni Liu

In order to process the abundant information in fuzzy clustering, one fault diagnosis method was proposed based on Rough Set reduction algorithm and Fuzzy equal relationship clustering. Not only the iteration numbers was reduced in the fuzzy equal relationship matrix, but also the clustering numbers was lower. Then the examples were applied to test its validity.


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