DocumentCode
1609199
Title
Intelligent Fault Diagnosis of Rotating Machinery Based on Grey Similar Relation Degree
Author
Xiong, Wei ; Su, Yanping ; Zhou, Yanjie ; Wang, Hongjun ; Zhang, Wenbin
Author_Institution
Eng. Coll., Honghe Univ., Mengzi, China
fYear
2012
Firstpage
335
Lastpage
337
Abstract
After deeply studying the relationship between reason and symptom of the fault, a novel intelligent fault diagnosis method was proposed based on grey similar relation degree. Firstly, the definition of grey relation degree was introduced. Secondly, on the base of analyzing the defects existed in the grey relation degree, the definition of grey similar relation degree was introduced. Thirdly, the symptom set and standard fault set had been established based on the known knowledge, experience and fault examples. Finally, the grey similar relation degree was used to describe the similarity between the faults and symptoms. Even the fault information was imperfect and the fault mechanism was not clear, the results of diagnosis would be more correct than before. The practical results show that this approach is quite efficient and intelligent. It´s suitable for on-line monitoring and diagnosis of rotating machinery.
Keywords
fault diagnosis; grey systems; matrix algebra; set theory; turbomachinery; fault mechanism; fault reason; fault symptom; grey similar relation degree; intelligent fault diagnosis; rotating machinery; standard fault set; symptom set; Educational institutions; Fault diagnosis; Industrial control; Machinery; Mathematical model; Standards; Vectors; grey similar relation degree; intelligent fault diagnosis; rotating machinery; standard fault set;
fLanguage
English
Publisher
ieee
Conference_Titel
Industrial Control and Electronics Engineering (ICICEE), 2012 International Conference on
Conference_Location
Xi´an
Print_ISBN
978-1-4673-1450-3
Type
conf
DOI
10.1109/ICICEE.2012.95
Filename
6322384
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