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
Link To Document :
بازگشت