DocumentCode
3508852
Title
An on-line monitoring and diagnostic method of rolling element bearing with AI
Author
Shao, Yimin ; Nezu, Kiktto
Author_Institution
Dept. of Mech. Eng., Gunma Univ., Japan
fYear
1995
fDate
26-28 Jul 1995
Firstpage
1543
Lastpage
1548
Abstract
A new concept of the degree of creditability of parameter value variations (DCPV factor) is proposed in this paper to solve problem that on-line monitoring and failure diagnosis of rolling element bearings are affected by monitoring parameter value variations caused by the intrusive vibration signals. Using the factor of the degree of creditability and the basic principle of expert systems, an on-line monitoring and diagnostic method of rolling element bearings with AI is developed. The technique enhances traditional vibration analysis and provides a means of automating the monitoring and diagnosis of a vibrating device
Keywords
computerised monitoring; diagnostic expert systems; fuzzy logic; mechanical engineering; monitoring; degree of creditability; diagnostic method; expert systems; intrusive vibration signals; online monitoring; rolling element bearing; vibrating device; Accelerometers; Artificial intelligence; Computerized monitoring; Condition monitoring; Diagnostic expert systems; Pulleys; Rolling bearings; Surface cracks; Testing; Vibrations;
fLanguage
English
Publisher
ieee
Conference_Titel
SICE '95. Proceedings of the 34th SICE Annual Conference. International Session Papers
Conference_Location
Hokkaido
Print_ISBN
0-7803-2781-0
Type
conf
DOI
10.1109/SICE.1995.526964
Filename
526964
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