Title :
A fuzzy-statistical reasoning model for bearings fault diagnosis
Author :
Stefanoiu, Dan ; Ionescu, Florin
Author_Institution :
Fac. of Mech. Eng., Univ. of Appl. Sci., Konstanz, Germany
Abstract :
When searching for faults threatening a system, the human expert sometimes performs an amazingly accurate analysis of available information, eventually by only using some elementary statistics. Automating the reasoning mechanisms founding such an analysis is, in general, a difficult attempt, but also a possible one, in some cases. The paper aims to introduce a nonconventional method of bearings faults diagnosis, based upon some statistical and fuzzy concepts.
Keywords :
entropy; fault diagnosis; fuzzy logic; inference mechanisms; pattern classification; vibration measurement; bearings fault diagnosis; fuzzy concepts; fuzzy entropy; fuzzy relations; fuzzy-statistical reasoning model; similarity defect classes; spectral statistics; statistical concepts; transitive closure; Encoding; Entropy; Fault detection; Fault diagnosis; Filters; Machinery; Mechanical engineering; Signal to noise ratio; Vibrations; Working environment noise;
Conference_Titel :
Systems, Man and Cybernetics, 2002 IEEE International Conference on
Print_ISBN :
0-7803-7437-1
DOI :
10.1109/ICSMC.2002.1175747
