Mechanics & Industry
Volume 15, Number 6, 2014
|Page(s)||477 - 485|
|Published online||01 September 2014|
Automation of fault diagnosis of bearing by application of fuzzy inference system (FIS)
Laboratory of Applied Precision Mechanics (LMPA), Institute of
Optics and Precision Mechanics, Setif-1 University, 19000
a Corresponding author: firstname.lastname@example.org
Received: 7 January 2014
Accepted: 15 May 2014
This work deals with the application of the fuzzy logic to automate diagnosis of bearing defects in rotating machines based on vibration signals. The classification tool used is a fuzzy inference system (FIS) of Mamdani type. The vector form of input contains parameters extracted from the signals collected from the test bench studied. The output vector contains the classes for the different operating modes of the experimental study. The results show that; pretreatment data (filtering, decimation,...), the choice of parameters of fuzzy inference system (input variables and output, types and parameters of membership functions associated with different input and output variables of the system, the generation of fuzzy inference rules,...) are of major importance for the performance of fuzzy inference system used as a tool for fault diagnosis of rotating machinery.
Key words: Rotating machines / fuzzy logic / fuzzy inference / Fault diagnosis / signal processing
© AFM, EDP Sciences 2014
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