Title :
A State Representation for the Diagnosis of a Roller Bearing and Kalman Filtering
Author_Institution :
Lesi Chartres
Abstract :
In this article, the detection of a fault on the inner race of a roller bearing is presented as a problem of optimal estimation of a hidden fault, via measures delivered by a vibration sensor. We propose a linear model for the transmission of a vibratory signal to the sensor´s diaphragm, that we validate with numerical simulations in two situations: with or without a fault. In both cases a Kalman filter is deduced and simulated
Keywords :
Kalman filters; fault diagnosis; rolling bearings; vibrations; Kalman filtering; fault detection; optimal estimation; roller bearing diagnosis; vibration sensor; Equations; Fault detection; Fault diagnosis; Filtering; Kalman filters; Rolling bearings; State estimation; Technological innovation; Vibration measurement; White noise;
Conference_Titel :
Information and Communication Technologies, 2006. ICTTA '06. 2nd
Conference_Location :
Damascus
Print_ISBN :
0-7803-9521-2
DOI :
10.1109/ICTTA.2006.1684688
