Abstract—Three-phase induction motors are the most-widely used electrical machines and are considered as the workhorses of the industry. About 60% of the electrical power generated is used by induction motors and hence have gained high importance. Their fault-free operation is desired in industrial processes. For this reason, detection of incipient faults has gained significance. Motor current signature analysis is the technique popularly used for the detection of fault in machines. It is non-intrusive and an online method, which analyses the health of the machine through the spectrum monitoring of the stator current. Bearing fault is the most common fault in IM and this paper deals with detection of Bearing fault using Artificial Neural Network (ANN).

Index Terms—Induction motor, MCSA, Bearing fault, ANN

Cite: S M Shashidhara and P Sangameswara Raju, "BEARING FAULT DETECTION OF INDUCTION MOTOR BY ANN METHOD," International Journal of Electrical and Electronic Engineering & Telecommunications, Vol. 3, No. 1, pp. 34-42, January 2014.