A FUZZY LOGIC APPROACH TO DIAGNOSE INDUCTION MOTOR FAULTS IN REMOTE SITE BY CELL PHONE

Abstract

Monitoring, fault detection, and diagnosis of electric induction motors are becoming increasingly important in the field of electrical machines as new data-processing techniques and methods for analyzing the motor stator current. Special attention has been devoted to noninvasive methods capable of detecting faults using measured data without requiring motor disassembly and its structural parts. Some enterprises such as Mining, Petroleum and Water and Sewage Treatment process uses induction motor of large power flow, what are installed at remote sites. The electrical and mechanical failures of such motors often disrupt productivity and require maintenance. Currently the containment of maintenance costs, these remote sites work without the presence of a service technician. A fuzzy logic approach may help to diagnose induction motor faults at these sites and to transmit the fault diagnosis (via 3G technology) to maintenance central or a cell phone programmed. The contribution of this paper is the use of fuzzy logic for the automated practical detection of broken bars in induction motors in remote locations without the presence of an experienced technician.