A Novel Fuzzyexpert Diagnosis System of Inner-faults for Three-phase Squirrel Cage Induction Motors

摘要

Three phase induction motors are widely used in industrial production all over the world. Due to high utilization rate, frequent starting and changing load condition, the appearance of failures in induction motors is relatively high. A sudden fault will cause large economic losses. Therefore, the early fault detection becomes very important. During practical operation of three-phase induction motors in industry, the inner faults may occur in their rotor and stator windings. These kinds of faults will make serious influence on the operation of the motor. There is insufficient R&D in the diagnosis system of inner-faults of squirrel cage induction motor. Thus a new research on the fuzzyexpert diagnosis system of inner-faults for three-phase induction motors is presented. The purpose of fault diagnosis is to isolate the cause of a system malfunction in a timely manner. This paper presents a new sequence performing diagnosis of the three-phase induction motors as: sample the fault symptoms, carry the fuzzyexpert forward & backward inference, deduce the fault hypotheses and conclude the fault discrimination. Among them, a novel technique of how to define the various membership functions and the relevant fuzzy sets concerning the uncertainty issues based on the symptoms of motor faults (experimental data), and how to construct the proper inference nets for producing the production rules are explained. Finally, a series of experiments of diagnosing the stator and rotor faults are shown.