Fault diagnosis of VSI fed induction motor drive using fuzzy logic approach

Monitoring the condition of induction motors is becoming highly important in various industries. There are many more condition monitoring methods including thermal monitoring, vibration monitoring,chemical monitoring and acoustic emission monitoring. But all monitoring methods require costlier sensors or specialized tools whereas current monitoring methods do not require additional sensors. This is because of electrical quantities associated with the electrical motors such as current and voltage are measured by using current and potential transformers that are installed always as a part of protection scheme. The output point of view current monitoring is non-interfering and implemented in the motor control center remotely from the motors being monitored. The present work intends the current monitoring method is applied to detect the various types of faults in induction motor such as electrically related faults. Knowledge based fuzzy logic approach helps in diagnosing the induction motor faults. Actually, fuzzy logic is just like a human intelligent processes and natural language enabling decisions to be made based on obscure information. Therefore, current work enforces fuzzy logic to induction motor fault spotting and resolving. The motor condition is identified by using linguistic variables. Fault condition is diagnosed based on the current amplitude in addition to the knowledge is expressed in membership function and fuzzy rules. The model is designed in MATLAB/SIMULINK with the data obtained under both healthy and different faulty conditions.