Hence detection and diagnosis and diagnosis of such faults is very essential for protection of induction motors against failures and permanent damages. In recent years, the monitoring and fault detection of electrical motors have moved to artificial intelligent techniques from traditional methods.
Such techniques require a minimum of intelligent configuration, since no detailed analysis of fault mechanism is necessary and no modeling required. The healthy state of Induction motor are indicated by associated current and voltage parameters.
And therefore this Fuzzy approach monitors current and voltage for diagnosis under different operating condition. In contrast to other conventional methods, this project would reduce time and energy required. This method can be extended to any type of electrical motors, big or small.
This project describes the application of fuzzy logic approach to the diagnosis of induction motor. A fuzzy logic–based system allows the transformation of heuristic terms into numerical values via fuzzy rules and membership functions.
When conducting fault diagnosis, several situations may occur in which an object is not obviously “good” or “bad”, but may fall in between. Considering that the interpretation of the condition of the induction motor as a fuzzy concept, fuzzy logic – based diagnosis approach can be developed which enables decision making to be made based on vague information.