Eccentricity Fault Diagnosis of the Induction Motor using the Decision Tree

In signal based fault diagnosis signal processing plays a key role. Signal processing techniques include the time domain, frequency domain and time-frequency area techniques. In this project, eccentricity fault diagnosis of the induction motor using the decision tree and coil voltage is investigated. With respect to diagnosis goal, three strategies can be followed. Isolation of faulty and healthy states, isolation of healthy, dynamic eccentricity and static eccentricity, and isolation of seven states of system (healthy, dynamic 10%, dynamic 30%, dynamic 50%, static 10%, static 30%, static 50%).