Robust Fault Diagnosis of Aircraft Induction Motor: Artificial Intillegent Technique Based Approach


  • Wathiq R. Abed, Muhanad A. Ahmed


Induction Motor (IM) are commonly used electrical drives in industry due to their excellent characteristics such as simple design Higher reliability, low cost and high performance. As a result, their reliability deficiency has gained significant attention in recent decades due to poor performance and high maintenance costs. This paper introduces a new approach to diagnosing different winding fault under different load and speed conditions. Simulink / Matlab was present to an analytical model for inter-turn fault diagnosisof the IM  in a normal and abnormal situation. A method of extraction of features based on the Principle Component Analysis ( PCA) was proposed to reduce computational complexity. The extracted function was then used to train the neural network ( NN). NN has been introduced as the fault classifier. The findings obtained from the simulation demonstrate the capacity of the current system to successfully diagnose different types of faults.

Keywords: Aircraft,  Fault Diagnosis, Induction Motor, feature extraction, Neural Network