Rotor Unbalance Detection in Electrical Induction Motors Using Orbital Analysis

Deterioration in mechanical parts of a motor causes faults that generate vibrations. Those vibrations can be related with a different type of motor fault. In this work, we propose a new computational model for identifying rotor unbalance problems in electrical induction motors. Measured vibrations are preprocessed in order to create orbits which represent characteristic patterns. Those patterns are used in a recognition process using an artificial neural network. Experimental results using vibration signals extracted from real situations show a good performance and effectiveness of the proposed model, providing a new way for recognizing unbalance problems in induction motors.