In this work, Self Organizing Map (SOM) is used in order to detect and classify the broken rotor bars and misalignment type mechanical faults that often occur in induction motors which are widely used in industry. The feature vector samples are extracted from the sampled line current of motors with fault and healthy one. These samples are the poles of the AR model which is obtained from the spe...

In this paper, we propose an adaptive statistical time-frequency method to detect broken bars using digital torque estimation. The key idea in the proposed method is to transform motor current into a time-frequency spectrum to capture the time variation of the frequency components and to analyze the spectrum statistically to distinguish fault conditions from the normal operating conditions of t...

In the motor current signal, characteristic frequency of broken rotor bar (BRB) fault is modulated by supply and it decreases with decrease load, resulting to be easily buried under light load conditions. Teager-Kaiser energy operator (TKEO) has shown better performance detect BRB faults than classical methods, such as envelope analysis spectral analysis. However, original definition TKEO leads...