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Multi-level stator winding failure investigation on the insulation material for industrial induction motor at its incipient stage can achieve tremendous energy savings, minimize maintenance costs, and enhance the operational life. Early detection has the main advantage of preventing motor failure, which gradually leads to catastrophic or complete shutdown. In this paper, the multi-level stator winding failure of an industrial induction motor in the numerical model was designed and implemented using Finite-Element Analysis (FEA). Since multi-level stator winding failure constitutes substantial time and frequency domains, the signature from the motor is analysed employing a time-frequency-based technique using wavelets. Early detection of the multi-level stator winding failures uses signatures from the experimental setup of both healthy and faulty motors by combining both modular and virtual instruments. FEA results were then validated under the same operating conditions using an experimental setup. It has been observed that the results obtained from the FEA are in good agreement with the experimental setup. The frequency component variation in the sensor frequency response for fault conditions at various severity levels suggests multiple frequency bands. When the motor was under the influence of a 50% stator turn-turn fault, a similar frequency band between 700-800 Hz was observed. As a result, the proposed research was accurate, with a correlation factor of 0.96.