Abstract: This paper presents a novel method of detection of inter turn shorts based on k means clustering technique. The percentage of inter turn shorts are classified using SVM (Support vector machines). Switched reluctance motors are very popular in these days, because of ease in manufacturing and operation. Though an electronic circuit can detect the faults like open and short, interturn short classification cannot be done effectively with electronics circuitry. More over an intelligent method can easily identify the fault and classify and hence the root cause of the fault may be guessed and rectified using this method of classification. The information used to include this intelligence in the system are just flux waveforms. Inter turn shorts are very critical for a long run operation of the motor. More over, the early detection minimizes the faulty operation time and ensures the plant stability and saves the life of motor too. Hence a system to detect the inter turn faults under a simulation model has been proposed in this paper.