Effective combination of motor fault diagnosis techniques

Induction motors are widely used across all the industries and accounts for major source of energy consumption. Inception of faults in motors may reduce its operational efficiency. Over a period of time, the propagation of fault in the motor may leads to the further drop in the efficiency. Various motor fault diagnosis techniques which use current signal, vibration signal and infrared thermography (IRT) to diagnose motor fault prior to its failure are available. Inspite of all these fault diagnosis techniques still failure of induction motor are reported in industries. The main reason is the mismanagement of the available fault diagnosis technique. No single fault diagnosis technique is effective in diagnosing every fault present in the motor. Therefore, a combination of these techniques is required to diagnose fault effectively. This paper proposed an effective combination of two fault diagnosis technique which could diagnose most of motor faults. Fuzzy arithmetic operation is used to identify this effective combination which helps in increasing motor availability and reduces downtime cost.