μ-analysis control adaptation for online stator and rotor fault diagnosis in induction machines

Induction machines are critical components in several industrial processes and are frequently integrated in commercially available equipments. The reliability of an induction motor is of great Importance in industrial as well as commercial, aerospace and military applications. in This paper two kinds of induction motor faults, stator short circuit and broken rotor bar fault, are investigated. The model used is the one developed by [14]. The proposed strategy consists in developing an observer based on μ analysis Control theory, characterized by robustness against model mismatches and disturbances, followed by a sliding mode estimator. The performance index, the parameter that permit to differentiate between faults and disturbances or noise, for the μ observer followed by the sliding mode estimator is amplitude and frequency. Simulations with nonlinear Machine model were carried out which demonstrated the effectiveness of the proposed algorithm. Moreover, μ analysis observer and sliding estimator exhibited robustness against unmodeled dynamics simulated by multiplicative uncertainty and significant rejection of disturbances and noise-effects attenuation which make the proposed strategy adequately close to the conditions of the real physical system.