Air gap eccentricity fault is one of the major faults that afflict the life and performance of rotating machines. Eccentricity fault, in the worst case, causes a stator rotor rub. Thus, a condition monitoring scheme to identify eccentricity fault at its initial stage is necessary. The most widely practised air gap monitoring schemes for synchronous machines are expensive and invasive sensors based. This work has focussed on developing an inexpensive, non-invasive, air gap monitoring technique especially for salient pole synchronous machines. Motor current signature analysis has been mostly preferred for the above mentioned purpose. By monitoring the frequency spectrum of the machine’s current, faulty condition can be isolated provided the fault specific frequency components are known beforehand.

The research work, therefore, has developed a specific permeance function using binomial series for salient pole machines that can be used to identify eccentricity specific harmonic components in the line current spectrum. Then by performing the magneto-motive force – specific permeance analysis the characteristic frequency components have been predicted. In order to validate the prediction as well as to identify a trend in the variation of these harmonic components with changing levels of eccentricity, mathematical models of a three phase reluctance synchronous machine and a three phase salient pole synchronous machine based on modified winding function approach have been developed. The models have been made to incorporate static, dynamic and mixed eccentricity conditions of varying severity. Also time stepped finite element based models have been simulated in Maxwell-2D to verify the theoretical predictions. With the help of eccentrically cut bushings, experiments were then conducted in the laboratory to corroborate the proposed eccentricity detection scheme.

It has been observed that non-idealities such as supply time harmonics, machine constructional asymmetry, supply voltage unbalance etc. negatively impact the diagnostic technique. Consequently, a residual estimation based fault detection scheme has been implemented successfully to distinguish eccentricity fault from healthy condition. Moreover, detection logic have been put forth to discriminate the type of eccentricity and to estimate the severity of the fault.