ABSTRACT
This chapter describes simple linear circuit theory based mathematical models used to predict electrical machine faults. Fault detection implies a two-valued outcome depending upon the normal or abnormal operating characteristics of a system. Fault diagnosis is the process that actually decides the cause, nature, and location of a fault. Knowledge-based methods usually depend upon qualitative process structure, functions, and qualitative models to predict fault. Model-based techniques use analytical models of the process to generate “normal outputs” that are compared with the actual process outputs to generate “residuals” that are ultimately used for fault detection. The dynamic eccentricity faults for a synchronous machine can be modeled in the same line as an induction motor. The modeling of synchronous machine is similar to an induction machine, except for the fact that the damper bars exist only on the pole faces of the machine and the air-gap or inverse air-gap function has saliency.
