Book excerpt: Induction motors are considered to be the work horse in all types of today's industries. In all mechanical applications, using an induction motor is considered to be the preferable, if not the optimum selection. Their failures, on the other hand, cause an interruption equal to their volume of dependency in any plant. This has initiated different maintenance programs that can extend equipment's life time and reduce sudden equipment failure. The down time that is mandated by conventional maintenance methods is no longer acceptable with tight industrial competition. Condition Monitoring using Motor Current Signature Analysis (MCSA) is the demanding methods that can significantly reduce unscheduled downtime and enable extended motor life. The potential of this method is very high especially for mechanical failure. The frequencies of components that reveal existence of any bearing or rotor-bars related faults are well defined. For other fault sources (e.g. Windings, Insulation) the analysis findings are not yet mature enough and there are uncertainties that make it less attractive. The research of this thesis looks at MCSA as a means to detect failure in stator windings of squirrel-cage induction machines. The approach in this thesis is to run the motors under various stator abnormality conditions and study the behavior of the frequency spectrum to correlate the changes that will appear due to specific faults. Different faults were simulated on two different motors (5 hp, 100 hp). The two machines were operated at normal operating condition and the indicator of stator abnormalities in the current spectrum was identified. The effect of loading on those components is one of the new aspects that are rarely mentioned in previous researches in the field of motor diagnostics.