Advanced Electrical Signature Analysis of Aircraft Electrical Generators

The electrical and mechanical failures (such as bearing and winding failures) combine to cause premature failures of the generators, which become a flight safety issue forcing the crew to land as soon as practical. Currently, diagnostic / prognostic technologies are not implemented for aircraft generators where repairs are time consuming and its costs are high. This paper presents the development of feature extraction and diagnostic algorithms to ultimately 1) differentiate between these failure modes and normal aircraft operational modes; and 2) determine the degree of damage of a generator. Electrical signature analysis based features were developed to distinguish between healthy and degraded generators while taking into account their operating conditions. The diagnostic algorithms were developed to have a high fault / high-hour detection rate along with a low false alarm rate. The feature extraction and diagnostic algorithms were evaluated against P-3 generator data (phase voltages / currents) collected at various loads and operating line frequencies for healthy, low-hour and high-hour generators. The results show that the electrical signature analysis of the generator's phase voltage(s) can be used to detect and track its health.