Looking past BIT - incipient fault detection and prognostics for avionics system power supplies

摘要

This paper presents an approach to enhancing current avionic system power supply diagnostics with prognostic techniques for improved equipment health management. The approach integrates techniques from engineering disciplines including automated testing, incipient fault detection and classification, fault to failure progression modeling, statistical reliability analysis, and automated reasoning. Novel features extracted from sensed parameters such as power quality, component operating temperature, control loop signature, and efficiency are analyzed using advanced fault detection and damage accumulation algorithms. Intelligent fusion of this diagnostic information with historical component reliability statistics provides a robust health state awareness as the basis for accurate prognostic predictions. Complementary prognostic techniques including analysis of projected operating conditions by physics-based component aging models and system level failure progression models are used to develop predictions of future equipment health. The diagnostic techniques and prognostic models have been demonstrated through accelerated failure testing of switching mode power supplies.