Novel Fault Diagnostic Technology for Aviation General Processing Module

Abstract

Avionics is the brain of a large passenger plane, which involves multi-disciplinary and multi-technology. This paper proposed a novel fault diagnosis method for aviation general processing module. Prognostic and health management (PHM) technology is utilized to master the health status in avionics system, for realizing condition maintenance. Parameter acquisition, feature extraction, failure analysis and system fault location are used to realize fault diagnosis. Four methods include physics of failure (PoF) model, bypass signal detection, functional parameter detection and boundary scan are utilized to analyze the fault principle in avionic general processing module. Use of PoF model can realize single mechanism fault diagnosis. Bypass signals are obtained from measurement data, which include power consumption, ground noise, static and dynamic current. The sampling parameters are obtained from the physical definition, the system state parameters and register monitoring parameters. Boundary scan method can affect the way the circuit works by real-time input transmission measurement. The experiment shows that the PHM technology can accurately diagnose faults.