Field Data Evaluation and Continuous Health Assessment of Critical Avionics Subsystem Degradation

Abstract

Effectively utilizing existing on-board and atwing data that encompasses environmental, built-in-test (BIT), vibration, and maintenance test results, can realize improved maintenance, survivability and critical failure rates via the identification of degrading components prior to critical failure. The authors have developed software to show the feasibility of onboard and at-wing prognostics using field data from an Army aircraft platform as a multifaceted case study for predicting and diagnosing the health of a mission-critical targeting subsystem.

A Framework for Health State Evaluation of the Complex Mechanical System With its Occurrence Probability of Failure Mode

“…Some scholars have carried out a series of research on the theory and technology of equipment health assessment in the fields of electricity, aviation and nuclear power. Dussault et al [4], applied intelligent reasoning model to evaluate the health state of critical airborne equipment by carrying out the airborne sensor data and maintenance test data. A three level health assessment mode, including, engine layer, aircraft layer and base layer, was summed up by Simon [5], for aircraft engines based on engine vibration data.…”