Measurement Parameter Selection on Adaptive Cycle Engine Gas Path Fault Diagnosis

Abstract Adaptive cycle engine has extraordinary performance in overall range. There is little public research on gas path fault diagnosis of adaptive cycle engine. The increased rotating components and variable mechanisms increase the diagnosis difficulty of adaptive cycle engine. Therefore, analysis mainly focused on how to simplify the fault modes and choose suitable measurement parameters. A linear fault diagnosis method based on least square algorithm was put forward to calculate more accuracy influence coefficient matrix, which can perform sensitivity and correlation analysis to find and identify similar faults. Suitable measurement parameters were chosen by calculating least square estimation bias. And seventeen measurement parameters are finally chosen to diagnose gas path fault of adaptive cycle engine. Choosing suitable measurement parameters can diagnose engine faults correctly which can reduce fuel consumption caused by efficiency degradation.