Turbocharging is an efficient approach for addressing power reduction and oil consumption increase in aviation piston engines during high-altitude flights.However,a turbocharger significantly increases the complexity ...Turbocharging is an efficient approach for addressing power reduction and oil consumption increase in aviation piston engines during high-altitude flights.However,a turbocharger significantly increases the complexity of a power system,and its considerably complex matching relation with the engine results in a coupling of failure modes.Conventional analytical methods are hard to identify failure-inducing factors.Consequently,safety issues are becoming increasingly prominent.This study focuses on methods for identifying failure-inducing factors.A whole-machine system model is established and validated through experimentation.The response surface method is employed to further abstract the system simulation model to a surrogate model(average error:~3%)in order to reduce the computational cost while ensuring accuracy.On this basis,an improved Correspondence Analysis(CA)-Polar Angle(PA)-based Classification(PAC)is proposed to identify the key factors affecting the failure mode of turbochargers.This identification method is based on the row profile coordinates G varying with the numerical deviations of the key factors,and is capable of effectively identifying the key factors affecting the failure.In a validation example,this method identifies the diameter of the exhaust valve(e_(2))as the primary factor affecting the safety margin for each work boundary.展开更多
基金supported by the Innovation Team of Complex System Safety and Airworthiness of Aeroengine from the Co-Innovation Center for Advanced Aeroengine of Chinafunded by the National Natural Science Foundation of China and the Civil Aviation Administration of China(No.U1833109)。
文摘Turbocharging is an efficient approach for addressing power reduction and oil consumption increase in aviation piston engines during high-altitude flights.However,a turbocharger significantly increases the complexity of a power system,and its considerably complex matching relation with the engine results in a coupling of failure modes.Conventional analytical methods are hard to identify failure-inducing factors.Consequently,safety issues are becoming increasingly prominent.This study focuses on methods for identifying failure-inducing factors.A whole-machine system model is established and validated through experimentation.The response surface method is employed to further abstract the system simulation model to a surrogate model(average error:~3%)in order to reduce the computational cost while ensuring accuracy.On this basis,an improved Correspondence Analysis(CA)-Polar Angle(PA)-based Classification(PAC)is proposed to identify the key factors affecting the failure mode of turbochargers.This identification method is based on the row profile coordinates G varying with the numerical deviations of the key factors,and is capable of effectively identifying the key factors affecting the failure.In a validation example,this method identifies the diameter of the exhaust valve(e_(2))as the primary factor affecting the safety margin for each work boundary.
