Research On Fault Diagnosis Of Aero-engine Digital Control System And Its Simulation Verification

Sensors and actuators failure diagnosis of aero-engine digital control system is studied, and the problems of engine modeling, control system design and fault diagnostic logic are dealt with in this paper. A new method describing the gas turbine performance model in case of lacking of component characteristic is presented based on similarity theory. Adaptive model based on component characteristic tracking was introduced to resolve the problem of model unfitting. A turbofan engine model is developed to illustrate the real time performance and the precision on the hardware platform. An adaptive speed control method combining the PID and single cell artificial neural network was proposed. The controller is realized with an EEC based on DSP and CAN Bus. The aeroengine sensor and actuator failure detection, isolation and accommodation system based on extended Kalman filter for a digital control system is developed, and a strategy to adapt the component characteristic using multivariable optimization is proposed. Both algorithms are verified by simulaton with fault diagnosing computer in loop. A novel method based on pattern recognition techniques is proposed. If a measurement set is fed to an adaptive performance analysis algorithm, a set of component performance modification factors(fault parameters) is produced, from which sensor faults patterns can be recognized.