Abstract

Combining a simplified on-board turbo-shaft model with sensor fault diagnostic logic, a model-based sensor fault diagnosis method is proposed. The existing fault diagnosis method for turbo-shaft engine key sensors is mainly based on a double redundancies technique, and this can't be satisfied in some occasions as lack of judgment. The simplified on-board model provides the analytical third channel against which the dual channel measurements are compared, while the hardware redundancy will increase the structure complexity and weight. The simplified turbo-shaft model contains the gas generator model and the power turbine model with loads, this is built up via dynamic parameters method. Sensor fault detection, diagnosis (FDD) logic is designed, and two types of sensor failures, such as the step faults and the drift faults, are simulated. When the discrepancy among the triplex channels exceeds a tolerance level, the fault diagnosis logic determines the cause of the difference. Through this approach, the sensor fault diagnosis system achieves the objectives of anomaly detection, sensor fault diagnosis and redundancy recovery. Finally, experiments on this method are carried out on a turbo-shaft engine, and two types of faults under different channel combinations are presented. The experimental results show that the proposed method for sensor fault diagnostics is efficient.

Highlights

  • With ever-increasing demands being placed on modern aero-engine control systems, the number of control variables and sensors is increasing [1]

  • Most aircraft engines have been enhanced by equipping the engines with a dual channel full authority digital electronic control (FADEC)

  • The sensor FDD system based on a simplified on-board model described in this paper is proposed and developed to diagnose turbo-shaft engine faults on-line

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Summary

Introduction

With ever-increasing demands being placed on modern aero-engine control systems, the number of control variables and sensors is increasing [1]. The fault-tolerant control and health management of aero-engines depend on accurate and reliable sensor readings, while most sensors work in the harsh environment of high temperature and strong vibration [2,3]. Most aircraft engines have been enhanced by equipping the engines with a dual channel full authority digital electronic control (FADEC). Sensor fault diagnosis and isolation (FDI) plays a key role in enhancing safety, reliability and reducing the operating cost of aircraft propulsion systems. Wallhagen and Arpasi proposed using analytical redundancy sensor technology to improve the reliability of the engine control system in 1974 [6].

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