A Signal Based Fault Detection for the Engine Crankshaft Faults of the FAR23 Aircraft

摘要

This paper presents a fault detection algorithm for the engine crankshaft faults of the FAR23 aircraft using a vibration signal data. The vibration signal data is acquired and processed to obtain a monitoring of the engine crankshaft. The paper describes in detail the approach of the vibration signal data followed to build up normal and fault models, such as, unbalance, shaft friction and mechanical looseness. This paper proposed fault detection algorithm is a plausible check. The plausible check effectively performs fault detection by generating threshold, which is applied aircraft mission profile, and analysis and algorithm design in the frequency domain after processing the fast fourier transform (FFT) of the vibration. The simulation model of the FAR23 aircraft engine is developed. Validity of developed fault detection algorithm is presented by the simulation and analysis results.