Abstract
Sensors play an important role in the health monitoring and fault diagnosis along the gas path of the turbofan engine. In order to obtain effective and accurate sensors signals in the faults diagnosis of engine gas path components, a new sensor optimization scheme based on combination of the baseline sensor and the additional sensor is proposed. This scheme combines the nonlinear component-level model of engine and Extended Kalman Filter algorithm. In this attribution, the component-level model is used to simulate the real engine, and the optimized sensor scheme is employed and testified under different faults of gas path components. The Square Sum of Estimation Error (SSEE) is obtained to verify the effectiveness of the optimization scheme for fault diagnosis. The results show that the scheme of baseline sensors with pressure sensor of LPT outlet cross — section has the best diagnostic results.
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