Sensor Selection Optimization for Aircraft Gas Turbine Engine Health Estimation
نویسندگان
چکیده
Sensor selection optimization can lead to significant improvements in the controllability and observability of a dynamic system. The aim of this research is to investigate optimal or alternate measurement sets for aircraft gas turbine engine health parameter estimation. A brute force search for the best sensor set is too computationally expensive. Therefore, a Monte Carlo approach is used to perform a probabilistic search for a near-optimal sensor set. The health of aircraft gas turbine engines can be estimated using fewer sensors while still obtaining an acceptable estimation error covariance, thereby minimizing the financial cost of the sensor set.
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