Aircraft turbofan engine health estimation using constrained Kalman filtering

被引:65
|
作者
Simon, D
Simon, DL
机构
[1] Cleveland State Univ, Dept Elect Engn, Cleveland, OH 44115 USA
[2] NASA, Glenn Res Ctr, USA, Res Lab, Cleveland, OH 44138 USA
来源
JOURNAL OF ENGINEERING FOR GAS TURBINES AND POWER-TRANSACTIONS OF THE ASME | 2005年 / 127卷 / 02期
关键词
D O I
10.1115/1.1789153
中图分类号
TH [机械、仪表工业];
学科分类号
0802 ;
摘要
Kalman filters are often used to estimate the state variables of a dynamic system. However in the application of Kalman filters some known signal information is often either ignored or dealt with heuristically. For instance, state-variable constraints (which may be based on physical considerations) are often neglected because they do not fit easily into the structure of the Kalman filter This paper develops an analytic method of incorporating state-variable inequality constraints in the Kalman filter. The resultant filter is a combination of a standard Kalman filter and a quadratic programming problem. The incorporation of state-variable constraints increases the computational effort of the filter but significantly improves its estimation accuracy. The improvement is proven theoretically and shown via simulation results obtained from application to a turbofan engine model. This model contains 16 state variables, 12 measurements, and 8 component health parameters. It is shown that the new algorithms provide improved performance in this example over unconstrained Kalman filtering.
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页码:323 / 328
页数:6
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