摘要
设计了适用于双轴涡扇发动机健康参数估计的平方根UKF滤波算法,解决了线性卡尔曼滤波器估计结果准确性依赖于线性模型精度;常规UKF算法中由于计算误差及噪声信号影响引起误差协方差矩阵负定而导致滤波结果发散等问题.提出了根据测量残差变化改进滤波收敛速度与稳定性的方法.发动机渐变与突变故障模式下仿真结果表明,平方根UKF估计算法收敛速度快,稳定性强,精度高,是一种有效的发动机气路部件健康参数估计与故障诊断方法.
An algorithm based on square root unscented Kalman filter （SRUKF） was presented to solve the aeroengine health parameter estimation problem. The SRUKF method could be applied to addresses the estimation inaccuracy of linear Kalman filter and the filtering divergence problem caused by error covariance matrix non-positive in general unscented Kalman filter. A method for improving the filtering convergence rate and stability was developed according to the residual vector. The results obtained from gradual and abrupt fault diagnostic simulation show that,SRUKF features rapid convergence,higher stability and accuracy,making it become an efficient estimation and fault diagnosis method for health parame- ters of gas path components in aeroengines.
出处
《航空动力学报》
EI
CAS
CSCD
北大核心
2008年第1期169-173,共5页
Journal of Aerospace Power
关键词
航空
航天推进系统
航空发动机
故障诊断
非线性滤波
平方根UKF
aerospace propulsion system
aeroengine
fault diagnostics
nonlinear filtering
square root unscented Kalman filter （SRUKF）
