航空发动机相似增益扩展卡尔曼滤波研究  

Study on Aero-Engine Similarity Gain Extended Kalman Filter Algorithm

作　　者：任新宇[1] 杨育武 樊思齐[1] 

机构地区：[1]西北工业大学动力与能源学院,陕西西安710072 [2]中航工业西安航空动力控制公司,陕西西安710077

出　　处：《测控技术》2011年第1期52-54,62,共4页Measurement & Control Technology

摘　　要：提出了一种用于估计航空发动机性能参数退化情况的基于相似增益的扩展卡尔曼滤波方法,滤波器由部件级非线性实时模型和卡尔曼滤波增益矩阵组成。增益矩阵在标准大气条件下设计,并通过相似理论将其扩展到全线。与常增益卡尔曼滤波算法相比,该方法具有更好的收敛性和滤波稳定性。系统仿真表明,该方法能够在当前的机载计算机上完成实时运算,仿真结果令人满意。The extended Kalman filter method based on similarity gain to identify the state of deterioration of the engine components is proposed.The filter consists of a nonlinear component level model and a filter gain matrix K.Gain matrix K is a constant matrix design at sea-level static condition,and should be transformed to actual flight condition with similarity correction factors.The hardware is used in the loop simulation facility to test for the onboard model＇s real-time capability.Simulation results show the model completed all operations in an airborne computer real-time and the precision is satisfactory.

关 键 词：航空发动机 相似理论 卡尔曼滤波 增益矩阵 

分 类 号：V233.7[航空宇航科学与技术—航空宇航推进理论与工程]