结合不确定度的发动机模型辨识气路诊断

针对航空发动机气路诊断中测量参数个数小于待诊断参数个数的不适定问题，利用了发动机平衡技术，结合非线性的发动机数学模型，并综合考虑了测量参数的不确定度和理论模型部件性能的不确定度，建立了一种结合不确定度的发动机气路故障诊断辨识算法——变分加权最小二乘法，并将该算法应用于某发动机的诊断分析中.结果表明:运用该方法可分析出测量数据和模型计算数据之间的差别，同时，利用所得的故障参数修正量修正原发动机数学模型，使模型计算推力与试验测量推力最大偏差由8.25%减小到1.66%，耗油率最大偏差由6.25%减小到1.50%. 

Pattern recognition with uncertainty for engine gas path diagnosis

For the ill-posed problem in aero-engine gas path diagnosis that the amount of measuring parameters is less than the amount of parameters to be measured, considering the uncertainty of both the measuring parameters and the theoretic model component characteristics, a fault diagnostic algorithm called variational weighed least squares was built using engine counterbalance technology and non-linear mathematical model. The algorithm was applied to an engine fault diagnosis. The results show that the difference between the measurements and calculation results can be obtained with the algorithm. At the same time, through modifying the original mathematical model by employing fault parameter corrections, the thrust maximum deviation between the calculation and measurement decreases from 8.25% to 1.66%, and the maximum deviation of fuel consumption rate from 6.25% to 1.50%.