基于遗传算法与评估模型的飞行载荷实测研究

Flight Load Measurement Based on Genetic Algorithm and Evaluating Model

为了得到飞行载荷实测所需的最优载荷方程,建立了可表征载荷方程数学意义和物理意义的评估模型,与遗传算法(GA)结合,以载荷方程评估驱动载荷方程建立,形成一种新的载荷方程建立方法——EMGA。通过建立某机翼根部剪力方程,比较了穷尽搜索(ES)法、传统GA和EMGA所建载荷方程的评估模型参数。最后将3种方法建立的方程用于飞行载荷实测。结果发现:和其他两种方法比较,本文提出的EMGA可得到最优的载荷方程;EMGA测得的飞行载荷分散性小,最优载荷方程的测量结果可作为最终的飞行载荷。

To obtain the optimum load equation for flight load measurement,load-equation-evaluating model is constructed which can represent the math and physics meanings of load equation.Based on the above model and genetic algorithm（GA）,a new method of building load equation—EMGA is proposed by the evaluation of load equation driving the building of load equation.Exhaust research（ES）method,traditional GA and EMGA are used to build the shear equations of certain wing root,where the evaluating parameters of load equations obtained with three methods are compared.Moreover,those built equations with the three methods are applied to measure flight load.The results show that the EMGA can obtain the optimum load equation;the dispersion level of flight load using EMGA is lower than those using ES method and GA,and the measured result using the optimum load equation is regarded as the final measured flight load.