基于遗传算法的爆炸冲击荷载参数识别方法

Parameter Identification Procedures of Explosion Shock Loading Based on Genetic Algorithm

基于改进的遗传算法 ,建立了根据测试系统动力响应观测数据反演爆炸冲击荷载参数的数值方法。遗传算法为解决反问题的不适定性提供了强有力的手段。数值模拟结果表明 ,所提出的爆炸冲击荷载参数随机反演方法具有全局搜索能力 ,并且具有良好的抗观测噪音能力。当测试系统的观测相对误差为 10 %时 ,参数反演结果的误差小于 8% ,所建立的参数反演方法具有良好的鲁棒性。

Based on genetic algorithm, a numerical computation procedure is presented to identify the parameters of the explosion shock loading. The genetic algorithm provided a powerful method for solving ill-posedness of inverse problem. The numerical simulation results show that the proposed inversion algorithm is able to get global minimization, and to prevent the measurement noises. The maximum relative error of inversion results is less than 8% when the measurement error of testing system is 10%. The proposed inversion algorithm is robust.