分组量子遗传算法在某翻转式弧形门水闸地基土层力学参数反演中的应用

Application of Classified Quantum Genetic Algorithm in Mechanical Parameters Inversion of Foundation for Switching Curved-gate Sluice

复杂运行条件下水闸的材料力学参数随着服役时间的增长往往会发生变化,因而利用现场原型监测资料对水闸材料力学参数进行实时反演,对掌握水闸整体安全工作性态具有重要价值。基于分组量子遗传算法建立水闸地基土层力学参数有限元联合反演模型,通过Matlab编程建立有限元软件调用接口,利用工程实测值与有限元计算值确立误差适应度函数,并通过分组量子遗传算法进行智能寻优,实现水闸地基土层力学参数反演。实例应用表明,该方法反演精度及运行速度均高于传统遗传算法,具有一定的实践应用价值。

The mechanical parameters of the sluice under complex operating conditions would change with the growth of service time.So,mechanical parameters inversion of sluice based on-site observations would be of great value for realtime control of the sluice security state.The combined inversion model of sluice foundation soil mechanics parameter was established based on the classified quantum genetic algorithm.The interface to call for the results of finite element software is established through Matlab and the difference between the measured value and the finite element calculation results is adopted as the fitness function.The reversion calculation of the sluice foundation mechanical parameters is optimized by using the intelligent classified genetic algorithm.It is proved that the proposed algorithm has better accuracy and higher convergence speed than traditional genetic algorithm,which is of practical value.