采用遗传算法对压力脉动过程中气泡模型参数的辨识

Parameter identification of gas bubble model in pressure pulsations using genetic algorithms

流动液体中的压力变化会引起气泡和气穴的产生及破灭,而气泡和气穴又会对液体的流动产生影响及压力变化.为了合理预测流控系统瞬态压力脉动过程中气泡和气穴的体积变化及其对脉动传播过程的影响,基于气泡溶解和析出的物理过程,建立了压力脉动过程中气泡和气穴产生及破灭的数学模型,并提出采用遗传算法对气泡模型中初始气泡体积、气体溶解和析出时间常数进行参数辨识.以一段液压油管路为研究对象,对管路中伴随气泡和气穴的瞬态压力脉动过程进行仿真及实验研究.利用仿真及实验结果,验证了采用遗传算法对气泡模型进行参数辨识的可行性.

Pressure changes in the flowing fluid result in the growth and collapse of gas bubbles and cavitation,which affects the fluid flowing and pressure.In order to predict gas bubble and cavitation volume change during the pressure pulsations in fluid control system and their effects on the pulsations,a mathematical model of gas bubble and cavitation is studied based on gas bubble resolving and releasing physical processes.The method using genetic algorithms（GAs） in parameter identification for the gas bubble model is presented,including the parameters of initial gas bubble volume,gas resolving time constant and releasing time constant.An example of pressure transients accompanying gas bubble and cavitation inside the hydraulic pipeline is simulated and tested.According to the simulation and experimental results,the feasibility of parameter identification for gas bubble model using GAs is verified.