基于响应面-遗传算法的印制电路板参数识别OA

The Printed Circuit Board Assembly(PCBA)is widely used in aerospace equipment.The necessary prerequisite for analyzing and optimizing the vibration reliability of electronic equipment in aviation equipment is to establish an accurate PCBA finite element model.Aiming at the physical parameters of PCBA finite element model are difficult to obtain through experiments,taking an aircraft electronic equipment PCBA as a case,first through the Central Composite Design(CCD)of the Minimum Run with Resolution V(MRRV).Secondly,the response surface function coefficients are determined according to the least square method and the response surface accuracy test is completed.The multi-objective function of the error between the response value and the modal test results is constructed.Thirdly,the Non-dominated Sorting Genetic Algorithm-Ⅱ(NSGA-Ⅱ)is used for multi-target parameter identification.The identified parameters are substituted into the Abaqus finite element model for simulation analysis.Lastly,the results of modal test are compared with the random vibration test.The results show that the average error of modal frequency is reduced to 2.70%,and the average error of random vibration response is 5.83%,which verified the effectiveness of this method for the identification of PCBA model parameters in airborne vibration environment.