1. 兰州交通大学机电工程学院
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孙永朋, 彭珍瑞, 白钰. 基于Kriging模型和小波包能量谱的随机模型修正[J]. 机械强度, 2023,(2):255-261.
SUN YongPeng, PENG ZhenRui, BAI Yu. STOCHASTIC MODEL UPDATING BASED ON THE KRIGING MODEL AND WAVELET PACKET ENERGY SPECTRUM (MT)[J]. Journal of Mechanical Strength , 2023,(2):255-261.
孙永朋, 彭珍瑞, 白钰. 基于Kriging模型和小波包能量谱的随机模型修正[J]. 机械强度, 2023,(2):255-261. DOI: 10.16579/j.issn.1001.9669.2023.02.001.
SUN YongPeng, PENG ZhenRui, BAI Yu. STOCHASTIC MODEL UPDATING BASED ON THE KRIGING MODEL AND WAVELET PACKET ENERGY SPECTRUM (MT)[J]. Journal of Mechanical Strength , 2023,(2):255-261. DOI: 10.16579/j.issn.1001.9669.2023.02.001.
针对随机模型修正精度和效率低的问题,提出一种基于Kriging模型和小波包能量谱的随机有限元模型修正方法。首先,假设模型待修正参数和响应特征均服从正态分布,将不确定性的模型修正转化为均值和标准差的修正;其次,将待修正参数作为Kriging模型输入,加速度频响函数经过小波包分解后提取的结点能量作为输出,引入政治优化算法优化相关系数以构造Kriging模型;然后,将最小化试验响应与预测响应之差的绝对值作为修正均值的目标函数,最小化交叉熵作为修正标准差的目标函数,通过政治优化算法先后修正参数均值和标准差;最后,以空间桁架结构为例,选取弹性模量和密度为待修正参数验证该方法的可行性。结果表明,所提方法能够有效地修正结构参数均值和标准差,修正后的参数均值、标准差的误差分别低于0.1%、3.5%。
Aiming at the low accuracy and efficiency of stochastic model updating, a stochastic finite element model updating method based on the Kriging model and wavelet packet energy spectrum was proposed. Firstly, assume that the parameters and response characteristics of the model to be updated obey normal distributions, the uncertainty model updating was transformed into the updating of mean and standard deviation. Secondly, the parameters to be updated were taken as inputs of Kriging model, the node energies extracted by the acceleration frequency response function after wavelet packet decomposition were taken as the outputs, the political optimizer algorithm was introduced to optimize the correlation coefficient to construct Kriging model. Then, minimize the absolute value of the difference between the test response and the predicted response as the objective function for updating mean, and minimize the cross entropy as the objective function for updating standard deviation, and updated the parameters mean and standard deviation through the political optimizer algorithm. Finally, taking a space truss structure as the example, the elastic modulus and density were selected as the parameters to be updated to verify the feasibility of the proposed method. The results show that the proposed method can effectively update the mean and standard deviation of structural parameters, and errors of the updated mean and standard deviation are less than 0.1% and 3.5%, respectively.
模型修正加速度频响函数交叉熵小波包能量谱Kriging模型
Model updatingAcceleration frequency response functionCross entropyWavelet packet energy spectrumKriging model
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