XU Yang, YANG GuangWu, CHEN KuanYu, et al. FREQUENCY DOMAIN DAMAGE CALCULATION AND EXPERIMENTAL VERIFICATION OF NON-GAUSSIAN EXCITATION BASED ON GMM MODEL (MT)[J]. Journal of Mechanical Strength , 2023,(4):955-961.
XU Yang, YANG GuangWu, CHEN KuanYu, et al. FREQUENCY DOMAIN DAMAGE CALCULATION AND EXPERIMENTAL VERIFICATION OF NON-GAUSSIAN EXCITATION BASED ON GMM MODEL (MT)[J]. Journal of Mechanical Strength , 2023,(4):955-961. DOI: 10.16579/j.issn.1001.9669.2023.04.027.
为了研究非高斯激励的频域计算方法,介绍了高斯混合模型(Gaussian Mixture Model, GMM),通过GMM模型将实测的非高斯激励转换成概率功率谱(Probabilistic Power Spectrum, PPSD),以此将非高斯激励引入频域。运用仿真和GMM-Dirlik模型获得对应的非高斯雨流分布,计算出试件的损伤;同时按照高斯假设,将激励直接转换成功率谱密度(Power Spectral Density, PSD)进行损伤的计算。然后,对试件进行了台架试验,获得了试件的应力响应,通过雨流计数获得应力范围雨流分布,计算出试件的损伤。将试验结果与仿真结果进行对比后发现,GMM-Dirlik模型得出的结果与试验相对误差为10.8%,而高斯假设得到的结果与试验相对误差较大,为45.3%,进一步说明了用高斯假设评估非高斯激励损伤的危险性。最后,对比非高斯激励和高斯分布概率密度函数的区别,解释了实测应力雨流分布在中间应力等级处出现下凹的现象,以及非高斯激励相对于高斯激励损伤变大的原因。
Abstract
In order to study the frequency domain calculation method of non-Gaussian excitation, Gaussian mixture model(GMM) is introduced. The measured non-Gaussian excitation is transformed into probabilistic power spectrum(PPSD) through GMM model, so that the non-Gaussian excitation is introduced into the frequency domain. The corresponding non-Gaussian rain flow distribution is obtained by simulation and GMM-Dirlik model, and the damage of the specimen is calculated. At the same time, according to the Gaussian hypothesis, the excitation is directly converted into PSD for damage calculation. Then, the bench test is carried out to obtain the stress response of the specimen, the rain flow distribution in the stress range is obtained by rain flow counting, and the damage of the specimen is calculated. After comparing the test results with the simulation results, it is found that the relative error between the results obtained by GMM-Dirlik model and the test is 10.8%, while the relative error between the results obtained by Gaussian hypothesis and the test is large, which is 45.3%, which further explains the risk of non-Gaussian excitation damage evaluated by Gaussian hypothesis. Finally, the difference between non-Gaussian excitation and Gaussian distribution probability density function is compared to explain the concave phenomenon of measured stress rain flow distribution at the middle stress level and the reason why the damage of non-Gaussian excitation is larger than that of Gaussian excitation.