地震波双模态时变修正Kanai-Tajimi非平稳随机模型的改进及参数识别
Improvement and Parameter Identification of Bimodal Time Variables Modified by the Kanai-Tajimi Nonstationary Stochastic Model Using Strong Ground Motion Records

在Vlachos等提出的双模态时变修正Kanai-Tajimi功率谱模型及其参数识别方法的基础上，利用杜修力等提出的Kanai-Tajimi功率谱滤波方法并引进遗传算法及二次优化识别技术进行改进，建立地震动时变功率谱的参数模型化方法。通过集集地震波的时变功率谱模型参数识别及模拟地震动算例，验证改进后的双模态时变修正Kanai-Tajimi功率谱模型的可行性和有效性，其方法可运用到重大工程结构抗震分析的设计地震动输入中。
The inversion of ground motion, a strong stochastic process with both amplitude and frequency dual nonstationary characteristics, is very difficult. Thus, finding a nonstationary ground motion modeling method that can simultaneously simulate ground motion characteristics and determine actual ground motion time-varying distribution characteristics has become an important endeavor in ground motion research. A genetic algorithm and quadratic optimization identification technique based on the Kanai-Tajimi power-spectrum filtering method proposed by Du Xiuli et al. are employed to improve the bimodal time-varying modified Kanai-Tajimi power spectral model and parameter identification method proposed by Vlachos et al. Additionally, a method for modeling time-varying power-spectrum parameters for ground motion is proposed. This method is ideal for improving the Kanai-Tajimi spectral model of earthquakes because it satisfies the requirements of high-and low-frequency power spectra by filtering the Kanai-Tajimi spectrum with a series of high-and low-pass filters. The nonstationary ground motion simulation method uses two random variables to accurately capture the second-order statistics of the original stochastic process by Liu Zhangjun, thereby providing an efficient and convenient approach for subsequent verification. The results of a Chi-Chi ground motion example verify that the improved bimodal time-variable Kanai-Tajimi nonstationary stochastic model shows good feasibility and effectiveness. The results of the present research provide an important reference for designing seismic waves during seismic analysis of major engineering structures.