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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
引用本文:钟庭,陈辉国,刘国粹,任俊儒. 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[J]. 地震工程学报, 2017, 39(1): 72-79
作者姓名:钟庭  陈辉国  刘国粹  任俊儒
作者单位:后勤工程学院军事土木工程系, 重庆 401311,后勤工程学院军事土木工程系, 重庆 401311,后勤工程学院军事土木工程系, 重庆 401311,后勤工程学院军事土木工程系, 重庆 401311
基金项目:国家自然科学基金项目(51478068)
摘    要: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。

关 键 词:地震动  时变功率谱  参数识别  双模态  遗传算法  二次优化
收稿时间:2016-09-14

Improvement and Parameter Identification of Bimodal Time Variables Modified by the Kanai-Tajimi Nonstationary Stochastic Model Using Strong Ground Motion Records
ZHONG Ting,CHEN Hui-guo,LIU Guo-cui and REN Jun-ru. Improvement and Parameter Identification of Bimodal Time Variables Modified by the Kanai-Tajimi Nonstationary Stochastic Model Using Strong Ground Motion Records[J]. China Earthguake Engineering Journal, 2017, 39(1): 72-79
Authors:ZHONG Ting  CHEN Hui-guo  LIU Guo-cui  REN Jun-ru
Affiliation:Department of Civil engineering, Logistical Engineering University, Chongqing 401311, China,Department of Civil engineering, Logistical Engineering University, Chongqing 401311, China,Department of Civil engineering, Logistical Engineering University, Chongqing 401311, China and Department of Civil engineering, Logistical Engineering University, Chongqing 401311, China
Abstract: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.
Keywords:ground motion  time-dependent power spectral density  parameter identification  bimodal  genetic algorithm  quadratic optimization
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