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基于PCA及PSO智能算法的地震动合成方法——以中国西部中强地震为例 被引量:6

A METHOD TO SIMULATE GROUND MOTION BASED ON PCA AND PSO INTELLIGENT ALGORITHMS——A CASE STUDY OF MODERATE MAGNITUDE EARTHQUAKES IN WESTERN CHINA
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摘要 地震动数值模拟方法可为地震危险性评估和结构抗震设计和评估提供地震输入,但是由于地震动模拟参数的不确定性以及模拟技术的局限性,模拟的地震动与目标地区的实际地震动特征可能存在较大差异。随着区域强震观测数据的增多,应考虑将目标区域的实测地震动特征融合到模拟的地震动中,以体现该区域地震动的特征。但是目前尚无成熟、合理的基于目标地区实际地震动合成设计地震动的方法。为了解决此问题,该文采用机器学习中的智能算法结合区域实际观测记录合成地震动时程。基于主成分分析算法从庞大的目标区域地震动数据库中提取表征本区域地震动特征的母波,采用合理的地震动模型构建区域地震动目标谱,再应用粒子群算法快速求解地震动的母波组合系数,使加权得到的反应谱与目标谱匹配,最终使得合成的地震动既满足目标谱的频谱特征、又符合本地实际地震动的时频特征。基于该文提出的方法,以中国西部地区的强震数据为基础,验证了方法的可行性和有效性,为考虑区域差异特征的地震动合成提供了新的思路和方法。 The numerical simulation method of ground motion can provide ground motion input for seismic hazard analysis and seismic design of structures. Due to the uncertainties associated with ground motion simulation parameters and the limitations of simulation technology, the simulated ground motions may be quite different from the actual ground motions of the target area. With the increased number of observed regional strong ground motions, it is meaningful to integrate the measured ground motion characteristics into the simulated ground motions to reflect the local characteristics of ground motion. But at present, there is no synthetic ground motion method considering the characteristics of ground motion in the target area. To solve this problem, the ground motion time history is synthesized by machine learning method combined with the actual observed ground motion in the target region. The principal component analysis algorithm is applied to extract the mother waves which represent the characteristics of the ground motion from the huge target ground motion database;the reasonable prediction equation is selected to predict the response spectrum;then the improved particle swarm optimization algorithm is applied to quickly solve the combination coefficient of the mother waves of the ground motion. Thus, the weighted new response spectrum matches that from the prediction equation, and the synthetic time history of ground motion not only meets the results of seismic hazard analysis, but also conforms to the characteristics of the local ground motion. Based on the method proposed in this paper, the feasibility and effectiveness of the method are verified by using the strong motions in Sichuan of China, which provides a new idea and method for the synthesis of ground motions considering the characteristics of regional ground motions.
作者 胡进军 张辉 靳超越 王中伟 胡磊 HU Jin-jun;ZHANG Hui;JIN Chao-yue;WANG Zhong-wei;HU Lei(Key Laboratory of Earthquake Engineering and Engineering Vibration,Institute of Engineering Mechanics,China Earthquake Administration,Harbin,Heilongjiang 150080,China)
出处 《工程力学》 EI CSCD 北大核心 2021年第3期159-168,共10页 Engineering Mechanics
基金 国家重点研发计划项目(2018YFC1504401) 国家自然科学基金重点项目(U1939210) 中国国家铁路集团有限公司科技研究开发计划项目(K2019G035)。
关键词 地震动模拟 机器学习 主成分分析算法 粒子群算法 区域地震动特征 ground motion simulation machine learning PCA PSO characteristics of regional ground motion
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