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地震动相位差谱的物理意义及拟合方法 被引量:2

Optimal Fitting Method of Phase Difference Spectrum of Natural Seismic Wave
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摘要 为了保证人工地震波具备强度非平稳特征和频率非平稳特征,需要通过拟合方法生成频率分布特征符合要求的人工峰点到时.天然地震波的峰点到时频率分布特征普遍存在"尾部突起"现象,因此提出利用正态分布拟合调整后的峰点到时频率分布特征的方法,并根据天然地震波的峰点到时频率分布峰值优化正态分布标准差.选取符合不同条件的640条天然地震波为研究对象,分别利用正态分布、对数正态分布、伽马分布对峰点到时频率分布特征进行拟合研究,发现利用正态分布拟合方法生成的人工峰点到时频率分布特征最符合天然地震波的峰点到时频率分布特征. To ensure that the artificial seismic wave has the characteristics of non-stationary intensity and frequency,it is necessary to generate the artificial peak arrival time that the frequency distribution characteristics meet the requirements by fitting method.The phenomenon of"tail protrusion"exists in the frequency distribution characteristics of peak arrival time of natural seismic waves.Therefore,a method of fitting the frequency distribution characteristics of peak arrival time with normal distribution was proposed,and the normal fitting standard deviation was optimized according to the maximum distribution frequency of peak arrival time of natural seismic waves.640 natural seismic waves that meet different conditions were selected as research objects.The frequency distribution characteristics of peak arrival time were fitted by normal distribution,lognormal distribution and gamma distribution,respectively.It is found that the frequency distribution characteristics of artificial peak arrival time generated by normal distribution fitting method are most consistent with the frequency distribution characteristics of peak arrival time of natural seismic waves.
作者 韩旭 彭凌云 王志涛 苏经宇 王丽华 HAN Xu;PENG Lingyun;WANG Zhitao;SU Jingyu;WANG Lihua(College of Architecture and Civil Engineering,Beijing University of Technology,Beijing 100124,China;Institute of Earthquake Resistance and Disaster Reduction,Beijing University of Technology,Beijing 100124,China)
出处 《北京工业大学学报》 CAS CSCD 北大核心 2019年第12期1232-1242,共11页 Journal of Beijing University of Technology
基金 国家重点研发计划资助项目(2018YFD1100902) 国家自然科学基金资助项目(51678017)
关键词 相位差谱 峰点到时 正态拟合方法 优化标准差 phase difference spectrum peak arrival time normal fitting method optimization standard deviation
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