基于小波分析的近断层地震动最强速度脉冲识别方法与应用

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振动与冲击 ›› 2021, Vol. 40 ›› Issue (8) : 41-49.

论文

赵天次，赵伯明

作者信息 +

Algorithm and application of the strongest velocity pulse identification of near-fault ground motion based on wavelet analysis

ZHAO Tianci，ZHAO Boming

Author information +

文章历史 +

摘要

基于小波分析方法提出一种最强速度脉冲识别算法，该算法考虑了地面运动的三个正交分量，并使用连续小波变换来识别具有最大能量的速度脉冲方向。应用该算法对NGA-Weat 2数据库中6 288条地震动记录进行分析，并与现有的脉冲识别方法的对比可知，该算法扩展了脉冲识别结果。建立脉冲峰值、周期与震级和断层距的统计模型，结果表明：最强速度脉冲的峰值随断层距的增加而减小，随着震级的增大而增大；与垂直或平行断层分量相比，最强速度脉冲分量具有更大的能量和更小的脉冲峰值。对比该模型与Shahi等(2014)的平面内最强速度脉冲模型，该模型的预测值在震级较小时大于Shahi等的模型，随着震级的增大二者差异逐渐减小，这是因为大震级下最强速度脉冲在水平面内所占的比例较大。

Abstract

An algorithm for the identification of the strongest velocity pulse was proposed based on wavelet analysis, which considers three orthogonal components of the ground motion. The algorithm uses continuous wavelet transforms of three orthogonal components to identify the orientation of the velocity pulse that has the largest energy. The proposed algorithm analyzed 6 288 strong motion records of NGA-West 2 database and expanded the identification results. The statistical models of pulse amplitude, period with magnitude, and fault distance were established. The results show that the peak of the strongest velocity pulse gradually reduces with the increase of the fault distance, while gradually rises with the magnitude. Comparing with the fault normal or fault parallel orientation component, the strongest velocity pulse component has larger energy and smaller peak velocity. Compared with the Shahi, et al(2014) model, the predicted value of the proposed model is larger when the magnitude is small. With the strongest velocity pulses occupying more in the horizontal direction under a large magnitude, the difference between the two models gradually decreases.

导出引用

赵天次，赵伯明. 基于小波分析的近断层地震动最强速度脉冲识别方法与应用[J]. 振动与冲击, 2021, 40(8): 41-49

ZHAO Tianci，ZHAO Boming. Algorithm and application of the strongest velocity pulse identification of near-fault ground motion based on wavelet analysis[J]. Journal of Vibration and Shock, 2021, 40(8): 41-49

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