...
首页> 外文期刊>Geoenvironmental Disasters >Application of wavelet for seismic wave analysis in Kathmandu Valley after the 2015 Gorkha earthquake, Nepal
【24h】

Application of wavelet for seismic wave analysis in Kathmandu Valley after the 2015 Gorkha earthquake, Nepal

机译:小波在2015年Gorkha地震后加德满都谷地震波分析的应用尼泊尔

获取原文
           

摘要

In this paper, we estimate the seismogenic energy during the Nepal Earthquake (25 April 2015) and studied the ground motion time-frequency characteristics in Kathmandu valley. The idea to analyze time-frequency characteristic of seismogenic energy signal is based on wavelet transform which we employed here. Wavelet transform has been used as a powerful signal analysis tools in various fields like compression, time-frequency analysis, earthquake parameter determination, climate studies, etc. This technique is particularly suitable for non-stationary signal. It is well recognized that the earthquake ground motion is a non-stationary random process. In order to characterize a non-stationary random process, it is required immeasurable samples in the mathematical sense. The wavelet transformation procedures that we follow here helps in random analyses of linear and non-linear structural systems, which are subjected to earthquake ground motion. The manners of seismic ground motion are characterized through wavelet coefficients associated to these signals. Both continuous wavelet transform (CWT) and discrete wavelet transform (DWT) techniques are applied to study ground motion in Kathmandu Valley in horizontal and vertical directions. These techniques help to point out the long-period ground motion with site response. We found that the long-period ground motions have enough power for structural damage. Comparing both the horizontal and the vertical motion, we observed that the most of the high amplitude signals are associated with the vertical motion: the high energy is released in that direction. It is found that the seismic energy is damped soon after the main event; however the period of damping is different. This can be seen on DWT curve where square wavelet coefficient is high at the time of aftershock and the value decrease with time. In other words, it is mostly associated with the arrival of Rayleigh waves. We concluded that long-period ground motions should be studied by earthquake engineers in order to avoid structural damage during the earthquake. Hence, by using wavelet technique we can specify the vulnerability of seismically active region and local topological features out there.
机译:在本文中,我们估计了尼泊尔地震期间的发神源能量(2015年4月25日),并研究了加德满都谷的地面运动时频特性。分析地震能量信号的时频特性的想法是基于我们在此所用的小波变换。小波变换已被用作各种领域的强大信号分析工具,如压缩,时频分析,地震参数确定,气候研究等。该技术特别适用于非静止信号。众所周知,地震地面运动是一种非静止的随机过程。为了表征非静止的随机过程,在数学意义上是必需的不可估量的样本。我们遵循的小波变换程序有助于随机分析线性和非线性结构系统,其受到地震地面运动。地震地面运动的方式通过与这些信号相关联的小波系数来表征。连续小波变换(CWT)和离散小波变换(DWT)技术应用于在水平和垂直方向上的加德满都河谷中研究地面运动。这些技术有助于指出具有现场反应的长期地面运动。我们发现长期地面运动有足够的结构损坏力量。比较水平和垂直运动,我们观察到,大多数高幅度信号与垂直运动相关联:在该方向上释放高能。结果发现,主事件后,地震能量很快就会受到阻尼;然而,阻尼的时期是不同的。这可以在DWT曲线上看出,在余震时平方小波系数高,并且随时间减少值。换句话说,它主要与瑞利波的到来相关联。我们得出结论,应通过地震工程师研究长期地面运动,以避免地震期间的结构损坏。因此,通过使用小波技术,我们可以指定地震活动区域和当地拓扑特征的脆弱性。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号