共查询到18条相似文献，搜索用时 76 毫秒
1.
系统分析了泰安重力观测资料正常和异常时信号的周期特征,研究了高频异常信号与台风、气压和强震之间的关系.结果表明:泰安重力观测正常时信号周期为2～4分钟,异常时信号周期只有2～3分钟,异常信号幅值约为正常信号的5倍;高频异常信号主要是由西太平洋洋面上生成的进入中国大陆或近海的台风引起的,占台风引起泰安重力出现高频异常信号的90%;重力高频信号与台风中心速度正相关,与台风距离负相关,并且随台风的结束高频信号也随之消失;少数高频异常信号与强震也有一定关系,占地震总数的17.24%;高频异常信号与气压变化无关. 相似文献
2.
3.
4.
5.
6.
在中国地震台网的宽频数字地震计和倾斜、重力仪的观测中,记录到来自西太平洋热带气旋（热带风暴、台风）引起的震颤波.通过对2006年来自西太平洋的全部热带气旋的分析,以及所观测到的震颤波与气旋运动过程中强度的变化、运动路径、观测点与其之间的距离变化等方面的分析研究得到以下结论：震颤信号的持续时间与热带气旋的生命过程基本相符,其中出现强震颤的时间大多为2～3天,特征为信号的包络线呈纺锤状叠加在观测背景上,震颤波的主要频率范围为0.13～0.33 Hz（周期：3～7 s）.我国内陆大部分区域内的宽频地震计、重力仪、倾斜仪等都能清晰记录到这类由热带气旋引起的震颤波.震颤波的强度主要与热带气旋的强度、运动路径以及气旋中心到地震观测台站的距离这几个因素直接相关;而震颤波的变化过程与热带气旋的运动和变化过程密切相关,其中强震颤波的出现时间与气旋过大陆板块边界进入大陆架的时间一致.经对热带气旋的结构、运动规律及动力学特点的了解分析,初步分析认为其主要源于热带气旋运动过程中与浅海区大陆架及陆地表面的摩擦、气压载荷变化以及由此产生的海浪对地壳板块的冲击,及板块边界断层对气旋扰动的响应.此外,我们对北印度洋孟加拉湾生成并在缅甸登陆的热带气旋也进行了实例分析.结果表明：与西太平洋相比,北印度洋热带气旋引起的震颤波对我国大陆的地震观测而言信号较弱. 相似文献
7.
2006年7月4日河北文安县发生了MＳ5.1地震，有6个地电场观测台布设在北京周围。本文阐述了地电场多极距观测系统的噪音识别原理及其在地电场数据分析中的应用方法。通过对首都圈6个地电场台观测资料的研究分析，在所选出的众多震前地电场异常信号中逐一排除，最后选定的5组地电场异常信号基本上被认为是震前地电场前兆异常信号。结果表明:①文安MＳ5.1地震前存在着地电场异常前兆信号；②文安地震前地电场异常前兆信号的出现存在着ldquo;敏感点rdquo;效应；③地电场异常前兆信号在不同的台站存在着不同步出现的现象，并且异常结束至发震时间间隔也不同；④离震中区较近的宝坻台记录到的震前地电场异常幅度较小，而离震中区较远的昌黎台记录到的震前地电场异常幅度则较大。 相似文献
8.
本文主要利用时频分析法，基于2016年以来山东省泰安台重力仪及宽频带地震仪观测到的资料，对风暴天气和台风天气引起的微震现象进行研究. 结果表明:这两种天气过程产生的微震信号的频率基本分布在2—20 s之间，能量集中在5—7 s，15 s附近存在一个能量平稳加强的频段；风暴天气产生的微震信号具有由高频向低频演化的动态特征；两种天气条件下产生的微震信号均具有连续、高频及持续时间长的性质，反映了微震信号激发源的移动特征。 结合泰安台微震与风暴和台风天气的一一对应情况，认为微震是一种与近海风暴或远海台风活动有关的微震动过程，而不是与地震有关的前兆异常。 相似文献
9.
2001年11月3日和12月25日江苏南通地区分别发生了ML3.8和ML4.1的地震群事件. 本文以上海崇明地电场台和南京地电场台ZD9A大地电场仪的观测资料为研究对象，在阐述了多极距地电场观测去噪音原理的基础上, 研究了这两个台站地电场多极距观测系统的资料在震前的异常变化特征. 结果表明: ① 多极距观测去噪音方法是一种很好的识别地电场噪音的方法；② 在震前20天、2天及42天离震中较近的崇明台NS和NE方向上分别接收到了地震电信号, 其持续时间最长的为9天，而较远的南京台出现的异常信号都是噪音信号而非地震电信号；③ 地电场多极距观测系统中公用电极的布极方式是不可取的. 相似文献
10.
在地震与固体潮台站的日常监测中,常发现有一些异常"脉动"信号叠加在固体潮曲线上.这些异常"脉动"与宽频带数字地震计的观测在时间上同步、一致,其中的一部分由发生在西太平洋上的热带气旋引起,而其他的则大多与强地震相伴随,统称为震颤异常波.本文介绍了华中科技大学的地震与固体潮观测台站(HUST)的概况,报道了该台应用 DZW重力仪和VS-1倾斜仪观测记录到的大量震颤异常波事例.大量观测事实表明:中国固体潮台站记录的震颤异常波,绝大多数只在DZW重力仪和VS-1倾斜仪的低通滤波1 通道(LP1)出现,而在其低通滤波2通道(LP2)和其他固体潮仪器中则罕有发现;震颤异常波的包络线大多呈"纺锤状"或"尾巴状",持续时间多为1~3天. 通过对震颤异常波和固体潮观测仪器的分析研究,得到以下结论:震颤异常波实际上就是一种来源复杂的地球脉动信号,响应范围广泛,可被宽频带数字地震计和固体潮仪器记录.由西太平洋上的热带气旋引起的震颤异常波的主要周期在3~7 s范围,而强震前的震颤异常波则除此外,还包含10~60 s及更长周期的信号.固体潮仪器对震颤异常波响应的差异是因为仪器的传递函数不同和特性所致. DZW重力仪和VS-1倾斜仪分钟值采样数据中的震颤异常波,只是真实信号的一种"混叠"或映射.强震前的震颤异常波是否与地震有关？是否是震兆？尚需做更深入细致的分析和研究. 相似文献
11.
We report here the observation result of joint observation of long period tremor signals with broadband seismome-ter,tiltmeter and gravimeter at the HUST(Huazhong University of Science and Technology)station.The observed data were compared and analyzed.Since 2005,the several tens of abnormal tremor signals which are weak,com-plex and duration of 2 to 3 days have been synchronously recorded by the different instruments.The tremor signals have the periodic domain in the range of 3 to 5 minutes,20 to 30 minutes and even more than 1 hour.The observa-tion shows such tremors are a physical existence.The analysis indicates that a part of the tremors caused by the typhoon from the western Pacific Ocean.These tremors have a close relationship with wind velocity of typhoon and distance between the typhoon center and the station.Except these,the cause of others is still unclear. 相似文献
12.
利用海南地震台网宽频带地震仪连续观测资料,分析不同自然环境下地脉动扰动信号,结果显示:在不同自然环境下,地震仪记录的地脉动扰动信号的形态、振幅、频率、扰动强度不同,其中登陆海岛的热带气旋引起的震颤信号频带窄、能量大、扰动强度较大,对地脉动干扰影响大,其次是天文潮期,远离海岛的热带气旋对地脉动干扰影响较小;不同路径、距离的热带气旋引起的震颤信号频率带一致,但扰动强度区别明显;不同自然环境对不同观测台站记录的地脉动信号均存在影响,只是程度稍有不同。 相似文献
13.
The seismic activity of the Nevado del Ruiz volcano was monitored during August–September 1985 using a three-component portable seismograph station placed on the upper part of the volcano. The objective was to investigate the frequency content of the seismic signals and the possible sources of the volcanic tremor. The seismicity showed a wide spectrum of signals, especially at the beginning of September. Some relevant patterns from the collected records, which have been analyzed by spectrum analysis, are presented. For the purpose of analysis, the records have been divided into several categories such as long-period events, tremor, cyclic tremor episodes, and strong seismic activity on September 8, 1985.The origin of the seismic signals must be considered in relation to the dynamical and acoustical properties of fluids and the shape and dimensions of the volcano's conduits.The main results of the present experiment and analysis show that the sources of the seismic signals are within the volcanic edifice. The signal characteristics indicate that the sources lie in fluid-phase interactions rather than in brittle fracturing of solid components. 相似文献
14.
15.
Gloria Curilem Jorge Vergara Gustavo Fuentealba Gonzalo Acuña Max Chacón 《Journal of Volcanology and Geothermal Research》2009
Each volcano has its own unique seismic activity. The aim of this work is to construct a system able to classify seismic signals for the Villarrica volcano, one of the most active volcanoes in South America. Since seismic signals are the result of particular processes inside the volcano's structure, they can be used to forecast volcanic activity. This paper describes the different kinds of seismic signals recorded at the Villarrica volcano and their significance. Three kind of signals were considered as most representative of this volcano's activity: the long-period, the tremor, and the energetic tremor signals. A classifier is implemented to read the seismic registers at 30-second intervals, extract the most relevant features of each interval, and classify them into one of the three kinds of signals considered as most representative of this particular volcano. To do so, 1033 different kinds of 30-s signals were extracted and classified by a human expert. A feature extraction process was applied to obtain the main characteristics of each of them. This process was developed using criteria which have been shown by others to effectively classify seismic signals, based on the experience of a human expert. The classifier was implemented with a Multi-Layer Perceptron (MLP) artificial neural network whose architecture and training process were optimized by means of a genetic algorithm. This technique searched for the most adequate MLP configuration to improve the classification performance, optimizing the number of hidden neurons, the transfer functions of the neurons, and the training algorithm. The optimization process also performed a feature selection to reduce the number of signal features, optimizing the number of network inputs. The results show that the optimized classifier reaches more than 93% exactitude. identifying the signals of each kind. The amplitude of the signals is the most important feature for its classification, followed by its frequency content. The described methodology can be used to classify more seismic signals to improve the study of the activity of this volcano or to extend the study to other active volcanoes of the region. 相似文献
16.
Andrea Cannata Giuseppe Di Grazia Marco Aliotta Carmelo Cassisi Placido Montalto Domenico Patanè 《Pure and Applied Geophysics》2013,170(11):1751-1771
Volcanoes generate a broad range of seismo-volcanic and infrasonic signals, whose features and variations are often closely related to volcanic activity. The study of these signals is hence very useful in the monitoring and investigation of volcano dynamics. The analysis of seismo-volcanic and infrasonic signals requires specifically developed techniques due to their unique characteristics, which are generally quite distinct compared with tectonic and volcano-tectonic earthquakes. In this work, we describe analysis methods used to detect and locate seismo-volcanic and infrasonic signals at Mt. Etna. Volcanic tremor sources are located using a method based on spatial seismic amplitude distribution, assuming propagation in a homogeneous medium. The tremor source is found by calculating the goodness of the linear regression fit (R 2) of the log-linearized equation of the seismic amplitude decay with distance. The location method for long-period events is based on the joint computation of semblance and R 2 values, and the location method of very long-period events is based on the application of radial semblance. Infrasonic events and tremor are located by semblance–brightness- and semblance-based methods, respectively. The techniques described here can also be applied to other volcanoes and do not require particular network geometries (such as arrays) but rather simple sparse networks. Using the source locations of all the considered signals, we were able to reconstruct the shallow plumbing system (above sea level) during 2011. 相似文献
17.
针对煤矿上覆岩层层状赋存和离层带的特点,构建矿井尺度的微震监测系统异向波速模型,模型中波速向量由地面探头速度与井下探头速度组成.研究了在只有强矿震信号和混有爆破信号两种条件下,以到时残差最小为目标和震源定位误差最小为目标的两种求解模型,模型求解选用具有全局寻优特性的遗传算法与CMEAS算法结合的混合算法.现场实际应用得出,只使用爆破信号的到时残差法最优,混有强矿震信号的到时残差法其次;与爆破信号定位所用的统一简化波速模型相比,震源定位误差大幅度降低.在此基础上进一步减低定位误差,还需从微震台网的优化布设方面解决. 相似文献
18.
Mt. Veniaminof, Alaska Peninsula, is a stratovolcano with a summit ice-filled caldera containing a small intracaldera cone
and active vent. From January 2 to February 21, 2005, Mt. Veniaminof erupted. The eruption was characterized by numerous small
ash emissions (VEI 0 to 1) and accompanied by low-frequency earthquake activity and volcanic tremor. We have performed spectral
analyses of the seismic signals in order to characterize them and to constrain their source. Continuous tremor has durations
of minutes to hours with dominant energy in the band 0.5–4.0 Hz, and spectra characterized by narrow peaks either irregularly
(non-harmonic tremor) or regularly spaced (harmonic tremor). The spectra of non-harmonic tremor resemble those of low-frequency
events recorded simultaneously with surface ash explosions, suggesting that the source mechanisms might be similar or related.
We propose that non-harmonic tremor at Mt. Veniaminof results from the coalescence of gas bubbles while low-frequency events
are related to the disruption of large gas pockets within the conduit. Harmonic tremor, characterized by regular and quasi-sinusoidal
waveforms, has duration of hours. Spectra containing up to five harmonics suggest the presence of a resonating source volume
that vibrates in a longitudinal acoustic mode. An interesting feature of harmonic tremor is that frequency is observed to
change over time; spectral lines move towards higher or lower values while the harmonic nature of the spectra is maintained.
Factors controlling the variable characteristics of harmonic tremor include changes in acoustic velocity at the source and
variations of the effective size of the resonator. 相似文献