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《地震研究进展(英文)》2021,1(3):100029
We developed an automatic seismic wave and phase detection software based on PhaseNet, an efficient and highly generalized deep learning neural network for P- and S-wave phase picking. The software organically combines multiple modules including application terminal interface, docker container, data visualization, SSH protocol data transmission and other auxiliary modules. Characterized by a series of technologically powerful functions, the software is highly convenient for all users. To obtain the P- and S-wave picks, one only needs to prepare three-component seismic data as input and customize some parameters in the interface. In particular, the software can automatically identify complex waveforms (i.e. continuous or truncated waves) and support multiple types of input data such as SAC, MSEED, NumPy array, etc. A test on the dataset of the Wenchuan aftershocks shows the generalization ability and detection accuracy of the software. The software is expected to increase the efficiency and subjectivity in the manual processing of large amounts of seismic data, thereby providing convenience to regional network monitoring staffs and researchers in the study of Earth's interior. 相似文献
104.
Investigation of waste disposal areas using electrical methods: a case study from Chania,Crete, Greece 总被引:1,自引:0,他引:1
Pantelis Soupios Ilias Papadopoulos Maria Kouli Irene Georgaki Filippos Vallianatos Eleni Kokkinou 《Environmental Geology》2007,51(7):1249-1261
A geophysical investigation of a landfill area was conducted as inextricable phase of a preliminary geotechnical, geological
and hydrogeological study of the area under investigation. Electrical resistivity tomography (ERT), one of the most promising
prospecting techniques mainly concerning its effective contribution to resolve several environmental problems, was applied
for the geophysical modeling. ERT is a robust imaging method the theory and implementation of which are well documented in
geophysical research literature. The survey site is located in Akrotirion Peninsula, about 7 km east of Chania city in Crete
I. The geological setting comprises Trypalion limestones, marly limestones and a clayed weathered layer. Cavities are also
identified at various scales which are recent tectono-karstic voids. Due to the above-mentioned geological singularity and
in the light of the requirement for an environmentally safe construction of the landfill, an ERT survey was carried out. Specifically,
seven geoelectrical tomographies were conducted reaching the prospecting depth of 36 m. The resulted images conduced, to overcome
geotechnical problems since the spatial distribution of karstic voids was determined, to plan the future sites for waste disposal
as the geological conditions were studied in detail and to reliably estimate the thickness of the already deposited wastes.
The resulted images were confirmed using available borehole logs and ambient noise measurements. 相似文献
105.
基于一类新小波函数基的GPS相位观测值周跳探测 总被引:3,自引:0,他引:3
阐述了可通过1个参数因子来调节前后差分点个数的思路,研究了利用小波分析来平滑原始资料和探测GPS相位观测值周跳的方法,并通过CHAMP卫星实测数据进行分析,得出一些有益的结论。实践表明,该方法提高了周跳探测的有效性。 相似文献
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为充分利用高分辨率遥感影像提供的细节信息,提高震害损毁建筑物检测精度,提出了一种图割框架下融合形状、边缘、角点等多种类型特征的损毁建筑物检测方法。该方法首先利用震前建筑物线划图提取包含单个建筑物的局部影像,用于图割能量函数建模,并分别根据建筑物的位置、形状、边缘以及角点构造能量函数的各约束项。在此基础上,通过最大流/最小割算法求解能量函数最小值,依据最小割能量进行地震前后局部影像中建筑物的相似性度量。最后利用最大期望算法(expectation maximization,EM)求得最小割能量的分类阈值,并根据错分率估值执行后处理以获得最终变化检测结果。采用2011年3月11日东日本大地震前后石卷港的高分辨率遥感影像进行试验,结果表明本文提出的方法能有效检测出损毁建筑物。 相似文献
108.
提出一种基于BP神经网络的结构破损诊断方法,该方法以结构破损前后柔度的变化作为破损诊断网络输入,为了解决由于系统响应样本数据空间分布不均匀对网络收敛速度及网络诊断影响问题,对网络训练样本采用广义空间格点进行了交换,模拟算例及应用实例均表明,本文方法能准确诊断结构破损位置与破坏程度,是一种有效的结构破损诊断方法. 相似文献
109.
本文提出了一种全张量磁梯度数据的斜导数边界识别方法,该方法利用全张量磁梯度数据定义了北向斜导数、东向斜导数和垂向斜导数.模型试验表明,北向和东向斜导数无法有效识别磁性异常体边界,异常形态复杂虚假异常较多,而垂向斜导数在高纬度斜磁化或者垂直磁化条件下可以清晰而准确得识别地质体的边界,具有一定的深度识别能力.与现有磁张量梯度的边界识别方法相比,识别效果好,可以有效均衡不同深度地质体的响应.将上述方法应用于大兴安岭地区实测航磁三分量数据转换得到的全张量数据,获得了研究区浅部磁性体的分布,并与三分量数据进行联合解释,取得良好的地质效果.
相似文献110.
Malachite green (MG), a traditional agent used in aquaculture although is not approved; its low cost and high efficacy make illicit use likely. We developed a small‐scale, simple, and sensitive dispersive liquid–liquid microextraction procedure for the assay of trace amounts of MG in aquatic environment of Trout fish. Fiber optic‐linear array detection spectrophotometry with charge‐coupled device detector benefiting from a microcell was used for this purpose. The method is based on enhancement effect of an anionic surfactant on the extraction of MG in to very fine multidroplets of microextraction solvent which made assisted by disperser solvent. Under the optimum conditions, the enrichment factor 77.5 was obtained from a 5‐mL water sample. The calibration graph was linear up to 5 × 10?7 mol L?1 with detection limit of 1 × 10?8 mol L?1. The relative standard deviation for seven replicate measurements of 4 × 10?7 and 5 × 10?8 mol L?1 of MG were 3.3 and 4.5%, respectively. 相似文献