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首页> 外文期刊>Seismological research letters >Using Component Ratios to Detect Metadata and Instrument Problems of Seismic Stations: Examples from 18 Yr of GEOSCOPE Data
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Using Component Ratios to Detect Metadata and Instrument Problems of Seismic Stations: Examples from 18 Yr of GEOSCOPE Data

机译：使用组分比率来检测地震站的元数据和仪器问题：从18年的地腔数据中的示例

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摘要

Replacement or deterioration of seismic instruments and the evolution of the installation conditions and sites can alter the seismic signal in very subtle ways; therefore, it is notoriously difficult to monitor the signal quality of permanent seismic stations. We present a simple way to characterize and monitor signal quality, using energy ratios between each pair of the three components, as a complement to existing methods. To calculate stable daily energy ratios over a large frequency range (0.01-5 Hz), we use the daily median energy ratio over all 5 min windows within the day. The method is applied to all GEOSCOPE stations, for continuous BH channel data collected since 2001. We show applications to identify past gain problems (stations ROCAM and CRZF), to provide feedback after field interventions at remote sites (Antarctic station DRV), and to shed light on complex instrument problems (stations ECH and KIP). Our results show that component energy ratios have excellent time resolution and that they are visually simple for identification of problems. They can be used both for ongoing continuous monitoring of the signal quality, or as a tool to identify past problems. The Python code to produce the results in this work and the Python code for daily monitoring used by GEOSCOPE are available (see Data and Resources).
机译：抗震仪器的替代或恶化以及安装条件和站点的演变可以以非常微妙的方式改变地震信号;因此，难以监测永久地震车站的信号质量难以监测。我们呈现了一种简单的方法来表征和监控信号质量，使用每对三个组件之间的能量比作为现有方法的补充。为了在大频率范围内计算稳定的日常能量比（0.01-5 Hz），我们在一天内使用每日中位能量比所有5分钟的窗户。该方法应用于所有Geoscope站，以便自2001年以来收集的连续BH频道数据。我们展示了识别过去的增益问题（站Rocam和CRZF）的应用，以在远程站点（南极站DRV）的现场干预后提供反馈，并提供复杂仪器问题上的闪光（车站ech和Kip）。我们的研究结果表明，组件能源比率具有良好的时分分辨率，并且它们在视觉上识别问题。它们都可以用于持续持续监控信号质量，或作为识别过去问题的工具。可以提供Python代码在此工作中生成结果和GeoScope使用的每日监控的Python代码（请参阅数据和资源）。

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