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ISSN 2096-7780 CN 10-1665/P

王丽红, 朱石军, 王同利, 李菊珍, 武敏捷, 钟世军. 北京地电台网典型干扰及影响因素浅析[J]. 地震科学进展 , 2021, (12): 560-568. DOI: 10.3969/j.issn.2096-7780.2021.12.004
引用本文: 王丽红, 朱石军, 王同利, 李菊珍, 武敏捷, 钟世军. 北京地电台网典型干扰及影响因素浅析[J]. 地震科学进展 , 2021, (12): 560-568. DOI: 10.3969/j.issn.2096-7780.2021.12.004
Wang Lihong, Zhu Shijun, Wang Tongli, Li Juzhen, Wu Minjie, Zhong Shijun. Analysis of typical interference and influence factors of Beijing geoelectric field observation network[J]. Progress in Earthquake Sciences, 2021, (12): 560-568. DOI: 10.3969/j.issn.2096-7780.2021.12.004
Citation: Wang Lihong, Zhu Shijun, Wang Tongli, Li Juzhen, Wu Minjie, Zhong Shijun. Analysis of typical interference and influence factors of Beijing geoelectric field observation network[J]. Progress in Earthquake Sciences, 2021, (12): 560-568. DOI: 10.3969/j.issn.2096-7780.2021.12.004

北京地电台网典型干扰及影响因素浅析

Analysis of typical interference and influence factors of Beijing geoelectric field observation network

  • 摘要: 本文基于数据跟踪分析工作,通过对北京地电台网2015年1月—2020年12月的非正常变化事件记录进行系统整理和汇总分析,研究得出北京地电台网的典型干扰有观测系统故障、自然环境影响、场地环境影响、人为干扰、地球物理事件和不明原因干扰6类。其中,场地环境干扰对地电台网的影响最为严重,占地电台网干扰的75%。场地环境干扰主要影响因素为城市轨道交通、抽水灌溉、设备漏电、工程影响和高压直流输电。开展井下地电观测是减小场地环境干扰的有效办法。研究成果为提高北京地电台网数据观测质量,更好地应用于地震预测研究提供了科学依据和技术参考。

     

    Abstract: In this paper, the abnormal event records of Beijing Geoelectric Field Observation Network (BGFON) from January 2015 to December 2020 are processed and analyzed. Based on the data tracking and analysis, it is concluded that the typical disturbances of BGFON include observation system failure, natural environment impact, site environment impact, man-made interference, geophysical event and unknown disturbance. The site environment disturbance has the most serious impact of BGFON, covering 75% of BGFON. The main influencing factors of site environmental disturbance include urban rail transit, pumping irrigation, equipment leakage, engineering influence, and high voltage direct current transmissionpower transmission. Underground deep well geoelectric observation is an effective way to reduce site environmental interference. The research results will help to improve the data observation quality of BGFON, and provide better supportfor earthquake prediction research.

     

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