Wang L W,Zhang X G,Zhang Y,Hu Z. 2021. Application of fractal interpolation method to geo-electric field interference data process. Acta Seismologica Sinica43(3):350−358. DOI: 10.11939/jass.20200137
Citation: Wang L W,Zhang X G,Zhang Y,Hu Z. 2021. Application of fractal interpolation method to geo-electric field interference data process. Acta Seismologica Sinica43(3):350−358. DOI: 10.11939/jass.20200137

Application of fractal interpolation method to geo-electric field interference data process

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  • Received Date: August 13, 2020
  • Revised Date: November 05, 2020
  • Available Online: July 06, 2021
  • Published Date: May 14, 2021
  • Geo-electric field and geo-electrical resistivity observation is one of the most important ways of earthquake monitoring. In recent years, geoelectric field observation has been subjected to more and more interference caused by subways, high-voltage direct current transmission, and electrical facilities, etc. Among all these interferences, there is a special type of known interference in the earthquake geo-electric field observation, which is so-called “interference from current” caused by the electric current in measuring geo-electrical resistivity if the geo-electric field and geo-electrical resistivity were observed at the same site. This kind of interference is characterized by short interference time, fixed interference waveform and fixed appearance time, and it will cause difficulties in identifying normal variation of geo-electric field and analyzing data. This paper deals with approaches of eliminating the interference data by using interpolation method. The fractal interpolation method and traditional Lagrange interpolation method were separately used. On the basis of introducing the principle of the two interpolation method, the processing result of the two methods on simulation data and actual data are compared, it demonstrates that fractal interpolation method has higher accuracy than that of Lagrange interpolation method. Then the fractal interpolation method was used in the actual data processing. The result shows that the method not only retrieves the section information effectively, but also preserves the overall original variation tendency of the observation data.
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