EMD decomposition-based signal denoising method for DC electrical methods

Jingri Huo; Guofu Wang; Hongli Li

doi:10.1117/12.2682604

26 May 2023 EMD decomposition-based signal denoising method for DC electrical methods

Jingri Huo, Guofu Wang, Hongli Li

Proceedings Volume 12700, International Conference on Electronic Information Engineering and Data Processing (EIEDP 2023); 127001C (2023) https://doi.org/10.1117/12.2682604
Event: International Conference on Electronic Information Engineering and Data Processing (EIEDP 2023), 2023, Nanchang, China

Abstract

The DC resistivity method uses the inherent conductive differences of subsurface materials as the basis for exploration to observe the earth's electric field, while human activities, nature and solar storms can cause changes in the earth's electric field, which in turn seriously affects the accuracy of exploration. Today the DC resistivity method is used for monitoring hazards such as landfill seepage, coal mine seepage, and slope seepage. The above hazards change slowly, and the monitored change signal is weak, and if there is earth current interference around it will bury the hazard signal. Therefore, it makes sense to noise cancel the signal for DC method. In this paper, Empirical Mode Decomposition (EMD), sliding average and least squares fitting are combined to propose a noise-canceling method for DC electrical law signals. In this paper, the effectiveness of the method is verified by theoretical simulations.

Citation Download Citation

Jingri Huo, Guofu Wang, and Hongli Li "EMD decomposition-based signal denoising method for DC electrical methods", Proc. SPIE 12700, International Conference on Electronic Information Engineering and Data Processing (EIEDP 2023), 127001C (26 May 2023); https://doi.org/10.1117/12.2682604

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