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Abstract <p>This paper systematically studies some of the precursor observation data in the Wuhai area since 2019. The results show: (1) The multifractal analysis and wavelet analysis methods mutually confirm and complement each other, and can effectively identify and extract the abnormal information (such as the time lag response to rainfall disturbance) that cannot be identified by a single analysis method in the precursor observation data. (2) The abnormal air pressure interference can be clearly identified from the curve shape of the multifractal spectrum. Meanwhile, the solid tide observation curve is basically synchronized with the short-term air pressure changes and their durations. (3) The wavelet analysis is more sensitive in identifying rainfall interference, while the multifractal analysis can better reflect the gradual cumulative process of the influence of rainfall on the precursor observations. (4) Explosion events are obviously manifested in the d1–d3 and d4 parts of the wavelet analysis details, and earthquake events are obviously reflected in the d1–d6 and d7 parts. There are obvious differences in the maximum values of the multifractal spectra, the singularity indices corresponding to the maximum values, and the spectrum widths among near-earthquake events, distant-earthquake events, and explosion events. The above work is the first to identify and systematically study the interference factors and their characteristics of the precursor observation data in the Wuhai area. It provides research examples for the identification and elimination of precursor abnormal information in this region, and offers a reference basis for the determination of short-term and imminent precursor anomalies in this area.</p>

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Research on the Identification of Some Precursory Abnormal Observations in Wuhai Area Since 2019 Based on Multifractal and Wavelet Analysis

  • 期刊论文

  • 发表日期：

    2025年10月2日

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  • Wang Youpeng,
  • Li Dewen,
  • Zheng Na,
  • Li Xin,
  • Zhao Xiaolong

摘要

Abstract

This paper systematically studies some of the precursor observation data in the Wuhai area since 2019. The results show: (1) The multifractal analysis and wavelet analysis methods mutually confirm and complement each other, and can effectively identify and extract the abnormal information (such as the time lag response to rainfall disturbance) that cannot be identified by a single analysis method in the precursor observation data. (2) The abnormal air pressure interference can be clearly identified from the curve shape of the multifractal spectrum. Meanwhile, the solid tide observation curve is basically synchronized with the short-term air pressure changes and their durations. (3) The wavelet analysis is more sensitive in identifying rainfall interference, while the multifractal analysis can better reflect the gradual cumulative process of the influence of rainfall on the precursor observations. (4) Explosion events are obviously manifested in the d1–d3 and d4 parts of the wavelet analysis details, and earthquake events are obviously reflected in the d1–d6 and d7 parts. There are obvious differences in the maximum values of the multifractal spectra, the singularity indices corresponding to the maximum values, and the spectrum widths among near-earthquake events, distant-earthquake events, and explosion events. The above work is the first to identify and systematically study the interference factors and their characteristics of the precursor observation data in the Wuhai area. It provides research examples for the identification and elimination of precursor abnormal information in this region, and offers a reference basis for the determination of short-term and imminent precursor anomalies in this area.