Enhanced infrasound denoising for debris flow analysis: Integrating empirical mode decomposition with an improved wavelet threshold algorithm

作     者：Dong, Hanchuan Liu, Shuang Liu, Dunlong Tao, Zhigang Fang, Lide Pang, Lili Zhang, Zhonghua 

作者机构：Hebei Univ Coll Qual & Tech Supervis Baoding 071002 Peoples R China China Geol Survey Ctr Hydrogeol & Environm Geol Survey Tianjin 300304 Peoples R China Hebei Key Lab Energy Metering & Safety Testing Tec Baoding 071002 Peoples R China Chinese Acad Sci Inst Mt Hazards & Environm Chengdu 610299 Peoples R China Chengdu Univ Informat & Technol Coll Software Engn Chengdu 610225 Peoples R China China Univ Min & Technol Sch Mech & Civil Engn Beijing 100083 Peoples R China 

出 版 物：《MEASUREMENT》 (测量)

年 卷 期：2024年第235卷

核心收录：

学科分类：08[工学] 080401[工学-精密仪器及机械] 0804[工学-仪器科学与技术] 081102[工学-检测技术与自动化装置] 0811[工学-控制科学与工程] 

基　　金：Key Research and Development Program of Tibet Autonomous Region [2022YFC3003403] Natural Science Foundation of Hebei Province [XZ202301ZY0039G] Geological Survey Project of China Geological Survey (No.DD20221747) [F2021201031] Dongchuan Debris Flow Observation and Research Station 

主　　题：Debris flow infrasound Empirical Mode Decomposition Wavelet threshold Noise reduction Sparrow search algorithm 

摘      要：The measurement and analysis of infrasound are widely utilized in debris flow monitoring and early warning. However, the infrasound signals are often contaminated by noise across various frequencies, posing significant challenges for feature extraction. The current methods for infrasound denoising are somewhat rudimentary and face several constraints. This study introduces a novel method for enhancing infrasound signals through denoising. This approach integrates empirical mode decomposition with an enhanced wavelet threshold algorithm, and improves the conventional wavelet threshold function. This study uses the Signal -to -Noise ratio, smoothness and correlation coefficient to fine-tune the wavelet parameters. Experiments in flumes with varying speeds and volumes were conducted to test the effectiveness of the denoising method. The results demonstrate that, compared to traditional methods, the proposed method improves the SNR by averages of 69.56%, 60.91%, and 55.63%. It offers a new alternative for the noise reduction of debris flow infrasound signals.