基于PSO改进遗传算法的矿井地质探测仪信号去噪方法  

Signal Denoising Method for Mine Geological Exploration Instrument Based on PSO Improving Genetic Algorithm

作　　者：刘莉彬 Liu Libin(Research Institute of Coal Geophysical Exploration,China National Administrator of Coal Geology,Baoding 072750,China)

机构地区：[1]中国煤炭地质总局地球物理勘探研究院,河北保定072750

出　　处：《煤矿机械》2025年第5期201-204,共4页Coal Mine Machinery

摘　　要：由于矿井地质环境复杂,导致探测仪接收的信号噪声大、信息提取困难。因此提出基于粒子群优化(PSO)改进遗传算法的矿井地质探测仪信号去噪方法。采用改进型自适应噪声完备集合经验模态分解(ICEEMDAN)对原始信号进行预处理,将其分解为多个本征模态函数分量及1个余项。利用基于PSO改进遗传算法的方法,通过优化个体的适应度值,精确寻找最优的信号去噪参数。在获取最优参数后,筛选出有效的本征模态函数分量和残余项,利用重构技术将它们重新组合,从而实现对矿井地质探测仪信号的有效去噪处理。实验结果表明,该方法能够在处理矿井地质探测仪的含噪信号时显著提升信号质量,为地质分析提供准确的数据基础。Due to the complex geological environment of mines,the signals received by detectors are high noise and difficult to extract information.Therefore,a mine geological exploration instrument signal denoising method based on particle swarm optimization(PSO)improving genetic algorithm was proposed.The original signal was preprocessed by using improved complete ensemble empirical mode decomposition with adaptive noise(ICEEMDAN),which decomposes it into multiple intrinsic mode function components and a remainder term.Using the method of improving genetic algorithm based on PSO,the fitness value of individuals was optimized to accurately find the optimal signal denoising parameters.After obtaining the optimal parameters,effective intrinsic mode function components and residual terms were selected,and they were recombined by using reconstruction techniques to achieve effective denoising processing of mine geological exploration instrument signals.The experimental results show that this method can significantly improve the signal quality when processing noise signals from mine geological detectors,and provide accurate data basis for geological analysis.

关 键 词：PSO 遗传算法 矿井地质探测仪 信号去噪 去噪最优参数 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]