Article(id=1236319263275938349, tenantId=1146029695717560320, journalId=1235980550691926019, issueId=1236316193171239730, articleNumber=null, orderNo=null, doi=10.3969/j.issn.0253-6099.2023.03.006, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1670169600000, receivedDateStr=2022-12-05, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1772691082066, onlineDateStr=2026-03-05, pubDate=1685548800000, pubDateStr=2023-06-01, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1772691082066, onlineIssueDateStr=2026-03-05, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1772691082066, creator=13701087609, updateTime=1772691082066, updator=13701087609, issue=Issue{id=1236316193171239730, tenantId=1146029695717560320, journalId=1235980550691926019, year='2023', volume='43', issue='3', pageStart='1', pageEnd='179', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1772690350096, creator=13701087609, updateTime=1772691872061, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1236322576809652696, tenantId=1146029695717560320, journalId=1235980550691926019, issueId=1236316193171239730, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1236322576809652697, tenantId=1146029695717560320, journalId=1235980550691926019, issueId=1236316193171239730, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=24, endPage=29, ext={EN=ArticleExt(id=1236319263657620023, articleId=1236319263275938349, tenantId=1146029695717560320, journalId=1235980550691926019, language=EN, title=Research on Microseismic Signal Denoising Based on ICEEMDAN and Blind Source Separation, columnId=1236276106018484431, journalTitle=Mining and Metallurgical Engineering, columnName=MINING, runingTitle=null, highlight=null, articleAbstract=

Microseismic signals collected during roadway construction in Jinfeng Gold Mine in the southwest Guizhou Province are non-stationary and also contaminated with background noise. For solving this problem, a noise reduction method based on the improved complete ensemble empirical mode decomposition with adaptive noise (ICEEMDAN) combined with blind source separation (BSS) was proposed. With this method, a microseismic signal can be preliminarily decomposed by ICEEMDAN algorithm, and then correlation coefficient and marginal spectrum of signal can be calculated with MATLAB. Components of noise-containing mode and main frequency of signal can be filtered, and FastICA algorithm is finally used for BSS to achieve noise reduction. The practical application in mine shows that compared to empirical mode decomposition (EMD) and traditional wavelet packet threshold method, the proposed method, with higher signal-to-noise ratio (24.142 5 dB), can bring better noise reduction effect with smaller standard error (0.012 18).

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针对黔西南锦丰金矿巷道施工采集的微震信号非平稳特征和背景噪声干扰问题，引入一种基于完善的自适应噪声完备集成经验模态分解（ICEEMDAN）与盲源分离联合的降噪方法。该方法通过ICEEMDAN算法对微震信号进行初步分解，再利用MATLAB平台计算出信号的相关系数和边际频谱，筛选出含噪模态分量和信号的主频率分量，最后通过FastICA算法进行盲源分离，实现降噪。实际应用结果表明，与经验模态分解（EMD）和小波包阈值传统方法相比，该方法信噪比更大（24.142 5 dB）、标准误差更小（0.012 18）、降噪效果更好。

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黄港（1997—），男，贵州铜仁人，硕士研究生，主要从事矿山灾害防治研究。

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黄港（1997—），男，贵州铜仁人，硕士研究生，主要从事矿山灾害防治研究。

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