Article(id=1314907658390434726, tenantId=1146029695717560320, journalId=1235980550691926019, issueId=1314907656704324517, articleNumber=null, orderNo=null, doi=10.3969/j.issn.0253-6099.2026.01.007, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1755619200000, receivedDateStr=2025-08-20, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1791428015563, onlineDateStr=2026-10-08, pubDate=null, pubDateStr=null, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1791428015563, onlineIssueDateStr=2026-10-08, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1791428015563, creator=13701087609, updateTime=1791428015563, updator=13701087609, issue=Issue{id=1314907656704324517, tenantId=1146029695717560320, journalId=1235980550691926019, year='2026', volume='46', issue='1', pageStart='1', pageEnd='206', issueExtLink='null', onlineDate='null', pubDate='1769875200000', pubDateStr='2026-02-01', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1791428015160, creator='13701087609', updateTime=1791430491940, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1314918045139690301, tenantId=1146029695717560320, journalId=1235980550691926019, issueId=1314907656704324517, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1314918045139690302, tenantId=1146029695717560320, journalId=1235980550691926019, issueId=1314907656704324517, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=44, endPage=50, ext={EN=ArticleExt(id=1314907658856002471, articleId=1314907658390434726, tenantId=1146029695717560320, journalId=1235980550691926019, language=EN, title=Noise Reduction of Blasting Vibration Signal Based on ITD - K-means - Wavelet Packet Method, columnId=1236276106018484431, journalTitle=Mining and Metallurgical Engineering, columnName=MINING, runingTitle=null, highlight=null, articleAbstract=
For solving noise interference in the measured blasting vibration signals, a noise reduction technique is proposed. Based on the Intrinsic Time-Scale Decomposition (ITD) algorithm, the signal is firstly decomposed into several Intrinsic Mode Functions (IMFs). And the K-means clustering is then used to calculate the correlation coefficient value for identifying the types of signal with noise. The wavelet packet method is used to denoise and reconstruct the types of signal with noise, so as to obtain desired signal. This technique was used to verify the noise reduction effect for both simulated and measured signals. The results show that in the noise reduction test for simulated signals, the ITD - K-means - wavelet packet method can achieve the highest signal-to-noise ratio (17.241 dB) and the smallest root mean square error (9.71×10-2), compared with the traditional wavelet packet method, the CEEMDAN method and the ITD method. The noise reduction test for measured signals shows that after processing with the ITD - K-means - wavelet packet method, the signal in the low-to-medium frequency band (0-60 Hz) can retain more energy of dominant frequency, thus high-frequency noise (>120 Hz) can be effectively suppressed.
, authors=Yuzhou SHEN
1, Yunpeng ZHANG
2, 3, Haiyue MA
2, authorsList=Yuzhou SHEN, Yunpeng ZHANG, Haiyue MA, authorCompany=null, correspAuthors=Yunpeng ZHANG, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null), CN=ArticleExt(id=1314907659610977193, articleId=1314907658390434726, tenantId=1146029695717560320, journalId=1235980550691926019, language=CN, title=基于ITD - K-means - 小波包法的爆破振动信号降噪研究, columnId=1236276106219811026, journalTitle=矿冶工程杂志, columnName=采矿, runingTitle=null, highlight=null, articleAbstract=
针对实测爆破振动信号中噪声干扰的问题,提出了一种爆破振动信号降噪方法。该方法基于固有时间尺度分解(ITD)算法,将信号分解为多个IMF分量;引入K-means算法进行聚类处理,计算各类别信号的相关系数值,识别含噪信号类别;通过小波包法对含噪信号进行降噪处理并重构,得到纯净信号。采用该方法对仿真信号和实测信号进行降噪验证,结果表明,在仿真信号降噪实验中,相较于传统的小波包法、CEEMDAN法和ITD法,ITD - K-means - 小波包法的信噪比(17.241 dB)最大,均方根误差(9.71×10-2)最小;在实测信号降噪实验中,经ITD - K-means - 小波包法处理后的信号在中低频段(0~60 Hz)保留了更多的优势主频能量,有效抑制了120 Hz以上的高频噪声。
, authors=申宇宙
1, 张云鹏
2, 3, 马海越
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申宇宙(2000—),男,山西长治人,硕士研究生,主要从事爆破领域研究。E-mail: 2087699959@qq.com
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申宇宙(2000—),男,山西长治人,硕士研究生,主要从事爆破领域研究。E-mail: 2087699959@qq.com
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