Article(id=1242133034128974280, tenantId=1146029695717560320, journalId=1146031591421210625, issueId=1242133009692959068, articleNumber=null, orderNo=15, doi=10.3981/j.issn.1000-7857.2015.02.013, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1402329600000, receivedDateStr=2014-06-10, revisedDate=1414857600000, revisedDateStr=2014-11-02, acceptedDate=null, acceptedDateStr=null, onlineDate=1423466432620, onlineDateStr=2015-02-09, pubDate=1422374400000, pubDateStr=2015-01-28, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1423466432620, onlineIssueDateStr=2015-02-09, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1774077193048, creator=sys-migrate, updateTime=1774077193048, updator=sys-migrate, issue=Issue{id=1242133009692959068, tenantId=1146029695717560320, journalId=1146031591421210625, year='2015', volume='33', issue='2', pageStart='1', pageEnd='128', issueExtLink='null', onlineDate='null', pubDate='1422374400000', pubDateStr='2015-01-28', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=3, issueType=-1, specialIssue=null, createTime=1774077187222, creator='sys-migrate', updateTime=1774077187222, updator='sys-migrate', preIssue=null, nextIssue=null, articleTotal=null, ext=null, issueFiles=null, downloadFileDto=null}, startPage=86, endPage=90, ext={EN=ArticleExt(id=1242133037111124448, articleId=1242133034128974280, tenantId=1146029695717560320, journalId=1146031591421210625, language=EN, title=Application of FFT spectrum analysis to identify microseismic signals, columnId=null, journalTitle=Science & Technology Review, columnName=null, runingTitle=null, highlight=null, articleAbstract=To identify large scale stopping blasting and large magnitude micro-seismic signals, the FFT spectral analysis method is used. The analysis of the stopping blasting and macro-scale rock fracture signals is made through power spectrum and magnitudefrequency characteristics. The distribution difference of the energy on the frequency brand can be revealed. It is shown that in the frequency brand distribution of the large magnitude micro-seismic signal, the amplitude value takes the maximum at about 10 Hz and 30~50 Hz. The large scale stopping blasting is in a narrow frequency brand. Its amplitude value is higher than the normal signal. It reaches the top amplitude at 10 Hz. From the energy distribution, the energy distribution of the blasting signal mostly in the 0-30 Hz low frequency area. It is because the blasting is always accompanied with an enormous energy, which is released very fast. The microseismic energy is distributed mostly in the range of 30-50 Hz. So for the two kinds of signal identifications, two kinds of signal spectrum characteristics may be used., authors=JIANG Wenwu¹, YANG Zuolin², XIE Jianmin², LI Jiafu³, authorsList=JIANG Wenwu, YANG Zuolin, XIE Jianmin, LI Jiafu, authorCompany=1. Mining Engineering Key Laboratory of Jiangxi Province, Jiangxi University of Science and Technology, Ganzhou 341000, China;
2. School of Resources and Environmental Engineering, Jiangxi University of Science and Technology, Ganzhou 341000, China;
3. Shanghai Pengxu Information Technology Co., Ltd., Shanghai 200000, China, correspAuthors=null, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=ZgKRL1rMH9W9R8A3Q2ynHg==, pdfFileSize=2621964, 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=1242133036175794642, articleId=1242133034128974280, tenantId=1146029695717560320, journalId=1146031591421210625, language=CN, title=FFT频谱分析在微震信号识别中的应用, columnId=1146540929516700224, journalTitle=科技导报, columnName=研究论文, runingTitle=null, highlight=null, articleAbstract=为识别采场大爆破信号与岩石破裂大震级微震信号,运用MATLAB 的快速傅里叶变换(FFT)频谱分析,对采场大爆破信号和大震级微震信号的功率谱和幅频特性进行分析,并对比两者能量在频带上的分布差异。研究表明,大震级微震信号频带分布较宽,且在30～50 Hz 达到了最大幅值,采场大爆破信号频带更窄、幅值更大、且一般在10 Hz 就能达到最大幅值。由于爆破释放的能量较大且释放的非常快,采场大爆破信号能量大多分布在0～30 Hz 的低频区域,大震级微震信号的能量大多分布于30～50 Hz 区域。利用信号特性实现对两种信号快速有效的辨识,为后期微震监测对地压风险区域的预测预报提供了准确的数据支撑。, authors=江文武¹, 杨作林², 谢建敏², 李家福³, authorsList=江文武, 杨作林, 谢建敏, 李家福, authorCompany=1. 江西理工大学江西省矿业工程重点实验室, 赣州341000;
2. 江西理工大学资源与环境工程学院, 赣州341000;
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