Article(id=1319263330062160308, tenantId=1146029695717560320, journalId=1185652524569653253, issueId=1319263322806014330, articleNumber=null, orderNo=null, doi=10.13647/j.cnki.btgkj.2018.01.022, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1509984000000, receivedDateStr=2017-11-07, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1792466488614, onlineDateStr=2026-10-20, pubDate=1519488000000, pubDateStr=2018-02-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1792466488614, onlineIssueDateStr=2026-10-20, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1792466488614, creator=13701087609, updateTime=1792466488614, updator=13701087609, issue=Issue{id=1319263322806014330, tenantId=1146029695717560320, journalId=1185652524569653253, year='2018', volume='44', issue='1', pageStart='1', pageEnd='98', issueExtLink='null', onlineDate='null', pubDate='1519488000000', pubDateStr='2018-02-25', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1792466486884, creator='13701087609', updateTime=1792467566463, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1319267850951438726, tenantId=1146029695717560320, journalId=1185652524569653253, issueId=1319263322806014330, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1319267850955633031, tenantId=1146029695717560320, journalId=1185652524569653253, issueId=1319263322806014330, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=68, endPage=71, ext={EN=ArticleExt(id=1319263331865711029, articleId=1319263330062160308, tenantId=1146029695717560320, journalId=1185652524569653253, language=EN, title=Fault Diagnosis and Analysis of Gearbox Based on ELMD Decomposition and MED, columnId=1319263323493880187, journalTitle=Science & Technology of Baotou Steel, columnName=Product Development and Technology, runingTitle=null, highlight=null, articleAbstract=

Aiming at the non-stationary characteristics of early failure vibration signal of gear and the fact that it is seriously affected by environmental noise and the fault feature is weak so it is hard to be extracted, the ensemble local mean decomposition is used to decompose the fault vibration signal of gear to obtain the product function of finite single component, so as to highlight the local characteristics of the signal. However, because of the noise interference, it is difficult to extract the fault feature frequency information from frequency spectrum of each component, and based on that, in the paper, the fault diagnosis method of ensemble local mean decomposition and minimum entropy deconvolution is proposed. Through the analysis of gear fault simulation experiment and project case, fault characteristic information of gear can be extracted accurately and effectively, which provides a new method for practical engineering application.

, authors=Shao-yong ZHAO1, 2, Xue-ping REN1, Fu-gui HAO1, 2, authorsList=Shao-yong ZHAO, Xue-ping REN, Fu-gui HAO, authorCompany=null, correspAuthors=null, 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=1319263332096397750, articleId=1319263330062160308, tenantId=1146029695717560320, journalId=1185652524569653253, language=CN, title=基于ELMD分解和MED的齿轮箱故障诊断分析, columnId=1319263323665846653, journalTitle=包钢科技, columnName=产品研发与工艺技术, runingTitle=null, highlight=null, articleAbstract=

针对齿轮早期故障振动信号的非平稳特性和现实中受环境噪声影响严重,故障特征微弱难以提取的问题,利用总体局部均值分解对齿轮故障振动信号进行分解得到有限个单分量的乘积函数,从而凸显信号的局部特性。但由于噪声的干扰,从各分量的频谱中很难提取故障特征频率信息。文章基于此提出总体局部均值分解和最小熵反褶积的故障诊断方法。通过对齿轮故障仿真实验和工程案列分析,能够准确、有效地提取齿轮故障特征信息,为实际工程应用提供了一种新方法。

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赵少勇(1986-),男,内蒙古包头市人,硕士,工程师,现从事设备运行管理工作。

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赵少勇(1986-),男,内蒙古包头市人,硕士,工程师,现从事设备运行管理工作。

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赵少勇(1986-),男,内蒙古包头市人,硕士,工程师,现从事设备运行管理工作。

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基于ELMD分解和MED的齿轮箱故障诊断分析
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赵少勇 1, 2 , 任学平 1 , 郝富贵 1, 2
包钢科技 | 产品研发与工艺技术 2018,44(1): 68-71
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包钢科技 |产品研发与工艺技术 2018 , 44 (1) : 68 -71
基于ELMD分解和MED的齿轮箱故障诊断分析
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赵少勇1, 2, 任学平1, 郝富贵1, 2
作者信息
  • 1.内蒙古科技大学机械学院,内蒙古 包头 014010
  • 2.内蒙古包钢钢联股份有限公司设备工程部,内蒙古 包头 014010
作者简介:

赵少勇(1986-),男,内蒙古包头市人,硕士,工程师,现从事设备运行管理工作。

Fault Diagnosis and Analysis of Gearbox Based on ELMD Decomposition and MED
Shao-yong ZHAO1, 2, Xue-ping REN1, Fu-gui HAO1, 2
Affiliations
  • 1.School of Mechanical Engineering, Inner Mongolia University of Science and Technology, Baotou 014010, Nei Monggol, China
  • 2.Equipment and Engineering Dept. of Inner Mongolia Steel Union Co. Ltd. of Baotou Steel (Group) Corp., Baotou 014010, Nei Monggol, China
出版时间: 2018-02-25 doi: 10.13647/j.cnki.btgkj.2018.01.022
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针对齿轮早期故障振动信号的非平稳特性和现实中受环境噪声影响严重,故障特征微弱难以提取的问题,利用总体局部均值分解对齿轮故障振动信号进行分解得到有限个单分量的乘积函数,从而凸显信号的局部特性。但由于噪声的干扰,从各分量的频谱中很难提取故障特征频率信息。文章基于此提出总体局部均值分解和最小熵反褶积的故障诊断方法。通过对齿轮故障仿真实验和工程案列分析,能够准确、有效地提取齿轮故障特征信息,为实际工程应用提供了一种新方法。

齿轮箱  /  时域分析  /  频域分析

Aiming at the non-stationary characteristics of early failure vibration signal of gear and the fact that it is seriously affected by environmental noise and the fault feature is weak so it is hard to be extracted, the ensemble local mean decomposition is used to decompose the fault vibration signal of gear to obtain the product function of finite single component, so as to highlight the local characteristics of the signal. However, because of the noise interference, it is difficult to extract the fault feature frequency information from frequency spectrum of each component, and based on that, in the paper, the fault diagnosis method of ensemble local mean decomposition and minimum entropy deconvolution is proposed. Through the analysis of gear fault simulation experiment and project case, fault characteristic information of gear can be extracted accurately and effectively, which provides a new method for practical engineering application.

gearbox  /  time domain analysis  /  frequency domain analysis
赵少勇, 任学平, 郝富贵. 基于ELMD分解和MED的齿轮箱故障诊断分析. 包钢科技, 2018 , 44 (1) : 68 -71 . DOI: 10.13647/j.cnki.btgkj.2018.01.022
Shao-yong ZHAO, Xue-ping REN, Fu-gui HAO. Fault Diagnosis and Analysis of Gearbox Based on ELMD Decomposition and MED[J]. Science & Technology of Baotou Steel, 2018 , 44 (1) : 68 -71 . DOI: 10.13647/j.cnki.btgkj.2018.01.022

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doi: 10.13647/j.cnki.btgkj.2018.01.022
  • 接收时间:2017-11-07
  • 首发时间:2026-10-20
  • 出版时间:2018-02-25
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  • 收稿日期:2017-11-07
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    1.内蒙古科技大学机械学院,内蒙古 包头 014010
    2.内蒙古包钢钢联股份有限公司设备工程部,内蒙古 包头 014010
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2种不同金属材料的力学参数
科
Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)
属
Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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