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The vibration signal of rolling bearing on the driving side of dust-removing fan of Iron-making Plant is with such characteristics as strong nonlinearity and modulation due to it is in service in the harsh environment of high temperature, high humidity and much dust as well as the complex working condition of strong background noise so that its fault character frequency is difficult to be extracted and identified. With the variational mode decomposition (VMD) and maximum correlated kurtosis deconvolution (MCKD), the noise reduction and extraction of fault character frequency for vibration signal of rolling bearing for dust-removing fan are realized as well as the fault identification is completed by envelope demodulation.

, authors=Yong-tao Sun1, Zi-xian Li2, Bo Qin2, authorsList=Yong-tao Sun, Zi-xian Li, Bo Qin, 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=1319241382837998018, articleId=1319241382334681536, tenantId=1146029695717560320, journalId=1185652524569653253, language=CN, title=VMD和MCKD在风机轴承故障辨识中的应用研究, columnId=1185882040256840459, journalTitle=包钢科技, columnName=设备与自动化, runingTitle=null, highlight=null, articleAbstract=

针对炼铁厂除尘风机服役在高温、高湿、多粉尘的恶劣环境下以及强背景噪声的复杂工况造成其驱动侧滚动轴承振动信号具有强非线性、强调制的特点,致使其故障特征频率难提取、难辨识的问题,融合变分模态分解(Variational Mode Decomposition, VMD)与最大相关峭度解卷积(Maximum Correlated Kurtosis Deconvolution, MCKD)实现了对除尘风机滚动轴承振动信号的降噪、故障特征频率的提取,并通过包络解调方法完成了故障的识别。

, authors=孙永涛1, 李子贤2, 秦波2, authorsList=孙永涛, 李子贤, 秦波, authorCompany=null, correspAuthors=null, authorNote=

孙永涛(1977-),男,内蒙古包头市人,硕士,高级工程师,主要从事烧结设备的运维和管理工作。

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孙永涛(1977-),男,内蒙古包头市人,硕士,高级工程师,主要从事烧结设备的运维和管理工作。

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孙永涛(1977-),男,内蒙古包头市人,硕士,高级工程师,主要从事烧结设备的运维和管理工作。

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VMD和MCKD在风机轴承故障辨识中的应用研究
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孙永涛 1 , 李子贤 2 , 秦波 2
包钢科技 | 设备与自动化 2020,46(4): 70-73
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包钢科技 |设备与自动化 2020 , 46 (4) : 70 -73
VMD和MCKD在风机轴承故障辨识中的应用研究
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孙永涛1, 李子贤2, 秦波2
作者信息
  • 1.内蒙古包钢钢联股份有限公司炼铁厂,内蒙古 包头 014010
  • 2.内蒙古科技大学机械工程学院,内蒙古 包头 014010
作者简介:

孙永涛(1977-),男,内蒙古包头市人,硕士,高级工程师,主要从事烧结设备的运维和管理工作。

Application Study of VMD and MCKD in Fault Identification for Bearing of Fan
Yong-tao Sun1, Zi-xian Li2, Bo Qin2
Affiliations
  • 1.Iron-making Plant of Inner Mongolia Baotou Steel Union Co., Ltd., Baotou 014010, Inner Mongolia Autonomous Region, China
  • 2.School of Mechanical Engineering, Inner Mongolia University of Science & Technology, Baotou 014010, Inner Mongolia Autonomous Region, China
出版时间: 2020-08-25 doi: 10.13647/j.cnki.btgkj.2020.04.019
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针对炼铁厂除尘风机服役在高温、高湿、多粉尘的恶劣环境下以及强背景噪声的复杂工况造成其驱动侧滚动轴承振动信号具有强非线性、强调制的特点,致使其故障特征频率难提取、难辨识的问题,融合变分模态分解(Variational Mode Decomposition, VMD)与最大相关峭度解卷积(Maximum Correlated Kurtosis Deconvolution, MCKD)实现了对除尘风机滚动轴承振动信号的降噪、故障特征频率的提取,并通过包络解调方法完成了故障的识别。

变分模态分解  /  最大相关峭度解卷积  /  滚动轴承  /  故障诊断

The vibration signal of rolling bearing on the driving side of dust-removing fan of Iron-making Plant is with such characteristics as strong nonlinearity and modulation due to it is in service in the harsh environment of high temperature, high humidity and much dust as well as the complex working condition of strong background noise so that its fault character frequency is difficult to be extracted and identified. With the variational mode decomposition (VMD) and maximum correlated kurtosis deconvolution (MCKD), the noise reduction and extraction of fault character frequency for vibration signal of rolling bearing for dust-removing fan are realized as well as the fault identification is completed by envelope demodulation.

variational mode decomposition  /  maximum correlated kurtosis deconvolution  /  rolling bearing  /  fault diagnosis
孙永涛, 李子贤, 秦波. VMD和MCKD在风机轴承故障辨识中的应用研究. 包钢科技, 2020 , 46 (4) : 70 -73 . DOI: 10.13647/j.cnki.btgkj.2020.04.019
Yong-tao Sun, Zi-xian Li, Bo Qin. Application Study of VMD and MCKD in Fault Identification for Bearing of Fan[J]. Science & Technology of Baotou Steel, 2020 , 46 (4) : 70 -73 . DOI: 10.13647/j.cnki.btgkj.2020.04.019

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doi: 10.13647/j.cnki.btgkj.2020.04.019
  • 接收时间:2020-04-22
  • 首发时间:2026-10-20
  • 出版时间:2020-08-25
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  • 收稿日期:2020-04-22
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    1.内蒙古包钢钢联股份有限公司炼铁厂,内蒙古 包头 014010
    2.内蒙古科技大学机械工程学院,内蒙古 包头 014010
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2种不同金属材料的力学参数
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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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