基于增量式等距映射同双重局部密度方法的工业过程故障检测
TP277; 针对工业过程的非线性和动态性问题,提出一种基于流形学习下的增量式等距映射(IISOMAP)与双重局部密度(DLD)相结合的故障检测方法(IISOMAP-DLD).利用IISOMAP将原始数据映射到低维流形特征子空间和剩余子空间;然后,在两个子空间中分别引入双重局部密度方法构建统计量对过程进行监控;最后,将IISOMAP-DLD方法应用到田纳西-伊斯曼(TE)过程.实验结果表明,IISOMAP-DLD对比其他方法有更高的故障检测率.IISOMAP在保留数据内在特征的同时,解决了过程的非线性问题,而双重局部密度方法可消除过程的动态性....
Saved in:
Published in | 上海交通大学学报 Vol. 58; no. 4; pp. 525 - 533 |
---|---|
Main Authors | , , , |
Format | Journal Article |
Language | Chinese |
Published |
沈阳化工大学理学院,沈阳 110142
2024
辽宁省化工过程工业智能化技术重点实验室,沈阳 110142%沈阳化工大学理学院,沈阳 110142 沈阳化工大学计算机科学与技术学院,沈阳 110142%沈阳化工大学计算机科学与技术学院,沈阳 110142 |
Subjects | |
Online Access | Get full text |
ISSN | 1006-2467 |
DOI | 10.16183/j.cnki.jsjtu.2022.423 |
Cover
Abstract | TP277; 针对工业过程的非线性和动态性问题,提出一种基于流形学习下的增量式等距映射(IISOMAP)与双重局部密度(DLD)相结合的故障检测方法(IISOMAP-DLD).利用IISOMAP将原始数据映射到低维流形特征子空间和剩余子空间;然后,在两个子空间中分别引入双重局部密度方法构建统计量对过程进行监控;最后,将IISOMAP-DLD方法应用到田纳西-伊斯曼(TE)过程.实验结果表明,IISOMAP-DLD对比其他方法有更高的故障检测率.IISOMAP在保留数据内在特征的同时,解决了过程的非线性问题,而双重局部密度方法可消除过程的动态性. |
---|---|
AbstractList | TP277; 针对工业过程的非线性和动态性问题,提出一种基于流形学习下的增量式等距映射(IISOMAP)与双重局部密度(DLD)相结合的故障检测方法(IISOMAP-DLD).利用IISOMAP将原始数据映射到低维流形特征子空间和剩余子空间;然后,在两个子空间中分别引入双重局部密度方法构建统计量对过程进行监控;最后,将IISOMAP-DLD方法应用到田纳西-伊斯曼(TE)过程.实验结果表明,IISOMAP-DLD对比其他方法有更高的故障检测率.IISOMAP在保留数据内在特征的同时,解决了过程的非线性问题,而双重局部密度方法可消除过程的动态性. |
Abstract_FL | To address the nonlinearity and dynamics of industrial processes,an incremental isometric mapping(IISOMAP)in combination with double local density(DLD)is proposed as a fault detection method(IISOMAP-DLD)based on stream shape learning.First,IISOMAP is used to map the raw data into a low-dimensional manifold feature subspace and a residual subspace.Then,the double local density method is introduced in the two subspaces respectively to construct statistics to monitor the process.Finally,the IISOMAP-DLD method is applied to the Tennessee-Eastman(TE)process,and the experimental results show that IISOMAP-DLD has a higher fault detection rate than the other methods.IISOMAP preserves the intrinsic characteristics of the data and solves the nonlinear problems of the process,while the double local density method can eliminate the dynamic of the process. |
Author | 冯立伟 孙立文 顾欢 李元 |
AuthorAffiliation | 沈阳化工大学理学院,沈阳 110142;沈阳化工大学计算机科学与技术学院,沈阳 110142%沈阳化工大学计算机科学与技术学院,沈阳 110142;辽宁省化工过程工业智能化技术重点实验室,沈阳 110142%沈阳化工大学理学院,沈阳 110142 |
AuthorAffiliation_xml | – name: 沈阳化工大学理学院,沈阳 110142;沈阳化工大学计算机科学与技术学院,沈阳 110142%沈阳化工大学计算机科学与技术学院,沈阳 110142;辽宁省化工过程工业智能化技术重点实验室,沈阳 110142%沈阳化工大学理学院,沈阳 110142 |
Author_FL | LI Yuan GU Huan SUN Liwen FENG Liwei |
Author_FL_xml | – sequence: 1 fullname: FENG Liwei – sequence: 2 fullname: SUN Liwen – sequence: 3 fullname: GU Huan – sequence: 4 fullname: LI Yuan |
Author_xml | – sequence: 1 fullname: 冯立伟 – sequence: 2 fullname: 孙立文 – sequence: 3 fullname: 顾欢 – sequence: 4 fullname: 李元 |
BookMark | eNrjYmDJy89LZWCQMzTQMzQztDDWz9JLzsvO1Msqziop1TMyMDLSMzEyZmHgNDQwMNM1MjEz52DgLS7OTDIwNTQ2M7cwM-BkCHw6f9eTXX1PF8172d7_dE__87WdL7bPfTZjwdMNLU8n9Dzt73nZ3vt0Y8PL5hVP17c93bXs2bSdzzZPfT6r5en2pU92zHqxv_35iu5nU1tfzprzbHHDs63dPAysaYk5xam8UJqbQdPNNcTZQ7c8MS8tMS89Piu_tCgPKBNfnJFVklJRkQR0qYmBiYGhkTEpagGuGWmz |
ClassificationCodes | TP277 |
ContentType | Journal Article |
Copyright | Copyright © Wanfang Data Co. Ltd. All Rights Reserved. |
Copyright_xml | – notice: Copyright © Wanfang Data Co. Ltd. All Rights Reserved. |
DBID | 2B. 4A8 92I 93N PSX TCJ |
DOI | 10.16183/j.cnki.jsjtu.2022.423 |
DatabaseName | Wanfang Data Journals - Hong Kong WANFANG Data Centre Wanfang Data Journals 万方数据期刊 - 香港版 China Online Journals (COJ) China Online Journals (COJ) |
DatabaseTitleList | |
DeliveryMethod | fulltext_linktorsrc |
Discipline | Sciences (General) |
DocumentTitle_FL | Industrial Process Fault Detection Based on Incremental Isometric Mapping and Double Local Density Method |
EndPage | 533 |
ExternalDocumentID | shjtdxxb202404012 |
GrantInformation_xml | – fundername: (国家自然科学基金); (国家自然科学基金) funderid: (国家自然科学基金); (国家自然科学基金) |
GroupedDBID | -03 2B. 4A8 5XA 5XD 92I 93N ABJNI ACGFS ALMA_UNASSIGNED_HOLDINGS CCEZO CEKLB CW9 GROUPED_DOAJ PSX TCJ TGT U1G U5M UY8 |
ID | FETCH-wanfang_journals_shjtdxxb2024040123 |
ISSN | 1006-2467 |
IngestDate | Thu May 29 03:56:07 EDT 2025 |
IsPeerReviewed | false |
IsScholarly | true |
Issue | 4 |
Keywords | 流形学习 local density 局部密度 isometric mapping(ISOMAP) 等距映射 fault detection 故障检测 dynamic 动态性 manifold learning |
Language | Chinese |
LinkModel | OpenURL |
MergedId | FETCHMERGED-wanfang_journals_shjtdxxb2024040123 |
ParticipantIDs | wanfang_journals_shjtdxxb202404012 |
PublicationCentury | 2000 |
PublicationDate | 2024 |
PublicationDateYYYYMMDD | 2024-01-01 |
PublicationDate_xml | – year: 2024 text: 2024 |
PublicationDecade | 2020 |
PublicationTitle | 上海交通大学学报 |
PublicationTitle_FL | Journal of Shanghai Jiaotong University |
PublicationYear | 2024 |
Publisher | 沈阳化工大学理学院,沈阳 110142 辽宁省化工过程工业智能化技术重点实验室,沈阳 110142%沈阳化工大学理学院,沈阳 110142 沈阳化工大学计算机科学与技术学院,沈阳 110142%沈阳化工大学计算机科学与技术学院,沈阳 110142 |
Publisher_xml | – name: 辽宁省化工过程工业智能化技术重点实验室,沈阳 110142%沈阳化工大学理学院,沈阳 110142 – name: 沈阳化工大学理学院,沈阳 110142 – name: 沈阳化工大学计算机科学与技术学院,沈阳 110142%沈阳化工大学计算机科学与技术学院,沈阳 110142 |
SSID | ssib051367860 ssib023167927 ssib002258139 ssj0040338 ssib001128960 ssib057620143 |
Score | 4.7669535 |
Snippet | TP277;... |
SourceID | wanfang |
SourceType | Aggregation Database |
StartPage | 525 |
Title | 基于增量式等距映射同双重局部密度方法的工业过程故障检测 |
URI | https://d.wanfangdata.com.cn/periodical/shjtdxxb202404012 |
Volume | 58 |
hasFullText | 1 |
inHoldings | 1 |
isFullTextHit | |
isPrint | |
link | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnR1daxNB8Kj1xRexfuA3RVywSGKyd3u3-7h3uVAEBaFC38pdLrWtEMGkUPpUsFqk1fpSkeIXitIX8QupFsE_00ubf-HM7LU5TMHqyzHZnZ3Py-7scjNrWRcTwb04ikQhiRKv4NilqBCVIlVQUkWJ8jivJ5iNfO26O3zTuToqRvsOfMl9tTTdiou12T3zSv7Hq9AGfsUs2X_w7C5RaAAY_AtP8DA89-VjFgqmqszXLHTwKUNs0ZwpABSDfb6sYosfEOAxXWFSsVAy32OqwkKXKcl0iXBKTDpEEIAAARiCgKFTIZwyfhiBLTbTkngBjktdmmmXCLrMVwj4NlMCmSqdUQamWpCoEhtRjCoSR8Ekkz4NB74CWQCCCrBF28QUCEKXnw-mM1JSZ71A39hBOyRkibgI_Kk9Aiok5C7g4lgtdl46UtpFnVAinyRy0HiqmkeBwUrlUEjn7nqOrHWZ-SEJH4A7uj0uWt14CbQ0d-vsnLnw7mkr6cOZlGQIiabEEQEy6tqxVzGPnJfXUKGo8ELwoJfm5TLeoJw79i3juQ93zMUlO-uWkLn_p5NbhIRJJc_iGWEKjfQslS5M5rRW1hq3J4tTzanWdBF05UXHJID_UYa8OTHVSmZmYjQHTPx4sfdB7nllkTvGoBAcAh7l5nOrhcxVnuVYeUHx3ZBXYMlA2cWH7S83JSdNNOWUbNuks2YWyLL8Ufore8pO2XeN8ahxKxcojhyxDmc7vEFt_q4DVt_sxFFrIFtDm4OXskLvQ8esG-mrjc2Nx-mbl52F5fTn8taHh9vrL9rPXqef5tMnS-nyUmfhUfp5rnNvLf34IN143376o_11ZWt1Pl1_t_l9dfvXwtbaYnvlfmf1efvtXPvb4nFrqBqOBMOFTLaxbBppjvUY1j5h9TfuNOonrcE4smt1nmAp8XGnXq7Fjodbkpjj9Bpzecq68Hd6p_eDdMY6hLA5XDxr9bfuTtfPQbjdis-Tf38DyyOsjA |
linkProvider | Directory of Open Access Journals |
openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=%E5%9F%BA%E4%BA%8E%E5%A2%9E%E9%87%8F%E5%BC%8F%E7%AD%89%E8%B7%9D%E6%98%A0%E5%B0%84%E5%90%8C%E5%8F%8C%E9%87%8D%E5%B1%80%E9%83%A8%E5%AF%86%E5%BA%A6%E6%96%B9%E6%B3%95%E7%9A%84%E5%B7%A5%E4%B8%9A%E8%BF%87%E7%A8%8B%E6%95%85%E9%9A%9C%E6%A3%80%E6%B5%8B&rft.jtitle=%E4%B8%8A%E6%B5%B7%E4%BA%A4%E9%80%9A%E5%A4%A7%E5%AD%A6%E5%AD%A6%E6%8A%A5&rft.au=%E5%86%AF%E7%AB%8B%E4%BC%9F&rft.au=%E5%AD%99%E7%AB%8B%E6%96%87&rft.au=%E9%A1%BE%E6%AC%A2&rft.au=%E6%9D%8E%E5%85%83&rft.date=2024&rft.pub=%E6%B2%88%E9%98%B3%E5%8C%96%E5%B7%A5%E5%A4%A7%E5%AD%A6%E7%90%86%E5%AD%A6%E9%99%A2%2C%E6%B2%88%E9%98%B3+110142&rft.issn=1006-2467&rft.volume=58&rft.issue=4&rft.spage=525&rft.epage=533&rft_id=info:doi/10.16183%2Fj.cnki.jsjtu.2022.423&rft.externalDocID=shjtdxxb202404012 |
thumbnail_s | http://utb.summon.serialssolutions.com/2.0.0/image/custom?url=http%3A%2F%2Fwww.wanfangdata.com.cn%2Fimages%2FPeriodicalImages%2Fshjtdxxb%2Fshjtdxxb.jpg |