Application of Improved Rough Set Reduction Algorithm in On-line Fault Diagnosis of Chemical Equipment

Application of Improved Rough Set Reduction Algorithm in On-line Fault Diagnosis of Chemical Equipment

The application of improved rough set reduction algorithm in Chemical Equipment on-line fault diagnosis is discussed. The rough set association degree is applied to attribute association degree matrix, and the improved rough set reduction algorithm is obtained, and the application scope of this meth...

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Main Authors: Chengzhang Ji, Shanqun Lu
Format: Article
Language:English
Published: AIDIC Servizi S.r.l. 2018-12-01
Series:Chemical Engineering Transactions
Online Access:https://www.cetjournal.it/index.php/cet/article/view/9498
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spelling doaj-ebbb17cc3d4341c3921455e407a5b8762021-02-16T21:11:14ZengAIDIC Servizi S.r.l.Chemical Engineering Transactions2283-92162018-12-017110.3303/CET1871215Application of Improved Rough Set Reduction Algorithm in On-line Fault Diagnosis of Chemical EquipmentChengzhang JiShanqun LuThe application of improved rough set reduction algorithm in Chemical Equipment on-line fault diagnosis is discussed. The rough set association degree is applied to attribute association degree matrix, and the improved rough set reduction algorithm is obtained, and the application scope of this method in Chemical Equipment online fault diagnosis is studied. The results show that the improved rough set reduction algorithm is a new data mining method, which can effectively solve the problem of attribute classification of equipment in online fault diagnosis. Therefore, the improved rough set reduction algorithm can quickly and effectively diagnose on-line faults in Chemical Equipment system and eliminate the corresponding faults in time.https://www.cetjournal.it/index.php/cet/article/view/9498
collection DOAJ
language English
format Article
sources DOAJ
author Chengzhang Ji
Shanqun Lu
spellingShingle Chengzhang Ji
Shanqun Lu
Application of Improved Rough Set Reduction Algorithm in On-line Fault Diagnosis of Chemical Equipment
Chemical Engineering Transactions
author_facet Chengzhang Ji
Shanqun Lu
author_sort Chengzhang Ji
title Application of Improved Rough Set Reduction Algorithm in On-line Fault Diagnosis of Chemical Equipment
title_short Application of Improved Rough Set Reduction Algorithm in On-line Fault Diagnosis of Chemical Equipment
title_full Application of Improved Rough Set Reduction Algorithm in On-line Fault Diagnosis of Chemical Equipment
title_fullStr Application of Improved Rough Set Reduction Algorithm in On-line Fault Diagnosis of Chemical Equipment
title_full_unstemmed Application of Improved Rough Set Reduction Algorithm in On-line Fault Diagnosis of Chemical Equipment
title_sort application of improved rough set reduction algorithm in on-line fault diagnosis of chemical equipment
publisher AIDIC Servizi S.r.l.
series Chemical Engineering Transactions
issn 2283-9216
publishDate 2018-12-01
description The application of improved rough set reduction algorithm in Chemical Equipment on-line fault diagnosis is discussed. The rough set association degree is applied to attribute association degree matrix, and the improved rough set reduction algorithm is obtained, and the application scope of this method in Chemical Equipment online fault diagnosis is studied. The results show that the improved rough set reduction algorithm is a new data mining method, which can effectively solve the problem of attribute classification of equipment in online fault diagnosis. Therefore, the improved rough set reduction algorithm can quickly and effectively diagnose on-line faults in Chemical Equipment system and eliminate the corresponding faults in time.
url https://www.cetjournal.it/index.php/cet/article/view/9498
work_keys_str_mv AT chengzhangji applicationofimprovedroughsetreductionalgorithminonlinefaultdiagnosisofchemicalequipment
AT shanqunlu applicationofimprovedroughsetreductionalgorithminonlinefaultdiagnosisofchemicalequipment
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