Industrial process fault detection based on IMDS-DLNS method
Aiming at the problem that when the multidimensional scaling (MDS) method is used to reduce the dimensionality of high-dimensional data,the new sample lacks the mapping matrix and cannot carry out low-dimensional embedding,an incremental multidimensional scaling (IMDS) method was proposed.Firstly,th...
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| Format: | Article |
| Language: | zho |
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Hebei University of Science and Technology
2022-06-01
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| Series: | Journal of Hebei University of Science and Technology |
| Subjects: | |
| Online Access: | http://xuebao.hebust.edu.cn/hbkjdx/ch/reader/create_pdf.aspx?file_no=b202203007&flag=1&journal_ |
| _version_ | 1797792670957961216 |
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| author | Liwei FENG Liwen SUN Huan GU Yuan LI |
| author_facet | Liwei FENG Liwen SUN Huan GU Yuan LI |
| author_sort | Liwei FENG |
| collection | DOAJ |
| description | Aiming at the problem that when the multidimensional scaling (MDS) method is used to reduce the dimensionality of high-dimensional data,the new sample lacks the mapping matrix and cannot carry out low-dimensional embedding,an incremental multidimensional scaling (IMDS) method was proposed.Firstly,the dual local nearest neighbor standardization (DLNS) technology was introduced to solve the problem of data having multiple centers and obvious variance differences after IMDS dimensionality reduction.Secondly,Hotelling T2</sup> statistics was used to monitor the process,and a fault detection method (IMDS-DLNS) with incremental multi-dimensional scale transformation and double local neighbor standardization was constructed.Finally,through numerical simulation of the process and penicillin fermentation process,the IMDS-DLNS method is compared with PCA,KPCA,FD-KNN and other methods,respectively.The results show that IMDS-DLNS has a higher fault detection rate compared to other methods.IMDS-DLNS method has good fault detection capabilities for multivariable and multimodal processes,and can guarantee product quality and production safety,which provides some reference for industrial process fault detection. |
| first_indexed | 2024-03-13T02:37:22Z |
| format | Article |
| id | doaj.art-6c603314f14145f697dda366c02bf1f2 |
| institution | Directory Open Access Journal |
| issn | 1008-1542 |
| language | zho |
| last_indexed | 2024-03-13T02:37:22Z |
| publishDate | 2022-06-01 |
| publisher | Hebei University of Science and Technology |
| record_format | Article |
| series | Journal of Hebei University of Science and Technology |
| spelling | doaj.art-6c603314f14145f697dda366c02bf1f22023-06-29T01:15:41ZzhoHebei University of Science and TechnologyJournal of Hebei University of Science and Technology1008-15422022-06-0143327728410.7535/hbkd.2022yx03007b202203007Industrial process fault detection based on IMDS-DLNS methodLiwei FENG0Liwen SUN1Huan GU2Yuan LI3College of Science,Shenyang University of Chemical Technology,Shenyang,Liaoning 110142,ChinaCollege of Computer Science and Technology,Shenyang University of Chemical Technology,Shenyang,Liaoning 110142,ChinaCollege of Computer Science and Technology,Shenyang University of Chemical Technology,Shenyang,Liaoning 110142,ChinaCollege of Science,Shenyang University of Chemical Technology,Shenyang,Liaoning 110142,ChinaAiming at the problem that when the multidimensional scaling (MDS) method is used to reduce the dimensionality of high-dimensional data,the new sample lacks the mapping matrix and cannot carry out low-dimensional embedding,an incremental multidimensional scaling (IMDS) method was proposed.Firstly,the dual local nearest neighbor standardization (DLNS) technology was introduced to solve the problem of data having multiple centers and obvious variance differences after IMDS dimensionality reduction.Secondly,Hotelling T2</sup> statistics was used to monitor the process,and a fault detection method (IMDS-DLNS) with incremental multi-dimensional scale transformation and double local neighbor standardization was constructed.Finally,through numerical simulation of the process and penicillin fermentation process,the IMDS-DLNS method is compared with PCA,KPCA,FD-KNN and other methods,respectively.The results show that IMDS-DLNS has a higher fault detection rate compared to other methods.IMDS-DLNS method has good fault detection capabilities for multivariable and multimodal processes,and can guarantee product quality and production safety,which provides some reference for industrial process fault detection.http://xuebao.hebust.edu.cn/hbkjdx/ch/reader/create_pdf.aspx?file_no=b202203007&flag=1&journal_other disciplines of automatic control technology; multi-modality; incremental multi-dimensional scale transformation; double local nearest neighbor standardization; fault detection |
| spellingShingle | Liwei FENG Liwen SUN Huan GU Yuan LI Industrial process fault detection based on IMDS-DLNS method Journal of Hebei University of Science and Technology other disciplines of automatic control technology; multi-modality; incremental multi-dimensional scale transformation; double local nearest neighbor standardization; fault detection |
| title | Industrial process fault detection based on IMDS-DLNS method |
| title_full | Industrial process fault detection based on IMDS-DLNS method |
| title_fullStr | Industrial process fault detection based on IMDS-DLNS method |
| title_full_unstemmed | Industrial process fault detection based on IMDS-DLNS method |
| title_short | Industrial process fault detection based on IMDS-DLNS method |
| title_sort | industrial process fault detection based on imds dlns method |
| topic | other disciplines of automatic control technology; multi-modality; incremental multi-dimensional scale transformation; double local nearest neighbor standardization; fault detection |
| url | http://xuebao.hebust.edu.cn/hbkjdx/ch/reader/create_pdf.aspx?file_no=b202203007&flag=1&journal_ |
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