Multimode Process Monitoring Method Based on Multiblock Projection Nonnegative Matrix Factorization
A multimode process monitoring method based on multiblock projection nonnegative matrix factorization (MPNMF) is proposed for traditional process monitoring methods which often adopt global model of data and ignore local information of data. Firstly, the training data set of each mode is partitioned...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2020-01-01
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| Series: | Advances in Mathematical Physics |
| Online Access: | http://dx.doi.org/10.1155/2020/4610493 |
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| author | Yan Wang Yu-Bo Zhao Chuang Li Chuan-Qian Zhu Shuai-shuai Han Xiao-Guang Gu |
| author_facet | Yan Wang Yu-Bo Zhao Chuang Li Chuan-Qian Zhu Shuai-shuai Han Xiao-Guang Gu |
| author_sort | Yan Wang |
| collection | DOAJ |
| description | A multimode process monitoring method based on multiblock projection nonnegative matrix factorization (MPNMF) is proposed for traditional process monitoring methods which often adopt global model of data and ignore local information of data. Firstly, the training data set of each mode is partitioned by the complete link algorithm and the multivariate data space is divided into several subblocks. Then, the projection nonnegative matrix factorization (PNMF) algorithm is used to model each subspace of each mode separately. A joint probabilistic statistic index is defined to identify the running modes of the process data. Finally, the Bayesian information criterion (BIC) is used to synthesize the statistics of each subblock and construct a new statistic for process monitoring. The proposed process monitoring method is applied to the TE process to verify its effectiveness. |
| format | Article |
| id | doaj-art-b0fb13dab09d4ff09cece2d55dbaf4da |
| institution | OA Journals |
| issn | 1687-9120 1687-9139 |
| language | English |
| publishDate | 2020-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Advances in Mathematical Physics |
| spelling | doaj-art-b0fb13dab09d4ff09cece2d55dbaf4da2025-08-20T02:23:36ZengWileyAdvances in Mathematical Physics1687-91201687-91392020-01-01202010.1155/2020/46104934610493Multimode Process Monitoring Method Based on Multiblock Projection Nonnegative Matrix FactorizationYan Wang0Yu-Bo Zhao1Chuang Li2Chuan-Qian Zhu3Shuai-shuai Han4Xiao-Guang Gu5School of Electrical and Information Engineering, Zhengzhou University of Light Industry, Zhengzhou 450002, ChinaSchool of Electrical and Information Engineering, Zhengzhou University of Light Industry, Zhengzhou 450002, ChinaSchool of Electrical and Information Engineering, Zhengzhou University of Light Industry, Zhengzhou 450002, ChinaSchool of Electrical and Information Engineering, Zhengzhou University of Light Industry, Zhengzhou 450002, ChinaSchool of Electrical and Information Engineering, Zhengzhou University of Light Industry, Zhengzhou 450002, ChinaIntelligent Manufacturing Big Data Platform (Zhengzhou) R&D Center, Zhengzhou Normal University, Zhengzhou 450044, ChinaA multimode process monitoring method based on multiblock projection nonnegative matrix factorization (MPNMF) is proposed for traditional process monitoring methods which often adopt global model of data and ignore local information of data. Firstly, the training data set of each mode is partitioned by the complete link algorithm and the multivariate data space is divided into several subblocks. Then, the projection nonnegative matrix factorization (PNMF) algorithm is used to model each subspace of each mode separately. A joint probabilistic statistic index is defined to identify the running modes of the process data. Finally, the Bayesian information criterion (BIC) is used to synthesize the statistics of each subblock and construct a new statistic for process monitoring. The proposed process monitoring method is applied to the TE process to verify its effectiveness.http://dx.doi.org/10.1155/2020/4610493 |
| spellingShingle | Yan Wang Yu-Bo Zhao Chuang Li Chuan-Qian Zhu Shuai-shuai Han Xiao-Guang Gu Multimode Process Monitoring Method Based on Multiblock Projection Nonnegative Matrix Factorization Advances in Mathematical Physics |
| title | Multimode Process Monitoring Method Based on Multiblock Projection Nonnegative Matrix Factorization |
| title_full | Multimode Process Monitoring Method Based on Multiblock Projection Nonnegative Matrix Factorization |
| title_fullStr | Multimode Process Monitoring Method Based on Multiblock Projection Nonnegative Matrix Factorization |
| title_full_unstemmed | Multimode Process Monitoring Method Based on Multiblock Projection Nonnegative Matrix Factorization |
| title_short | Multimode Process Monitoring Method Based on Multiblock Projection Nonnegative Matrix Factorization |
| title_sort | multimode process monitoring method based on multiblock projection nonnegative matrix factorization |
| url | http://dx.doi.org/10.1155/2020/4610493 |
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