A Distributed Chemical Process Monitoring Method Based on Regularized GCCA Model

A chemical process, distributed technology, applied in the direction of program control, electrical test/monitoring, test/monitoring control system, etc.
CN111913461BActive Publication Date: 2022-03-18SHANDONG LONGSHENGHE CHEM CO LTD
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Patent Information

Authority / Receiving Office
CN Β· China
Patent Type
Patents(China)
Current Assignee / Owner
SHANDONG LONGSHENGHE CHEM CO LTD
Publication Date
2022-03-18

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Abstract

The invention discloses a distributed chemical process monitoring method based on a regularized GCCA model, which is used to solve the problem of distributed chemical process monitoring. The method of the present invention utilizes the involved regularized generalized canonical correlation analysis (GCCA) algorithm to simultaneously consider the commonality between variable blocks and the uniqueness within each block when implementing multi-block modeling, and can be applied to overlapping and non-overlapping variables at the same time Chunking mode. Compared with the traditional method, the regularized GCCA algorithm involved in the method of the present invention takes the common features between the variable sub-blocks into consideration through the square of the typical correlation coefficient, and further uses the least squares regression algorithm to describe the inter-block correlation features. relationship between. In addition, the method of the present invention also considers inter-block correlation features and intra-block features separately, and uses two comprehensive monitoring indicators to implement monitoring separately. Therefore, the method of the present invention is a more superior distributed chemical process operation state monitoring method.
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Description

technical field

[0001] The invention relates to a data-driven process monitoring method, in particular to a distributed chemical process monitoring method based on a regularized GCCA model. Background technique

[0002] The increasingly complex and large-scale development model of the modern chemical industrial production system pays more and more attention to the application of computer technology, advanced instrumentation technology, and artificial intelligence technology in management production, monitoring, scheduling and other issues. Nowadays, modern chemical process objects can store offline and measure massive sampling data online in real time. These data contain potentially useful information that can reflect the operating status of the production process, laying a solid data foundation for monitoring the operating status of the chemical process. In the past ten years, both academia and industry have invested a lot of manpower and material resources in researching d...

Claims

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