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Non-Gaussian process monitoring method based on multi-variable block interleaving correlation elimination

A cross-correlation and process monitoring technology, applied in the field of non-Gaussian process monitoring based on multi-variable block cross-correlation elimination, can solve problems such as cross-correlation cannot be taken into account

Active Publication Date: 2018-08-07
NINGBO UNIV
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Problems solved by technology

Therefore, according to the method of dividing the production unit into variable sub-blocks, and then directly building multiple distributed process monitoring models, the cross-correlation between different production units cannot be taken into account.
Therefore, the traditional distributed non-Gaussian process monitoring method needs to be further improved

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  • Non-Gaussian process monitoring method based on multi-variable block interleaving correlation elimination
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  • Non-Gaussian process monitoring method based on multi-variable block interleaving correlation elimination

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Embodiment Construction

[0066] The method of the present invention will be described in detail below in conjunction with the accompanying drawings and specific examples of implementation.

[0067] Such as figure 1 As shown, a fault monitoring method based on multi-unit variable cross-correlation decoupling strategy. The specific implementation process of the method of the present invention and its superiority over the traditional ICA-based non-Gaussian process monitoring method will be described below in conjunction with an example of a specific industrial process.

[0068] The application object is from Tennessee-Eastman (TE) chemical process experiment, and the prototype is an actual process flow of Eastman chemical production workshop. Such as figure 2 As shown, the production flow of the TE process is relatively complex, including five main production units: reactor, condenser, separation tower, stripping tower, and compressor. The TE process has been widely used in fault monitoring research ...

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Abstract

The invention discloses a non-Gaussian process monitoring method based on multi-variable block interleaving correlation elimination, and aims to take interleaving correlation into a distributed process modeling and process monitoring, thereby applying more reliable and effective distributed non-Gaussian process monitoring. The method comprises the steps of dividing all measuring variables into a plurality of variable sub-blocks according to ownership of the variable which is measured by each production unit; secondly, eliminating interleaving correlation information between each variable sub-block and other variable sub-block by means of a regression model; and finally, performing modeling based on an independent component analysis algorithm and non-Gaussian process monitoring by means ofthe error after interleaving correlation elimination. Compared with a traditional method, the method of the invention is mainly advantageous in that the regression model is utilized for taking the interleaving correlation between different multi-variable sub-blocks is considered, and the error after interleaving correlation elimination is used as a new monitoring object.

Description

technical field [0001] The invention relates to a data-driven process monitoring method, in particular to a non-Gaussian process monitoring method based on multivariable block cross-correlation elimination. Background technique [0002] Real-time monitoring of the operating status of the production process is of great significance to ensure production safety and product quality stability. The process monitoring technology usually adopted in production practice is the well-known fault monitoring method, which aims to identify abnormalities in the system in a timely manner. state. In recent years, with the advancement of large-scale industrialization and "big data" construction, a large amount of sample data can be easily collected during the production process, but it is impossible to establish an accurate mechanism model for it. In this application background, the traditional fault monitoring method based on the mechanism model has encountered a development bottleneck, whil...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G05B19/418
CPCG05B19/41885G05B2219/32339Y02P90/02
Inventor 潘茂湖童楚东俞海珍
Owner NINGBO UNIV
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