Polymerization reactor fault diagnosis method based on combination of DKPCA (dynamic kernel principal component analysis) and FDA (Fisher's discriminant analysis)

A technology of fault diagnosis and aggregation kettle, applied in special data processing applications, instruments, electrical digital data processing, etc., can solve problems such as economic loss, dynamic nonlinearity, large-scale accidents, etc., and achieve the effect of improving accuracy and efficiency

Inactive Publication Date: 2016-01-20
SHENYANG INSTITUTE OF CHEMICAL TECHNOLOGY
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Problems solved by technology

As a chemical product, PVC resin has a complex mechanism of faults in the production process, and there are serious dynamics and nonlinearities in the production process. large accident

Method used

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Examples

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Comparison scheme
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Embodiment Construction

[0015] The present invention will be described in detail below in conjunction with examples.

[0016] 1. First, construct the augmented matrix, and construct the augmented matrix containing the observed values ​​at the previous time by expanding each observed variable with the previous observations. The augmented matrix is ​​as follows:

[0017] (1)

[0018] 2. Obtain the dynamic kernel pivot under normal data and the dynamic kernel pivot of the data collected online through nuclear principal component analysis. Among them, the description of the nuclear principal component analysis calculation pivot is as follows:

[0019] via nonlinear mapping put the input space , mapped to the feature space superior. , in the feature space On, calculate the covariance matrix

[0020] (2)

[0021] by determining The eigenvectors can be obtained in the space the pivot in The eigenvectors of are directly related to the PCA of the input space.

[0022] (3)

[0023] in...

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Abstract

The present invention provides a polymerization reactor fault diagnosis method based on combination of DKPCA (dynamic kernel principal component analysis) and FDA (Fisher's discriminant analysis), and relates to a polymerization reactor fault diagnosis method. The method aims at features in a polyvinyl chloride (PVC) polymerization production process that the number of fault types is relatively large, the types are complex, and so on, and provides a polymerization reactor fault diagnosis method based on combination of DKPCA and FDA. Fault diagnosis is performed on a PVC polymerization process by using the kernel principal component analysis and the dynamic kernel principal component analysis algorithm separately, and meanwhile, further separation of the fault data is performed by using an FDA method. A simulation research result shows that the kernel principal component analysis has the relatively good fault diagnosis accuracy on the PVC polymerization process, and the FDA can further realize fault separation, so that faults can be monitored in an actual PVC polymerization production process.

Description

technical field [0001] The invention relates to a method for diagnosing a failure of a polymerization kettle, in particular to a method for diagnosing a failure of a polymerization process of a polymerization kettle integrated with DKPCA-FDA. Background technique [0002] Polyvinyl chloride resin (PVC) is an important organic synthetic material and a chemical product with multiple uses. Its products have good physical and chemical properties and are widely used in industry, construction, agriculture, electric power, public utilities and other fields . As a chemical product, PVC resin has a complex mechanism of faults in the production process, and there are serious dynamics and nonlinearities in the production process. large accident. Contents of the invention [0003] The purpose of the present invention is to provide an intelligent fault diagnosis method for the polymerization process of the polymerization kettle. The method adopts the method of combining DKPCA and FDA...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F19/00
Inventor 高淑芝吴晓峰郎丹张萌张国光
Owner SHENYANG INSTITUTE OF CHEMICAL TECHNOLOGY
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