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Industrial process fault diagnosis method based on information fusion

A fault diagnosis and industrial process technology, applied in the direction of program control, instrument, test/monitoring control system, etc., can solve problems such as inability to adapt, and achieve the effect of high fault diagnosis accuracy

Inactive Publication Date: 2020-08-25
NANJING UNIV OF SCI & TECH
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  • Abstract
  • Description
  • Claims
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Problems solved by technology

[0004] Due to the limitations of the above methods, a single method can no longer adapt to all possible problems in the actual production system of modern industry

Method used

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  • Industrial process fault diagnosis method based on information fusion
  • Industrial process fault diagnosis method based on information fusion
  • Industrial process fault diagnosis method based on information fusion

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Embodiment

[0048] The data of the industrial process comes from the chemical process simulation experiment of TE (Tennessee Eastman-Tennessee-Eastman) in the United States, and the prototype comes from the actual production process of Tennessee Eastman Chemical Company. TE process is a commonly used standard problem, which can better simulate some typical characteristics of actual complex industrial systems, so it is widely used in the research of typical chemical process fault diagnosis. The whole process includes 5 main units: reactor, condenser, compressor, steam separator and stripper. The whole TE process has 4 reactants, 2 products, an inert component and a by-product. The whole process contains a total of 53 state variables, which are 12 operating variables and 41 measurement variables, but only 52 state variables are actually used. Among them, 41 measured variables consist of 22 continuous measured variables (sampled by the system every 3 minutes) and 19 component measured varia...

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Abstract

The invention discloses an industrial process fault diagnosis method based on information fusion. A KPCA data processing method can be used for dealing with the nonlinear problem of data. Two machinelearning methods of SVM based on a statistical learning theory and SOM based on an artificial neural network are used to realize decision of a fault type, a D-S evidence theory is used to carry out information fusion on a decision result, and an obtained final diagnosis result has higher fault diagnosis precision. According to the invention, a plurality of methods are fused to replace an originalsingle method to process fault diagnosis of a complex industrial process, so that the multi-fault type diagnosis capability and the fault diagnosis precision are improved.

Description

technical field [0001] The invention belongs to the field of industrial process control, and in particular relates to an industrial process fault diagnosis method based on information fusion. Background technique [0002] With the development of modern production and the advancement of science and technology, modern industrial production equipment is becoming more and more large-scale, complex and automated. Since the actual industrial production process is extremely complex, there are many operating variables, and there are process data such as linear, nonlinear, Gaussian, and non-Gaussian, which makes the monitoring of this industrial process insufficient by using a single diagnostic method, making those occurrences Faults may go undiagnosed, which may adversely affect production safety, efficiency, and product quality. Therefore, a better diagnostic method that can accurately point out process faults has become one of the hot issues in the research of industrial producti...

Claims

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Application Information

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IPC IPC(8): G05B23/02
CPCG05B23/0243G05B2219/24065
Inventor 张胜杰周凌柯
Owner NANJING UNIV OF SCI & TECH
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