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A Fault Variable Isolation Method Based on Nested Iterative Fisher Discriminant Analysis

A Fisher discriminant and iterative technique, applied in instrumentation, electrical testing/monitoring, control/regulating systems, etc., which can solve problems such as unreported research, inability to decompose and extract potential information of process data, and singularity of intra-class scatter matrix.

Active Publication Date: 2017-06-06
ZHEJIANG UNIV
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Problems solved by technology

However, when the online fault diagnosis method based on the traditional Fisher discriminant analysis is applied to the actual chemical process, there are three problems: first, the chemical process data is often highly coupled, which may lead to the singularity of the intra-class scatter matrix, so that it cannot Carry out singular value decomposition to extract potential information of process data
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  • A Fault Variable Isolation Method Based on Nested Iterative Fisher Discriminant Analysis
  • A Fault Variable Isolation Method Based on Nested Iterative Fisher Discriminant Analysis
  • A Fault Variable Isolation Method Based on Nested Iterative Fisher Discriminant Analysis

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Embodiment Construction

[0092] The present invention will be described in further detail below in conjunction with the accompanying drawings and specific examples.

[0093] Taking the Tennessee-Eastman process as an example, the Tennessee-Eastman process is a typical complex chemical production process. The process consists of five main operating mechanisms, namely reactor, product condenser, vapor-liquid separator, circulation Compressor and product stripper. During the whole process, two parts of process variables can be collected: 41 measured variables and 11 manipulated variables. Variables are shown in Tables 1 and 2.

[0094] Table 1 Tennessee-Eastman Process Measured Variables Table

[0095] serial number variable name serial number variable name serial number variable name 1 A component feed flow 2 D component feed flow 3 E component feed flow 4 A and C component feed flow 5 circulation flow 6 Reactor feed flow 7 Reactor pressure 8 Reacto...

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Abstract

The invention discloses a nested iterative fisher discriminant analysis-based fault diagnosis isolation method. According to the method, potential information included in process data is fully mined, and variables with effects of different extents on a fault can be effectively distinguished, so that discrimination model is established according to different types respectively, the model precision is improved, the performance of on-line fault diagnosis is greatly improved, the reliability and the credibility of actual on-line fault diagnosis are enhanced, accurate repair of the fault by an industrial engineer is facilitated, and thus safe and reliable operation of actual production and high-quality pursuit of products are guaranteed.

Description

technical field [0001] The invention belongs to the field of chemical process statistical monitoring, in particular to a fault variable isolation method based on nested iterative Fisher discriminant analysis. Background technique [0002] As an important production method in industrial production, chemical process is closely related to people's life, and has been widely used in metallurgy, oil refining, papermaking, leather making and other fields. How to ensure the safety of chemical process production, improve product quality and economic benefits is the focus of attention. With the increasingly complex chemical process, online fault detection and diagnosis are becoming more and more important. Fault diagnosis refers to further judging what kind of fault has occurred after the fault is detected. The fault variable isolation can be used to identify the types of faults that occur, to ensure the safe and reliable operation of production and the high quality of products, so ...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G05B23/02
CPCG05B23/0254
Inventor 赵春晖李文卿
Owner ZHEJIANG UNIV
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