A Principal Component Analysis Modeling Method for Cracking Reaction Furnace Temperature

A principal component analysis, cracking reaction technology, applied in the field of automatic industrial process control, can solve the problem of difficulty in modeling the temperature object of cracking furnace and other problems

Active Publication Date: 2020-04-24
HANGZHOU DIANZI UNIV
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  • Description
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Problems solved by technology

[0003] The object of the present invention is to solve the problem that the modeling process of the cracking furnace temperature object is relatively difficult, and provide a principal component analysis algorithm and a neural network structure parameter optimization model for the cracking furnace temperature by means of data collection, model establishment, and optimization. model method

Method used

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  • A Principal Component Analysis Modeling Method for Cracking Reaction Furnace Temperature
  • A Principal Component Analysis Modeling Method for Cracking Reaction Furnace Temperature
  • A Principal Component Analysis Modeling Method for Cracking Reaction Furnace Temperature

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Embodiment Construction

[0046] Taking the temperature of the cracking reactor as the actual object, taking the opening of the fuel valve as the input, and taking the temperature of the cracking reactor as the output, the model of the cracking reactor temperature is established.

[0047] The steps of the inventive method comprise:

[0048] Step 1. Collect the real-time operation data of the process and establish the improved neural network model of the process object. The specific steps are as follows:

[0049] 1-1. According to the established model and comprehensive principal component analysis method, the optimal solution for a given subset p is obtained in the following form:

[0050]

[0051] Among them, S is the covariance matrix of the data, S 2 The square of the covariance matrix, S P Select p×p subarrays of p variables in S in . To find the inverse of a matrix, tr() finds the trace of the matrix in parentheses.

[0052] Transform it into a minimization problem denoted as J 1 , of the...

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Abstract

The invention discloses a cracking reaction furnace temperature main component analysis modeling method. According to the method, by collecting the input and output data of a process object, and combining with a neural network model, an improved principal component analysis method is used for modeling, the network layer and the parameters of the neural network model are optimized by combining theimproved genetic algorithm operator, and the temperature prediction method of the cracking reaction furnace is obtained. The model established by the method has high accuracy, and the dynamic characteristics of the process object can be well described.

Description

technical field [0001] The invention belongs to the field of automatic industrial process control and relates to a principal component analysis modeling method for the temperature of a cracking reaction furnace. Background technique [0002] In the actual industrial process, because the physical or chemical properties of many complex actual process objects are unknown, system modeling is a very important part of advanced control technology. For example, the pyrolysis reactor is a kind of production equipment for the production of important chemical raw materials such as ethylene, and the production technology of important chemical raw materials such as ethylene is the embodiment of a country's chemical industry capabilities. The temperature control of the pyrolysis reactor is very important during production. The temperature of the pyrolysis reaction directly controls the production of the pyrolysis reactants and affects the quality and quantity of the pyrolysis products. A...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G05B13/04G05D23/32
CPCG05B13/048G05D23/32
Inventor 薛安克王建中胡德文张日东王俊宏张乐
Owner HANGZHOU DIANZI UNIV
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