Blast furnace ironmaking multi-objective intelligent optimization method based on adaptive genetic algorithm

A genetic algorithm and blast furnace ironmaking technology, applied in the field of multi-objective intelligent optimization of blast furnaces, can solve the problems of large fluctuations in product quality, low comprehensive energy efficiency, heavy environmental load, etc., to avoid local extremes, improve comprehensive energy efficiency, and efficiently and accurately take effect

Inactive Publication Date: 2019-11-01
ZHEJIANG UNIV
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Problems solved by technology

[0002] At present, the blast furnace ironmaking process faces problems such as heavy environmental load, low resource utilization rate, low overall energy efficiency, large fluctuations in product quality, and low product added value.

Method used

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  • Blast furnace ironmaking multi-objective intelligent optimization method based on adaptive genetic algorithm
  • Blast furnace ironmaking multi-objective intelligent optimization method based on adaptive genetic algorithm
  • Blast furnace ironmaking multi-objective intelligent optimization method based on adaptive genetic algorithm

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Embodiment Construction

[0039] Embodiments of the present invention will be further described below in conjunction with the accompanying drawings.

[0040] Take a domestic volume as 2650m 3 large blast furnace ( figure 1 ) as the object, a multi-objective intelligent optimization method for blast furnace ironmaking based on adaptive population genetic algorithm is described, the method has the following steps:

[0041] 1. For ironmaking data preprocessing, the data is standardized and normalized through data cleaning. Data preprocessing includes the data cleaning process, eliminating abnormal values, deleting invalid values, and aligning the time axis.

[0042] 2. Model the blast furnace ironmaking process, and use the deep learning method to establish a virtual model of the physical object. The blast furnace modeling method is:

[0043] (2.1) Select the input and output variables of the blast furnace based on the correlation analysis and the furnace manager’s operating experience, and determine th...

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Abstract

The invention discloses a blast furnace ironmaking multi-objective intelligent optimization method based on an adaptive genetic algorithm. According to the self-adaptive genetic algorithm, the population fitness skewness coefficient is continuously calculated in the iteration process. The population scale is automatically updated according to the change trend of the population fitness skewness coefficient so as to obtain the optimal search performance. The method is applied to blast furnace ironmaking process index multi-objective optimization. Aiming at different crude fuel qualities, production conditions and market conditions, a factory has different requirements on various indexes of the blast furnace. The fitness function of the genetic algorithm is solved by setting the weight of each index through the furnace length. The population size is automatically updated according to the positive and negative change trend of the fitness function in the evolution process so as to ensure that the algorithm has the optimal optimization performance. By applying the self-adaptive genetic algorithm to the ironmaking process, the problem of multi-target optimization of mutual coupling of blast furnaces can be effectively solved. Compared with a traditional optimization algorithm, the method has the advantages that local extremum can be effectively avoided, and a globally optimal solutioncan be efficiently and accurately solved.

Description

technical field [0001] The invention belongs to the field of industrial process modeling, simulation and optimization, in particular to a blast furnace multi-objective intelligent optimization method based on adaptive genetic algorithm. Background technique [0002] At present, the blast furnace ironmaking process faces problems such as heavy environmental load, low resource utilization rate, low comprehensive energy efficiency, large fluctuations in product quality, and low product added value. Therefore, the research and development of multi-objective intelligent optimization technology for the key elements of the ironmaking process under the mass customization production mode is the only way to realize the green and intelligent blast furnace ironmaking process. The connotation of the collaborative optimization of key elements of the ironmaking process is multi-process function repositioning, interface technology, and narrow-window control of the entire process. The expect...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/04G06N3/12G06N3/08G06N3/04
CPCG06Q10/04G06N3/126G06N3/08G06N3/045
Inventor 周恒杨春节
Owner ZHEJIANG UNIV
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