Converter steelmaking process cost control method and system based on BP neural network

A BP neural network and converter steelmaking technology, which is applied in neural learning methods, biological neural network models, steel manufacturing processes, etc., can solve the problem of high cost of converter steelmaking and achieve the effect of high cost

Active Publication Date: 2016-11-16
CHONGQING UNIVERSITY OF SCIENCE AND TECHNOLOGY
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Problems solved by technology

[0006] In view of the above problems, the purpose of the present invention is to provide a method and system for optimizing the c

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  • Converter steelmaking process cost control method and system based on BP neural network
  • Converter steelmaking process cost control method and system based on BP neural network
  • Converter steelmaking process cost control method and system based on BP neural network

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[0032] In the following description, for purposes of explanation, numerous specific details are set forth in order to provide a thorough understanding of one or more embodiments. It may be evident, however, that these embodiments may be practiced without these specific details.

[0033] Aiming at the aforementioned problem of high cost in the iron and steel industry, the present invention proposes a cost optimization control method and system for converter steelmaking process based on BP neural network. The BP neural network method is used to dig out the potential law between raw material formula, operating parameters and steelmaking cost; and the intelligent optimization algorithm is used to use this law to obtain the operating parameters at the lowest cost, providing guidance for the optimal production of the actual production of the enterprise.

[0034] Among them, it should be noted that the BP (Back Propagation) neural network is a multi-layer feed-forward network trained...

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Abstract

The invention provides a converter steelmaking process cost optimal control method and system based on the BP neural network. The method comprises the steps that control parameters affecting the cost are selected according to a converter steelmaking process; a modeling sample set is established; a uniformization sample set is obtained; three layers of BP neural network algorithms are established; modeling is conducted on data obtained through converter steelmaking simulation experiments by adoption of the BP neural network algorithms, and neural network parameters are obtained; by use of a genetic algorithm, models established through the BP neural network algorithms are optimized, extremums of the established models are obtained, and optimal control parameters are determined according to the extremums of the established models; and the minimum cost value of the converter steelmaking process is determined according to the comparison results of obtained optimal control parameter cost values and the minimum cost values in the modeling sample set. The problem of the high cost of the converter steelmaking can be solved by use of the converter steelmaking process cost control method and system based on the BP neural network.

Description

technical field [0001] The present invention relates to the technical field of steelmaking, and more specifically, to a method and system for cost optimization control of converter steelmaking process based on BP neural network. Background technique [0002] At present, the iron and steel industry has entered a trough, and the industry's profits have been infinitely compressed. Only by reducing its own costs can it seek development. Therefore, reducing costs and increasing efficiency in the steel industry is the relentless pursuit of all steel mills. However, the high temperature, high risk and high cost of the iron and steel production process cannot be carried out on a large scale. [0003] Among them, the experimental basic oxygen furnace steelmaking method is a steelmaking process in which molten iron is smelted into molten steel. By supplying oxygen to the molten pool, an oxidation reaction occurs to reduce the carbon content of molten steel in the molten pool. This s...

Claims

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Application Information

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IPC IPC(8): C21C5/30G06N3/08
CPCC21C5/30C21C2300/06G06N3/084Y02P10/25
Inventor 张倩影耿讯辜小花李太福唐海红王坎
Owner CHONGQING UNIVERSITY OF SCIENCE AND TECHNOLOGY
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