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Metallurgical enterprise converter gas scheduling method based on knowledge

A converter gas and scheduling method technology, applied in the field of information

Active Publication Date: 2017-05-10
DALIAN UNIV OF TECH +1
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  • Abstract
  • Description
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AI Technical Summary

Problems solved by technology

[0005] The technical problem to be solved by the present invention is the problem of balance scheduling of converter gas in existing metallurgical enterprises

Method used

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  • Metallurgical enterprise converter gas scheduling method based on knowledge
  • Metallurgical enterprise converter gas scheduling method based on knowledge
  • Metallurgical enterprise converter gas scheduling method based on knowledge

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Embodiment Construction

[0022] In order to better understand the technical solution of the present invention, the embodiment of the present invention will be further described by taking the converter gas system of Baosteel Iron and Steel Enterprise, which has a relatively high level of automation in China, as an example. The company's converter gas system currently has 6 converters as converter gas generating units, which generate about 200km per hour 3 There are about 30 main consumers of converter gas, mainly including blast furnaces, hot and cold rolling, lime kilns, etc.; in addition, there are generator sets, three 70-ton low-pressure boilers and one thermoelectric unit as gas regulating users ; The pipe network is equipped with four 80,000 m 3 gas cabinet. Although the on-site gas dispatchers use the real-time monitoring and counter alarm mechanism to judge the current production and consumption of the gas pipeline network through manual decision-making, and formulate the current adjustment pl...

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Abstract

The invention provides a metallurgical enterprise converter gas scheduling method based on knowledge. The method comprises steps: firstly, as for a procedure variable which is needed in a scheduling decision process but can not be acquired directly, a neural network model is adopted for modeling analysis, and a neural network model based on data is formed; secondly, a production rule model based on fuzzy clustering is designed, through carrying out clustering analysis and association rule mining on historical data, knowledge information contained in the data is mined, fusion with expert prior knowledge is further carried out, and a production model based on knowledge is built; and finally, an online updating strategy for the production rule model is designed, if large deviation exists between a reasoning result and a practical solution, the output parameters of the production rule are updated. By using the method of the invention, the balance state of a converter gas system can be dynamically analyzed, a corresponding scheduling scheme can be obtained, and decision by the scheduling person can be reasonably guided.

Description

technical field [0001] The invention belongs to the field of information technology, relates to big data analysis, knowledge extraction and fuzzy reasoning modeling, and is a knowledge-based method for balance scheduling of converter gas in metallurgical enterprises. The present invention utilizes scheduling experience knowledge and a large amount of historical data existing on the metallurgical enterprise site to design a production rule model based on fuzzy clustering. The prior knowledge of experts is integrated to establish a knowledge-based gas dispatching model, so as to effectively guide the on-site dispatchers to carry out balanced dispatching of the converter gas system. This method can be widely used in other energy medium systems of metallurgical enterprises. Background technique [0002] Metallurgical enterprises are industries with high energy consumption, high pollution and high emissions. Energy saving and consumption reduction has always been one of the mos...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06N5/04G06F17/50
CPCG06N5/048G06F30/20G06F2111/10
Inventor 吕政赵珺刘颖盛春阳王伟冯为民汪晶
Owner DALIAN UNIV OF TECH
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