Online prediction method for iron ore sintering bed permeability states

A technology of air permeability and material layer, which is applied in the field of online prediction of air permeability state of sintered material layer, can solve problems such as poor effect, and achieve good learning ability and generalization ability, classification method and scientific modeling idea.

Active Publication Date: 2016-10-12
CENT SOUTH UNIV
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Problems solved by technology

JasbirKhosa et al. from Queensland Advanced Technology Center in Australia predicted the air permeability of iron ore after granulation through particle size distributio

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  • Online prediction method for iron ore sintering bed permeability states
  • Online prediction method for iron ore sintering bed permeability states
  • Online prediction method for iron ore sintering bed permeability states

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Embodiment Construction

[0041] The present invention will be further described below with reference to the accompanying drawings and embodiments.

[0042] The method of the present invention adopts the state parameters and operation parameters as input, and adopts the method of cluster analysis to judge the air permeability state of the material layer; This predicts the state of the permeability of the sintered layer, and the relationship between the parameters is as follows: figure 1 shown.

[0043] An online prediction method for the air permeability state of an iron ore sintered material layer, the specific steps are as follows:

[0044] Step 1: The production data such as the speed of the trolley or the frequency of the main exhaust fan (selected by the sintering machine using the variable frequency fan), the exhaust gas temperature of the middle and rear bellows (the fitting curve calculates the sintering end point and the end point temperature) and other production data are built into the mate...

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Abstract

The invention discloses an online prediction method for iron ore sintering bed permeability states. According to the method, a fuzzy clustering algorithm is employed; a trolley speed, a sintering end point and an end point temperature are taken as input data; the sintering bed permeability states are classified into five classes; a prediction model for the sintering bed permeability states is established by employing a support vector machine method according to history data of mixture particle size distribution, mixture moisture, a solid fuel proportion, bed thickness, mixture temperature, negative pressure of an ignition furnace and negative pressure of a 1# wind box, and the corresponding permeability state data; and the bed permeability states are predicted by employing the prediction model according to the online detection data of the mixture particle size distribution, the mixture moisture, the solid fuel proportion, the bed thickness, the mixture temperature, the negative pressure of the ignition furnace and the negative pressure of the 1# wind box. The method is scientific and reasonable. Through application of the method, the prediction result is accurate, and the hit rate reaches 87.5%.

Description

technical field [0001] The technology of the invention belongs to the field of iron ore sintering, and provides an online prediction method for the gas permeability state of a sintered material layer. Background technique [0002] The fluctuating state and changing law of the gas in the iron ore sintering material layer are related to the mass transfer, heat transfer and physical and chemical reaction progress of the sintering process. The gas permeability state of the material layer has an important influence on the antegrade of the sintering process, as well as the yield, quality and energy consumption of the sintered ore. Therefore, it is of great significance to realize the comprehensive evaluation and online identification of the gas permeability state of the sintered layer to guide the actual production. [0003] The sintering air permeability is divided into the original material layer air permeability and the sintering process air permeability. The typical evaluati...

Claims

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Application Information

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IPC IPC(8): G06K9/62G06N3/12C22B1/16
CPCG06N3/126C22B1/16G06F18/23213
Inventor 陈许玲范晓慧甘敏黄晓贤袁礼顺姜涛李光辉郭宇峰杨永斌李骞张元波朱忠平黄柱成许斌彭志伟徐斌杨凌志张鑫杨桂明赵新泽
Owner CENT SOUTH UNIV
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