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Prediction method of calcium yield during calcium processing based on deep neural network

A technology of deep neural network and prediction method is applied in the field of yield prediction, which can solve the problems of inability to predict the yield of calcium treatment process, control of calcium content within a certain range, and unstable control of calcium content, so as to improve production efficiency. And the effect of product quality, reduction of production cost, and reduction of nozzle nodules

Active Publication Date: 2022-03-11
YANSHAN UNIV +1
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Problems solved by technology

Therefore, it is difficult for calcium alloy to be added to molten steel, and it is difficult to control the calcium content in molten steel within a certain range during the calcium treatment process.
For most iron and steel enterprises, the calcium treatment process is based on experience to feed calcium, and the yield rate of the calcium treatment process cannot be predicted, so the control of calcium content is unstable

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  • Prediction method of calcium yield during calcium processing based on deep neural network
  • Prediction method of calcium yield during calcium processing based on deep neural network
  • Prediction method of calcium yield during calcium processing based on deep neural network

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Embodiment Construction

[0040] Exemplary embodiments, features, and aspects of the present invention will be described in detail below with reference to the accompanying drawings. The same reference numbers in the figures indicate functionally identical or similar elements. While various aspects of the embodiments are shown in drawings, the drawings are not necessarily drawn to scale unless specifically indicated.

[0041] According to an embodiment of the present invention, a method for predicting the yield of calcium in a molten steel calcium treatment process based on a deep neural network is provided.

[0042] Such as figure 1 As shown, the method for predicting the yield of calcium in the calcium processing process based on the deep neural network according to the embodiment of the present invention comprises the following steps:

[0043]Step 1: Obtain in advance the production and operation data of steel grades that have adopted calcium treatment technology in a domestic factory in the past y...

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Abstract

The invention discloses a method for predicting the yield of calcium in the calcium treatment process based on a deep neural network, and relates to the calcium treatment process of molten steel refining in the field of iron and steel metallurgy, which includes the following steps: obtaining the production of each heat in advance and operating data information to construct a data set; train and test the deep neural network based on the constructed data set, and establish a prediction model; based on the prediction model, the actual production and operation data information of each furnace is used as input to predict and calculate the current calcium harvest Rate. The invention can predict the yield rate of calcium in the calcium treatment process, which is beneficial to accurately control the calcium content in steel, stably control the calcium treatment process, improve the calcium treatment effect, improve product quality, and ensure production stability.

Description

technical field [0001] The invention belongs to the field of molten steel refining in iron and steel metallurgy, and in particular relates to a method for predicting the yield of calcium in the calcium treatment process based on a deep neural network. Background technique [0002] In the smelting process of molten steel, in order to effectively reduce the oxygen content in molten steel to a low level, aluminum is widely used as a strong deoxidizer in the steelmaking process. However, the addition of aluminum will generate a large number of alumina inclusions, which will easily lead to nodulation at the nozzle, affect the continuous casting process and lead to a decline in product performance. Therefore, metal calcium is added to the molten steel to modify the alumina inclusions in the molten steel into liquid calcium aluminate, reduce nozzle nodules, ensure smooth continuous casting, and improve product quality. At the same time, the presence of calcium in steel can also co...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F30/27G16C20/10G16C20/30G16C20/70G06N3/08C21C7/00G06F111/06G06F113/08
CPCG06F30/27G16C20/10G16C20/30G16C20/70G06N3/08C21C7/0056G06F2113/08G06F2111/06G06N3/09G06N3/084G06N3/0499
Inventor 张立峰王伟健任强任英罗艳
Owner YANSHAN UNIV
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