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Cement firing coal consumption detection method and system based on random forest model

A random forest model and detection method technology, applied in computer parts, character and pattern recognition, complex mathematical operations, etc., can solve problems such as large lag nonlinearity and difficult mathematical models

Pending Publication Date: 2021-01-05
YANSHAN UNIV
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  • Application Information

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Problems solved by technology

[0004] Since the cement firing system itself has the characteristics of large hysteresis, nonlinearity, time-varying time-delay and strong coupling between variables, it is difficult to establish an accurate mathematical model for it.

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  • Cement firing coal consumption detection method and system based on random forest model
  • Cement firing coal consumption detection method and system based on random forest model
  • Cement firing coal consumption detection method and system based on random forest model

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Embodiment Construction

[0038] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some, not all, embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.

[0039] The purpose of the present invention is to provide a cement burning coal consumption detection method and system based on a random forest model, which solves the strong coupling relationship and hysteresis among multiple variables and improves the detection efficiency of coal consumption.

[0040] In order to make the above objects, features and advantages of the present invention more comprehensible, the present invention will be further described in de...

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Abstract

The invention relates to a cement firing coal consumption detection method and system based on a random forest model. The method comprises the following steps: collecting a data set; wherein the dataset comprises coal consumption and industrial parameters related to the coal consumption; building a random forest model according to the data set; taking the industrial parameters as input and the coal consumption as output, and training the random forest model by constructing a CART regression tree model; and inputting to-be-predicted industrial parameters into the trained random forest model toobtain output coal consumption. According to the invention, the strong coupling relationship and hysteresis quality among multiple variables are solved, and the coal consumption detection efficiencyis improved.

Description

technical field [0001] The invention relates to the technical field of cement firing, in particular to a method and system for detecting coal consumption in cement firing based on a random forest model. Background technique [0002] The cement firing system is a very important part of cement production. According to the relevant data of the cement industry, my country's cement production ranks in the forefront of the world. In the process of cement production, coal consumption is a very important indicator. Effectively predicting coal consumption indicators and realizing online prediction of coal consumption indicators are of great significance for improving cement production efficiency and even improving the national economic level. However, because the firing system in the cement production process, especially the rotary kiln, has the characteristics of nonlinearity and strong coupling, it is difficult to establish a coal consumption index prediction model for the cement f...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62G06F17/11
CPCG06F17/11G06F18/24323G06F18/214
Inventor 郝晓辰高勇赵彦涛冀亚坤杨旭年张策
Owner YANSHAN UNIV