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Predicting method of material grain size distribution in ball-milling process

A particle size distribution and material technology, applied in neural learning methods, biological neural network models, special data processing applications, etc., can solve problems such as complex dynamic characteristics of the process, time-varying and complex ore sources, and inability to guarantee long-term prediction accuracy

Active Publication Date: 2017-06-20
CENT SOUTH UNIV
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Problems solved by technology

However, domestic ore sources are complex, and the dynamic characteristics of the process are complex, changeable, and time-varying. If the prediction model cannot be corrected online, its prediction accuracy cannot be guaranteed for a long time

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  • Predicting method of material grain size distribution in ball-milling process
  • Predicting method of material grain size distribution in ball-milling process
  • Predicting method of material grain size distribution in ball-milling process

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Embodiment Construction

[0015] The specific implementation manners of the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. The following examples are used to illustrate the present invention, but are not intended to limit the scope of the present invention.

[0016] Aiming at the shortcomings of insufficient prediction of particle size distribution of ball milling materials in the prior art and inability to correct the prediction results on-line, the present invention proposes a method for predicting particle size distribution of ball milling materials.

[0017] figure 1 A schematic flow chart of a method for predicting material particle size distribution in a ball milling process according to an embodiment of the present invention is shown, as can be seen from the figure, including:

[0018] S1. Based on the crushing distribution function of the material, the continuous crushing rate function and the residence time distributi...

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Abstract

The invention provides a predicting method of material grain size distribution in a ball-milling process. The method comprises the following steps: acquiring a material grain size distribution predicting model of continuous ore grinding based on a crushing distribution function, a continuous crushing rate function and a standing time distribution function of a material; acquiring a predicted error between the predicted material grain size distribution and the actual material grain size distribution based on the material grain size distribution predicting function; and setting an adjusting threshold value and a plurality of error intervals, and correspondingly adjusting the predicting model based on the relationship between the probability of the predicting error in different error intervals within a certain time and the adjusting threshold value. The method provided by the invention creates conditions for guiding ball-milling production and realizing optimized control of the ball-milling process and energy-saving power consumption.

Description

technical field [0001] The invention relates to the technical field of ball milling material analysis, and more specifically, to a method for predicting material particle size distribution in a ball milling process. Background technique [0002] The ball milling process is an important link in the beneficiation process. It uses a ball mill to grind minerals to the particle size required by the operation, so as to facilitate flotation and obtain more concentrates. During the ball milling process, over-grinding will cause the power consumption and steel consumption of the ball mill itself, and will also increase the power consumption of the classifier; under-grinding will also cause energy consumption, which cannot meet the requirements of subsequent production. For this reason, optimizing the operation of the ball milling process, grinding the minerals to the particle size required by the operation and maintaining stability is of great significance for improving flotation eff...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/50G06N3/08
CPCG06F30/20G06N3/08
Inventor 王雅琳杨少明孙备张鹏程彭凯王晓丽桂卫华
Owner CENT SOUTH UNIV
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