Ore dressing comprehensive index prediction method based on ore blending product property

A technology of comprehensive indicators and prediction methods, which is applied in the field of prediction of comprehensive indicators of mineral processing based on the properties of mineral blending products. lost effect

Inactive Publication Date: 2017-09-05
NORTHEASTERN UNIV
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Problems solved by technology

The current method is mainly judged based on the experience of the operator. This method has hig

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  • Ore dressing comprehensive index prediction method based on ore blending product property
  • Ore dressing comprehensive index prediction method based on ore blending product property
  • Ore dressing comprehensive index prediction method based on ore blending product property

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Example Embodiment

[0022] Attached below figure 1 , taking the actual situation of a certain mineral processing plant as an example, the specific implementation of the present invention is described in detail.

[0023] The ore dressing comprehensive index prediction method of the present embodiment comprises the following steps:

[0024] Step 1: Collect historical data on the properties of ore blending products, including the total iron grade, magnetic iron value, ferrous value, iron carbonate value, iron silicate value, ore particle size, and magnetic separation tube yield of the selected ore;

[0025] Table 1 Historical data table of properties of ore blending products

[0026]

[0027] Step 2: Collect historical data on the properties of mineral processing products corresponding to mineral blending products, including comprehensive concentrate grade, comprehensive tailings grade, ore selection ratio, and ore cost;

[0028] Table 2 Historical data of mineral processing product properties ...

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Abstract

The invention discloses an ore dressing comprehensive index prediction method based on an ore blending product property. The ore dressing comprehensive index prediction method of the invention can determine an ore blending product property affecting a comprehensive index of the ore dressing product by combining with a site condition and professional experience, collects history data of the ore blending product property and the ore dressing comprehensive index, fits out a relation between the ore blending product quality and the ore dressing comprehensive index through a BP neural network algorithm and stores the relation as a function, and inputs various properties of the ore blending product to obtain a prediction value of the ore dressing comprehensive property. The ore dressing comprehensive index prediction method based on the ore blending product property is based on data modeling, combines an optimal algorithm with the professional experience, fast and accurately predicts the ore dressing comprehensive property and provides a basis for formulating an ore dressing strategy. Meanwhile, the ore dressing comprehensive index prediction method changes the current prediction method relaying on artificial experience determination and improves enterprise working experience.

Description

technical field [0001] The invention belongs to the technical field of prediction of mineral processing comprehensive indexes, and in particular relates to a method for predicting mineral processing comprehensive indexes based on the properties of mineral blending products. Background technique [0002] The quality of comprehensive properties of mineral processing products is a matter of great concern to mineral processing plants, and excellent mineral processing products are the guarantee for the profitability of mineral processing plants. Generally, the source of ore raw materials used in mineral processing plants is relatively single, so the process of mineral processing is often stable for different batches of ore. However, due to the large number of procedures in mineral processing operations, operators are often required to fine-tune different product indicators. When the beneficiation process remains stable, the properties of the mineral blending products, that is, th...

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Application Information

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IPC IPC(8): G06Q10/06G06Q50/02
CPCG06Q10/06375G06Q50/02
Inventor 高宪文刘炳宇张鼎森王明顺李欣阳郝得智刘博健
Owner NORTHEASTERN UNIV
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