Antimony floatation working condition recognition method and system

Abstract

The invention provides an antimony floatation working condition recognition method and system. The antimony floatation working condition recognition method includes the steps of preprocessing recorded antimony floatation foam image characteristic data, extracting key foam characteristics which are highly sensitive to working condition changes and have no relations or have weak relations with one another from the processed foam image characteristic data, fusing various key foam characteristics based on the matter-element extension theory, setting up the relational degree matrix between the key foam characteristics of working conditions to be recognized and types of preset working conditions through a correlation function, combining the subjective weighting method with the objective weighting method through the game theory method and by means of the optimization theory to obtain the comprehensive weight of the key foam characteristics, calculating the comprehensive relational degree between the working conditions to be recognized and the types of the preset working conditions based on the relational degree matrix and the comprehensive weight, determining the types of the working conditions to be recognized according to the maximum relational degree principle, and forecasting the level change tendency of the working conditions.

Description

technical field [0001] The invention relates to the technical field of froth flotation, in particular to a method and system for identifying antimony flotation working conditions. Background technique [0002] Antimony is often referred to as a hardening agent for metals or alloys. After adding different proportions of antimony to metals, the hardness of the metal will increase, which can be used to make arms. Antimony has become an important strategic metal. Antimony ore is a non-renewable resource and plays an important role in the national economy. In order to make full use of limited mineral resources and realize the sustainable development of mineral resources, the modern antimony smelting process pays more and more attention to the separation level of mineral resources and the mineral processing process. energy consumption and emissions issues. For this reason, many large enterprises have established mineral froth flotation production lines. [0003] Froth flotation ...

AI Technical Summary

Problems solved by technology

However, the neural network requires a large training sample, which has disadvantages such as over-learning, easy to fall into local minimum points, and slow convergence speed; the support vector machine has a large amount of calculation, it is difficult to choose a suitable kernel, and the accuracy rate drops sharply when the categories are too close, etc. problems, there are still some difficulties in the application

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