A Soft Sensing Method of Antimony Ore Grade Based on Selective Fusion of Heterogeneous Classifiers

Abstract

The invention provides an antimony ore grade soft-measurement method based on the selective fusion of a heterogeneous classifier. The method comprises the step of together forming a feature space based on the pretreatment of antimony flotation froth image feature data and production data related to the grade of the antimony ore. According to the method, firstly, some feathers are randomly selected to form a plurality of sub-sample spaces. Secondly, a plurality of different sub-samples in each sub-sample space are sampled through the bootstrap sampling process. At the same time, the PCA analysis is conducted on each sub-sample to obtain key features that are high in sensitivity to grade change and free of / weak in dependency. Thirdly, two KELMs are conducted respectively for each sub-sample set to construct a candidate sub-model, based on an RBF kernal of better learning ability and a polynomial kernel type KELM of better generalization ability. Fourthly, each candidate sub-model is endowed with a weight based on the method of information entropy. Finally, all candidate sub-models are sorted from small to large based on the RMSE, and then an optimal weighted sub-model combination is selected as a final model for the prediction on the grade of the antimony ore.

Description

technical field [0001] The invention belongs to the technical field of froth flotation, and in particular relates to a method for predicting the grade of an antimony flotation concentrate. Background technique [0002] Froth flotation is one of the most important beneficiation methods in today's antimony smelting. Flotation method is a method of sorting minerals by using the different physical and chemical properties of the surface of mineral particles to lead to different hydrophilicity. Practical value. Through continuous stirring and aeration during the flotation process, a large number of bubbles with different sizes, colors, shapes and textures can be formed, and mineral particles adhere to the surface of the bubbles to achieve mineral separation. Concentrate grade is one of the important production indicators of mineral flotation process. On-site operators regularly collect pulp foam samples according to requirements, and use off-line testing to determine the content...

AI Technical Summary

Problems solved by technology

[0004] Aiming at the difficulty of on-line detection of concentrate grade in the flotation process and the insufficiency of the prior art in predicting the grade of antimony flotation concentrate, the present invention utilizes various characteristics related to the grade of antimony concentrate to propose a selective weighted fusion with Antimony Flotation Concentrate Grade Prediction Method Based on KELM with Different Kernel Functions

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