Method and system for predicting key indexes in zinc hydrometallurgy cobalt removal process

Abstract

The invention discloses a method and a system for predicting key indexes in a zinc hydrometallurgy cobalt removal process. The method comprises the following steps: acquiring data of a plurality of process variables of a reactor in the zinc hydrometallurgy process; inputting the data of the plurality of process variables into a graph attention network to train and determine parameters of the graph attention network so as to construct data features and relation features of the plurality of process variables; and performing training determination on parameters of a full-connection prediction layer of the graph attention network according to the data features and the relation features of the plurality of process variables obtained after training the parameters of the graph attention network. According to the method and the device, the problem of low prediction precision in a technical scheme for predicting the key indexes in the cobalt removal process in zinc hydrometallurgy in the prior art is solved, so that an accurate outlet cobalt ion concentration key index prediction model is established aiming at the complex nonlinearity and interdependence relationship among the variables in the cobalt removal process; and the prediction precision is improved.

Description

technical field [0001] The present application relates to the field of zinc hydrometallurgy and cobalt removal, and in particular, to a method and system for predicting key indicators in the process of hydrometallurgy zinc removal and cobalt removal. Background technique [0002] Zinc is an important non-ferrous metal raw material with a wide range of uses. At present, the main production methods of zinc are pyrometallurgical zinc and hydrometallurgy zinc, among which hydrometallurgy is the most important zinc smelting method in the world. The zinc output obtained by this technology accounts for 80% to 85% of the total output, and it shows an increasing trend with the development of technology. Among them, the cobalt removal process is an important step in the hydrometallurgical zinc process, and the cobalt ions are gradually removed by adding zinc powder and catalyst. The rational operation of the cobalt removal process requires on-line detection of the key indicator of c...

AI Technical Summary

Problems solved by technology

[0007] The embodiment of the present application provides a method and system for predicting key indicators of the cobalt removal process in zinc hydrometallurgy, to at least solve the problem of poor prediction accuracy in the technical solutions for predicting key indicators of the cobalt removal process in zinc hydrometallurgy in related technologies. high problem

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