Multi-component content prediction method and system in rare earth extraction process

Abstract

The invention provides a multi-component content prediction method under the condition of coexistence of rare earth ions with color characteristics and without color characteristics, and relates to the field of component content prediction in the rare earth extraction process. The method comprises: the problem that the component content is difficult to quickly and accurately detect exists in the rare earth extraction process; the GA-ELM-based rare earth extraction process multi-component content prediction method is provided for solving the problem that the original color feature-based singlerare earth element component content detection method is not applicable due to the fact that the image color features of a CePr/Nd mixed solution containing colorless Ce ions are greatly different from those of a Pr/Nd solution. The method comprises the following steps: firstly, searching H and S components with the maximum correlation with the component content in an HSI color space; secondly, establishing a multi-component content soft measurement model based on an extreme learning machine ELM by taking H and S component first moments as input; for the uncertainty of an initial weight and athreshold value of an ELM model, using a genetic algorithm GA to optimize model parameters, so that the precision of the optimized ELM model with the component content is higher.

Description

technical field [0001] The invention relates to the field of component content measurement, in particular to a multi-component content prediction method and system in a rare earth extraction process. Background technique [0002] Rare earths are composed of 17 elements such as lanthanides, scandium and yttrium, and exist in the form of symbiotic ores. The purification of rare earth elements mainly adopts the cascade extraction and separation process. In the rare earth cascade extraction process, some rare earth ions have special color characteristics, and this feature is closely related to the content of rare earth components. Regarding the color characteristics of praseodymium ions and neodymium ions in the praseodymium / neodymium extraction production process, some scholars have actually In the production process, machine vision technology is used to realize the soft measurement of component content. A rapid detection system for rare earth component content based on machin...

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Problems solved by technology

But these are all rare earth extraction solutions with ion characteristic colors as the research object, and do not involve the detection

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