LIBS-based bauxite component quantitative detection method and related apparatus

By combining the LIBS system with machine learning models, rapid and accurate quantitative detection of bauxite components has been achieved, solving the problems of complex and time-consuming sample processing in traditional methods and improving the efficiency of automated ore blending in alumina production.

WO2025241437A1 Publication Date: 2025-11-27ZHENGZHOU NON FERROUS METALS RES INST CO LTD OF CHALCO
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Patent Information

Application Number
PCT/CN2024/132045
Authority / Receiving Office
WO · WO
Patent Type
Applications
Current Assignee / Owner
Priority Date
2024-05-23
Filing Date
2024-11-14
Publication Date
2025-11-27

AI Technical Summary

Technical Problem

Traditional methods for quantitative analysis of bauxite components involve complex sample pretreatment, long analysis time, large amounts of chemical reagents, and are prone to human error, which affects the efficiency of automated ore blending in alumina production.

Method used

A LIBS-based quantitative detection method for bauxite components is adopted. By controlling the LIBS system to collect spectral data, preprocessing it, extracting characteristic elements, and combining it with a machine learning model for component analysis, the sample processing steps are eliminated, enabling rapid quantitative detection.

Benefits of technology

It improves the efficiency and accuracy of bauxite composition detection, enhances the effectiveness of automated ore blending in alumina production, and reduces human error and detection time.

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Abstract

An LIBS-based bauxite component quantitative detection method and a related apparatus. The method comprises: controlling an LIBS system to collect actual spectral data of bauxite under test; preprocessing the actual spectral data to obtain preprocessed actual spectral data; on the basis of the preprocessed actual spectral data, extracting corresponding feature elements to be detected, said feature elements comprising one or more of information about feature wavelengths to be detected, information about element wavelengths to be detected, and information about remaining wavelengths to be detected; and, on the basis of said feature elements and a quantitative detection model, determining component information of said bauxite.
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