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Efficient weakly supervised LIBS feature selection method in quantitative analysis of iron ore slurry.

Tong Chen, Lanxiang Sun, Haibin Yu

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    |March 17, 2022
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    A new spectral distance variable selection method improves real-time iron analysis in mineral flotation slurries. This LIBS-based analyzer achieves high precision, reducing prediction error to 0.75% for better process control.

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    Area of Science:

    • Analytical Chemistry
    • Materials Science
    • Mineral Processing

    Background:

    • On-stream elemental analysis is crucial for controlling mineral flotation processes.
    • Real-time monitoring of iron content in ore slurries is essential for process optimization.
    • Developing high-precision quantitative analysis methods for slurries presents significant challenges.

    Purpose of the Study:

    • To introduce a novel weakly supervised feature selection method for raw spectral data.
    • To enhance the precision of a Laser-Induced Breakdown Spectroscopy (LIBS)-based slurry analyzer for iron ore concentrate.
    • To overcome limitations in achieving high-accuracy quantitative analysis in slurry samples.

    Main Methods:

    • Development of a spectral distance variable selection method utilizing prior information of identical reference concentrations for multiple spectra of the same sample.
    • Application of the LIBSlurry analyzer for on-stream monitoring of iron ore concentrate slurry during mineral flotation.
    • Comparison of the proposed feature selection method against full-spectrum input and traditional wrapper methods.

    Main Results:

    • The spectral distance variable selection method significantly improved prediction accuracy compared to full-spectrum input and other feature selection techniques.
    • The root mean square error of prediction for iron content was reduced to 0.75%.
    • Selected features demonstrated reduced over-fitting compared to traditional wrapper methods.

    Conclusions:

    • The proposed weakly supervised feature selection method is effective for improving quantitative analysis of iron content in slurries.
    • The LIBSlurry analyzer, enhanced by this method, shows successful application potential in mineral flotation process control.
    • High-precision on-stream analysis of slurries is achievable, leading to better process management.