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Switching and optimizing control for coal flotation process based on a hybrid model.

Zhiyong Dong1, Ranfeng Wang1, Minqiang Fan1

  • 1College of Mining Engineering, Taiyuan University of Technology, Taiyuan, Shanxi, China.

Plos One
|October 18, 2017
PubMed
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This study introduces a hybrid control model for coal flotation, optimizing froth depth and reagent dosage. The method uses advanced signal processing and machine learning for efficient coal preparation.

Area of Science:

  • Mineral Processing
  • Chemical Engineering
  • Control Systems Engineering

Background:

  • Flotation columns are crucial for coal preparation, but their complex operation is influenced by variables like froth depth and reagent dosage.
  • Optimizing these variables is essential for efficient coal flotation and requires advanced control strategies.
  • Existing methods may not fully address the dynamic and complex nature of coal flotation processes.

Purpose of the Study:

  • To propose and evaluate a novel hybrid switching and optimizing control method for coal flotation columns.
  • To develop a model that dynamically adjusts froth depth and reagent dosage based on operating conditions.
  • To improve the efficiency and performance of industrial coal flotation processes.

Main Methods:

Related Experiment Videos

  • Signal pre-processing using wavelet analysis and principal component analysis (PCA).
  • Development of a fuzzy control model for optimizing froth depth set points.
  • Design of an expert system for optimizing reagent dosages.
  • Implementation of a least squares-support vector machine (LS-SVM) for operating condition identification and model switching.

    • Main Results:

    • A hybrid control model integrating signal processing, fuzzy logic, expert systems, and LS-SVM was developed.
    • The model was evaluated using industrial data from a coal flotation column.
    • The proposed hybrid model demonstrated satisfactory performance in controlling the flotation process.

    Conclusions:

    • The hybrid switching and optimizing control method offers a robust approach for managing complex coal flotation operations.
    • Integrating advanced analytical techniques and control strategies enhances the efficiency of coal preparation.
    • The developed model provides a practical solution for optimizing froth depth and reagent dosage in industrial settings.