Intelligent predictive control of cleaning flotation process based on froth texture features

被引:0
|
作者
Cao, Binfang [1 ,2 ]
Xie, Yongfang [1 ]
Yang, Chunhua [1 ]
Gui, Weihua [1 ]
Li, Jianqi [2 ]
机构
[1] Cent S Univ, Sch Informat Sci & Engn, Changsha, Hunan, Peoples R China
[2] Hunan Univ Arts & Sci, Coll Phys & Elect Sci, Changde, Hunan, Peoples R China
来源
2014 11TH WORLD CONGRESS ON INTELLIGENT CONTROL AND AUTOMATION (WCICA) | 2014年
基金
中国国家自然科学基金; 高等学校博士学科点专项科研基金;
关键词
Cleaning flotation; Froth image; Texture features; On-line predictive control; COOCCURRENCE MATRICES; CLASSIFICATION;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Cleaning process is the key stage affecting the final concentrate grade of mineral flotation. The operation parameters are normally adjusted manually by operators to achieve the optimal control of the concentrate grade. However, this method is of great subjectivity, randomness and uncertainty. Therefore, an intelligent predictive control method for the cleaning process based on the froth texture features is proposed in this paper. Firstly, the features of cleaner flotation froth are analyzed, and the significant features are expressed with texture features by using the color co-occurrence matrix. Then an improved online prediction model is constructed and optimized by rolling optimization with the differential evolution algorithm, in order to achieve the optimal control of the pulp level. The validation of industrial data shows the effectiveness of the proposed method in bauxite cleaning flotation process, which is applied to stabilize the flotation process and concentrate grade.
引用
收藏
页码:766 / 771
页数:6
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