Probability density function of bubble size based reagent dosage predictive control for copper roughing flotation

被引：40
作者：
Zhu, Jianyong [1 ,2 ]
Gui, Weihua [1 ]
Yang, Chunhua [1 ]
Xu, Honglei [1 ,3 ]
Wang, Xiaoli [1 ]
机构：
[1] Cent South Univ, Sch Informat Sci & Engn, Changsha 410083, Hunan, Peoples R China
[2] JiangXi Univ Sci & Technol, Nanchang 330029, Peoples R China
[3] Curtin Univ, Dept Math & Stat, Perth, WA 6845, Australia
来源：
CONTROL ENGINEERING PRACTICE | 2014年 / 29卷
基金：
中国国家自然科学基金;
关键词：
Froth flotation; Reagent dosage; Predictive control; Bubble size; Probability density function; MLS-SVM; IMPLEMENTATION; DISTRIBUTIONS; FROTHERS; SYSTEMS; SURFACE;
D O I：
10.1016/j.conengprac.2014.02.021
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
As an effective measurement indicator of bubble stability, bubble size structure is believed to be closely related to flotation performance in copper roughing flotation. Moreover, reagent dosage has a very important influence on bubble size structure. In this paper, a novel reagent dosage predictive control method based on probability density function (PDF) of bubble size is proposed to implement the indices of roughing circuit. Firstly, the froth images captured in the copper roughing are segmented by using a two-pass watershed algorithm. In order to characterize bubble size structure with non-Gaussian feature, an entropy based B-spline estimator is hence investigated to depict the PDF of the bubble size. Since the weights of B-spline are interrelated and related to the reagent dosage, a multi-output least square support vector machine (MLS-SVM) is applied to depict a dynamic relationship between the weights and the reagent dosage. Finally, an entropy based optimization algorithm is proposed to determine reagent dosage in order to implement tracking control for the PDF of the output bubble size. Experimental results can show the effectiveness of the proposed method. (C) 2014 Elsevier Ltd. All rights reserved.
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页码：1 / 12
页数：12
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