Robust SoftSensing of Slurry pH Using LSSVR for Mineral Flotation Process

Abstract

Abstract: Considering the poor stability of detectors and serious manual detection timedelay, a novel soft sensor was proposed based on least squares support vector regression (LSSVR) with sparsity using image features as instrumental variable. Firstly, multiple kernels were combined and the kernel matrix was reduced according to an improved minus cluster algorithm. Then the partial least squares regression was used to improve the robustness and precision of the soft sensor. The experiment verified the presented model which performs high precision and good reliability compared with standard LSSVR, weighted LSSVR and multiplekernel LSSVR.

Key words: mineral flotation, pH, softsensing, least squares support vector regression (LSSVR), minus cluster

CLC Number:

TP274
TP923

REN Hui-Feng, YANG Chun-Hua, ZHOU Xuan, GUI Wei-Hua, YAN Feng. Robust SoftSensing of Slurry pH Using LSSVR for Mineral Flotation Process[J]. Journal of Shanghai Jiaotong University, 2011, 45(08): 1136-1139.

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