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浮选过程关键工艺指标精矿品位和尾矿品位难以实现在线连续检测,且与浮选过程给矿浓度、给矿量、给矿粒度、给矿品位和浮选药剂量等因素动态特性具有强非线性、不确定性等综合复杂特性,难以建立精确数学模型。在分析了浮选过程工艺指标相关影响因素的基础上,采用最小二乘支持向量机(LS-SVM)建立了浮选过程工艺技术指标软测量模型,现场生产数据仿真研究结果表明了所提出的软测量模型的有效性。
Flotation process key process indicators Concentrate grade and tailings grade difficult to achieve online continuous detection, and the flotation process to give the concentration of ore, to the amount of ore, to the ore particle size, feed grade and flotation dosage and other factors have strong dynamic characteristics Nonlinear, uncertainties and other complex features, it is difficult to establish an accurate mathematical model. Based on the analysis of the influencing factors of process index of flotation process, the soft-sensing model of technological index of flotation process was established by least-squares support vector machine (LS-SVM). The simulation results of field production data show that the proposed method The effectiveness of the soft-sensing model.