There are few methods of semi-autogenous(SAG)mill power prediction in the full-scale without using long experiments.In this work,the effects of different operating parameters such as feed moisture,mass flowrate,mill l...There are few methods of semi-autogenous(SAG)mill power prediction in the full-scale without using long experiments.In this work,the effects of different operating parameters such as feed moisture,mass flowrate,mill load cell mass,SAG mill solid percentage,inlet and outlet water to the SAG mill and work index are studied.A total number of185full-scale SAG mill works are utilized to develop the artificial neural network(ANN)and the hybrid of ANN and genetic algorithm(GANN)models with relations of input and output data in the full-scale.The results show that the GANN model is more efficient than the ANN model in predicting SAG mill power.The sensitivity analysis was also performed to determine the most effective input parameters on SAG mill power.The sensitivity analysis of the GANN model shows that the work index,inlet water to the SAG mill,mill load cell weight,SAG mill solid percentage,mass flowrate and feed moisture have a direct relationship with mill power,while outlet water to the SAG mill has an inverse relationship with mill power.The results show that the GANN model could be useful to evaluate a good output to changes in input operation parameters.展开更多
半自磨机具有多变量、非线性、强耦合、大滞后、时变性等特征,且很多过程参数难以检测,难以通过常规控制方法实现自动控制。为此,乌山选矿厂以人工经验为基础,找出半自磨机工作时给矿量、磨音、功率、轴压、磨矿浓度、给矿粒度比例之间...半自磨机具有多变量、非线性、强耦合、大滞后、时变性等特征,且很多过程参数难以检测,难以通过常规控制方法实现自动控制。为此,乌山选矿厂以人工经验为基础,找出半自磨机工作时给矿量、磨音、功率、轴压、磨矿浓度、给矿粒度比例之间的关系,并用计算机语言表述出来,得到一种定性的智能控制系统。实践表明:这种半自磨机智能控制系统可根据服务器设定的控制策略,实时采集半自磨机过程参数,自动调整至最优的半自磨机运行状态,在乌山选矿厂应用后较原人工控制可以提高处理量24.7 t/h、延长衬板使用寿命11.1 d、降低吨矿能耗0.49 k Wh/t,具有显著的经济效益,在金属矿山领域具有重要推广应用前景。展开更多
文摘There are few methods of semi-autogenous(SAG)mill power prediction in the full-scale without using long experiments.In this work,the effects of different operating parameters such as feed moisture,mass flowrate,mill load cell mass,SAG mill solid percentage,inlet and outlet water to the SAG mill and work index are studied.A total number of185full-scale SAG mill works are utilized to develop the artificial neural network(ANN)and the hybrid of ANN and genetic algorithm(GANN)models with relations of input and output data in the full-scale.The results show that the GANN model is more efficient than the ANN model in predicting SAG mill power.The sensitivity analysis was also performed to determine the most effective input parameters on SAG mill power.The sensitivity analysis of the GANN model shows that the work index,inlet water to the SAG mill,mill load cell weight,SAG mill solid percentage,mass flowrate and feed moisture have a direct relationship with mill power,while outlet water to the SAG mill has an inverse relationship with mill power.The results show that the GANN model could be useful to evaluate a good output to changes in input operation parameters.
文摘半自磨机具有多变量、非线性、强耦合、大滞后、时变性等特征,且很多过程参数难以检测,难以通过常规控制方法实现自动控制。为此,乌山选矿厂以人工经验为基础,找出半自磨机工作时给矿量、磨音、功率、轴压、磨矿浓度、给矿粒度比例之间的关系,并用计算机语言表述出来,得到一种定性的智能控制系统。实践表明:这种半自磨机智能控制系统可根据服务器设定的控制策略,实时采集半自磨机过程参数,自动调整至最优的半自磨机运行状态,在乌山选矿厂应用后较原人工控制可以提高处理量24.7 t/h、延长衬板使用寿命11.1 d、降低吨矿能耗0.49 k Wh/t,具有显著的经济效益,在金属矿山领域具有重要推广应用前景。
