[1]
|
Niu Fu-Sheng, Liu Rui-Qin, Zheng Wei-Min, Yan Man-Zhi. 600 Asks of Mineral Processing Knowledge. Beijing: Metallurgical Industry Press, 2008. 9-13(牛福生, 刘瑞芹, 郑为民, 闫满志. 选矿知识600问. 北京: 冶金工业出版社, 2008. 9-13)
|
[2]
|
Nakhaeie F, Sam A, Mosavi M R. Concentrate grade prediction in an industrial flotation column using artificial neural network. Arabian Journal for Science and Engineering, 2013, 38(5): 1011-1023
|
[3]
|
Bergh L G, Yianatos J. The long way towards multivariate predictive control of flotation processes. Journal of Process Control, 2011, 21(2): 226-234
|
[4]
|
Kampjarvi P, Jamsa-Jounela S L. Level control strategies for flotation cells. Minerals Engineering, 2003, 16(11): 1061-1068
|
[5]
|
Maldonado M, Desbiens A, Del Villar R. Potential use of model predictive control for optimizing the column flotation process. International Journal of Mineral Processing, 2009, 93(1): 26-33
|
[6]
|
Bouchard J, Desbiens A, Del Villar R. Recent advances in bias and froth depth control in flotation columns. Minerals Engineering, 2005, 18(7): 709-720
|
[7]
|
Wang He, Li Ying-Gen, Wang Huan-Gang, Xu Wen-Li. A design of feed-forward control for flotation cell level. Non-Ferrous Metals (Mineral Processing), 2010, (6): 41-44(王赫, 李映根, 王焕钢, 徐文立. 串级浮选槽液位的前馈控制设计方法. 有色金属(选矿部分), 2010, (6): 41-44)
|
[8]
|
Liu J J, MacGregor J F. Froth-based modeling and control of flotation processes. Minerals Engineering, 2008, 21(9): 642-651
|
[9]
|
Nunez F, Cipriano A. Visual information model based predictor for froth speed control in flotation process. Minerals Engineering, 2009, 22(4): 366-371
|
[10]
|
Cao Bin-Fang, Xie Yong-Fang, Gui Wei-Hua, Wei Li-Jun, Yang Chun-Hua. Integrated prediction model of bauxite concentrate grade based on distributed machine vision. Minerals Engineering, 2013, 53: 31-38
|
[11]
|
Marais C, Aldrich C. Estimation of platinum flotation grades from froth image data. Minerals Engineering, 2011, 24(5): 433-441
|
[12]
|
Bartolacci G, Pelletier P, Tessier J, Duchense C, Bosse P, Founier J. Application of numerical image analysis to process diagnosis and physical parameter measurement in mineral processes, Part I: Flotation control based on froth textural characteristics. Minerals Engineering, 2006, 19(6-8): 737-747
|
[13]
|
Ata S. Phenomena in the froth phase of flotation: a review. International Journal of Mineral Processing, 2012, 102-103: 1-12
|
[14]
|
Aldrich C, Marais C, Shean B J, Cilliers J J. Online monitoring and control of froth flotation systems with machine vision: a review. International Journal of Mineral Processing, 2010, 96(4): 1-13
|
[15]
|
Behbahani M, Saghaee A, Noorossana R. A case-based reasoning system development for statistical process control: case representation and retrieval. Computers and Industrial Engineering, 2012, 63(4): 1107-1117
|
[16]
|
Pian Jin-Xiang, Chai Tian-You, Li Jie-Jia. Application of case-based reasoning and iterative learning to laminar cooling process control. Acta Automatica Sinica, 2012, 38(12): 2032-2037(片锦香, 柴天佑, 李界家. 案例推理及迭代学习在层流冷却控制中的应用. 自动化学报, 2012, 38(12): 2032-2037)
|
[17]
|
Nakhaei F, Mosavi M R, Sam A, Vaghei Y. Recovery and grade accurate prediction of pilot plant flotation column concentrate: neural network and statistical techniques. International Journal of Mineral Processing, 2012, 110(7): 140-154
|
[18]
|
Wang Yao-Nan, Yuan Xiao-Fang. SVM Approximate-based internal model control strategy. Acta Automatica Sinica, 2008, 34(2): 172-179(王耀南, 袁小芳. 基于支持向量机逼近的内模控制系统及应用. 自动化学报, 2008, 34(2): 172-179)
|
[19]
|
Zhou Kai-Jun, Yang Chun-Hua, Mu Xue-Min, Gui Wei-Hua. Flotation recovery prediction based on froth features and LS-SVM. Chinese Journal of Scientific Instrument, 2009, 30(6): 1295-1300(周开军, 阳春华, 牟学民, 桂卫华. 基于泡沫特征与LS-SVM的浮选回收率预测. 仪器仪表学报, 2009, 30(6): 1295-1300)
|
[20]
|
Gui Wei-Hua, Yang Chun-Hua, Xie Yong-Fang, Tang Zhao-Hui. Bubble Image Processing and Process Monitoring techniques of Mineral Flotation. Changsha: Central South University Press, 2013. 95-142(桂卫华, 阳春华, 谢永芳, 唐朝晖. 矿物浮选泡沫图像处理与过程监测技术. 长沙: 中南大学出版社, 2013. 95-142)
|
[21]
|
Yang Chun-Hua, Zhou Kai-Jun, Mu Xue-Min, Gui Wei-Hua. Froth color and size measurement method for flotation based on computer vision. Chinese Journal of Scientific Instrument, 2009, 30(4): 717-721(阳春华, 周开军, 牟学民, 桂卫华. 基于计算机视觉的浮选泡沫颜色及尺寸测量方法. 仪器仪表学报, 2009, 30(4): 717-721)
|
[22]
|
Liu Wen-Li, Lu Mai-Xi, Wang Fan, Wang Yong. Extraction of textural feature and recognition of coal flotation froth. Journal of Chemical Industry and Engineering (China), 2003, 54(6): 830-835(刘文礼, 路迈西, 王凡, 王勇. 煤泥浮选泡沫图像纹理特征的提取及泡沫状态的识别. 化工学报, 2003, 54(6): 830-835)
|
[23]
|
Gui Wei-Hua, Yang Chun-Hua, Xu De-Gang, Lu Ming, Xie Yong-Fang. Machine-vision-based online measuring and controlling technologies for mineral flotation: a review. Acta Automatica Sinica, 2013, 39(11): 1879-1888(桂卫华, 阳春华, 徐德刚, 卢明, 谢永芳. 基于机器视觉的矿物浮选过程监控技术研究进展. 自动化学报, 2013, 39(11): 1879-1888)
|
[24]
|
Geng Zeng-Xian, Chai Tian-You. Intelligently optimal index setting for flotation process by CBR. Journal of Northeastern University (Natural Science), 2008, 29(6): 761-764(耿增显, 柴天佑. 基于案例推理的浮选过程智能优化设定. 东北大学学报(自然科学版), 2008, 29(6): 761-764)
|
[25]
|
Li H B, Chai T Y, Zhang L Y. Hybrid intelligent optimal control for flotation processes. In: Proceedings of the 2012 American Control Conference (ACC). Montreal, Canada: IEEE, 2012. 4891-4896
|
[26]
|
Jiang Yi-Zhang, Deng Zhao-Hong, Wang Shi-Tong. Mamdani-larsen type transfer learning fuzzy system. Acta Automatica Sinica, 2012, 38(9): 1393-1409(蒋亦樟, 邓赵红, 王士同. ML型迁移学习模糊系统. 自动化学报, 2012, 38(9): 1393-1409)
|