A new method of testing frother performance was proposed. Four parameters were tested： maximum foam volume, foam half-life, gas-liquid ratio and mean foam rise velocity. Among them the former two parameters indicate ...A new method of testing frother performance was proposed. Four parameters were tested： maximum foam volume, foam half-life, gas-liquid ratio and mean foam rise velocity. Among them the former two parameters indicate frother＇s foaming ability and foam stability respectively, and the latter two indicate water carrying ability and foam viscosity, respectively. The performance of four frothers in a two-phase （solution-air） system was tested and batch flotation tests on a copper ore were carried out. By analyzing frother performance in a two-phase system and comparing with the flotation results, correlation between them was found. Higher-copper concentrate grade was obtained by frothers with weak water carrying ability and low foam viscosity. And frothers with strong foaming ability and stable foam tend to obtain higher copper recovery.展开更多
Coal is the world's most abundant fossil fuel.Coal froth flotation is a widely used cleaning process to separate coal from mineral impurities.Flotation of coarse coal particles,ultrafine coal particles and oxidize...Coal is the world's most abundant fossil fuel.Coal froth flotation is a widely used cleaning process to separate coal from mineral impurities.Flotation of coarse coal particles,ultrafine coal particles and oxidized coal particles is well known to be difficult and complex.In this paper,the nanobubbles' effects on the flotation of the varying particle size,particle density and floatability coal samples were evaluated using a bank of pilot scale flotation cells,a laboratory scale and a pilot scale specially designed flotation column.The parameters evaluated during this study include the flow rate ratio between the nanobubble generator and the conventional size bubble generator,the superficial air velocity,collector dosage,frother concentration,flotation feed rate,feed solids concentration,feed particle size,and the superficial wash water flow rate,etc.The results show that the use of nanobubbles in a bank of mechanical cells flotation and column flotation increased the flotation recovery by 8%～27% at a given product grade.Nanobubbles increased the flotation rate constants of 600～355,355～180,180～75,and 75～0 microns size coal particles by 98.0%,98.4%,50.0% and 41.6%,respectively.The separation selectivity index was increased by up to 34%,depending on the flotation feed characteristics and the flotation conditions.展开更多
A multi layered, feed forward Artificial Neural Network (ANN) was used to study the effect of feed mean size, collector dosage and impeller speed on flotation recovery and grade. The results of 30 flotation experiment...A multi layered, feed forward Artificial Neural Network (ANN) was used to study the effect of feed mean size, collector dosage and impeller speed on flotation recovery and grade. The results of 30 flotation experiments conducted on Jordanian siliceous phosphate were used for training the network while another 10 experiments were used for validation. Simulation results showed that a four layer network with a [9 11 5 9 2] architecture was the one that gave the least mean squared error (MSE). Using this ANN to optimize the flotation process showed that the optimum flotation parameters were 321.28 μm for the feed mean size, 0.7354 kg/TOF for the collector dosage and 1225.25 RPM for the impeller speed. Studying the effect of these parameters on flotation recovery and grade was done by analysis of variance, ANOVA. The results showed that grade was more sensitive to changes in flotation parameters than was recovery. They also showed that changes in collector dosage had a more significant effect on flotation grade and recovery than did changes in feed mean size or impeller speed.展开更多
Segmenting blurred and conglutinated bubbles in a flotation image is done using a new segmentation method based on Seed Region and Boundary Growing（SRBG）.Bright pixels located on bubble tops were extracted as the se...Segmenting blurred and conglutinated bubbles in a flotation image is done using a new segmentation method based on Seed Region and Boundary Growing（SRBG）.Bright pixels located on bubble tops were extracted as the seed regions.Seed boundaries are divided into four curves：left-top,right-top,right-bottom, and left-bottom.Bubbles are segmented from the seed boundary by moving these curves to the bubble boundaries along the corresponding directions.The SRBG method can remove noisy areas and it avoids over- and under-segmentation problems.Each bubble is segmented separately rather than segmenting the entire flotation image.The segmentation results from the SRBG method are more accurate than those from the Watershed algorithm.展开更多
Conventional feature description methods have large errors in froth features due to the fact that the image during the zinc flotation process of froth flotation is dynamic,and the existing image features rarely have t...Conventional feature description methods have large errors in froth features due to the fact that the image during the zinc flotation process of froth flotation is dynamic,and the existing image features rarely have time series information.Based on the conventional froth size distribution characteristics,this paper proposes a size trend core feature(STCF)considering the froth size distribution,i.e.,a feature centered on the time series of the froth size distribution.The core features of the trend are extracted,the inter-frame change factor and the inter-frame stability factor are given and two calculation methods of the feature factors are proposed.Meanwhile,the STCF feature algorithm was established based on the core features by adding the inter-frame change factor and the inter-frame stability factor.Finally,a flotation condition recognition model based on BP neural network was established.The experiments show that the recognition model has achieved excellent results,proving that the method proposed effectively overcomes the limitation of the lack of dynamic information in the existing traditional size distribution features and the introduction of the two factors can improve the classification accuracy to varying degrees.展开更多
基金Project(51174229)supported by the National Natural Science Foundation of China
文摘A new method of testing frother performance was proposed. Four parameters were tested： maximum foam volume, foam half-life, gas-liquid ratio and mean foam rise velocity. Among them the former two parameters indicate frother＇s foaming ability and foam stability respectively, and the latter two indicate water carrying ability and foam viscosity, respectively. The performance of four frothers in a two-phase （solution-air） system was tested and batch flotation tests on a copper ore were carried out. By analyzing frother performance in a two-phase system and comparing with the flotation results, correlation between them was found. Higher-copper concentrate grade was obtained by frothers with weak water carrying ability and low foam viscosity. And frothers with strong foaming ability and stable foam tend to obtain higher copper recovery.
文摘Coal is the world's most abundant fossil fuel.Coal froth flotation is a widely used cleaning process to separate coal from mineral impurities.Flotation of coarse coal particles,ultrafine coal particles and oxidized coal particles is well known to be difficult and complex.In this paper,the nanobubbles' effects on the flotation of the varying particle size,particle density and floatability coal samples were evaluated using a bank of pilot scale flotation cells,a laboratory scale and a pilot scale specially designed flotation column.The parameters evaluated during this study include the flow rate ratio between the nanobubble generator and the conventional size bubble generator,the superficial air velocity,collector dosage,frother concentration,flotation feed rate,feed solids concentration,feed particle size,and the superficial wash water flow rate,etc.The results show that the use of nanobubbles in a bank of mechanical cells flotation and column flotation increased the flotation recovery by 8%～27% at a given product grade.Nanobubbles increased the flotation rate constants of 600～355,355～180,180～75,and 75～0 microns size coal particles by 98.0%,98.4%,50.0% and 41.6%,respectively.The separation selectivity index was increased by up to 34%,depending on the flotation feed characteristics and the flotation conditions.
文摘A multi layered, feed forward Artificial Neural Network (ANN) was used to study the effect of feed mean size, collector dosage and impeller speed on flotation recovery and grade. The results of 30 flotation experiments conducted on Jordanian siliceous phosphate were used for training the network while another 10 experiments were used for validation. Simulation results showed that a four layer network with a [9 11 5 9 2] architecture was the one that gave the least mean squared error (MSE). Using this ANN to optimize the flotation process showed that the optimum flotation parameters were 321.28 μm for the feed mean size, 0.7354 kg/TOF for the collector dosage and 1225.25 RPM for the impeller speed. Studying the effect of these parameters on flotation recovery and grade was done by analysis of variance, ANOVA. The results showed that grade was more sensitive to changes in flotation parameters than was recovery. They also showed that changes in collector dosage had a more significant effect on flotation grade and recovery than did changes in feed mean size or impeller speed.
基金supported in part by the National Science & Technology Support Plan of China(No.2009BAB48B02)
文摘Segmenting blurred and conglutinated bubbles in a flotation image is done using a new segmentation method based on Seed Region and Boundary Growing（SRBG）.Bright pixels located on bubble tops were extracted as the seed regions.Seed boundaries are divided into four curves：left-top,right-top,right-bottom, and left-bottom.Bubbles are segmented from the seed boundary by moving these curves to the bubble boundaries along the corresponding directions.The SRBG method can remove noisy areas and it avoids over- and under-segmentation problems.Each bubble is segmented separately rather than segmenting the entire flotation image.The segmentation results from the SRBG method are more accurate than those from the Watershed algorithm.
基金Project(U1701261)supported by the National Science Foundation of China,Guangdong Joint Fund of Key ProjectsProject(61771492)supported by the National Natural Science Foundation of ChinaProject(2018GK4016)supported by Hunan Province Strategic Emerging Industry Science and Technology Research and Major Science and Technology Achievement Transformation Project,China。
文摘Conventional feature description methods have large errors in froth features due to the fact that the image during the zinc flotation process of froth flotation is dynamic,and the existing image features rarely have time series information.Based on the conventional froth size distribution characteristics,this paper proposes a size trend core feature(STCF)considering the froth size distribution,i.e.,a feature centered on the time series of the froth size distribution.The core features of the trend are extracted,the inter-frame change factor and the inter-frame stability factor are given and two calculation methods of the feature factors are proposed.Meanwhile,the STCF feature algorithm was established based on the core features by adding the inter-frame change factor and the inter-frame stability factor.Finally,a flotation condition recognition model based on BP neural network was established.The experiments show that the recognition model has achieved excellent results,proving that the method proposed effectively overcomes the limitation of the lack of dynamic information in the existing traditional size distribution features and the introduction of the two factors can improve the classification accuracy to varying degrees.
