A froth velocity measurement method based on improved U-Net++semantic segmentation in flotation process

During flotation,the features of the froth image are highly correlated with the concentrate grade and the corresponding working conditions.The static features such as color and size of the bubbles and the dynamic features such as velocity have obvious differences between different working conditions.The extraction of these features is typically relied on the outcomes of image segmentation at the froth edge,making the segmentation of froth image the basis for studying its visual information.Meanwhile,the absence of scientifically reliable training data with label and the necessity to manually construct dataset and label make the study difficult in the mineral flotation.To solve this problem,this paper constructs a tungsten concentrate froth image dataset,and proposes a data augmentation network based on Conditional Generative Adversarial Nets(cGAN)and a U-Net++-based edge segmentation network.The performance of this algorithm is also evaluated and contrasted with other algorithms in this paper.On the results of semantic segmentation,a phase-correlationbased velocity extraction method is finally suggested.

Nanobubble generation and its applications in froth flotation(part Ⅱ):fundamental study and theoretical analysis

Froth flotation is a commonly employed technology to improve the quality of raw coal and minerals.Coal and minerals particle size and surface hydrophobicity are two main parameters that affect three key steps in froth flotation process:particle-bubble collision,adhesion,and detachment.This paper fundamentally investigated the effects of nanobubble on coal and phosphate flotation.It has been found that the presence of nanobubble in flotation pulp could widen the coal and phosphate flotation particle size range,increase the particle surface hydrophobicity,and thus improve the coal and phosphate froth flotation recovery.

Nanobubble generation and its application in froth flotation (part I): nanobubble generation and its effects on properties of microbubble and millimeter scale bubble solutions

A special nanobubble generation system has been developed for evaluating the effect of nanobubble on froth flotation. In this study, an eight-factor five-level Central Composite Experimental Design was conducted for investigating eight important parameters governing the median size and the volume of nanobubbles. These process parameters included surfactant concentration, dissolved oxygen (O2) content, dissolved carbon dioxide gas (CO2) content, pressure drop in cavitation tube nozzle, <50 nm hydrophobic particle concentration, <50 nm hydrophilic particle concentration, slurry temperature and the time interval after nanobubble generation. The properties, stability and uniformity of nanobubbles were investigated. The study of the produced nanobubble’s effects on the characteristics of microbubble solutions and millimeter scale bubble solutions was performed in a 50.8 mm column.

Nanobubble generation and its applications in froth flotation(partⅢ):specially designed laboratory scale column flotation of phosphate

Froth flotation is used widely for upgrading raw phosphate.The flotation recovery of coarse phosphate(-1.18+0.425 mm) is much lower than that achieved on the-0.425+0.15 mm size fraction.Enhanced recovery of coarse phosphate particles is of great economic and environmental importance for phosphate industry.In this investigation,four different phosphate samples were aquired,characterized and tested in a specially designed laboratory-scale flotation column.Significant recovery improvement of coarse phosphate flotation was achieved using cavitation-generated nanobubble though its effects differ among the four testing phosphate samples.The laboratory-scale flotation column test results indicate that nanobubble increased P_2O_5 recovery by up to 10%～30%for a given Acid Insoluble(A.I.) rejection,depending on the characteristic of phosphate samples.The improvement effect of nanobubble on the hard-to-float particles was more significant than that on easy-to-float particles,especially at lower collector dosages.Nanobubbles reduced the collector dosage by 1/3 to 1/2.Nanobubbles almost doubled the coarse phosphate flotation rate constant and increased the flotation selectivity index by up to 25%.

Nanobubble generation and its applications in froth flotation(part IV):mechanical cells and specially designed column flotation of coal

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.

Froth flotation of scheelite – A review

Froth flotation of scheelite has regained new focus since the 2010s and research regarding floatability and reagents has made great progress over the years. The main objective was and remains the selective flotation of scheelite from other calcium-bearing minerals, in particular calcite, fluorite and apatite. Due to similar properties, most attempts have limited success or only specific application(linked to a type of ore or a location). This article aims at reviewing all general physical-chemical information on froth flotation of scheelite, including electrokinetic properties, influence of p H and already existing reagents as well as ones still under examination. It appears that chelating or mixed collectors and modified versions of sodium silicate and quebracho hold great promise for scheelite flotation, while the use of said depressants and/or promoters seems inevitable.

Froth flotation of refuse coal fines and process optimization using 2D surface plots

Refuse coal fines of size <500 μm was collected from a metallurgical coal preparation plant located in the eastern coalfield region of India. The coal was beneficiated using froth flotation technique to recover clean coal with ash content of about 20% with the highest possible yield. Diesel oil as collector and pine oil as frother were used. Box-Behnken statistical design was followed for analyzing the performance at varying pulp density, collector and frother dosage. Results were discussed using 2D surface plots. Response function predictions determined by the regression analysis show coefficient of correlation(R^2) for yield and the ash content as 0.72 and 0.86, respectively. The highest yield of 45.79% is obtained at pulp density 10%, collector dose 2 kg/t and frother dose 1.5 kg/t. The lowest ash content of 18.9% is obtained at pulp density 10%, collector dose 1 kg/t and frother dose 1 kg/t.

On the optimization of froth flotation by the use of an artificial neural network

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.

Analysis of Texture of Froth Image in Coal Flotation

Froth image features of coal flotation have been extracted and studied by neighboring grey level dependence matrix, spatial grey level dependence matrix and grey level histogram. In this paper, a basic algorithm of unsupervised learning pattern classification is presented, and coal flotation froth images are classified by means of self organizing map (SOM). By extracting features from 51 flotation froth images with laboratory column, four types of froth images are classified. The correct rate of SOM cluster is satisfactory. And a good relationship of froth type with average ash content is also observed.

Minimalization of Ash from Iranian Gilsonite by Froth Flotation

Gilsonite is a natural, brittle, and glisten tar hydrocarbon, which widely uses in the chemical, paint, and oil industry, besides asphalt production and thermal insulation. Major gangues of Gilsonite are gypsum, pyrite, silica, dolomite, calcite, and shale which are known as ash. Due to the fine liberation degree of gangue minerals from Gilsonite, most of the physical mineral processing methods are not applicable. Gilsonite has partially a behavior like coal in flotation due to its high carbon content and the similar composition of ash. As a result, flotation is one of the best methods to decrease the ash content of Gilsonite. In this study, four factors i.e. the dosage of collector, frother, and depressant, and solid to liquid ratio in three levels were examined in flotation to reduce the ash content and increase the recovery of Gilsonite. These tests were designed with the Taguchi method by Design-Expert software. Our results showed the lowest ash content of 5.2% was obtained in the condition which 200 g/t Gasoil as collector, 100 g/t MIBC as a frother, 300 g/t sodium silicate as a depressant, and pulp density was 5% solid to liquid weight ratio.

Kinetic approach to the study of froth flotation applied to a lepidolite ore

The number of published studies related to the optimization of lithium extraction from low-grade ores has increased as the demand for lithium has grown. However, no study related to the kinetics of the concentration stage of lithium-containing minerals by froth flotation has yet been reported. To establish a factorial design of batch flotation experiments, we conducted a set of kinetic tests to determine the most selective alternative collector, define a range of pulp p H values, and estimate a near-optimum flotation time. Both collectors（Aeromine 3000 C and Armeen 12D） provided the required flotation selectivity, although this selectivity was lost in the case of pulp p H values outside the range between 2 and 4. Cumulative mineral recovery curves were used to adjust a classical kinetic model that was modified with a non-negative parameter representing a delay time. The computation of the near-optimum flotation time as the maximizer of a separation efficiency（SE） function must be performed with caution. We instead propose to define the near-optimum flotation time as the time interval required to achieve 95%–99% of the maximum value of the SE function.

Separation of azodicarbonamide from surface of diatomite by froth flotation

The separation of azodicarbonamide(AC)from the surface of diatomite by froth flotation is investigated in this research.Pure samples of diatomite,AC and1:1mixtures of the two were floated in a lab-scale flotation cell withcollector dosage,frother type and dosage,and pH varied to determine the optimum experimental conditions.The diatomite sample and products from flotation tests were characterized using scanning electron microscopy(SEM)equipped with energy dispersive X-ray spectroscopy(EDX).The results of the flotation tests indicate that there is less AC on the surface of diatomite after flotation compared to the feed,while the AC present in diatomite pores remains unchanged.Additionally,Fourier transform infrared spectroscopy(FT-IR)was employed to study the mechanism of interaction between reagents and minerals.

2^kFactorial Experiments on Factors that Influence the Recovery of Gold during the Upgrade of Ilesha-Itagunmodi Gold Ore through Froth Flotation

A low-grade gold ore from Ilesha-Itagunmodi, south western Nigeria was panned, dried and ball-milled before sieving into fractions. The morphological, mineralogical and chemical composition was studied by optical micro-scopy (Reflected and Transmission), X-ray diffraction (XRD) and Energy Dispersive X-ray fluorescence (XRF), respectively. The sieved fractions were subjected to chemical analysis (AAS). The +106 μm sieve had the highest concentration of the mineral and was then selected for the upgrade through froth flotation using standard reagents. In this paper a report on a 2k factorial experiment that provides an understanding of the impact of operational variables on the quantity of gold mineral obtained from the ore during froth flotation is presented. Analysis results showed that Ilesha-Itagunmodi gold ore is non-refractory with fine grain particles, amenable to froth flotation and contained about 20 other associated minerals, gold had a concentration of about 0.0024%. A com-bination of P-Xanthate and amine glycol collectors at a pH of 9.2 only produced a considerable increase in gold yield. This translated to about 87.13% increase in recovery of gold from the ore. Analysis of variance (ANOVA) was carried out and the model equation obtained was subsequently optimised to obtain a model equation that could be used in predicting the recoverable quantity of gold, indicating that F11,1-values for Collector concentration, Frother concentration, pH and Conditioning time were 156.86, 6.96, 43.81, and 56.77 respectively. A model with an F value of 88.41 was obtained which indicated that the model was significant. The model equation obtained was subsequently optimised to be able to predict the recoverable quantity of gold. A “Pred R-Squared” value of 0.9365 (93.65%) was also obtained and is in reasonable agreement with the “Adj R-Squared” value of 0.9534 (95.34%). It was established that Ilesha placer gold ore is amenable to froth flotation using standard reagents.

The Method of Flotation Froth Image Segmentation Based on Threshold Level Set

A novel flotation froth image segmentation based on threshold level set method is put forward in view of the problem of over-segmentation and under-segmentation which occurs when the existing method segmented the flotation froth images. Firstly, the proposed method adopts histogram equalization to improve the contrast of the image, and then chooses the upper threshold and lower threshold from grey value of histogram of the image equalization, and complete image segmentation using the level set method. In this paper, the model which integrates edge with region level set model is utilized, and the speed energy term is introduced to segment the target. Experimental results show that the proposed method has better segmentation results and higher segmentation efficiency on the images with under-segmentation and incorrect segmentation, and it is meaningful for ore dressing industrial.

STUDIES ON THE FROTH CHARACTERISTICS OF COMPOSITE COLLECTORS IN NONMETALLIC MINERAL FLOTATION

The flotation results of a phosphate ore are improved by replacing the conventional collectors of fatty acids with composite collectors. The synergistic effect on the froth characteristics in systems using composite collectors has then been studied, and the concept of 'mixed hemimicellae' has been proposed in the adsorption of composite collectors at the air/solution interfaces.

浮选泡沫图像特征提取方法研究进展

机器视觉作为设备操作人员的工具,在泡沫浮选设备的监测中得到了广泛的应用。利用泡沫图像数据集建立预测识别模型,以初级泡沫特征参数为输入,以品位和回收率等浮选指标为输出。根据是否需要手动提取浮选泡沫图像特征,可以将特征提取算法划分为两大类别:一种是基于颜色、形态特征等的传统手动特征提取方法,另一种是基于深度神经网络的自动特征提取方法。本文总结并归纳了近年来浮选泡沫图像特征提取算法领域的研究进展,分析了各种方法的优势和不足,对当前难以人工识别泡沫状态及实现浮选自动化提升浮选效率,具有一定的指导价值。

硫化—胺法浮选菱锌矿体系中两相和三相泡沫的性能研究

硫化—胺法是氧化锌的主要选别方法之一,在工业生产中的指标较好,但存在浮选泡沫发黏、难消泡的问题。研究了硫化-胺法浮选菱锌矿体系中两相泡沫和三相泡沫的性能,考察了硫化钠用量、十二胺用量、矿物含量、矿物粒度、矿物种类等对泡沫稳定性的影响,并测试了不同矿物含量的矿浆黏度。结果表明,在采用硫化—胺法浮选菱锌矿时,加入硫化钠能够提高两相和三相泡沫的稳定性。不同粒度的矿物颗粒对泡沫稳定性影响不同,加入-74+37μm粒级的菱锌矿和石英颗粒均能够降低泡沫稳定性,而加入-37μm粒级的菱锌矿和石英颗粒均能够提高泡沫稳定性,-18μm的石英颗粒影响尤为明显。当十二胺与微细粒级石英共同存在时,浮选泡沫尤为稳定。加入石英颗粒后的三相泡沫半衰期均高于菱锌矿,这是由于石英矿浆的黏度高于菱锌矿,因而泡沫液膜的Marangoni效应增强,导致排液速率变慢,泡沫液膜变薄速率下降,泡沫稳定性更强。

基于浮选泡沫图像预测精矿品位的研究进展

随着人工智能技术在矿业生产的广泛应用,利用计算机视觉技术提高精矿品位预测的准确性和效率已成为必然趋势。在综述了传统图像处理算法和深度学习算法在精矿品位预测中的应用与发展历程基础上,并探讨了未来的发展趋势和挑战。传统图像处理技术通过提取泡沫图像的尺寸、颜色、纹理和流速等特征,结合分水岭分割、颜色矩、灰度共生矩阵和局部点特征匹配等算法进行特征提取。这些特征在计算资源有限的场景中具有一定的应用价值,但在应对精矿品位预测任务时精度较低。深度学习技术通过构建合适的模型架构并利用大量数据进行训练,能够提取高层语义特征,具有较高的预测精度,与图形处理单元(GPU)等高效运算设备配合使用,可实现高性能和高效率的统一。介绍了支持向量机(SVM)、极限学习机(ELM)等机器学习算法以及多层感知器(MLP)、全连接层和多尺度特征融合等深度学习算法在特征映射和品位预测中的应用,以及深度学习模型的发展历程。最后综述了工业界视觉检测系统的应用现状,并从数据驱动模型、多模态数据融合、算法实时性和数据集规模等方面分析了该领域所面临的挑战和未来发展趋势。

萘磺酸钠对硫化铅锌矿中碳质物的选择性抑制

针对硫化铅锌矿中碳质物吸附浮选药剂、恶化浮选效果的问题,本文以隐晶质石墨为难浮碳质物,研究了抑制剂萘磺酸钠(2-NSS)对方铅矿、闪锌矿以及隐晶质石墨浮选行为的影响。结果表明:2-NSS对难浮碳质物石墨具有明显的抑制作用。加入2-NSS后,方铅矿品位从82.28%提高至85.93%,回收率从82.08%提高至97.06%;闪锌矿品位从61.19%提高至63.48%,回收率从89.31%提高至93.46%。接触角试验、红外光谱分析、吸附量测试、浮选泡沫分析等结果表明:2-NSS易吸附于石墨表面,难吸附于铅锌硫矿物表面,2-NSS吸附于石墨表面后,能减弱捕收剂异丁基黄原酸钠(SIX)在石墨表面的吸附,减少药剂消耗,浮选泡沫更稳定。DFT模拟分析结果表明:2-NSS主要通过π-π堆积作用吸附于石墨表面。

基于质心−凸包−自适应聚类法的浮选泡沫动态特征提取

面对复杂的浮选现场环境及浮选泡沫自身相互粘连导致的边界不清等情况,现有泡沫动态特征(流动速度和崩塌率)提取方法往往无法准确划定属于每个泡沫的动态特征采样区域、不能全面匹配相邻帧间的特征点对且难以有效识别崩塌区域。针对上述问题,提出了一种基于质心−凸包−自适应聚类法的浮选泡沫动态特征提取方法。该方法采用集成Swin−Transformer多尺度特征提取能力的改进型Mask2Former,实现对泡沫质心的精准定位和崩塌区域的有效识别;通过最优凸包评价函数搜寻目标泡沫周围相邻一圈泡沫质心构建的凸包,拟合出接近实际泡沫轮廓的动态特征采样区域;运用基于Transformer的局部图像特征匹配(LoFTR)算法匹配相邻帧图像间的特征点对;针对动态特征采样区域内部的所有特征点对,通过基于OPTICS算法的主特征自适应聚类法提取每个泡沫的主要流动速度。实验结果表明,在普通泡沫质心定位和崩塌区域识别任务中,该方法分别取得了88.83%,97.92%的准确率及77.90%,96.52%的交并比;以2.69%的平均剔除率实现了99.93%的特征点对匹配正确率;在多种工况下均能有效划定与实际泡沫边界相近的特征采样区域,进而定量提取每个泡沫的动态特征。