Classification performance comprehensive evaluation of an air classifier based on fuzzy analytic hierarchy process

The classification performance evaluation goal for an air classifier is usually limited to one of the classification performance indices including cut size, classification precision, Newton classification efficiency and degree of dispersion. This method hardly evaluates these performance indices of an air classifier comprehensively and suitably. In order to evaluate the classification performance truly and synthetically, Fuzzy Analytic Hierarchy Process is used to calculate the weights of the classification performance indices after determining the hierarchical model in the present paper. The dimensionless transformation eliminates the effect of the different dimensions. Then, the comprehensive evaluation value of the classification performance for each experiment is obtained using the linear weighted method. The maximum value corresponds to the best classification performance among these evaluation values. In the present study, a turbo air classifier is used as the classification system and talc powders are used as materials. The best classification performance indices are a cut size of 16.5 μm, a classification precision of 0.59, a Newton classification efficiency of 57%, and a degree of dispersion of 2.13. The corresponding optimal operational parameter combinations are: the feeding speed is 40 kg·h^–1, the air inlet velocity is 5 m·s^–1 and the rotor cage's rotary speed is 1200·min^–1. This assessment method avoids the limitation of evaluating a single classification performance index and the incomplete information derived from single factor experiments. Furthermore, the method also provides quantitative evaluation criteria for the classification performance of an air classifier. In the proposed method, the classification performance indices can be selected and the precedence relation matrix of Fuzzy Analytic Hierarchy Process can be set flexibly according to production requirements.     

Analysis and optimization of process parameters affecting classification performances indices of the turbo air classifier

Classification performance indices of a turbo air classifier mainly include cut size, classification precision, and Newton's classification efficiency, which would be effected by the process parameters including air inlet velocity, rotor cage's rotary speed and feeding speed. Orthogonal experiment method was used to analyze the influence of process parameters on the classification performance indices according to quartz sand powder classification experimental data as well as the calcium carbonate classification experimental data. Through range analysis of the orthogonal experiments for quartz sand and calcium carbonate, it is found that air inlet velocity and rotor cage's rotary speed play an important role on classification performance indices including classification accuracy, cut size and its corresponding Newton's classification efficiency. Feeding speed has slight impact on these performance indices. The best optimized combination of the process parameters for quartz sand was: when air inlet velocity was 20 m · s^–1, rotor cage rotary speed was 900 min^–1 and feeding speed was 56.69 kg · h^–1, the high Newton's classification efficiency and classification accuracy could be obtained and the corresponding values were 73% and 0.66. This best optimized combination was among the 9 group orthogonal experiments for quartz sand. The best optimized combination of the process parameters for calcium carbonate was: air inlet velocity was 14 m · s^–1, rotor cage rotary speed was 1200 min^–1 and feeding speed was 120 kg · h^–1. However this best optimized combination wasn't among the 9 group orthogonal experiments for calcium carbonate. The evaluated value of the Newton's classification efficiency of cut size can be obtained, which was 73%. In order to verify this evaluated value, the classification experiment for calcium carbonate with this best optimized combination of process parameters was carried out and experimental value of Newton's classification efficiency was 75%, which was close to the evaluated value. Through orthogonal experiment analysis, the influence law of process parameters on classification performances indices of the turbo air classifier can be acquired and the optimized combination of process parameters can be obtained. It paves the way of the development of the turbo air classifier.     

CFD simulation and performance optimization of a new horizontal turbo air classifier

A new horizontal turbo air classifier equipped with two inclined air inlets has been introduced. The flow field and classification performance of the classifier have been investigated using CFD method and response surface methodology (RSM). Simulation results show that the flow field is composed of the primary swirling flow and the secondary upward washing air, and the uniformly distributed swirling flow occupies the classifying chamber. The tangential gas velocity reaches the maximum value on the outer surface of the rotor cage, generating strong centrifugal force for the particle classification. The discrete phase model (DPM) can predict the cut sizes, but cannot present the fish-hook phenomenon. The desirable experimental condition by targeting the cut size of 20 μm and minimizing the classifying accuracy index is, rotor speed of 1373.6 rpm, primary air volume flow rate of 261.8 m³/h and secondary air volume flow rate of 42.4 m³/h. The corresponding fine and coarse fraction loss are less than 1.42% and 7.24%, respectively. This study provides a new strategy to design the horizontal turbo air classifier.     

Effect of rotor cage's outer and inner radii on the inner flow field of the turbo air classifier

The effects of rotor cage's outer and inner radii on flow field of the turbo air classifier are comparatively analyzed by numerical simulation using ANSYS-FLUENT. The results of quantitative analysis show when the rotor cage's outer and inner radii are increased, the tangential velocity, radial velocity and upward axial velocity decrease in the annular region and near the entrance of the rotor cage. However, when the rotor cage's outer and inner radii are too large or too small, the tangential velocity and radial velocity will be fluctuated greatly. Moreover, the rotor cage's outer and inner radii directly influence the radial velocity distribution in the rotor cage channel. The rotor cage's outer and inner radii should not be too large or too small. Therefore, in the seven contrast rotor cage models, model 100–70 and 90–60 are selected to carry out the calcium carbonate classification experiments due to their small tangential velocity and radial velocity fluctuations and well-distribution in the rotor cage channel. The experimental results reflect the characteristics of the numerically simulated flow field in the classifier.     

CFD simulation and optimization of the flow field in horizontal turbo air classifiers

This paper mainly presents a numerical study of the gas flow in horizontal turbo air classifiers. The effect of the air-inlet direction on the performance of classifier was also investigated through powder classification experiments. The simulated results show that the vertical vortex is the dominant flow in conical part of the classifier and there exists the horizontal vortex in the classifying chamber. The tangential velocity profile resembles a Rankine vortex inside the rotor cage. The vertical vortex intensity increases with increasing the inlet air velocity, while the rotor cage speed has limited effect on the control of gas pathlines in the classifying chamber. Horizontal turbo air classifiers are divided into four quadrants according to the air-inlet direction. For classifiers in quadrants I and III, a double-layer flow with opposite directions generates around the rotor cage which causes a secondary vortex. The secondary vortex is eliminated and the airflow becomes uniform in the classifier that belongs to quadrant Π or IV. The experimental results with fluidized catalytic cracking catalysts and fly ash demonstrate that cut sizes of this classifier decrease averagely by 5 μm and 2.2 μm respectively, and the classification accuracy increases by 7.5–10.3%.     

涡轮式超细气流分级技术研究和设备研制

本文引用涡轮──气流分级原理，研制成功具有卧式涡轮分级和二次风清洗粗粉机构的超细气流分级装置．实验表明，这些技术措施对提高分级细度、分级精度、回收率及产品粒度均匀性都有显著效果．对于新型超细分级装置的设计和应用具有指导意义．     

Effect of the rotor cage chassis on inner flow field of a turbo air classifier

As the connection between the center of rotor cage and the coarse powder collecting cone, rotor cage chassis of the turbo air classifier directly influences airflow movement in the classifier. In order to study the effect of rotor cage chassis on the inner flow field of a turbo air classifier, the flow fields of four rotor cage chassis structures with different opening size are simulated and compared using ANSYS-FLUENT 17.0. The simulation results show that there is “bypass flow” phenomenon for the classifier with the open rotor cage chassis, compared with the closed rotor cage chassis. The “bypass flow” phenomenon can change the airflow velocity distribution of the annular region. For the open rotor cage chassis, its opening size has no significant effect on the flow field distribution and the airflow velocity. However, the open or closed rotor cage chassis has great effect on the flow field distribution and the airflow velocity. The calcium carbonate classification comparative experiments are carried using the open and closed rotor cage chassis structures. The experiment results show that the open rotor cage chassis can decrease the cut size, and the closed rotor cage chassis can improve the classification accuracy.     

Structure optimization of rotor cage blades for turbo air classifier based on entropy production analysis

Entropy production theory based on the second law of thermodynamics was introduced for evaluating the flow field inside the turbo air classifier. The three new types of rotor cage with the wedge blades, the inverted wedge blades and the spindle blades were designed, and the flow field and the classification performance of the classifiers were investigated. The results show that, compared to the rectangular blades, the productions of total entropy, turbulent entropy and wall entropy of the wedge blades are reduced by 17.3%, 25.86% and 3.34%, respectively. The corresponding effective airflow area increases by 7.5%, and the residence time of 5 μm particle is shorten by 16%. The classifier with the wedge blades has smaller cut size and higher classifying sharpness. The results validate that the turbulent entropy generation can be an indicator for monitoring the overall flow field and the classifiers’ performance.     

Experimental and CFD study on a cyclonic classifier with new flow pattern

Physical principle of conventional top-inlet classifier (CTC) with reverse-flow pattern leads to the heavily fine particles entrainment in coarse fraction. Present work concentrates on the flow-field design for less downward airflow at near-wall region of the classifier. A new middle-inlet classifier (NMC) is proposed and analyzed using computational fluid dynamics (CFD) method and powder classification experiments. The results showed that new flow pattern characterized by a pair of vortexes was created in the new classifier. The upper vortex with 80% of the total air volume moves upward and forms the washing effect at near-wall region, which effectively reduces the fine particles entrainment in coarse fraction. The downer vortex with reverse-flow pattern discharges the coarse particles timely. The radial centrifugal sedimentation combined with the axial counter-current washing effect dominates the particle classification in the NMC. Compared to the CTC, classification accuracy index of the NMC with double-vortex averagely increases by 27% with a pressure drop reduction of more than 38%. This work offers a new principle for high-efficiency particle classification and new strategy for improving the classification performance of turbo air classifiers and hydrocyclones.     

Sorting of fine powder by gravitational classification chambers

Gravitational classification chambers (GCCs) were generally never used to classify fine powder because of its poor accuracy. However, in this study, a high quality closed-loop wind tunnel was designed and manufactured to improve this GCC drawback. A high quality closed-loop wind tunnel was designed to provide a low wall interference and low turbulence level in the test section. A wide-span feeder fed the powder smoothly as a curtain with a uniform aerodynamic interaction by the cross wind. The classification performance of GCCs has therefore been improved, and it could now classify lead–tin (Pb–Sn) powder with particle sizes smaller than 200 μm by controlling feeding rate and cross flow speed. Our experimental results show that GCCs have good classification performance from the view of the index of classification size ratio (CSR) by controlling cross flow speed and feeding rate. For GCCs the best sharpness index is about 0.4, the CSR is 1.09, and the cut size is 15.8 μm. The results demonstrate that GCCs had a fine powder classification capability and its cut-point was accurate enough for use in a classification operation. Furthermore, GCCs could be used to reduce ultra fine powder from raw powder. The volume percentage under 10 μm of raw material decreased from 7.61% to 0.64% through three repeatable classifications. This function could be considered as a good pre-process for specific classifiers (sieves or centrifugal classifiers). The product efficiency of this specific classifier could be increased by coupling it with GCCs.     

Design of the new guide vane for the turbo air classifier

The guide vane is a common guide part in a turbo air classifier. However, there is a lack of a theoretical design basis and an analogy method is often used to design the guide vanes. The guide vanes’ effects of improving the flow field distribution are obtained by means of comparison of the flow field of the classifiers with and without guide vanes. However, the guide vane of a 15° setting angle should be optimized due to the non-uniform airflow circumferential distribution in the annular region. To obtain a well-distributed flow field of a turbo air classifier, a design method for the guide vane is provided based on the airflow trajectory in the volute and a new guide vane of a 10° setting angle is designed under the operating condition of 12–1200. The numerical simulation results show that the standard deviation of circumferential radial and tangential velocity is decreased. Besides, the trajectories of the particles with the same size in different circumferential positions show their classification results are consistent. This guide vane design method is feasible and provides the design references for the turbo air classifiers.     

离心式细粉空气分级机的设计研究与工业应用

根据对离心式空气分级机分级机理与流场研究,找出了影响分级粒径和分级精度的主要因素;总结了一套细粉空气分级机的设计方法;并进一步为国内石油催化裂化催化剂生产厂设计了4套催化剂细粉分级生产装置,成功地将催化剂产品中小于20μm的细粉含量控制在1.5%～3%,使国产的裂化催化剂产品粒度分布达到了国际市场的要求。     

Vortex analysis and flow field optimization for the particle classifier with three rotary cages

The particle classifiers with three rotary cages have significant advantage in powder handling capacity. The flow field inside the classifiers were investigated from the perspective of vortex using Q criterion. Formation process and distribution of the vortices were intuitively exhibited. Structure of the guide cone was further optimized, and the classifying performance of the classifiers was evaluated. The results show that complex vortex structures were formed inside the classifier. The large-scale columnar vortex under the guide cone oscillates irregularly. This unwanted vortex is eliminated by extending the guide cone. The structure of the guide cone has little effect on the cut size, but the optimized guide cone with the long cylinder and cone significantly enhances the separation degree of the fine and coarse particles. The classifier obtains finer silica powder with a median size of 2.5 μm and higher Newton efficiency about 71.5%.     

Microfine Classification of Highly Loaded Suspensions

ABSTRACT

A centrifugal classifier has been designed, consisting of a rectangular rotor with two classification chambers and six rotating joints for connecting water and slurry streams with the rotor. The feed slurry enters the rotor in the middle of the classification chamber. Coarse particles settle to the outside, form a fluidized bed in front of the water inlet, and are sucked out of the rotor. Fine particles are carried to the inner radius with the main water flow. With the flow rates of classification water, feed, underflow, and the number of revolutions, the same cut size is adjusted. This paper presents experimental results with cutsizes between 0.5 and 5μm. The feed slurry was variated up to 30vol%. The performance of the classifier is remarkable, yielding up to 90% recovery of fine panicles.     

β-SiC微粉的气流分级工艺

采用生产型流化床对喷式气流粉碎分级机对β-SiC微粉进行气流粉碎分级实验研究,通过探讨不同的工艺参数对分级效果的影响,确定最佳进料速率、每一个粒级的产物所对应的最佳分级轮转速和进料粒度,并优化工艺流程.结果表明,最佳进料速率为42 kg/h;针对不同粒度的产物确定了最佳的分级轮转速;采用优化工艺能够高效地、稳定地获得不同粒径的分级产品,可实现粒度大于W2.5产品的β-SiC微粉的精细分级,分级产物粒度分布窄,颗粒形貌均匀.     

涡流空气分级机的分级特性

通过对重质碳酸钙和石英在CF型涡流分级机不同转速下进行分级实验,并利用计算流体力学软件对分级特性进行数值模拟。结果表明,随着转速增加,粒度d50和d90都减小,分级效率先增大后减小;在相同的参数下,不同物料的分级效果是不同的;随着转速的增加,涡流分级机流场的涡流现象增强,当转速增加到一定的程度时,出现了反流现象,使已经分离出的细粒又返回到分级区,从而影响分级机的分级效率。     

CXM型超细分级磨风口环气相流场的数值模拟

为探究CXM型超细分级磨风口环处结构参数与操作参数对粉碎区粉碎效果的影响,采用标准k-ε两方程湍流模型及多重参考系MRF模型对粉碎室内气相流场进行数值模拟。结果表明:在相同空气进风量及同一转速下,减小径向间隙有利于破坏物料环流层,当间隙为5～10 mm时,所形成的上升气流有助于物料的粉碎与分级。转盘转速的大小,一方面考虑转盘材质对转速的限制,另一方面应根据物料的物化特性结合生产经验确定转盘转速,以达到能量利用率最高。     

空气制冷机中小流量透平膨胀机的试验研究

研制开发了一个小型透平－逆Brayton循环空气制冷机系统。简要介绍了制冷机系统的研制意义及组成，对研制的小型空气制冷机系统进行了试验研究，着重研究了高速气体轴承低温透平膨胀机的热力学性能及机械性能。试验结果表明，在设计工况下研制的低温透平膨胀机具有较高的效率，且能稳定工作于设计转速。此外降温试验表明，研制的小型空气制冷机能达到设计要求的制冷温度－70℃。     

Continuous fine particle classification by water elutriator with applied electro-potential

In order to classify fine particles in slurry continuously, a horizontal type water elutriator with electrical potential is newly developed. The experimental classification performance was compared with the numerical calculation. Test particles used were pure silica particles with the mass median diameters of 3.5 and 2.5 μm.The effects of inlet flow rate, slurry concentration, applied electro-potential and the shape of inlet on the classification performance were also studied. The classification accuracy increased by applying the electro-potential and the cut size decreased with an increase in the electro-potential. The classification performance with a three-layer inlet was higher than that with a two-layer inlet.The experimental data agreed well with the numerical calculation. It is further shown that the 50% cut size was about 1 μm for a relatively short time, and the newly developed water elutriator is, therefore, effective for the classification of fine particles in slurries.     

气流分级机流场的数值模拟与优化

运用计算流体力学数值模拟的方法,研究气流分级机的内部气流流场情况,并对于分级机的工作参数进行优化。通过采用滑移网格技术模拟分级轮在气流分级机内的旋转,用结构网格与非结构网格结合的方法对气流分级机进行网格划分,主要研究了分级轮不同叶片数(4、6、12片),不同转速(500、1000、2000、3000r/min)下分级机内部流场情况并给出了相关解释。通过对不同参数的比较给出了优化的参数。模拟结果表明,分级轮转速越高、叶片数越多,分级效果越好。