本文選題：渦輪氣流分級機 + 工藝參數(shù)�。� 參考：《西南科技大學》2017年碩士論文

【摘要】：目前,超細粉體材料正在滲入整個工業(yè)部門和高技術(shù)領(lǐng)域,更被譽為現(xiàn)代高新技術(shù)的原點,已應用到化工、輕工、冶金、電子、高技術(shù)陶瓷、生物醫(yī)學以及國防尖端技術(shù)等領(lǐng)域。用粉碎法生產(chǎn)超細粉體,很難一次通過粉碎就能達到所需粒度要求,必須要通過分級的方式將粒度達到要求的產(chǎn)品分離出來加以利用。因此能夠控制分級粒徑,提高分級精度,對超細粉體材料的制備來說具有重要意義。渦輪氣流分級機是一種典型的干法超細粉分級設(shè)備,由于其分級范圍廣、分級精度高等優(yōu)點在超細粉體工業(yè)中應用十分廣泛。但從目前的文獻來看,對渦輪氣流分級機的工藝參數(shù)研究還存在不足。本文對渦輪氣流分級機的相關(guān)理論、結(jié)構(gòu)進行了介紹,將現(xiàn)有國內(nèi)外先進的氣流分級機進行了分類說明。對現(xiàn)有的分級機性能評價指標進行了分析,在現(xiàn)有指標的基礎(chǔ)上進行了改進,得到了一種適用于工程領(lǐng)域的分級機性能評價指標。針對分級機二次風清洗參數(shù)進行了實驗研究,得出了分級機二次風量、二次風上升氣流速度對分級機相對分級精度的影響規(guī)律。由實驗結(jié)果可知,LNJ-36A系列渦輪氣流分級機的最佳二次風量為150m3/h,最佳二次風量下的最優(yōu)二次風上升氣流速度為3.91~4.73m/s,分級機調(diào)隙錐的最優(yōu)間隙值為12.5~15mm。為了更好地分析實驗現(xiàn)象,對分級機二次風清洗區(qū)域的流場進行了數(shù)值模擬,得出分級機二次風有效清洗區(qū)域為0~110mm,同時得到了二次風清洗區(qū)域的流場分布規(guī)律。針對分級機端面密封參數(shù)進行了實驗研究,得出了分級機端面密封間隙、氣流密封壓力對分級機相對分級精度的影響規(guī)律。由實驗結(jié)果可知,LNJ-36A系列渦輪氣流分級機的適宜端面密封間隙為3mm,其最佳氣流密封壓力為0.15MPa。同時通過對分級機端面密封區(qū)域流場的數(shù)值模擬,得出氣流密封失效壓力為0.05MPa,同時得到了有無氣封的流場情況,為實驗結(jié)果作出了進一步解釋。
[Abstract]:At present, ultrafine powder materials are infiltrating into the entire industrial sector and high-tech fields, and are also regarded as the origin of modern high and new technology. They have been applied to chemical, light, metallurgical, electronic, high-tech ceramics,Biomedicine and defense cutting-edge technology and other areas.It is difficult to achieve the required particle size by grinding the ultrafine powder in one time, and it is necessary to separate and utilize the products with the required particle size by means of classification.Therefore, it can control the particle size and improve the classification accuracy, which is of great significance to the preparation of ultrafine powder materials.Turbine airflow classifier is a typical dry ultrafine powder classifier. It is widely used in ultrafine powder industry because of its wide classification range and high classification accuracy.However, according to the current literature, the research on the technological parameters of the turbine airflow classifier is still insufficient.In this paper, the theory and structure of turbine classifier are introduced, and the advanced airflow classifiers at home and abroad are classified and explained.The existing performance evaluation index of classifier is analyzed and improved on the basis of the existing index, and a performance evaluation index suitable for engineering field is obtained.Based on the experimental study of the secondary air cleaning parameters of the classifier, the influence of the secondary air volume and the secondary air updraft velocity on the relative classification accuracy of the classifier is obtained.The experimental results show that the optimal secondary air flow rate of LNJ-36A series turbine air classifier is 150 m3 / h, the optimal secondary air flow velocity is 3.91 ~ 4.73 m / s, and the optimal clearance value of the clearance cone of classifier is 12.5 ~ 15 m ~ (-1) m ~ (-1) 路L ~ (-1) 路L ~ (-1) 路L ~ (-1) 路L ~ (-1) 路L ~ (-1) 路L ~ (-1) 路L ~ (-1) 路L ~ (-1).In order to better analyze the experimental phenomena, the flow field in the secondary air cleaning area of the classifier is numerically simulated. It is concluded that the effective cleaning area of the secondary air of the classifier is 0 ~ 110mm, and the flow field distribution law of the secondary air cleaning area is obtained.Based on the experimental study on the sealing parameters of the end face of the classifier, the influence of the seal clearance on the end face of the classifier and the pressure of the airflow seal on the relative classification accuracy of the classifier is obtained.The experimental results show that the suitable end face seal clearance of LNJ-36A series turbine airflow classifier is 3 mm and the optimum airflow seal pressure is 0.15 MPA.Through the numerical simulation of the flow field in the sealing area of the end face of the classifier, the failure pressure of the airflow seal is obtained to be 0.05MPa, and the flow field with or without the gas seal is obtained, which further explains the experimental results.
【學位授予單位】：西南科技大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：TB44

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