一种气流分级机端面密封特性研究

发布时间：2018-06-13 02:01

本文选题：气流分级机 + 迷宫密封　；参考：《化工进展》2017年03期

【摘要】：涡轮气流分级机是应用十分广泛的超细分级设备,但是仍存在分级机端面跑粗现象。本文通过实验探究分级机端面间隙对不同物料分级效果的影响,并在传统迷宫密封的基础上设计一种气密封装置,探究不同气封压力对不同物料分级效果的影响,并以相对分级精度为评价指标。利用Ansys Workbench 15.0软件,对气流密封的流体区域进行了数值模拟,得出了压力场和速度场的分布情况。模拟及实验结果表明:相对分级精度随着分级机端面间隙的增大而减少,当间隙保持在3mm左右时,相对分级精度较高且分级机亦可正常运转;在分级机端面间隙为3mm以下时,增加气流密封,相对分级精度随气封压力的增加先增大后减小,当气密封压力为0.15MPa时,粉煤灰和矿渣的相对分级精度最高;气流密封的失效压力为0.05MPa;在相同间隙的情况下,增加气密封,粉煤灰和矿渣的相对分级精度分别从0.202、0.187增加到0.458、0.408,分级机性能得到提高,分级效果更为良好。
[Abstract]:The turbo air classifier is a very widely used superfine classification equipment, but there is still a rough phenomenon in the end face of the classifier. In this paper, the effect of the end gap of the classifier on the classification effect of different materials is investigated. A kind of airtight package is designed on the basis of the traditional labyrinth seal, and the classification of different gas seal pressure on the classification of different materials is explored. The effect is influenced by the relative classification accuracy as the evaluation index. Using the Ansys Workbench 15 software, the flow area of the airflow seal is numerically simulated, and the distribution of the pressure field and velocity field is obtained. The simulation and experimental results show that the relative classification accuracy decreases with the increase of the end gap of the classifier, and the clearance remains in the 3M. When the M is around, the relative classification precision is higher and the classifier can operate normally. When the end gap of the classifier is below 3mm, the airflow seal is increased and the relative classification accuracy increases first and then decreases with the increase of gas seal pressure. When the gas seal pressure is 0.15MPa, the phase of fly ash and slag is the highest, and the failure pressure of airflow seal is 0.05M Pa, when the gas seal is added, the relative classification accuracy of fly ash and slag is increased from 0.202,0.187 to 0.458,0.408 in the same gap, and the performance of the classifier is improved and the grading effect is better.
【作者单位】：西南科技大学制造科学与工程学院;西南科技大学环境与资源学院;
【基金】：西南科技大学研究生创新基金(15ycx130) 国家自然科学基金(11402218)项目
【分类号】：TQ051.8

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