基于浮选法的鼠笼式鲜枸杞分级机的设计与试验

Design and test of mouse cage fresh wolfberry classifier based on flotation method

[目的]提高鲜枸杞分级效率。[方法]设计基于浮选法的鼠笼式鲜枸杞分级机,以鲜枸杞横径为分级指标。利用鲜枸杞密度小于水的物理特性,运用浮选原理研制鲜枸杞分级机。通过力学分析及试验测量,计算和规定了分级机的理论结构参数。基于ANSYS Fluent模拟分级过程,分析模拟结果,并验证和精确该分级机的理论结构参数。[结果]分级机具体参数为:鼠笼直径0.34 m,长度2.1 m,辊杠直径10 mm,鼠笼倾斜角度17°,水流量1.7×10-2 m3/s,水流速3.5 m/s,鼠笼转速12 r/min。平行试验结果表明,鲜枸杞平均分级准确率约为93.79%,鲜枸杞无损率为98.21%;批量试验表明,鲜枸杞平均生产能力为1020.6 kg/h,平均分级准确率为92.85%。[结论]试验研制的基于浮选法的鼠笼式鲜枸杞分级机能够实现鲜枸杞低损、快速、高效分级。

[Objective]Improve the rapid grading technology of fresh goji berries.[Methods]Utilizing the physical properties of fresh goji berries with a density lower than water,a fresh goji berry classifier was developed using flotation principles.The theoretical structural parameters of the classifier were calculated and specified through mechanical analysis and experimental measurements.Based on ANSYS Fluent simulation of the grading process,analyzed the simulation results,and verified and accurately determined the theoretical structural parameters of the classifier.[Results]The specific parameters of the classifier were:cage diameter 0.34 m,length 2.1 m,roller bar diameter 10mm,cage tilt angle 17°,water flow rate 1.7×10-2 m3/s,water flow rate 3.5 m/s,cage speed 12 r/min.Using parallel and batch testing methods,the production efficiency and capacity of the prototype were verified.The parallel test results showed that the average classification accuracy of fresh goji berries was about 93.79%,and the non-destructive rate of fresh goji berries was 98.21%.Batch experiments have shown that the average production capacity of fresh goji berries was 1020.6 kg/h,and the average classification accuracy was 92.85%.[Conclusion]The squirrel cage fresh goji berry classifier developed in this article based on flotation method can achieve low loss,fast,and efficient classification of fresh goji berries.