茶鲜叶分选可实现茶叶高值化,但茶鲜叶易形成团聚体且难以分散,影响分选结果和效率。通过交叉气流分散茶鲜叶中的团聚体,交叉气流茶鲜叶团聚体分散装置由机架、对射光电传感器、输送带、滑轨、观察板、活动铰链、气嘴等部件组成。基于CFD-DEM联合仿真,分析了气嘴偏移量、气嘴行内间距、气嘴倾斜角度对分散程度的影响;采用Design-Expert 13软件设计三因素三水平正交试验方案,利用响应面优化得到了最佳参数组合。样机试验结果表明,气嘴采用最佳参数组合布置时,分散后得到的茶鲜叶散落矩形面积为0.343 m2、茶鲜叶面积占比为0.241,相较于未进行分散的茶鲜叶物料分别提升了90.6%和50.6%,且试验值与预测值的相对误差均小于5%。本装置实现了茶鲜叶团聚体的有效分散,为后续精准分选提供了理想的物料预处理条件。
Sorting fresh tea leaves can achieve high value tea production, but fresh tea leaves are prone to agglomeration and difficult to disperse, which affects the sorting results and efficiency. In this paper, disperse aggregates in fresh tea leaves by cross airflow. The fresh tea leaf agglomeration dispersing device based on cross airflow consists of a frame, opposite-facing photoelectric sensor, conveyer belt, slide rail, observation plate, movable hinge, air nozzle and other components. Based on CFD-DEM joint simulation, the influence of the air nozzle offset, air nozzle line spacing, and tilt angle of air nozzle on the dispersion degree was analyzed. Design-Expert 13 software was used to design a three-factor, three-level orthogonal test protocol, and the optimal parameter combination was obtained using response surface optimization. The experimental results show that when the air nozzle was arranged with the optimal combination of parameters, the rectangular area of dispersed fresh tea leaves obtained after dispersion was 0.343 m2, and the percentage of fresh tea leaves area was 0.241, which were 90.6% and 50.6% higher than the tea fresh leaf material without dispersion, respectively. The relative errors between the experimental and predicted values was less than 5%. This device achieved effective dispersion of fresh tea leaf agglomerates, providing ideal material pretreatment conditions for subsequent accurate sorting.
[1] 吴芹瑶, 杨江帆, 林程, 等. 中国茶叶生产布局变迁研究[J]. 茶叶科学, 2022, 42(2): 290-300.
Wu Q Y, Yang J F, Lin C, et al.Research on the changes of China's tea production layout[J]. Journal of Tea Science, 2022, 42(2): 290-300.
[2] 徐正炳, 季玉琴, 罗龙新. 茶鲜叶分级标准的研究[J]. 中国茶叶, 1990(6): 13-15.
Xu Z B, Ji Y Q, Luo L X.Research on the grading standards for fresh tea leaves[J]. China Tea, 1990(6): 13-15.
[3] 黄海涛, 毛宇骁, 李红莉, 等. 茶鲜叶机械化采收装备与技术研究进展[J]. 中国茶叶, 2023, 45(8): 18-23, 31.
Huang H T, Mao Y X, Li H L, et al.Research progress on mechanized harvesting equipment and technology for fresh tea leaves[J]. China Tea, 2023, 45(8): 18-23, 31.
[4] 张开兴, 马国良, 胡芳源, 等. 绿茶风选装备设计与性能试验[J]. 农业机械学报, 2023, 54(s2): 366-374, 387.
Zhang K X, Ma G L, Hu F Y, et al.Design of equipment and experiment on air separation performance of green tea[J]. Transactions of the Chinese Society for Agricultural Machinery, 2023, 54(s2): 366-374, 387.
[5] 欧阳腾雨. 双层茶叶风选机的控制系统设计与试验[D]. 合肥: 安徽农业大学, 2022.
Ouyang T Y.Design and test of control system for a double-layer tea winnowing machine [D]. Hefei: Anhui Agricultural University, 2022.
[6] 高士伟, 叶飞, 滕靖, 等. 新型鲜叶滚筒分级机的研制与参数优化[J]. 茶叶通讯, 2019, 46(4): 436-440.
Gao S W, Ye F, Teng J, et al.Development and parameter optimization of new roller screening machine for fresh tea leaves[J]. Journal of Tea Communication, 2019, 46(4): 436-440.
[7] 张兰兰, 董迹芬, 唐萌, 等. 名优茶机采鲜叶分级技术研究[J]. 浙江大学学报(农业与生命科学版), 2012, 38(5): 593-598.
Zhang L L, Dong J F, Tang M, et al.Classification technology of machine-plucking high-quality tea[J]. Journal of Zhejiang University (Agriculture and Life Sciences), 2012, 38(5): 593-598.
[8] Zhang X C, Wu Z M, Cao C M, et al.Design and operation of a deep-learning-based fresh tea-leaf sorting robot[J]. Computers and Electronics in Agriculture, 2023, 206: 107664. doi: 10.1016/j.compag.2023.107664.
[9] 夏先春, 甘密, 汪飞, 等. 湄潭翠芽鲜叶筛分设备关键技术的研究设计[J]. 现代机械, 2022(6): 99-102.
Xia X C, Gan M, Wang F, et al.Design of key technology of screening equipment for fresh leaves of Meitan Cuiya tea[J]. Modern Machinery, 2022(6): 99-102.
[10] Chen Z W, He L Y, Ye Y, et al.Automatic sorting of fresh tea leaves using vision-based recognition method[J]. Journal of Food Process Engineering, 2020, 43(9): e13474. doi: 10.1111/jfpe.13474.
[11] Wang R Y, Sun L A, Chen Z W, et al.Experimental evaluation of chain-driven mesh belt sorting system for machine-plucked fresh tea leaves[J]. Applied Engineering in Agriculture, 2020, 36(3): 399-409.
[12] Haider A, Levenspiel O.Drag coefficient and terminal velocity of spherical and nonspherical particles[J]. Powder Technology, 1989, 58(1): 63-70.
[13] Schiller V L.Über die grundlegenden Berechnungen bei der Schwerkraftaufbereitung[J]. Zeitschrift des Vereines Deutscher Ingenieure, 1933, 77(12): 318-320.
[14] Franquet E, Perrier V, Gibout S, et al.Free underexpanded jets in a quiescent medium: a review[J]. Progress in Aerospace Sciences, 2015, 77: 25-53. doi: 10.1016/j.paerosci.2015.06.006.
[15] 胡芳源. 名优绿茶风选技术与装备研制[D]. 泰安: 山东农业大学, 2023.
Hu F Y.Development of Wind Separation technology and equipment for famous and excellent green tea [D]. Tai'an: Shandong Agricultural University, 2023.
[16] 杜哲, 李邓辉, 李心平, 等. 茶茎秆离散元模型参数标定与试验[J]. 农业机械学报, 2025, 56(1): 311-320.
Du Z, Li D H, Li X P, et al.Calibration and experiment of discrete element model parameters for tea stem[J]. Transactions of the Chinese Society for Agricultural Machinery, 2025, 56(1): 311-320.
[17] 吕昊威, 武传宇, 涂政, 等. 基于EDEM的机采茶鲜叶振动式分级机分级参数优化[J]. 茶叶科学, 2022, 42(1): 120-130.
Lü H W, Wu C Y, Tu Z, et al.EDEM-based optimization of classification parameters of machine-picked tea fresh leaf vibratory classifier[J]. Journal of Tea Science, 2022, 42(1): 120-130.
[18] Sun H, John S.O, Salah A, et al. Pollutant cross-transmission in courtyard buildings: wind tunnel experiments and computational fluid dynamics (CFD) evaluation[J]. Building and Environment, 2024, 264: 111919. doi: 10.1016/j.buildenv.2024.111919.
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