基于EDEM的机采茶鲜叶振动式分级机分级参数优化

摘要/Abstract

摘要： 针对目前机采茶鲜叶分级设备存在的分级效率低、对鲜叶损伤大等问题。以振动式机采茶鲜叶分级机为试验对象,提出了一种茶鲜叶粘弹性物料建模方法,并以振动频率、振动方向角、振幅为自变量,以筛分率、优质茶筛分率为目标优化值,基于EDEM软件对其进行仿真试验,运用响应面优化法得到优化参数为振动频率29.0 Hz、振幅9.0 mm、振动方向角34.7°。在此参数下,仿真试验得到的筛分率为75.38%,优质茶筛分率为95.65%。根据最优参数组合开展仿真与样机验证试验,结果表明,样机验证试验得到的筛分率为71.07%,优质茶筛分率为93.26%。结合仿真试验和样机试验结果,筛分率的准确性达到93.9%,而优质茶筛分率的准确性达到97.4%。基于响应面分析法的仿真优化参数具有较高的可靠性,在此最优参数下,分级机具有较好的分级效果。本研究可以为机采茶鲜叶分级设备的优化提供参考。

关键词: 机采茶鲜叶, 振动分级机, 鲜叶物料建模, 响应面优化

Abstract: In view of the low grading efficiency and large damage to fresh leaves of the current machine-picked tea fresh leaf grading equipment, a vibrating machine-picking fresh tea leaf classifier was used in this study as the test object, and a new tea leaf viscoelastic material modeling method was proposed. The vibration frequency, vibration direction angle, and amplitude were used as independent variables. The sieving rate and famous tea sieving rate were used as target optimization values. The simulation test was carried out based on the EDEM software. Using the response surface optimization method, the optimized parameters were obtained as the vibration frequency of 29.0 Hz, the amplitude of 9.0 mm, and the vibration direction angle of 34.7°. Under this parameter, the sieving rate obtained by the simulation test was 75.38%, and the sieving rate of famous tea was 95.65%. According to the optimal parameter combination, the simulation and prototype verification test were carried out, and the results show that the sieving rate obtained by the prototype verification test was 71.07%, and the sieving rate of famous tea was 93.26%. Combining the simulation test and prototype test results, the accuracy of the screening rate reached 93.9%, and the accuracy of the screening rate of famous tea reached 97.4%. The simulation optimization parameters based on response surface analysis had high reliability. Under this optimal parameter, the classifier had a better classification effect. This study provided a reference for the optimization of machine-picked tea fresh leaf grading equipment.

Key words: machine-picked fresh tea leaves, vibration classifier, fresh leaves material modeling, response surface optimization

中图分类号:

吕昊威, 武传宇, 涂政, 陈建能, 贾江鸣, 陈之威, 叶阳. 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.

LYU Haowei, WU Chuanyu, TU Zheng, CHEN Jianneng, JIA Jiangming, CHEN Zhiwei, YE Yang. EDEM-based Optimization of Classification Parameters of Machine-picked Tea Fresh Leaf Vibratory Classifier[J]. Journal of Tea Science, 2022, 42(1): 120-130.

参考文献

[1] 唐小林, 李文萃, 范起业, 等. 机采茶鲜叶分类分级技术及相关设备研究进展[J]. 中国茶叶加工, 2015(2): 5-8.
Tang X L, Li W C, Fan Q Y, et al.Research on the classification technology and the grading equipment of machine-plucking fresh leaves[J]. Chinese Tea Processing, 2015(2): 5-8.
[2] 沈宝国, 董春旺, 蒋修定, 等. 茶树鲜叶分选研究现状与展望[J]. 中国农机化学报, 2016, 37(8): 87-90.
Shen B G, Dong C W, Jiang X D, et al.Current research and future development of tea sorting technology[J]. Journal of Chinese Agricultural Mechanization, 2016, 37(8): 87-90.
[3] 胡永光, 李建钢, 陆海燕, 等. 等直径滚筒式茶鲜叶分级机设计与试验[J]. 农业机械学报, 2015, 46(s1): 116-121.
Hu Y G, Li J G, Lu H Y, et al.Design and experiment of equant-diameter roller screening machine for fresh tea leaves[J]. Transactions of the Chinese Society for Agricultural, 2015, 46(s1): 116-121.
[4] 袁海波, 滑金杰, 邓余良, 等. 基于YJY-2型鲜叶分级机的机采茶叶分级分类工艺优化[J]. 农业工程学报, 2016, 32(6): 276-282.
Yuan H B, Hua J J, Deng Y L, et al.Optimization of grading and classification technology for machine-picking leaves based on YJY-2 type classifier[J]. Transactions of the Chinese Society of Agricultural Engineering, 2016, 32(6): 276-282.
[5] 王荣扬. 柔性片状物料气固耦合数值计算及机采茶鲜叶分选装置试验研究[D]. 杭州: 浙江理工大学, 2020.
Wang R Y.Numerical simulations of gas-solid coupling mechanism of flexible flaky materials and experimental studies of the sorting equipment for machine-plucked fresh tea leaves [D]. Hangzhou: Zhejiang Sci-Tech University, 2020.
[6] 骆耀平, 王永镜, 张兰兰, 等. 名优茶鲜叶原料分级机研究[J]. 茶叶, 2012, 38(1): 27-33.
Luo Y P, Wang Y J, Zhang L L, et al.Study on the grading machine of high quality tea leaf material[J]. Journal of Tea, 2012, 38(1): 27-33.
[7] 任广鑫, 范起业, 何鑫, 等. 大宗茶鲜叶原料分级机的研制与实验[J]. 食品工业科技, 2013, 34(7): 290-292, 304.
Ren G X, Fan Q Y, He X, et al.Development and experiment of the grading machine for ordinary tea leaf material[J]. Science and Technology of Food Industry, 2013, 34(7): 290-292, 304.
[8] 张舰, 刘凡一, 陈军, 等. 基于DEM的谷物清选筛振动筛分虚拟试验研究[J]. 农机化研究, 2019, 41(2): 187-191.
Zhang J, Liu F Y, Chen J, et al.Virtual vibration screening experiments of grain cleaning sieve based on DEM[J]. Journal of Agricultural Mechanization Research, 2019, 41(2): 187-191.
[9] 钟江, 黄剑虹, 杨韬, 等. 茶叶风选机优化研究[J]. 茶叶科学, 2013, 33(6): 576-583.
Zhong J, Huang J H, Yang T, et al.Optimization study of tea winnowing machine[J]. Journal of Tea Science, 2013, 33(6): 576-583.
[10] 王美美, 王万章, 杨立权, 等. 基于EDEM的玉米子粒建模方法的研究[J]. 河南农业大学学报, 2018, 52(1): 80-84, 103.
Wang M M, Wang W Z, Yang L Q, et al.Research of discrete element modeling method of maize kernel based on EDEM[J]. Journal of Henan Agricultural University, 2018, 52(1): 80-84, 103.
[11] 原建博, 李骅, 吴崇友, 等. 基于离散单元法的水稻籽粒快速颗粒建模研究[J]. 南京农业大学学报, 2018, 41(6): 1151-1158.
Yuan J B, Li H, Wu C Y, et al.Study on apace particle modeling of rice grain basis on the discrete element method[J]. Journal of Nanjing Agricultural University, 2018, 41(6): 1151-1158.
[12] 李金光, 刘雪美, 邹亮亮, 等. 菠菜主根离散元建模方法与试验验证[J]. 农机化研究, 2021, 43(8): 181-185, 191.
Li J G, Liu M X, Zou L L, et al.Discrete element modeling method and experimental verification of spinach main-root[J]. Journal of Agricultural Mechanization Research, 2021, 43(8): 181-185, 191.
[13] 李兵, 李为宁, 柏宣丙, 等. 基于EDEM的茶鲜叶分级机的筛分率的研究[J]. 茶叶科学, 2019, 39(4): 484-494.
Li B, Li W N, Bai X B, et al.Research on screening rate of fresh tea leaves classifier based on EDEM[J]. Journal of Tea Science, 2019, 39(4): 484-494.
[14] 何磊, 张宪, 赵章风, 等. 基于PFC3D的茶叶杀青过程数值模拟和设备参数分析[J]. 茶叶, 2013, 39(1): 17-23.
He L, Zhang X, Zhao Z F, et al.Numerical simulation and parameter analysis of fresh tea leaf fixation process based on PFC3D[J]. Journal of Tea, 2013, 39(1): 17-23.
[15] 张西良, 柯于仁, 孙鹏飞, 等. 基于EDEM的椭球形颗粒直线振动筛分分离粒度研究[J]. 江苏农业科学, 2018, 46(14): 188-191.
Zhang X L, Ke Y R, Sun P F, et al.Study on the particle size of ellipsoidal particles by linear vibrating sieving based on EDEM[J]. Jiangsu Agricultural Sciences, 2018, 46(14): 188-191.