文成糯米山药机械化去皮关键技术研究与装备设计
Key Technologies and Equipment Design for Mechanical Peeling of Wencheng Glutinous Yam
摘要: 文成糯米山药作为国家地理标志产品,其深加工产业发展受制于传统人工去皮效率低、损伤大、易褐变等瓶颈。本文以推动特色农产品加工机械化、智能化为目标,针对糯米山药外形不规则、粘液多、质地脆等物理特性,系统分析了其机械化去皮的技术难点。通过对比多种去皮方案,创新性地提出“蒸汽预处理软化协同机器视觉引导自适应柔性切削”的机械化去皮技术路线。基于此,设计了一套集成视觉识别、PLC控制与自适应刀具的糯米山药去皮原理样机,本研究明确了关键工艺参数(如蒸汽温度90℃~98℃、时间25~40秒;超声波频率25~40 kHz),为解决文成糯米山药产业化去皮难题提供了切实可行的机械化技术方案,对提升地方特色农产品附加值和产业竞争力具有重要现实意义。
Abstract: As a national geographical indication product, the deep processing industry of Wencheng glutinous yam is constrained by bottlenecks such as low efficiency, high damage, and easy browning in traditional manual peeling. To promote the mechanization and intelligence of characteristic agricultural product processing, this paper systematically analyzes the technical difficulties in mechanical peeling of glutinous yam based on its physical characteristics, including irregular shape, high mucus content, and brittle texture. By comparing various peeling solutions, an innovative mechanized peeling technical route of “steam pretreatment softening combined with machine vision-guided adaptive flexible cutting” is proposed. Based on this, a prototype machine for glutinous yam peeling was designed, integrating visual recognition, PLC control, and adaptive cutting tools. This study clarifies key process parameters (such as steam temperature of 90˚C~98˚C, time of 25~40 seconds; ultrasonic frequency of 25~40 kHz), providing a practical mechanized technical solution to address the industrial peeling challenges of Wencheng glutinous yam. It holds significant practical importance for enhancing the added value and industrial competitiveness of local characteristic agricultural products.
文章引用:胡允森. 文成糯米山药机械化去皮关键技术研究与装备设计[J]. 农业科学, 2026, 16(2): 287-293. https://doi.org/10.12677/hjas.2026.162038

参考文献

[1] 金再欣. 文成糯米莳特征特性及栽培技术要点[J]. 中国农技推广, 2018, 34(4): 34-35.
[2] 张琦. 山药清洗去皮机传动装置设计[J]. 时代农机, 2016, 43(6): 72-73.
[3] 李政. 佛手山药去皮机械研究可行性报告[J]. 湖北农机化, 2020(3): 136-137.
[4] 焦瑞泽. 文成山药多糖和黏液质的理化性质及生物活性[D]: [硕士学位论文]. 杭州: 浙江大学, 2022.
[5] 李政. 用于无损草莓收获的柔性机器人系统: 设计、控制与评估[J]. 野外机器人学报, 2021, 38(6): 935-953.
[6] 王福军. 根茎类蔬菜机械化去皮技术研究进展[J]. 农业机械学报, 2021, 52(S1): 1-10.
[7] 唐楠锐. 荸荠去皮技术研究进展与发展趋势[J]. 中国农机化学报, 2023, 44(7): 101-110.
[8] 李培刚. 新鲜果蔬加工关键技术[J]. 农业机械, 2022(5): 80-83.
[9] 吴清政. 机器视觉在农业机械路径规划中的应用[J]. 工业控制计算机, 2023, 36(5): 92-94.
[10] 刘同金. 计算机视觉在果蔬分类中的应用[J]. 现代农业科技, 2020(5): 258, 262.
[11] 宁祎. 喷涂机器人路径规划方法分析与展望[J]. 科学技术与工程, 2019, 19(35): 19-27.
[12] 杨俊. 基于机器视觉的鲢鱼头加工装置设计及试验[J]. 华中农业大学学报, 2023, 42(1): 178-187.
[13] 俞国红. 自适应仿形甘薯削皮机优化设计与试验[J]. 农业机械学报, 2021, 52(3): 135-142.
[14] 曹光矗. 薯类作物去皮技术及设备研究进展与展望[J]. 农业工程, 2020, 10(5): 8-14.
[15] 魏丽娜. 表面不规则的难清洗果蔬清洗技术研究进展[J]. 食品安全质量检测学报, 2023, 14(14): 175-183.