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茶叶科学 ›› 2019, Vol. 39 ›› Issue (6): 742-752.doi: 10.13305/j.cnki.jts.2019.06.013

• • 上一篇    

茶叶加工过程远程云监控与溯源研究及系统设计

蒋建东, 周倩, 潘柏松, 赵章风, 钟江, 乔欣, 张宪   

  1. 浙江工业大学机械工程学院,浙江 杭州 310023
  • 收稿日期:2019-03-07 修回日期:2019-07-18 出版日期:2019-12-15 发布日期:2019-12-24
  • 作者简介:蒋建东,男,博士,教授,主要研究方向为机械动力学,机电系统控制,jiangjd@zjut.edu.cn
  • 基金资助:
    浙江省科技计划项目(2017C02027)

Research and System Design of Tea Processing Remote Cloud Monitoring and Traceability

JIANG Jiandong, ZHOU Qian, PAN Bosong, ZHAO Zhangfeng, ZHONG Jiang, QIAO Xin, ZHANG Xian   

  1. School of mechanical engineering, Zhejiang University of technology, Hangzhou 310023, China
  • Received:2019-03-07 Revised:2019-07-18 Online:2019-12-15 Published:2019-12-24

摘要: 针对茶叶加工过程远程监控需求及茶叶溯源的加工环节缺失问题,构建了茶叶加工过程中茶叶状态参数及加工设备工艺参数远程物联网监测平台,实现了茶叶加工生产线远程设备运行参数监测监控与茶叶品质溯源。本研究采用B/S框架实现信息实时显示,综合鲜叶采摘信息和生产信息完备溯源过程,运用层次分析法分析生产过程参数对茶叶品质的影响,建立了茶叶加工过程溯源评价模型。在此基础上,构建茶叶生产离线与在线数据库融合质量评价模型,提高了数据存储质量。针对黄山毛峰初制加工生产线进行了远程监控系统开发及溯源信息采集验证试验,结果显示,平台运行稳定,数据显示准确完整,实时性较好。研究结果可为茶叶品质优化及大数据分析提供技术支持。

关键词: 茶叶生产, 远程监控, 溯源, 层次分析, 数据融合

Abstract: In view of the remote monitoring demand of tea processing and the lack of tea processing traceability, a remote IoT (Internet of things) monitoring platform for state parameters during tea processing was proposed. It achieved the remote monitoring of both processing line and tea state. A traceability evaluation model of tea processing was established by using B/S framework to show real-time information, combined data of both fresh leaf states and tracing information of processing, and analytic hierarchy process to analyze the effects of production parameters on tea quality. On this basis, the quality evaluation model of tea production offline and online database fusion was constructed to improve the quality of data storage. Finally, the remote monitoring system development and traceability information collection verification test were carried out for the Huangshan Maofeng preliminary processing production line. The results show that the platform is stable, the data display is accurate and complete, and the real-time performance is good, which provides technical support for tea quality optimization and big data analysis.

Key words: tea production, remote monitoring, traceability, analytical hierarchy process, data fusion

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