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基于物联网技术的仓储烟叶霉变状态智能监测方法研究 被引量:4

Research on intelligent monitoring method of tobacco leaf mildew status in storage based on Internet of things technology
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摘要 为对烟叶仓储中的霉变状态进行全方面的快速检测,解决传统霉变检测手段流程复杂需要人工判定的问题,基于物联网技术与BP神经网络算法搭建了一套烟叶仓储环境特定参数的监测平台,从而实现对仓储烟叶霉变状态的智能监测。首先,设计了烟叶仓储环境数据采集终端和手持无线中继器,手持无线中继器用于唤醒数据采集终端,并利用无线射频传输的方式获取终端采集的环境参数,同时通过GPRS将数据发送到服务器,服务器完成数据解析处理。之后,基于BP神经网络算法建立了烟叶状态识别模型,通过对所采集环境参数进行分析处理,得出烟叶状态,并通过仿真试验验证了模型的有效性。最后,开发并完成了烟叶仓储环境智能监测信息管理系统,实现烟叶环境参数和烟叶霉变状态的直观显示和报警。测试结果表明,利用物联网技术并结合BP神经网络算法,能够有效地完成仓储烟叶霉变状态的监测,具有一定的实际应用价值。 In order to quickly detect the moldy state in tobacco storage in all aspects and solve the problem that the traditional moldy detection method is complicated and requires manual judgment,a set of monitoring of specific parameters of the tobacco storage envi⁃ronment was built based on the Internet of things technology and BP neural network algorithm.Platform,so as to realize the intelligent monitoring of the moldy status of the stored tobacco leaves.First,design a tobacco leaf storage environment data collection terminal and a handheld wireless repeater.The handheld wireless repeater was used to wake up the data collection terminal,and use radio fre⁃quency transmission to obtain the environmental parameters collected by the terminal,and send the data to the server via GPRS.The server completes data analysis processing.After that,a tobacco leaf status recognition model was established based on the BP neural network algorithm,and the tobacco leaf status was obtained by analyzing and processing the collected environmental parameters,and the effectiveness of the model was verified by experimental simulation.Finally,an intelligent monitoring information management sys⁃tem for tobacco storage environment was developed and completed to realize the visual display and alarm of tobacco environmental pa⁃rameters and tobacco mildew status.The test results showed that the use of the Internet of things technology combined with the BP neu⁃ral network algorithm can effectively complete the monitoring of the moldy state of the stored tobacco leaves,which has certain practi⁃cal application value.
作者 张竞超 翟乃琦 王一博 云利军 ZHANG Jing-chao;ZHAI Nai-qi;WANG Yi-bo;YUN Li-jun(School of Information,Yunnan Normal University,Kunming 650500,China)
出处 《湖北农业科学》 2021年第20期167-170,178,共5页 Hubei Agricultural Sciences
基金 云南省应用基础研究计划重点项目(2018FA033) 云南师范大学研究生科研创新基金项目(yjs2018129)。
关键词 仓储烟叶 BP神经网络 物联网技术 霉变状态监测 tobacco storage BP neural network Internet of things technology mildew status monitoring
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