摘要
基于CH32V307VCT6构建了智能大棚环境检测系统,能够实时检测大棚的空气温度、空气湿度、土壤温度、土壤湿度、土壤氮磷钾微量元素的含量、土壤pH值和光照强度等关键参数。检测到的环境参数会实时地显示在上位机界面,以直观清晰的方式展现给巡检人员。智能大棚环境检测系统可以根据不同农作物所需要的环境参数来设置不同的阈值,神经网络模型通过对比实时监测数据与预设阈值,给出相应的指令来调整风扇转速和水泵功率,以实现精准的环境调控。并通过模拟实验改变大棚空气温度、空气湿度、光照强度、光源的方向等参数,来检验风扇电机、水泵电机、补光系统、自动追光系统的运行情况,实验结果表明该智能大棚环境检测系统具有响应快、自动化和智能化程度高等特点,有效保障了农作物的最佳生长条件,提升了资源利用效率,实现了节能减排的绿色生产目标。
The intelligent greenhouse environment detection system is constructed based on CH32V307VCT6,which can detect key parameters such as air temperature,air humidity,soil temperature,soil humidity,content of soil nitrogen,phosphorus,potassium and trace elements,soil pH value and light intensity in the greenhouse in real time.The detected environmental parameters will be displayed on the upper computer interface in real time and presented to the inspection personnel in an intuitive and clear way.The intelligent greenhouse environment detection system can set different thresholds according to the environmental parameters required by different crops.The neural network model gives corresponding instructions to adjust the fan speed and water pump power by comparing the real-time monitoring data with the preset threshold to achieve accurate environmental regulation.And through simulation experiments to change parameters such as greenhouse air temperature,air humidity,light intensity,and light source direction to test the operation of fan motors,water pump motors,supplementary lighting systems,and automatic light-tracking systems.The experimental results show that the intelligent greenhouse environment detection systemhas the characteristics of fast response,high degree of automation and intelligence,effectively ensuring the best growth conditions for crops,improving resource utilization efficiency,and achieving the green production goal of energy conservation and emission reduction.
作者
李得至
周金涛
Li Dezhi;Zhou Jintao(School of Electronic Information and Electrical Engineering,Yangtze University,Jingzhou,Hubei 434023,China)
出处
《机电工程技术》
2025年第16期102-106,共5页
Mechanical & Electrical Engineering Technology
作者简介
李得至(2000-),男,四川德阳人,硕士研究生,研究领域为检测技术与仪器;周金涛(2001-),男,湖北安陆人,硕士研究生,研究领域为深度学习目标检测。
