摘要
为了实现远程大棚温度控制,基于大数据分析设计了温度控制系统,采用5个温度传感器检测大棚温度,利用大数据融合技术,计算得到能表征整个大棚温度的数据。其过程如下:①剔除偶发因素造成的大偏差数据;②单个传感器检测数据融合,得到可以表征该传感器检测温度的数据;③对多个传感器表征温度进行融合,得到能表征整个大棚温度的数据。建立秋冬季黄瓜最优生长温度模型,并作为温度调控的理论目标值。大棚温度调控采用模糊控制的方法进行,将实际温度和理论目标值的偏差e及其偏差率ec作为模糊系统输入,将加热系统控制阀开启量作为模糊系统输出,进行测试,结果表明:系统具有一定的滞后性,调控温度性能良好。
In order to achieve the remote temperature control for greenhouse,this system was designed based on big data analysis.5 temperature sensors were used to detect greenhouse temperature,the datum was calculated,which could characterize the temperature of the whole greenhouse.The process is as follows:①the datum with large deviation caused by accidental factors were removed.②datum was fixed which detect by single sensor,and this data characterized the temperature of this sensor.③datum was fixed which detect by different sensors,and this data characterized the temperature of the whole greenhouse.Optimal growth temperature model for cucumber in autumn and winter was achieved,and taken as theoretical target value for temperature control.The temperature of greenhouse was controlled by fuzzy control,the deviation e between the actual temperature and the theoretical target value,and the deviation rate ec were taken as the fuzzy system inputs.opening amount of control valve in heating system was taken as the fuzzy system outputs.To test this system,this system had a good temperature control performance with certain hysteresis.
作者
刘睿潇
郑明伟
Liu Ruixiao;Zheng Mingwei(Weifang Engineering Vocational College,Qingzhou 262500,China;Weifang Vocational College,Weifang 261041,China)
出处
《农机化研究》
北大核心
2023年第7期94-98,共5页
Journal of Agricultural Mechanization Research
基金
山东省高等学校科技计划项目(J16LN72)。
关键词
大数据融合
模糊控制
最优生长模型
温室
big data fusion
fuzzy control
optimal growth model
groenhouse
