摘要
土壤温度是影响作物生长及温室热环境的重要因素之一。为了准确预测温室土壤温度,采用计算传热学理论构建了温室土壤一维非稳态传热模型。为解决土壤传热模型边界条件难以获取的问题,采用长短记忆神经网络模型(LSTM)构建了边界条件预测模型,实现了对边界条件数据的准确预测。在传感器测量获取边界条件情况下开展温室土壤一维非稳态传热模型精度验证试验,结果表明不同深度土壤温度计算值和测量值变化趋势较为一致,两者平均绝对误差(MAE)最大值为1.29℃,最大绝对误差(MaxAE)最大值为2.16℃。对边界条件预测模型精度进行了验证,结果显示边界条件计算值与测量值决定系数R^(2)为0.99,MAE最大值为0.18℃,MaxAE最大值为2.63℃,结果表明本文构建的边界条件预测模型能够准确地预测边界条件。将边界条件预测与测量数据分别引入温室土壤一维非稳态传热模型,将两种情况下不同深度土壤温度计算结果与测量结果进行对比,结果显示,预测边界和测量边界情况下不同深度土壤温度计算结果较为一致,两种情况土壤温度计算值与测量值决定系数R^(2)相差最大为0.03,MAE相差最大为0.14℃,MaxAE相差最大为0.92℃。在预测边界情况下,所构建的温室土壤一维非稳态传热模型能够准确地对不同深度土壤温度进行预测。
Soil temperature is one of the important factors affecting crop growth and greenhouse thermal environment.In order to accurately predict the greenhouse soil temperature,a one-dimensional unsteady heat transfer model of soil was constructed by using theory of computational fluid dynamics.In order to solve the difficult problem of obtaining boundary condition,a boundary condition prediction model was constructed by using long short term memory(LSTM)neural network.Accuracy verification test of one-dimensional unsteady soil heat transfer model was firstly carried out with boundary condition measured by sensor.The results showed that the variation trend of calculated and measured soil temperature in different seasons and depths were consistent.The maximum value of mean absolute error(MAE)and max absolute error(MaxAE)between predicted and measured soil temperature were 1.29℃and 2.16℃,respectively.Secondly,the prediction model of boundary condition was verified.The results showed that the determination coefficient(R^(2))between predicted and measured value of boundary condition was 0.99.The maximum value of MAE and MaxAE between predicted and measured value of boundary condition were 0.18℃and 2.63℃,respectively.The results indicated that the model could accurately predict the boundary condition.Finally,the predicted and measured boundary condition data were introduced into one-dimensional unsteady heat transfer model of soil,respectively.The calculated results of the model with measured and predicted boundary condition were compared with the measured soil data.The results showed that the simulation results of soil temperature with predicted and measured boundary condition were consistent.The maximum deviation of R^(2),MAE and MaxAE between calculated and measured soil temperature under measured and calculated soil boundary condition were 0.03,0.14℃and 0.92℃,respectively.The above results showed that one-dimensional unsteady heat transfer model of soil under predicted boundary condition can predict the soil temperature in different depths accurately.
作者
张观山
丁小明
陈月锋
董维
何芬
尹义蕾
李天华
齐飞
ZHANG Guanshan;DING Xiaoming;CHEN Yuefeng;DONG Wei;HE Fen;YIN Yilei;LI Tianhua;QI Fei(Academy of Agricultural Planning and Engineering,Ministry of Agriculture and Rural Affairs,Beijing 100125,China;College of Mechanical and Electronic Engineering,Shandong Agricultural University,Taian 271018,China;Key Laboratory of Farm Building in Structure and Intelligent Construction,Ministry of Agriculture and Rural Affairs,Beijing 100125,China;Zhejiang Branch of Chinese Academy of Agricultural Mechanization Sciences Group Co.,Ltd.,Shaoxing 312039,China)
出处
《农业机械学报》
北大核心
2025年第8期634-643,共10页
Transactions of the Chinese Society for Agricultural Machinery
基金
国家自然科学基金项目(32201657)
山东省自然科学基金项目(ZR2021QF091)
农业农村部规划设计研究院自主研发计划项目(SP202101)
山东省重点研发计划重大科技创新工程项目(2022CXGC020708)
山东省重点研发计划项目(2023TZXD065)
北京市智能温室蔬菜创新团队项目(BAIC12-2024-08)。
关键词
温室
土壤温度
边界条件
LSTM
传热模型
greenhouse
soil temperature
boundary condition
LSTM
heat transfer model
作者简介
张观山(1988-),男,博士后,山东农业大学副教授,主要从事设施农业研究,E-mail:zgsh9919@sdau.edu.cn;通信作者:齐飞(1967-),男,研究员,主要从事设施农业研究,E-mail:qf2008@188.com。
