摘要
温度控制对提高室内舒适度和节约能源有重大意义,室内温度的准确性和预测是室内温度精准监控的前提。设计出一种基于Fluent的室内温度智能监测系统。使用基于空间结构和实际温度模拟的Fluent仿真模型解决传感器布置及传感器数据冗余问题;搭建了基于MQTT(Message Queuing Telemetry Transport)协议的云服务器实现本地、云服务器和PC(Personal Computer)端人机交互界面之间的通信;通过使用卡尔曼滤波和数据融合技术进行温度数据的整合,提升了数据判别的准确性;并采用LSTM(Long Short-Term Memory)实现室内下一时刻温度的预测,达到控制温度和节约能源的目的。实际实验表明所述的系统可以实现室内温度的智能监控,LSTM的预测结果误差满足预期,系统整体运行达到预期效果。
Temperature control is of great significance to improve indoor comfort and save energy,and the accuracy and prediction of indoor temperature is the premise of accurate indoor temperature monitoring.In this paper,an intelligent indoor temperature monitoring system based on Fluent is designed.A Fluent model based on spatial structure and actual temperature is used to indicate the sensor locations and sensor data redundancy.A cloud server based on MQTT(Message Queuing Telemetry Transport)protocol is built to realize the communication between local,cloud server and PC(Personal Computer)-side human-computer interface.The temperature data is integrated by Kalman filtering and data fusion technology,which improves the accuracy of data discrimination.Besides,LSTM(Long Short-Term Memory)is used to predict the next moment of indoor temperature to achieve the purpose of controlling temperature and saving energy.Field experiments show that this system can realize the intelligent monitoring of indoor temperature and the error of LSTM algorithm meets prediction well.In addition,this intelligent system works as designed.
作者
杨佳晨
徐建
YANG Jia-chen;XU Jian(School of Electrical and Electronic Engineering,Wuhan Polytechnic University,Wuhan 430023,China)
出处
《武汉轻工大学学报》
CAS
2023年第1期101-107,共7页
Journal of Wuhan Polytechnic University
