Optimization of indoor temperature sensor layout using proper orthogonal decomposition and Greedy algorithm
作者单位：School of Electrical and Information Engineering Jiangsu University
会议名称：《第43届中国控制会议》
会议日期：1000年
学科分类：12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 080202[工学-机械电子工程] 081104[工学-模式识别与智能系统] 08[工学] 081304[工学-建筑技术科学] 0835[工学-软件工程] 0802[工学-机械工程] 0813[工学-建筑学] 0811[工学-控制科学与工程] 0812[工学-计算机科学与技术（可授工学、理学学位）]
关 键 词：Large-space building Proper orthogonal decomposition Greedy algorithm Sensor layout optimization
摘 要：Accurately estimating the distributed indoor thermal environmental parameters with limited sensors is crucial for indoor environmental quality and building energy efficiency. This study combines proper orthogonal decomposition and greedy algorithm for sensors layout s optimization in a large-space thermal environment. Firstly, choose the initial quantity and positions of sensors, and collect steady temperature field information based on the feasible range of environmental variables;Secondly,extract features from the collected dataset using proper orthogonal decomposition, and determine the optimal number of sensors based on the energy proportion of the eigenvalues;Thirdly, select the sensor positions iteratively based on the correlations of eigenvectors and sensors using greedy algorithm. A field experiment for performance validation is conducted using a matrix of72 temperature sensors in a large cafeteria. By using the collected 27 snapshot datasets, the temperature field can be reconstructed by Linear Stochastic Estimation using only six optimal sensors(steady-state error: 0.2433, RMSE). The proposed POD-Greedy optimization strategy is also compared with another heuristic inference method. The better performance shows great potential for engineering practice and applications.