基于势场模拟的温度传感器优化布置研究  

Optimal temperature sensor placement based on potential simulation

作　　者：汪小龙[1,2] 何正亚[1] 方潜生[1] 葛运建[2] 汪增福[2] 

机构地区：[1]安徽建筑工业学院安徽省智能建筑重点实验室,合肥230022 [2]中国科学院合肥智能机械研究所传感技术联合国家重点实验室,合肥230031

出　　处：《低温与超导》2012年第2期76-80,共5页Cryogenics and Superconductivity

基　　金：国家自然科学基金(61073161;60875026;重大国际合作60910005)项目资助

摘　　要：以信息连续分布的智能空间内传感器优化布置为研究目标,以温度信息为例对智能空间进行势场模拟,在等势线上选取曲率较大、密集的点作为兴趣点(POI),提取POI初集;提出了一种基于质量阈值聚类的自适应二分法(简称QT算法),对兴POI初集进行优化;通过仿真和实测实验验证,在减少传感器数目的同时能够合理的规划区域中各被监测点,使得各传感器节点的效能得到很好的利用;所提出的方法同样适合智能空间中其它连续的信息场,如湿度、风速、电磁污染和VOCs等。This paper addressed the sensor - optimization of continuously - distributed - information for smart space. Poten- tial for temperature information was simulated, and POIs were selected in equipotential lines of large curvature or high density, thus the primary POI - Set was formed ; A novel Quality - Threshold - Clustering - Recursive - Bisection algorithm＇ （QT） was proposed for the Optimization of POI - Set ; Simulations and experiments show that minimum sensors may give reasonable results for sensor utilization and information acquisition; Method proposed may similarly be used for other information fields, including humidity, wind field, electromagnetic pollution ,VOCs and etc.

关 键 词：智能空间 势场模拟 兴趣点 传感器优化布置 

分 类 号：TP3-12[自动化与计算机技术—计算机科学与技术]