摘要
确定室内污染源的位置对于保障室内空气品质和环境安全均具有重要意义。针对机械通风室内稳定流场中时变污染源的定位问题,本文提出了一种基于改进粒子群算法的多机器人嗅觉方法(UPSO)并通过实验验证了该方法的有效性。在实验中,以周期性时变源为对象,利用风扇营造稳定流场环境,通过3台机器人进行源定位实验。针对两个典型的源位置CS1(下风区)和CS2(回流区),利用UPSO方法分别开展了15组独立实验,分别成功了15组和12组(成功率分别为100%和80%),说明UPSO方法具有较高的成功率。进而针对源位置CS1,利用基于标准粒子群算法的源定位方法(SPSO)进行实验,该方法仅成功了2组(成功率为13.3%)。对比UPSO和SPSO方法的实验结果说明了本文方法的成功率明显高于SPSO方法,SPSO由于成功率较低尚不能满足实际应用的需求。
Locating indoor contaminant sources is important for ensuring indoor air quality and environmental safety.This study presented a particle swarm optimization( PSO) algorithm based multi-robot olfaction method( UPSO) for locating time-varying contaminant source in the indoor steady flow field with mechanical ventilation,and verified the effectiveness of UPSO through experiments.In the experiment,three robots were used to locate the periodic timevarying source in a steady flow field produced by a fan.For the two typical source locations CS1( downwind zone)and CS2( recirculation zone),15 and 12 experiments out of 15 experiments by using the UPSO method were successful,with success rates of 100% and 80%,respectively,indicating a high success rate of UPSO.For CS1,15 experiments were conducted by using the method based on the standard particle swarm optimization algorithm( SPSO),only 2 experiments were successful,with the success rate of 13.3%.A comparison of the experimental results of UPSO and SPSO methods indicated that the UPSO method performs much better than SPSO in terms of success rate,and SPSO method cannot meet the requirements of practical applications due to its low success rate.
作者
姜明瑞
廖禹
姜文青
杨洲
蔡浩
奉祁林
王强
杨艺斌
JIANG Mingrui;LIAO Yu;JIANG Wenqing;YANG Zhou;CAI Hao;FENG Qilin;WANG Qiang;YANG Yibin(College of Urban Construction,Nanjing Tech University,Nanjing 211800,China;College of Computer Science and Technology,Nanjing Tech University,Nanjing 211800,China;College of Energy Science and Engineering,Nanjing Tech University,Nanjing 211800,China;Research Institute for National Defense Engineering of Academy of Military Science PLA China,Beijing 100850,China;The 32182 Troop of PLA,100042;College of National Defense Engineering,Army Engineering University,Nanjing 210007,China)
出处
《建筑科学》
CSCD
北大核心
2020年第4期46-52,85,共8页
Building Science
基金
国家重点基础研究发展计划(973计划)“燃(油)气泄漏爆燃灾害安全性基础研究”(2015CB058000)
国家自然科学基金“受限空间中多个危险重气泄漏源的快速辨识问题研究”(51478468)
江苏省大学生创新创业训练计划项目(201910291029Z)。
关键词
时变污染源
机械通风
源定位
移动机器人嗅觉
室内环境
time-varying contaminant source
mechanical ventilation
source localization
mobile robot olfaction
indoor environment
