| 基于无人机的施工扬尘污染源自动监测系统设计与实现 |
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| 引用本文： | 马国鑫,韩豫,陆建飞,姚佳玥,尤少迪.基于无人机的施工扬尘污染源自动监测系统设计与实现[J].中国环境监测,2018,34(1):151-156. |
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| 作者姓名： | 马国鑫 韩豫 陆建飞 姚佳玥 尤少迪 |
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| 作者单位： | 江苏大学土木工程与力学学院, 江苏 镇江 212013,江苏大学土木工程与力学学院, 江苏 镇江 212013,江苏大学土木工程与力学学院, 江苏 镇江 212013,江苏大学土木工程与力学学院, 江苏 镇江 212013,澳洲国立大学国家信息通信技术中心, 澳大利亚 堪培拉 2600 |
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| 基金项目： | 国家自然科学基金资助项目（11272137）；国家自然科学基金青年科学基金资助项目（51408266）；教育部人文社会科学研究青年基金项目（14YJCZH047）；江苏省普通高校研究生科研创新计划项目（KYLX16_0904） |
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| 摘 要： | 施工扬尘是大气污染物的主要来源和施工环境监测的重点对象,但传统监测手段的效率和效果有限。为此,综合使用无人机和图像识别技术,以HSV特征提取、直方图对比、非零像素点计算为核心,设计了施工扬尘污染源自动监测系统的结构、功能及运行流程,并对运行效果进行了测试。研究和测试表明:该系统可实现监测区航拍、污染源特征提取、污染源存在性检验、污染源种类判定和污染源分布区面积计算;该系统污染源存在性检验正确率为71%,污染源面积计算效率较高,污染源特征比对效果相对稳定,基本满足施工扬尘污染源监测需求。
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| 关 键 词： | 施工环境管理 扬尘监测 图像识别 无人机 系统设计 |
| 收稿时间： | 2016/10/9 0:00:00 |
| 修稿时间： | 2016/12/23 0:00:00 |
Design and Implementation of Automatic Monitoring System for Constructional Fugitive Dust Pollution Sources Based on UAV |
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| MA Guoxin,HAN Yu,LU Jianfei,YAO Jiayue and YOU Shaodi.Design and Implementation of Automatic Monitoring System for Constructional Fugitive Dust Pollution Sources Based on UAV[J].Environmental Monitoring in China,2018,34(1):151-156. |
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| Authors: | MA Guoxin HAN Yu LU Jianfei YAO Jiayue and YOU Shaodi |
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| Institution: | Faculty of Civil Engineering and Mechanics, Jiangsu University, Zhenjiang 212013, China,Faculty of Civil Engineering and Mechanics, Jiangsu University, Zhenjiang 212013, China,Faculty of Civil Engineering and Mechanics, Jiangsu University, Zhenjiang 212013, China,Faculty of Civil Engineering and Mechanics, Jiangsu University, Zhenjiang 212013, China and National ICT Australia and Australian National University, Canberra 2600, Australia |
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| Abstract: | The constructional fugitive dust pollution has been receiving more and more attentions due to the environmental and economic concerns. In the present study, an automatic monitoring system that can monitor constructional fugitive dust pollution has been proposed which utilizes UAV and image recognition technology. The system was further analyzed for its efficiency and effectiveness. The results showed that the system proposed here could collect the images of dust pollution monitoring area by UAV, extract and further identify the characteristics of pollution sources, ultimately enabling the determination of the existence and category of the pollution source, as well as its area calculation. Moreover, it was experimentally proven the correctness of existence test is 71% and the determination efficiency was relatively higher and more stable as compared to routine monitoring methods, which can meet the basic needs of constructional fugitive dust monitoring. |
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| Keywords: | constructional environmental management fugitive dust monitoring image recognition UAV system design |
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