融合多传感器数据的空气细颗粒物自动监测技术优化  

Technology optimization of automatic airborne fine particulate matter monitoring by fusing multi-sensor data

作　　者：王璐 WANG Lu(Danzhou Environmental Monitoring Station,HanNan Danzhou 571700 China)

机构地区：[1]儋州市环境监测站,海南儋州571700

出　　处：《粘接》2023年第10期189-192,共4页Adhesion

摘　　要：针对监测空气细颗粒物的过程,在监测数据处理上很难保证高水平的数据可信度,提出融合多传感器数据的空气细颗粒物自动监测技术。利用无线射频技术和灰尘传感器采集空气细颗粒物数据,集合各个传感器的数据,经过处理得到多维数据向量集,将向量集作为输入项,利用贝叶斯定理融合多传感器监测数据,得到处理后的监测数据,在GPRS逻辑结构的支持下,实现监测数据的自动传输。实验结果表明:提出的空气细颗粒物自动监测技术在无障碍环境和有障碍环境下均能保持高水平的数据通信能力,数据丢包率低,监测数据误差小,数据可信度更高。To address the difficulty of ensuring a high level of data credibility in the process of monitoring fine particulate matter in the air,an automatic monitoring technology for fine particulate matter in the air that integrates multiple sensor data is proposed.Wireless radio frequency technology and dust sensors were used to collect fine particulate matter data in the air,and the data from each sensor were aggregated,processed to obtain a multidimensional data vector set,which was used as the input item.The Bayesian theorem is used to fuse the multiple sensor monitoring data,and the processed monitoring data were obtained.With the support of the GPRS logical structure,the automatic transmission of monitoring data was realized.The experimental results showed that the proposed automatic monitoring technology for fine air particles could maintain a high level of data communication capability in both barrier-free and obstruction-free environments,with low packet loss rate,small monitoring data errors and higher data reliability.

关 键 词：多传感器 信息融合 细颗粒物 自动化 实时监测 

分 类 号：TP23[自动化与计算机技术—检测技术与自动化装置] X84[自动化与计算机技术—控制科学与工程]