陶红波,方勇,许广宏,卜冬曜,金彦亮.基于卡尔曼滤波的车内空气质量远程实时监测系统[J].电子测量技术,2016,39(11):126-130
基于卡尔曼滤波的车内空气质量远程实时监测系统
Remote monitoring system for air quality in vehicle based on kalman filter
  
DOI:
中文关键词:  车内空气质量  传感器  卡尔曼滤波
英文关键词:air quality in vehicle  air sensors  Kalman filtering  remote monitoring
基金项目:海汽车集团科技基金会(2015 1505)资助项目
作者单位
陶红波 上海大学通信与信息工程学院上海200444 
方勇 上海大学通信与信息工程学院上海200444 
许广宏 泛亚汽车技术中心有限公司上海201201 
卜冬曜 上海大学通信与信息工程学院上海200444 
金彦亮 上海大学通信与信息工程学院上海200444 
AuthorInstitution
Tao Hongbo School of Communication and InformationEngineering, ShanghaiUniversity, Shanghai 200444,China 
Fang Yong School of Communication and InformationEngineering, ShanghaiUniversity, Shanghai 200444,China 
Xu Guanghong Pan Asia Technical Automotive Center Co., Ltd, Shanghai 
Bu Dongyao School of Communication and InformationEngineering, ShanghaiUniversity, Shanghai 200444,China 
Jin Yanliang School of Communication and InformationEngineering, ShanghaiUniversity, Shanghai 200444,China 
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中文摘要:
      针对车内空气质量远程实时监测,设计了一种基于卡尔曼滤波的车内空气远程实时监测系统。系统以Exynos 4412微处理器为控制与信号处理核心,通过多个气体传感器采集PM2.5、PM10、甲醛浓度以及温度、湿度数据,在均值滤波消除数据的脉冲噪声后,利用卡尔曼滤波递归估计出气体最优数值,降低车辆不同状态下对传感器采集数值的精度影响,提高车辆空气质量监测的精度。监测数据在安卓开发板上绘图显示,并发送至移动终端,实现远程实时监测。当超过空气正常阈值,移动端可反向对车内进行声光报警与通风控制。实验表明,该系统能够有效提高污染气体监测的准确性与移动性。
英文摘要:
      In this paper, a remote monitoring system for air quality in vehicle is designed based on Kalman filter. The microprocessor Exynos 4412 is used as the controller and signal processer in this system. The data of PM2.5, PM10, formaldehyde, temperature and humidity are obtained by gas sensors.The mean filteringis used to eliminate pulse noiseof data and the Kalman filtering is used to calculatethe optimal estimation values. Thesedatadrawgraphics are displayed on theAndroid boardand sentto mobile terminal for remote real time monitoring.When the data is more than the normal threshold, the mobile terminal is able to give the acousto optic alarm and control the car air system. The experimental results show that the system can effectively improve the accuracy of pollution monitoring and mobility.
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