摘要
针对光散射法在实时测量颗粒物浓度时噪声信号干扰微弱散射光信号的难题,本文设计并研制了一种基于自适应卡尔曼滤波算法与Mie散射原理的在线监测系统。该系统具备自动追踪浓度变化、低测量误差、低检出限以及实时监测的特点。通过MATLAB仿真优化了光源波长和探测角度,并完成了光路设计、硬件电路搭建及软件流程开发。实验标定结果表明,系统测量误差可控制在01mg/m^(3)以内;Allan方差分析显示,检出限在227s积分时间下达到06948μg/m^(3)。嵌入自适应卡尔曼滤波算法后,系统可在测量后1μs内快速响应浓度变化,并实现有效滤波,滤波后标准偏差最大降低567,显著提高了测量的稳定性。研究结果证明,该系统在颗粒物浓度实时监测中具有良好的精度和可靠性。
To address the challenge of noise interference with weak scattered light signals in real time particle concentration measurements using the light scattering method,an online monitoring system based on an adaptive Kalman filtering algorithm and Mie scattering theory is designed and developed.The system is characterized by automatic tracking of concentration variations,low measurement error,low detection limit,and real time monitoring capabilities.MATLAB simulations are conducted to optimize the light source wavelength and detection angle,accompanied by the design of the optical path,hardware circuits,and software processes.Experimental calibration results indicate that the measurement error is controlled within 0.1 mg/m.Allan variance analysis shows that the detection limit reaches 0.6948μg/m with an integration time of 227 s.By integrating the adaptive Kalman filtering algorithm,the system can respond to concentration changes within 1μs after measurement and achieve effective noise filtering.The standard deviation after filtering is reduced by up to 56.7%compared to before filtering,significantly improving measurement stability.Research findings demonstrate the system exhibits satisfactory accuracy and reliability in real time particulate matter concentration monitoring.
作者
王雪超
杨松杰
何孙东
刘素梅
谢节玲
潘孙强
李博
WANG Xue-chao;YANG Song-jie;HE Sun-dong;LIU Su-mei;XIE Jie-ling;PAN Sun-qiang;LI Bo(School of Physics,Zhejiang University of Technology,Hangzhou 310023,China;Hangzhou Pengpu Technology Co.,LTD,Hangzhou 310000,China;Zhejiang Institute of Quality Sciences,Hangzhou 310018,China)
出处
《激光与红外》
北大核心
2025年第10期1617-1624,共8页
Laser & Infrared
