摘要
针对高尘环境下的烟气浓度测量,提出了采用小波滤波结合遗传算法反演气体浓度的光谱数据处理方法,并对信号噪声比较低的实测光谱数据进行了浓度反演.结果表明:在各种烟尘浓度下,利用该算法都能大幅度减少烟尘颗粒物Mie散射对差分吸收光谱(DOAS)法的影响,气体浓度反演结果接近于真实值,表明该算法具有较高的浓度反演精度和良好的抗粉尘干扰能力,且具有很小的零点误差.
Aiming at the flue gas concentration measurement in high dust concentration environment, a new spectral data processing method of wavelet combined with genetic algorithm to reverse gas concentration was proposed. It was applied in the concentration inversion of experimental spectral data at low noise. Re- sults show that, under various dust concentration conditions, the influence of particles Mie scattering to differential optical absorption spectroscopy （DOAS） can be decreased greatly by this method. The inversion result of gas concentration is close to reality value. It shows that this algorithm has high precision of concentration inversion and good performance of anti-jamming to dust, and has small zero point error.
出处
《动力工程》
CSCD
北大核心
2009年第5期436-439,455,共5页
Power Engineering
基金
国家自然科学基金重点资助项目(50836003)
关键词
烟气
烟尘颗粒物
烟气排放监测
差分吸收光谱法(DOAS)
遗传算法
MIE散射
flue gas
flue gas dust particles
flue gas emission monitoring
differential optical absorptionspectroscopy （DOAS） technique
genetic algorithm
Mie scattering
