用紫外连续光谱对烟气排放有害成分的在线监测的关键和难题是: 如何从连续的混合气体吸收光谱信号中分离并解算各气体的浓度, 为此基于朗伯-比尔定律我们提出了一种递推迭代反演解算算法, 该算法利用各气体在190～290 nm波段的特征吸收峰, 结合吸光度的二元叠加性, 在某种气体的一个特征吸收点上假设其他气体没有吸收, 推出该气体的初始浓度, 然后切换到另外一个特征吸收点上, 将该气体吸收光子数从测出的总吸收光子数中减去, 得到另一气体的初始浓度, 依此类推得到各气体的初始浓度； 然后再回到第一种气体的特征吸收点上, 从吸收的总光子数中减去其他各气体的吸收光子数, 再次得到第一种气体的一次迭代浓度, 依此类推得到其他气体的一次迭代浓度, 重复迭代直到相邻两次得到的浓度差小于某一值为止, 得到的各气体的浓度即为各气体的精确浓度。 实验结果表明: 该方法能够一次同时解算出多种有害气体浓度且精度达±2%, 算法简单满足实时性需求, 抗干扰能力强, 适合工程实际应用。

The key and challenge problem of in-situ monitoring poisonous elements of gases is how to separate the various gases absorption signal from mixed gases absorption spectroscopy and compute it’s accuracy concentration? Here we present a new algorithms in return recursion iteration based on Lambert-Beer principle. In the algorithms, recurred by the character of absorption peak of various gases in the band of 190～290 nm UV rays continuous spectroscopy and the character of twin element fold for absorbance are used. Firstly, the authors suppose that there is no absorption for others gases in the character absorption band for a certain gas, the authors can inference the initial concentration of the gas. Then the authors switch to another character spectroscopy, and put the photons that gases absorption out of the total number of absorbed photons that are measured. So we could get the initial concentration of another gas. By analogy the authros can get the initial concentration of all kinds of other poisonous elements. Then come back to the character spectroscopy of the first gas, the authors can get a new concentration of the first gas from the difference between the total number of absorbed photons and the photons that other gases absorption. By analogy the authors can get the iterative concentration of other gases, by irterating this process repeatly for some times until the measurement error of the adjacent gas concentration is smaller than a certain numerical value. Finally the authros can get the real and accurate concentration of all kinds of gases. Experiment shows that the authors can get the accurate concentration of all kinds of gases with the algorithm. The accuracy can be within 2%, and at the same time, it is easy enough to satisfy the necessity of real-time requirement. In addition it could be used to measure the concentration of many kinds of gas at a time. It is robust and suitable to be taken into practice.