基于递归迭代算法的烟气分析

Xiaohui Su, Tongxin Hu
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引用次数: 0

摘要

烟气光谱分析的关键是如何从连续混合气体吸收光谱信号中分离和计算不同种类气体的浓度。本文在兰伯特-比尔定律的基础上,提出了一种新的迭代递归算法。该算法利用吸光度的叠加,实现了数据的非线性拟合。它利用波长最优和循环迭代的优点来区分不同成分的混合气体。实验结果表明,该方法可即时计算各种有害气体浓度,精度可达±2%。此外,该算法可同时测量多种气体的浓度,具有较强的抗干扰能力,适合工程实际应用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Flue Gas Analysis Based on Recursive Iteration Algorithm
The key point of flue gas spectra analysis is how to separate and calculate the concentration of different kinds of gas, which is from continuous mixed gas absorption spectrum signal. In this paper, a new iteration of the recursive algorithm is put forward on the basis of Lambert-Beer's law. This algorithm, using the superposition of the absorbance, achieves data nonlinear fitting. It takes the advantages of the wavelength optimum and the circular iteration to distinguish the gas mixture of different composition. Experimental results show that this method can calculate a variety of harmful gas concentration immediately, and the accuracy is up to ± 2%. In addition, this algorithm could be used to measure the concentration of many kinds of gases at one time, and it obtains strong anti-jamming capability which is suitable for practical application of engineering.
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