针对水质监测的紫外-可见光谱双光程融合优化算法

发布时间：2018-08-18 15:17

【摘要】：紫外-可见光谱法多参数水质在线监测系统面对复杂水体时,常需要频繁改变探头光程以保持光谱较高的信噪比。然而,适合的光程往往需要大量实验才可确定,难以满足在线监测系统对实时性、精度、灵敏度、稳定性等的实际需求。研究了一种紫外-可见光谱双光程融合优化算法,将同时采集的长短两种光程光谱使用了滑窗法估计它们光谱噪声方差分布,确定光谱强噪声区间;由于长短光程光谱的信号强度不同,使用了遗传算法计算得到双光谱融合的最佳增益匹配倍率;最后,按噪声方差分布使用分段加权方式得到较高信噪比的双光程融合光谱。实验结果表明,利用该法对重庆长寿湖水样、嘉陵江某排污口及邻苯二甲酸氢钾标准溶液三种样本进行测试,其融合光谱在200~250 nm区域的强噪声得到抑制,零值干扰左推至220nm之前,样本的峰值信噪比均有显著提高,证明了算法的有效性和普适性。该算法无需大量实验以获得最佳光程,对于拓宽紫外-可见光谱水质在线监测系统的应用范围具有较为重要的现实意义。
[Abstract]:UV-Vis multi-parameter water quality on-line monitoring system often needs to change the probe path frequently in order to maintain a high spectral signal-to-noise ratio (SNR) in the face of complex water bodies. However, the suitable optical path is often determined by a large number of experiments. It is difficult to meet the real time, precision, sensitivity, stability and other practical requirements of on-line monitoring system. In this paper, an optimization algorithm of UV-Vis dual optical path fusion is studied. The sliding window method is used to estimate the variance distribution of the spectrum noise and to determine the range of spectral strong noise from the two optical path spectra collected at the same time. Because the signal intensity of the long and short optical path spectrum is different, the genetic algorithm is used to calculate the optimal gain matching ratio of the double spectral fusion. Finally, according to the noise variance distribution, the two-path fusion spectrum with higher signal-to-noise ratio is obtained by using piecewise weighting method. The experimental results show that the method is used to test the water samples of Changshou Lake in Chongqing, a sewage outlet in Jialing River and the standard solution of potassium hydrogen phthalate. The strong noise of the fusion spectrum is suppressed in the region of 200 ~ 250nm. The peak signal-to-noise ratio (PSNR) of the sample is improved significantly before zero interference is pushed left to 220nm, which proves the validity and universality of the algorithm. The algorithm does not need a large number of experiments to obtain the optimal optical path, which is of great practical significance for widening the application range of the UV-Vis spectral water quality on-line monitoring system.
【作者单位】：重庆大学光电技术及系统教育部重点实验室;重庆工业职业技术学院;重庆市九龙坡区市政园林局;重庆理工大学;
【基金】：国家自然科学基金项目(61401049) 四川省科技支撑计划项目(2012SZ0111) 重庆市研究生科研创新项目(CYS14039)资助
【分类号】：X832;O657.3

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