遗传算法优化小波阈值对水质光谱数据的去噪研究  

Denoising of Water Quality Spectral Data by Optimizing Wavelet Threshold Based on Genetic Algorithm

作　　者：肖渝 黄丽雯[1] 汤斌[1] 肖棋森 赵明富[1] 李奉笑 XIAO Yu;HUANG Liwen;TANG Bin;XIAO Qisen;ZHAO Mingfu;LI Fengxiao(Chongqing Key Laboratory of Fiber Optic Sensor and Photodetector,Chongqing University of Technology,Chongqing 400054,China)

机构地区：[1]重庆理工大学光纤传感与光电检测重庆市重点实验室,重庆400054

出　　处：《大气与环境光学学报》2021年第5期432-442,共11页Journal of Atmospheric and Environmental Optics

基　　金：国家自然科学基金青年基金项目,61805029;重庆市教委科研基金项目,KJQN201905605。

摘　　要：针对紫外-可见光谱法水质检测系统易受到仪器本身和外界环境的噪声干扰,所测得的光谱数据存在大量系统和杂散光噪声的问题,在对紫外-可见光谱法水质检测系统的噪声源分析的基础上提出将遗传算法应用于小波阈值优化的去噪方法,并与小波软阈值、SG平滑和中值滤波方法进行了对比。为评价去噪效果,对同一浓度的邻苯二甲酸氢钾标液的紫外-可见光谱数据进行去噪实验。在采用遗传算法选取小波最优阈值对标液进行去噪处理的同时,还采用传统小波软阈值去噪、SG平滑和中值滤波去噪作为对比。为验证该算法的实际可行性,进一步用这四种方法对某地排水沟和某污水处理厂排水口的实际水样光谱进行去噪处理。实验结果表明:基于遗传算法的小波阈值去噪效果良好,相较于传统的小波软阈值去噪、SG平滑和中值滤波的方法,信噪比分别提高了2.2994、5.7066、2.6155 dB,均方根误差分别减小了0.0028、0.0087、0.0033,峰值信噪比分别提高了2.0837、5.2569、2.7375 dB。基于遗传算法的小波阈值去噪算法不仅抑制了光谱数据中的噪声,同时也提高了系统精度,为紫外-可见光谱法水质光谱去噪处理提供了一种新的解决办法。Aiming at the problem that the ultraviolet-visible(UV-Vis)spectroscopy water quality detection system is susceptible to the noise interference from the instrument itself and the external environment,and there are a large number of system and stray light noise in the measured spectrum data,based on the analysis of the noise source of the water quality detection system by UV-Vis spectroscopy,a denoising method using genetic algorithm to optimize wavelet threshold is proposed and compared with the wavelet soft threshold,SG smoothing and median filtering methods.In order to evaluate the denoising effect,denoising experiments are carried out on the UV-Vis spectrum data of potassium hydrogen phthalate standard solution with the same concentration.The genetic algorithm is used to select the wavelet optimal threshold for denoising,and at the same time,the traditional wavelet soft threshold denoising,SG smoothing denoising and median filter denoising are also used for comparison.In order to verify the practical feasibility of the algorithm,the four methods are further used to denoise the spectra of actual water sample from a domestic sewage and outlets of a sewage treatment plant.The experimental results show that the wavelet threshold denoising effect based on genetic algorithm is obvious.Compared with the traditional wavelet soft threshold denoising,SG smoothing and median filtering methods,the signal-to-noise ratio of the new denoising method has been improved by 2.2994,5.7066 and 2.6155 dB respectively,the root mean square error has been increased by 0.0028,0.0087 and 0.0033,and the peak signal-to-noise ratio has increased by 2.0837,5.2569 and 2.7375 dB.It is shown that the wavelet threshold denoising based on genetic algorithm not only suppresses the noise in spectral data,but also improves the system accuracy,which provides a new solution for water quality spectral denoising by ultraviolet-visible spectroscopy.

关 键 词：紫外-可见光谱法 水质检测 遗传算法 小波阈值去噪 

分 类 号：X832[环境科学与工程—环境工程]