Guan Li, Tong Yifei, Li Jingwei, Wu Shaofeng, Li Dongbo
School of Mechanical Engineering, Nanjing University of Science and Technology Nanjing 210094 P. R. China
RSC Adv. 2019 Apr 11;9(20):11296-11304. doi: 10.1039/c8ra10089f. eCollection 2019 Apr 9.
To overcome the shortcomings of single or multi-wavelength ultraviolet-visible (UV-Vis) absorbance spectroscopic methods, fluorescence spectroscopic or wet chemistry methods for chemical oxygen demand (COD) measurement, an online detection method based on multi-source spectral feature-level fusion was developed and evaluated. In this method, UV-Vis absorbance spectra (deuterium-halogen lamp as light source) and fluorescence emission spectra (405 nm wavelength laser as excitation source) were measured online by a spectrophotometer (PG2000-Pro-Ex, Ocean Optics). Discrete wavelet transform (DWT) and a successive projections algorithm (SPA) were utilized to realize signal de-noising and feature extraction on the two types of spectra, respectively. Feature-level fusion and least-square support vector regression (LS-SVR) were used to establish the COD measurement model. Through comparison of experiments and results, it is shown that the proposed method has a good performance on both noise tolerance and measurement accuracy.
为克服单波长或多波长紫外可见（UV-Vis）吸光光谱法、化学需氧量（COD）测量的荧光光谱法或湿化学法的缺点，开发并评估了一种基于多源光谱特征级融合的在线检测方法。在该方法中，通过分光光度计（PG2000-Pro-Ex，海洋光学公司）在线测量UV-Vis吸光光谱（以氘卤灯作为光源）和荧光发射光谱（以405 nm波长激光作为激发源）。分别利用离散小波变换（DWT）和连续投影算法（SPA）对这两种光谱进行信号去噪和特征提取。采用特征级融合和最小二乘支持向量回归（LS-SVR）建立COD测量模型。通过实验和结果比较表明，所提方法在噪声容忍度和测量精度方面均具有良好性能。
