An online surface water COD measurement method based on multi-source spectral feature-level fusion.

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.