YANGMan-zi,WANGXiao-dong,LIUChang-qing,et al.Optimization of COD Prediction Model Based on Ultraviolet-visible Spectrum[J].China Water & Wastewater,2022,38(21):113-119.
Optimization of COD Prediction Model Based on Ultraviolet-visible Spectrum
China Water & Wastewater[ISSN:1000-4062/CN:12-1073/TU]
volume:
第38卷
Number:
第21期
Page:
113-119
Column:
Date of publication:
2022-11-01
- Keywords:
- ultraviolet-visible spectrum; full-spectrum analysis; chemical oxygen demand; principal component regression; partial least squares regression; model optimization
- Abstract:
- The accuracy, real?time and reliability of on-line water quality monitoring are the bottlenecks that restrict the improvement of automation level and the realization of intelligent management of wastewater treatment plants. The spectrometer was placed in a wastewater treatment plant in Qingdao to obtain the UV-Vis full-spectrum (200-737.5 nm) data of sewage. Meanwhile, the COD of corresponding samples was analyzed in the laboratory. COD prediction models were constructed based on principal component regression (PCR) method and partial least squares regression (PLSR) method, characteristic wavelengths were selected to reconstruct the model by using the idea of twice regression analysis, and the influence of different methods and different types of wavelength on improving the prediction ability of the model was discussed in detail. Compared with PCR method, the model constructed by PLSR method had better predictive ability. Based on PLSR method, the characteristic absorption wavelengths of COD and the characteristic adsorption wavelengths of nitrate and turbidity were selected for calibration, and the COD model obtained the optimal prediction ability. The goodness of fit (R2) of the model was 0.992, and the root mean square error of prediction (RMESP) was 1.979 mg/L. Therefore, the combined modeling method of COD characteristic absorption wavelength and non-predicted target characteristic wavelength could further improve the prediction accuracy of the model.
Last Update:
2022-11-01