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

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This study introduces a new online method for measuring chemical oxygen demand (COD) by fusing UV-Vis and fluorescence spectra. The advanced technique improves noise tolerance and measurement accuracy for environmental monitoring.

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Area of Science:

  • Analytical Chemistry
  • Environmental Science

Background:

  • Traditional chemical oxygen demand (COD) measurements face limitations with single or multi-wavelength UV-Vis absorbance, fluorescence spectroscopy, and wet chemistry methods.
  • Existing methods often struggle with accuracy and noise interference in online monitoring applications.

Purpose of the Study:

  • To develop and evaluate an advanced online detection method for COD measurement.
  • To overcome the shortcomings of existing spectroscopic and wet chemistry techniques for COD determination.

Main Methods:

  • Developed a multi-source spectral feature-level fusion method for online COD detection.
  • Utilized UV-Vis absorbance and fluorescence emission spectra, measured using a deuterium-halogen lamp and a 405 nm laser, respectively.
  • Applied Discrete Wavelet Transform (DWT) for signal de-noising and Successive Projections Algorithm (SPA) for feature extraction.
  • Established a COD measurement model using feature-level fusion and Least-Square Support Vector Regression (LS-SVR).

Main Results:

  • The proposed method demonstrated robust performance in terms of noise tolerance.
  • Experimental results indicated high measurement accuracy for COD determination.
  • The fusion approach effectively integrated spectral information from multiple sources.

Conclusions:

  • The developed multi-source spectral feature-level fusion method offers a significant improvement over traditional COD measurement techniques.
  • This approach provides a reliable and accurate online monitoring solution for COD in environmental applications.
  • The combination of DWT, SPA, and LS-SVR enhances the robustness and precision of spectral analysis for water quality assessment.