A novel method for rapid diagnosis of operational stability in wastewater treatment plants using three-dimensional...

Accurate identification of water samples at key stages of wastewater treatment plants (WWTPs) plays a vital role in ensuring the stable operation of WWTPs. Three-dimensional fluorescence spectroscopy is an effective tool for water quality monitoring in WWTPs. However, water samples of the WWTP have the characteristic that the fluorescence shapes in the main stages are similar, and there is no significant difference in the fluorescence intensity values between adjacent stages, which makes it difficult for traditional two-dimensional matrix analysis methods to achieve effective identification. In view of these problems, this study proposes an identification method for water samples at key stages of the WWTP based on fluorescence feature images. This method first used the three-dimensional Savitzky-Golay (SG) smoothing algorithm to smooth and denoise the three-dimensional fluorescence spectra of WWTP water samples; then a wavelength-dependent threshold is introduced based on the mean filtering algorithm to select the fluorescence regions of the denoised spectra; next, the principal component analysis (PCA) algorithm was used to reduce the dimensionality of the selected fluorescence image; finally, the support vector machine (SVM) algorithm was employed to establish an identification model for water samples at key stages of WWTPs. The research results show that the proposed fluorescence feature image method can quickly and accurately identify water samples, and the accuracy for water samples from the influent tank, anaerobic tank, aerobic tank, anoxic tank, secondary sedimentation tank, and effluent tank can reach 100%, which is better than SG smoothing, PCA, and the method of only using wavelength - dependent threshold - mean filtering (WM). In addition, the reliability and stability of the method were validated using the holdout method. Therefore, the proposed method can be a potential approach for evaluating the operational stability of WWTPs.