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Simultaneously monitoring the particle size distribution, morphology and suspended solids concentration in wastewater applying digital image analysis (DIA)

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Abstract

The efficiency of particle sedimentation in wastewater treatment is seriously affected by particle size distribution and morphology. A laser particle size analyzer is typically to analyze particle size distribution in wastewater. However, using this analyzer for on-line monitoring is difficult. This analyzer cannot measure particle morphology. An on-line digital image analysis (DIA) system was setup in this study to simultaneously measure particle size distribution and morphology in wastewater. The DIA measurement results show that the predominant particle size with an equivalent diameter (ED) was 10–40 μm. The particle size distribution measured by the DIA method similar to that measured with the laser particle size analyzer, indicating that the DIA method precisely measures particle size distribution. In addition, the mean fractal dimension (D f) of a set of particles was measured simultaneously, resulting in a good linear relationship between suspended solids (SS) precipitation efficiencies in samples. Finally, by combining the DIA measurement results with an artificial neural network (ANN), the SS concentrations of sample can be precisely predicted and the SS precipitation efficiencies were also evaluated.

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Authors and Affiliations

  1. Department of Safety, Health and Environmental Engineering, National United University, Miao-Li, 360, Taiwan, Republic of China

    Ruey-Fang Yu, Wen-Po Cheng & Mei-Ling Chu

  2. Department of Environmental Engineering and Management, Chaoyang University of Technology, Taichung, 413, Taiwan, Republic of China

    Ho-Wen Chen

Authors
  1. Ruey-Fang Yu
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  2. Ho-Wen Chen
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  3. Wen-Po Cheng
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  4. Mei-Ling Chu
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Correspondence to Ruey-Fang Yu.

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Yu, RF., Chen, HW., Cheng, WP. et al. Simultaneously monitoring the particle size distribution, morphology and suspended solids concentration in wastewater applying digital image analysis (DIA). Environ Monit Assess 148, 19–26 (2009). https://doi.org/10.1007/s10661-007-0135-z

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  • DOI: https://doi.org/10.1007/s10661-007-0135-z

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