Journal
ENVIRONMENTAL MONITORING AND ASSESSMENT
Volume 148, Issue 1-4, Pages 19-26Publisher
SPRINGER
DOI: 10.1007/s10661-007-0135-z
Keywords
Artificial neural network; Digital image analysis; Particle morphology; Suspended solids; Particle size distribution
Categories
Funding
- National Science Council of the Republic of China, Taiwan [NSC-94-2211-E-239-001]
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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 mu m. 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 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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