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Digital microscopic image application (DMIA), an automatic method for particle size distribution analysis in waste
S Cazares1, J A Barrios1, C Maya1
1Instituto de Ingeniería, Universidad Nacional Autónoma de México, Coordinación de Ingeniería Ambiental, Circuito Escolar S/N, Ciudad Universitaria, Coyoacán, Ciudad de México, 04510, México
Summary
A new digital microscopic imaging application (DMIA) offers a cost-effective alternative for measuring particle size distribution in environmental samples. This method, using neural networks, provides comparable results to laser diffraction, reducing complexity and time.
Area of Science:
- Environmental Science
- Analytical Chemistry
- Biotechnology
Background:
- Particle size distribution is a critical physical property in environmental samples.
- Conventional methods like laser diffraction are accurate but expensive and complex.
- There is a need for more accessible particle size analysis techniques.
Purpose of the Study:
- To develop and validate a digital microscopic imaging application (DMIA) for determining particle size distribution.
- To adapt existing algorithms and integrate neural network (NN) and Bayesian approaches for enhanced accuracy.
- To offer a cost-effective and less complex alternative to traditional methods.
Main Methods:
- A digital microscopic imaging application (DMIA) was developed using algorithms from helminth egg detection software.
- The DMIA incorporated neural network (NN) and Bayesian algorithms for particle size analysis.
- The method was applied to waste activated sludge (WAS), recirculated sludge (RCS), and pre-treated sludge (PTS) samples.
Main Results:
- The DMIA successfully determined particle size distribution in various sludge samples.
- Recirculation and electro-oxidation pre-treatment significantly reduced particle size and increased solubilization.
- DMIA results, particularly the 90th percentile of equivalent diameter, showed good agreement with laser diffraction measurements.
Conclusions:
- The developed DMIA provides a viable, less complex, and more economical alternative to laser diffraction for particle size analysis.
- The method demonstrates the effectiveness of integrating digital imaging with advanced algorithms for environmental sample characterization.
- Pre-treatment processes significantly impact sludge particle characteristics, which can be effectively monitored by DMIA.
