Recent Progress on Pressure‐Driven Electro‐Dewatering (<scp>PED</scp>) of Contaminated Sludge

Ramadan, Bimastyaji Surya; Farhah, A. D.; Hadiwidodo, Mochtar; Budihardjo, Mochamad Arief

doi:10.1002/9781119670186.ch25

Cited by 2 publications

(1 citation statement)

References 67 publications

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“…At present, there are many researches about optimization of dehydration, such as designing a dehydration circuit 9 , optimizing the filter medium 10 , 11 , driving the electric dehydration by pressure 12 , 13 . Although electrically driven dehydration is highly efficient, it is energy-consuming and low stability performance.…”

Section: Introductionmentioning

confidence: 99%

Optimization of dewatering process of concentrate pressure filtering by support vector regression

Liu

You

2022

Sci Rep

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This work studies the mechanism and optimization methods of the filter press dehydration process to better improve the efficiency of the concentrate filter press dehydration operation. Machine learning (ML) models of radial basis function (RBF)–OLS, RBF-generalized regression neural network, and support vector regression (SVR) are constructed, and laboratory and industrial simulations are performed separately, finally, optimization methods for the filtration dewatering process are designed and applied. In laboratory, all the machine learning models have obvious mistakes, but it can be seen that SVR has the best simulation effect. In order to achieve the optimization of the entire filtration and dewatering process, we obtained enough data from the industrial filtration and dewatering system, and in the industrial simulation results all the machine learning models performed considerably, SVR achieves the best accuracy in industrial simulation, and the simulated mean relative error of moisture and processing capacity are 1.57% and 3.81%, the model was tested with newly collected industrial data to verify the credibility. The optimal simulation results are obtained by optimization method based on control variables. Results show that the ML method of SVR and optimization methods of control variables applied to the industry not only can save energy consumption and cost but also can improves the efficiency of filter press operation fundamentally, which will provide some options for intelligent dewatering process and other industrial production optimization.

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Section: Introductionmentioning

confidence: 99%

Optimization of dewatering process of concentrate pressure filtering by support vector regression

Liu

You

2022

Sci Rep

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A Pore-Scale Physical Model for Electric Dewatering of Municipal Sludge Based on Fractal Geometry

Wang

et al. 2023

J. Environ. Eng.

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Recent Progress on Pressure‐Driven Electro‐Dewatering (PED) of Contaminated Sludge

Cited by 2 publications

References 67 publications

Optimization of dewatering process of concentrate pressure filtering by support vector regression

Optimization of dewatering process of concentrate pressure filtering by support vector regression

A Pore-Scale Physical Model for Electric Dewatering of Municipal Sludge Based on Fractal Geometry

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