Evolution of coal flocs during flocculation under different stirring velocities

ABSTRACT

A dynamic floc measurement system was developed to analyze flocs during sedimentation and automatically extract floc characteristics without damaging them. An optimized algorithm was proposed to remove fuzzy flocs, and visual inspection verified that this algorithm achieved satisfactory separation performance between well-defined and fuzzy flocs. This program was used to study the development of coal flocs and showed that the flocs grew rapidly at the beginning of flocculation. The floc size at equilibrium at low stirring velocities was larger than those at high stirring velocities. A high stirring velocity can cause irreversible damage to the flocs, and those flocs cannot be restored to their original size by decreasing the stirring velocity. In addition, the fractal dimension decreased with increasing time, indicating that there is an optimal stirring velocity which can be selected to enhance the size and structure of flocs. This research provided an effective way to study the characteristics of flocs, and the change process of the flocs under different stirring velocities was investigated in detail to understand the growth, breakage, and regrowth process.

KEYWORDS:

• Coal flocs
• dynamic measurement system
• stirring velocity
• flocculation process

Notations

A, projected area of floc; D_f, fractal dimension; d, equivalent circle diameter; d_i, clarity value of each floc; G_ave, average gray level of flocs in the minimum rectangular; I, gray matrix corresponding to the image; I_gx, I_gy, convolution gradient of the image in the x and y directions; $\bar{K}$, normalized Gauss convolution kernel; K_x, K_y, Gauss convolution kernel in the x and y directions; L, characteristic length of floc; n, parameter that can be set by users; ROI_i, smallest rectangle containing the floc; α, the proportion constant; α_i, clarity value of each floc calculated by a new approach; σ, parameter that can be set by users

Acknowledgements

This research was funded by the National Natural Science Foundation of China (no. 51974324) and Open Foundation of State Key Laboratory of Mineral Processing (no. BGRIMM-KJSKL-2020-22).