Acta Optica Sinica, Volume. 38, Issue 12, 1215009(2018)

Research on Measurement of Volume and Surface Area of Flotation Bubbles Based on Machine Vision

Xiuman Liang1、*, Wentao Liu1、*, Fusheng Niu2, and Tong Tian1
Author Affiliations
  • 1 College of Electrical Engineering, North China University of Science and Technology, Tangshan, Hebei 0 63210, China
  • 2 College of Mining Engineering, North China University of Science and Technology, Tangshan, Hebei 0 63210, China
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    Due to the impact of particles, the mechanical agitation and other factors, the rising floatation bubbles causes severe deflection and deformation. The horizontal set partitioning method is proposed for measuring the volume and surface area of the air bubbles. First, we establish an observation system for moving bubbles during the flotation process, and collect the bubble image. We use an edge detection method based on area segmentation to extract bubble edge. For overlapping bubbles, we use curvature scale space corner detection algorithm and direction chain code to mark the pits, thereby divide the overlapping contour. The edges of independent bubbles are fitted and reconstructed by least squares. Then we calculate the deflection angle of the bubble according to the edge, and adaptively select the separation interval, and finally the volume and surface area of the bubble are obtained by the accumulation of the divided portions. Experimental results show that the edge extracted by this method is accurate and not easily affected by the light environment. Under the conditions of different agitation rates, the average error and standard deviation of the measured bubble volume are 4.52% and 0.057 mm 3, which are more accurate than other methods.

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    Xiuman Liang, Wentao Liu, Fusheng Niu, Tong Tian. Research on Measurement of Volume and Surface Area of Flotation Bubbles Based on Machine Vision[J]. Acta Optica Sinica, 2018, 38(12): 1215009

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    Paper Information

    Category: Machine Vision

    Received: Jun. 15, 2018

    Accepted: Aug. 13, 2018

    Published Online: May. 10, 2019

    The Author Email:

    DOI:10.3788/AOS201838.1215009

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