Abstract
Coal flow volume is the essential basic data support for intelligent speed regulation and energy-saving control of coal mine transportation systems. To accurately measure the coal flow volume of conveyor belts, an innovative coal flow volume detection method for conveyor belts based on TOF vision was proposed in the paper. Both depth and grayscale images of the coal flow were collected by a TOF camera. Then an improved fast marching method based on the grayscale image was used to achieve depth image restoration. The coal flow volume of conveyor belts could be calculated by using the surface fitting method. Experimental results demonstrate that the coal flow detection accuracy of the proposed method can reach 97.35%, and the single-frame image processing time is less than 70.72ms. The proposed method is verified to meet the accuracy and real-time requirements of coal mines.
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