Online Coke Granularity Estimation By Using Digital Image

by Terry Yuan-Fang Chen, Chun-Hung Wu, Der-Her Wang

Publisher - National Cheng Kung University, Taiwan, Republic of China. China Steel Corporation, Taiwan, Republic of China.

Category - Engineering & IT

A computer-based vision system was established for on-line coke granularity inspection by using a high-speed shutter CCD camera. A digital scheme that combines image enhancement, thresholding and morphology techniques was developed to detect individual coke properly from the coke image. The surface coke size was then determined by using the area moment of inertia principle with rotational search for estimation the granularity of cokes. Since the granularity of surface cokes measured is not equivalent to that of the real piled total cokes, the granularity of surface cokes measured on-line by our system was compared to the real ones measured by sieves manually. Statistic number and size difference between surface and total cokes were analyzed, and the results were used to modify the measured results for more accurate estimation. Test results of surface cokes show that an average size error of ±2% between the system and manual measurement was obtained. After modification, the error of granularity estimated from our system for total cokes could be less than 10%.

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