A Dynamic Image Analysis Method for Fragmentation Measurement in Blasting
Abstract
Fragment size optimization with selection of best values of blast design variables is an important process in mine-mill fragmentation system to maximize the system performance. This calls for measurement and analysis of mean fragment size with respect to blast design parameters. Digital image analysis technique is the most accepted method for measurement of blasted fragment sizes and their distribution. For quick assessment of the fragment sizes, a new novel method based on the digital images extracted from a blast video is reported in this paper. Correction factor for the size of fragments, considering the face movement is also proposed. The method has been tested with the help of seven blast data sets. The proposed dynamic image analysis technique can not only be used in fragment size estimation but also to assess the time-progressive size reduction in a blast, which can help designing the delay timing. Further, a possibility to estimate the in-situ block size is also explored with this method. The images of blast fragmentation were extracted from their videos at an interval of 0.08 s. These images were analyzed later for measurement of mean fragment size at respective times. The fragment size of the complete muck generated by the blast was also measured and correlated well with the sizes achieved from video analysis. The analysis revealed that from 0.08 s to 0.56 s from the initiation of the blasts, the fragment size reduction progressed from 58% to 80% of the estimated in-situ rock block sizes. Significant effect of blast design variables and two firing patterns on the mean fragment size was also observed. The analysis suggested that V-type firing pattern provides finer fragment size in comparison to the diagonal firing pattern. The suggested method provides an easy yet fast way for the assessment of blast fragment size.
Keyword(s)
Blasting, Blast Design, Dynamic image analysis, Fragmentation
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