机构地区:[1]Faculty of Mining Engineering,Petroleum and Geophysics,Shahrood University of Technology
出 处:《Journal of Rock Mechanics and Geotechnical Engineering》2019年第2期325-336,共12页岩石力学与岩土工程学报(英文版)
摘 要:The main purpose of blasting in open pit mines is to produce the feed for crushing stage with the optimum dimensions from in situ rocks. The size distribution of muck pile indicates the efficiency of blasting pattern to reach the required optimum sizes. Nevertheless, there is no mature model to predict fragmentation distribution to date that can be used in various open pit mines. Therefore, a new framework to evaluate and predict fragmentation distribution is presented based on the image analysis approach. For this purpose, the data collected from Jajarm bauxite mine in Iran were used as the sources in this study. The image analysis process was performed by Split-Desktop software to find out fragmentation distribution, uniformity index and average size of the fragmented rocks. Then, two different approaches including the multivariate regression method and the decision-making trial and evaluation laboratory(DEMATEL) technique were incorporated to develop new models of the uniformity index and the average size to improve the Rosin-Rammler function. The performances of the proposed models were evaluated in four blasting operation sites. The results obtained indicate that the regression model possesses a better performance in prediction of the uniformity index and the average size and subsequently the fragmentation distribution in comparison with DEMATEL and conventional Rosin-Rammler models.The main purpose of blasting in open pit mines is to produce the feed for crushing stage with the optimum dimensions from in situ rocks. The size distribution of muck pile indicates the efficiency of blasting pattern to reach the required optimum sizes. Nevertheless, there is no mature model to predict fragmentation distribution to date that can be used in various open pit mines. Therefore, a new framework to evaluate and predict fragmentation distribution is presented based on the image analysis approach. For this purpose, the data collected from Jajarm bauxite mine in Iran were used as the sources in this study. The image analysis process was performed by Split-Desktop software to find out fragmentation distribution, uniformity index and average size of the fragmented rocks. Then, two different approaches including the multivariate regression method and the decision-making trial and evaluation laboratory(DEMATEL) technique were incorporated to develop new models of the uniformity index and the average size to improve the Rosin-Rammler function. The performances of the proposed models were evaluated in four blasting operation sites. The results obtained indicate that the regression model possesses a better performance in prediction of the uniformity index and the average size and subsequently the fragmentation distribution in comparison with DEMATEL and conventional Rosin-Rammler models.
关 键 词:Rock FRAGMENTATION Image analysis Open PIT mine Split-desktop software package Decision-making TRIAL and EVALUATION laboratory(DEMATEL)technique
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