Evaluation of Blasting Efficiency in Surface Mines

Abstract

Drilling and blasting are the major unit operations in opencast mining. In spite of the best efforts to introduce mechanization in the opencast mines, blasting continue to dominate the production. Beside the production in open cast mining blasting and vibration also cause environmental problem. In bench blast design, not only the technical and economic aspects, such as block size, uniformity and cost, but also the elimination of environmental problems resulting from ground vibration, air blast and fly rock should be taken into consideration. The evaluation of ground vibration components plays an important role in the minimization of the environmental complaints. Odisha is rich in iron ore deposit and the mines invariably need blasting for loosen the rock mass. These are frequent complaints from the people surrounding the zone about adverse effect of blasting. This study is an attempt to evaluate same of those aspects. Two active iron ore mine have been considered for the analysis of ground vibration, air over pressure, flyrock as well as fragmentation parameters. There exist a few established approaches as USBM, Langefors-Kilstrom, Ambraseys-Hendron, Indian standard and CMRI to predict those. In this investigation the utility of those approaches are evaluated. It was observed that the two region Koira and Daitarido not confirm strongly to the five approaches. Artificial neural network is a technique that is gain wide acceptance even in heterogeneous condition. This study also finds that the prediction by ground vibration, air over pressure and fly rock by ANN would be better alternative. Model equation has also been developed with ANN approach. Mutual relations between stemming length, depth, fragmentation size, powder factor, explosive charge have also been determined.