APPLICATION OF IMAGE DIGITAL PROCESSING TO EVALUATE ACCURACY IN PREDICTING ROCK FRAGMENTATION INDUCED BY BLASTING

Predicting rock fragmentation induced by blasting operation is important in order to evaluate the success of blasting operation. It is necessary to select a method that is in accordance with the characteristics of geological condition and rock mass so that it can quickly provide accurate information. This study aims to evaluate whether Kuz-Ram model is accurate enough in predicting fragmentation of andesite. The analysis was carried out statistically by comparing the andesite fragmentation based on theoretical calculation method by Kuz-Ram model to the fragmentation based on image analysis method by Split Desktop which represents the actual field condition. The data were obtained from 30 blasting operations on andesite. The analysis result shows that the fragmentation based on the theoretical calculation using KuzRam model is not significantly different from the fragmentation based on Split Desktop. The maximum error of percent passing predicted by Kuz-Ram model is around 7% with an average error of 4.94%. Based on the result, calculation using Kuz-Ram theory can be performed to predict fragmentation of andesite.

Automated summary

This study evaluated the accuracy of the Kuz-Ram model in predicting the fragmentation of andesite. By comparing the theoretical calculation results of the Kuz-Ram model with the image analysis results of Split Desktop, it was found that there was no significant difference between the two. The maximum error of the Kuz-Ram model is about 7%, and the average error is 4.94%. Therefore, the Kuz-Ram model can be used to predict the fragmentation of andesite.