Prediction of back break in blasting using random decision trees

Abstract

Back break is an unsolicited phenomenon caused due to rock condition, blast geometry, explosive and initiation system in mines. It does not help in creating a smooth high wall and free face for next blasting due to cracks, overhang and under-hang. It can cause rockfall during drilling due to the cracks present in the in situ rock mass at the perimeter. Due to improper free face created from the previous blast and the presence of loose strata in the face increases the overall cost of production. Therefore, predicting and subsequently optimising back break shall reduce their problems to some extent. In this paper, an attempt is made to predict back break using the random forest method. The variables used for the study was such as burden to spacing ratio, stemming to hole-depth ratio, p-wave velocity and the density of explosive. For the random forest model, R2 0.9791 and RMSE 0.87899 and for linear regression was R2 was 0.824 and root mean square error (RMSE) 0.72, respectively. From the field trials, it was evident that the use of low-density emulsion can help in reducing the back break and optimise the overall cost of the blasting process. The same results were validated using Random forest method wherein the model R2 was 0.9791 and RMSE was 0.8799.