ABSTRACT
Blasting engineers need right information at the right time to achieve safe and productive blasting. This paper explains how to use Image Processing (IP) and Machine Learning (ML) to compensate the drilling inaccuracy through adjustment of the drillhole explosives in order to enhance the Explosive Energy Distribution (EED). Accordingly, images of the drilled blasting site are collected by a specially programmed Unmanned Aerial Vehicle (UAV) and processed by a photogrammetry software to provide orthomosaic map and Digital Elevation Model (DEM) of the site. Subsequently, the models are analyzed to identify as-built locations of the drillholes, and finally, an optimization model is run to manipulate the amount and configuration of the charges in each drillhole in order to reach the most uniform explosive energy distribution in the rock mass. Current paper’s focus is on the process of models generation and identification of the exact locations of the drillholes.
