Reconstruction of the trajectories of rock fragments induced by blasts in an open pit mine by 3D analysis (Valdilecha Quarry, Madrid, Spain)

This work is based on a proof of concept, whose main goal is to determine whether it is feasible to rebuild rock fragment trajectories ejected from blasts. The initial focus is on creating and improving methods for precisely estimating the three-dimensional motions of rock fragments using photogrammetric analytic tools to improve the safety in mining operations. The objective is to test the effectiveness of the suggested methodologies and establish their applicability in actual mining scenarios, passing from the conceptual stage to an experimental pilot phase. The reconstructed trajectory methodology must be successful in moving from proof of concept to actual use in order to increase safety precautions and provide information that can be used to optimize blasting procedures. To achieve this, two cameras with High Frame Rate (HFR) capabilities are required to record the blasts, which will be carried out in the Valdilecha Quarry near Madrid (Spain). As proposed by the proof of concept, the photogrammetric analysis has been employed to extract the 3D motion of the objects, allowing the estimation of their movements using computational models by analysing each frame of the recorded videos. The Sony DSC-RX100 VII is chosen as the preferred camera for the study. It satisfies the requirements for HFR availability (used to capture slow-motion sequences), frame rate, pixel size and shooting time, ensuring optimal data capture for the application of the photogrammetric techniques. Finally, the developed approach has been tested in the field to reach the experimental pilot phase. As common in experimental work, moving from the controlled laboratory environment to the field presents its own difficulties. As expected, there were several problems in the analysis of the field recordings, due to the different environmental conditions. However, these difficulties have offered important information for enhancing the process in future iterations. The process can be further refined to produce more accurate and dependable outcomes in real-world circumstances through ongoing improvement and adaption.