Developing a Model for the Identification of Onset of Failure of Slopes in Surface Mines

Abstract

Mine slope failures are a grave issue, leading to loss of life and substantial harm to infrastructure and equipment. Although they are intricate, most of these slope characteristics can be anticipated. Global mining companies have devoted significant efforts to mitigating mine slope failures due to the risk of human and material losses. Consequently, multiple inquiries and research have been conducted to gain a deeper understanding of these occurrences and their growth. This study presents the development of an automated technique for monitoring displacement data and detecting the initiation of slope failure, which coincides with the onset of acceleration. A specific dataset is processed using a five-step methodology. If the analysis yields a positive outcome for a certain set of slope monitoring data, it indicates that the slope is experiencing acceleration. It assists us in identifying the commencement of the acceleration of the slope. The produced result can serve as an advanced alert system that predicts slope collapses in order to prevent potentially disastrous slope incidents, enhancing overall mining efficiency and safety protocols.