A comparative study on machine learning approaches for rock mass classification using drilling data

arXiv:2403.10404v1 Announce Type: new
Abstract: Current rock engineering design in drill and blast tunnelling primarily relies on engineers' observational assessments. Measure While Drilling (MWD) data, a high-resolution sensor dataset collected during tunnel excavation, is underutilised, mainly serving for geological visualisation. This study aims to automate the translation of MWD data into actionable metrics for rock engineering. It seeks to link data to specific engineering actions, thus providing critical decision support for geological challenges ahead of the tunnel face. Leveraging a …

abstract arxiv automate classification cs.cv cs.lg current data dataset design engineering engineering design engineers machine machine learning sensor study type