Refined sticking monitoring of drilling tool for drilling rig in underground coal mine: From mechanism analysis to data mining

Abstract

Sticking status often occurs to drilling tools of drilling rigs in underground coal mine, which causes production efficiency decrease, equipment damage, and even personal injury or death. However, unclear sticking mechanism, nonstationary condition, and complex coupling relationships between variables make it challenging for real-time sticking monitoring. Hence, a refined sticking monitoring method is proposed for drilling tool in underground coal mine, from mechanism analysis, modelling simulation, to data-driven monitoring. The mechanical model of the drilling tool under normal and stuck drilling conditions is firstly established to analyze the multivariate coupling mechanism of drilling tools and select the parameters related to stuck drilling. In order to explore the correlation between the data, a drilling coal breaking process is simulated to explore the actual drilling performance, and the synergistic rule of change between the multiple variables is revealed, which can also be verified via the experimental data. Based on the synergistic change trend among variables, a refined sticking monitoring method called stationarity based hierarchically cointegrating analysis (SHCA) is proposed toward hybrid-frequency and hybrid-stationarity multivariable data to monitor the sticking status. The experimental results show efficacy and superiority of the proposed monitoring method.