Drilling signals analysis for tricone bit condition monitoring

This paper presents a novel approach to investigate the relations between drilling signals and bit wear condition in real world full-scale mining operations. This research addresses the increasing demand for automation in mining to increase the efficiency, safety, and ability to work in harsh environments. A crucial issue in fully autonomous unmanned drilling is to have a system to detect the bit wear condition through the drilling signals analysis in real time. In this work, based on extensive field studies, a novel qualitative method for tricone bit wear state classification is developed and introduced. The relations between drilling vibration as well as electric motor current signals and bit wear are investigated and bit failure vibration frequencies, regardless of the geological conditions, are introduced. Bit failure frequencies are experimentally investigated and analytically calculated. Finally, the effect of bit design parameters on the failure frequencies is presented for the application of bit wear condition monitoring and bit failure prediction.