Reliability Assessment of Mining System Based on Time Mining Data

Abstract

The degradation of mechanical systems is a typical phenomenon accompanying most systems. When considering dependability, safety and cost-effectiveness, the degradation may result in serious consequences. Direct advancing degradation in all technical systems is not easy to observe. In order to do so, related information is used, e.g. the study of diagnostic and operation measures-signals. This article presents a study of the deterioration of a mining head with multi-tool knives. There is a dataset containing the records of the drilling head behaviour in standard operation. The records contain typical operation characteristics such as moment and power for both sharp and blunt knives. Degradation modelling of the studied mining head knives is performed with stochastic continuous diffusion processes. They are Pearson type, Gauss-Markov type and Levy type processes. The achieved results are expected to be used for the observation of i) the first passage time of degradation critical value), ii) the prediction of residual useful life, and iii) the rationalization of in field operation and maintenance.