Coupling of an IOT wear sensor and numerical modelling in predicting wear evolution of a slurry pump

Abstract

Slurry pump is an integral system between upstream and downstream mineral processing circuit to transport product streams. It is critical to monitor the slurry pump liner wear to ensure safe and efficient circuit operation, as well as achieving targeted product quality. This study aims to develop a digital wear sensor to monitor slurry pump liner wear and to predict its wear evolution by coupling to a numerical modelling framework. The digital sensor is designed to track and report live point-wise thickness on a slurry pump liner while in operation. A liner wear evolution model was then developed by integrating the wear sensor reading and wear intensity results obtained through numerical modelling. The wear intensity was obtained by coupling Smoothed Particle Hydrodynamics and Discrete Element Modelling. Liner wear evolution prediction results were subsequently compared with site measurements after operating for 95 days. Results suggested that the liner wear evolution prediction showed good agreements with measured results in terms of high wear zone as well as quantitative wear rate prediction. Outcome of this study can be utilised in mineral processing industry for safer operation as well as automated plant monitoring.