Numerical simulation of cable shovel resistive forces in oil sands excavation

Abstract

The cable shovel is an important primary excavator in surface mining operations. The production function of this shovel becomes more critical in the Athabasca oil sands formation with little or no pre-production blasting. The random occurrence of shales, dolomites and limestones in this formation causes a high digging resistance, mechanical wear, tear and failure, resulting in high maintenance costs. Research is currently underway to develop an intelligent navigation technology to provide smart shovel excavation in this formation. This paper contributes to this research by developing a numerical simulation model for determining the resistive force on a shovel dipper during excavation. The spatial dynamics of the dipper geometry and the loaded material weight are modelled using ordinary differential equations and solved using the Runge – Kutta algorithm. Numerical simulation results show that the depth of cut increases with an increase in crowd arm extension speed and a decrease in hoist rope retraction speed. The results also show that the dipper digging and loading rate is proportional to the speed of crowd arm extension and hoist rope retraction. For a constant hoist rope retraction speed, the optimum dipper trajectory is defined for crowd arm extension speeds and vice versa. Also, the digging time for crowd arm extension and hoist rope retraction speeds sampled from a uniform distribution between 0.15 and 0.35 m/s follows a triangular distribution with minimum 6.12 s, mode 7.26 s and maximum 13.7 s. Using these results, production engineers can parameterize shovel excavation schemes for optimum production performance.

Keywords:

• Cable shovel excavation
• Geometric modelling
• Numerical simulation
• Digging time characterization

Notes

* Aside from the work of Hendricks et al. (1989), there is no report of raw data on observed signals. All previous workers have been content with reporting the statistics from such studies. This may be because the study of the stochastic nature of these variables has never been the issue.