Digging force and power consumption during robotic excavation of cable shovel: experimental study and DEM simulation

ABSTRACT

Cable shovels are on the top priority of the most widely used machinery in open-pit mining industry, the automation of which offers great potential to improve both production efficiency and equipment reliability. Rational evaluations of digging force and power consumption serve as one of the fundamental techniques of realising autonomous operation of cable shovels. In this study, because of the wide range of digging parameters in theoretical calculation, the method of simulation is used to narrow the range of digging parameters in theoretical calculation, so that the digging force can be accurately and efficiently predicted by the method of theoretical calculation. Furthermore, scale-model-based experiments were taken in order to validate the effectiveness of the simulation results. Conclusively, although the theoretical calculation can numerically predict the power consumption in an acceptable extent ($R^2>0.85$), the fitted value of unit resistance to excavation for the theoretical calculation was out of its empirical value range according to the classical theory applied to the prediction of digging resistance in the design of cable shovel. On the other hand, the simulation results were shown to be highly consistent with the experimental results ($R^2>0.9$), which demonstrate the efficiency of the simulation method in evaluating dynamic working performance of cable shovels.

KEYWORDS:

• Digging force
• power consumption
• cable shovel
• scale model
• DEM simulation

Acknowledgments

Acknowledgements, the support of He Tian, Ruipeng Yang and Da Cui, who helped in the implement of field tests, is highly appreciated. This study was conducted under a collaboration between Taiyuan Heavy Industry Co., Ltd and Jilin University.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work was supported by the National Natural Science Foundation of China [Grant No. 51775225 and 51875232].