The electric cable shovel (ECS) is one of the core pieces of equipment used in open-pit mining, and the prediction of its excavating resistance is the basis and focus of optimization design, such as excavation trajectory planning and structure optimization of the ECS. Aiming to predict the excavating resistance of an ECS, a computer simulation method for the excavating resistance based on EDEM-RecurDyn bidirectional coupling simulation is proposed herein. Taking the China-made WK series ECS as the research object, a 1/30 scale model of the ECS was set up, a prototype model test bench of the ECS was built, and the kinematics solution and force analysis of the excavating process were carried out. According to the actual excavation conditions and excavating process of the ECS, a discrete element model of the material stack and a multibody dynamics model of the ECS prototype were established. The EDEM-RecurDyn bidirectional coupling simulation of the excavating process were realized using interface technology, and the excavating resistance levels under different speed combinations and different material repose angles were simulated and analyzed. In order to verify the accuracy of the simulation results, the feasibility and reliability of the EDEM-RecurDyn bidirectional coupling simulation were verified by physical experiments. The results show that the simulated excavating resistance is basically consistent with the excavating resistance measured in the experiment in terms of peak value and change trend, which verifies the feasibility and reliability of the EDEM-RecurDyn bidirectional coupling simulation to study the excavating resistance of an ECS.
The mining rope shovel (MRS) is one of the core pieces of equipment for open-pit mining, and is currently moving towards intelligent and unmanned transformation, replacing traditional manual operations with intelligent mining. Aiming at the demand for online planning of an intelligent shovel excavation trajectory, an MRS excavating trajectory planning method based on material surface perception is proposed here. First, point cloud data of the material stacking surface are obtained through laser radar to perceive the excavation environment and these point cloud data are horizontally calibrated and filtered to reconstruct the surface morphology of the material surface to provide a material surface model for calculation of the mining volume in the subsequent trajectory planning. Second, kinematics and dynamics analysis of the MRS excavation device are carried out using the Product of Exponentials (PoE) and Lagrange equation, providing a theoretical basis for calculating the excavation energy consumption in trajectory planning. Then, the trajectory model of the bucket tooth tip is established by the method of sixth-order polynomial interpolation. The unit mass excavation energy consumption and unit mass excavation time are taken as the objective function, and the motor performance and the geometric size of the MRS are taken as constraints. The grey wolf optimizer is used for iterative optimization to realize efficient and energy-saving excavation trajectory planning of the MRS. Finally, trajectory planning is carried out for material surfaces with four different shapes (typical, convex, concave, and convex–concave). The results of experimental validation show that the actual hoist and crowd forces are essentially consistent with the planned hoist and crowd forces in terms of the peak value and trend variations, verifying the accuracy of the calculation model and confirming that the full bucket rate and various parameters meet the constraints. Therefore, the trajectory planning method based on material surface perception are feasible for application to different excavation conditions.
Mining electric shovels (MES) are one of the key pieces of equipment for mining, and their comprehensive performance plays an important role in mining efficiency. Based on the screw theory, this paper proposes a comprehensive configuration method for an MES working device and selects a new mining electric shovel working device with a larger excavation range, taking the working device as an example for dimensional optimization and simulation analysis. Firstly, based on the closed-loop vector equation, the position inverse solution of the mechanism is analyzed, and the correctness of the position equation is verified by the simulation and by numerical solutions. Then, the constraints of the mechanism are analyzed, and the numerical method and the position equation are combined to solve for the workspace of the mechanism. The dimensional parameters of the mechanism are optimized by genetic algorithms. The workspace of the optimized working device is increased by 13.4789%. Finally, the mining results of the two MES, the working devices, are simulated and verified by experiment. It is shown that the experimental results are basically consistent with the simulation results. The excavation quality difference of the two working devices are 2.02% and 2.20%, which verifies the correctness of the kinematics equation of the working device and the feasibility of the new working device.
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