Optimization of kinematic parameters of continuous miner based on LS-DYNA simulation analysis and NSGA-II algorithm

• Proposed an optimization framework integrating LS-DYNA simulation and NSGA-II algorithm for kinematic parameter tuning of continuous miners. • Established mathematical models linking kinematic parameters to cutting performance, enabling data-driven optimization for continuous miner design. • Optimized cutting arm swing speed (5.685 m/min) and drum speed (49.706 r/min) to enhance cutting force (136.89 kN) and power (336.41 kW) while reducing energy consumption (0.534 kW·h/m³). • Validated simulation results experimentally with errors below 6.54%, demonstrating high accuracy and practical applicability.Improved cutting efficiency and stability under complex coal seam conditions, offering significant engineering value for mining operations. The drum is a critical component of continuous miners, which has a significant impact on the mining efficiency and stability of the equipment. Improper synchronization of drum speed and cutting arm swing speed leads to excessive wear and reduced performance. This study proposes a novel optimization framework combining LS-DYNA simulations and the NSGA-II algorithm to address this issue. A finite element model of the cutting process was established using LS-DYNA, and simulation data were used to construct a response surface model (RSM) relating drum speed and swing speed to cutting force, power, and specific energy consumption. Using the EML340 continuous miner as a case study, a dynamic model of drum-coal interaction was established through Hypermesh and LS-DYNA, analyzing stress distribution, load characteristics, and energy consumption. A multi-objective optimization model was formulated to maximize cutting force and power while minimizing specific cutting energy, constrained by rated power and operational limits. The NSGA-II-derived Pareto solution was analyzed with the VIKOR method identifying the optimal parameter combination, and the optimal parameters: when cutting arm swing speed of 5.685m/min and drum speed of 49.706 r/min, the cutting force of 145.442 kN, power of 336.41 kW, and specific cutting energy of 0.914 kW·h/m 3 . Experimental validation on the EML340 test bench demonstrated optimization results and experimental data errors below 6.54%, confirming the method's reliability. This approach eliminates the reliance on costly physical trials and provides a data-driven strategy for optimizing continuous miner kinematics, with wide application prospects in mining equipment design and operational planning.