Mechanical Characteristics and Parameter Optimization of Intelligent Mining Bionic Cutting Tools

As important working parts of intelligent mining equipment, the conical picks frequently fail due to wear and fatigue fracture of the pick body during use. In the paper, the method that could improve the mechanical properties of the conical pick by cold press forming bionic structure was proposed. Through the combination of numerical simulation and Box-Behnken response surface experiment, the regression equations of the residual compressive stress and the work hardening degree with respect to the cold pressing speed, the friction coefficient, the dimple depth and the dimple radius. Research shows that the significance of the influence on the residual compressive stress is in the order of dimple depth > cold pressing speed > friction coefficient >dimple radius, and the significance of the influence on the work hardening degree is in the order of dimple depth > dimple radius > friction coefficient > cold pressing speed. The optimal parameter combination for the cold pressing forming of the bionic pick was obtained. The research results provide the new method for the preparation of bionic structure and has important theoretical and application values for optimizing the performance and production of pick.