Friction and Wear Mathematical Modeling and Optimization Design of Surface Microstructure Parameters of Unfolding Wheel based on Experiment and Numerical Simulation

Abstract

Objective: In order to improve the friction-increasing and wear-reducing performance of the unfolding wheel surface, the surface microstructure of the unfolding wheel used in the detection of 8 kinds of steel balls was optimized by parameter matching. Method: Firstly, based on Hertz's theory, the contact area between steel balls of different sizes and the unfolding wheel are analyzed. The wear depth model is established based on Archard adhesive wear model. Secondly, the appropriate microstructure parameters for friction and wear experiments were selected. The finite element analysis software is used to simulate the stress on the surface of the microstructure unfolding wheel and calculate the wear depth. According to the experimental results, the relationship between friction coefficient, wear depth and microstructure parameters is obtained by data fitting, and the objective function of optimization design is established. Finally, based on the genetic algorithm DNSGA-II and Python, the parameters are optimized, and the optimal solution is obtained by using the TOPSIS method. Results: The feasibility of the simulation method is verified by friction and wear experiments, and the correctness of the optimization method is verified. Conclusion: The research shows that the optimal parameters matching of microstructure for steel ball diameters of Ф16.6688mm~Ф22.2250mm: the shape is rhombus; the area of a single pit is close to the contact area, which is 0.0319mm2 ~ 0.0554mm2; the pit depth is 145μm~150μm, and the surface density of microstructure is (5.4~5.6) /mm2.