Parametric modeling of mechanical reducer gear based on particle swarm optimization

摘要

The mechanical reducer gear has the advantages of good meshing performance, strong bearing capacity and smooth transmission, which has been widely used in the mechanical transmission system. But the traditional design cycle of mechanical reducer gear parameters is long, especially the gear calibration analysis, the calculation process is cumbersome and labor intensity is high, which leads to the incomplete interface of mechanical reducer gear model. In order to improve the analysis accuracy, a lot of correction work is needed. Therefore, based on particle swarm optimization algorithm for mechanical reducer gear parametric modeling research. Based on SolidWorks 3D software, the parametric development of spur gear, modified helical gear, bevel gear, internal gear, tooth root transition curve and helix is carried out. The finite element contact theory is introduced to calculate the contact problem of two cylinders, and compared with the classical Hertz theory, the correctness of the theory is verified. On this basis, the influence of friction on the contact stress and meshing strength of gears is obtained by setting different sliding friction coefficients, and compared with the theoretical calculation results, the correctness of the finite element analysis is verified.