Transactions of Materials and Heat Treatment

Title：Housing fillet optimization of universal section mill by BP-NSGA combined with FEM

Authors： Ma Jinhong Chen Wei Zhang Wenzhi Li Juan

Unit： Hebei United University Yanshan University

KeyWords： universal section mill housing fillet improved NSGA BP neural network FEM

ClassificationCode：TG333.13

year,vol(issue):pagenumber：2014,39(6):137-141

Abstract：

The housing fillet of universal section mill directly influents the stress distribution and the longitudinal and lateral deformation of housing, thus affects its intensity, stiffness, service life and H-beam precision and size. According to the stress features and geometric symmetry of the housing fillet of the housing fillet of universal section mill, the FEM model of housing was set up. The influence of housing fillet on the stress distribution and displacement was analysed by FEM software ANSYS. By the improved Non-dominated Sorting Genetic Algorithms (NSGA) with elite strategy combined with FEM, a new kind of optimization method was established. BP neural network was used to establish the fitness function of NSGA. Taking longitudinal displacement and volume of housing as objective function, this new kind of optimization method and the zero-order and first -order optimization method with ANSYS were used to optimize the housing fillet of universal section mill. Compared with the zero-order and first-order optimization method with ANSYS, the optimization result of this new optimization method is better.

Funds：

唐山市科技发展计划资助项目（08360201A-1）

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