Research on automatic mesh generation of transformer based on parametric modeling

In recent years, the rapid development of China’s power system has put forward higher requirements for the performance and reliability of key equipment transformers, and the accurate analysis of their electromagnetic fields is crucial. Finite element analysis is the core means, and efficient and accurate mesh generation is one of the necessary steps. Aiming at the current transformer simulation generally relies on foreign commercial software, the meshing process is complicated and has poor compatibility with independent simulation platforms, this study focuses on developing a set of automatic mesh generation system for three-phase three-column transformers. The system adopts the collaborative architecture of C++ and Gmsh, and is based on the idea of parametric modeling, which automatically constructs the geometric model and completes the mesh dissections by inputting the core size, winding distribution and other core parameters. The system innovatively integrates the physical field driving strategy to realize the intelligent adaptive profile optimization in key areas. Through the self-developed post-processing engine, the system is able to process mesh data and output standardized files in a lightweight manner, completely getting rid of the dependence on foreign simulation platform tools, and providing a seamless interface to connect with independent finite element simulation software. The system realizes the automatic coverage of the whole process from parameter input to simulation mesh generation, and the core contains three modules: parametric modeling, intelligent sectioning and autonomous post-processing. Users only need to set a small number of global parameters, and the system can automatically generate optimized differentiated meshes based on built-in knowledge, which significantly simplifies the pre-processing process. The system marks a key step towards efficient, accurate and autonomous transformer mesh dissection, significantly reduces the intensity of manual operation, and provides an important technical support for automated mesh generation for the construction of localized transformer electromagnetic simulation ecology. Future work will focus on function expansion and application deepening.