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高筋薄腹板类锻件通常具有较大的尺寸和较复杂的内腔,需要在锻造成形过程中进行合理的预成形设计。提出了一种三维预成形设计方法,以一个典型的高筋薄腹板类锻件为例,根据静电场与锻造速度场分布的相似性,用静电场等势面模拟获得其预锻形状;然后利用Deform-3D进行锻造模拟,对预锻形状进行验证和评估;最后通过构建神经网络,建立了毛坯尺寸、等势面电势值和等效应变差值、锻件填充率的映射关系,并结合遗传算法搜索最优解,实现了毛坯和预锻件的联合优化设计。结果表明,本方法可以快速而准确地设计出预成形件,可靠性较高。
High-strength thin-walled web forgings usually have larger dimensions and more complex lumens that require a reasonable preform design during forging. A three-dimensional preform design method was proposed. Taking a typical high-strength thin web forgings as an example, the shape of the pre-forging was simulated by the equipotential surface of the electrostatic field according to the similarity of the electrostatic field and forging speed field distribution. Then, Forging simulation was carried out by Deform-3D to verify and evaluate the shape of pre-forging. Finally, the mapping relationship between blank size, equipotential potential potential value and equivalent strain difference and forging filling rate was established by constructing neural network. The algorithm searches for the optimal solution to realize the joint optimization design of blank and pre-forging. The results show that the method can design the preform quickly and accurately and has high reliability.