针对产品的性能要求制定合理的热轧工艺,提出将组织性能预测与控制技术应用于热轧工艺的优化设计.基于大量生产数据,建立了包含10个BP神经网络的模型组以描述化学成分、工艺和力学性能的对应关系,屈服强度、抗拉强度和伸长率的预测精度分别达到了±6%、±6%和±4%.结合多目标粒子群优化算法,针对客户对性能的需求,在化学成分和工艺约束已知的条件下,对热轧工艺进行了优化计算.工艺优化计算结果与现场生产数据吻合良好,验证了工艺优化设计的有效性,从而为热轧最优工艺设计提供指导.
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