钢的连续冷却转变图的神经网络计算模型及预测软件设计

Neural Network Calculation Model and Prediction Software Design for Continuous Cooling Transformation Diagrams of Steels

建立了基于人工神经网络技术预测钢的过冷奥氏体连续冷却转变 (CCT)图的计算模型 ,并在此基础上设计了一种预测CCT图的软件—Eagleye2 0 0 3。在计算模型中综合考虑了CCT图的物理意义和几何特征 ,同时为了方便计算也忽略了一些次要因素。通过该软件可以根据钢的化学成分和热处理工艺预测其连续冷却转变图 ,这对钢的合金设计及组织、性能预测都有很大帮助。

A computer software for predicting the continuous cooling transformation (CCT) diagrams of supercooling austenite steels was developed on the basis of artificial neural network model.In the model,both the physical meaning and geometrical features of the CCT diagrams were considered and some subordinative aspects were simplified to facilitate the computation.The CCT diagrams of steels with different chemical compositions and heat-treatment parameters can be predicted using the software and it is helpful to the alloy design and optimization of new materials.The software has user-friendly graphic interface and has been verified to be accurate.