球墨铸铁球化不良和衰退的仿真研究

The Simulation Analysis of Abnormal Nodularizing and Decaying in Nodular Cast Iron

在球铁件缺陷诊断的神经网络模型基础上 ,借助于MATLAB环境中的NEURALNETWORKTOOLBOX工具箱 ,对球铁件球化不良与球化衰退和一些主要影响因素间关系进行了仿真研究 ,并对得到的仿真趋势图进行了详细的分析。仿真表明 ,严格控制各化学成分及浇注温度可有效地消除球化不良和衰退 ,对提高球铁件质量及控制球铁生产工艺参数具有积极作用。该方法大大方便了球铁缺陷的分析 ,可有效地应用于实际生产中。

Based on the neural network model for diagnosing defects of ductile iron castings, an investigation in influence factors of abnormal nodularizing and decaying defects in nodular iron casting is conducted by MATLAB NEURAL NETWORK TOOLBOX. The simulation results show that the abnormal nodularizing and decaying defects can be eliminated effectively by controlling chemical composition and pouring temperature. The method proves itself an aid to improving the quality of the castings and controlling the process of ductile cast iron production, making it easy to analyze the cause producing defects of ductile iron casting in practical production.