【摘 要】
：
本文基于正交试验-神经网络的方法,采用双辉离子渗碳技术对奥氏体OCr18ni9不锈钢进行了渗碳性能试验研究。对正交试验结果进行极差分析和方差分析,得到了较优的试验参数配置
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本文基于正交试验-神经网络的方法,采用双辉离子渗碳技术对奥氏体OCr18ni9不锈钢进行了渗碳性能试验研究。对正交试验结果进行极差分析和方差分析,得到了较优的试验参数配置。采用神经网络,建立渗层性能预测模型,证明了神经网络在渗层性能预测方面的可靠性,为以后的科学实践提供了一种合理的方法。
Based on the orthogonal experiment - neural network method, the carburizing performance of austenitic OCr18ni9 stainless steel was studied by double hull ion carburization. The range of orthogonal test results and analysis of variance, obtained better experimental parameter configuration. The neural network is used to establish the prediction model of seepage performance, which proves the reliability of neural network in the prediction of seepage performance, which provides a reasonable method for future scientific practice.
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