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首页> 外文期刊>Materials Science and Technology: MST: A publication of the Institute of Metals >Prediction of surface hardness after ferritic nitrocarburising of steels using artificial neural networks
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Prediction of surface hardness after ferritic nitrocarburising of steels using artificial neural networks

机译:使用人工神经网络预测钢的铁素体氮碳共渗后的表面硬度

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摘要

A model for prediction of the surface hardness of structural steels after nitrocarburising has been designed. The model is based on a back propagation feedforward artificial neural network. The performance of the model was checked, using data from the published literature. Good correspondence between predicted from the artificial neural network (ANN) and experimental data was observed. The effects of the chromium, manganese, and nickel contents in the steels on the hardness were studied. Using the model the surface hardnesses after nitrocarburising for some commonly used steels are also predicted. The ANN model has been designed with the aim of optimising the application of nitrocarburising technology.
机译:设计了氮碳共渗后预测结构钢表面硬度的模型。该模型基于反向传播前馈人工神经网络。使用来自公开文献的数据检查了模型的性能。观察到人工神经网络(ANN)的预测与实验数据之间的良好对应关系。研究了钢中铬,锰和镍含量对硬度的影响。使用该模型还可以预测某些常用钢在氮碳共渗后的表面硬度。 ANN模型的设计旨在优化氮碳共渗技术的应用。

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