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用BP人工神经网络及材料微观分析方法研究了热处理工艺对P20钢硬度的影响。结果表明,BP网络能根据淬火及回火温度精确预测P20钢热处理后的硬度;BP网络预测结果表明,P20钢经800～920℃淬火及530～650℃回火,在给定的淬火温度下,随回火温度的增加硬度急剧降低;在给定的回火温度下,随淬火温度的增加硬度略有增加。材料微观分析表明:这主要归因于回火温度升高造成的碳化物长大和α相的回复程度的加剧及淬火温度升高造成的碳及合金元素固溶量的增加。
The effect of heat treatment process on the hardness of P20 steel was studied by BP artificial neural network and material microscopic analysis. The results show that the BP network can accurately predict the hardness of the P20 steel after heat treatment according to the quenching and tempering temperatures. The BP network prediction results show that the P20 steel is tempered at 800-920 ° C and tempered at 530-650 ° C at a given quenching temperature , With the tempering temperature increased sharply decreased hardness; at a given tempering temperature, with the increase of quenching temperature slightly increased hardness. The microscopic analysis of the material shows that this is mainly attributed to the increase of the carbide growth and the α-phase recovery due to the tempering temperature and the increase of the solid solution amount of the carbon and alloy elements caused by the increase of the quenching temperature.