张哲健
,
武志红
,
李琨
硅酸盐通报
基于神经网络的BP算法,建立了预测红柱石基耐火材料抗铜液侵蚀性能的模型.根据试验所得的试样侵蚀面积大小,训练人工神经网络模型,拟合出输入参数(红柱石百分含量、矾土百分含量、体积密度和烧结后的耐压强度)与输出参数(试样烧结后的侵蚀面积)之间的非线性关系,设计完成了红柱石基耐火材料抗铜液侵蚀性能的BP网络模型,并以此模型分析计算在新的红柱石百分比和矾土百分比等性能参数情况下的试样烧结侵蚀面积.与实验结果对比,两者符合较好,为耐火材料的性能预测提供了一条有效途径.
关键词:
神经网络
,
红柱石
,
侵蚀
,
BP算法
D. K. Zhang and J. T. Niu (National Key Laboratory of AdVanced Welding Production Technology of HIT
,
Harbin 150001
,
China)
金属学报(英文版)
By using alternating current plasma arc welding,the influences were studied of such parameters as welding curent,arc voltage,welding speed,wire feed rate,and magnitude of ion gas flow on front melting width,wdle reinforcement,and back melting width of LF6 aluminum alloy.Model of the formation of welding seam in alternating current plasma arc welding of aluminum was set up with the method of artificial neural neural network - BP algorithm. Qyakuty of formation was consequently predicted and evaluated.The experimental result shows that,compared with other modeling methods,artificial network model can be used to more accurately predict formation of weld,and to guide the production practice.
关键词:
alternating current plasma arc
,
null
,
null
,
null
Ning FAN
,
Xiangbo ZE
,
Zihui GAO
材料科学技术（英）
The artificial neural networks (ANN) which have broad application were proposed to develop multiphase ceramic cutting tool materials. Based on the back propagation algorithm of the forward multilayer perceptron, the models to predict volume content of composition in particle reinforced ceramics are established. The Al¬2O¬3/TiN ceramic cutting tool material was developed by ANN, whose mechanical properties fully satisfy the cutting requirements.
关键词:
Multiphase ceramics
,
null
,
null
