将人工神经网络理论和算法应用于双辉离子渗碳的研究，在对人工神经网络训练的基础上，建立了双辉离子渗碳工艺与渗层性能预报的数学模型。
On the basis of the training of network, the mathematics model on the relationship between double glow plasma carbonizing and prediction of properties is built.
将多重空心阴极溅射靶应用于双辉离子金属渗镀试验。结果表明，这种方法可以加速金属渗镀层的形成。
The result shows that this method has a high surface alloying and deposition rate, and the multiple structure made of alloying and coating layers can be formed, in double glow suface alloying process.
将多重空心阴极溅射靶应用于双辉离子金属渗镀试验。结果表明，这种方法可以加速金属渗镀层的形成。
The result shows that this method has a high surface alloying and deposition rate, and the multiple structure made of alloying and coating layers can be formed, in double glow suface alloying process.
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