无机材料学报

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神经网络模型在Si/C/N吸收剂介电性能控制中的应用

焦桓; 周万城; 罗发   

  1. 西北工业大学凝固技术国家重点实验室; 西安 710072
  • 收稿日期:2001-07-30 修回日期:2001-08-31 出版日期:2002-07-20 网络出版日期:2002-07-20

A Neural Network Model for Dielectric Loss of Si/C/N Nano Powder

JIAO Huan; ZHOU Wan-Cheng; LUO Fa   

  1. State Key Laboratory of Solidification Processing; Northwestern Polytechnical University; Xi an 710072; China)
  • Received:2001-07-30 Revised:2001-08-31 Published:2002-07-20 Online:2002-07-20

摘要: 研制高温吸波材料是我国隐身技术的一个新领域,本文应用神经网络技术建立了Si/C/N纳米粉体氮含量-介电损耗角正切变化规律的模型,以期能解决粉体成分对粉体介电损耗角正切的影响问题.研究结果表明,所建立的神经网络模型,可以比较准确和全面地反映粉体成分对介电损耗角正切的影响程度及其规律,模型对粉体氮含量与介电损耗角正切之间关系的预测与实验结果相吻合,证实了将人工神经网络模型应用于高温吸收剂的介电损耗角正切控制和吸收剂的优化是有效和可行的.

关键词: Si/C/N纳米吸收剂, 介电性能, 神经网络, 模型

Abstract: High temperature absorber is a great obstacle for development of stealth material. Si/C/N nano powder is
a potential candidate of high temperature absorber. In order to optimizer and control the dielectric loss of Si/C/N nano powder, neural network (NN)
model was developed. The output of NN model was found to be best fit with the sample data’s. With the help of the NN model, a series of predictions
about the dielectric loss-nitrogen content were made. Finally, the prediction about the influence of nitrogen content of Si/C/N nano powder and frequency
on the dielectric loss predicted by NN model was identical well with the experimental results, which shows that the model established by NN can mirror
the dielectric loss-results relationships and inner regularity in the high temperature absorber.

Key words: Si/C/N nano powder, dielectric loss, neural network, modeling

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