微波吸收聚合物基复合材料及人工神经网络的研究
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摘要
本文开展了乙炔碳黑(CB)和掺杂聚苯胺(PAn)等吸波剂填充丁腈橡胶(NBR)或聚氯乙烯(PVC)吸波性能的研究。把吸波剂填充到基体材料中,制成板材。通过测试材料的吸波性能、电磁参数及材料的电导率,就吸波剂的种类和含量等方面对材料吸波性能的影响进行了研究;同时,做成了两层和多层结构吸波材料,与单层结构吸波材料的吸波性能进行了对比;制成了不同厚度、不同基体的吸波材料,对它们的吸波性能也进行了对比研究。另外,还应用MATLAB软件,通过建立三层BP网络,对材料的吸收性能进行了模拟、预测。重要的实验内容和结果包括:
     1.研究了吸波材料中CB和PAn含量不同时,其对材料吸收性能的影响。结果表明:材料的电导率对其吸收性能有影响,随材料电导率的增大,材料的吸收峰向低频移动;
     2.比较了不同结构吸波材料的吸收性能。结果证明:两层或多层结构的吸波材料,如果采用合理的结构,其吸收性能明显好于单层的;
     3.一种固定组成的吸波材料,其吸波性能的好坏与样品的厚度有关。材料组成为NBR/CB/PAn(100/25/25),厚度分别为4、2、1mm的三种样品中,2mm样品的吸收性能最好,在9.47GHz处,其最大吸收衰减为22.99dB;
     4.用材料的复电磁参数(ε"、ε'、μ'、μ')作为输入向量,材料的吸收衰减值作输出向量,建立三层BP网络进行模拟、预测。预测结果较好,结果误差不超过10%。
The microwave absorption properties of composites formulated by mixing butadiene-acrylonitrile rubber (NBR) or polyvinyl chloride (PVC) with the carbon Black(CB) and Polyaniline (PAn) were investigated in this paper. The reflection loss, the complex permittivity and permeability and the electric conductivity of the materials were measured. The absorption properties depended on the category and content levels of absorbers. The absorption properties of samples with single layer structure were compared with these of the two-layer or more layer structure samples. In addition, the effect of the thickness and matrix polymer of the composites on the absorption property was discussed. Moreover, with application the MATLAB software to establish three-layer BP network, the absorption properties were imitated and predicted. Experiment and results mainly included:
    1. The microwave absorption properties of different composites with different CB and PAn levels were determined. The results showed that the electric conductivity of the composites had an influence on the absorption properties. With increasing of the electric conductivity of materials, the absorption peak moved to lower frequency.
    2. The samples with two and four layers structure were produced. They showed that thu absorption properties of multi-layer structure samples were better than these of the single layer samples if the structure was designed principally.
    3. The absorption property of a given composites was related to the samples thickness. In the case of the composites with composition of
    
    
    
    NBR/CB/PAn (100/25/25) , the best absorption property was obtained from the 2mm thick sample among the 4mm, 2mm and 1mm thick samples, exhibiting the biggest reflection losses 22. 99dB
    4. By inputting the complex permittivity and permeability ( ) as the vector and the reflection loss as the output vector, the three-layer BP network was established . It can be used to imitate and predict the reflection loss. The prediction result was good, and the error did not exceed 10%.
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