利用神经网络改进PI系统的性能

M. K. Jameii, M. Nekoui
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引用次数: 4

摘要

脉冲感应系统包括非常便宜和经常使用的金属探测器,除其他应用外,还用于地质和地雷探测机器人。这些系统只检测金属的存在,但不能区分它们。本文介绍了一种方法,该方法使用多层感知网络根据它们的电磁特性来区分金属。这种方法已经在含有铁、铜和铝三种金属的200个不同样品上进行了测试。结果表明,该方法的精度在95%以上。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Improving the Performance of the PI Systems through the Use of Neural Network
Pulse induction systems include the very cheep and often-used metal detectors employed, besides other applications, in geology and mine-detecting robots. these systems only detect the presence of metals but are not capable of distinguishing them from each other in this article a method is introduced in which multiple layer perception networks are used to distinguish metals from each other on the basis of their electromagnetic characteristics . This method has been tested on 200 different samples containing the three metals iron, copper and aluminum. The results obtained show the degree of accuracy of the proposed method is over 95 percent.
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