Experimental Identification of Nonlinear Vibratory Systems by Neural Networks.
Experimental Identification of Nonlinear Vibratory Systems by Neural Networks.
复制标题
通过神经网络进行非线性振动系统的实验识别。
DOI：
10.1299/kikaic.67.3398
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发表时间：
2001
期刊：
影响因子：
--
通讯作者：
S. Miyata
中科院分区：
文献类型：
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作者：
K. Kamiya;K. Yasuda;S. Miyata
近年来，基于神经网络的非线性振动系统辨识技术引起了工程技术人员的兴趣。到目前为止发展起来的识别技术可以从整体上确定客观振动系统的输入输出关系。他们不能单独确定系统的参数。在这篇报告中，我们提出了一种新的实验辨识技术，它可以确定系统的线性参数和非线性项。数值模拟和实验验证了该技术的适用性。
Recently identification techniques using neural networks for nonlinear vibratory systems attract interests of engineers. The identification techniques developed so far can determine the input-output relation of the objective vibratory system as a whole. They cannot determine the parameters of the system separately. In this report, we propose a new experimental identification technique which can determine the linear parameters as well as nonlinear terms of the system. The applicability of the technique is confirmed by numerical simulation and experiment.