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Study on State Recognition of ASCE Benchmark based on Lyapunov Exponent Spectrum Entropy

机译：基于Lyapunov指数谱熵的国家识别敏捷基准的研究

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The paper has made a maximum Lyapunov exponent and Lyapunov exponent spectrum entropy analysis of ASCE Benchmark using non-linear theory and chaos time sequence. The maximum Lyapunov exponents in the two kinds of structural monitored data are both over zero, indicating that in the structural system chaos phenomenon has appeared. And, experiments have shown that the maximum Lyapunov exponent is sensitive of the amount of samples and the time delay. So, to compute the chaos index, the amount of samples and the time duration are of importance. Meanwhile, the Lyapunov exponent spectrum entropy is effective to measure the chaotic characteristic of the system, but ,the entropy is less sensitive to state recognition more than the max Lyapunov exponent.
机译：本文采用了使用非线性理论和混沌时间序列的asce基准的Lyapunov指数和Lyapunov指数谱熵分析。两种结构监测数据中的最大Lyapunov指数均均为零，表明在结构系统中出现了混沌现象。并且，实验表明，最大Lyapunov指数对样品的量和时间延迟敏感。因此，要计算混沌索引，样本量和时间持续时间非常重要。同时，Lyapunov指数谱熵是测量系统的混沌特性的有效性，但是，熵对国家识别的敏感程度不如Max Lyapunov指数更敏感。

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