Hyperchaotic probe for damage identification using nonlinear prediction error

李雅普诺夫指数 混乱的 吸引子 激发 控制理论(社会学) 灵敏度(控制系统) 非线性系统 数学 洛伦兹系统 达芬方程 计算机科学 统计物理学 物理 数学分析 工程类 人工智能 电子工程 量子力学 控制(管理)
作者
Shahab Torkamani,Eric A. Butcher,Michael D. Todd,Gyuhae Park
出处
期刊:Mechanical Systems and Signal Processing [Elsevier BV]
卷期号:29: 457-473 被引量:23
标识
DOI:10.1016/j.ymssp.2011.12.019
摘要

The idea of damage assessment based on using a steady-state chaotic excitation and state space embedding, proposed during the recent few years, has led to the development of a computationally feasible health monitoring technique based on comparisons between the geometry of a baseline attractor and a test attractor at some unknown state of health. This study explores an extension to this concept, namely a hyperchaotic excitation. Three different types of Lorenz chaotic/hyperchaotic oscillators are used to provide the excitations and comparisons are made using a prediction error feature called 'nonlinear auto-prediction error', which is based on attractor geometry, to evaluate the efficiency of chaotic excitation versus hyperchaotic ones. An 8-degree-of-freedom system and a cantilever beam are two models that are used for numerical simulation. A comparison between the results from the chaotic excitation with the results from each of the hyperchaotic excitations, obtained for both of the numerical models, highlights the higher sensitivity of a hyperchaotic excitation relative to a chaotic excitation. The experimental results also confirm the numerical results conveying the higher sensitivity of the hyperchaotic excitation compared to the chaotic one. A hyperchaotic excitation having three positive Lyapunov exponents is shown in some cases to be even more sensitive than a two-positive-Lyapunov-exponent hyperchaotic excitation.
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