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基于独立成分分析的结构模态参数识别 被引量:4

Structural modal parameters identification based on independent component analysis
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摘要 结构模态参数,包括模态振型、模态频率和模态阻尼,是结构健康监测与结构状态评估的前提。通过采用独立成分分析(Independent Component Analysis,ICA)技术将结构的响应信号分解为若干个相互独立的表征各阶特性的分离信号,进而采用单自由度系统参数识别技术对分离信号进行识别,从而完成对结构的模态振型、模态频率和模态阻尼的识别。最后,采用一三层框架模型作为数值算例对该方法进行验证。结果表明,ICA技术可以有效地识别结构模态参数。 Structural modal parameters, including the structural modal shape, frequency and damping ratio, are the prerequisite of structural health monitoring and structural condition assessment. The method of independent component analysis (ICA) is presented to separate structural output signals into several independent signals representing the characteristic of each degree, and then parameter identification of the single degree of freedom is adapted to identify the structural shape, frequency and damping ratio. At last, a numerical simulation of three- floor framework model has been used to verify the method herein. The results show that the structural modal parameters can be identified effectively by ICA.
出处 《苏州科技学院学报(工程技术版)》 CAS 2014年第3期40-45,共6页 Journal of Suzhou University of Science and Technology (Engineering and Technology)
基金 江苏省自然科学基金项目(BK20141180) 苏州科技学院科研基金项目(XKZ201304) 苏州科技学院研究生科研创新计划项目(SKCX12S_025)
关键词 独立成分分析 FASTICA算法 结构模态参数识别 independent component analysis FastICA algorithm structural modal parameters identification
作者简介 (1989-).男.江苏苏州人.硕士研究生。 (1973-),男,副教授,博士,从事桥梁健康监测与振动控制方面的研究,Email:changjun21@126.
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