基于特征波导纳法和敏感性分析的大型周期支撑结构损伤识别

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摘要提出了一种基于特征波导纳法和敏感性分析的大型周期支撑结构损伤识别方法。通过分析存在单一损伤单元有限周期支撑结构的自由波传播规律，建立了周期结构无量纲自振频率变化对基本周期单元刚度变化的敏感性分析矩阵。通过求解敏感性识别方程组，实现基于测量自振频率变化的大型周期支撑结构损伤检测。同时，分析表明所提出无量纲自振频率的敏感性与结构参数无关，即无需知道原始结构的准确几何物理参数就能确定敏感性系数。分别以一周期支撑梁与周期支撑法兰接头管道为例进行研究，表明本文方法仅用量测损伤前后的前几阶自振频率变化就能较准确地进行周期支撑结构多损伤识别。

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	尹涛尹孟林

关键词 ：特征波导纳, 敏感性分析, 周期结构, 损伤识别, 法兰连接管道

Abstract：This paper develops a novel damage detection methodology for large periodically-supported structures based on the characteristic receptance method and sensitivity analysis technique. By analyzing the free vibration of a finite periodically-supported structure with a single disorder based on the wave propagation method, the sensitivity matrix of the non-dimensional natural frequencies with respect to the change in element stiffness is obtained. And then, the damage scenarios in large periodically-supported structures are identified with the damage induced changes of natural frequencies by solving a set of underdetermined equations based on the sensitivity matrix,. Furthermore, it is found that the sensitivities of the non-dimensional natural frequencies are independent of the structural physical parameters and thus any prior information of the original structures is never required. The proposed method is demonstrated by the numerical case studies conducted for both a periodically-supported beam and a periodically-supported flanged pipeline with various damage scenarios by utilizing only the frequency measurements for the first few modes before and after damage.

Key words： Characteristic receptance sensitivity analysis periodic structures damage detection flanged pipeline.

收稿日期: 2016-05-10 出版日期: 2017-11-15

引用本文:

尹涛尹孟林. 基于特征波导纳法和敏感性分析的大型周期支撑结构损伤识别[J]. 振动与冲击, 2017, 36(22): 93-99.
YIN Tao YIN Meng-Lin. Damage detection in large periodically-supported structures based on the characteristic receptance method and sensitivity-based approach. JOURNAL OF VIBRATION AND SHOCK, 2017, 36(22): 93-99.

链接本文:

http://jvs.sjtu.edu.cn/CN/ 或 http://jvs.sjtu.edu.cn/CN/Y2017/V36/I22/93

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