Structural Damage Detection Based on Structural Macro-Strain Mode Shapes Extracted From Non-Stationary Output Responses

拉伤 模式(计算机接口) 结构工程 控制理论(社会学) 计算机科学 材料科学 工程类 人工智能 医学 内科学 控制(管理) 程序设计语言 操作系统
作者
S.H. Chen,Zheng Xiong,Xiongjun Yang,Tao Zheng,Ben Yang,Ying Lei
出处
期刊:Measurement Science and Technology [IOP Publishing]
卷期号:35 (9): 096107-096107
标识
DOI:10.1088/1361-6501/ad4c85
摘要

Abstract Long-gauge fiber Bragg grating strain sensors have been widely employed because of their broader measuring range and higher sensitivity. However, current structural damage detection methods using macro-strain modal parameters are based on structural frequency response function or stationary power spectrum density, which are not applicable to non-stationary responses. To overcome this limitation, an improved method is proposed in this paper for structural damage detection based on structural macro-strain responses under unknown multi-point non-stationary excitations. First, a new concept of macro-strain energy spectrum transmissibility (MEST) is proposed using structural non-stationary macro-strain responses, and it is derived that MEST at a certain system pole equals the ratio of macro-strain mode shape. Then, the singular value decomposition technique is adopted for the MEST matrix to identify structural natural frequencies and macro-strain mode shapes. Finally, two damage detection indicators are constructed based on the identified normalized macro-strain mode shape (NMMS). The first indicator is the difference in structural NMMS before and after structural damage. The second one is based on the curvatures of structural NMMS, which can be used for structures without intact baseline. Numerical verifications are conducted to identify beam-type structural damage under multi-point non-stationary excitations or vehicle loads. Five damage scenarios with different measurement noise levels are investigated, and damage detection results validate the effectiveness of the proposed method.

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