B-Spline signature responses in structural change detection: method development

被引:0
|
作者
Gedney, Brennan L. [1 ]
Naseri, Reza [1 ]
Al Kharousi, Shadhan [1 ]
Rizos, Dimitrios C. [1 ]
机构
[1] Univ South Carolina, 300 Main Str, Columbia, SC 29208 USA
关键词
Change detection; signature response; data-driven approach; direct time domain; B-Spline basis functions; DAMAGE LOCALIZATION; IDENTIFICATION;
D O I
10.1177/14759217241265444
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Damage detection is perhaps the most critical objective of structural health monitoring. Proper documentation of the progression of structural damage from onset to failure enables performance-based maintenance that mitigates risk and contains socioeconomic impact. Recently, damage detection methods that focus on change detection through analyses of the structural global response in the frequency or time domain have garnered attention due to their efficiency and accuracy. This work proposes a novel time-domain, nonparametric, data-driven change detection method. The time-domain B-Spline transfer function is defined as a signature time history response of the structure, referred to in this work as the B-Spline signature response (BSR). BSR may be computed directly through a physics-based simulation, or it be extracted in a discrete form from measurements of displacement, velocity, or acceleration time histories of structural response to any external excitation. The BSR is independent of loading, is a characteristic of the system, and captures the condition of the structure at the time of acquisition without the need for identifying structural properties. In this work, the fundamentals of the BSR concept are introduced first along with the process of extracting a BSR from structural responses to arbitrary excitations. Verification and validation studies are conducted based on computer simulations and laboratory testing and are discussed in detail. Subsequently, an approach is proposed to detect change through correlation of BSR signals acquired at different times during the monitoring period. Any changes in the intrinsic characteristics affecting the response cause BSR changes and correlation loss. The change detection methodology is demonstrated through computer simulations and experimental investigations. Initial parametric studies are conducted to investigate the suitability of the proposed approach to detect small structural changes. This article demonstrates the validity of the proposed method and establishes the framework for further development and case-specific applications.
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页数:16
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