4.7 Article

A novel vibration based breathing crack localization technique using a single sensor measurement

期刊

MECHANICAL SYSTEMS AND SIGNAL PROCESSING
卷 122, 期 -, 页码 117-138

出版社

ACADEMIC PRESS LTD- ELSEVIER SCIENCE LTD
DOI: 10.1016/j.ymssp.2018.12.019

关键词

Breathing crack; Superharmonics; Spectral density function; Nonlinearity; Curvature; Singular spectrum analysis; Pairwise eigenvalues; Zero strain energy nodes; Particle swarm optimisation; Nelder Mead algorithm

向作者/读者索取更多资源

Structural damages such as a fatigue-breathing crack can result in nonlinear dynamical signatures that can significantly enhance their detection. Majority of the existing vibration based breathing crack diagnosis techniques demands rather a dense sensor network in order to detect, precisely locate the spatial location and characterize the breathing crack as the change in the dynamic characteristics of a structure with breathing crack is much smaller when compared to open cracks of the same magnitude. Further, the quality of identification improves with the increase in the number of sensors. In this paper, a novel vibration-based damage detection technique based on the zero strain energy nodes concept is proposed for the first time to identify the exact spatial location of the breathing crack using a single sensor measurement. Two different procedures based on sweep sine and harmonic excitation are outlined for breathing crack localization. Multi-level Singular Spectrum Analysis (M-SSA) is used in the present work to conclude about the presence of nonlinear behaviour of the structure and also for the identification of frequencies at which the cracked structure behaves linearly. Numerical and experimental investigations presented in this paper clearly establish that the proposed approach has the ability to identify single and as well as multiple breathing cracks present anywhere in the structure even with noise contaminated measurements. (C) 2018 Elsevier Ltd. All rights reserved.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.7
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据