Paper
8 March 2014 Identification of fatigue cracks through separating dynamic responses
Guirong Yan, K. Zhao, R. Q. Feng, J. R. Yi
Author Affiliations +
Abstract
During the service life of structures, fatigue cracks may occur in structural components due to dynamic loadings acting on them, such as wind loads, live loads and ground motion. If undetected timely, these fatigue cracks may lead to a catastrophic failure of the overall structure. Although a number of approaches to detecting fatigue cracks have been proposed, some of them appear rather sophisticated or expensive (requiring complicated equipment), and others suffer from a lack of sensitivity. In this study, a simple approach to detecting fatigue cracks is developed based on the bilinear behavior of fatigue cracks. First, a simple system identification method for bilinear systems is proposed by using the dynamic characteristics of bilinear systems. This method transfers nonlinear system identification into linear system identification by dividing impulse or free-vibration responses into different parts corresponding to each stiffness region according to the stiffness interface. In this way, the natural frequency of each region can be identified using any modal identification approach applicable to linear systems. Second, the procedure for identifying the existence of breathing fatigue cracks and quantifying the cracks qualitatively is proposed by looking for the difference in the identified natural frequency between regions. The proposed system identification method and crack detection procedure have been successfully validated by numerical simulations.
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Guirong Yan, K. Zhao, R. Q. Feng, and J. R. Yi "Identification of fatigue cracks through separating dynamic responses", Proc. SPIE 9061, Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2014, 90613D (8 March 2014); https://doi.org/10.1117/12.2048024
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KEYWORDS
System identification

Complex systems

Oscillators

Numerical simulations

Inspection

Electroluminescence

Environmental sensing

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