Issue |
MATEC Web Conf.
Volume 148, 2018
International Conference on Engineering Vibration (ICoEV 2017)
|
|
---|---|---|
Article Number | 14006 | |
Number of page(s) | 6 | |
Section | Vibration-Based Structural Health Monitoring Data Analysis and Time Series Methods | |
DOI | https://doi.org/10.1051/matecconf/201814814006 | |
Published online | 02 February 2018 |
Vibration-based damage detection of structural joints in presence of uncertainty
1
Dept. of Mechanical Engineering, University of Wasit, Iraq
2
Dept. of Mechanical Engineering, University College London, London, UK
3
Mechanical and Aerospace Engineering, University of Strathclyde, Glasgow, UK
* Corresponding author: hrazzaq@uowasit.edu.iq, husseinmec@yahoo.com
Early damage detection of structure’s joints is essential in order to ensure the integrity of structures. Vibration-based methods are the most popular way of diagnosing damage in machinery joints. Any technique that is used for such a purpose requires dealing with the variability inherent to the system due to manufacturing tolerances, environmental conditions or aging. The level of variability in vibrational response can be very high for mass-produced complex structures that possess a large number of components. In this study, a simple and efficient time frequency method is proposed for detection of damage in connecting joints. The method suggests using singular spectrum analysis for building a reference space from the signals measured on a healthy structure and then compares all other signals to that reference space in order to detect the presence of faults. A model of two plates connected by a series of mounts is used to examine the effectiveness of the method where the uncertainty in the mount properties is taken into account to model the variability in the built-up structure. The motivation behind the simplified model is to identify the faulty mounts in trim-structure joints of an automotive vehicle where a large number of simple plastic clips are used to connect the trims to the vehicle structure.
© The Authors, published by EDP Sciences, 2018
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (http://creativecommons.org/licenses/by/4.0/).
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