A comparative evaluation of two statistical analysis methods for damage detection using fibre optic sensor data Online publication date: Wed, 20-May-2015
by Masoud Malekzadeh; F. Necati Catbas
International Journal of Reliability and Safety (IJRS), Vol. 8, No. 2/3/4, 2014
Abstract: One of the commonly used optic sensing technologies is a point sensor with Fibre Bragg Grating (FBG), which is employed with an in-house developed FBG interrogator. It is critical to couple such sensing capabilities with effective data analysis methods that can identify structural changes and detect possible damage. In this study, Robust Regression Analysis (RRA) and Cross Correlation Analysis (CCA) are employed to analyse strain data collected with FBG sensors that are installed on a 4-span bridge type structure. In order to test the efficiency of these non-parametric data analysis approaches, several tests are conducted with different damage scenarios in the laboratory environment. The efficiency of FBG sensors in conjunction with RRA and CCA algorithms for detection and localising damage are explored. Based on the findings, the RRA and CCA methods with FBGs can be expected to deliver promising results as to observing and detecting both local and global damage.
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Reliability and Safety (IJRS):
Login with your Inderscience username and password:
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.
If you still need assistance, please email subs@inderscience.com