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Mathematical Problems in Engineering
Volume 2016 (2016), Article ID 3734258, 13 pages
Research Article

Novel Damage Detection Techniques for Structural Health Monitoring Using a Hybrid Sensor

School of Reliability and Systems Engineering, Beihang University, 37 Xueyuan Road, Haidian District, Beijing 100191, China

Received 19 February 2016; Revised 30 March 2016; Accepted 4 April 2016

Academic Editor: Wenyu Zhao

Copyright © 2016 Dengjiang Wang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


This study presents a technique for detecting fatigue cracks based on a hybrid sensor monitoring system consisting of a combination of intelligent coating monitoring (ICM) and piezoelectric transducer (PZT) sensors. An experimental procedure using this hybrid sensor system was designed to monitor the cracks generated by fatigue testing in plate structures. A probability of detection (POD) model that quantifies the reliability of damage detection for a specific sensor or the nondestructive testing (NDT) method was used to evaluate the weight factor for the ICM and PZT sensors. To estimate the uncertainty of model parameters in this study, the Bayesian method was employed. Realistic data from fatigue testing was used to validate the overall method, and the results show that the novel damage detection technique using a hybrid sensor can quantify fatigue cracks more accurately than results obtained by conventional sensor methods.