We found a match
Your institution may have access to this item. Find your institution then sign in to continue.
- Title
Fatigue crack monitoring of aerospace structure based on lamb waves and binary tree support vector machines.
- Authors
Shenbo Lu; Li Zhou
- Abstract
To overcome the difficulty in identifying the fatigue crack in key parts of aerospace structure, a kind of methods aimed to monitor the crack length based on matching pursuit (MP) method and binary tree support vector machines (BT-SVM) classification algorithm was developed. In this method, Lamb wave signals were decomposed into a linear combination of several Chirplet atoms by MP method, and then the matching parameters were extracted as feature vectors for training and testing in BT-SVM classification algorithm. At the same time, a lug joint model was created with a certain ratio and the effect of crack extension on Lamb wave signals propagation was studied. At last, fatigue loading experiments were carried out in lug joints and tail reinforced frames of aircraft. The results showed that this method can monitor the length of fatigue crack effectively, which presents a new approach for monitoring the fatigue crack.
- Subjects
FATIGUE crack growth; LAMB waves; SUPPORT vector machines; CLASSIFICATION algorithms; CHIRPLET transform (Signal processing); AIRPLANE design
- Publication
Journal of Vibroengineering, 2017, Vol 19, Issue 5, p3271
- ISSN
1392-8716
- Publication type
Article
- DOI
10.21595/jve.2017.17528