Title
Multi-Dimensional Uniform Initialization Gaussian Mixture Model For Spar Crack Quantification Under Uncertainty
Abstract
Guided Wave (GW)-based crack monitoring method as a promising method has been widely studied, as this method is sensitive to small cracks and can cover a wide monitoring range. Online crack quantification is difficult as the initiation and growth of crack are affected by various uncertainties. In addition, crack-sensitive GW features are influenced by time-varying conditions which further increase the difficulty in crack quantification. Considering these uncertainties, the Gaussian mixture model (GMM) is studied to model the probability distribution of GW features. To further improve the accuracy and stability of crack quantification under uncertainties, this paper proposes a multi-dimensional uniform initialization GMM. First, the multi-channel GW features are integrated to increase the accuracy of crack quantification, as GW features from different channels have different sensitivity to cracks. Then, the uniform initialization method is adopted to provide more stable initial parameters in the expectation-maximization algorithm. In addition, the relationship between the probability migration index of GMMs and crack length is calibrated with fatigue tests on prior specimens. Finally, the proposed method is applied for online crack quantification on the notched specimen of an aircraft spar with complex fan-shaped cracks under uncertainty.
Year
DOI
Venue
2021
10.3390/s21041283
SENSORS
Keywords
DocType
Volume
structural health monitoring, guided wave, Gaussian mixture model, crack quantification, uncertainty, time-varying conditions
Journal
21
Issue
ISSN
Citations 
4
1424-8220
0
PageRank 
References 
Authors
0.34
0
3
Name
Order
Citations
PageRank
Qiuhui Xu100.34
Shenfang Yuan27612.49
Tianxiang Huang300.34