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Open AccessArticle

Multi-Dimensional Uniform Initialization Gaussian Mixture Model for Spar Crack Quantification under Uncertainty

Research Center of Structural Health Monitoring and Prognosis, State Key Lab of Mechanics and Control of Mechanical Structures, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China
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Academic Editor: Luca De Marchi
Sensors 2021, 21(4), 1283; https://doi.org/10.3390/s21041283
Received: 4 January 2021 / Revised: 24 January 2021 / Accepted: 5 February 2021 / Published: 11 February 2021
(This article belongs to the Special Issue Data Acquisition and Processing for Fault Diagnosis)
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. View Full-Text
Keywords: structural health monitoring; guided wave; Gaussian mixture model; crack quantification; uncertainty; time-varying conditions structural health monitoring; guided wave; Gaussian mixture model; crack quantification; uncertainty; time-varying conditions
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MDPI and ACS Style

Xu, Q.; Yuan, S.; Huang, T. Multi-Dimensional Uniform Initialization Gaussian Mixture Model for Spar Crack Quantification under Uncertainty. Sensors 2021, 21, 1283. https://doi.org/10.3390/s21041283

AMA Style

Xu Q, Yuan S, Huang T. Multi-Dimensional Uniform Initialization Gaussian Mixture Model for Spar Crack Quantification under Uncertainty. Sensors. 2021; 21(4):1283. https://doi.org/10.3390/s21041283

Chicago/Turabian Style

Xu, Qiuhui; Yuan, Shenfang; Huang, Tianxiang. 2021. "Multi-Dimensional Uniform Initialization Gaussian Mixture Model for Spar Crack Quantification under Uncertainty" Sensors 21, no. 4: 1283. https://doi.org/10.3390/s21041283

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