Aerostat Airbag Damage Detection Based on VMD Decomposition and GenSVM. Issue 1 (1st January 2022)

• Record Type: Journal Article
• Authors: Wang, Mei; Chen, Zhipeng; Wang, Pingan; Zhu, Haiping; Fan, Liangzhi
• Is Part Of: Journal of physics. Volume 2173:Issue 1(2022)
• Publication Date: 2022-01-01
• Subjects: Physics -- Congresses; 530.5
• DOI: 10.1088/1742-6596/2173/1/012056
• Languages: English
• ISSNs: 1742-6588

Abstract

Abstract: The capsule of the buoy is usually woven with composite materials. The existence of material anisotropy makes it difficult to establish the degradation mechanism model of the capsule, which affects the defect detection and health management of the capsule. To this end, this paper proposes a data-driven airbag defect detection method based on stress wave measurement. Firstly, strain signals under acoustic excitation are collected by sticking strain gauges on the surface of the capsule. Then, VMD is used to decompose the signal and extract the energy characteristics of each modal signal component to construct the feature vector. Finally, the feature vector is input into the GenSVM model for defect type recognition. The example analysis shows the effectiveness and applicability of the proposed method.