The Damage Physical Features Extraction Algorithms Based on Denoising FBG Signal in Aluminum Alloy Structures

作者：Meng Zhang, Weifang Zhang, Yan Zhao, Wei Dai, Yudong Lan · 发表于：2020 11th International Conference on Prognostics and System Health Management (PHM-2020 Jinan) · 年份：2020 · DOI：10.1109/phm-jinan48558.2020.00011 · 研究领域：Advanced Fiber Optic Sensors、Structural Health Monitoring Techniques、Ultrasonics and Acoustic Wave Propagation

Fiber Bragg gratings (FBG) sensor has attracted considerable attention for structural health monitoring (SHM) in aerospace aluminum alloy structures in recent years. The experimental FBG signals used to detect flaws contains noise. Therefore, in this paper, an algorithm that combines variational mode decomposition (VMD) with discrete wavelet transform (DWT) was proposed to deal with the signal denoising problem. Then, it is a challenge problem for structural damage detection to extract the features that sensitive to damage and robust to noise from the FBG signal response. This paper presents several damage features extraction algorithms, such as the multi-peaks central wavelength algorithm, full width at half Maximum (FWHM) algorithm, the spectral difference algorithm and the spectral area algorithm. Then, the denoised structure signal can be used to test the damage features extraction algorithm effectiveness and for future damage detection.