Open Access

ARTICLE

A Modified Principal Component Analysis Method for Honeycomb Sandwich Panel Debonding Recognition Based on Distributed Optical Fiber Sensing Signals

Shuai Chen¹, Yinwei Ma², Zhongshu Wang², Zongmei Xu³, Song Zhang¹, Jianle Li¹, Hao Xu¹, Zhanjun Wu^1,*

1 State Key Laboratory of Structural Analysis for Industrial Equipment, Dalian University of Technology, Dalian, 116024, China
2 Beijing Aerospace Technology Institution, Beijing, 116024, China
3 College of Water-Conservancy and Civil Engineering, Shandong Agricultural University, Taian, 271000, China

* Corresponding Author: Zhanjun Wu. Email:

Structural Durability & Health Monitoring 2024, 18(2), 125-141. https://doi.org/10.32604/sdhm.2024.042594

Received 05 June 2023; Accepted 28 November 2023; Issue published 22 March 2024

Abstract

The safety and integrity requirements of aerospace composite structures necessitate real-time health monitoring throughout their service life. To this end, distributed optical fiber sensors utilizing back Rayleigh scattering have been extensively deployed in structural health monitoring due to their advantages, such as lightweight and ease of embedding. However, identifying the precise location of damage from the optical fiber signals remains a critical challenge. In this paper, a novel approach which namely Modified Sliding Window Principal Component Analysis (MSWPCA) was proposed to facilitate automatic damage identification and localization via distributed optical fiber sensors. The proposed method is able to extract signal characteristics interfered by measurement noise to improve the accuracy of damage detection. Specifically, we applied the MSWPCA method to monitor and analyze the debonding propagation process in honeycomb sandwich panel structures. Our findings demonstrate that the training model exhibits high precision in detecting the location and size of honeycomb debonding, thereby facilitating reliable and efficient online assessment of the structural health state.

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