Vibration-Based Detection of Non-Overlapping Delaminations in FRP Beams Using Frequency Shifts

Zhifang Zhang, Shoutao Li, Hemant Kumar Singh, Xudong Lan,Ke Zhang,Hongxu Wang,Ching-Tai Ng,Caizheng Wang

Journal of Sound and Vibration(2024)

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摘要
Extensive research has been carried out on the detection of single delamination in fibre-reinforced polymer (FRP) structures using different structural health monitoring (SHM) approaches, including the vibration-based assessment methods. However, there are limited studies that on the detection of multiple delaminations, which could occur in many real-world scenarios. To address this research gap, this paper aims at developing a vibration-based method to assess the two non-overlapping delaminations in FRP beams based on changes in natural frequencies. A theoretical model of vibrating FRP beams with two non-overlapping delaminations was constructed and used for generating the multiple frequencies of the delaminated beams. By analysing the frequency shifts of the FRP beams before and after the occurrence of damage, the delamination characteristics (location and severity) can be inversely predicted using optimisation algorithms. The accuracy and efficiency of the frequency-based inverse algorithm were verified experimentally by modal testing on FRP beam specimens with one and two non-overlapping delaminations. It is interesting to observe that using the proposed vibration-based method, the single delamination in FRP specimens can also be predicted as two non-overlapping delaminations, with a major one matching the original single delamination and a minor one that can be neglected. Thus, the current vibration-based delamination assessment approach is flexible in identifying the prediction of either single or double non-overlapping delaminations in FRP beams, and therefore, it potentially has wider applicability than the existing single delamination detection methods.
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关键词
Delamination detection,Non-overlapping delaminations,Structural health monitoring,Natural frequency,Machine learning algorithms
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