Journal
MEASUREMENT
Volume 178, Issue -, Pages -Publisher
ELSEVIER SCI LTD
DOI: 10.1016/j.measurement.2021.109393
Keywords
Multi-damage localization; Full-field vibration measurements; Robust principal component analysis; Adaptive denoising; Data fusion
Funding
- Fundamental Research Funds for the Central Universities [3102019HTQD011]
- Natural Science Basic Research Plan in Shaanxi Province of China [2020JQ-109]
- National Natural Science Foundation of China [51905388]
Ask authors/readers for more resources
A novel robust multidamage localization method is proposed based on adaptive denoising and data fusion, which significantly enhances the accuracy of multi-damage localization by optimizing the process of damage feature extraction and data fusion.
Structural damage localization by using full-field vibration measurements is inevitably contaminated by measurement noise and not robust for multi-damage cases. To overcome these problems, a novel robust multidamage localization method is proposed based on adaptive denoising and data fusion. The major contributions are in three aspects. Firstly, an evaluator of multi-damage localization performance is proposed, which converts the damage localization into an optimization problem. Secondly, a hierarchical clustering is adopted to evaluate the damage zones by examining spatial characteristics of the damage. Thirdly, a data fusion strategy is developed based on the assessment of damage localization performance, which guarantees providing robust multi-damage localization results. In addition, numerical and experimental studies of multi-damaged plates are conducted to validate the feasibility and effectiveness of the proposed method. It is found that the accuracy of the multi-damage localization is significantly enhanced by optimizing the process of damage feature extraction and data fusion.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available