A machine learning approach for health monitoring of a steel frame structure using statistical features of vibration data
Author:
Publisher
Springer Science and Business Media LLC
Subject
Civil and Structural Engineering
Link
https://link.springer.com/content/pdf/10.1007/s42107-023-00755-6.pdf
Reference38 articles.
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3. An, Y. H., & Ou, J. P. (2014). Structural damage localisation for a frame structure from changes in curvature of approximate entropy feature vectors. Nondestructive Testing and Evaluation, 29(1), 80–97. https://doi.org/10.1080/10589759.2013.858716
4. Bandara, R. P., Chan, T. H. T., & Thambiratnam, D. P. (2014). Frequency response function based damage identification using principal component analysis and pattern recognition technique. Engineering Structures, 66, 116–128. https://doi.org/10.1016/j.engstruct.2014.01.044
5. Figueiredo, E., Park, G., Farrar, C. R., Worden, K., & Figueiras, J. (2011). Machine learning algorithms for damage detection under operational and environmental variability. Structural Health Monitoring, 10(6), 559–572. https://doi.org/10.1177/1475921710388971
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