Principal component analysis for structural damage detection
A detailed description of the procedure and applications can be found in papers:
https://hal.inria.fr/hal-01021053/
https://hal.inria.fr/file/index/docid/1021053/filename/0324.pdf
Rodolfo Villamizar, Oscar Eduardo Perez, Jhonatan Camacho Navarro. Automatic Tuning
of a Pipeline Faults Detection Algorithm. Le Cam, Vincent and Mevel, Laurent and Schoefs,
Franck. EWSHM - 7th European Workshop on Structural Health Monitoring, Jul 2014, Nantes,
France. <hal-01021235>
Method is highly sensible to the feature normalization method.
Cite As
Jhonatan Camacho (2026). Principal component analysis for structural damage detection (https://www.mathworks.com/matlabcentral/fileexchange/48410-principal-component-analysis-for-structural-damage-detection), MATLAB Central File Exchange. Retrieved .
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- AI and Statistics > Statistics and Machine Learning Toolbox > Dimensionality Reduction and Feature Extraction >
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