| Títol: | Damage detection index based on statistical inference and PCA |
| Autor: | Mujica Delgado, Luis Eduardo
Ruiz Ordóñez, Magda
Pozo Montero, Francesc
Rodellar Benedé, José |
| Altres autors/autores: | Universitat Politècnica de Catalunya. Departament de Matemàtica Aplicada III |
| Editorial: | Destech |
| Matèries: | Àrees temàtiques de la UPC::Enginyeria civil::Materials i estructures
Structural health monitoring
Estructures, Teoria de les |
| Tipus de document: | Conference lecture |
| Descripció: | This paper is focused on the development of new estimators propounding if someone statistical law could estimate or infer a system without damage knowing its reliability. This new measurement considers each experiment, and consequently, each
projection to the PCA model as a random variable. An in-depth statistical analysis is
performed for SHM. PCA projections are obtained from the undamaged structure
(baseline projection). If these projections are considered as the set of possible results
(population), then the new projections from the current structure (healthy or not) are
defined as random samples. Therefore, the probability distribution of the baseline
projection can be found. This new distribution can make an inference about the state of the structure and determine if there is damage in it. Consequently, the relative likelihood of each new projection is determined. If the new projection is strongly related with the population, then the structure is healthy. Otherwise, the relation indicates the damage. |
| Altres identificadors i accés: | Mujica, L.E. [et al.]. Damage detection index based on statistical inference and PCA. A: International Workshop on Structural Health Monitoring. "Structural health monitoring 2011: condition-based maintenance and intelligent structures : proceedings of the 8th International workshop on structural health monitoring, Stanford University, Stanford, CA, September 13-15, 2011". Stanford, CA: Destech, 2011.
978-1-60595-053-2
http://hdl.handle.net/2117/15362 |
| Disponible al dipòsit: | E-prints UPC
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