A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Investigation of damage mechanisms of polymer concrete. Multivariable analysis based on temporal features extracted from acoustic emission signals
The aim of this work is to identify and characterize the local damage in polymer concrete materials with the use of acoustic emission (AE). Polymer concrete materials are complex composites which damage and time-to-failure mechanisms still require a better understanding. The damage investigation in those materials is reached with the analysis of acoustic emission signals collected from static three point bending tests. Unsupervised pattern recognition analyses (fuzzy C-means clustering) associated with a principal component analysis are used for the classification of AE events. As few studies are reported in these materials, several model concrete samples are experimented in order to match each cluster with the corresponding damage mechanism of the material under investigation. This method provides the time dependency of each identified damage mechanism as a function of test time. We show through this approach that it is possible, using AE, to identify the most critical damage mechanisms leading to the final failure of the material. The possibility of assessing time to failure of the tested samples from AE is also investigated.
Investigation of damage mechanisms of polymer concrete. Multivariable analysis based on temporal features extracted from acoustic emission signals
The aim of this work is to identify and characterize the local damage in polymer concrete materials with the use of acoustic emission (AE). Polymer concrete materials are complex composites which damage and time-to-failure mechanisms still require a better understanding. The damage investigation in those materials is reached with the analysis of acoustic emission signals collected from static three point bending tests. Unsupervised pattern recognition analyses (fuzzy C-means clustering) associated with a principal component analysis are used for the classification of AE events. As few studies are reported in these materials, several model concrete samples are experimented in order to match each cluster with the corresponding damage mechanism of the material under investigation. This method provides the time dependency of each identified damage mechanism as a function of test time. We show through this approach that it is possible, using AE, to identify the most critical damage mechanisms leading to the final failure of the material. The possibility of assessing time to failure of the tested samples from AE is also investigated.
Investigation of damage mechanisms of polymer concrete. Multivariable analysis based on temporal features extracted from acoustic emission signals
Untersuchung des Schadensmechanismus von Polymerbeton. Multivariable Analyse auf der Grundlage temporärer Merkmale aus Schallemissionssignalen extrahiert
Marec, Anne (author) / Berbaoui, Rachid (author) / Tomas, Jean-Hugh (author) / El Mahi, Abderrahim (author) / El Guerjouma, Rachid (author)
2009
6 Seiten, 6 Bilder, 1 Tabelle, 6 Quellen
(nicht paginiert)
Conference paper
Storage medium
English
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