Structural health monitoring with self-organizing maps and artificial neural networks
Abstract
The use of self-organizing maps and artificial neural networks for structural health monitoring is presented in this paper. The authors recently developed a nonparametric structural damage detection algorithm for extracting damage indices from the ambient vibration response of a structure. The algorithm is based on self-organizing maps with a multilayer feedforward pattern recognition neural network. After the training of the self-organizing maps, the algorithm was tested analytically under various damage scenarios based on stiffness reduction of beam members and boundary condition changes of a grid structure. The results indicated that proposed algorithm can successfully locate and quantify damage on the structure.
Collections
- Civil and Environmental Engineering [892 items ]
- Electrical Engineering [2857 items ]
Related items
Showing items related by title, author, creator and subject.
-
Design and synthesis of novel chalcones as potent selective monoamine oxidase-B inhibitors
Hammuda, Arwa; Shalaby, Raed; Rovida, Stefano; Edmondson, Dale E.; Binda, Claudi; Khalil, Ashraf... more authors ... less authors ( Elsevier Masson SAS , 2016 , Article)A novel series of substituted chalcones were designed and synthesized to be evaluated as selective human MAO-B inhibitors. A combination of either methylsulfonyl or trifluoromethyl substituents on the aromatic ketone moiety ... -
Structural Damage Detection in Civil Engineering with Machine Learning: Current State of the Art
Avci O.; Abdeljaber O.; Kiranyaz, Mustafa Serkan ( Springer , 2022 , Conference)This paper presents a brief overview of vibration-based structural damage detection studies that are based on machine learning (ML) in civil engineering structures. The review includes both parametric and nonparametric ... -
Structural damage detection in real time: Implementation of 1D convolutional neural networks for SHM applications
Avci O.; Abdeljaber O.; Kiranyaz, Mustafa Serkan; Inman D. ( Springer , 2017 , Conference)Most of the classical structural damage detection systems involve two processes, feature extraction and feature classification. Usually, the feature extraction process requires large computational effort which prevent the ...

