![](/images/graphics-bg.png)
A Damage Classification Approach for Structural Health Monitoring Using Machine Learning
Joint Authors
Pozo, Francesc
Tibaduiza, Diego
Torres-Arredondo, Miguel Ángel
Vitola, Jaime
Anaya, Maribel
Source
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-14, 14 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-12-02
Country of Publication
Egypt
No. of Pages
14
Main Subjects
Abstract EN
Inspection strategies with guided wave-based approaches give to structural health monitoring (SHM) applications several advantages, among them, the possibility of the use of real data from the structure which enables continuous monitoring and online damage identification.
These kinds of inspection strategies are based on the fact that these waves can propagate over relatively long distances and are able to interact sensitively with and uniquely with different types of defects.
The principal goal for SHM is oriented to the development of efficient methodologies to process these data and provide results associated with the different levels of the damage identification process.
As a contribution, this work presents a damage detection and classification methodology which includes the use of data collected from a structure under different structural states by means of a piezoelectric sensor network taking advantage of the use of guided waves, hierarchical nonlinear principal component analysis (h-NLPCA), and machine learning.
The methodology is evaluated and tested in two structures: (i) a carbon fibre reinforced polymer (CFRP) sandwich structure with some damages on the multilayered composite sandwich structure and (ii) a CFRP composite plate.
Damages in the structures were intentionally produced to simulate different damage mechanisms, that is, delamination and cracking of the skin.
American Psychological Association (APA)
Tibaduiza, Diego& Torres-Arredondo, Miguel Ángel& Vitola, Jaime& Anaya, Maribel& Pozo, Francesc. 2018. A Damage Classification Approach for Structural Health Monitoring Using Machine Learning. Complexity،Vol. 2018, no. 2018, pp.1-14.
https://search.emarefa.net/detail/BIM-1134484
Modern Language Association (MLA)
Tibaduiza, Diego…[et al.]. A Damage Classification Approach for Structural Health Monitoring Using Machine Learning. Complexity No. 2018 (2018), pp.1-14.
https://search.emarefa.net/detail/BIM-1134484
American Medical Association (AMA)
Tibaduiza, Diego& Torres-Arredondo, Miguel Ángel& Vitola, Jaime& Anaya, Maribel& Pozo, Francesc. A Damage Classification Approach for Structural Health Monitoring Using Machine Learning. Complexity. 2018. Vol. 2018, no. 2018, pp.1-14.
https://search.emarefa.net/detail/BIM-1134484
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1134484