Probabilistic Neural Network and Fuzzy Cluster Analysis Methods Applied to Impedance-Based SHM for Damage Classification
Joint Authors
Steffen, Valder
Palomino, Lizeth Vargas
Finzi Neto, Roberto Mendes
Source
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-12, 12 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-05-27
Country of Publication
Egypt
No. of Pages
12
Main Subjects
Abstract EN
Impedance-based structural health monitoring technique is performed by measuring the variation of the electromechanical impedance of the structure caused by the presence of damage.
The impedance signals are collected from patches of piezoelectric material bonded on the surface of the structure (or embedded).
Through these piezoceramic sensor-actuators, the electromechanical impedance, which is directly related to the mechanical impedance of the structure, is obtained.
Based on the variation of the impedance signals, the presence of damage can be detected.
A particular damage metric is used to quantify the damage.
Distinguishing damage groups from a universe containing different types of damage is a major challenge in structural health monitoring.
There are several types of failures that can occur in a given structure, such as cracks, fissures, loss of mechanical components (e.g., rivets), corrosion, and wear.
It is important to characterize each type of damage from the impedance signals considered.
In the present paper, probabilistic neural network and fuzzy cluster analysis methods are used for identification, localization, and classification of two types of damage, namely, cracks and rivet losses.
The results show that probabilistic neural network and fuzzy cluster analysis methods are useful for identification, localization, and classification of these types of damage.
American Psychological Association (APA)
Palomino, Lizeth Vargas& Steffen, Valder& Finzi Neto, Roberto Mendes. 2014. Probabilistic Neural Network and Fuzzy Cluster Analysis Methods Applied to Impedance-Based SHM for Damage Classification. Shock and Vibration،Vol. 2014, no. 2014, pp.1-12.
https://search.emarefa.net/detail/BIM-1047908
Modern Language Association (MLA)
Palomino, Lizeth Vargas…[et al.]. Probabilistic Neural Network and Fuzzy Cluster Analysis Methods Applied to Impedance-Based SHM for Damage Classification. Shock and Vibration No. 2014 (2014), pp.1-12.
https://search.emarefa.net/detail/BIM-1047908
American Medical Association (AMA)
Palomino, Lizeth Vargas& Steffen, Valder& Finzi Neto, Roberto Mendes. Probabilistic Neural Network and Fuzzy Cluster Analysis Methods Applied to Impedance-Based SHM for Damage Classification. Shock and Vibration. 2014. Vol. 2014, no. 2014, pp.1-12.
https://search.emarefa.net/detail/BIM-1047908
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1047908