A Neural-Wavelet Technique for Damage Identification in the ASCE Benchmark Structure Using Phase II Experimental Data
Author
Source
Issue
Vol. 2010, Issue 2010 (31 Dec. 2010), pp.1-13, 13 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2010-08-16
Country of Publication
Egypt
No. of Pages
13
Main Subjects
Abstract EN
Damage pattern recognition research represents one of the most challenging tasks in structural health monitoring (SHM).
The vagueness in defining damage and the significant overlap between damage states contribute to the challenges associated with proper damage classification.
Uncertainties in the damage features and how they propagate during the damage detection process also contribute to uncertainties in SHM.
This paper introduces an integrated method for damage feature extraction and damage recognition.
We describe a robust damage detection method that is based on using artificial neural network (ANN) to compute the wavelet energy of acceleration signals acquired from the structure.
We suggest using the wavelet energy as a damage feature to classify damage states in structures.
A case study is presented that shows the ability of the proposed method to detect and pattern damage using the American Society of Civil Engineers (ASCEs) benchmark structure.
It is suggested that an optimal ANN architecture can detect damage occurrence with good accuracy and can provide damage quantification with reasonable accuracy to varying levels of damage.
American Psychological Association (APA)
Reda Taha, Mahmoud M.. 2010. A Neural-Wavelet Technique for Damage Identification in the ASCE Benchmark Structure Using Phase II Experimental Data. Advances in Civil Engineering،Vol. 2010, no. 2010, pp.1-13.
https://search.emarefa.net/detail/BIM-489628
Modern Language Association (MLA)
Reda Taha, Mahmoud M.. A Neural-Wavelet Technique for Damage Identification in the ASCE Benchmark Structure Using Phase II Experimental Data. Advances in Civil Engineering No. 2010 (2010), pp.1-13.
https://search.emarefa.net/detail/BIM-489628
American Medical Association (AMA)
Reda Taha, Mahmoud M.. A Neural-Wavelet Technique for Damage Identification in the ASCE Benchmark Structure Using Phase II Experimental Data. Advances in Civil Engineering. 2010. Vol. 2010, no. 2010, pp.1-13.
https://search.emarefa.net/detail/BIM-489628
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-489628