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Investigation of Time Series Representations and Similarity Measures for Structural Damage Pattern Recognition
Joint Authors
Liu, Wenjia
Chen, Bo
Swartz, R. Andrew
Source
Issue
Vol. 2013, Issue 2013 (31 Dec. 2013), pp.1-13, 13 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2013-09-26
Country of Publication
Egypt
No. of Pages
13
Main Subjects
Medicine
Information Technology and Computer Science
Abstract EN
This paper investigates the time series representation methods and similarity measures for sensor data feature extraction and structural damage pattern recognition.
Both model-based time series representation and dimensionality reduction methods are studied to compare the effectiveness of feature extraction for damage pattern recognition.
The evaluation of feature extraction methods is performed by examining the separation of feature vectors among different damage patterns and the pattern recognition success rate.
In addition, the impact of similarity measures on the pattern recognition success rate and the metrics for damage localization are also investigated.
The test data used in this study are from the System Identification to Monitor Civil Engineering Structures (SIMCES) Z24 Bridge damage detection tests, a rigorous instrumentation campaign that recorded the dynamic performance of a concrete box-girder bridge under progressively increasing damage scenarios.
A number of progressive damage test case datasets and damage test data with different damage modalities are used.
The simulation results show that both time series representation methods and similarity measures have significant impact on the pattern recognition success rate.
American Psychological Association (APA)
Liu, Wenjia& Chen, Bo& Swartz, R. Andrew. 2013. Investigation of Time Series Representations and Similarity Measures for Structural Damage Pattern Recognition. The Scientific World Journal،Vol. 2013, no. 2013, pp.1-13.
https://search.emarefa.net/detail/BIM-1011769
Modern Language Association (MLA)
Liu, Wenjia…[et al.]. Investigation of Time Series Representations and Similarity Measures for Structural Damage Pattern Recognition. The Scientific World Journal No. 2013 (2013), pp.1-13.
https://search.emarefa.net/detail/BIM-1011769
American Medical Association (AMA)
Liu, Wenjia& Chen, Bo& Swartz, R. Andrew. Investigation of Time Series Representations and Similarity Measures for Structural Damage Pattern Recognition. The Scientific World Journal. 2013. Vol. 2013, no. 2013, pp.1-13.
https://search.emarefa.net/detail/BIM-1011769
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1011769