scholarly journals Classification of damage in structural systems using time series analysis and supervised and unsupervised pattern recognition techniques

2010 ◽  
Author(s):  
Piotr Omenzetter ◽  
Oliver R. de Lautour
Keyword(s):  
Time Series ◽  
Pattern Recognition ◽  
Time Series Analysis ◽  
Structural Systems ◽  
Pattern Recognition Techniques ◽  
Series Analysis

Structural Health Monitoring Using Statistical Pattern Recognition Techniques

2001 ◽  
Vol 123 (4) ◽  
pp. 706-711 ◽  
Author(s):  
Hoon Sohn ◽  
Charles R. Farrar ◽  
Norman F. Hunter ◽  
Keith Worden
Keyword(s):  
Time Series ◽  
Pattern Recognition ◽  
Structural Health Monitoring ◽  
Time Series Analysis ◽  
Health Monitoring ◽  
Statistical Pattern Recognition ◽  
Pattern Recognition Techniques ◽  
Series Analysis ◽  
Statistical Pattern ◽  
Auto Regressive

This paper casts structural health monitoring in the context of a statistical pattern recognition paradigm. Two pattern recognition techniques based on time series analysis are applied to fiber optic strain gauge data obtained from two different structural conditions of a surface-effect fast patrol boat. The first technique is based on a two-stage time series analysis combining Auto-Regressive (AR) and Auto-Regressive with eXogenous inputs (ARX) prediction models. The second technique employs an outlier analysis with the Mahalanobis distance measure. The main objective is to extract features and construct a statistical model that distinguishes the signals recorded under the different structural conditions of the boat. These two techniques were successfully applied to the patrol boat data clearly distinguishing data sets obtained from different structural conditions.

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