scholarly journals Nonlinear feature identification of impedance-based structural health monitoring

2004 ◽  
Author(s):  
Amanda C. Rutherford ◽  
Gyuhae Park ◽  
Hoon Sohn ◽  
Charles R. Farrar
Keyword(s):  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Feature Identification ◽  
Structural Health ◽  
Nonlinear Feature

scholarly journals Underexposed Vision-Based Sensors’ Image Enhancement for Feature Identification in Close-Range Photogrammetry and Structural Health Monitoring

2021 ◽  
Vol 11 (23) ◽  
pp. 11086
Author(s):  
Luna Ngeljaratan ◽  
Mohamed A. Moustafa
Keyword(s):  
Structural Health Monitoring ◽  
Image Enhancement ◽  
Health Monitoring ◽  
Bundle Adjustment ◽  
Practical Implementation ◽  
Identification Algorithm ◽  
Feature Identification ◽  
Structural Health ◽  
Close Range Photogrammetry ◽  
Close Range

This paper describes an alternative structural health monitoring (SHM) framework for low-light settings or dark environments using underexposed images from vision-based sensors based on the practical implementation of image enhancement algorithms. The proposed framework was validated by two experimental works monitored by two vision systems under ambient lights without assistance from additional lightings. The first experiment monitored six artificial templates attached to a sliding bar that was displaced by a standard one-inch steel block. The effect of image enhancement in the feature identification and bundle adjustment integrated into the close-range photogrammetry were evaluated. The second validation was from a seismic shake table test of a full-scale three-story building tested at E-Defense in Japan. Overall, this study demonstrated the efficiency and robustness of the proposed image enhancement framework in (i) modifying the original image characteristics so the feature identification algorithm is capable of accurately detecting, locating and registering the existing features on the object; (ii) integrating the identified features into the automatic bundle adjustment in the close-range photogrammetry process; and (iii) assessing the measurement of identified features in static and dynamic SHM, and in structural system identification, with high accuracy.

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