TY - GEN
T1 - Towards an automated damage detection system for miter gates on navigation locks
T2 - 11th International Workshop on Structural Health Monitoring 2017: Real-Time Material State Awareness and Data-Driven Safety Assurance, IWSHM 2017
AU - Eick, Brian A.
AU - Spencer, Billie F.
AU - Smith, Matthew D.
AU - Alexander, Quincy G.
AU - Foltz, Stuart D.
PY - 2017
Y1 - 2017
N2 - Navigation locks are critical infrastructure components, and their closure for maintenance and repair can have significant impacts on the global economy. The current state of inspection and monitoring of lock components is generally to close the lock and perform a visual inspection. While structural health monitoring (SHM) of navigation locks is gaining acceptance, automation of the SHM process is lacking. This paper reports on efforts to develop an automated damage detection system for miter gates of navigation locks. The study focuses on using strain gage measurements to identify the redistribution of load throughout lock gates in the presence of damage. To eliminate the environmental variability in the data, a new damage sensitive feature is introduced, termed here as "slope" and defined as the derivative of the strain with respect to the water levels in the lock chamber. The slopes form a new, stationary time series effectively purged of environmental effects. Principal Component Analysis (PCA), a method of analyzing multivariate, stationary time series, is then used to detect significant changes in the statistics of slopes as an indication of damage. To validate the approach, damage is simulated in a finite element model, and the resulting changes in strain from the finite element model are superimposed on the measured data. The results demonstrate the potential of the proposed approach for detecting damage in navigational lock gates.
AB - Navigation locks are critical infrastructure components, and their closure for maintenance and repair can have significant impacts on the global economy. The current state of inspection and monitoring of lock components is generally to close the lock and perform a visual inspection. While structural health monitoring (SHM) of navigation locks is gaining acceptance, automation of the SHM process is lacking. This paper reports on efforts to develop an automated damage detection system for miter gates of navigation locks. The study focuses on using strain gage measurements to identify the redistribution of load throughout lock gates in the presence of damage. To eliminate the environmental variability in the data, a new damage sensitive feature is introduced, termed here as "slope" and defined as the derivative of the strain with respect to the water levels in the lock chamber. The slopes form a new, stationary time series effectively purged of environmental effects. Principal Component Analysis (PCA), a method of analyzing multivariate, stationary time series, is then used to detect significant changes in the statistics of slopes as an indication of damage. To validate the approach, damage is simulated in a finite element model, and the resulting changes in strain from the finite element model are superimposed on the measured data. The results demonstrate the potential of the proposed approach for detecting damage in navigational lock gates.
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U2 - 10.12783/shm2017/13881
DO - 10.12783/shm2017/13881
M3 - Conference contribution
AN - SCOPUS:85032449509
T3 - Structural Health Monitoring 2017: Real-Time Material State Awareness and Data-Driven Safety Assurance - Proceedings of the 11th International Workshop on Structural Health Monitoring, IWSHM 2017
SP - 307
EP - 314
BT - Structural Health Monitoring 2017
A2 - Chang, Fu-Kuo
A2 - Kopsaftopoulos, Fotis
PB - DEStech Publications
Y2 - 12 September 2017 through 14 September 2017
ER -