Structural health monitoring (SHM) has been adopted as a technique to monitor the structure performance to detect damage in aging infrastructure. The ultimate goals of implementing an SHM system are to improve infrastructure maintenance, increase public safety, and minimize the economic impact of an extreme loading event by streamlining repair and retrofit measures. With the recent advances in wireless communication technology, wireless SHM systems have emerged as a promising alternative solution for rapid, accurate and low-cost structural monitoring. This article presents an enabling, developing damage algorithm to advance the detection and diagnosis of damage to structures for SHM using networks of wireless smart sensors. Networks of wireless smart sensors are being used as a vibration based structural monitoring network that allows extraction of mode shapes from output-only vibration data from an underground structure. The mode shape information can further be used in modal methods of damage detection. These sensors are being used to experimentally verify analytical models of post-earthquake evaluation based on system identification analysis. Damage measurement system could play a significant role in monitoring/recording with a higher level of completeness the actual seismic response of structures and in non-destructive seismic damage assessment techniques based on dynamic signature analysis.
[1]
Edward Sazonov,et al.
Optimal spatial sampling interval for damage detection by curvature or strain energy mode shapes
,
2005
.
[2]
Jerome P. Lynch,et al.
Automated Modal Parameter Estimation by Parallel Processing within Wireless Monitoring Systems
,
2008
.
[3]
Daniele Inaudi,et al.
OVERVIEW OF EUROPEAN ACTIVITIES IN THE HEALTH MONITORING OF BRIDGES
,
2002
.
[4]
Edward Sazonov,et al.
Reservation-based protocol for monitoring applications using IEEE 802.15.4 sensor networks
,
2008,
Int. J. Sens. Networks.
[5]
Billie F. Spencer,et al.
Autonomous decentralized structural health monitoring using smart sensors
,
2009
.
[6]
Billie F. Spencer,et al.
Smart sensing technology: opportunities and challenges
,
2004
.