TY - GEN
T1 - Decentralized bridge health monitoring using wireless smart sensors
AU - Jang, S.
AU - Sim, S. H.
AU - Jo, H.
AU - Spencer, B. F.
PY - 2010
Y1 - 2010
N2 - Wireless Smart Sensor Networks (WSSN) facilitates a new paradigm to structural health monitoring (SHM) for civil infrastructure. Conventionally, SHM systems employing wired sensors and central data acquisition have been used to characterize the state of a structure; however, wide-spread implementation has been limited due to difficulties in cabling, high equipment cost, and long setup time. WSSNs offer a unique opportunity to overcome such difficulties. Recent advances in sensor technology have realized low-cost, smart sensors with on-board computation and wireless communication capabilities, making deployment of a dense array of sensors on large civil structures both feasible and economical. Wireless smart sensors have shown their tremendous potential for SHM in recent full-scale bridge monitoring examples. However, structural damage identification in WSSNs, a primary objective of SHM, has yet to reach its full potential. This paper presents an implementation of the stochastic dynamic damage locating vector (SDDLV) method on the Imote2 sensor platform and experimental validation in a laboratory environment. The WSSN application is developed based on the Illinois SHM Project (ISHMP) Services Toolsuite (http://shm.cs.uiuc.edu), combining decentralized data aggregation, system identification, receptance-based damage detection, and global damage assessment. The laboratory experiment uses a three-dimensional truss structure with a network of Imote2 sensors for decentralized damage identification. Future efforts to deploy a long-term structural health monitoring system for a fullscale steel truss bridge are also described.
AB - Wireless Smart Sensor Networks (WSSN) facilitates a new paradigm to structural health monitoring (SHM) for civil infrastructure. Conventionally, SHM systems employing wired sensors and central data acquisition have been used to characterize the state of a structure; however, wide-spread implementation has been limited due to difficulties in cabling, high equipment cost, and long setup time. WSSNs offer a unique opportunity to overcome such difficulties. Recent advances in sensor technology have realized low-cost, smart sensors with on-board computation and wireless communication capabilities, making deployment of a dense array of sensors on large civil structures both feasible and economical. Wireless smart sensors have shown their tremendous potential for SHM in recent full-scale bridge monitoring examples. However, structural damage identification in WSSNs, a primary objective of SHM, has yet to reach its full potential. This paper presents an implementation of the stochastic dynamic damage locating vector (SDDLV) method on the Imote2 sensor platform and experimental validation in a laboratory environment. The WSSN application is developed based on the Illinois SHM Project (ISHMP) Services Toolsuite (http://shm.cs.uiuc.edu), combining decentralized data aggregation, system identification, receptance-based damage detection, and global damage assessment. The laboratory experiment uses a three-dimensional truss structure with a network of Imote2 sensors for decentralized damage identification. Future efforts to deploy a long-term structural health monitoring system for a fullscale steel truss bridge are also described.
KW - Damage locating vector
KW - Decentralized data aggregation
KW - Output-only modal identification
KW - Receptance matrix
KW - Structural health monitoring
KW - Wireless smart sensor
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U2 - 10.1117/12.847527
DO - 10.1117/12.847527
M3 - Conference contribution
AN - SCOPUS:77953514789
SN - 9780819480620
T3 - Proceedings of SPIE - The International Society for Optical Engineering
BT - Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2010
T2 - Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2010
Y2 - 8 March 2010 through 11 March 2010
ER -