TY - GEN
T1 - A novel bridge structure damage diagnosis algorithm based on statistical pattern recognition
AU - Xiao, Haitao
AU - Lu, Cheng
AU - Ogai, Harutoshi
AU - Roy, Koushik
PY - 2014/10/23
Y1 - 2014/10/23
N2 - This paper presents a structure damage detection algorithm based on statistical pattern recognition to analyze the acquired data to evaluate the health level of bridge. In this algorithm a novel statistical pattern recognition damage detection algorithm including a new damage sensitive index DSPR is proposed to determine the severity and location of damages. This paper also presents simulation and experiment, including a detection experiment of making artificial damage to a real bridge, to show that our design choices are indeed quite effective.
AB - This paper presents a structure damage detection algorithm based on statistical pattern recognition to analyze the acquired data to evaluate the health level of bridge. In this algorithm a novel statistical pattern recognition damage detection algorithm including a new damage sensitive index DSPR is proposed to determine the severity and location of damages. This paper also presents simulation and experiment, including a detection experiment of making artificial damage to a real bridge, to show that our design choices are indeed quite effective.
KW - Statistical pattern recognition
KW - WSN (wireless sensor network)
KW - bridge diagnosis
KW - system design
UR - http://www.scopus.com/inward/record.url?scp=84911873864&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84911873864&partnerID=8YFLogxK
U2 - 10.1109/SICE.2014.6935224
DO - 10.1109/SICE.2014.6935224
M3 - Conference contribution
AN - SCOPUS:84911873864
T3 - Proceedings of the SICE Annual Conference
SP - 775
EP - 780
BT - Proceedings of the SICE Annual Conference
PB - Society of Instrument and Control Engineers (SICE)
T2 - 2014 53rd Annual Conference of the Society of Instrument and Control Engineers of Japan, SICE 2014
Y2 - 9 September 2014 through 12 September 2014
ER -