DocumentCode :
2887397
Title :
Structural health monitoring at Los Alamos National Laboratory
Author :
Farrar, Charles R. ; Doebling, Scott W.
Author_Institution :
Los Alamos Nat. Lab., NM, USA
fYear :
1999
fDate :
1999
Firstpage :
42401
Lastpage :
42404
Abstract :
Los Alamos National Laboratory (LANL) has several ongoing programs to identify damage in structures and mechanical systems from changes in their dynamic characteristics. This paper provides a summary of LANL´s involvement with this technology, past experiences in this field including damage detection studies on large civil engineering infrastructure and the directions that research in this area will be taking in the future. The research began by taking a strictly model-based approach to the vibration-based damage detection problem. Recent work has recognized that it is more appropriate to view the damage detection problem as an exercise in statistical pattern recognition. Therefore, a general statistical pattern recognition paradigm will be proposed
Keywords :
condition monitoring; bridges; complex structures; damage identification; dynamic characteristics change; dynamic response; eight DOF test system; large civil engineering infrastructure; machine learning; mechanical systems; modal tests; model-based approach; rotating machinery monitoring; seismically-induced buckling; statistical pattern recognition; structural health monitoring; supervised learning; unsupervised learning; vibration-based damage detection;
fLanguage :
English
Publisher :
iet
Conference_Titel :
Condition Monitoring: Machinery, External Structures and Health (Ref. No. 1999/034), IEE Colloquium on
Conference_Location :
Birmingham
Type :
conf
DOI :
10.1049/ic:19990185
Filename :
772130
Link To Document :
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