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