DocumentCode :
2814574
Title :
Application of Support Vector Machine in Structure Damage Identification
Author :
Yang, Yan ; Liu, Tian-yi
Author_Institution :
Key Lab. of Fiber Opt. Sensing Technol., Wuhan Univ. of Technol., Wuhan, China
fYear :
2009
fDate :
19-20 Dec. 2009
Firstpage :
1
Lastpage :
3
Abstract :
Since the security accident of structures occurred continually in recent years, the damage identification is paid close attention by scholars. The support vector machine (SVM) as a new method of statistical theory is applied to identify structural damage in this paper. The relative change quantity of modal flexibility, used as the characteristic index of damage identification, is input in SVM classifier to identify the location and degree of structural damage. A simulative simply supported beam is set up and input with different level noises. The analysis results indicate that this method is feasible to identify the location and degree of structure damage with low noise.
Keywords :
accidents; condition monitoring; structural engineering computing; support vector machines; SVM classifier; civil engineering structure damage; modal flexibility; structure damage identification; structures security accident; support vector machine; Accidents; Classification algorithms; Educational technology; Equations; Kernel; Machine learning algorithms; Monitoring; Optical fibers; Support vector machine classification; Support vector machines;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information Engineering and Computer Science, 2009. ICIECS 2009. International Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-4994-1
Type :
conf
DOI :
10.1109/ICIECS.2009.5363204
Filename :
5363204
Link To Document :
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