DocumentCode :
2363276
Title :
Structural Health Monitoring using Adaptive LMS Filters
Author :
Nayyerloo, M. ; Chase, J. Geoffrey ; MacRae, Gregory A. ; Chen, Xiaoqi ; Hann, Christopher E.
Author_Institution :
Dept. of Mech. Eng., Univ. of Canterbury, Christchurch
fYear :
2008
fDate :
2-4 Dec. 2008
Firstpage :
397
Lastpage :
402
Abstract :
A structure´s level of damage is determined using a non-linear model-based method utilizing a Bouc-Wen hysteretic model. It employs adaptive least mean squares (LMS) filtering theory in real time to identify changes in stiffness due to modeling error damage, as well as permanent displacements, which are critical to determining ongoing safety and use. The structural health monitoring (SHM) method is validated on a 4-story shear structure model undergoing seismic excitation with 10% uniform noise added. The method identifies stiffness changes within 0.5-1.0% inside 0.2-1.0 seconds at different sampling frequencies. Permanent deflections are identified to within 10% of the true value in 1.0 second, converging further over the remainder of the record.
Keywords :
adaptive filters; condition monitoring; earthquake engineering; flaw detection; least mean squares methods; seismology; structural engineering; 4-story shear structure model; Bouc-Wen hysteretic model; adaptive LMS filters; damage detection; least mean squares filtering theory; seismic excitation; structural health monitoring; Adaptive filters; Condition monitoring; Displacement measurement; Filtering theory; Frequency; Hysteresis; Least squares approximation; Robustness; Safety; Velocity measurement; Bouc-Wen model; LMS; SHM; adaptive filtering; computer vision; damage detection; line scan camera; non-linear structure; structural health monitoring;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Mechatronics and Machine Vision in Practice, 2008. M2VIP 2008. 15th International Conference on
Conference_Location :
Auckland
Print_ISBN :
978-1-4244-3779-5
Electronic_ISBN :
978-0-473-13532-4
Type :
conf
DOI :
10.1109/MMVIP.2008.4749566
Filename :
4749566
Link To Document :
بازگشت