Structural health monitoring using adaptive LMS filters

被引：1

作者：

Nayyerloo, Mostafa ^{[1
]}

Chase, J. Geoffrey ^{[1
]}

MacRae, Gregory A. ^{[2
]}

Chen, XiaoQi ^{[1
]}

Hann, Christopher E. ^{[1
]}

机构：

[1] Univ Canterbury, Dept Mech Engn, Private Bag 4800, Christchurch 8140, New Zealand

[2] Univ Canterbury, Dept Civil & Nat Resources Engn, Christchurch 8140, New Zealand

来源：

INTERNATIONAL JOURNAL OF COMPUTER APPLICATIONS IN TECHNOLOGY | 2010年 / 39卷 / 1-3期

关键词：

SHM; structural health monitoring; adaptive filtering; LMS; least mean squares; Bouc-Wen model; damage detection; non-linear structure; computer vision; line scan camera;

D O I：

10.1504/IJCAT.2010.034741

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

A structure's level of damage is determined using a non-linear model-based method utilising a Bouc-Wen hysteretic model. It employs adaptive Least Mean Squares (LMS) filtering theory in real time to identify changes in stiffness due to modelling error damage, as well as plastic and permanent displacements, which are critical to determining ongoing safety and use. The Structural Health Monitoring (SHM) method is validated on a four-storey shear structure model undergoing seismic excitation. For the simulated structure, the algorithm identifies stiffness changes to within 10% of the true value in 0.20 s, and permanent deflection is identified to within 5% of the actual as-modelled value using noise-free simulation-derived structural responses.

引用

页码：130 / 136

页数：7

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