Detection and quantification of non-linear structural behavior using principal component analysis

被引:39
作者
Hot, A. [1 ]
Kerschen, G. [2 ]
Foltete, E. [1 ]
Cogan, S. [1 ]
机构
[1] FEMTO ST Inst, Dept Appl Mech, F-25000 Besancon, France
[2] Univ Liege, Dept Aerosp & Mech Engn, Struct Dynam Res Grp, B-4000 Liege, Belgium
关键词
Non-linear detection; Principal component analysis; Subspace comparison; Design margins; SENSOR VALIDATION; IDENTIFICATION;
D O I
10.1016/j.ymssp.2011.06.006
中图分类号
TH [机械、仪表工业];
学科分类号
0802 ;
摘要
The detection of non-linear behavior in structural dynamics is a very important step to the extent that the presence of non-linearities, even local, can affect the global dynamic behavior of a structure. A large number of techniques that enable engineers to detect non-linear behavior can be found in the literature but most of these methods exploit frequency domain data and give better results with a stepped-sine excitation. The goal of this paper is to propose an alternative methodology that is based on the principal component analysis and uses time responses obtained with a random excitation. Two criteria will be used to quantify the difference between two response subspaces, based on the angle between them and the residual error resulting from the projection of one on the other. The concept of limit of linearity and design decision margins is also addressed in this paper. The methodology is demonstrated using an academic simulated system and then using measured data of a simplified solar array system. (C) 2011 Elsevier Ltd. All rights reserved.
引用
收藏
页码:104 / 116
页数:13
相关论文
共 14 条
[1]  
American Society of Mechanical Engineers (ASME), 2006, GUID VER VAL COMP SO, V10
[2]  
[Anonymous], 2001, Nonlinearity in Structural Dynamics: Detection, Identification and Modelling, DOI DOI 10.1201/9780429138331
[3]   NUMERICAL METHODS FOR COMPUTING ANGLES BETWEEN LINEAR SUBSPACES [J].
BJORCK, A ;
GOLUB, GH .
MATHEMATICS OF COMPUTATION, 1973, 27 (123) :579-594
[4]  
De Boe P., 2003, Structural Health Monitoring, V2, P137, DOI DOI 10.1177/1475921703002002005
[5]   Considering high harmonics for identification of non-linear systems by Hilbert transform [J].
Feldman, Michael .
MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2007, 21 (02) :943-958
[6]   Sensor validation for smart structures [J].
Friswell, MI ;
Inman, DJ .
JOURNAL OF INTELLIGENT MATERIAL SYSTEMS AND STRUCTURES, 1999, 10 (12) :973-982
[7]   Detection and description of non-linear phenomena in experimental modal analysis via linearity plots [J].
Göge, D ;
Sinapius, M ;
Füllekrug, U ;
Link, M .
INTERNATIONAL JOURNAL OF NON-LINEAR MECHANICS, 2005, 40 (01) :27-48
[8]  
Golub GH., 1989, MATRIX COMPUTATIONS, DOI DOI 10.56021/9781421407944
[9]  
Hot A., 2009, P 11 EUR C SPAC STRU
[10]   Past, present and future of nonlinear system identification in structural dynamics [J].
Kerschen, G ;
Worden, K ;
Vakakis, AF ;
Golinval, JC .
MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2006, 20 (03) :505-592