Vibration based damage detection in composite beams under temperature variations using Poincaré maps

2012 ◽  
Vol 62 (1) ◽  
pp. 120-132 ◽  
Author(s):  
Emil Manoach ◽  
Sylwester Samborski ◽  
Andrzej Mitura ◽  
Jerzy Warminski
Keyword(s):  
Damage Detection ◽  
Composite Beams ◽  
Poincaré Maps ◽  
Temperature Variations ◽  
Poincare Maps

scholarly journals A Robust Poincare Maps Method for Damage Detection based on Single Type of Measurement

2017 ◽  
Vol 842 ◽  
pp. 012001 ◽  
Author(s):  
Zhi-Bo Yang ◽  
Ya-Nan Wang ◽  
Hao Zuo ◽  
Xing-Wu Zhang ◽  
Yong Xie ◽  
...  
Keyword(s):  
Damage Detection ◽  
Single Type ◽  
Poincaré Maps ◽  
Poincare Maps

Bifurcations and chaos in converters. Discontinuous vector fields and singular Poincaré maps

Nonlinearity ◽  
2000 ◽  
Vol 13 (4) ◽  
pp. 1095-1121 ◽  
Author(s):  
Gerard Olivar ◽  
Enric Fossas ◽  
Carles Batlle
Keyword(s):  
Vector Fields ◽  
Poincaré Maps ◽  
Poincare Maps ◽  
Discontinuous Vector Fields

CHAOS AND TWO-TORI IN A NEW FAMILY OF 4-CNNS

2007 ◽  
Vol 17 (03) ◽  
pp. 953-963 ◽  
Author(s):  
XIAO-SONG YANG ◽  
YAN HUANG
Keyword(s):  
Neural Networks ◽  
Limit Cycle ◽  
Limit Cycles ◽  
Cellular Neural Networks ◽  
Lyapunov Spectrum ◽  
Regular Array ◽  
Poincaré Maps ◽  
One Dimensional ◽  
Poincare Maps ◽  
New Family

In this paper we demonstrate chaos, two-tori and limit cycles in a new family of Cellular Neural Networks which is a one-dimensional regular array of four cells. The Lyapunov spectrum is calculated in a range of parameters, the bifurcation plots are presented as well. Furthermore, we confirm the nature of limit cycle, chaos and two-tori by studying Poincaré maps.

Dynamic Analysis of a Lü Model in Six Dimensions and Its Projections

2017 ◽  
Vol 18 (5) ◽  
pp. 371-384 ◽  
Author(s):  
Luis Alberto Quezada-Téllez ◽  
Salvador Carrillo-Moreno ◽  
Oscar Rosas-Jaimes ◽  
José Job Flores-Godoy ◽  
Guillermo Fernández-Anaya
Keyword(s):  
Dynamic Analysis ◽  
Complex Variables ◽  
Bifurcation Diagrams ◽  
Poincaré Maps ◽  
Five Dimensions ◽  
Strange Nonchaotic Attractor ◽  
The Real ◽  
Poincare Maps ◽  
Extended Complex ◽  
Six Dimensions

AbstractIn this article, extended complex Lü models (ECLMs) are proposed. They are obtained by substituting the real variables of the classical Lü model by complex variables. These projections, spanning from five dimensions (5D) and six dimensions (6D), are studied in their dynamics, which include phase spaces, calculations of eigenvalues and Lyapunov’s exponents, Poincaré maps, bifurcation diagrams, and related analyses. It is shown that in the case of a 5D extension, we have obtained chaotic trajectories; meanwhile the 6D extension shows quasiperiodic and hyperchaotic behaviors and it exhibits strange nonchaotic attractor (SNA) features.

Observation and Evolution of Chaos for an Autonomous System

1984 ◽  
Vol 51 (3) ◽  
pp. 664-673 ◽  
Author(s):  
E. H. Dowell
Keyword(s):  
Elastic Plate ◽  
Physical Interpretation ◽  
Autonomous System ◽  
Phase Plane ◽  
Power Spectra ◽  
Poincaré Maps ◽  
Flowing Fluid ◽  
Poincare Maps ◽  
Time Histories

Time histories, phase plane portraits, power spectra, and Poincare maps are used as descriptors to observe the evolution of chaos in an autonomous system. Although the motions of such a system can be quite complex, these descriptors prove helpful in detecting the essential structure of the motion. Here the principal interest is in phase plane portraits and Poincare maps, their methods of construction, and physical interpretation. The system chosen for study has been previously discussed in the literature, i.e., the flutter of a buckled elastic plate in a flowing fluid.

scholarly journals A transmittance-based methodology for damage detection under uncertainty: An application to a set of composite beams with manufacturing variability subject to impact damage and varying operating conditions

2018 ◽  
Vol 18 (1) ◽  
pp. 318-333 ◽  
Author(s):  
Aggelos G Poulimenos ◽  
John S Sakellariou
Keyword(s):  
Damage Detection ◽  
Production Line ◽  
Composite Structures ◽  
Impact Damage ◽  
Parametric Representation ◽  
Composite Beams ◽  
Operating Conditions ◽  
Ratio Test ◽  
Detection Characteristic ◽  
Testing Procedures

Oftentimes, the complexity in manufacturing composite materials leads to corresponding structures which although they may have the same design specifications they are not identical. Thus, composite parts manufactured in the same production line present differences in their dynamics which combined with additional uncertainties due to different operating conditions may lead to the complete concealment of effects caused by small, incipient, damages making their detection highly challenging. This damage detection problem in nominally identical composite structures is pursued in this study through a novel data-based response-only methodology that is founded on the autoregressive with exogenous (ARX) excitation parametric representation of the transmittance function between vibration measurements at two different locations on the structure. This is a statistical time series methodology within which two schemes are formulated. In the first, a single-reference transmittance model representing the healthy structure is employed, while multiple transmittance models from a sample of available healthy structures are used in the second. The model residual signal constitutes for both schemes the damage detection characteristic quantity that is used in appropriate hypothesis testing procedures with the likelihood ratio test. The methodology is experimentally assessed via damage detection for a population of composite beams which are manufactured in the same production line representing the half of the tail of a twin-boom unmanned aerial vehicle. The damage detection results demonstrate the superiority of the multiple transmittance models based scheme that may effectively detect damages under significant manufacturing variability and varying boundary conditions.

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