Vibration mode shape recognition using image processing

Wang, Weizhuo; Mottershead, John E.; Mares, Cristinel

doi:10.1016/j.jsv.2009.05.024

Cited by 57 publications

(33 citation statements)

References 22 publications

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“…Thus, the general form of SD can be expressed as : Shape descriptors are so dependant on the kernel function. Fourier, Wavelets and Zernike moments have been successfully used [22][23][24] for modeshape recognition and finite element model updating. Here We choose to analyse modeshapes using the Elliptic Fourier Descriptor.Some properties of the FDs directly follow from the underlying theory of the Fourier transforms and series, for instance, the invariance to geometric transformations.…”

Section: Elliptic Fourier Descriptorsmentioning

confidence: 99%

“…An advanced criteria "correlation of Fourier Descriptor" adapted from correlation of Zernike moment [22][23][24] should be developed to distinguish close modes using the advantage of comparing at different levels of approximation (From Fourier to Wavelets Descriptors). Changes in modal parameters (frequency, damping, mode shapes) are commonly used in SHM to detect, localize and identify damages in structures.…”

Section: Fig 5 Dissimiliraties Can Be Seen Between Mode 10 and 15 Cmentioning

confidence: 99%

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Modeshapes Recognition Using Fourier Descriptors: A Simple SHM Example

Morlier

Bergh

Mevel

2012

Topics in Modal Analysis II, Volume 6

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OATAO is an open access repository that collects the work of Toulouse researchers and makes it freely available over the web where possible. This is an author-deposited version published in: http://oatao.univ-toulouse.fr/ Eprints ID: 5162Any correspondence concerning this service should be sent to the repository administrator: staff-oatao@inp-toulouse.fr Modeshapes recognition using Fourier descriptors: a simple SHM example ABSTRACTThe main objective of this study is to develop an alternative criterion for modeshape classification, as the currently available one, MAC (Modal Assurance Criteria), is only a vector correlation representing modeshape similarities. This new method is developed to provide a set of features (Fourier Descriptors) for comparing modeshapes with "local" similarities of higher interest than "global" similarities using nodal lines. These lines are able to characterize modeshapes very easily. So when damage occurs, we are able to track the few descriptors changes to localise the damage. We validated our method on a CFCF plate demonstrating the quality of the damage localisation and possible use in a "mode tracking" application (space structure).

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Section: Elliptic Fourier Descriptorsmentioning

confidence: 99%

Section: Fig 5 Dissimiliraties Can Be Seen Between Mode 10 and 15 Cmentioning

confidence: 99%

Modeshapes Recognition Using Fourier Descriptors: A Simple SHM Example

Morlier

Bergh

Mevel

2012

Topics in Modal Analysis II, Volume 6

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“…stress/strain, mode shapes etc, in a succinct form. Shape feature extraction [3,4] is one of the feasible ways to tackle such problems.…”

Section: Introductionmentioning

confidence: 99%

“…More substantial shape features may be obtained by functional transformations [4]. In this case, the original shape may be expressed as a set of coefficients (coordinates) of the decomposition kernels (bases) in the feature space.…”

Section: Introductionmentioning

confidence: 99%

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Construction of Shape Features for the Representation of Full-Field Displacement/Strain Data

Wang

Mottershead

Patki

et al. 2010

AMM

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The achievement of high levels of confidence in finite element models involves their validation using measured responses such as static strains or vibration mode shapes. A huge amount of data with a high level of information redundancy is usually obtained in both the detailed finite element prediction and the full-field measurements so that achieving a meaningful validation becomes a challenging problem. In order to extract useful shape features from such data, image processing and pattern recognition techniques may be used. One of the most commonly adopted shape feature extraction procedures is the Fourier transform in which the original data may be expressed as a set of coefficients (coordinates) of the decomposition kernels (bases) in the feature space. Localised effects can be detected by the wavelet transform. The acquired shape features are succinct and therefore simplify the model validation, based on the full-field data, allowing it to be achieved in a more effective and efficient way. In this paper, full-field finite element strain patterns of a plate with a centred circular hole are considered. A special set of orthonormal shape decomposition kernels based on the circular Zernike polynomials are constructed by the Gram-Schmidt orthonormalization process. It is found that the strain patterns can suitably be represented by only a very small number of shape features from the derived kernels.

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Finite Element Model Updating

Carvaho

Datta

Gupta

et al. 2018

Structural Health Monitoring of Large Civil Engineering Structures

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This thesis focuses on engineering, specifically structural, systems that are approximated by finite element models (FEMs). Initial FEMs are found to have poor accuracies and improved or updated models are sort. From the literature we note that a common set of challenges still persists in all FEM work. These are; which aspects of the model are most uncertain, how can we efficiently update the model and finally how do we know that our chosen model is the best for the system at hand. This is the finite element model updating problem. These challenges are reinforced by the number of different FEMs that can be proposed for any one system and the difficulty of determining the best model from these. Moreover all the said challenges are applicable to all possible FEMs. To address these challenges we propose that the FEM updating problem be analyzed in a multi-model context. What is implicit in this proposal is that updating one model in isolation will not be very informative. This proposed I would like to thank my parents; Lindiwe and Shole Mthembu for their unwavering support, guidance and giving me a better background than they had. I would also like to thank my sister, Sindi and brother Menzi for their support and companionship. I would like to thank Namwawa Siwale for the encouragement, patience and support throughout this thesis. I would also like to thank Professor Tshilidzi Marwala for his encouragement and supervision during this work. In addition I thank Professors Michael Friswell and Sondipon Adhikari for their insights and recommendations during this thesis.

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Vibration mode shape recognition using image processing

Cited by 57 publications

References 22 publications

Modeshapes Recognition Using Fourier Descriptors: A Simple SHM Example

Modeshapes Recognition Using Fourier Descriptors: A Simple SHM Example

Construction of Shape Features for the Representation of Full-Field Displacement/Strain Data

Finite Element Model Updating

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