Computation of Full-field Strains Using Principal Component Analysis

Grama, Srinivas N.; Subramanian, Subramanian

doi:10.1007/s11340-013-9800-z

Cited by 20 publications

(27 citation statements)

References 49 publications

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“…2 that there is only one dominant singular value, which is larger than the other singular values. This is agreed well with the fact that there is only one dominant deformation pattern in each direction [16]. It can be seen that the dominant singular values decrease monotonically with the decrease of SNR.…”

Section: Uniform Translationsupporting

confidence: 88%

“…Zhao et al [14,15] proposed a fast Hermite element method and an improved Hermite finite element smoothing method to smooth and differentiate noisy displacement field in DIC. Grama and Subramanian [16] proposed a novel method for strain calculation from full-field data, which is based on the multivariate analysis technique of Principal Component Analysis (PCA) using which the singular vectors and singular values for each component of the displacement field were obtained. By choosing only the dominant singular values and their corresponding singular vectors, the dimensionality of the displacement data is sharply reduced and a significant portion of the noise is eliminated.…”

Section: Introductionmentioning

confidence: 99%

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Displacement field denoising for high-temperature digital image correlation using principal component analysis

Hao

Zhu

et al. 2016

Mechanics of Advanced Materials and Structures

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Principal component analysis (PCA) was extended to minimize the noise effect in digital image correlation (DIC) measurement under high-temperature atmosphere environment.First, the principle of PCA was introduced, and the singular vectors and singular values for each component of the displacement fields from DIC were obtained. Then, the simulated hightemperature speckle images were developed to investigate the influences of noise on DIC method under high-temperature environment. Finally, the displacement fields of several special conditions were extracted from the simulated speckle images and experimental images, also the

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Section: Uniform Translationsupporting

confidence: 88%

Section: Introductionmentioning

confidence: 99%

Displacement field denoising for high-temperature digital image correlation using principal component analysis

Hao

Zhu

et al. 2016

Mechanics of Advanced Materials and Structures

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“…As done in the numerical example, the deformation gradient F was computed applying the gradient function to the displacement field obtained by DIC, afterwards, all the other quantities were derived from F (i.e., ϵ , Δ ϵ ,

{\overset{\overset{ϵ}{true}}{true}}_{p}

\overset{σ}{true}

normalΔ \overset{ε}{true}

, and

\overset{ε}{true}

). More advanced derivation functions could be used to evaluate the deformation gradient and the strain field, for example, using polynomials or other approaches . However, in the present application, the gradient function is satisfactory and produce accurate strain field maps, as illustrated in Figure .…”

Section: Resultsmentioning

confidence: 99%

A general linear method to evaluate the hardening behaviour of metals at large strain with full‐field measurements

Rossi

Lattanzi

Barlat

2018

Strain

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The hardening behaviour of metals is generally described in terms of a stress‐strain curve derived from experiments. In this paper, a linear method to identify the stress‐strain curve starting from full‐field measurement data is presented. This method can be applied to any stress state using a generic yield function, the only requirement is that the full‐field measurement is extended up to the border of the specimen. The method is presented and validated using a finite element model of a notched specimen. Moreover, experiments were performed on specimens cut from a BH340 steel sheet to illustrate the viability to actual cases. Two geometries were considered, a standard uniaxial test, where the method was used to evaluate the post‐necking behaviour, and a notched specimen with a heterogeneous strain field. The proposed method, named linear stress‐strain curve identification (LSSCI), can be a useful tool in combination with inverse methods to identify the constitutive behaviour of metals in large strain plasticity.

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“…The strain component fields ε 1 , ε 2 and ε 6 are expressed as linear combinations of the piecewise-continuous p dominant [5] Right Eigenfunctions Left Eigenfunctions…”

Section: Modified Evfm Equationsmentioning

confidence: 99%

“…systematically constructed using the eigenfunctions [5] of the measured strain fields. The VFs so chosen have clear physical meaning and are directly determined using Principal Component Analysis of the measured strains and result in a compact set of algebraic equations in the unknown material parameters without introducing other unknown parameters to be solved for.…”

Section: Introductionmentioning

confidence: 99%