Subpixel Speckle Displacement Measurement Using a Digital Processing Technique

Oulamara, Ammar; Tribillon, G.; Duvernoy, J.

doi:10.1080/09500348814551271

Cited by 18 publications

(8 citation statements)

References 7 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…To achieve higher resolutions, the discrete intercorrelation function is interpolated in the neighborhood of its discrete maximum by a quadratic polynomial. 16 …”

Section: ~(Kmentioning

confidence: 99%

Analysis of strain localization during tensile tests by digital image correlation

Wattrisse

Chrysochoos

Muracciole

et al. 2001

Experimental Mechanics

258

178

View full text Add to dashboard Cite

ABSTRACTmThis paper presents an imaging technique developed to study the strain localization phenomena that occur during the tension of thin, flat steel samples. The data are processed using digital speckle image correlation to derive the two in-plane components of the displacement vectors. The authors observe that the calculation of the intercorrelation function reveals a systematic error and propose a numerical method to limit its influence. Plastic incompressibility and thin-sheet assumptions are used to derive the third displacement component and, hence, the various strain and strain rate components. Numerous checks are presented at each step in processing the data to determine the final accuracy of the strain measurements. It is estimated that this accuracy is quite sufficient to track the inception and the development of localization. Examples of possible application are presented for mild steels whose strain localization mechanisms appear to be precocious and gradual.KEY WORDS--Digital image correlation, strain rate measurement, necking, material behavior, steel Over the past two decades, the simulation tools used in mechanics of materials have become increasingly powerful. Progress made in the field of scientific computation is giving rise to a new branch of mechanics called computational mechanics of solids.1 It allows the use of more realistic, and also more complex, models of behavior.Of course, the consistency of the simulation results depends very much on the validity of the constitutive equations implemented in the computational codes. These phenomenological equations are, most often, identified on the basis of experiments carried out on particular structures for which stress and strain patterns are supposed to be known. For instance, we assume that strain and stress fields are homogeneous in the gage part of a sample during a simple tensile test. This homogeneity hypothesis, often implicitly assumed, is necessary to estimate the stress and the strain from load and displacement measurements. Naturally, as soon as a strain localization occurs--local necking, LiJders bands, transformation bands and so on--the mechanical fields are B.

show abstract

“…To achieve higher resolutions, the discrete intercorrelation function is interpolated in the neighborhood of its discrete maximum by a quadratic polynomial. 16 …”

Section: ~(Kmentioning

confidence: 99%

Analysis of strain localization during tensile tests by digital image correlation

Wattrisse

Chrysochoos

Muracciole

et al. 2001

Experimental Mechanics

258

178

View full text Add to dashboard Cite

show abstract

“…Various rules of thumb suggest that the number of poles for short data records be of the order of one third to one half the number of data records. 7 For this application, in which we are certain that all the spectral energy is located in a narrow band (the focused bright line), we found that the fewer number of poles tended to suffice and that results became erratic for the number of poles exceeding one third the number of data records. One factor that was of use in the determination of the number of poles to use was the consistency of the estimates provided by the two angles.…”

Section: Drilled Billetmentioning

confidence: 85%

Transform method of processing for speckle strain-rate measurements

et al. 1994

View full text Add to dashboard Cite

We have developed a highly sensitive method for measuring thermal expansion, mechanical strain, and creep rates. We use the well-known technique of observing laser speckle with a pair of linear array cameras, but we employ a data-processing approach based on a two-dimensional transform of the speckle histories from each camera. This technique can effect large gauge sizes, which are important in the assessment of the spatial statistics of creep. Further, the algorithm provides simultaneous global estimates of the strain rates at both small- and large-scale sizes. This feature may be of value in the investigation of materials with different short- and long-range orders. General advantages of our technique are compact design, modest resolution requirements, insensitivity to slow surface microstructure changes (as seen with oxidation), and insensitivity to zero-mean-noise processes such as turbulence and vibration. Herein we detail the theory of our technique and the results of a number of experiments. Thesetests are intended to demonstrate the performance advantages and limitations of the transform method of processing speckle strain-rate data.

show abstract

“…These discrete data were interpolated in the vicinity of their maximum by quadratic functions giving a subpixel displacement resolution [14].…”

Section: Dicmentioning

confidence: 99%

An inverse method applied to the determination of deformation energy distributions in the presence of pre-hardening stresses

Latourte

Samida

Chrysochoos

et al. 2008

The Journal of Strain Analysis for Engineering Design

View full text Add to dashboard Cite

This paper presents an experimental procedure to estimate the deformation energy distribution within plane samples submitted to mechanical loading. This procedure combined a digital image correlation (DIC) technique giving in-plane displacement fields with an identification method that separately provided fields of material properties and stress distributions developed during the loading. The method was first applied to simulated data to characterize the capabilities of the image processing. Finite element computations were first performed on a complex structure using a standard linear kinematical hardening model to generate multistage loadings leading to heterogeneous displacements and distributions of deformation energy. Loads and displacements were then used as inputs to check the robustness of the image processing by comparing the identified deformation energy fields with the computed ones. The procedure was then applied to experimental data. Tests were conducted under conditions similar to the numerical tests. The identification of a linear kinematical hardening model gave deformation energy patterns showing a good agreement with the simulated results, even in the presence of residual stresses induced by a prehardening.

show abstract

Subpixel Speckle Displacement Measurement Using a Digital Processing Technique

Cited by 18 publications

References 7 publications

Analysis of strain localization during tensile tests by digital image correlation

Analysis of strain localization during tensile tests by digital image correlation

Transform method of processing for speckle strain-rate measurements

An inverse method applied to the determination of deformation energy distributions in the presence of pre-hardening stresses

Contact Info

Product

Resources

About