Influence of Noise-Generating Factors on Cross-Correlation Electron Backscatter Diffraction (EBSD) Measurement of Geometrically Necessary Dislocations (GNDs)

Abstract

Studies of dislocation density evolution are fundamental to improved understanding in various areas of deformation mechanics. Recent advances in cross-correlation techniques, applied to electron backscatter diffraction (EBSD) data have particularly shed light on geometrically necessary dislocation (GND) behavior. However, the framework is relatively computationally expensive-patterns are typically saved from the EBSD scan and analyzed offline. A better understanding of the impact of EBSD pattern degradation, such as binning, compression, and various forms of noise, is vital to enable optimization of rapid and low-cost GND analysis. This paper tackles the problem by setting up a set of simulated patterns that mimic real patterns corresponding to a known GND field. The patterns are subsequently degraded in terms of resolution and noise, and the GND densities calculated from the degraded patterns using cross-correlation ESBD are compared with the known values. Some confirmation of validity of the computational degradation of patterns by considering real pattern degradation is also undertaken. The results demonstrate that the EBSD technique is not particularly sensitive to lower levels of binning and image compression, but the precision is sensitive to Poisson-type noise. Some insight is also gained concerning effects of mixed patterns at a grain boundary on measured GND content.

A consistent full-field integrated DIC framework for HR-EBSD

“…To this end, the mean strain error (✏ E ) is plotted over increasing noise levels reaching 20%, with insets visually showing the noise in EBSPs and residuals. At fairly large noise levels of up to 5%, the strain errors remain relatively small (below 10 5 ), whereas a further increase of the noise causes lower accuracies, but remarkably still below 10 4 for extreme noise of 20% (which is comparably noisy to "Poisson noise level 16" from [39]), though at the expense of an increase in the number of iterations required for proper convergence. Note that, in IDIC, the image residual field is often recommended as a powerful tool to evaluate the performance of the algorithm in experiments and to assess the correlation convergence and possible systematic errors in the underlying model, which can be identified from regions in the residual field with increased amplitude, as, e.g., demonstrated in [40].…”

Resolving pseudosymmetry in γ-TiAl using cross-correlation electron backscatter diffraction with dynamically simulated reference patterns

“…The resolution of the images was incrementally reduced by simply binning the original patterns (1024 Â 1024 resolution) as they were read into the algorithm. Poisson noise was introduced into the experimental patterns as they were read into the algorithm using the method reported by Hansen et al (2017). The noise and resolution were varied independently.…”

Atomistic survey of grain boundary-dislocation interactions in FCC nickel

“…The work presented here is part of a collaborative effort involving experimental work [10][11][12][13], mesoscale modeling [14,15], and atomistic simulations [16] aimed at better understanding how large populations of dislocations interact with GBs. The present work contributes by investigating the attributes that affect the GB-dislocation interactions at the atomic scale, which can then be used to inform the mesoscale modeling and interpret experimental observations.…”