Automated measurement of sintering degree in optical microscopy through image analysis of particle joins

In general terms, sintering describes the bonding of particles into a more coherent structure, where joins form between packed particles, usually as a result of heating. Characterization of sintering is an important topic in the fields of metallurgy, steel, iron ore pellets, ceramics, and snow for understanding material properties and material strength. Characterization using image analysis has been applied in a number of these fields but is either semi-automatic, requiring human interaction in the analysis, or based on statistical sampling and stereology to characterize the sample. This paper presents a novel fully automatic image analysis algorithm to analyze and determine the degree of sintering based on analysis of the particle joins and structure. Quantitative image analysis of the sintering degree is demonstrated for samples of iron ore pellets but could be readily applied to other packed particle materials. Microscope images of polished cross-sections of iron ore pellets have been imaged in their entirety and automated analysis of hundreds of images has been performed. Joins between particles have been identified based on morphological image processing and features have been calculated based on the geometric properties and curvature of these joins. The features have been analyzed and determined to hold discriminative power by displaying properties consistent with sintering theory and results from traditional pellet diameter measurements on the heated samples, and a statistical evaluation using the Welch t-test. HighlightsSintering describes the bonding of particles into a more coherent structure.We present an automatic image analysis algorithm to determine the sintering degree.Particle join geometric properties and curvature are computed.These features are shown to display properties consistent with sintering theory.Results are validated with physical dilation measurements on iron ore pellets.

[1]  Thierry Chartier,et al.  The use of image analysis for sintering investigations: The example of CeO2 doped with TiO2 , 2005 .

[2]  Bo Björkman,et al.  Mechanisms in oxidation and sintering of magnetite iron ore green pellets , 2008 .

[3]  N. Otsu.  A threshold selection method from gray level histograms , 1979 .

[4]  Jacques-Olivier Lachaud,et al.  Curvature Based Corner Detector for Discrete, Noisy and Multi-Scale Contours , 2008, Int. J. Shape Model..

[5]  Vladimir Kovalevsky,et al.  Curvature in Digital 2D Images , 2001, Int. J. Pattern Recognit. Artif. Intell..

[6]  A. Molinari,et al.  Investigation of liquid-phase sintering by image analysis , 1995 .

[7]  Cécile Coléou,et al.  Full three-dimensional modelling of curvature-dependent snow metamorphism: first results and comparison with experimental tomographic data , 2003 .

[8]  Isabelle Debled-Rennesson,et al.  A Linear Algorithm for Segmentation of Digital Curves , 1995, Int. J. Pattern Recognit. Artif. Intell..

[9]  James F. Shackelford,et al.  Introduction to materials science for engineers , 1985 .

[10]  Cécile Coléou,et al.  Computation of 3D curvatures on a wet snow sample , 1999 .

[11]  Kurt Meyer.  Pelletizing of iron ores , 1980 .

[12]  Welch Bl.  THE GENERALIZATION OF ‘STUDENT'S’ PROBLEM WHEN SEVERAL DIFFERENT POPULATION VARLANCES ARE INVOLVED , 1947 .

[13]  Jean Serra,et al.  Image Analysis and Mathematical Morphology , 1983 .

[14]  Azriel Rosenfeld,et al.  Digital geometry - geometric methods for digital picture analysis , 2004 .

[15]  Reinhard Klette,et al.  A Comparative Study on 2D Curvature Estimators , 2007, 2007 International Conference on Computing: Theory and Applications (ICCTA'07).

[16]  Frida Nellros,et al.  Automated image analysis of iron-ore pellet structure using optical microscopy , 2011 .

[17]  Jean-Louis Chermant,et al.  Morphological analysis of sintering , 1981 .

[18]  T. Fahidy,et al.  Solid state sintering in the induration of iron ore pellets , 1974, Metallurgical and Materials Transactions B.

[19]  A. Molinari,et al.  Image analysis investigation of the effect of the process variables on the porosity of sintered chromium steels , 2003 .

[20]  Sidney Ray,et al.  Applied photographic optics , 1998 .

[21]  Isabelle Debled-Rennesson,et al.  Optimal blurred segments decomposition of noisy shapes in linear time , 2006, Comput. Graph..

[22]  B. L. Welch.  The generalisation of student's problems when several different population variances are involved. , 1947, Biometrika.

[23]  Jean-Louis Chermant,et al.  Characterization of the microstructure of ceramics by image analysis , 1986 .

[24]  I. T. Young,et al.  Quantitative Microscopy , 1984, Definitions.

[25]  Bo Björkman,et al.  Binding mechanisms in wet iron ore green pellets with a bentonite binder , 2006 .

[26]  R. German.  Sintering theory and practice , 1996 .

[27]  Edward R. Dougherty,et al.  Hands-on Morphological Image Processing , 2003 .

[28]  Cécile Coléou,et al.  Three-dimensional geometric measurements of snow microstructural evolution under isothermal conditions , 2004, Annals of Glaciology.