Academic literature on the topic 'Transformation texture'

The study shows the need for express systems, in which it is necessary to perform the analysis of texture images in various areas of diagnosis, for example, in medical express diagnostics of dermatologic disorders. Since the reliability of decision-making in such systems depends on the quality of image segmentation, which, as a rule, have the nature of spectral-statistical textures, it is advisable to develop methods for segmentation of such images and models for their presentation. A model of spectral-statistical texture is proposed, which takes into account the random nature of changes in the field variations and quasi-harmonics. On its basis, a vector-difference method of texture segmentation has been developed, which is based on the vector transformation of images of spectral and statistical textures based on vector algebra. The stages of the vector-difference method are the following: an evaluation of the spectral texture feature; an evaluation of the statistical texture feature; vector-difference transformation of texture images; a boundary detection of the homogeneous regions. For each pixel of the image in the processing aperture, the features of the spectral and statistical texture are evaluated. Statistical texture evaluation was performed by the quadratic-amplitude transformation. At the stage of vector-difference transformation of texture images, a vector of features of each pixel of an image is constructed, the elements of which are estimates of features of a spectral and statistical texture, and the modulus of the difference of two vectors is calculated. At the stage of boundary detection of homogeneous regions, Canny method was applied. The developed vector-difference texture segmentation method was applied both to model images of spectral-statistical texture and to texture images obtained in technical and medical diagnostics systems, namely, for images of psoriasis disease and wear zones of cutting tools. To compare the segmentation results, frequency-detector and amplitude-detector methods of texture segmentation were applied to these images. The quality of segmentation of homogeneous textured regions was evaluated by the Pratt's criterion and by constructing a confusion matrix. The research results showed that the developed vector-difference texture segmentation method has increased noise tolerance at a sufficient processing speed.

Low-carbon steels used for deep-drawability applications have properties which depend greatly on their crystallographic texture. It is therefore important to control the texture evolution during the thermomechanical processing. Until recently, little attention has been paid on the understanding of the textures formation after hot-rolling, which are produced by phase transformation, although it is recognised that they have an effect on the development of the texture in the further process (cold rolling and annealing). Indeed, one of the main difficulties consists in the measurement of texture above ambient temperature, in the austenite range. In the present work, EBSD technique is employed on a low-C steel and a method is proposed to determine local austenite orientation thanks to martensitic one, even if there is no residual austenite in the steel. The orientation relationships between the austenite phase and each of its product phases, here martensite and polygonal ferrite, are analysed and compared. Common Kurdjumov Sachs variants are detected for both phases. Variations in the intensities of these variants are also detected and could be due to the different phase transformation mechanisms, diffusion or shear.

Three fcc Ni–Co alloys with different stacking fault energies (SFE's) were cold rolled 95% and their textures were characterized by the orientation distribution function (ODF) method. BCC transformation textures were calculated from these experimental textures using three different orientation relationships for the γ→α transformation. The transformed ODF's derived from the Bain relationship were much sharper than the ones deduced from the Kurdjumov–Sachs (K–S) or the Nishiyama–Wassermann (N–W) relations. The ferrite texture determined on a controlled rolled steel, heavily deformed in the unrecrystallized γ region, agrees reasonably well with the bcc texture calculated using the K–S relation from the rolled Ni–Co alloy with similar SFE. The major texture components of the ferrite, namely {332}〈113〉 and {311}〈011〉, are found to originate from the two major rolling texture components of the austenite, i.e. the {110}〈112〉(Bs) and {112}〈111〉(Cu), respectively. Such ferrite transformation from heavily deformed austenite seems to follow the K–S relationship without any variant selection. By contrast, the texture of the martensite produced from deformed austenite appears to involve significant amounts of variant selection.

A Theory is Developed for Martensite Variants that have Different Start Temperatures but Existin the same Steel. Themethod Enables the Volume Fractions of each Kind Ofmartensite to be Followed Asa Function of the Steel Temperature. the Problemis Relevant to the Calculation of Detail in Transformationtexture when Phase Changes Occur under the Influence of External Stress. it should Allow for the Firsttime, the Estimation of both the Location of Crystallographic Poles on a Stereographic Projection, Andthe Diffraction Intensity Associated with that Location. it is Found that the Increment of Transformationas a Function of Undercooling is Identical for all Variants, once Simultaneous Transformation Begins.Any Variance in the Absolute Fractions is due to the Differences in the Martensite-Start Temperature.

Transformation behaviors and texture of Ni47Ti44Nb9 cold-rolled plates were studied by differential scanning calorimetry and X-ray diffraction test. R phase transformation does not occur in Ni47Ti44Nb9cold-rolled plate annealed at 350°C-750°C followed by quenching into the water. Martensite transformation temperature first increases and then decreases with increment of annealing temperature, and the maximum achieves at 700°C. The heat of reverse martensite transformation increases, while hardness decreases as annealing temperature increases. The major texture of cold-rolled plate is {332} and spread from {332} to {110}. When the annealing temperature is above 600°C, the major textures are {332} and {111} recrystallization texture in secondary cold-rolled plate.

This paper investigates the bulk texture evolution during cold rolling and annealing of Dual Phase steels for different processing conditions, i.e. cold reduction within the reduction range of 45 to 73% and annealing at temperatures between 650 and 850°C, which includes the recovery, recrystallisation and partial phase transformation domains. Textures have been measured by X-ray diffraction. The results reveal that the rolling texture is strengthened during the recovery process or initial stage of recrystallisation while during recrystallisation a weak RD-ND type of texture appears. During subsequent phase transformation the RD-ND type of texture further weakens and later randomises as the second phase fraction increases beyond 75%.