Automatic measurement method for separated-out particles in steel and morphology classification method thereof

Abstract

The invention discloses an automatic measuring and morphological classification method for particles precipitated from steel, comprising the steps as follows: firstly, the electron micrographs of the target particles precipitated from steel are subjected to image binary segmentation so as to obtain the binary images of the particles; the binary images of the target particles are denoised by a morphological filtering method, a seed filling method is adopted to fill holes, and the particles to be separated are determined by the domain value determined by experience criterion and the separation of agglomerate particles is carried out; the particles after separation are subjected to region labeling; finally, the neural network morphological classification models of the target particles precipitated from steel are established; and results are displayed and output in the form of graph files. The method can obtain ideal measuring and classification effect without omission inspection and re-inspection; the measurement accuracy of particle size can reach plus or minus 2 microns, the particle size distribution anastomotic rate can be more than 91.7 percent, and the anastomotic rate of morphological classification can be more than 90.5 percent; the particle measuring and classification of one view field cost only a few minutes; and the method has excellent universality and can be used in all the particle measuring and classification works with complex backgrounds and morphologies in the material field and biological field.

Description

technical field [0001] The invention relates to the field of microstructure analysis of steel, in particular to a method for measuring precipitated particles in a transmission electron microscope film image and a transmission electron microscope complex image of a steel sample and its shape classification analysis method. Background technique [0002] With the rapid development of scientific and technological research on iron and steel materials, the research and development of various steel types has gradually been established on the basis of the quantitative relationship between composition, structure, structure and performance. structure and microstructure to obtain the desired properties. For multi-phase steel grades, the particle size, shape and distribution of precipitated particles in the steel have a decisive impact on its structure and properties. In order to improve the performance of steel, give full play to the effect of beneficial precipitated particles, and co...

AI Technical Summary

Problems solved by technology

[0004] The purpose of the present invention is to provide a kind of automatic measurement of precipitated particles in steel based on particle shape characteristics and neural network classification method, aiming at the defects of low efficiency and low precision of the current working mode of manual measurement calculation and statistics by artificial grid method and morphological classification and statistical methods, using computer to realize accurate and efficient measurement, classification and statistical work of the particle size and shape of precipitated particles in steel

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