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

A technology for automatic measurement and morphological classification. It is used in measurement devices, image analysis, particle size analysis, etc. It can solve problems such as low accuracy and low efficiency, and achieve excellent universality.

Inactive Publication Date: 2009-08-19
JIANGSU UNIV
View PDF0 Cites 22 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Automatic measurement method for separated-out particles in steel and morphology classification method thereof
  • Automatic measurement method for separated-out particles in steel and morphology classification method thereof
  • Automatic measurement method for separated-out particles in steel and morphology classification method thereof

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0033] Such as figure 2 As shown, first to figure 2 The original image is preprocessed. First, the median filter method is used to smooth the image to remove the noise brought to the precipitated particle image during film production or acquisition, and then the contrast of the image is increased through gray balance processing. In view of the fact that the present invention only involves the determination of the morphological characteristics of the precipitated particles, that is, the separate analysis of the precipitated particles in the image has nothing to do with the color information, so binary segmentation can be performed on it to obtain a black and white template that completely separates the precipitated particles from the background, That is, the binary image of the particle. Due to the diversity and complexity of the images of precipitated particles in steel, the gray contrast value between the particles and the background is very constant, and the multi-region ...

Embodiment 2

[0113] Place Figure 8 The image shown in this image has a large number of precipitated particles and a complex background. Concrete processing procedure of the present invention is: first to Figure 8 The target image shown is preprocessed, the holes are filled by morphological filtering and the improved seed filling method is used, and the agglomerated particles are segmented by using the empirical criterion threshold value, thereby restoring the real shape of the target particles, and obtaining Figure 9 The effect diagram after binary segmentation, morphological filtering and defect particle processing is shown. On this basis, the particle measurement and particle shape classification statistics are carried out, and then the particle size distribution of the precipitated particles is obtained as follows: Figure 10a The morphological distribution of the precipitated particles is shown as Figure 10b As shown, the particle size measurement and analysis results are shown ...

Embodiment 3

[0117] Such as Figure 11 The image shown has stuck particles and a lot of background noise. The specific processing process of the present invention is as follows: firstly, the target image is preprocessed, the holes are filled through morphological filtering and the improved seed filling method is used, and the agglomerated particles are segmented by applying the empirical criterion threshold, thereby restoring the true shape of the target particles, Got Figure 12 The binary segmented and morphologically filtered image shown, and Figure 13 The effect diagram after binary segmentation, morphological filtering and defect particle processing is shown. On this basis, the particle measurement and particle shape classification statistics are carried out, and then the particle size distribution of the precipitated particles is shown in Figure 14a and the shape distribution of the precipitated particles is shown in Figure 14a. Figure 14b As shown, its particle size measurement...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

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...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
IPC IPC(8): G06K9/62G06T7/00G06N3/02G01N15/02
Inventor 李新城朱伟兴张炎
Owner JIANGSU UNIV
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap