CN-122023709-A - Three-dimensional space distribution characterization method and system for inclusions in alloy steel

CN122023709ACN 122023709 ACN122023709 ACN 122023709ACN-122023709-A

Abstract

The invention relates to the technical field of ferrous metallurgy, in particular to a method and a system for representing three-dimensional spatial distribution of inclusions in alloy steel; the method comprises the steps of combining an alloy steel sample with X-ray tomography and layer cutting imaging, scanning and imaging layer by layer, reserving sample integrity, acquiring three-dimensional distribution information of inclusions, filling blank through data interpolation, constructing three-dimensional data, and facilitating processing analysis after voxelization simplification. And finally, fitting actual data by using a space point process model, establishing a distribution characteristic model, verifying data reliability and having prediction capability, and predicting inclusion distribution under different processes, thereby providing support for production optimization and the like.

Inventors

Pan Guochuan
PAN QINGCHUAN
XU XIANHUA
KANG KAI
ZHOU BAIWEI
FENG CHENGKAI
CHEN CHANGXU
Weng tuo
LI JINLONG
YANG XISHENG
ZHAO JIAXING

Assignees

浙江浙能乐清发电有限责任公司
中国特种设备检测研究院

Dates

Publication Date: 20260512
Application Date: 20251209

Claims (10)

1. A method for characterizing the three-dimensional spatial distribution of inclusions in alloy steel, the method comprising the steps of: step S1, randomly extracting samples from alloy billets or alloy steel finished products to be detected, cutting the extracted samples into the dimensions of 10mm multiplied by 5mm, removing scratches and deformation layers on the surfaces of the cut samples by means of mechanical polishing and chemical polishing, and controlling the surface flatness of the cut samples to be +/-0.5 ; Step S2, performing multi-angle scanning on the sample with the flatness reaching the standard in the step S1 in a step length of 0.5-5 degrees by adopting an X-ray tomography mode, collecting tomographic projection data obtained by scanning, and generating three-dimensional tomographic image data with a first resolution, wherein the first resolution is 10-50 ; Slicing the scanned sample layer by focusing the ion beam, and obtaining a two-dimensional image with a second resolution by using SEM after each slicing to obtain layered two-dimensional image data, wherein the thickness of the slice is controlled to be less than or equal to 50 The second resolution is 100 -1 ; S3, dividing the three-dimensional tomographic image data and the layer-cut two-dimensional image data, converting the divided three-dimensional tomographic image data into a three-dimensional model in a voxel three-dimensional reconstruction mode, distinguishing inclusions from a steel matrix in the three-dimensional model based on a gray threshold value and edge detection, and calculating the size, shape parameters and position coordinates of the inclusions; And S4, counting the number density, size distribution and shape distribution data of the inclusions, calculating the average interval and aggregation degree index of the inclusions in the alloy steel, displaying the spatial distribution of the inclusions in a three-dimensional graph form, and establishing and outputting a mathematical model for describing the spatial distribution of the inclusions.
2. The method according to claim 1, wherein in step S3, the blank region between the three-dimensional tomographic image data and the sliced two-dimensional image data is supplemented by a Kriging interpolation algorithm, the interpolated three-dimensional data is discretized into 3D voxels, and the size of each 3D voxel is equal to or smaller than 1 3 。
3. The method according to claim 2, wherein in step S3, the inclusions are separated from the steel matrix by an adaptive thresholding algorithm, and the inclusion boundary profile is optimized in combination with edge detection.
4. The method according to claim 1, wherein in step S3, noise is removed by using an open operation or a closed operation method, the shape of the inclusions is corrected, and size and shape parameters including at least volume, surface area, long axis/short axis ratio are calculated.
5. The method for characterizing three-dimensional spatial distribution of inclusions in alloy steel according to claim 1, wherein a coordinate system based on a three-dimensional model records a spatial position of each inclusion, and counts a relative distance between each inclusion and a steel matrix, the spatial position being a spatial three-dimensional coordinate.
6. The method according to claim 1, wherein in step S4, the poisson point process or Ma Erke f random field model is used to fit the spatial distribution characteristics of the inclusions, and the average spacing and the aggregation level are quantified, and the aggregation level includes at least Gini coefficient or spatial autocorrelation coefficient.
7. The method according to claim 1, wherein in step S3, the three-dimensional tomographic image data and the layered two-dimensional image data are segmented, noise in the image is removed first, and then contrast ratio between the inclusions in the image and the steel matrix is enhanced by histogram equalization, and the inclusions are separated from the steel matrix according to a gray threshold.
8. The method for characterizing three-dimensional spatial distribution of inclusions in alloy steel according to any one of claims 1 to 7, wherein in step S4, a digital model selects a spatial point process model, fits the spatial point process model with actual data, and obtains a feature model of inclusion distribution after passing the mathematical model verification by statistically checking goodness of fit of the mathematical model, and inputs process parameters including at least smelting temperature and deoxidizer type through the mathematical model, and outputs a predicted result of inclusion distribution.
9. The system for characterizing a three-dimensional spatial distribution of inclusions in steel alloys according to any of the claims 1-8, wherein the system comprises, The sample preparation unit is used for randomly extracting samples from alloy billets or alloy steel finished products to be detected, cutting the extracted samples into the dimensions of 10mm multiplied by 5mm, and removing surface scratches and deformation layers through mechanical polishing and chemical polishing to ensure that the surface flatness of the samples reaches +/-0.5 ; A scanning unit for performing X-ray tomography, wherein the sample is scanned at multiple angles in a step length of 0.5-5 degrees, tomographic projection data are collected, and three-dimensional tomographic image data with a first resolution of 10-50 is generated Slicing layer by focusing ion beam, obtaining two-dimensional image with second resolution by SEM after each slicing, and forming slice two-dimensional image data, wherein the slice thickness is less than or equal to 50 The second resolution is 100nm-1 ; The data processing unit is used for dividing the three-dimensional tomographic image data and the layer-cut two-dimensional image data, and converting the three-dimensional tomographic image data into a three-dimensional model through voxel three-dimensional reconstruction; and the spatial distribution characterization unit is used for counting the number density, the size distribution and the shape distribution data of the inclusions, calculating the average interval and the aggregation degree index of the inclusions in the alloy steel, displaying the spatial distribution of the inclusions in a three-dimensional graph form, and establishing and outputting a mathematical model for describing the spatial distribution of the inclusions.
10. A machine-readable storage medium having stored thereon instructions for causing a machine to perform the method of characterizing the three-dimensional spatial distribution of inclusions in alloy steel according to any one of claims 1-8.

Description

Three-dimensional space distribution characterization method and system for inclusions in alloy steel Technical Field The invention relates to the technical field of ferrous metallurgy, in particular to a method and a system for representing three-dimensional spatial distribution of inclusions in alloy steel. Background In the production process of steel, the existence of inclusions in the steel is a problem which cannot be ignored. The inclusions in steel mean non-metallic substances or other metallic substances contained in the steel material, which are not expected to exist. The formation of these inclusions is not occasional and is usually produced during the smelting, casting or processing of the steel. For example, P91 steel, which is a high-performance alloy steel, also called T91 steel, belongs to the 9% chromium alloy steel series, and is widely used in high-temperature, high-pressure industrial environments by virtue of its excellent properties. Inclusions have a crucial influence on the performance of P91 steel. The type, size, shape and distribution of the alloy can affect the mechanical property, corrosion resistance and welding property of the steel to different degrees. In view of this, it is particularly necessary to accurately detect inclusions in P91 steel. CN113030143A discloses a method for detecting the corrosion activity of inclusions in low alloy steel, which comprises the steps of firstly cutting a sample with the thickness of 10mm multiplied by 10mm from a low alloy steel plate to be used as an original sample to be detected, secondly polishing the original sample to be detected by using silicon carbide sand paper, and mechanically polishing until the surface roughness is smaller than 0.8The method comprises the steps of obtaining a polished sample to be tested, sequentially cleaning the polished sample to be tested with acetone, deionized water and alcohol, drying to obtain a prefabricated sample to be tested, placing the prefabricated sample to be tested in a full-automatic inclusion analyzer to obtain the number and density rho of inclusions in the prefabricated sample to be tested, placing the prefabricated sample to be tested in a field emission scanning electron microscope, setting the accelerating voltage of the field emission scanning electron microscope to be 10-30 kV, randomly selecting 30-50 inclusions in the prefabricated sample, carrying out component identification on the 30-50 inclusions selected in the prefabricated sample by utilizing an X-ray energy spectrometer, measuring the type number n of the inclusions in the prefabricated sample to be tested to be the natural number of the inclusions which is more than or equal to 1 and less than or equal to 30-50, selecting one inclusion in the n types, sequentially recording the radius R, i=1, n of each type of the selected inclusions, and the residual stress sigma of the selected type i and the matrix in the n types of the inclusion, and sequentially recording the residual stress sigma of the matrix. And step seven, comparing the obtained residual stress sigma at the interface between the ith inclusion and the matrix in the selected various inclusions with the compressive yield strength sigma of the original Ri test sample to be tested, wherein if the obtained residual stress sigma is larger than the compressive yield strength sigma of the original test sample to be tested, the ith inclusion is an R corrosion active inclusion, and if the obtained residual stress sigma is smaller than or equal to the compressive yield strength sigma of the original test sample, the R is a non-corrosion active inclusion, and step eight, repeating the steps six and seven to sequentially obtain the corrosion activity of each inclusion in the selected inclusions. In the prior art, the imaging technology is difficult to accurately display the shape, size and position information of the inclusion due to insufficient resolution and definition, so that parameter measurement is inaccurate due to the fact that the boundary of the inclusion cannot be accurately identified, meanwhile, the traditional method is often limited to analysis and characterization of the existing data, prediction capability is lacked, and the method is difficult to directly apply to actual production. Disclosure of Invention Aiming at the problems existing in the prior art, the invention aims to provide a three-dimensional spatial distribution characterization method of inclusions in alloy steel. In order to solve the problems, the technical scheme adopted by the invention is as follows: A method for characterizing the three-dimensional spatial distribution of inclusions in an alloy steel, the method comprising the steps of: step S1, randomly extracting samples from alloy billets or alloy steel finished products to be detected, cutting the extracted samples into the dimensions of 10mm multiplied by 5mm, removing scratches and deformation layers on the surfaces of the cut samp