Composition uniformity detection method based on microscopic images of titanium alloy ingots

By partitioning and analyzing the composition of the microscopic images of titanium alloy ingots and combining them with electron probe technology, the problem of accuracy in detecting the composition uniformity of titanium alloy ingots was solved, and a more comprehensive composition uniformity assessment was achieved.

CN120182277BActive Publication Date: 2025-09-30BAOJI TOPUDA TITANIUM IND CO LTD
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Patent Information

Application Number
CN202510661123.8
Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
Filing Date
2025-05-22
Publication Date
2025-09-30
Estimated Expiration
2045-05-22

AI Technical Summary

Technical Problem

When testing the compositional uniformity of titanium alloy ingots, existing technologies are not accurate enough and cannot accurately reflect the compositional uniformity of the sample, especially because the morphological structure of different grains affects the strength, plasticity and toughness of the material.

Method used

By obtaining a microscopic image of the titanium alloy ingot, dividing it into blocks with preset side lengths, determining the grayscale level and principal component vector of each grain, calculating the phase structure attribution coefficient, combining electron probe analysis with component analysis, evaluating the uniformity of the phase structure and components, and comprehensively determining the composition uniformity.

Benefits of technology

The comprehensiveness, reliability and accuracy of the microscopic image composition uniformity detection of titanium alloy ingots have been improved, and the composition uniformity of the samples can be reflected more accurately.

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Abstract

The present invention relates to the technical field of image data processing, and more particularly to a method for detecting composition uniformity based on microscopic images of titanium alloy ingots, comprising the steps of obtaining a sample image, determining the grayscale level of each grain based on the number and grayscale value of pixels in each grain in the sample image, obtaining the principal component vectors of the grains, determining the phase structure attribution coefficient of the grains based on the number and modulus of the principal component vectors of the grains, the grayscale level and area of ​​the grains, further determining each phase structure grain in the sample image, determining the phase structure uniformity of the sample image based on the number of grains of each structural phase, obtaining the component uniformity of the sample image using the same method as for the phase structure uniformity, and determining the comprehensive uniformity of the sample image based on the component uniformity and phase structure uniformity of the sample image. The present invention combines the sample composition and grain morphology to comprehensively evaluate the composition uniformity of the sample, thereby improving the reliability of the sample composition uniformity detection.
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