Metallographic detection method and system based on image recognition

Through the metallographic detection method based on image recognition, images are collected using high-resolution microscopes and industrial cameras, combined with intelligent algorithms and automated measurements, the problems of low efficiency and insufficient accuracy of traditional metallographic detection are solved, and efficient and accurate metallographic structure analysis is achieved.

CN120489956APending Publication Date: 2025-08-15SHAANXI TIANCHENG ADVANCED MATERIAL LAB CO LTD
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Patent Information

Application Number
CN202510767126.X
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-06-10
Publication Date
2025-08-15

AI Technical Summary

Technical Problem

Traditional metallographic detection methods are inefficient, limited accuracy, insufficient standardization, weak complex organizational analysis capabilities and strong environmental dependence, making it difficult to meet the needs of modern industry for high-precision and automated testing.

Method used

Metallographic detection method based on image recognition is adopted, images are collected through high-resolution optical microscope and industrial cameras, grain boundaries are extracted in combination with median filtering and adaptive binarization algorithms, and grain boundary recognition is used to assist grain boundary recognition to realize multi-parameter automated measurements and generate intelligent reports.

Benefits of technology

It significantly improves the efficiency and accuracy of metallographic tissue analysis, reduces dependence on professionals, and builds a high-precision and high-efficiency metallographic tissue detection system, suitable for aerospace and medical devices and other fields.

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Abstract

The invention discloses a metallographic detection method and system based on image recognition, and belongs to the technical field of metallographic detection. The detection method comprises the following steps: image acquisition and preprocessing: acquiring a metal metallographic image by an optical microscope, performing median filtering and denoising, and extracting a grain boundary by adaptive binarization; and field-of-view and scale calibration: selecting a corresponding scale according to the shooting magnification. The multi-parameter automatic measurement comprises grain size analysis, grain size rating, second phase analysis and intelligent report generation, a report is automatically generated based on a preset template and comprises an original image, a binary image, measurement data and a histogram, and report fonts and layout can be adjusted in real time through a visual control. According to the detection method disclosed by the invention, the efficiency, the precision and the reliability of metallographic structure analysis of the metal material are remarkably improved through the full-process design of image acquisition standardization, preprocessing intellectualization, data analysis automation and report generation templating.
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