High-throughput digital full-field metallographic in-situ statistic characterization analyzer and analysis method

Abstract

The invention belongs to the technical field of material properties characterization, and particularly relates to a high-throughput digital full-field metallographic in-situ statistic characterization analyzer and analysis method. The analyzer comprises a high-throughput automatic sampling scanning system, a digital signal processing system and an intelligent analysis system, wherein the high-throughput automatic sampling scanning system comprises a sample table (1), an X-axis guiderail (2), a Y-axis guiderail (3) and a Z-axis guiderail (4); the digital signal processing system comprises a metallographic microscope (5), a CCD digital camera (6), an interface (7), an image processing device (8) and a lighting source (12). The analyzer is capable of realizing high-throughput data acquisition through obtaining a large amount of original digital signals of metallographic structures of samples in a large scale range (cm2 level), realizing the automatic identification, rating and evaluation of various metallographic structures through statistically analyzing a large amount of original digital signals and realizing the positioning of the metallographic structures on original positions through precise point-to-point corresponding of original digital signals and the surface of the samples.

Description

technical field [0001] The invention belongs to the technical field of performance characterization of metal materials, and in particular relates to a high-throughput digital full-field metallographic in-situ statistical characterization analyzer and an analysis method. Background technique [0002] The chemical composition of metal materials (steel, copper, aluminum, nickel and other alloys) and the physical and chemical states of various components inside the alloy are called metallographic structures. The structure of the material directly affects its physical and mechanical properties. The research and improvement of the chemical composition, heat treatment process, and cold and hot processing process essentially improve the hardness, toughness, wear resistance and other properties of the material by changing the internal structure. [0003] Metallographic structure analysis is one of the commonly used characterization methods in material structure analysis, which is div...

AI Technical Summary

Problems solved by technology

Although the macroscopic inspection can characterize the obvious segregation, defects and other structures in a large range of materials, it cannot characterize the tiny organizational structure; although the microscopic inspection can characterize the intrinsic properties of some specific areas, due to the limitation of the field of view of the micro area (general observation The diameter of the field of view is about 2mm to 100μm), and the artificial selection of the field of view is often subjective, random and accidental. The field of view that can be observed is limited, and it is easy to miss defective parts, lacking a comprehensive understanding of the overall material The reproducibility and accuracy are not high, and the microstructure in the metal material is not evenly distributed, so the determination of any parameter cannot only rely on the human eye to measure one or several fields of view under the microscope, and a large number of In order to ensure the reliability of the measurement results, there are still doubts about its statistical representativeness.

In addition, this traditional manual determination is not only poor in consistency, but also slow in speed and heavy in workload, which affects the correct characterization of sample performance.

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