Method for rapidly measuring and finely classifying full-form crystal grains of steel material
A technology of fine classification and grain, which is applied in the direction of measuring device, particle size analysis, particle and sedimentation analysis, etc. It can solve the problems of low accuracy of measurement results, inability to classify particle size, and not to mention the classification of grain shape.
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Embodiment 1
[0058] Use the image acquisition system to obtain the original image of the steel and metal phase weaving. The hardware of the image acquisition system is as follows: figure 2 Shown: including steel sample 1, professional microscope 2, camera (CCD) 3, computer 4, printer 5, computer 4 is inserted with an image acquisition card, the specific steps of image acquisition are to use the microscope to adjust the image to a suitable focal length, and then When the image is clearest, it will be captured and stored in the image acquisition card (original image), and then subsequent graphics processing can be performed.
[0059] The original image of this embodiment is as image 3 shown. right first image 3 The original image of the target image is denoised by conventional morphological reconstruction filtering. In order to further process the original image into a clear image with a lot of useful information, it is necessary to use the combination of conventional top-hat-bottom-ha...
Embodiment 2
[0127] In view of the fact that ultra-fine grain steel is a new type of steel that has been widely used in recent years, its main feature is that its metallographic structure is mostly extremely fine grains, and its grain size is usually about 5 microns. The original metallographic image of grain steel is as Figure 18 shown. Depend on Figure 18 It can be seen that the grains are fine, the average grain size is about 1 / 4 of that of Example 1, and there are many strip-shaped, thick needle-shaped, sharp needle-shaped grains, which can only be relied on in the previous microstructure analysis. Professionals perform measurement classification in a manual mode with low precision. Now use the present invention to measure and classify its crystal grains. First, the improved local adaptive threshold segmentation method is used for binary segmentation, and the effect is as follows: Figure 19 shown; and then use the new modified watershed segmentation algorithm based on limit corr...
Embodiment 3
[0134] Take the original image of conventional steel with a grain size of about 20 microns, which is widely used in the machinery industry, such as Figure 26 shown. Depend on Figure 26 Visible, its crystal grain is very thick, and average particle size is about 5 times of embodiment 2. Now use the present invention to measure and classify its crystal grains. First, the improved local adaptive threshold segmentation method is used for binary segmentation, and the effect is as follows: Figure 27 shown; and then use the new modified watershed segmentation algorithm based on limit corrosion to Figure 27 Boundary restoration of the binary image; the improved seed filling algorithm is used to fill the intragranular pores, and the processing effect is as follows Figure 28 As shown; set the scale and calibrate the area of each grain, measure and calculate the grain morphological characteristic parameters such as grain area, perimeter, aspect ratio, grain size, circularity, ...
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