Mixed crystal degree automatic measurement and fine classification method for steel crystal grains, and system thereof

An automatic measurement and fine classification technology, applied in particle size analysis, measuring devices, particle and sedimentation analysis, etc., can solve the problems of uneven distribution of steel grain size, inability to perform quantitative characterization, unevenness, etc.

Inactive Publication Date: 2015-09-02
JIANGSU UNIV
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Problems solved by technology

[0003] At present, since the existing quantitative metallographic analysis methods are not involved in the quantitative characterization and classification of the full-form grain size and mixed crystallinity of all steel products, the composition, process, structure and performance of new steel research and development At the time of control, this work is still in the preliminary exploration stage, and can only b

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  • Mixed crystal degree automatic measurement and fine classification method for steel crystal grains, and system thereof
  • Mixed crystal degree automatic measurement and fine classification method for steel crystal grains, and system thereof
  • Mixed crystal degree automatic measurement and fine classification method for steel crystal grains, and system thereof

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Embodiment 1

[0104] Use the image acquisition device to obtain the original image of the grain to be tested. The hardware of the image acquisition device is as follows: figure 2 As shown: it includes a steel sample 1, a professional metallographic microscope 2, a camera 3, a computer 4 and a printer 5, and the computer 4 is attached with an image acquisition card.

[0105] The specific steps of image acquisition are to use the professional metallographic microscope 2 to adjust the image to a suitable focal length, and use the camera 3 to take pictures and store the image in the computer 4 when the original image of the steel grain to be tested is the clearest In the acquisition card, the original image of the steel sample 1 steel grain to be measured (such as image 3 shown), followed by subsequent image preprocessing.

[0106] The image preprocessing process includes: median filter denoising, binary segmentation, grain missing boundary repair and grain hole filling.

[0107] The proces...

Embodiment 2

[0171] like Figure 8 The original image shown is the metallographic structure and grain image of steel sample 2. The processing process of the present invention is as follows: firstly, the target image is subjected to median filter denoising and an improved local adaptive threshold segmentation algorithm is used to perform binary segmentation processing, and the image after median filter denoising and binary segmentation is as follows: Figure 9 As shown; and then use the new modified watershed segmentation algorithm based on extreme corrosion and the improved seed filling algorithm to repair grain missing boundaries and fill intragranular holes. The image after defect repair is as follows Figure 10 Shown; set the scale and calibrate the area of ​​each grain, the image after area calibration is as follows Figure 11 Shown; Measure and calculate characteristic parameters such as grain area, grain size, grain mixed crystal degree GME; Completed the automatic measurement and f...

Embodiment 3

[0173] like Figure 13 The original image shown is the metallographic structure and grain image of steel sample 3. The processing process of the present invention is as follows: firstly, the target image is subjected to median filter denoising and an improved local adaptive threshold segmentation algorithm is used to perform binary segmentation processing, and the image after median filter denoising and binary segmentation is as follows: Figure 14 As shown; and then use the new modified watershed segmentation algorithm based on extreme corrosion and the improved seed filling algorithm to repair grain missing boundaries and fill intragranular holes. The image after defect repair is as follows Figure 15 Shown; set the scale and calibrate the area of ​​each grain, the image after area calibration is as follows Figure 16 Shown; Measure and calculate characteristic parameters such as grain area, grain size, grain mixed crystal degree GME; Completed the automatic measurement and...

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Abstract

The invention belongs to the analysis field of quantitative metallography on all-form crystal grains in a steel material microstructure and particularly relates to an automatic measurement and fine classification method for steel crystal grains, and a system thereof. According to the method, an image acquisition device acquires the original images of to-be-measured crystal grains of the steel material firstly, and then the original images are pre-processed by an image pre-processing module. The pre-processed images are subjected to the region labeling treatment by an automatic measurement module, and then the images of to-be-measured crystal grains can be obtained. After that, the geometry characteristic parameters of the images of to-be-measured crystal grains are extracted, and then the characteristic morphological parameters of target crystal grains are measured through the random field area algorithm. The area of crystal grains is obtained, and then the grain size of crystal grains and the mixed crystal degree (GME) of crystal grains can be figured out. The mixed crystal degree (GME) of crystal grains is automatically classified by an automatic classification module according to a most suitable threshold. In this way, the blank in measuring and classifying the mixed crystal degree of steel crystal grains in the prior art can be filled up. Meanwhile, the characterization precision of the images of steel crystal grains is up to plus/minus 0.001 [mu]m. Therefore, by adopting the above method and the above system, the characterization precision of the images of steel crystal grains is highest during the steel metallographic structure analysis process.

Description

technical field [0001] The invention relates to the field of quantitative metallographic analysis of steel material microstructure full-morphological grains, in particular to an automatic measurement and fine classification method and system for steel grain mixed crystals. Background technique [0002] With the rapid development of iron and steel material science and technology, the research and development of various steel materials has gradually been established on the basis of the quantitative relationship between composition, structure and performance. Method, through the quantitative analysis of the metallographic structure of various steel materials, especially the grain size and mixed crystal degree, the quantitative relationship between the microstructure and macroscopic properties was established. In order to ascertain the influence law of the grain size and distribution of all-form grains in steel on the strength / toughness of steel, especially the relevant influenc...

Claims

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Application Information

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IPC IPC(8): G01N15/00G01N15/02G06K9/62
Inventor 李新城唐永春朱伟兴陈轶王晓莉孙昀杰杨骐佑齐超
Owner JIANGSU UNIV
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