CN114486878A - Method for collecting uranium oxide ceramic pellet microscopic images in batches - Google Patents
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- CN114486878A CN114486878A CN202011263959.6A CN202011263959A CN114486878A CN 114486878 A CN114486878 A CN 114486878A CN 202011263959 A CN202011263959 A CN 202011263959A CN 114486878 A CN114486878 A CN 114486878A
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Abstract
The invention discloses a method for collecting micro-images of uranium oxide ceramic pellets in batches, which comprises the following steps: step 1: placing and sampling; step 2: splicing and collecting low-power images; and step 3: calibrating a detection area; and 4, step 4: calculating an acquisition field of view; and 5: moving the acquisition field of view in sequence; step 6: focusing correction and automatic focusing; and 7: collecting and storing images; and 8: and (5) manually supplementing and collecting. The invention has the beneficial effects that: the method is used for batch acquisition of the pore structure and grain structure images of the uranium oxide fuel pellets of the nuclear fuel element, and is used for analysis and measurement of subsequent pore distribution and grain size. The automatic focusing device is suitable for continuous batch collection of a plurality of samples of any size after being embedded, the collection field spacing does not need to be manually calculated according to pellet samples of different sizes, and whole-course automatic focusing can be realized in the batch collection process of the plurality of samples without manual intervention. The batch collection efficiency is improved by more than 100%, and the automatic focusing success rate is improved by more than 100%.
Description
Technical Field
The invention belongs to the field of nuclear fuel manufacturing, and particularly relates to a method for collecting micro images of uranium oxide ceramic pellets in batches.
Background
In the manufacturing of the uranium oxide pellet of the nuclear fuel element, a quantitative metallographic analysis method is required to measure indexes representing microstructures such as material porosity, grain size, second phase content and the like so as to control the process and the product quality. To ensure that the measurement results are not affected by sample inhomogeneities, a large number of microscopic images are acquired in batches on the same test surface of the sample for analysis and statistics. In the mainstream software (Axiovision and Zen of Zeiss, Leica of Leica, germany, and Stream of Olympus, japan) with a batch acquisition function currently used for an automatic microscope, the existing batch acquisition method is that after an electric stage of the automatic microscope is manually moved to an acquisition starting point or a central point of an acquisition area, the automatic electric stage is controlled to move to a preset position for acquisition by setting the number of acquisition fields and the distance between the fields. Need manual positioning, and need calculate collection area size in advance, and do not revise to sample surface unevenness in the acquisition process, therefore operating procedure is loaded down with trivial details, and is poor to not unidimensional sample adaptability, and is poor to big sample or gather the adaptability on a large scale, influences collection efficiency and collection quality in batches, and the process needs artificial intervention, and degree of automation is not enough, is unfavorable for the radiation environment and uses.
Disclosure of Invention
The invention aims to provide a method for collecting uranium oxide ceramic pellet microscopic images in batches, which is suitable for automatically collecting large samples and large-scale microscopic images required by various uranium oxide ceramic pellet microscopic tissue analyses, can visually mark detection areas with any sizes, automatically calculates detection fields, and can automatically correct slight unevenness of sample surfaces in the collection process. Therefore, the operation steps are simplified, manual intervention and deviation are reduced, the collection efficiency and the collection quality are improved, and the irradiation risk in the test process is reduced.
The technical scheme of the invention is as follows: a uranium oxide ceramic pellet microscopic image batch acquisition method comprises the following steps:
step 1: placing and sampling;
step 2: splicing and collecting low-power images;
and step 3: calibrating a detection area;
and 4, step 4: calculating an acquisition field of view;
and 5: moving the acquisition field of view in sequence;
step 6: focusing correction and automatic focusing;
and 7: collecting and storing images;
and 8: and (5) manually supplementing and collecting.
The step 1 comprises the steps of placing the prepared mosaic sample in the center of an objective table, observing the mosaic sample through a microscopic image displayed in real time in an eyepiece or a computer, moving the sample to the center of a view field and keeping the sample horizontal and vertical.
The step 2 comprises the steps of setting an acquisition range in a computer program, starting acquisition, automatically controlling a microscope electric objective turret to be switched to a low-power objective by the program, calculating to obtain a single view field coverage range through calibration information and camera resolution, calculating to obtain each view field position required by covering the acquisition range according to at least 10% of each view field overlap, controlling a microscope electric objective table through the program to finish the acquisition of each view field image, and synthesizing a seamless low-power image covering the whole acquisition range by using an image splicing algorithm.
And 3, extracting the outline of the pellet sample by using an image segmentation algorithm to obtain the circumscribed outline of the pellet, and then obtaining the bounding box of the detection area by translating and zooming according to the requirement of the detection item on the detection area.
in the formula: wl: detection field of view pixel width, H, displayed on the low power imagel: detection field pixel height on the low power route, W: image pixel width, H: image pixel height, Sxh，Syh: x-axis and Y-axis calibration values, S, at image detection magnificationxl，Syl: x-axis and Y-axis calibration of the low power image.
And 5, after the collection of the view field is confirmed, the automatic collection of the view field can be started, the program collects the images in sequence according to the drawing sequence of the bounding box, the objective lens is switched to a preset collection multiplying power, each view field is traversed, the pixel coordinate in the low-power image is converted into the physical coordinate of the microscope objective table according to the formula (2), and the objective table is controlled to move to a corresponding position.
In the formula: xs，Ys: physical coordinates of the stage at the corresponding position, Xi，Yi: coordinates of pixel points of any point in the image, Sx，Sy: calibration values of an X axis and a Y axis under a current magnification of an image, W: image pixel width, H: the image pixel height.
The step 6 comprises adopting a tilt compensation method, utilizing the nearly linear relation of sample tilt, calculating the focus position of the next field according to the formula (3) by using the focus height difference of the two fields before the collection of the fields, and then controlling the microscope to automatically move to the focus position for automatic focusing to reduce the actual focusing distance
Zi＝Zi-1+Zi-1-Zi-2(i＞2,Xi＝Xi-1＝Xi-2Or Yi＝Yi-1＝Yi-2) (3)
In the formula: xi，Yi，Zi: the ith view field X-axis and Y-axisThe coordinate position of the Z-axis.
And 7, automatically storing and collecting all the collected photos into corresponding folders according to the bounding boxes and the collection multiplying power.
And the step 8 comprises the steps of viewing all the collected photos through a program after all the field-of-view collection is finished, and directly jumping to the original collection position and re-focusing and supplementing collection to ensure the collection quality of all the photos because the original collection position is recorded in the photos, if the photos have the problem of focusing contamination.
The invention has the beneficial effects that: the method is used for batch acquisition of the pore structure and grain structure images of the uranium oxide fuel pellets of the nuclear fuel element, and is used for analysis and measurement of subsequent pore distribution and grain size. The automatic focusing device is suitable for continuous batch collection of a plurality of samples of any size after being embedded, the collection field spacing does not need to be manually calculated according to pellet samples of different sizes, and whole-course automatic focusing can be realized in the batch collection process of the plurality of samples without manual intervention. The batch collection efficiency is improved by more than 100%, and the automatic focusing success rate is improved by more than 100%.
Drawings
FIG. 1 is a flow chart of a method for collecting micro images of uranium oxide ceramic pellets in batches, which is provided by the invention;
FIG. 2 is a schematic view of macroscopic image acquisition of a sample;
fig. 3 is a schematic view of acquisition field generation.
In the figure: the test method comprises the following steps of 1 objective table, 2 mosaic test sample, 3 pellet test samples, 4 low-power view field coverage, 5 pellet test samples, 6 detection area bounding frames and 7 detection view field preview frames.
Detailed Description
The invention is described in further detail below with reference to the figures and the embodiments.
The automatic metallographic microscope used in the invention is a microscope which is at least provided with an electric objective table and an electric objective turret and can be connected with a computer and adopts a reflection light source. The motion of the electric component can be controlled by a computer program, and the real-time position of the electric component can be obtained by the computer program. The microscopic image can be input into a computer through a camera for real-time display and photographic recording. For the purposes of the present invention, a low power objective lens (typically 1.25X) and a high power objective lens for the inspection item are also required.
The nuclear fuel element uranium oxide pellet of the invention includes but is not limited to UO2Pellet and gadolinium-containing UO2Pellet, U-PuO2Ceramic fuel pellets such as mixed fuel pellets generally have low to moderate radioactivity, and are embedded by using materials such as sulfur and the like which are convenient to recover before batch microscopic image acquisition, and then a required test surface of a test sample is obtained by using modes such as metallographic sample preparation, etching and the like.
With UO2Microstructure examination of pellets is an example, and a batch collection procedure is shown in fig. 1.
A uranium oxide ceramic pellet microscopic image batch acquisition method comprises the following steps:
step 1: placing the sample
The prepared embedded sample 2 is placed in the center of the objective table 1, if an upright metallographic microscope is adopted, the sample needs to be placed in the center of the objective table after the upper surface and the lower surface of the sample are parallel through a flattening device. And (4) observing a microscopic image displayed in real time through an ocular lens or a computer, moving the sample to the central position of the visual field and keeping the sample horizontal and vertical.
And 2, step: tiled acquisition low power image
The acquisition range is set in the computer program, all pellet samples 3 to be detected are covered, acquisition is started, and the program automatically controls the microscope electric objective turret to be switched to the low power objective (1.25X). And calculating to obtain a single view field coverage range 4 through calibration information and camera resolution, and then calculating to obtain each view field position required for covering the acquisition range according to at least 10% of each view field overlap. The electric objective table of the microscope is controlled by a program to complete the acquisition of each view field image, and the images are synthesized into a seamless low-power image covering the whole acquisition range by using an image splicing algorithm.
And step 3: calibrating a detection region
A typical low-magnification image is schematically shown in fig. 2, and includes two pellet samples 5, the outline of the pellet sample is extracted by using an image segmentation algorithm to obtain the circumscribed outline of the pellet, and then the bounding box 6 of the detection area is obtained by translating and zooming according to the requirement of the detection item on the detection area.
And 4, step 4: calculating the acquisition field of view
The bounding box of the calibration detection area can be drawn manually on the macroscopic image by using mouse dragging. Software calculates each view field position according to the number of horizontal and vertical view fields required by a preset detection item and the principle of uniform distribution in a bounding box, calculates the equivalent size of each view field on a low-magnification image according to the detection magnification and corresponding calibration information required by the detection item and a formula (1), and finally draws a preview box 7 of each view field range on the low-magnification image, so that inspectors can adjust the detection area and the number of view fields according to the position, the coverage rate and the like of the preview box, and the representativeness of the collected view fields is ensured. Multiple groups of acquisition fields of view under different magnifications can be generated in the same bounding box, and the typical application is used for UO2The porosity distribution of the pellets was checked to ensure that all sizes of porosity could be measured.
In the formula: wl: detection field of view pixel width, H, displayed on the low power imagel: detection field pixel height on the low power route, W: image pixel width, H: image pixel height, Sxh，Syh: x-axis and Y-axis calibration values, S, at image detection magnificationxl，Syl: x-axis and Y-axis calibration of the low power image.
And 5: sequentially moving acquisition field of view
After the collection field of view is confirmed, automatic collection of the field of view can be started, the program collects the images in sequence according to the drawing sequence of the bounding box, the objective lens is switched to a preset collection multiplying power, each field of view is traversed, the pixel coordinates in the low-power images are converted into the physical coordinates of the microscope objective table according to the formula 2, and the objective table is controlled to move to a corresponding position.
In the formula: xs, Ys: physical coordinates of the stage at the corresponding position, Xi, Yi: pixel point coordinates of any point in the image, Sx, Sy: calibration values of an X axis and a Y axis under a current magnification of an image, W: image pixel width, H: the image pixel height.
The first field of each group of collection fields uses artificial focusing to determine the position of the initial focal plane, and the rest fields focus the microscopic image clearly through automatic focusing to complete image collection and storage without manual intervention. During the acquisition process, the field of view currently being acquired can be displayed in real time by using the low-power image and the field of view preview box in fig. 3.
Step 6: focus correction and autofocus
Because the surfaces of the samples are not on the same focal plane inevitably in the embedding and sample preparation processes and the microscope, the focusing position of each field can deviate to a certain extent, the efficiency of automatic focusing is influenced, and even the automatic focusing cannot be realized. Therefore, the inclination compensation method is designed, the focusing position of the latter field can be calculated by using the focusing height difference of the two fields before the collection field according to the formula (3) by utilizing the nearly linear relation of the sample inclination, and then the microscope is controlled to automatically move to the focusing position for automatic focusing, so that the actual focusing distance is reduced.
Zi＝Zi-1+Zi-1-Zi-2(i＞2,Xi＝Xi-1＝Xi-2Or Yi＝Yi-1＝Yi-2) (3)
In the formula: xi，Yi，Zi: and the coordinate positions of the X axis, the Y axis and the Z axis of the ith view field.
And 7: capturing and saving images
All the collected photos are automatically stored and collected into corresponding folders according to the bounding boxes and the collection multiplying power, and the work of analyzing, calculating, counting and the like of corresponding microstructure indexes can be carried out subsequently by adopting image analysis software.
And 8: artificially supplemented collection
After all the field of view collection is completed, all the collected photos can be checked through the program, and because the original collection position is recorded in the photos, if the photos have the problems of focusing contamination and the like, the photos can directly jump to the original collection position, and are focused again for additional collection, so that the collection quality of all the photos is ensured.
Claims (9)
1. A uranium oxide ceramic pellet microscopic image batch acquisition method is characterized by comprising the following steps:
step 1: placing and sampling;
step 2: splicing and collecting low-power images;
and step 3: calibrating a detection area;
and 4, step 4: calculating an acquisition field of view;
and 5: sequentially moving the acquisition field of view;
step 6: focusing correction and automatic focusing;
and 7: collecting and storing images;
and 8: and (5) manually supplementing and collecting.
2. A method for batch collection of uranium oxide ceramic pellet microscopic images according to claim 1, wherein: the step 1 comprises the steps of placing the prepared mosaic sample in the center of an objective table, observing the mosaic sample through a microscopic image displayed in real time in an eyepiece or a computer, moving the sample to the center of a view field and keeping the sample horizontal and vertical.
3. A method for batch collection of uranium oxide ceramic pellet microscopic images according to claim 1, wherein: the step 2 comprises the steps of setting an acquisition range in a computer program, starting acquisition, automatically controlling a microscope electric objective turret to be switched to a low-power objective by the program, calculating to obtain a single view field coverage range through calibration information and camera resolution, calculating to obtain each view field position required by covering the acquisition range according to at least 10% of each view field overlap, controlling a microscope electric objective table through the program to finish the acquisition of each view field image, and synthesizing a seamless low-power image covering the whole acquisition range by using an image splicing algorithm.
4. A method for collecting uranium oxide ceramic pellet microscopic images in batch according to claim 1, wherein the method comprises the following steps: and 3, extracting the outline of the pellet sample by using an image segmentation algorithm to obtain the circumscribed outline of the pellet, and then obtaining the bounding box of the detection area by translating and zooming according to the requirement of the detection item on the detection area.
5. A method for batch collection of uranium oxide ceramic pellet microscopic images according to claim 1, wherein: step 4 comprises manually drawing a bounding box for calibrating the detection area on the macroscopic image by using a mouse to drag, calculating the position of each field of view according to the number of transverse and longitudinal fields of view required by a preset detection item and the principle of uniform distribution in the bounding box, calculating the equivalent size of each field of view on the macroscopic image according to a formula (1) and the detection magnification and corresponding calibration information required by the detection item, finally drawing a preview box of each field of view range on the macroscopic image, adjusting the number of the detection area and the field of view according to the position and the coverage rate of the preview box to ensure the representativeness of the collection field of view, and generating a plurality of groups of collection fields of view under different magnifications in the same bounding box,
in the formula: wl: detection field of view pixel width, H, displayed on the low power imagel: detection field pixel height on the low power route, W: image pixel width, H: image pixel height, Sxh，Syh: x-axis and Y-axis calibration values, S, at image detection magnificationxl，Syl: x-axis and Y-axis calibration of the low power image.
6. A method for batch collection of uranium oxide ceramic pellet microscopic images according to claim 1, wherein: and 5, after confirming the collection of the view field, starting automatic collection of the view field, sequentially collecting the view field by a program according to the drawing sequence of the delimiting frame, switching the objective lens to a preset collection multiplying power, traversing each view field, converting pixel coordinates in the low-power image into physical coordinates of a microscope objective table according to a formula (2), and controlling the objective table to move to a corresponding position.
In the formula: xs，Ys: physical coordinates of the stage at the corresponding position, Xi，Yi: coordinates of pixel points of any point in the image, Sx，Sy: calibration values of an X axis and a Y axis under a current magnification of an image, W: image pixel width, H: the image pixel height.
7. A method for batch collection of uranium oxide ceramic pellet microscopic images according to claim 1, wherein: the step 6 comprises adopting a tilt compensation method, utilizing the nearly linear relation of sample tilt, calculating the focus position of the next field according to the formula (3) by using the focus height difference of the two fields before the collection of the fields, and then controlling the microscope to automatically move to the focus position for automatic focusing to reduce the actual focusing distance
Zi＝Zi-1+Zi-1-Zi-2(i＞2,Xi＝Xi-1＝Xi-2Or Yi＝Yi-1＝Yi-2) (3)
In the formula: xi，Yi，Zi: and the coordinate positions of the X axis, the Y axis and the Z axis of the ith view field.
8. A method for batch collection of uranium oxide ceramic pellet microscopic images according to claim 1, wherein: and 7, automatically storing and collecting all the collected photos into corresponding folders according to the bounding boxes and the collection multiplying power.
9. A method for batch collection of uranium oxide ceramic pellet microscopic images according to claim 1, wherein: and the step 8 comprises the steps of viewing all the collected photos through a program after all the field-of-view collection is finished, and directly jumping to the original collection position and re-focusing and supplementing collection to ensure the collection quality of all the photos because the original collection position is recorded in the photos, if the photos have the problem of focusing contamination.
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN117392242A (en) * | 2023-12-11 | 2024-01-12 | 中国电子产品可靠性与环境试验研究所（（工业和信息化部电子第五研究所）（中国赛宝实验室）） | Imaging system calibration method, device, computer equipment and storage medium |
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| CN1651905A (en) * | 2005-02-05 | 2005-08-10 | 石家庄钢铁股份有限公司 | Quantitative analyzing method for non-metal residue in steel |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117392242A (en) * | 2023-12-11 | 2024-01-12 | 中国电子产品可靠性与环境试验研究所（（工业和信息化部电子第五研究所）（中国赛宝实验室）） | Imaging system calibration method, device, computer equipment and storage medium |
| CN117392242B (en) * | 2023-12-11 | 2024-04-19 | 中国电子产品可靠性与环境试验研究所（（工业和信息化部电子第五研究所）（中国赛宝实验室）） | Imaging system calibration method, device, computer equipment and storage medium |
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