CN110933401A - Automatic monitoring method in selective laser melting molding equipment - Google Patents
Automatic monitoring method in selective laser melting molding equipment Download PDFInfo
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- CN110933401A CN110933401A CN201911188363.1A CN201911188363A CN110933401A CN 110933401 A CN110933401 A CN 110933401A CN 201911188363 A CN201911188363 A CN 201911188363A CN 110933401 A CN110933401 A CN 110933401A
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Abstract
An automatic monitoring method in selective laser melting molding equipment comprises the following steps: s1: installing a camera in the molding cavity, so that a lens of the camera is aligned to the working plane; s2: the laser outputs laser, and a positioning image is scanned on a working plane; s3: the camera acquires a positioning image to obtain a shot image, and the camera uploads image data of the shot image to the data processing module; s5: the data processing module establishes a mapping relationship between the positioning image and the shot image through an image correction algorithm. The posture correction and illumination correction flow of the camera in the later period is simplified. The correction process is automatic unattended operation. The number of the cameras can be flexibly increased or decreased temporarily according to the requirements, and the limitation of the windowing position of the cavity is avoided.
Description
Technical Field
The invention relates to the field of additive manufacturing, in particular to an automatic monitoring method in selective laser melting molding equipment.
Background
The prior art scheme is through opening up the window on the shaping chamber, installs the industrial level camera outside the cavity and through this window alignment work plane. The resulting drawbacks include:
install the camera outside the shaping chamber, need open up the window on the shaping chamber, increase the processing degree of difficulty and cost to the shaping chamber that needs gas seal. Which is disadvantageous to the miniaturization of the device.
The camera is outside the molding cavity, and the working plane distance that needs to shoot is far away, needs the long focus camera, requires to improve to the camera, leads to the camera volume increase, the cost increase. This is disadvantageous in the miniaturization of the apparatus.
For scenes needing multi-angle shooting, the contradiction of installing the camera outside the forming cavity is more excited.
Adopt above-mentioned camera to monitor discernment and need the machining of high accuracy and install to cooperate, increase the processing and the installation degree of difficulty, simultaneously, in case mechanical structure appears the skew in the use, will destroy the discernment precision. Meanwhile, the camera is used for monitoring, an automatic identification monitoring function does not exist at present, after the camera is started, the working platform in the cavity cannot be automatically corrected, and the abnormity of the working plane is difficult to accurately judge by manual experience. Therefore, it is desirable to provide an automated monitoring method within a laser selective melting and forming apparatus.
Disclosure of Invention
Aiming at the defects of the prior art, the invention provides an automatic monitoring method in selective laser melting molding equipment, which has the following specific technical scheme:
an automatic monitoring method in selective laser melting molding equipment is characterized in that: the method comprises the following steps:
s1: installing a camera in the molding cavity, so that a lens of the camera is aligned to the working plane;
s2: the laser outputs laser, and a positioning image is scanned on a working plane;
s3: the camera acquires a positioning image to obtain a shot image, and the camera uploads image data of the shot image to the data processing module;
s4: the data processing module establishes a mapping relation between the positioning image and the shot image through an image correction algorithm;
s5: setting a standard image in a database, comparing the shot image with the standard image by a data processing module, judging whether an abnormal point exists between the shot image and the standard image, if so, entering S6, otherwise, entering S7;
s6: the data processing module corrects the shot image, geometrically corrects the abnormal points on the shot image to obtain corresponding coordinates on the positioning image, and the step is S7;
s7: and the data processing module is used for carrying out illumination correction on the shot image.
Further: the S4 includes the following steps:
s41: setting a first plane coordinate system on a working plane, defining the coordinates on the working plane as (x, y), the upper left corner as (-1, 1), the upper right corner as (1, 1), the lower left corner as (-1, -1), the lower right corner as (1, -1), and the center as (0, 0);
s42: setting a second plane coordinate system on the shot picture, defining the coordinates in the shot picture as (i, j), the upper left corner as (-1, 1), the upper right corner as (1, 1), the lower left corner as (-1, -1), the lower right corner as (1, -1), and the center as (0, 0), -1< i, j < 1;
s43: establishing a mapping relation between the first plane coordinate system and the second plane coordinate system, wherein the mapping relation is as follows:
y(i，j)＝ai2+bi+cj2+dj+e
x(i，j)＝fi2+gi+hj2+kj+l
calculating the point coordinates of the actual working plane through the point coordinates of the shot picture:
working plane coordinates a ═ a (x, y);
shooting picture coordinates B ═ B (i, j);
A＝F(B)＝Fabcdefghkl(B)；
s44: setting 441 marks on the working plane, wherein the 441 marks are marked with A0～A441；
The data processing module identifies coordinates B of 441 marks in the captured image0～B441B0～B441And establishing a corresponding relationship An＝Fn(Bn)。
Further: the S44 includes the following steps:
s441: setting 441 marks on the working plane, wherein the 441 marks are marked with A0～A441The mark is a cross-shaped structure, and the length of the transverse line and the vertical line of the mark is 2 d;
s442: the data module binarizes all pixels by using a red component for the shot image, wherein the red component is black when being more than 100, and is white when not;
s443: randomly taking a black point, traversing the black points { C } communicated with the black point, and finding a point C in the black point C, wherein the sum of the distances from the point C to all the points { C } is the minimum, so that the black point C is considered as a mark point B;
s444: find the closest (-1, 1) point in { B }, set it to B-1，1Then find the nearest B-1，1Two points of (1), the value of the i component is greater and is marked as B-0.9，1And the component of i is small and is marked as B-1，0.9. Recursion in turn, resuming with the above method, through B-0.9,1And B-1,0.9Find B-0.8,1B-0.9,0.9B-1,0.8This continues until all { B } s are found to correspond to point (i, j).
Further: the illumination correction comprises the following steps:
s71: the data processing module extracts a shot image;
s72: the data processing module calculates the difference value of the shot image and the standard illumination image according to pixels and corrects the brightness gradient introduced by illumination.
Further: the camera is a CCD camera, the visual angle is 45 degrees, the resolution ratio is more than 1000 multiplied by 1000 pixels, and the size of the camera body is less than 50mm multiplied by 20 mm.
Further: s2 is that the laser draws 441 cross marks on the working plane by laser circulation.
Further: the S6 includes the following steps:
s61: for any one BnAnd (3) obtaining the nearest 5 marked coordinate points, jointly solving according to a multivariate linear equation system to obtain the values of a, b, c, d, e, F, g, h, k and l to obtain FnThe expression of (1);
s62: for any point B (i, j) on the shot image, the nearest 5 points B are obtained1～B5Obtaining 5 transformation formulas, and calculating 5 converted working plane coordinates A1～A5；
To working plane coordinate A1～A5According to their respective 5Distance S from point to B (i, j)1～S5And weighting and averaging to obtain A (x, y), and finishing the correction.
Further: the generation process of the standard illumination image comprises the following steps:
s1: a powder paving system of the equipment completes one-time powder paving to obtain a work plane after the powder paving;
s2: the camera is used for shooting, the data processing module is used for denoising the shot image in a Gaussian blur mode, and the processed image is stored in a database as a standard illumination image.
The invention has the beneficial effects that: first, in terms of physical structure, in the case of implementing camera installation and calibration. And windows do not need to be opened, so that the processing requirement of the cavity is reduced, and the processing cost is reduced.
And secondly, the requirements on the camera are reduced, so that the cost is reduced, the size of the camera is reduced, and the camera installation and correction flow is simplified.
Thirdly, the posture correction and illumination correction flow of the camera in the later period is simplified. The correction process is automatic unattended operation. The number of the cameras can be flexibly increased or decreased temporarily according to the requirements, and the limitation of the windowing position of the cavity is avoided.
Drawings
FIG. 1 is a schematic structural view of the present invention;
FIG. 2 is a flow chart of the operation of the present invention.
Detailed Description
The following detailed description of the preferred embodiments of the present invention, taken in conjunction with the accompanying drawings, will make the advantages and features of the invention easier to understand by those skilled in the art, and thus will clearly and clearly define the scope of the invention.
As shown in fig. 1 and 2: an automatic monitoring method in selective laser melting molding equipment comprises the following steps:
s1: the camera is installed in the molding cavity, so that the lens of the camera is aligned to the working plane, in the embodiment, the camera is a CCD camera, the visual angle is 45 degrees, the resolution ratio is more than 1000 multiplied by 1000 pixels, and the size of the camera body is less than 50mm multiplied by 20 mm.
S2: outputting laser by a laser device, and scanning a positioning image on a working plane, wherein the specific process is that the laser device circularly draws 441 cross marks on the working plane through the laser;
s3: the camera acquires a positioning image to obtain a shot image, and the camera uploads image data of the shot image to the data processing module;
s4: the data processing module establishes a mapping relation between the positioning image and the shot image through an image correction algorithm;
in this embodiment, the S4 includes the following steps:
s41: setting a first plane coordinate system on a working plane, defining the coordinates on the working plane as (x, y), the upper left corner as (-1, 1), the upper right corner as (1, 1), the lower left corner as (-1, -1), the lower right corner as (1, -1), and the center as (0, 0);
s42: setting a second plane coordinate system on the shot picture, defining the coordinates in the shot picture as (i, j), the upper left corner as (-1, 1), the upper right corner as (1, 1), the lower left corner as (-1, -1), the lower right corner as (1, -1), and the center as (0, 0), -1< i, j < 1;
s43: establishing a mapping relation between the first plane coordinate system and the second plane coordinate system, wherein the mapping relation is as follows:
y(i，j)＝ai2+bi+cj2+dj+e
x(i，j)＝fi2+gi+hj2+kj+l
calculating the point coordinates of the actual working plane through the point coordinates of the shot picture:
working plane coordinates a ═ a (x, y);
shooting picture coordinates B ═ B (i, j);
A＝F(B)＝Fabcdefghkl(B)；
s44: setting 441 marks on the working plane, wherein the 441 marks are marked with A0～A441；
The data processing module identifies coordinates B of 441 marks in the captured image0～B441And establishing a corresponding relationship An＝Fn(Bn)。
Wherein the S44 includes the following steps:
s441: setting 441 marks on the working plane, wherein the 441 marks are marked with A0～A441The mark is a cross-shaped structure, and the length of the transverse line and the vertical line of the mark is 2 d;
s442: the data module binarizes all pixels by using a red component for the shot image, wherein the red component is black when being more than 100, and is white when not;
s443: randomly taking a black point, traversing the black points { C } communicated with the black point, and finding a point C in the black point C, wherein the sum of the distances from the point C to all the points { C } is the minimum, so that the black point C is considered as a mark point B;
s444: find the closest (-1, 1) point in { B }, set it to B-1，1Then find the nearest B-1，1Two points of (1), the value of the i component is greater and is marked as B-0.9，1And the component of i is small and is marked as B-1，0.9. Recursion in turn, resuming with the above method, through B-0.9,1And B-1,0.9Find B-0.8,1B-0.9,0.9B-1,0.8This continues until all { B } s are found to correspond to point (i, j).
S5: setting a standard image in a database, comparing the shot image with the standard image by a data processing module, judging whether an abnormal point exists between the shot image and the standard image, if so, entering S6, otherwise, entering S7;
s6: the data processing module corrects the shot image, geometrically corrects the abnormal points on the shot image to obtain corresponding coordinates on the positioning image, and the step is S7;
in this example, the S6 includes the following steps:
s61: for any one BnAnd (3) obtaining the nearest 5 marked coordinate points, jointly solving according to a multivariate linear equation system to obtain the values of a, b, c, d, e, F, g, h, k and l to obtain FnThe expression of (1);
s62: for any point B (i, j) on the shot image, the nearest 5 points B are obtained1～B5To obtain 5 variantsConverting formula to calculate 5 converted working plane coordinates A1～A5；
To working plane coordinate A1～A5According to the distance S from the corresponding 5 points to B (i, j)1～S5And weighting and averaging to obtain A (x, y), and finishing the correction.
S7: and the data processing module is used for carrying out illumination correction on the shot image.
The illumination correction comprises the following steps:
s71: the data processing module extracts a shot image;
s72: the data processing module calculates the difference value of the shot image and the standard illumination image according to pixels and corrects the brightness gradient introduced by illumination.
The generation process of the standard illumination image in S72 is:
s1: a powder paving system of the equipment completes one-time powder paving to obtain a work plane after the powder paving;
s2: the camera is used for shooting, the data processing module is used for denoising the shot image in a Gaussian blur mode, and the processed image is stored in a database as a standard illumination image.
Claims (8)
1. An automatic monitoring method in selective laser melting molding equipment is characterized in that: the method comprises the following steps:
s1: installing a camera in the molding cavity, so that a lens of the camera is aligned to the working plane;
s2: the laser outputs laser, and a positioning image is scanned on a working plane;
s3: the camera acquires a positioning image to obtain a shot image, and the camera uploads image data of the shot image to the data processing module;
s4: the data processing module establishes a mapping relation between the positioning image and the shot image through an image correction algorithm;
s5: setting a standard image in a database, comparing the shot image with the standard image by a data processing module, judging whether an abnormal point exists between the shot image and the standard image, if so, entering S6, otherwise, entering S7;
s6: the data processing module corrects the shot image, geometrically corrects the abnormal points on the shot image to obtain corresponding coordinates on the positioning image, and the step is S7;
s7: and the data processing module is used for carrying out illumination correction on the shot image.
2. The automated monitoring method in a selective laser melting molding apparatus according to claim 1, wherein:
the S4 includes the following steps:
s41: setting a first plane coordinate system on a working plane, defining the coordinates on the working plane as (x, y), the upper left corner as (-1, 1), the upper right corner as (1, 1), the lower left corner as (-1, -1), the lower right corner as (1, -1), and the center as (0, 0);
s42: setting a second plane coordinate system on the shot picture, defining the coordinates in the shot picture as (i, j), the upper left corner as (-1, 1), the upper right corner as (1, 1), the lower left corner as (-1, -1), the lower right corner as (1, -1), and the center as (0, 0), -1< i, j < 1;
s43: establishing a mapping relation between the first plane coordinate system and the second plane coordinate system, wherein the mapping relation is as follows:
y(i，j)＝ai2+bi+cj2+dj+e
x(i，j)＝fi2+gi+hj2+kj+l
calculating the point coordinates of the actual working plane through the point coordinates of the shot picture:
working plane coordinates a ═ a (x, y);
shooting picture coordinates B ═ B (i, j);
A＝F(B)＝Fabcdefghkl(B)；
s44: setting 441 marks on the working plane, wherein the 441 marks are marked with A0～A441；
The data processing module identifies coordinates B of 441 marks in the captured image0～B441B0～B441And establishing a corresponding relationship An＝Fn(Bn)。
3. The automated monitoring method in a selective laser melting molding apparatus according to claim 1, wherein:
the S44 includes the following steps:
s441: setting 441 marks on the working plane, wherein the 441 marks are marked with A0～A441The mark is a cross-shaped structure, and the length of the transverse line and the vertical line of the mark is 2 d;
s442: the data module binarizes all pixels by using a red component for the shot image, wherein the red component is black when being more than 100, and is white when not;
s443: randomly taking a black point, traversing the black points { C } communicated with the black point, finding a black point C in the black point C, and determining the black point C as a mark point B if the sum of the distances from the black point C to all the points { C } is minimum;
s444: find the closest (-1, 1) point in { B }, set it to B-1，1Then find the nearest B-1，1Two points of (1), the value of the i component is greater and is marked as B-0.9，1And the component of i is small and is marked as B-1，0.9. Recursion in turn, resuming with the above method, through B-0.9,1And B-1,0.9Find B-0.8,1B-0.9,0.9B-1,0.8This continues until all { B } s are found to correspond to point (i, j).
4. The automated monitoring method in a selective laser melting molding apparatus according to claim 1, wherein:
the illumination correction comprises the following steps:
s71: the data processing module extracts a shot image;
s72: the data processing module calculates the difference value of the shot image and the standard illumination image according to pixels and corrects the brightness gradient introduced by illumination.
5. The automated monitoring method in a selective laser melting molding apparatus according to claim 1, wherein: the camera is a CCD camera, the visual angle is 45 degrees, the resolution ratio is more than 1000 multiplied by 1000 pixels, and the size of the camera body is less than 50mm multiplied by 20 mm.
6. The automated monitoring method in a selective laser melting molding apparatus according to claim 3, wherein: s2 is that the laser draws 441 cross marks on the working plane by laser circulation.
7. The automated monitoring method in a selective laser melting molding apparatus according to claim 1, wherein:
the S6 includes the following steps:
s61: for any one BnAnd (3) obtaining the nearest 5 marked coordinate points, jointly solving according to a multivariate linear equation system to obtain the values of a, b, c, d, e, F, g, h, k and l to obtain FnThe expression of (1);
s62: for any point B (i, j) on the shot image, 5 points B with the nearest distance are obtained1～B5Obtaining 5 transformation formulas, and calculating 5 converted working plane coordinates A1～A5；
To working plane coordinate A1～A5According to the distance S from the corresponding 5 points to B (i, j)1～S5S1～S5And weighting and averaging to obtain A (x, y), and finishing the correction.
8. The automated monitoring method in a selective laser melting molding apparatus according to claim 1, wherein:
the generation process of the standard illumination image comprises the following steps:
s1: a powder paving system of the equipment completes one-time powder paving to obtain a work plane after the powder paving;
s2: the camera is used for shooting, the data processing module is used for denoising the shot image in a Gaussian blur mode, and the processed image is stored in a database as a standard illumination image.
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Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106363171A (en) * | 2016-09-29 | 2017-02-01 | 中北大学 | Selective laser melting forming molten bath real-time monitoring device and monitoring method |
| CN206392865U (en) * | 2017-01-18 | 2017-08-11 | 张远明 | A kind of intelligent laser selective melting former |
| CN108580899A (en) * | 2018-07-17 | 2018-09-28 | 西安空天能源动力智能制造研究院有限公司 | A kind of off-axis monitoring device of the melt-processed process in selective laser and method |
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- 2019-11-28 CN CN201911188363.1A patent/CN110933401A/en active Pending
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106363171A (en) * | 2016-09-29 | 2017-02-01 | 中北大学 | Selective laser melting forming molten bath real-time monitoring device and monitoring method |
| CN206392865U (en) * | 2017-01-18 | 2017-08-11 | 张远明 | A kind of intelligent laser selective melting former |
| CN108580899A (en) * | 2018-07-17 | 2018-09-28 | 西安空天能源动力智能制造研究院有限公司 | A kind of off-axis monitoring device of the melt-processed process in selective laser and method |
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Application publication date: 20200327 |