CN107688028B - Laser additive manufacturing lap joint rate online monitoring method - Google Patents
Laser additive manufacturing lap joint rate online monitoring method Download PDFInfo
- Publication number
- CN107688028B CN107688028B CN201710669368.0A CN201710669368A CN107688028B CN 107688028 B CN107688028 B CN 107688028B CN 201710669368 A CN201710669368 A CN 201710669368A CN 107688028 B CN107688028 B CN 107688028B
- Authority
- CN
- China
- Prior art keywords
- laser
- image
- lap joint
- lap
- additive manufacturing
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 239000000654 additive Substances 0.000 title claims abstract description 45
- 230000000996 additive effect Effects 0.000 title claims abstract description 45
- 238000012544 monitoring process Methods 0.000 title claims abstract description 45
- 238000004519 manufacturing process Methods 0.000 title claims abstract description 38
- 238000000034 method Methods 0.000 title claims abstract description 30
- 238000012545 processing Methods 0.000 claims abstract description 45
- 238000000605 extraction Methods 0.000 claims abstract description 17
- 238000001914 filtration Methods 0.000 claims abstract description 11
- 238000007781 pre-processing Methods 0.000 claims abstract description 6
- 239000000463 material Substances 0.000 claims description 32
- 239000000843 powder Substances 0.000 claims description 19
- 238000006073 displacement reaction Methods 0.000 claims description 17
- 239000000758 substrate Substances 0.000 claims description 7
- 230000005540 biological transmission Effects 0.000 claims description 6
- 230000003287 optical effect Effects 0.000 claims description 6
- 230000009467 reduction Effects 0.000 claims description 6
- 239000004065 semiconductor Substances 0.000 claims description 4
- 239000002893 slag Substances 0.000 claims description 4
- 238000009826 distribution Methods 0.000 claims description 3
- 239000013307 optical fiber Substances 0.000 claims description 3
- 230000007547 defect Effects 0.000 description 6
- 238000013461 design Methods 0.000 description 6
- 239000011159 matrix material Substances 0.000 description 5
- 238000005516 engineering process Methods 0.000 description 4
- 230000008569 process Effects 0.000 description 3
- 230000008859 change Effects 0.000 description 2
- 238000011160 research Methods 0.000 description 2
- 230000000007 visual effect Effects 0.000 description 2
- 238000004458 analytical method Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000006243 chemical reaction Methods 0.000 description 1
- 239000011248 coating agent Substances 0.000 description 1
- 238000000576 coating method Methods 0.000 description 1
- 239000011365 complex material Substances 0.000 description 1
- 238000001514 detection method Methods 0.000 description 1
- 230000004392 development of vision Effects 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 230000010354 integration Effects 0.000 description 1
- 238000004372 laser cladding Methods 0.000 description 1
- 238000003754 machining Methods 0.000 description 1
- 239000002184 metal Substances 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000005457 optimization Methods 0.000 description 1
- 238000003672 processing method Methods 0.000 description 1
- 238000003892 spreading Methods 0.000 description 1
- 230000007480 spreading Effects 0.000 description 1
- 238000012360 testing method Methods 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/84—Systems specially adapted for particular applications
- G01N21/88—Investigating the presence of flaws or contamination
- G01N21/95—Investigating the presence of flaws or contamination characterised by the material or shape of the object to be examined
Landscapes
- Physics & Mathematics (AREA)
- Health & Medical Sciences (AREA)
- Life Sciences & Earth Sciences (AREA)
- Chemical & Material Sciences (AREA)
- Analytical Chemistry (AREA)
- Biochemistry (AREA)
- General Health & Medical Sciences (AREA)
- General Physics & Mathematics (AREA)
- Immunology (AREA)
- Pathology (AREA)
- Laser Beam Processing (AREA)
Abstract
The invention discloses an on-line monitoring method for the overlap ratio of laser additive manufacturing. The image online processing unit comprises a gray processing module, an image filtering and noise reducing module, a width feature extraction module and a lap joint feature extraction module; the lap-joint rate on-line processing unit can correct the acquired lap-joint rate characteristics in real time according to the data of the image on-line processing unit and the pose information of the on-line monitoring system, and obtain an actual lap-joint value and a lap-joint rate value on line. The laser additive manufacturing lap joint rate monitoring method realizes rapid and reliable monitoring of the laser additive manufacturing lap joint rate through image calibration, acquisition, preprocessing, correction, calculation and the like.
Description
Technical Field
The invention belongs to the technical field of laser additive manufacturing online monitoring, and particularly relates to an online monitoring method for a laser additive manufacturing lap joint rate.
Background
The additive manufacturing is different from the traditional equal-material and material-reducing manufacturing in a processing mode, has the advantages of being direct, rapid, flexible, intelligent and the like, and can effectively process complex structures, complex materials and small-batch parts. Laser is used as an energy source in laser additive manufacturing, so that the laser additive manufacturing method has the advantages of wide applicable materials, no need of a vacuum environment, relatively low cost and the like, and is widely applied to additive manufacturing.
Laser additive manufacturing, especially the additive manufacturing of metal products in the industrial field, has poor quality uniformity and more influence factors, wherein the problems of dimensional accuracy and defects always influence the popularization and application of the technology. In the laser additive manufacturing, except that a single-pass multilayer processing is adopted for individual thin-wall parts, the rest application fields including forming, repairing, coating and the like all need to be subjected to multi-pass lap joint processing. In multiple processing, the uneven surface of the additive part can be caused by the excessively low overlapping rate, and higher roughness is generated; an excessively high overlapping rate can cause the height of the material adding part to be abnormally increased, and the material adding part is seriously deformed; meanwhile, the width of each channel or even the same channel in additive manufacturing is not stable due to reasons of heat balance, pose change and the like; defects such as blowholes, slag inclusions, etc. are also often produced at the lap joints between the roads. Therefore, in order to obtain laser additive parts with higher dimensional accuracy and no defects, especially in the processing of complex structures or gradient materials, a large amount of resources are required to be consumed in the design of the overlapping ratio.
In the field of laser additive manufacturing, research on obtaining high-quality parts by means of online monitoring and feedback control has been advanced to some extent, but no effective method for online monitoring and feedback adjustment of the lap joint rate exists in the research. At present, the determination of the lap joint rate in the laser additive manufacturing still mainly depends on a large number of pre-tests, and intelligent online monitoring and feedback adjustment cannot be carried out according to the processing conditions.
Therefore, the problems that a large amount of resources are consumed in the design of the lap joint rate and online monitoring and feedback adjustment cannot be performed are solved, and an effective solution is not provided, and the problems have important influences on the processing quality and resource utilization of laser material increase. Therefore, there is a need for a monitoring method capable of online monitoring the laser additive manufacturing lap ratio, so as to solve the design problem of the lap ratio and the online monitoring problem in the online monitoring and feedback adjustment.
Disclosure of Invention
Aiming at the defects of the prior art, the invention provides an online monitoring method for the laser additive manufacturing lap joint rate, so that the problems that a large amount of resources are consumed in the design of the lap joint rate in the additive manufacturing process, and the online monitoring is performed in the online monitoring and feedback adjustment process are solved, the actual lap joint value and the actual lap joint rate value can be obtained in real time, the optimal design and feedback adjustment of the lap joint rate are performed on the basis of the actual lap joint value and the actual lap joint rate value, the method can enable the laser additive manufacturing quality to be higher, and the resources to be more saved.
The technical scheme of the invention is as follows:
a laser vibration material disk (MEG) overlap ratio on-line monitoring method, the laser vibration material disk (MEG) overlap ratio on-line monitoring system used in the method increases an image on-line processing unit and an overlap ratio on-line processing unit on the basis of the original on-line monitoring system; the original online monitoring system comprises a laser, a laser head, a displacement device, a material feeding device and an image coaxial acquisition unit;
the image online processing unit comprises a gray processing module, an image filtering and noise reducing module, a width feature extraction module and a lap joint feature extraction module;
the lap joint rate online processing unit corrects the acquired features of the lap joint in real time according to the data of the image online processing unit and the pose information of the online monitoring system, and obtains an actual lap joint value and a lap joint rate value online;
the method comprises the following steps:
(1) adjusting the distance between the laser head and the substrate to be within the range of 2mm above and below the powder convergence position, focusing an image coaxial acquisition unit through a calibration plate, and calibrating the ratio of an image to an actual size, wherein the ratio of the image pixel value to the actual size is n: 1;
(2) the relative displacement of the laser head and the base body or the material added part is controlled by a displacement device, the pose information of the laser head and the base body or the material added part is determined by the angles of the displacement device and the base body or the material added part, the material added processing is carried out on the base body or the material added part, the laser molten pool image is collected in real time through an image coaxial collecting unit, and the collecting frame rate range is 20-200 fps;
(3) the image online processing unit is used for preprocessing the acquired image, wherein the preprocessing comprises gray processing, image filtering and noise reduction, width feature extraction and lap joint feature extraction, and the processing time is 5-50 ms;
the gray level processing makes the gray level distribution range in the gray level histogram of the original image compressed to at least 1/2 of the original image;
the image filtering noise reduction removes powder splashing interference outside a molten pool area, and removes powder splashing interference, molten pool slag interference and molten pool bubble interference with a pixel value smaller than 10 in the molten pool area;
the width characteristic extraction can obtain the pixel value L of the maximum width of the molten pool perpendicular to the scanning direction;
the characteristic extraction of the lap joint can obtain the position of the lap joint parallel to the scanning direction and the pixel value S of the vertical distance between the position and the leftmost end of the current additive part molten pool;
(4) according to the calibration proportion n:1 in the step (1) and the position and posture information in the step (2), wherein the position and posture information comprises a laser head inclination angle α and a matrix or added material part inclination angle β, the previous width feature L extracted in the step (3) is used1Leading the characteristic S of the current lap joint part into an on-line lap joint rate processing unit according to a formula
Obtaining an actual lap joint value D; according to the formula
The actual lap ratio η is obtained.
In the technical scheme, the laser comprises a semiconductor laser or an Nd-YAG laser, and the laser head are connected in an optical fiber mode.
The material feeding device comprises a powder feeding device, a wire feeding device or a powder spreading device.
The displacement device comprises a numerical control machine tool or a robot.
The coaxial image acquisition unit comprises a 45-degree spectroscope, an optical filter, a lens and a camera which are arranged in the laser head, the spectroscope can realize forward transmission of laser and reverse transmission of visible light, the optical filter can filter strong light and interference light, and the lens and the camera can clearly acquire laser material-increasing molten pool images at each moment.
The invention has the beneficial effects that:
1. the method can be used for monitoring the laser additive manufacturing lap joint rate on line, acquiring the actual lap joint rate value in real time, has short processing time and is stable and reliable, can be used for monitoring the lap joint rate under the conventional condition, and can also be used for designing and optimizing the lap joint rate under a complex structure and a gradient material.
2. The invention has high integration degree, can be embedded into the current monitoring system without adding excessive hardware equipment, can acquire width data in real time, and can carry out deeper analysis aiming at the visual image of a molten pool, such as online detection of defects and the like.
3. The invention has strong applicability, is not limited by the problems of the properties, the size, the surface state and the like of the feeding material or the matrix material, and has better adaptability.
Drawings
Fig. 1 is a schematic structural diagram of an on-line monitoring system for a laser additive manufacturing lap joint rate.
Fig. 2 is a schematic flow chart of an on-line monitoring method for the laser additive manufacturing lap joint rate.
Fig. 3(a) (b) (c) (d) (e) are monitoring images and lap joint characteristics at 0.83, 0.67, 0.50, 0.31, 0.05 lap joint rates during processing of 316L matrix and 316L powder in accordance with example of the present invention.
In the figure: 1, a laser; 2 a displacement device; 3, a laser head; 4 a material feeding device;
5, an image coaxial acquisition unit; 6, a computer.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention. In addition, the technical features involved in the embodiments of the present invention described below may be combined with each other as long as they do not conflict with each other.
In laser additive manufacturing, a lap joint is easy to generate defects, the width of each channel or even the same channel in additive manufacturing is possibly different due to reasons of heat balance, pose change and the like, and particularly in the process of machining a complex structure or a gradient material, the lap joint rate is more difficult to design. With the popularization of laser additive, the optimization of laser head structure and the development of vision sensing technology, coaxial vision monitoring technology is gradually applied to laser additive, and various image processing methods are also gradually tried. Therefore, the invention provides the on-line monitoring method of the laser additive manufacturing lap joint rate by fully utilizing the prior advanced technology and algorithm.
Referring to FIG. 1, the hardware platform of the present embodiment includes
The laser 1: the laser 1 is a semiconductor laser in this embodiment;
the displacement device 2: the displacement device 2 is a six-axis robot in this embodiment;
and 3, laser head 3: the laser head 3 is a laser cladding head in the embodiment;
material feeding device 4: the material feeding device 4 is a powder feeder in this embodiment;
image coaxial acquisition unit 5: the visual image acquisition equipment in the image coaxial acquisition unit is a CMOS camera in the embodiment;
the computer 6: the computer 6 includes an image on-line processing unit and a lap ratio on-line processing unit in this embodiment.
The powder and the matrix material adopted in the embodiment are both 316L powder, the diameter of the powder is 40-120 μm, and the size of the matrix is 120 × 30 × 10 mm.
From fig. 2, the steps of the embodiment are:
(1) adjusting the distance between the laser head 3 and the substrate to the powder convergence position, namely 15mm, focusing an image coaxial acquisition unit through a calibration plate, and calibrating the ratio of an image to an actual size, wherein the ratio of an image pixel value to the actual size of 1mm is 130: 1;
(2) the relative displacement of the laser head 3 and the substrate or the material added part is controlled by the displacement device 2, the pose information is determined by the relative angle between the displacement device 2 and the substrate, the relative angle is not more than 30 degrees, the image coaxial acquisition unit 5 acquires the laser molten pool image in real time, and the acquisition frame rate is 100 fps;
(3) the image online processing unit is used for preprocessing the acquired image, and comprises gray processing, image filtering and noise reduction, width feature extraction and lap joint feature extraction, wherein the overall processing time is 10-30 ms for each frame of image;
the gray level processing is to adjust the gray level distribution range in the original image gray level histogram to 3-150 through Gamma conversion and contrast adjustment so as to enhance the image details;
the image filtering noise reduction is carried out, powder splashing interference outside a molten pool area is removed through Gaussian filtering, median filtering and small pixel target removal, and powder splashing interference, molten pool slag interference and molten pool bubble interference with pixel values smaller than 10 in the molten pool area are removed;
the width characteristic extraction is carried out, and a pixel value L of the maximum width of a molten pool perpendicular to the scanning direction is obtained through pixel addition operation;
extracting the characteristics of the lap joint, namely selecting a trough of a pixel summation value of a molten pool parallel to the scanning direction as a lap joint position through pixel summation operation, wherein the characteristic of the lap joint is shown in a figure 3, and the pixel value of the position at the vertical distance from the previous processing part is S;
(4) according to the calibration ratio 130:1 in the step (1) and the position and posture information in the step (2), wherein the position and posture information comprises the inclination angle 0 degree of the laser head and the inclination angle 0 degree of the base body or the added material part, and the previous width characteristic L extracted in the step (3) is used for determining the previous width characteristic L1Leading the characteristic S of the current lap joint part into an on-line lap joint rate processing unit,
according to the formula
Obtaining an actual lap joint value D;
according to the formula
Obtaining an actual lap joint ratio η;
in this embodiment, the ideal overlap ratio (0.50) shown in FIG. 3(c) can be determined, which results in higher surface accuracy at the ideal overlap ratio, which is suitable for the 316L substrate and 316L powder, with the substrate horizontal and perpendicular to the laser head.
It will be understood by those skilled in the art that the foregoing is merely a preferred embodiment of the present invention, and is not intended to limit the invention, and that any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included within the scope of the present invention.
Claims (10)
1. The laser additive manufacturing lap-joint rate on-line monitoring method is characterized in that an image on-line processing unit and a lap-joint rate on-line processing unit are added on the basis of an original on-line monitoring system in a laser additive manufacturing lap-joint rate on-line monitoring system used in the method; the original online monitoring system comprises a laser, a laser head, a displacement device, a material feeding device and an image coaxial acquisition unit;
the image online processing unit comprises a gray processing module, an image filtering and noise reducing module, a width feature extraction module and a lap joint feature extraction module;
the lap joint rate online processing unit corrects the acquired features of the lap joint in real time according to the data of the image online processing unit and the pose information of the online monitoring system, and obtains an actual lap joint value and a lap joint rate value online;
the method comprises the following steps:
(1) adjusting the distance between the laser head and the substrate to 2mm from the powder convergence position of the laser head, focusing an image coaxial acquisition unit through a calibration plate, and calibrating the ratio of an image to an actual size, wherein the ratio of an image pixel value to the actual size is n: 1;
(2) the relative displacement of the laser head and the base body or the material added part is controlled by a displacement device, the pose information of the laser head and the base body or the material added part is determined by the angles of the displacement device and the base body or the material added part, the material added processing is carried out on the base body or the material added part, laser molten pool images are collected in real time through an image coaxial collecting unit, and the collecting frame rate range is 20-200 fps, wherein the pose information comprises a laser head inclination angle α and a base body or material added part inclination angle β;
(3) the image online processing unit is used for preprocessing the acquired image, wherein the preprocessing comprises gray processing, image filtering and noise reduction, width feature extraction and lap joint feature extraction, and the processing time is 5-50 ms;
the width characteristic extraction is to obtain a pixel value L of the maximum width of the molten pool perpendicular to the scanning direction;
the characteristic extraction of the lap joint is to obtain the position of the lap joint parallel to the scanning direction and the pixel value S of the vertical distance between the position and the farthest position of the lap joint end of the current additive part molten pool;
(4) according to the calibration proportion n:1 in the step (1) and the pose information in the step (2), the previous width feature L extracted in the step (3) is used for determining the previous width feature L1Leading the characteristic S of the current lap joint part into an on-line lap joint rate processing unit according to a formula
Obtaining an actual lap joint value D; according to the formula
The actual lap ratio η is obtained.
2. The method of claim 1, wherein the gray-scale processing is performed to compress the gray-scale distribution range in the gray-scale histogram of the original image at least to 1/2 of the original image.
3. The laser additive manufacturing overlap ratio online monitoring method according to claim 1 or 2, wherein the image filtering noise reduction is to remove powder splash interference outside a molten pool area, and to remove powder splash, molten pool slag and molten pool bubble interference with a pixel value less than 10 in the molten pool area.
4. The laser additive manufacturing lap joint rate online monitoring method according to claim 1 or 2, wherein the laser comprises a semiconductor laser or an Nd-YAG laser, and the laser head are connected in an optical fiber connection mode.
5. The laser additive manufacturing lap joint rate online monitoring method according to claim 3, wherein the laser comprises a semiconductor laser or an Nd-YAG laser, and the laser head are connected in an optical fiber connection mode.
6. The laser additive manufacturing lap-joint rate on-line monitoring method according to claim 5, wherein the material feeding device comprises a powder feeding device, a wire feeding device or a powder laying device.
7. The laser additive manufacturing lap-joint rate on-line monitoring method according to claim 1, 2, 5 or 6, wherein the displacement device comprises a numerical control machine or a robot.
8. The laser additive manufacturing lap joint rate on-line monitoring method according to claim 3, wherein the displacement device comprises a numerical control machine or a robot.
9. The on-line monitoring method for the laser additive manufacturing lap ratio according to claim 1, 2, 5, 6 or 8, characterized in that the image coaxial acquisition unit comprises a 45 ° spectroscope, an optical filter, a lens and a camera which are arranged in the laser head, the spectroscope realizes forward transmission of laser and reverse transmission of visible light, the optical filter filters strong light and interference light, and the lens and the camera clearly acquire laser additive molten pool images at each moment.
10. The on-line monitoring method for the laser additive manufacturing overlap ratio according to claim 7, wherein the image coaxial acquisition unit comprises a 45 ° spectroscope, an optical filter, a lens and a camera which are arranged in the laser head, the spectroscope realizes forward transmission of laser and reverse transmission of visible light, the optical filter filters strong light and interference light, and the lens and the camera clearly acquire the laser additive weld pool image at each moment.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710669368.0A CN107688028B (en) | 2017-08-08 | 2017-08-08 | Laser additive manufacturing lap joint rate online monitoring method |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710669368.0A CN107688028B (en) | 2017-08-08 | 2017-08-08 | Laser additive manufacturing lap joint rate online monitoring method |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN107688028A CN107688028A (en) | 2018-02-13 |
| CN107688028B true CN107688028B (en) | 2020-07-14 |
Family
ID=61153283
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201710669368.0A Active CN107688028B (en) | 2017-08-08 | 2017-08-08 | Laser additive manufacturing lap joint rate online monitoring method |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN107688028B (en) |
Families Citing this family (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108608119B (en) * | 2018-05-03 | 2021-04-27 | 苏州大学 | Laser additive manufacturing online monitoring method |
| CN108931535B (en) * | 2018-09-11 | 2021-01-05 | 大连理工大学 | Online monitoring method for laser additive manufacturing pore defects |
| CN109136912B (en) * | 2018-09-11 | 2020-01-17 | 大连理工大学 | On-line monitoring and negative feedback state identification method for defocusing amount in laser cladding |
| CN108956609B (en) * | 2018-09-11 | 2021-04-20 | 大连理工大学 | Laser additive manufacturing powder utilization rate on-line monitoring method |
| CN110340363B (en) * | 2019-05-16 | 2022-12-06 | 西北工业大学 | Detection device and method for interaction of synchronous powder feeding laser additive manufacturing light powder |
| CN115056239B (en) * | 2022-07-06 | 2023-05-26 | 山东大学 | Laser cladding method and system for film wall robot |
| CN115508376A (en) * | 2022-08-24 | 2022-12-23 | 上海交通大学 | Laser cladding head machining state real-time monitoring system and method |
Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2005014027A (en) * | 2003-06-24 | 2005-01-20 | Enshu Ltd | Weld zone image processing method, welding management system, feedback system for welding machine, and butt line detection system |
| CN102191495A (en) * | 2010-03-05 | 2011-09-21 | 南昌航空大学 | Method for quickly preparing metal ceramic coating through laser induced composite fusioncast |
| CN102513708A (en) * | 2011-11-25 | 2012-06-27 | 湖南大学 | Active type integrating device of micro-pore monitoring and seam tracking in short-wavelength laser welding |
| CN103506756A (en) * | 2013-09-11 | 2014-01-15 | 上海交通大学 | Laser lap welding gap detecting system and laser lap welding gap detecting method based on molten pool image visual sensing |
| CN103604813A (en) * | 2013-12-05 | 2014-02-26 | 上海彩石激光科技有限公司 | Molten pool monitoring device for laser processing process |
| CN105335946A (en) * | 2015-09-22 | 2016-02-17 | 中国科学院西安光学精密机械研究所 | Histogram compactness transformation method |
| CN106338521A (en) * | 2016-09-22 | 2017-01-18 | 华中科技大学 | Additive manufacturing surface defect, internal defect and shape composite detection method and device |
| CN106404795A (en) * | 2016-10-26 | 2017-02-15 | 华中科技大学 | Infrared information-based metal additive manufacturing process control apparatus and method |
| CN106735210A (en) * | 2016-12-15 | 2017-05-31 | 南京中科煜宸激光技术有限公司 | A kind of control system and control method for powder feeding formula increasing material manufacturing equipment |
| CN106984813A (en) * | 2017-04-14 | 2017-07-28 | 华南理工大学 | A kind of melt-processed process coaxial monitoring method and device in selective laser |
-
2017
- 2017-08-08 CN CN201710669368.0A patent/CN107688028B/en active Active
Patent Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2005014027A (en) * | 2003-06-24 | 2005-01-20 | Enshu Ltd | Weld zone image processing method, welding management system, feedback system for welding machine, and butt line detection system |
| CN102191495A (en) * | 2010-03-05 | 2011-09-21 | 南昌航空大学 | Method for quickly preparing metal ceramic coating through laser induced composite fusioncast |
| CN102513708A (en) * | 2011-11-25 | 2012-06-27 | 湖南大学 | Active type integrating device of micro-pore monitoring and seam tracking in short-wavelength laser welding |
| CN103506756A (en) * | 2013-09-11 | 2014-01-15 | 上海交通大学 | Laser lap welding gap detecting system and laser lap welding gap detecting method based on molten pool image visual sensing |
| CN103604813A (en) * | 2013-12-05 | 2014-02-26 | 上海彩石激光科技有限公司 | Molten pool monitoring device for laser processing process |
| CN105335946A (en) * | 2015-09-22 | 2016-02-17 | 中国科学院西安光学精密机械研究所 | Histogram compactness transformation method |
| CN106338521A (en) * | 2016-09-22 | 2017-01-18 | 华中科技大学 | Additive manufacturing surface defect, internal defect and shape composite detection method and device |
| CN106404795A (en) * | 2016-10-26 | 2017-02-15 | 华中科技大学 | Infrared information-based metal additive manufacturing process control apparatus and method |
| CN106735210A (en) * | 2016-12-15 | 2017-05-31 | 南京中科煜宸激光技术有限公司 | A kind of control system and control method for powder feeding formula increasing material manufacturing equipment |
| CN106984813A (en) * | 2017-04-14 | 2017-07-28 | 华南理工大学 | A kind of melt-processed process coaxial monitoring method and device in selective laser |
Also Published As
| Publication number | Publication date |
|---|---|
| CN107688028A (en) | 2018-02-13 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN107688028B (en) | Laser additive manufacturing lap joint rate online monitoring method | |
| CN108931535B (en) | Online monitoring method for laser additive manufacturing pore defects | |
| CN109136912B (en) | On-line monitoring and negative feedback state identification method for defocusing amount in laser cladding | |
| CN106181162B (en) | A kind of real-time weld joint tracking detection method based on machine vision | |
| CN108489986B (en) | Additive manufacturing online detection and repair method | |
| CN108956609B (en) | Laser additive manufacturing powder utilization rate on-line monitoring method | |
| CN111192307B (en) | Self-adaptive deviation rectifying method based on laser cutting of three-dimensional part | |
| CN109676135A (en) | A kind of laser gain material manufacture vision grey value difference on-line monitoring and bug repairing apparatus | |
| CN102455171B (en) | Method for detecting geometric shape of back of tailor-welding weld and implementing device thereof | |
| US20080314878A1 (en) | Apparatus and method for controlling a machining system | |
| CN102073148B (en) | High-accuracy visual coaxial optical alignment assembly system for miniature structural member | |
| CN108637435A (en) | A kind of three-dimensional seam tracking system and method for view-based access control model and arc voltage sensing | |
| CN106392267A (en) | Line laser real-time welding seam tracking method for six-freedom-degree welding robot | |
| CN106881462A (en) | A kind of on-line checking for selective laser fusing forming defects and optimization system | |
| CN112191993B (en) | Argon arc welding seam tracking system and method | |
| CN111390168B (en) | On-line monitoring and negative feedback state identification method for defocusing amount of laser melting deposition powder flow | |
| CN114140439A (en) | Laser welding seam feature point identification method and device based on deep learning | |
| CN106056603A (en) | Stereoscopic vision-based welding execution parameter on-line detection method | |
| CN112238292A (en) | Method for tracking space curve track of friction stir welding robot based on vision | |
| CN111398271A (en) | Detection optimization system and method for laser near-net-shape defect | |
| CN114257736A (en) | Self-adaptive shooting method for workpieces | |
| CN111761224A (en) | Metal additive manufacturing online mobile monitoring mechanism and online appearance detection equipment | |
| CN111113410B (en) | Robot motion control method for visual adaptive detection, computer readable storage medium and robot | |
| CN116638099A (en) | System and method for online monitoring of lap-joint machining air hole defects in laser additive manufacturing | |
| CN109934820B (en) | Method for detecting linear edge sub-pixels in laser tailor-welded workpiece image |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |