Non-leveling surface autonomous identification robot additive manufacturing forming precision control method

A technology of additive manufacturing and precision control, applied in the fields of additive manufacturing and machine vision, it can solve the problems of difficult matching of imaging points of two cameras and complex algorithms, so as to ensure welding quality and stability, high processing precision, and processing process. concise effect

Active Publication Date: 2019-04-19
NANJING UNIV OF SCI & TECH
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  • Summary
  • Abstract
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  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, in the process of 3D reconstruction in this method, it is difficult to match the corresponding imaging points of the two cameras, and the algorithm is complicated

Method used

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  • Non-leveling surface autonomous identification robot additive manufacturing forming precision control method
  • Non-leveling surface autonomous identification robot additive manufacturing forming precision control method
  • Non-leveling surface autonomous identification robot additive manufacturing forming precision control method

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Embodiment Construction

[0032] Below in conjunction with accompanying drawing and embodiment the present invention will be further described:

[0033] A method for autonomously identifying non-flat surfaces and controlling the forming accuracy of robotic additive manufacturing. The device includes: two M1214-MP2-computar lenses with a focal length of 12mm and an Acer K132 projector (with a resolution of 1280×800) The three-dimensional measurement system, the TIG welding torch and Precitec YC-30 laser laser fixed together by the fixture, the six-axis robot of Japan YASKWA company, the robot control cabinet, the Miller Dynasty350 welding machine, the wire feeder is WF-007A, the welding torch fixture one Set, computer, welding torch water cooling device, shielding gas device.

[0034] Specific implementation steps:

[0035] Step 1: Use an angle grinder to grind the upper surface of the workpiece to be additively manufactured (Q235A substrate, the size is 200mm×200mm×40mm, with uneven surface) to remove...

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Abstract

The invention discloses a non-leveling surface autonomous identification robot additive manufacturing forming precision control method. A CMOS camera and a projector form a three-dimensional measuringsystem, the surface image of a workpiece is collected, the binocular vision based on structured light is combined, the characteristic data of the surface of the workpiece are extracted, and a controller is used for reconstructing a three-dimensional model and determining electric arc melting parameters; flat-peak valley filling operation of non-filler wire melting is carried out in a protective atmosphere by utilizing a TIG welding gun; the corresponding energy is set according to the measured value of the surface flatness, and a laser heat source is used for carrying out laser melting treatment on the surface through the laser; and the actual surface flatness is detected, and the actual surface flatness is compared with the standard surface flatness, if not, the process is repeated untilthe process is qualified. According to the non-leveling surface autonomous identification robot additive manufacturing forming precision control method, the surface precision of an arc additive partcan be effectively improved, welding quality and stability are guaranteed, and therefore the quality of the arc additive forming part can be effectively improved.

Description

technical field [0001] The invention belongs to the technical field of machine vision and the technical field of additive manufacturing, and in particular relates to a method for controlling the forming accuracy of additive manufacturing of a non-flat surface self-identifying robot. Background technique [0002] The characteristics of traditional welding are complex process factors, high labor intensity, long production cycle, and poor working environment. Sex is very important. [0003] With the advancement of science and technology in recent years, the application of machine vision in industrial production has become more and more extensive. Machines are used to replace people in measurement and judgment to reduce errors caused by human subjective factors. The ingested target is converted into an image signal through machine vision products, and converted into a digital signal according to information such as pixel distribution, brightness, and color. The image processing...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): B23K26/342B23K26/348B23K26/70
CPCB23K26/342B23K26/348B23K26/70
Inventor 王克鸿金鸣黄勇吴统立许雪宗
Owner NANJING UNIV OF SCI & TECH
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