Unlock instant, AI-driven research and patent intelligence for your innovation.
A seam tracking method and device based on independent deviation correction deep learning
What is Al technical title?
Al technical title is built by PatSnap Al team. It summarizes the technical point description of the patent document.
A deep learning and tracking device technology, applied in welding equipment, arc welding equipment, manufacturing tools, etc., can solve the problems of noise interference, tracking failure, welding seam tracking accuracy reduction, etc., to improve welding efficiency and welding seam tracking accuracy. , the effect of suppressing tracking drift
Active Publication Date: 2022-05-20
GUANGDONG UNIV OF TECH
View PDF7 Cites 0 Cited by
Summary
Abstract
Description
Claims
Application Information
AI Technical Summary
This helps you quickly interpret patents by identifying the three key elements:
Problems solved by technology
Method used
Benefits of technology
Problems solved by technology
[0009] During the on-site welding process, there is strong noise interference in the weld image information detected by the line-structured light vision sensor, which reduces the accuracy of weld seam tracking
In recent years, the target tracking algorithm has been applied to the field of seam tracking and has achieved good results. However, under the interference of strong noise, there is still the problem of tracking drift leading to tracking failure in the tracking process.
Method used
the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more
Image
Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
Click on the blue label to locate the original text in one second.
Reading with bidirectional positioning of images and text.
Smart Image
Examples
Experimental program
Comparison scheme
Effect test
Embodiment 1
[0067] This embodiment provides a seam tracking method based on independent deviation correction deep learning.
[0068] The welding method described in this embodiment is based on the seam tracking method (KCF-YOLOV3) of kernel correlation filtering (KCF) combined with deep learning detection (YOLOV3). In the real-time welding process, the KCF algorithm constructs a large number of positive and negative samples through cyclic shifting, uses ridge regression to train the classifier online, and uses the property that the cyclic matrix can be diagonalized in Fourier space to convert the operation of the matrix into the vector Hadamard Product, which greatly reduces the amount of calculation, so that the algorithm meets the real-time requirements, and uses the Gaussian kernel function mapping to improve the tracking accuracy.
[0069] The traditional kernel correlation filter tracking is a short-term target tracking method, and its limitation is that it is easy to accumulate trac...
Embodiment 2
[0095] This embodiment provides a seam tracking device based on independent deviation correction deep learning, such as Figure 3-4 As shown, the device includes: a working platform 9, a controller 1, a vertical guide rail 3, a horizontal guide rail 4, a welding gun fixture 6, a line structured light visual sensor 5, and a servo servo motor 2;
[0096] The working platform 9 is used to place the workpiece 10 to be welded;
[0097] The controller 1, the vertical guide rail 3, the horizontal guide rail 4, the welding torch fixture 6, the line structured light vision sensor 5, and the servo servo motor 2 are arranged above the working platform 9;
[0098] The horizontal guide rail 4 is arranged on the vertical guide rail 3, and can slide up and down along the vertical guide rail 3;
[0099] The servo motor 2 is arranged on one end of the horizontal guide rail 4;
[0100] The welding gun fixture 6 and the line structured light vision sensor 5 are arranged on the horizontal guide r...
the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More
PUM
Login to View More
Abstract
The invention relates to a welding seam tracking method and device based on independent deviation correction deep learning. The device includes: a working platform, a controller, a vertical guide rail, a horizontal guide rail, a welding torch fixture, a line structured light visual sensor, and a servo motor The method includes: S1: collecting structured light pictures of welds; S2: reading structured light pictures of welds; S3: using YOLOV3 to identify the current weld type and locate the center position of the weld; S4: the weld positioned by S3 The center position is used as the tracking target, and the KCF tracker is initialized; S5: Welding starts, and the KCF-YOLOV3 algorithm is used to track the weld in real time; until the end of welding. The welding device and welding method of the present invention can automatically identify various weld seams and accurately locate the central area of the weld seams, which can effectively improve the weld seam detection speed and recognition accuracy, thereby improving welding efficiency.
Description
technical field [0001] The present invention relates to the field of welding technology, and more specifically, to a welding seam tracking method and device based on independent deviation correction deep learning. Background technique [0002] The welding seam tracking technology based on structured light vision combines the advantages of computer vision and laser three-dimensional measurement technology. Because of the advantages of sexiness, coherence and ability concentration, it is widely used in the light source of structured light. At present, the seam tracking under the line structured light vision sensor has been relatively mature. In order to reduce the interference of strong arc light during the welding process, a filter lens with a certain bandwidth is usually installed in front of the camera lens to maintain a clear structured light image, and the center position of the weld seam is obtained through signal acquisition and image processing. [0003] The current ...
Claims
the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More
Application Information
Patent Timeline
Application Date:The date an application was filed.
Publication Date:The date a patent or application was officially published.
First Publication Date:The earliest publication date of a patent with the same application number.
Issue Date:Publication date of the patent grant document.
PCT Entry Date:The Entry date of PCT National Phase.
Estimated Expiry Date:The statutory expiry date of a patent right according to the Patent Law, and it is the longest term of protection that the patent right can achieve without the termination of the patent right due to other reasons(Term extension factor has been taken into account ).
Invalid Date:Actual expiry date is based on effective date or publication date of legal transaction data of invalid patent.
Login to View More 
Login to View More