Automatic welding and defect detection method based on self-learning

An automatic welding and defect detection technology, applied in optical testing defects/defects, measuring devices, scientific instruments, etc., can solve the problems of high automation, self-learning and self-evolution of intelligent welding production lines.

Active Publication Date: 2019-12-31
HANGZHOU DIANZI UNIV
View PDF4 Cites 27 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Existing welding quality inspection equipment is usually separated from the welding robot arm process and requires manual assistance
This method of judging wel

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
  • Automatic welding and defect detection method based on self-learning
  • Automatic welding and defect detection method based on self-learning
  • Automatic welding and defect detection method based on self-learning

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0076] In order to meet the flexible welding production requirements of PCB non-standard components and realize intelligent automatic welding in the true sense, the present invention proposes an automatic welding and defect detection method and system based on self-learning.

[0077] In order to achieve this goal, the technical solution of the present invention comprises the following steps:

[0078] Step 1, use knowledge-based rough positioning of solder joints, plan the optimal welding path, and provide running directions for the vision system and robotic arm.

[0079] Step 2, based on the fine positioning of solder joints based on machine vision, and judge the type of solder joints, accurately guide the robotic arm to find the position of the solder joints, and implement targeted automatic welding.

[0080] Step 3, adopt the solder joint defect detection based on online deep reinforcement learning, automatically detect the solder joint defect and judge the type, and provide...

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

No PUM Login to view more

Abstract

The invention discloses an automatic welding and defect detection method based on self-learning. The method provided by the invention comprises the steps that 1 knowledge-based coarse welding spot positioning is used, and the optimal welding path is planned to provide a vision system and a robotic arm with a running direction; 2 fine positioning of welding spots is carried out based on machine vision, and the types of welding spots are judged; the robotic arm is accurately guided to find the location of welding spots, so as to implement targeted automatic welding; and 3 welding spot defect detection based on online deep reinforcement learning is used to automatically detect welding spot defects and determine the type, so as to provide basis and guidance for secondary repair welding at thesame station. According to the invention, a path planning algorithm is used to optimize the welding path of a camera and the robotic arm to improve the production efficiency; a deep neural network which fuses multi-layer features is used to facilitate the detection of many small target scenes with welding spots; for a single type of target, the weight of coordinate loss is improved, and the positioning accuracy is improved; and threshold filtering is carried out on the results, which filters out interference targets, and improves the recognition accuracy.

Description

technical field [0001] The invention relates to the field of machine vision, in particular to an automatic welding and defect detection method based on self-learning. Background technique [0002] The electronics manufacturing industry continues to grow and has become one of the most important strategic industries in the world today. In the information age, electronic products are not only used in small calculators, mobile phones, and notebook computers, but also in large industrial equipment, automobiles, military weapon systems, and aviation equipment. The electronics manufacturing industry has become an important symbol to measure a country's economic development, scientific and technological progress and comprehensive national strength. In recent years, my country's electronic information manufacturing industry has grown at an annual rate of more than 20%, and has become a pillar industry of the national economy. [0003] Surface mount technology (Surface Mount Technol...

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
no application Login to view more
IPC IPC(8): H05K3/34G01N21/956G01N21/88
CPCG01N21/8851G01N21/956G01N2021/95646H05K3/34H05K2203/163H05K2203/166
Inventor 张桦杨铭凯沈菲项雷雷吴以凡戴国骏
Owner HANGZHOU DIANZI UNIV
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap