Supercharge Your Innovation With Domain-Expert AI Agents!

Drilling defect detection system based on machine vision and detection method thereof

A defect detection and machine vision technology, applied in the direction of optical testing flaws/defects, instruments, measuring devices, etc., can solve the problems of large amount of image processing operations, affecting the efficiency of automated production lines, etc., to achieve the effect of rapid marking and reducing the impact

Active Publication Date: 2019-08-06
NORTH CHINA INST OF AEROSPACE ENG
View PDF5 Cites 3 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Due to the presence of a large number of burrs and other interference factors on the drilling surface, resulting in a large amount of image processing calculations, which directly affects the efficiency of the entire automated production line

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
  • Drilling defect detection system based on machine vision and detection method thereof
  • Drilling defect detection system based on machine vision and detection method thereof
  • Drilling defect detection system based on machine vision and detection method thereof

Examples

Experimental program
Comparison scheme
Effect test

specific Embodiment approach

[0041] Reference figure 1 , A specific embodiment of the present invention includes:

[0042] Image acquisition module 1 for acquiring borehole images;

[0043] Image preprocessing module 2, used to preprocess the collected borehole images;

[0044] Image layering module 3, used for layering processing of pre-processed borehole images;

[0045] The defect detection module 4 is used to detect the defect area in the layered borehole image.

[0046] A detection method of the above-mentioned drilling defect detection system based on machine vision includes the following steps:

[0047] A. Image acquisition module 1 collects borehole images in two directions parallel to the borehole axis and at an angle of 45° to the borehole axis;

[0048] B. The image preprocessing module 2 preprocesses the two borehole images collected in step A to obtain a composite image, which reduces image distortion and noise interference during the collection process;

[0049] C. The image layering module 3 performs l...

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 a drilling defect detection system based on machine vision, and the system comprises an image collection module which is used for collecting a drilling image; an image pre-processing module which is used for pre-processing the acquired drill hole image; an image layering module which is used for carrying out layering processing on the preprocessed drilling image; and a defect detection module which is used for detecting a defect area in the layered drilling image. The defects in the prior art can be overcome, the detection precision is guaranteed, meanwhile, the calculation amount is reduced, and the detection speed is increased.

Description

Technical field [0001] The invention relates to the technical field of machine vision, in particular to a drilling defect detection system based on machine vision and a detection method thereof. Background technique [0002] In automated production lines, the inspection of drilling is usually carried out by means of machine vision inspection. Due to the large number of burrs and other interference factors on the drilling surface, the image processing operation is large, which directly affects the efficiency of the entire automated production line. Summary of the invention [0003] The technical problem to be solved by the present invention is to provide a drilling defect detection system and a detection method based on machine vision, which can solve the deficiencies of the prior art, reduce the amount of calculation while ensuring the detection accuracy, and increase the detection speed. [0004] To solve the above technical problems, the technical solutions adopted by the present...

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): G06T7/00G06T5/00G01N21/88
CPCG06T7/0004G01N21/8851G01N2021/888G01N2021/8887G06T2207/30108G06T5/70
Inventor 王俊红王喜斌郭向鑫李宏颖周泽明姚晓琼李宗睿
Owner NORTH CHINA INST OF AEROSPACE ENG
Features
  • R&D
  • Intellectual Property
  • Life Sciences
  • Materials
  • Tech Scout
Why Patsnap Eureka
  • Unparalleled Data Quality
  • Higher Quality Content
  • 60% Fewer Hallucinations
Social media
Patsnap Eureka Blog
Learn More

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

© 2025 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com