Open AccessX-ray Image Recognition Method for Crimping Defects of Strain Clamp Based on OpenCV
Author(s) -
Pengwu Li,
Ronghai Liu
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/2121/1/012025
Subject(s) - clamp , python (programming language) , crimp , computer vision , artificial intelligence , computer science , image quality , computer graphics (images) , image (mathematics) , materials science , clamping , composite material , operating system
The crimp quality of the tension clamp of the line affects the safety of the power grid. At present, the measurement of the quality of the tension clamp has certain limitations. An X-ray image detection method for strain clamp based on image processing technology is proposed. Firstly, the X-ray image of the strain clamp is taken and the image is preprocessed. Secondly, by selecting the defect part image of the typical defect sample, using some statements of OpenCV Python Library in Python to quickly identify and detect other X-ray pictures, and mark the defect part of other pictures. Finally, whether it is a defect is determined according to the cumulative value image of the gray value distribution of the marked defect area. Through the research in this paper, the rapid identification of the X-ray image of the crimping position of the tension clamp can be realized, which has important reference value for the engineering application of the crimping quality inspection of the tension clamp.