Weld defect real-time detection method and system based on 3D point cloud

Abstract

The invention discloses a weld defect real-time detection method and system based on 3D point cloud. The method comprises the following steps: setting a normal weld contour template based on historical data; scanning the cross section of the welding seam through line laser, collecting 3D point cloud data of the welding seam in real time, and recording initial contour data obtained through real-time scanning of the line laser as data; carrying out inflection point detection based on a DBSCAN density clustering algorithm, and determining current weld contour data; and calculating the distance d between the current welding seam contour data and the normal welding seam contour template through a DTW algorithm so as to judge whether defects exist on the surface of the welding seam. According to the method, whether the defects exist on the surface of the weld joint can be effectively distinguished without constructing a complex machine learning or neural network model, calculation resources are greatly saved, meanwhile, rapid and accurate real-time detection is achieved, therefore, the defects are found as early as possible in actual production, losses are reduced, weld joint scrapping is avoided, the repair cost is reduced, and high production value is achieved.

Description

technical field [0001] The invention relates to a method and system for real-time detection of weld defects based on 3D point clouds, belonging to the technical field of intelligent welding. Background technique [0002] The quality inspection during the welding process is very important, which determines whether the weld is qualified and meets the requirements for use. At present, the quality inspection of welds mainly includes: weld appearance shape and surface defect inspection, weld internal defect inspection, weld performance inspection and so on. Among them, the detection of internal defects of welds is mainly realized by non-destructive testing methods such as X-ray and ultrasonic flaw detection. The above methods are mainly used in the detection of welds of pressure vessels and important load-bearing structures. At present, there are perfect and strict quality inspection standards; welds Performance testing includes testing of mechanical properties, corrosion proper...

AI Technical Summary

Problems solved by technology

[0005] Purpose of the invention: Aiming at the problems existing in the prior art, the present invention provides a real-time detection method and system for weld defects based on 3D point cloud, which can effectively identify the weld surface without building complex machine learning or neural network models Whether there is a defect greatly saves computing resources. At the same time, under a certain camera frame rate, fast and accurate real-time detection can be achieved, so that defects can be found as early as possible in actual production, reducing losses, avoiding weld scrapping, and reducing repair costs. high production value

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