Weld joint surface defect detection method and system based on machine vision

Abstract

The invention discloses a weld joint surface defect detection method based on machine vision, and manual detection is replaced. A CCD camera and a zero-degree auxiliary light source are arranged to achieve real-time collecting of weld joint images, the surface evenness change of a workpiece can be reflected through lighting, and collapse detection and recognition are facilitated. Meanwhile, a combined algorithm for weld joint surface defect enhancement, segmentation, extraction and recognition is provided, and classified detection of splashing and collapsing is achieved. Automatic qualification diagnosis is realized through the area and characteristics of a weld defect region, and morphological characteristics such as the number, area, perimeter and circularity of weld defects are stored.The detection mode has the characteristics of process visualization, practicability, operation safety and the like, and compared with a traditional visual detection mode, the detection mode can adaptto detection and evaluation of metal welding seams and glue welding seams of carbon steel, stainless steel, aluminum alloy and the like, such as product structures of large railway vehicles, intercityand urban motor train units, high-speed motor train units and the like.

Description

technical field [0001] The invention belongs to the technical field of detection, in particular to a machine vision-based detection method and system for weld surface defects. Background technique [0002] With the development of modern industrial technology, welding, as an important metal connection technology, is widely used in various fields such as automobiles, high-speed trains, construction, and aerospace industries. However, due to the influence of various factors in the welding process, various defects inevitably appear in the weldment, such as collapse, surface depression, undercut, spatter, etc., which seriously affect the quality of the weld. In order to improve the quality of welds, the detection of weld surface defects is essential, but the currently commonly used means of weld surface quality detection is manual evaluation, which has the disadvantages of low efficiency and high subjectivity. With the improvement of welding automation, real-time, efficient and ...

AI Technical Summary

Problems solved by technology

The visual inspection method has been widely used due to its advantages of strong flexibility and simple operation. However, this detection method is affected by subjective factors such as the professional level of the inspectors, making it difficult to achieve objectivity, standardization and standardization of the detection results. , while the efficiency is very low

However, the radiographic inspection method is difficult to inspect the welds of large structural parts due to the limited size of the equipment. At the same time, it is not suitable to inspect defects such as welds on the surface of the welds and splashes.

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