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

A welding seam surface and defect inspection technology, applied in the field of inspection, can solve the problems of difficulty in objectification, standardization and standardization of inspection results, difficulty in inspection of welding seam of large-scale structural parts, and limited equipment size, etc., and achieves obvious reliability advantages. Avoid human error and test data accurately and objectively

Pending Publication Date: 2020-11-24
NANJING ZHONGCHE PUZHEN URBAN RAIL VEHICLE CO LTD
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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 t

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

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Embodiment Construction

[0043] The present invention will be further described below in conjunction with the accompanying drawings. The following examples are only used to illustrate the technical solution of the present invention more clearly, but not to limit the protection scope of the present invention.

[0044] Such as figure 1 As shown, the hardware of the real-time acquisition platform for weld surface images includes: CCD camera, lens, ring-shaped LED 0° light source, and fixed platform. The camera adopts a CCD 5 million area array camera and supporting lens, controls the photosensitive and weld picture collection through the detection system software, and the collection area is 200x100mm. The ring-shaped LED 0° light source is used as the auxiliary light source. The zero-degree ring-shaped white light source can effectively reflect the flatness of the weld surface through zero-degree lighting. The sunken area will appear dark because the light source cannot be illuminated, and the raised pa...

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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 ...

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Application Information

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IPC IPC(8): G01N21/88G06T7/00G06T7/187
CPCG01N21/8851G06T7/0006G06T7/187G01N2021/8861G01N2021/8874G01N2021/8887G01N2021/8883G06T2207/10004
Inventor 火巧英翁志洪魏瑞霞佟琛刘建军武美妮戴忠晨陈云霞
Owner NANJING ZHONGCHE PUZHEN URBAN RAIL VEHICLE CO LTD
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