Weld seam surface detect feature extraction method based on grayscale image morphology

A grayscale image and weld surface technology, applied in the field of non-destructive testing, can solve the problems of few researches on the detection and identification of weld surface defects

Active Publication Date: 2016-09-28
BEIJING UNIV OF TECH
View PDF2 Cites 66 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] At present, the technology of welding seam inspection based on X-rays is mostly aimed at the detection of internal defects of weld seam welding, and there is little research on the technology of detection and identification of surface defects of internal welding seams

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
  • Weld seam surface detect feature extraction method based on grayscale image morphology
  • Weld seam surface detect feature extraction method based on grayscale image morphology
  • Weld seam surface detect feature extraction method based on grayscale image morphology

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0052] Below in conjunction with concrete experiment the present invention will be further described:

[0053] In this experiment, the samples with holes on the surface of the weld and the weld bead on the surface of the weld are selected as feature extraction images, and the samples with good surface welding quality are selected as the verification images of the edge extraction algorithm in the early stage. Such as figure 1 shown. Step 1: Image acquisition.

[0054] An industrial CCD camera is used to collect images of defects such as holes and welding spots on the internal weld surface of the transducer. The collected images are true-color RGB images, with image size 480*360, hue 4, saturation 100, contrast -4, and each value is fixed. constant.

[0055] Step 2: Image pre-processing.

[0056] According to the formula (1), the true color RGB image is converted into a grayscale image. as shown in picture 2.

[0057] Step 3: Image preprocessing.

[0058] Median filterin...

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 relates to a weld seam surface defect feature extraction method based on the grayscale image morphology, which comprises the steps of setting shooting parameters of a miniature CCD camera according to an acquired image; converting the acquired true color image into a grayscale image, and carrying out median filtering processing on the image; eliminating a white interference region generated by residue noise and background texture by adopting a minimum area deleting method; avoiding influences imposed on edge line extraction by an undetermined black region through region filling processing; processing a completely filled weld seam region through an expansion algorithm so as to acquire a weld seam region whose area is identical to the actual weld seam area; extracting an edge line of the filled and expanded weld seam region by adopting a Canny operator so as to realize positioning for the weld seam region; and drawing a cross section grayscale B scanning curve which is vertical with the weld seam edge, wherein a gray-scale value of the weld seam surface changes obviously on the B scanning curve when the weld seam surface has defects such as a hole and an overlap, so that different types of defects at the weld seam surface are judged. The weld seam surface detect feature extraction method realizes accurate positioning for the weld seam edge and accurate recognition for the defects such as overlaps and holes.

Description

technical field [0001] The invention relates to a method for detecting welding seam defects, in particular to a method for detecting and identifying weld seam defects based on image processing technology. The method is applicable to the detection and identification of welding defects in internal welds of energy-transforming equipment such as pipelines, boilers, and headers, and belongs to the field of non-destructive testing. Background technique [0002] With the development of my country's industrial industry, boilers, pipes, headers and other energy-transforming equipment are the key components to withstand high temperature and high pressure, and their manufacturing quality has attracted more and more attention. Transducer equipment not only bears the internal pressure caused by the action of the medium, but also bears the stress caused by the temperature difference between the inside and the outside, and the failure and damage can easily occur in the internal welding are...

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
Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/00G06T7/40
CPCG06T7/0004G06T2207/10024G06T2207/30152
Inventor 焦敬品李思源常予何存富吴斌
Owner BEIJING UNIV OF TECH
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products