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Workpiece flaw identification method based on compound characteristics in magnaflux powder inspection environment

A technology of magnetic particle flaw detection and compound features, which is applied in character and pattern recognition, material magnetic variables, computer components, etc., can solve problems such as limited applicability, single flaw features, and lack of stability

Inactive Publication Date: 2010-10-06
UNIV OF ELECTRONIC SCI & TECH OF CHINA
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  • Abstract
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  • Application Information

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Problems solved by technology

[0007] However, the scheme of the present invention only uses wavelet transform to extract the frequency domain features of the image, and the scar features are single, which is only suitable for the detection of specific scars. The detection threshold is set artificially, which has no stability, and is not conducive to popularization Limited, lack of learning mechanism for scar features, and human factors have a great influence on the final detection results
Therefore, the accuracy of the scheme for scar recognition is not high, and the type of scar cannot be further identified

Method used

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  • Workpiece flaw identification method based on compound characteristics in magnaflux powder inspection environment
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  • Workpiece flaw identification method based on compound characteristics in magnaflux powder inspection environment

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Embodiment 1

[0105] Embodiment 1: as figure 1 As shown in the figure, the flow chart of the automatic detection of flaws in the workpiece image under the magnetic particle inspection environment is described in the figure. This flow chart describes a method for identifying workpiece flaws based on composite features in a magnetic particle inspection environment, including the following steps:

[0106] Step 1: In the process of automatic flaw detection of the workpiece image, the image preprocessing of the workpiece image collected under the magnetic particle inspection environment is firstly carried out. The image preprocessing process includes image noise filtering, image enhancement and image segmentation. After the image segmentation is completed, the obtained Workpiece foreground area, image morphology operation is performed on the foreground area of ​​the workpiece, and suspicious scar area is extracted. Since the magnetic particle inspection environment will be affected by a lot of ...

Embodiment 2

[0176] Embodiment 2: Embodiment 1 is aimed at the automatic detection method of flaws in images under the magnetic particle inspection environment. On the basis of Embodiment 1, the present invention also proposes an automatic detection method for flaws in the workpiece video under the magnetic particle inspection environment. For the automatic detection of flaws in the workpiece video, each video frame can be regarded as a workpiece image, but the biggest difference between the flaw detection in the video and the flaw detection in the image is that the same workpiece will form a continuous image sequence in the video, In this image sequence, there are both video frames judged to have scars and video frames judged to have no scars. Therefore, the recognition of scars is aimed at image sequences rather than single pictures. like Figure 8 As shown, the method for identifying workpiece flaws in the workpiece video under the magnetic particle inspection environment is described,...

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Abstract

The invention relates to a workpiece flaw identification method based on compound characteristics in a magnaflux powder inspection environment, which comprises the following steps of: firstly, preprocessing workpiece images collected in the magnaflux powder inspection environment in the process of flaw automatic detection for the workpiece images, wherein the image preprocessing process comprises an image filtering, image enhancement and image segmentation; after accomplishing the image segmentation, obtaining the foreground regions of the workpieces; performing image morphologic operation on the foreground regions of the workpieces to extract the suspicious flaw regions; performing a surface transverse flaw detection step, extracting the transverse flaw characteristics for the suspicious flaw regions by using a surface transverse flaw detection technology, automatically classifying the flaw characteristics of an SVW classifier obtained by automatically learning the transverse flaw sample set to determine whether the surface transverse flaws in the suspicious flaw regions exist or not. The invention has the advantages of low dependence to the detected objects and convenience for application, thereby realizing the workpiece flaw identification of various parts in the magnaflux powder inspection environment.

Description

technical field [0001] The invention belongs to the technical field of automatic detection, and in particular relates to a workpiece non-destructive flaw detection technology under the environment of magnetic particle flaw detection. Background technique [0002] With the rapid development of my country's economy, market competition is becoming increasingly fierce, and users pay more attention to product quality than before. Various non-destructive testing equipment are widely used in the production and manufacturing process of enterprises, but with this In stark contrast, automatic flaw recognition cannot be performed on flaw detection images or industrial flaw detection videos obtained by non-destructive flaw detection equipment. Unstable test results. [0003] As an important and widely used industrial non-destructive testing technology, magnetic particle flaw detection technology is to magnetize workpieces made of magnetic materials such as steel. Angle, due to the chang...

Claims

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Application Information

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IPC IPC(8): G01N27/84G06T7/00G06K9/54G06K9/62
Inventor 周景磊叶茂张旭东赵欣王波
Owner UNIV OF ELECTRONIC SCI & TECH OF CHINA
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