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Machine vision based detection method of defect of geometrical shape of back surface of E type magnet

A technology of machine vision and defect detection, which is applied in the field of image processing, can solve problems such as low detection efficiency, geometric defects on the back of E-shaped magnetic materials, and large amount of calculation, etc., to achieve small memory space, fast calculation speed, and small amount of calculation. Effect

Active Publication Date: 2015-06-24
宁波智能装备研究院有限公司
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  • Abstract
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  • Claims
  • Application Information

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Problems solved by technology

[0003] The purpose of the present invention is to provide a machine vision-based method for detecting geometric defects on the back of E-shaped magnetic materials in order to solve the problems of large amount of calculation and low detection efficiency in the existing detection methods for E-shaped magnetic materials

Method used

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  • Machine vision based detection method of defect of geometrical shape of back surface of E type magnet
  • Machine vision based detection method of defect of geometrical shape of back surface of E type magnet
  • Machine vision based detection method of defect of geometrical shape of back surface of E type magnet

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specific Embodiment approach 1

[0023] Specific implementation mode one, the following combination figure 1 Illustrate the present embodiment, the E-type magnetic material backside geometry defect detection method based on machine vision described in the present embodiment, it is realized by the following steps:

[0024] Step 1. Adjust the camera to obtain the image on the back of the E-shaped magnetic material to be tested; the pixel of the image is 1024×1028;

[0025] Step 2, determine the position of the E-shaped magnetic material to be tested in the image obtained in step 1, use the two regions where the edge of the magnetic material is located as the detection image, and simultaneously perform threshold transformation on the image obtained in step 1 to obtain a binary image;

[0026] Step 3. According to the obtained binarized image, the two areas where the left edge and right edge of the E-shaped magnetic material to be tested are located in the obtained image are used as binarized sub-images, and then...

specific Embodiment approach 2

[0040] Specific implementation mode two, the following combination figure 1 Describe this embodiment, this embodiment is a further description of Embodiment 1, the method for detecting geometric defects on the back of the E-shaped magnetic material based on machine vision described in this embodiment, the camera in the step 1 is equipped with a telecentric lens camera.

specific Embodiment approach 3

[0041] Specific implementation mode three, the following combination figure 1 Describe this embodiment, this embodiment is a further description to Embodiment 1, the E-shaped magnetic material backside geometric defect detection method based on machine vision described in this embodiment, in the described step 3, obtain the binary value according to the step 1 The image is used to determine the position of the E-shaped magnetic material to be tested, and the method for determining the position of the E-shaped magnetic material to be tested is:

[0042] Obtain the vertical coordinates of the upper and lower edges of the E-shaped magnetic material and the horizontal coordinates of the left and right edges, and use these four coordinate values ​​to represent the position of the E-shaped magnetic material;

[0043] The method to obtain the ordinate of the upper edge and the lower edge of the E-shaped magnetic material is: project the binarized image onto the ordinate, the projecti...

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Abstract

The invention relates to a machine vision based detection method of the defects of the geometrical shape of the back surface of an E type magnet, belonging to the field of image processing and aiming at solving the problems of large calculated amount and low detection efficiency of the traditional detection method of the E type magnet. The machine vision based detection method comprises the following steps of: acquiring an image of the back surface of the E type magnet by applying a camera; utilizing two areas in which the left side edge and the right side edge of the obtained image are positioned as binarized subimages; carrying out communicated area marking and expansion operation on the image, and then utilizing the image as a filter template; filtering an edge image with disturbance points, which is subjected to Canny edge detection, by using the filter template; respectively carrying out Hough transformation on the upper part and the lower part of each binarized subimage to obtain two fitting straight lines; if an included angle of the two fitting straight lines is larger than N degrees, determining that the deformation of the back surface of the E type magnet to be detected is overlarge, wherein N is a positive integer; and if not, calculating the length and the deformation rate of the E type magnet.

Description

technical field [0001] The invention relates to a machine vision-based method for detecting geometric shape defects on the back of an E-shaped magnetic material, belonging to the field of image processing. Background technique [0002] At present, E-shaped magnetic materials are widely used in transformers, which are used in a symmetrical combination of two E-shaped magnetic materials. Therefore, it is necessary to effectively detect whether there are defects in the geometric shape of the E-shaped magnetic materials. When used in combination, magnetic flux leakage will occur, which will seriously affect the life of the transformer and cause a large loss of energy. Therefore, it is an important part in the industrial production of E-shaped magnetic materials to detect whether there are defects in the geometric shape of E-shaped magnetic materials. At present, the size detection of E-type magnetic materials in industrial production is still in the state of sorting by producti...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G01B11/24G01B11/03G01B11/16G06K9/60
Inventor 高会军孙昊张世浩盛典丁长兴于金泳孙光辉刘雨
Owner 宁波智能装备研究院有限公司
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