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Machine vision-based detection method for defect on end face of spark plug

A technology of machine vision and detection method, which is applied in the direction of optical testing for defects/defects, which can solve the problems of reduced productivity, false detection and missed detection, eye fatigue, etc., and achieve the effect of low cost, convenient detection and high efficiency

Active Publication Date: 2015-10-07
UNIV OF ELECTRONICS SCI & TECH OF CHINA
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  • Abstract
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  • Application Information

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Problems solved by technology

For this kind of defect, the existing inspection method is to use artificial visual inspection. A single worker will produce eye fatigue when visually inspecting for a long time, which may lead to false detection and missed detection, and even to a certain extent. Reduce productivity and affect product quality

Method used

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  • Machine vision-based detection method for defect on end face of spark plug
  • Machine vision-based detection method for defect on end face of spark plug
  • Machine vision-based detection method for defect on end face of spark plug

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Embodiment Construction

[0035] Below in conjunction with accompanying drawing, the detection method of spark plug end face defect in the present invention is described in detail:

[0036] The end face defects of the spark plug, according to the possible causes of oil and gas leakage, such defects generally show that the length of the defect along the radial direction of the end face is longer. Such as figure 1 Shown:

[0037] In addition, due to the large dust in the production workshop, small spots appear on the end surface, which easily leads to a high false detection rate. Secondly, due to the process, there will be some car marks on the end face of the spark plug. These car marks appear as circumferential scratches on the end face, which are easily misjudged as defects. In addition, there are oil stains on the production line, and these factors will bring difficulties to the correct detection of the end face. Such as figure 1 , only the arrows are defects, and the dark spots in other position...

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Abstract

The invention provides a machine vision-based detection method for a defect on the end face of a spark plug. The method comprises the following steps: acquiring the image of the end face of the spark plug and acquiring a circular ring image representing the end face of the spark plug from the acquired image; then searching for the external circle and the inner circle of a circular ring, the circle center of the circular ring and other information; subjecting the circular ring image to polar coordinate conversion so as to convert the circular ring into a rectangle; and subjecting the rectangle to treatment like filtering and denoising so as to find out the position of the defect of the spark plug The machine vision-based detection method provided by the invention has the advantages of low cost and high detection efficiency.

Description

technical field [0001] The invention relates to an algorithm for detecting a spark plug end face defect. Background technique [0002] During the processing of spark plugs, defects such as scratches and pits will occur on the surface of the spark plug shell, which will affect the product quality. Therefore, in the production process of spark plugs, it is necessary to strictly prevent such defective products from flowing into the next processing procedure, so as to prevent defective products from flowing into the market and causing adverse effects. For this kind of defect, the existing inspection method is to use artificial visual inspection. A single worker will produce eye fatigue when visually inspecting for a long time, which may lead to false detection and missed detection, and even to a certain extent. Reduce productivity and affect product quality. [0003] The algorithm described in the present invention is applied to the visual detection system of this type of prod...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01N21/88
Inventor 杜晓辉张静刘娟秀罗颖杨先明刘霖刘永叶玉堂
Owner UNIV OF ELECTRONICS SCI & TECH OF CHINA