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Chain type conveyor belt defect detection method based on image processing

An image processing and defect detection technology, which is applied in the field of cigarette production, can solve the problems of missed detection, missed detection, cracks, scratches, protruding parts, etc.

Active Publication Date: 2019-10-08
芜湖启迪睿视信息技术有限公司
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  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

During positioning, when the position of the camera changes, the positioning of the conveyor belt will fail, resulting in missed detection
In addition, when sorting, the number of defective chain conveyor belts is much less than that of non-defective chain conveyor belts. Insufficient sample number of defective chain conveyor belts will cause the computer to fail to identify defects such as cracks, protruding parts, and sunken parts. Conveyor belt, resulting in missed detection
[0003] To sum up, at this stage, the chain conveyor belt defect detection based on human eyes and the chain conveyor belt defect detection based on machine vision are prone to missed detection of defects such as cracks, scratches, and protruding parts.

Method used

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  • Chain type conveyor belt defect detection method based on image processing
  • Chain type conveyor belt defect detection method based on image processing
  • Chain type conveyor belt defect detection method based on image processing

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Embodiment Construction

[0035] In order to make the technical means, creative features, goals and effects achieved by the present invention easy to understand, the present invention will be further described below in conjunction with specific embodiments.

[0036] A chain conveyor belt defect detection method based on image processing, the method comprises the following steps:

[0037] Step 1: Camera and light source installation: the camera is installed on the side of the chain conveyor, and the light source is installed on the left and right sides of the camera;

[0038] Step 2: Image acquisition and positioning: collect the real-time image of the chain conveyor belt through the camera, and use the Gaussian scale pyramid to image img (x 0 ,y 0 ) coordinate pixel value img(x 0 ,y 0 ) to obtain the pixel value Src(x, y) of the (x, y) coordinate point of the multi-scale image Src, and position the scaled image through the pre-built multi-angle rotation model to obtain the chain conveyor belt The d...

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Abstract

The invention discloses a chain type conveyor belt defect detection method based on image processing, and relates to the technical field of cigarette production. According to the invention, the methodcomprises the steps of erecting a camera on the side surface of a to-be-detected chain type conveyor belt, then collecting a real-time image of the chain type conveying belt through the camera; carrying out the scale scaling on the image through a Gaussian scale pyramid; using a pre-constructed multi-angle rotation model to position the image after scale scaling, obtaining the chain conveyor beltregions, converting the area of the chain conveyor belt into a grayscale image through differential multi-core Gaussian filtering, and filtering the grayscale image; enhancing the detection area of the chain type conveying belt by using the index change; carrying out image segmentation on the enhanced image, selecting and counting the characteristics of a defect-free chain type conveyor belt, andfinally comparing the characteristics of the defect-free chain type conveyor belt counted in advance with the corresponding characteristics of the chain type conveyor belt in an image collected in real time to judge whether the chain type conveyor belt has defects or not.

Description

technical field [0001] The invention relates to the technical field of cigarette production, in particular to a defect detection method for chain conveyor belts based on image processing. Background technique [0002] The defect detection of chain conveyor belt is mainly divided into two types: defect detection based on human eyes and defect detection based on machine vision. Among them, the defect detection based on human eyes is realized by observing the chain conveyor belt with human eyes. If the length of the chain conveyor belt is too long, the sampling personnel will have visual fatigue, which will easily cause the defects of the chain conveyor belt to be missed. In addition, the sampling personnel Generally, the chain is regularly inspected, and the chain cannot be monitored in real time. Therefore, the conveyor belt may be damaged during the detection gap of the sampling inspector. The defect detection of the chain conveyor belt based on machine vision is realized t...

Claims

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Application Information

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IPC IPC(8): G06T7/00G06T7/70G06T3/40G06T5/00G06T7/10
CPCG06T7/0004G06T7/70G06T3/40G06T7/10G06T5/94G06T5/70
Inventor 张宇阳李彦伟周志军
Owner 芜湖启迪睿视信息技术有限公司
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