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Zinc dross image recognition and classification method

A technology of image recognition and classification methods, applied in character and pattern recognition, instruments, biological neural network models, etc., can solve the problems of unrecognizable on-site zinc slag pictures, low operation efficiency, low degree of automation, etc., to increase the generalization ability , reduce the workload, improve the effect of accuracy

Active Publication Date: 2020-11-24
WUHAN UNIV OF SCI & TECH
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Problems solved by technology

This type of product only makes partial improvements and alternative research on the robot structure. Most slag-picking robots still use the mainstream "blind fishing" operation method, that is, to carry out slag-picking actions in the set target area. Due to the lack of visual sensors, Unable to identify on-site zinc slag pictures, indiscriminate selection of target areas, low degree of automation, low operating efficiency, and difficulty in determining the optimal frequency of slag removal have not been resolved.

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  • Zinc dross image recognition and classification method
  • Zinc dross image recognition and classification method
  • Zinc dross image recognition and classification method

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Embodiment Construction

[0043] The embodiment of the present application solves the problem of lack of flexibility in visual slag removal in the existing slag removal operation by providing a zinc slag image recognition and classification method.

[0044] The technical solution of the embodiment of the present application is to solve the above-mentioned technical problems, and the general idea is as follows:

[0045] 1) Preprocessing of the zinc pot image dataset. Due to the complex background of the slag removal scene and the possibility of noise in the captured pictures, it is necessary to denoise the pictures and extract the regions of interest. The gray values ​​of the uninteresting regions in the pictures are all set to 0, and the other regions remain unchanged.

[0046]2) Cut the pretreated zinc pot picture into small pictures and label them. Considering that the on-site visual sensor of the slag removal robot is fixed, and the size of the zinc pot and the actuator of the slag removal robot is...

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Abstract

The invention discloses a zinc dross image recognition and classification method, which belongs to the technical field of image processing and dross fishing, and comprises the following steps: preprocessing a zinc pot image data set; cutting the preprocessed picture into small pieces of pictures, and labeling; making the cut small pictures into a training set, a verification set and a test set; training the training set by adopting a convolutional neural network and testing performance; and identifying and classifying the zinc dross images by using the debugged network. The invention providesa visual zinc dross identification scheme for an existing dross fishing robot, and compared with a full-coverage dross fishing and blind fishing mode, the operation efficiency is improved, and the dross fishing cost is reduced.

Description

technical field [0001] The invention belongs to the technical field of slag removal, and in particular relates to a method for identifying and classifying zinc slag images. Background technique [0002] Hot-dip galvanizing is also called hot-dip galvanizing and hot-dip galvanizing. It is an effective metal anti-corrosion method. It is mainly used in metal structure facilities in various industries. In the process, the zinc layer is attached to the surface of the steel member, so as to achieve the purpose of anticorrosion. During the galvanizing process, due to the continuous melting of iron into the zinc solution, the uneven composition and temperature of the zinc pot, and the oxidation caused by air knife injection, the generation of zinc dross is inevitable. Zinc slag defects on the surface of hot-dip galvanized strip steel become one of the main quality defects of hot-dip galvanized products, which seriously affects the appearance quality of hot-dip galvanized products. ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06K9/32G06K9/40G06K9/46G06K9/62G06N3/04
CPCG06V20/10G06V10/30G06V10/25G06V10/40G06N3/045G06F18/214G06F18/24
Inventor 熊凌张振洲陈刚李克波吴怀宇但斌斌程磊陈洋陈志环陈琳郑秀娟
Owner WUHAN UNIV OF SCI & TECH
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