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Coal and coal gangue sorting system and method based on polarization imaging

A polarization imaging and sorting system technology, applied in sorting and other directions, can solve the problems of being easily affected by ambient light, dust pollution, low recognition rate, etc. The effect of high recognition rate

Active Publication Date: 2022-07-19
HOHAI UNIV CHANGZHOU
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AI Technical Summary

Problems solved by technology

Manual sorting is labor-intensive and low in production efficiency
The wet separation method consumes a lot of water and electricity, and the dust generated is polluting
The X-ray method has problems such as radiation pollution and bulky equipment
The machine vision method has become the future development direction because of its high degree of automation and no pollution. However, the existing machine vision methods still have problems such as low recognition rate and easy to be affected by ambient light.

Method used

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  • Coal and coal gangue sorting system and method based on polarization imaging
  • Coal and coal gangue sorting system and method based on polarization imaging
  • Coal and coal gangue sorting system and method based on polarization imaging

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Effect test

Embodiment 1

[0201] The sample set is divided into training set and test set according to the ratio of 2:8. Input the training set data into the support vector machine to get the classification model, and use the test set data to calculate the classification accuracy.

[0202] Collect 100 polarization intensity images of coal and gangue samples respectively, divide them into training set and test set according to the ratio of 2:8, and use the histogram cross kernel as the kernel function to carry out support vector machine modeling and classification, among which 80 coal samples predict 5 mistakes were made, and 0 of the 80 coal gangue samples were wrongly predicted. The results showed that the classification accuracy was 96.875%, the false alarm rate was 3.125%, and the missed detection rate was 0%.

[0203] The polarization imaging-based coal and coal gangue sorting system and sorting method provided by the present invention have the same effect on the sorting of objects of other materia...

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PUM

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Abstract

The invention belongs to the technical field of coal sorting, and specifically provides a system and method for sorting coal and coal gangue based on polarization imaging. The system includes a vibrating screen, a conveyor belt, a photoelectric switch, a light box, a polarization camera, a control cabinet, an industrial computer, Parallel robot, coal gangue material frame and coal material frame. The invention adopts the polarization camera to synchronously collects polarization intensity images of four angles of reflected light from coal and coal gangue surfaces, calculates the average polarization intensity image, polarization angle image and polarization degree image, and extracts 10 features of the three images to form a 30-dimensional image. Eigenvectors for sorting coal and coal gangue. The present invention adopts polarization intensity images in four directions, which improves the accuracy of classification features compared with ordinary images or polarization intensity images in a single direction.

Description

technical field [0001] The invention belongs to the technical field of coal sorting, and in particular relates to a system and method for sorting coal and coal gangue based on polarization imaging. Background technique [0002] In the process of coal mining, a large amount of solid waste such as coal gangue needs to be sorted out. At present, the sorting methods at home and abroad are mainly manual sorting, wet sorting, ray method and machine vision method. Manual sorting has high labor intensity and low production efficiency. The wet separation method consumes a lot of water and electricity, and the dust produced is polluting. The radiation method has problems such as radiation pollution and heavy equipment. Machine vision methods have become the future development direction because of their high degree of automation and pollution-free. However, the existing machine vision methods still have problems such as low recognition rate and easy to be affected by ambient light. ...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): B07C5/34B07C5/02B07C5/36
CPCB07C5/3422B07C5/3425B07C5/02B07C5/361B07C2501/0063
Inventor 谭治英王子龙赵宝来费仲文沙刘力刘拓张瀛龚涛徐孝彬骆敏舟
Owner HOHAI UNIV CHANGZHOU
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