CN112686250A - Coal gangue classification method, device, equipment and storage medium - Google Patents
Coal gangue classification method, device, equipment and storage medium Download PDFInfo
- Publication number
- CN112686250A CN112686250A CN202011543765.1A CN202011543765A CN112686250A CN 112686250 A CN112686250 A CN 112686250A CN 202011543765 A CN202011543765 A CN 202011543765A CN 112686250 A CN112686250 A CN 112686250A
- Authority
- CN
- China
- Prior art keywords
- coal gangue
- classification
- coal
- classified
- image information
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 239000003245 coal Substances 0.000 title claims abstract description 147
- 238000000034 method Methods 0.000 title claims abstract description 31
- 238000003860 storage Methods 0.000 title claims abstract description 12
- OKTJSMMVPCPJKN-UHFFFAOYSA-N Carbon Chemical compound [C] OKTJSMMVPCPJKN-UHFFFAOYSA-N 0.000 claims abstract description 25
- 229910052799 carbon Inorganic materials 0.000 claims abstract description 25
- 238000004590 computer program Methods 0.000 claims description 10
- 239000010879 coal refuse Substances 0.000 claims description 7
- 239000002994 raw material Substances 0.000 description 3
- 230000002411 adverse Effects 0.000 description 2
- 238000002485 combustion reaction Methods 0.000 description 2
- 238000010586 diagram Methods 0.000 description 2
- 230000000694 effects Effects 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
- 239000000463 material Substances 0.000 description 2
- 230000002269 spontaneous effect Effects 0.000 description 2
- 238000009825 accumulation Methods 0.000 description 1
- 230000005540 biological transmission Effects 0.000 description 1
- 238000005261 decarburization Methods 0.000 description 1
- 230000007613 environmental effect Effects 0.000 description 1
- 239000012467 final product Substances 0.000 description 1
- 230000007774 longterm Effects 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
- 238000005065 mining Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000003062 neural network model Methods 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 238000010248 power generation Methods 0.000 description 1
- 239000000047 product Substances 0.000 description 1
- NIFIFKQPDTWWGU-UHFFFAOYSA-N pyrite Chemical compound [Fe+2].[S-][S-] NIFIFKQPDTWWGU-UHFFFAOYSA-N 0.000 description 1
- 229910052683 pyrite Inorganic materials 0.000 description 1
- 239000011028 pyrite Substances 0.000 description 1
- 239000004065 semiconductor Substances 0.000 description 1
- 150000004763 sulfides Chemical class 0.000 description 1
- 230000000007 visual effect Effects 0.000 description 1
- 239000002699 waste material Substances 0.000 description 1
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 description 1
Images
Landscapes
- Information Retrieval, Db Structures And Fs Structures Therefor (AREA)
Abstract
The present disclosure provides a coal gangue classification method, apparatus, device and storage medium, the method comprising: establishing a coal gangue classification identification model according to different carbon contents of coal gangue; acquiring image information of the coal gangue to be classified; and comparing the acquired image information of the coal gangue to be classified with the coal gangue classification identification model, marking the classification of the coal gangue corresponding to the classification to be classified and outputting. The coal gangue is divided into different categories according to different carbon contents, so that the coal gangue of different categories respectively enters different subsequent processes, and the comprehensive utilization economic benefit of the coal gangue is improved.
Description
Technical Field
The present disclosure relates to the field of image recognition technologies, and in particular, to a coal gangue classification method, apparatus, device, and storage medium.
Background
China is a coal-rich country, a large amount of coal gangue is generated in the coal production process, and if the coal gangue cannot be timely treated and reasonably utilized, serious environmental problems and resource waste are caused. At present, 45 hundred million tons of coal gangue are accumulated in China, 1600 coal gangue hills with large scale occupy 1.5 million hectares of land, and the accumulation amount is increased gradually at a speed of 1.5-2.0 hundred million tons every year. The long-term stacking of the coal gangue not only occupies a large amount of land, but also pollutes the atmosphere and water sources after sulfides contained in the coal gangue are emitted, thereby causing serious consequences. The pyrite contained in the coal gangue is easy to be oxidized by air, the released heat can promote the coal contained in the coal gangue to be weathered to be spontaneous combustion, and the spontaneous combustion of the coal gangue can cause serious pollution and harm to mining areas and surrounding environments. The comprehensive utilization of coal gangue is not slow. In the prior art, the coal gangue is stacked and stored roughly, if the coal gangue is directly and comprehensively utilized without classification, adverse effects are brought to subsequent processes, and the quality of final products is reduced.
Disclosure of Invention
In order to solve at least one of the above technical problems, the present disclosure provides a coal gangue classification method, apparatus, device and storage medium.
According to one aspect of the disclosure, a coal gangue classification method comprises the following steps:
establishing a coal gangue classification identification model according to different carbon contents of coal gangue;
acquiring image information of the coal gangue to be classified;
and comparing the acquired image information of the coal gangue to be classified with the coal gangue classification identification model, marking the classification of the coal gangue corresponding to the classification to be classified and outputting.
According to at least one embodiment of the present disclosure, the specific process of establishing the coal gangue classification identification model is as follows:
acquiring image information of coal gangue with different carbon contents, and marking positions;
and constructing an image recognition model of coal gangue with different carbon contents, outputting position image information marked with coal gangue with different carbon contents as a target of the recognition model, inputting original image information as a target, and training the recognition model.
According to at least one embodiment of the present disclosure, the image information is a picture or a video image.
According to at least one embodiment of the present disclosure, the coal gangue classification and identification model includes three categories of coal gangue, and the carbon contents C of the three categories of coal gangue are: c of the I-type coal gangue is less than 5 percent, C of the II-type coal gangue is more than or equal to 5 percent and less than 20 percent, and C of the III-type coal gangue is more than or equal to 20 percent.
According to an aspect of the present disclosure, a coal gangue classification device includes:
the image acquisition module is used for acquiring image information of the coal gangue to be classified;
and the data processing module is used for establishing a coal gangue classification identification model according to different carbon contents of the coal gangue, comparing the image information of the coal gangue to be classified with the coal gangue classification identification model, marking the position of the coal gangue corresponding to the coal gangue to be classified and outputting the position.
According to at least one embodiment of the present disclosure, further comprising:
and the conveying module is used for conveying the coal gangue to be classified.
According to at least one embodiment of the present disclosure, the image acquisition module is an industrial camera or a camera device.
According to at least one embodiment of the present disclosure, the image capture module is a handheld image capture device.
According to one aspect of the disclosure, a computer device comprises a memory and a processor, wherein the memory stores a computer program, and the processor implements the coal gangue classification method according to any one of the above items when executing the computer program.
According to an aspect of the disclosure, a computer-readable storage medium stores a computer program, which when executed by a processor implements the coal gangue classification method of any one of the above.
Drawings
The accompanying drawings, which are included to provide a further understanding of the disclosure and are incorporated in and constitute a part of this specification, illustrate exemplary embodiments of the disclosure and together with the description serve to explain the principles of the disclosure.
Fig. 1 is a schematic flow diagram of a coal gangue classification method according to an embodiment of the present disclosure.
Fig. 2 is a schematic flow chart of establishing a coal gangue classification identification model in the coal gangue classification method according to the embodiment of the disclosure.
Fig. 3 is a schematic view of a first embodiment of a coal refuse sorting apparatus according to the present disclosure.
Fig. 4 is a schematic view of a second embodiment of a coal refuse sorting apparatus according to the present disclosure.
Fig. 5 is a schematic diagram of a computer device according to an embodiment of the present disclosure.
Detailed Description
The present disclosure will be described in further detail with reference to the drawings and embodiments. It is to be understood that the specific embodiments described herein are for purposes of illustration only and are not to be construed as limitations of the present disclosure. It should be further noted that, for the convenience of description, only the portions relevant to the present disclosure are shown in the drawings.
It should be noted that the embodiments and features of the embodiments in the present disclosure may be combined with each other without conflict. The present disclosure will be described in detail below with reference to the accompanying drawings in conjunction with embodiments.
In the prior art, the coal gangue is not stacked according to different carbon contents in a classified manner, and if the coal gangue is directly used, the subsequent process is adversely affected, and the performance of a final product is reduced. Therefore, the coal gangue classification method based on the visual identification technology is provided, the coal gangue is classified into different categories according to different carbon contents, the coal gangue of different categories is subjected to different subsequent processes, and the comprehensive utilization economic benefit of the coal gangue is improved.
As shown in fig. 1, according to a first embodiment of the present disclosure, there is provided a coal gangue classification method, including the steps of:
s100, establishing a coal gangue classification identification model according to different carbon contents of coal gangue;
s200, acquiring image information of the coal gangue to be classified;
and S300, comparing the acquired image information of the coal gangue to be classified with the coal gangue classification identification model, marking the classification of the coal gangue corresponding to be classified and outputting.
The coal gangue classification and identification model is used for distinguishing the carbon content of coal gangue so as to divide the coal gangue into different categories, the categories of the coal gangue are determined according to subsequent processes, according to one embodiment of the disclosure, the coal gangue classification and identification model comprises three categories of coal gangue, and the carbon content C of the coal gangue of the three categories is respectively: c of the I-type coal gangue is less than 5 percent, C of the II-type coal gangue is more than or equal to 5 percent and less than 20 percent, and C of the III-type coal gangue is more than or equal to 20 percent. Wherein, the I-type coal gangue can be directly used as a raw material for preparing ceramsite lightweight aggregate from coal gangue; the II-class coal gangue can be used as a roadbed raw material or a ceramsite light aggregate raw material after a decarburization pretreatment process; the III-class coal gangue is used for coal gangue power generation or other purposes.
The coal gangue image information of the three categories can be used as the input of a coal gangue classification identification model, and the output result can obtain the I-class coal gangue, the II-class coal gangue, the III-class coal gangue, the position information of each category of coal gangue and the like.
The coal gangue classification and identification model can be obtained by training the existing neural network model through coal gangue samples with different carbon contents, or the coal gangue classification and identification model is established in the following way, so that the coal gangue classification and identification model meeting the actual requirement is obtained
As shown in fig. 2, according to an embodiment of the present disclosure, a specific process of establishing the coal gangue classification recognition model is as follows:
acquiring image information of coal gangue with different carbon contents, and marking positions;
and constructing an image recognition model of coal gangue with different carbon contents, outputting position image information marked with coal gangue with different carbon contents as a target of the recognition model, inputting original image information as a target, and training the recognition model.
The acquired image information of the coal gangue with different carbon contents can be pictures or video images, and correspondingly, the image information of the coal gangue to be classified can be pictures or video images, and is determined according to an image acquisition device.
As shown in fig. 3, according to an aspect of the present disclosure, a coal refuse sorting apparatus 400 includes:
the image acquisition module 401 is configured to acquire image information of coal gangue to be classified;
and the data processing module 402 is configured to establish a coal gangue classification identification model according to different carbon contents of the coal gangue, compare image information of the coal gangue to be classified with the coal gangue classification identification model, mark a position corresponding to the coal gangue to be classified, and output the position.
As shown in fig. 4, according to an embodiment of the present disclosure, further includes: and the conveying module 403 is used for conveying the coal gangue to be classified. The conveying module can be an existing conveying device such as a belt conveyor. The image acquisition module can be installed in the transport module top, and the transport module lasts to the preceding gangue of waiting to classify, when waiting to classify the gangue and pass through image acquisition module below, gathers the image information of waiting to classify the gangue by image acquisition module, and image acquisition module conveys the image information transmission of the gangue of waiting to classify to data processing module and compares.
According to one embodiment of the disclosure, the image acquisition module is an industrial camera or a camera device, so that pictures or video information of the coal gangue can be obtained.
According to an embodiment of the present disclosure, the image acquisition module is a handheld image acquisition device, so that the coal gangue classification device 400 of the present disclosure can be handheld and is convenient to use in the field and other environments.
The coal gangue classification device 400 provided in this embodiment may be used to execute the coal gangue classification method, and the principle and the technical effect are similar, which are not described herein again.
As shown in fig. 5, according to an aspect of the present disclosure, a computer device 500 includes a memory 501 and a processor 502, where the memory 501 stores a computer program, and the processor 502 implements the coal gangue classification method according to any one of the above embodiments when executing the computer program. The memory 501 stores programs and data necessary for the operation of the computer device 500, and the memory 501 and the processor 502 are connected to each other through a bus. Further, the computer device 500 further comprises an input module 504 for inputting information such as data, for example, a keyboard, a mouse, etc.; the computer device 500 further comprises an output module 503, such as a display, for outputting information, such as images.
According to an aspect of the present disclosure, a computer-readable storage medium stores a computer program, and the computer program is executed by a processor to implement the coal gangue classification method according to any one of the above embodiments. The computer readable storage medium may be a computer readable signal medium or a computer readable storage medium or a combination of both. The computer readable storage medium can be an electronic, magnetic, optical, electromagnetic, infrared, semiconductor system, apparatus, or device, or a combination of one or more of the foregoing, such as a computer diskette, hard disk, or the like.
In the description herein, reference to the description of the terms "one embodiment/mode," "some embodiments/modes," "example," "specific example," or "some examples," etc., means that a particular feature, structure, material, or characteristic described in connection with the embodiment/mode or example is included in at least one embodiment/mode or example of the application. In this specification, the schematic representations of the terms used above are not necessarily intended to be the same embodiment/mode or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments/modes or examples. Furthermore, the various embodiments/aspects or examples and features of the various embodiments/aspects or examples described in this specification can be combined and combined by one skilled in the art without conflicting therewith.
Furthermore, the terms "first", "second" and "first" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one such feature. In the description of the present application, "plurality" means at least two, e.g., two, three, etc., unless specifically limited otherwise.
It will be understood by those skilled in the art that the foregoing embodiments are merely for clarity of illustration of the disclosure and are not intended to limit the scope of the disclosure. Other variations or modifications may occur to those skilled in the art, based on the foregoing disclosure, and are still within the scope of the present disclosure.
Claims (10)
1. A coal gangue classification method is characterized by comprising the following steps:
establishing a coal gangue classification identification model according to different carbon contents of coal gangue;
acquiring image information of the coal gangue to be classified;
and comparing the acquired image information of the coal gangue to be classified with the coal gangue classification identification model, marking the classification of the coal gangue corresponding to the classification to be classified and outputting.
2. The coal gangue classification method of claim 1, wherein the concrete process of establishing the coal gangue classification identification model is as follows:
acquiring image information of coal gangue with different carbon contents, and marking positions;
and constructing an image recognition model of coal gangue with different carbon contents, outputting position image information marked with coal gangue with different carbon contents as a target of the recognition model, inputting original image information as a target, and training the recognition model.
3. The coal refuse classification method of claim 1, characterized in that the image information is a picture or a video image.
4. The coal gangue classification method of claim 1, wherein the coal gangue classification and identification model comprises three categories of coal gangue, and the carbon contents C of the three categories of coal gangue are respectively: c of the I-type coal gangue is less than 5 percent, C of the II-type coal gangue is more than or equal to 5 percent and less than 20 percent, and C of the III-type coal gangue is more than or equal to 20 percent.
5. A coal gangue classification device is characterized by comprising:
the image acquisition module is used for acquiring image information of the coal gangue to be classified;
and the data processing module is used for establishing a coal gangue classification identification model according to different carbon contents of the coal gangue, comparing the image information of the coal gangue to be classified with the coal gangue classification identification model, marking the position of the coal gangue corresponding to the coal gangue to be classified and outputting the position.
6. The coal refuse classification apparatus of claim 5, further comprising:
and the conveying module is used for conveying the coal gangue to be classified.
7. The coal refuse classification device of claim 5 or 6, characterized in that the image acquisition module is an industrial camera or a camera device.
8. The coal refuse classification device of claim 5 or 6, characterized in that the image acquisition module is a hand-held image acquisition device.
9. A computer device, characterized by comprising a memory and a processor, the memory storing a computer program, the processor implementing the coal gangue classification method of any one of claims 1-4 when executing the computer program.
10. A computer-readable storage medium, characterized in that the computer-readable storage medium stores a computer program which, when executed by a processor, implements the coal gangue classification method of any one of claims 1-4.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011543765.1A CN112686250A (en) | 2020-12-23 | 2020-12-23 | Coal gangue classification method, device, equipment and storage medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011543765.1A CN112686250A (en) | 2020-12-23 | 2020-12-23 | Coal gangue classification method, device, equipment and storage medium |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN112686250A true CN112686250A (en) | 2021-04-20 |
Family
ID=75451455
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202011543765.1A Pending CN112686250A (en) | 2020-12-23 | 2020-12-23 | Coal gangue classification method, device, equipment and storage medium |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN112686250A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115646848A (en) * | 2022-10-21 | 2023-01-31 | 微山金源煤矿 | Intelligent classification method and system for coal mine |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110441320A (en) * | 2019-08-05 | 2019-11-12 | 北京泰豪信息科技有限公司 | A kind of gangue detection method, apparatus and system |
| CN110516712A (en) * | 2019-08-01 | 2019-11-29 | 仲恺农业工程学院 | Insect pest image-recognizing method, insect pest monitoring method, device, equipment and medium |
| CN111077093A (en) * | 2020-01-10 | 2020-04-28 | 安徽理工大学 | Method and device for quickly detecting coal gangue based on multispectral technology |
| CN111318461A (en) * | 2020-03-11 | 2020-06-23 | 河南理工大学 | Gangue letter sorting system based on machine vision |
| CN111709935A (en) * | 2020-06-17 | 2020-09-25 | 西安科技大学 | Real-time coal gangue positioning and identifying method for ground moving belt |
| CN112070168A (en) * | 2020-09-10 | 2020-12-11 | 深兰人工智能芯片研究院（江苏）有限公司 | Coal sorting method and device |
-
2020
- 2020-12-23 CN CN202011543765.1A patent/CN112686250A/en active Pending
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110516712A (en) * | 2019-08-01 | 2019-11-29 | 仲恺农业工程学院 | Insect pest image-recognizing method, insect pest monitoring method, device, equipment and medium |
| CN110441320A (en) * | 2019-08-05 | 2019-11-12 | 北京泰豪信息科技有限公司 | A kind of gangue detection method, apparatus and system |
| CN111077093A (en) * | 2020-01-10 | 2020-04-28 | 安徽理工大学 | Method and device for quickly detecting coal gangue based on multispectral technology |
| CN111318461A (en) * | 2020-03-11 | 2020-06-23 | 河南理工大学 | Gangue letter sorting system based on machine vision |
| CN111709935A (en) * | 2020-06-17 | 2020-09-25 | 西安科技大学 | Real-time coal gangue positioning and identifying method for ground moving belt |
| CN112070168A (en) * | 2020-09-10 | 2020-12-11 | 深兰人工智能芯片研究院（江苏）有限公司 | Coal sorting method and device |
Non-Patent Citations (1)
| Title |
|---|
| 孙 坚等: "工业固体废弃物资源综合利用技术现状", 《材料导报Ａ：综述篇》, vol. 26, no. 6, pages 105 - 109 * |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115646848A (en) * | 2022-10-21 | 2023-01-31 | 微山金源煤矿 | Intelligent classification method and system for coal mine |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN110363102B (en) | Object identification processing method and device for PDF (Portable document Format) file | |
| CN111626117B (en) | Garbage sorting system and method based on target detection | |
| Bobulski et al. | PET waste classification method and plastic waste DataBase-WaDaBa | |
| Wu et al. | An inspection and classification method for chip solder joints using color grads and Boolean rules | |
| CN112686250A (en) | Coal gangue classification method, device, equipment and storage medium | |
| CN104317946A (en) | Multi-key image-based image content retrieval method | |
| CN105868269A (en) | Precise image searching method based on region convolutional neural network | |
| CN112893159A (en) | Coal gangue sorting method based on image recognition | |
| CN108170697B (en) | International trade file processing method and system and server | |
| EP0780782A3 (en) | Separation of touching characters in optical character recognition | |
| CN105095468A (en) | Novel image retrieval method and system | |
| Huang et al. | Recognition of blurring alphabet character on timing pulley drawing based on HALCON image processing technology | |
| CN112529513A (en) | Intelligent seal checking method and system | |
| Romero et al. | Enhanced plastic recycling using RGB+ Depth fusion with MassFaster and MassMask R-CNN | |
| CN107790403B (en) | A kind of sorting system of Financial Billing and the method for sorting of Financial Billing | |
| CN109684942A (en) | A kind of Full-automatic tableware method for sorting of view-based access control model identification | |
| CN116150474A (en) | Comment ordering method and device, electronic equipment and readable storage medium | |
| CN201796362U (en) | Automatic file classifying system | |
| Ghosh et al. | Text/non-text scene image classification using deep ensemble network | |
| CN112871745A (en) | Coal gangue classification model obtaining method, coal gangue classification model obtaining device and coal gangue classification method equipment | |
| Sundar | A Novel Low-Cost Approach For Detection, Classification, and Quantification of Microplastic Pollution in Freshwater Ecosystems using IoT devices and Instance Segmentation | |
| Amao | Automating taxonomic and systematic search of benthic foraminifera in an online database. | |
| Jiawang et al. | Fast plug-in capacitors polarity detection with morphology and SVM fusion method in automatic optical inspection system | |
| CN108596280A (en) | Image identification method for literature search | |
| Koyanaka et al. | Individual model identification of waste digital devices by the combination of CNN-based image recognition and measured values of mass and 3D shape features |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |