CN116510901A - Intelligent household garbage sorting system - Google Patents
Intelligent household garbage sorting system Download PDFInfo
- Publication number
- CN116510901A CN116510901A CN202310470206.XA CN202310470206A CN116510901A CN 116510901 A CN116510901 A CN 116510901A CN 202310470206 A CN202310470206 A CN 202310470206A CN 116510901 A CN116510901 A CN 116510901A
- Authority
- CN
- China
- Prior art keywords
- garbage
- module
- magnetic separation
- household garbage
- classification
- 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
- 238000007885 magnetic separation Methods 0.000 claims abstract description 31
- 238000012216 screening Methods 0.000 claims abstract description 21
- 238000011084 recovery Methods 0.000 claims abstract description 15
- 239000000463 material Substances 0.000 claims abstract description 14
- 239000002184 metal Substances 0.000 claims abstract description 14
- 229910052751 metal Inorganic materials 0.000 claims abstract description 14
- 239000002699 waste material Substances 0.000 claims abstract description 14
- XEEYBQQBJWHFJM-UHFFFAOYSA-N Iron Chemical compound [Fe] XEEYBQQBJWHFJM-UHFFFAOYSA-N 0.000 claims abstract description 10
- 238000000926 separation method Methods 0.000 claims abstract description 8
- 239000007788 liquid Substances 0.000 claims abstract description 6
- 239000011521 glass Substances 0.000 claims abstract description 5
- 239000003864 humus Substances 0.000 claims abstract description 5
- 229910052742 iron Inorganic materials 0.000 claims abstract description 5
- 150000002739 metals Chemical class 0.000 claims abstract description 5
- -1 organic matters Substances 0.000 claims abstract description 5
- 229920003023 plastic Polymers 0.000 claims abstract description 5
- 239000004033 plastic Substances 0.000 claims abstract description 5
- 239000004753 textile Substances 0.000 claims abstract description 5
- 238000002203 pretreatment Methods 0.000 claims abstract description 4
- 239000002689 soil Substances 0.000 claims abstract description 4
- 238000013135 deep learning Methods 0.000 claims description 7
- 238000001514 detection method Methods 0.000 claims description 7
- 238000004064 recycling Methods 0.000 claims description 7
- 238000005516 engineering process Methods 0.000 claims description 5
- 238000012545 processing Methods 0.000 claims description 5
- 230000011218 segmentation Effects 0.000 claims description 5
- 238000001914 filtration Methods 0.000 claims description 4
- 238000013461 design Methods 0.000 claims description 3
- 238000007781 pre-processing Methods 0.000 claims description 3
- 238000005070 sampling Methods 0.000 claims description 3
- 230000008878 coupling Effects 0.000 claims description 2
- 238000010168 coupling process Methods 0.000 claims description 2
- 238000005859 coupling reaction Methods 0.000 claims description 2
- 230000002708 enhancing effect Effects 0.000 claims description 2
- 238000013528 artificial neural network Methods 0.000 abstract description 3
- 239000010791 domestic waste Substances 0.000 abstract description 2
- 238000011161 development Methods 0.000 description 3
- 230000018109 developmental process Effects 0.000 description 3
- 238000000605 extraction Methods 0.000 description 3
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 230000004075 alteration Effects 0.000 description 1
- 238000004458 analytical method Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000003912 environmental pollution Methods 0.000 description 1
- 230000004927 fusion Effects 0.000 description 1
- 230000005389 magnetism Effects 0.000 description 1
- 238000007726 management method Methods 0.000 description 1
- 238000000034 method Methods 0.000 description 1
- 230000001737 promoting effect Effects 0.000 description 1
- 239000007787 solid Substances 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
Classifications
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B03—SEPARATION OF SOLID MATERIALS USING LIQUIDS OR USING PNEUMATIC TABLES OR JIGS; MAGNETIC OR ELECTROSTATIC SEPARATION OF SOLID MATERIALS FROM SOLID MATERIALS OR FLUIDS; SEPARATION BY HIGH-VOLTAGE ELECTRIC FIELDS
- B03C—MAGNETIC OR ELECTROSTATIC SEPARATION OF SOLID MATERIALS FROM SOLID MATERIALS OR FLUIDS; SEPARATION BY HIGH-VOLTAGE ELECTRIC FIELDS
- B03C1/00—Magnetic separation
- B03C1/02—Magnetic separation acting directly on the substance being separated
- B03C1/30—Combinations with other devices, not otherwise provided for
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B02—CRUSHING, PULVERISING, OR DISINTEGRATING; PREPARATORY TREATMENT OF GRAIN FOR MILLING
- B02C—CRUSHING, PULVERISING, OR DISINTEGRATING IN GENERAL; MILLING GRAIN
- B02C23/00—Auxiliary methods or auxiliary devices or accessories specially adapted for crushing or disintegrating not provided for in preceding groups or not specially adapted to apparatus covered by a single preceding group
- B02C23/08—Separating or sorting of material, associated with crushing or disintegrating
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B07—SEPARATING SOLIDS FROM SOLIDS; SORTING
- B07C—POSTAL SORTING; SORTING INDIVIDUAL ARTICLES, OR BULK MATERIAL FIT TO BE SORTED PIECE-MEAL, e.g. BY PICKING
- B07C5/00—Sorting according to a characteristic or feature of the articles or material being sorted, e.g. by control effected by devices which detect or measure such characteristic or feature; Sorting by manually actuated devices, e.g. switches
- B07C5/34—Sorting according to other particular properties
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B07—SEPARATING SOLIDS FROM SOLIDS; SORTING
- B07C—POSTAL SORTING; SORTING INDIVIDUAL ARTICLES, OR BULK MATERIAL FIT TO BE SORTED PIECE-MEAL, e.g. BY PICKING
- B07C5/00—Sorting according to a characteristic or feature of the articles or material being sorted, e.g. by control effected by devices which detect or measure such characteristic or feature; Sorting by manually actuated devices, e.g. switches
- B07C5/36—Sorting apparatus characterised by the means used for distribution
- B07C5/361—Processing or control devices therefor, e.g. escort memory
Landscapes
- Engineering & Computer Science (AREA)
- Food Science & Technology (AREA)
- Processing Of Solid Wastes (AREA)
Abstract
The invention discloses an intelligent household garbage sorting system which consists of a screening module, a magnetic separation module, an image acquisition module, a secondary magnetic separation module, a classification module, a crushing module, a secondary screening module and a recovery tank; the garbage sorting system divides the household garbage into garbage which is classified into humus soil, waste plastic, organic matters, iron products, glass, nonferrous metals, waste textiles, electronic and electric products and the like, wherein the classification rate is 95%; the screening system is used for pre-treatment before garbage enters the system, so that solid-liquid separation of materials is realized, and pretreatment is completed. The invention automatically identifies different kinds of household garbage, and obtains the deep and data set specific characteristic representation through the learning of classifying a large amount of garbage based on the artificial neural network and the representation learning. Through the screening, the magnetic separation, the secondary screening, the automatic continuous increase of magnetic separation is classified and recycle to the kind of domestic waste to can sort better.
Description
Technical Field
The invention belongs to the technical field of garbage classification, and particularly relates to an intelligent household garbage sorting system.
Background
The rapid population growth, the economic high-speed development and the continuous improvement of the urban level lead the urban garbage produced by China every year to be increased, thereby not only causing the resource waste, but also generating the environmental pollution. Therefore, garbage classification is continuously paid attention to by people in various countries and communities, and the state-to-place government has brought out urban household garbage classification as an important part of sustainable development strategies and related policies, so that the establishment of garbage treatment systems in classification throwing, classification collection, classification transportation and classification animal houses is required to be quickened, and household garbage classification is taken as an important measure for promoting green development.
Disclosure of Invention
The invention aims to provide an intelligent household garbage sorting system for solving the problems in the background technology.
In order to achieve the above purpose, the present invention provides the following technical solutions: an intelligent household garbage sorting system comprises a screening module, a magnetic separation module, an image acquisition module, a secondary magnetic separation module, a classification module, a crushing module, a secondary screening module and a recovery tank;
the garbage sorting system divides the household garbage into garbage which is classified into humus soil, waste plastic, organic matters, iron products, glass, nonferrous metals, waste textiles, electronic and electric products and the like, wherein the classification rate is 95%;
the screening system is used for pre-treatment before garbage enters the system, so that solid-liquid separation of materials is realized, and pretreatment is completed;
the magnetic separation unit is convenient and fast for recycling metal in the material, is of a transverse transportation conveyor belt structure, one end of the magnetic separation unit is connected with an outlet of the crushing unit of the separation system, the other end of the magnetic separation unit is a material outlet, the magnetic separation unit is connected with an inlet of the metal recovery unit, and after image recognition and crushing, secondary magnetic separation is carried out, and materials such as magnetic metal are recovered, and the recovery rate is 85%;
the household garbage intelligent sorting system is characterized in that a sorting garbage channel is arranged below a storage plate in the design of the household garbage intelligent sorting system, a digital steering engine based on PWM signal control is adopted in the system, and after power-on, the household garbage intelligent sorting system is initialized through a timer, an I/O port and an AD sampling. And changing the duty cycle of the corresponding timer channel according to the angle, generating a steering engine control signal, driving the steering engine to rotate to the corresponding angle, determining the type of garbage, and then driving the steering engine to rotate and delivering the determined type of garbage into the corresponding garbage recycling bin, thereby completing the identification and classification operation.
Furthermore, the organic coupling of the multiple classification means applies a deep learning algorithm to carry out intelligent detection classification on the household garbage.
Furthermore, preprocessing is performed before the garbage image is analyzed, irrelevant information in the image is eliminated after the garbage image is subjected to processing steps such as filtering, enhancing, segmentation, extracting characteristic values and the like, useful real information is recovered, the detectability of relevant information is enhanced, garbage data is simplified, and the target detection and classification are performed by adopting a deep learning-based technology.
Furthermore, the secondary screening unit is used for sending the re-screened garbage to the recovery pool, collecting the household garbage in a sorting mode and reducing the number of waste treatment.
The beneficial technical effects of the invention are as follows:
the invention automatically identifies different kinds of household garbage, and obtains the deep and data set specific characteristic representation through the learning of classifying a large amount of garbage based on the artificial neural network and the representation learning. Through the screening, the magnetic separation, the secondary screening, the automatic continuous increase of magnetic separation is classified and recycle to the kind of domestic waste to can sort better. The labor cost is greatly reduced, the problems of random stacking of garbage and household garbage landfill are overcome, the household garbage can be reused, and the automatic management is realized.
Drawings
The accompanying drawings are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate the invention and together with the embodiments of the invention, serve to explain the invention.
FIG. 1 is a flow chart of an intelligent household garbage equipment system of the invention;
fig. 2 is a block diagram of an image acquisition module of the intelligent household garbage equipment system.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Referring to fig. 1-2, the present invention provides a technical scheme of a threat information acquisition fusion system based on a multi-source network space: the device consists of a screening module, a magnetic separation module, an image acquisition module, a secondary magnetic separation module, a classification module, a crushing module, a secondary screening module and a recovery tank;
the garbage sorting system divides the household garbage into garbage which is classified into humus soil, waste plastic, organic matters, iron products, glass, nonferrous metals, waste textiles, electronic and electric products and the like, wherein the classification rate is 95%;
the screening system is used for pre-treatment before garbage enters the system, so that solid-liquid separation of materials is realized, and pretreatment is completed;
the magnetic separation unit is convenient and fast for recycling metal in the material, is of a transverse transportation conveyor belt structure, one end of the magnetic separation unit is connected with an outlet of the crushing unit of the separation system, the other end of the magnetic separation unit is a material outlet, the magnetic separation unit is connected with an inlet of the metal recovery unit, and after image recognition and crushing, secondary magnetic separation is carried out, and materials such as magnetic metal are recovered, and the recovery rate is 85%;
the household garbage intelligent sorting system is characterized in that a sorting garbage channel is arranged below a storage plate in the design of the household garbage intelligent sorting system, a digital steering engine based on PWM signal control is adopted in the system, and after power-on, the household garbage intelligent sorting system is initialized through a timer, an I/O port and an AD sampling. And changing the duty cycle of the corresponding timer channel according to the angle, generating a steering engine control signal, driving the steering engine to rotate to the corresponding angle, determining the type of garbage, and then driving the steering engine to rotate and delivering the determined type of garbage into the corresponding garbage recycling bin, thereby completing the identification and classification operation.
In this embodiment, the multiple classification means are organically coupled, and the deep learning algorithm is applied to perform intelligent detection classification on the household garbage.
In this embodiment, preprocessing is performed before the garbage image is analyzed, after the garbage image is subjected to processing steps such as filtering, enhancement, segmentation, feature value extraction and the like, irrelevant information in the image is eliminated, useful real information is recovered, the detectability of relevant information is enhanced, garbage data is simplified, and a deep learning-based technology is adopted to perform target detection and classification.
In the embodiment, the secondary screening unit is used for sending the garbage subjected to secondary screening to the recovery tank, collecting and gathering the household garbage in a sorting mode, and reducing the number of waste treatment.
The working principle and the using flow of the invention are as follows:
(1) The system firstly enters the screening module for solid-liquid separation of the household garbage, the liquid in the household garbage is recycled, the solid part enters the image acquisition module firstly, the household garbage is classified into humus (kitchen garbage), waste plastics, organic matters, iron products, glass, nonferrous metals, waste textiles, electronic and electric products and the like according to image recognition and comparison, the classification rate is up to 90 percent, and the household garbage is matched with the subsequent recycling pool;
(2) The classified garbage enters a crushing device for small crushing treatment, classified garbage is subjected to first magnetic separation, materials containing magnetism are classified and recycled, other household garbage is classified and enters a classification module, the rest garbage which is not treated enters a secondary magnetic separation module for second magnetic separation, and the secondary magnetic separation is carried out and enters a recovery tank for classification. Carrying out classified recovery treatment;
(3) After the infrared module detects the delivery state, the system image acquisition is switched into a normal working mode from a dormant mode, household garbage is delivered from an inlet of the equipment and enters an upper-layer object placing table, an image acquisition module is arranged at the top of the object placing table, a steering engine is connected to the bottom of the object placing table, the object placing table can be driven to rotate, images are acquired once every 45 degrees of rotation, the total acquisition is 5 times, the 5 times of image data are fused and spliced by a weighted average method, a complete garbage image without ghost is obtained, and accurate image data are provided for the next step of image identification and classification, as shown in fig. 2;
(4) Pretreatment is required before analysis (feature extraction, segmentation, matching, recognition, etc.) of the garbage image. After the garbage image is subjected to processing steps such as filtering, enhancement, segmentation, characteristic value extraction and the like, irrelevant information in the image is eliminated, useful real information is recovered, the detectability of related information is enhanced, garbage data is simplified to the maximum extent, and a deep learning-based technology is adopted for target detection and classification;
(5) In the equipment, a power module supplies power for a camera, a microprocessor core board and a steering engine, the microprocessor is used for data processing and sending commands to control the whole system to run, a classification module utilizes a neural network trained classifier for identifying and classifying household garbage, the steering engine is arranged in a garbage can to drive a storage board to rotate, a valve is arranged on the storage board, the lower part of the storage board corresponds to a plurality of garbage cans, the rotating angle of the steering engine can be adjusted after the garbage types are determined, the valve is opened, and classified delivery is realized.
The above is a preferred embodiment of the present invention, and a person skilled in the art can also make alterations and modifications to the above embodiment, therefore, the present invention is not limited to the above specific embodiment, and any obvious improvements, substitutions or modifications made by the person skilled in the art on the basis of the present invention are all within the scope of the present invention.
Claims (4)
1. An intelligent household garbage sorting system is characterized in that: the device consists of a screening module, a magnetic separation module, an image acquisition module, a secondary magnetic separation module, a classification module, a crushing module, a secondary screening module and a recovery tank;
the garbage sorting system divides the household garbage into garbage which is classified into humus soil, waste plastic, organic matters, iron products, glass, nonferrous metals, waste textiles, electronic and electric products and the like, wherein the classification rate is 95%;
the screening system is used for pre-treatment before garbage enters the system, so that solid-liquid separation of materials is realized, and pretreatment is completed;
the magnetic separation unit is convenient and fast for recycling metal in the material, is of a transverse transportation conveyor belt structure, one end of the magnetic separation unit is connected with an outlet of the crushing unit of the separation system, the other end of the magnetic separation unit is a material outlet, the magnetic separation unit is connected with an inlet of the metal recovery unit, and after image recognition and crushing, secondary magnetic separation is carried out, and materials such as magnetic metal are recovered, and the recovery rate is 85%;
the household garbage intelligent sorting system is characterized in that a sorting garbage channel is arranged below a storage plate in the design of the household garbage intelligent sorting system, a digital steering engine based on PWM signal control is adopted in the system, and after power-on, the household garbage intelligent sorting system is initialized through a timer, an I/O port and an AD sampling. And changing the duty cycle of the corresponding timer channel according to the angle, generating a steering engine control signal, driving the steering engine to rotate to the corresponding angle, determining the type of garbage, and then driving the steering engine to rotate and delivering the determined type of garbage into the corresponding garbage recycling bin, thereby completing the identification and classification operation.
2. The intelligent household garbage sorting system according to claim 1, wherein: and the organic coupling of the multiple classification means is used for carrying out intelligent detection classification on the household garbage by applying a deep learning algorithm.
3. The intelligent household garbage sorting system according to claim 1, wherein: before the garbage image is analyzed, preprocessing is carried out, irrelevant information in the garbage image is eliminated after the garbage image is subjected to processing steps such as filtering, enhancing, segmentation, extracting characteristic values and the like, useful real information is recovered, the detectability of relevant information is enhanced, garbage data is simplified, and the target detection and classification are carried out by adopting a technology based on deep learning.
4. The intelligent household garbage sorting system according to claim 1, wherein: the secondary screening unit is used for sending the re-screened garbage to the recovery tank, collecting and gathering household garbage in a sorting mode, and reducing the number of waste treatment.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310470206.XA CN116510901A (en) | 2023-04-27 | 2023-04-27 | Intelligent household garbage sorting system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310470206.XA CN116510901A (en) | 2023-04-27 | 2023-04-27 | Intelligent household garbage sorting system |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN116510901A true CN116510901A (en) | 2023-08-01 |
Family
ID=87404173
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202310470206.XA Pending CN116510901A (en) | 2023-04-27 | 2023-04-27 | Intelligent household garbage sorting system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN116510901A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117409009A (en) * | 2023-12-15 | 2024-01-16 | 长沙矿冶研究院有限责任公司 | Real-time sorting method for dry magnetic separation particles based on UNet |
-
2023
- 2023-04-27 CN CN202310470206.XA patent/CN116510901A/en active Pending
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117409009A (en) * | 2023-12-15 | 2024-01-16 | 长沙矿冶研究院有限责任公司 | Real-time sorting method for dry magnetic separation particles based on UNet |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN109606991B (en) | Intelligent garbage can and garbage classification method based on deep learning | |
| Bobulski et al. | Deep learning for plastic waste classification system | |
| Sreelakshmi et al. | Capsule neural networks and visualization for segregation of plastic and non-plastic wastes | |
| WO2020206862A1 (en) | Automatic sorting system | |
| CN108971190B (en) | Machine vision-based household garbage sorting method | |
| CN206489651U (en) | " internet+" Packaging Bottle intelligence recovery system | |
| CN116510901A (en) | Intelligent household garbage sorting system | |
| CN109261539A (en) | A kind of garbage sorting system and method for view-based access control model identification and convolutional neural networks | |
| CN112827846B (en) | Automatic garbage classification device and method | |
| Sunny et al. | Design of a convolutional neural network based smart waste disposal system | |
| CN112733936A (en) | Recyclable garbage classification method based on image recognition | |
| CN111340443A (en) | Refined garbage classification full-flow processing method | |
| CN110665852A (en) | Intelligent identification and separate refining device and method for common household garbage | |
| Tarun et al. | Segregation of plastic and non-plastic waste using convolutional neural network | |
| CN113807347A (en) | Kitchen waste impurity identification method based on target detection technology | |
| Ji et al. | Automatic sorting of low-value recyclable waste: a comparative experimental study | |
| Faria et al. | Classification of organic and solid waste using deep convolutional neural networks | |
| CN211437083U (en) | Intelligent garbage sorting device based on infrared vision | |
| CN112170232A (en) | Industrial grade garbage classification method and device | |
| Cai et al. | Research on computer vision-based waste sorting system | |
| CN116651599A (en) | Intelligent sorting system for social scrap steel | |
| CN215624437U (en) | Domestic waste recovery system based on ROS intelligence AGV dolly | |
| CN217576626U (en) | Classification garbage can | |
| CN212654886U (en) | Rubbish automatic classification bucket based on raspberry group control | |
| CN112620165B (en) | Garbage classification method |
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 |