CN215031272U - Recoverable rubbish sorting device based on degree of depth study - Google Patents
Recoverable rubbish sorting device based on degree of depth study Download PDFInfo
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- CN215031272U CN215031272U CN202022614892.8U CN202022614892U CN215031272U CN 215031272 U CN215031272 U CN 215031272U CN 202022614892 U CN202022614892 U CN 202022614892U CN 215031272 U CN215031272 U CN 215031272U
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- garbage
- conveying belt
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- rotating shaft
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- 239000010813 municipal solid waste Substances 0.000 title claims abstract description 68
- 230000007246 mechanism Effects 0.000 claims abstract description 35
- 238000013135 deep learning Methods 0.000 claims abstract description 13
- 238000012856 packing Methods 0.000 claims abstract description 13
- 238000007599 discharging Methods 0.000 claims abstract description 6
- 239000010819 recyclable waste Substances 0.000 claims description 8
- 230000000007 visual effect Effects 0.000 claims description 7
- 238000001514 detection method Methods 0.000 claims description 4
- 239000002699 waste material Substances 0.000 claims 2
- 239000000463 material Substances 0.000 abstract description 4
- 238000011084 recovery Methods 0.000 abstract description 2
- 238000004806 packaging method and process Methods 0.000 description 12
- 230000000694 effects Effects 0.000 description 2
- 229920003023 plastic Polymers 0.000 description 2
- 239000004033 plastic Substances 0.000 description 2
- 238000013473 artificial intelligence Methods 0.000 description 1
- 238000013528 artificial neural network Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000012512 characterization method Methods 0.000 description 1
- 230000006835 compression Effects 0.000 description 1
- 238000007906 compression Methods 0.000 description 1
- 239000011521 glass Substances 0.000 description 1
- 238000010801 machine learning Methods 0.000 description 1
- 239000002184 metal Substances 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000003058 natural language processing Methods 0.000 description 1
- 230000009467 reduction Effects 0.000 description 1
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- Processing Of Solid Wastes (AREA)
Abstract
The utility model provides a recoverable garbage sorting device based on deep learning, which relates to the technical field of garbage recovery, and comprises a garbage processing box, a feeding hopper, a discharging hopper, a supporting column, a base, an electric rotating shaft, a mechanical arm, a first conveying belt, a packing machine, a classification recognition mechanism and a second conveying belt, the utility model can sort out the classified recoverable garbage through four groups of different discharge ports, then convey the garbage to the packing machine through the first conveying belt, pack the garbage, convey the packed recoverable garbage through the second conveying belt, carry out the next step of integral processing, can improve the labor efficiency, lighten the labor intensity and save manpower, scan and recognize whether the object on the first conveying belt is classified by arranging the classification recognition mechanism, sort out the object on the first conveying belt through the electric rotating shaft and the mechanical arm, can classify the wrong rubbish of classification to be used for carrying out accurate letter sorting to the material, make categorised more accurate.
Description
Technical Field
The utility model relates to a rubbish recovery technical field specifically is a recoverable rubbish sorting device.
Background
Deep learning is one of the directions of artificial intelligence research, is a branch of machine learning, is an artificial neural network as a framework, the algorithm for performing characterization learning on data has been applied to the fields of computer vision, speech recognition, natural language processing, audio recognition, bioinformatics and the like and obtains excellent effects, the recyclable garbage is recyclable garbage, is an important factor for the main work of household garbage classification and influencing garbage reduction, and comprises paper, hardboard, glass, plastics, metal, plastic packages and the like which can be recycled per se or materials, and the recyclable garbage sorting device based on deep learning;
the initial sorting system is an operation system completely based on manpower, the goods are extracted by manual searching and carrying, the operation efficiency of the sorting system is low, and the high requirements of modern logistics distribution on speed and accuracy cannot be met;
therefore, further research needs to be conducted on the existing recyclable waste sorting apparatus to provide a new recyclable waste sorting apparatus based on deep learning.
SUMMERY OF THE UTILITY MODEL
The utility model aims to solve the weak point that exists among the prior art, provide recoverable rubbish sorting device based on degree of depth study.
In order to achieve the above object, the utility model provides a following technical scheme: a recyclable garbage sorting device based on deep learning comprises a garbage processing box, a feed hopper, a discharge hopper, a support column, a base, an electric rotating shaft, a mechanical arm, a first conveyor belt, a packing machine, a classification and identification mechanism and a second conveyor belt, a discharge port is arranged on the side surface of the garbage treatment box, a feed hopper is arranged at the upper end of the left side of the garbage treatment box, the garbage disposal box is provided with a discharge hopper at the upper end of the left side of the feed hopper, the bottom of the discharge hopper is provided with a support column, the garbage disposal box is provided with a base at the right side of the feed hopper, the upper end of the base is provided with an electric rotating shaft, the front surface of the electric rotating shaft is provided with a mechanical arm, the side surface of the garbage disposal box is provided with a first conveyor belt, the other end of the first conveyor belt is provided with a packaging machine, the upper end of the packaging machine is provided with a classification recognition mechanism, and the other end of the packaging machine is provided with a second conveyor belt.
Preferably, the garbage disposal box, the electric rotating shaft, the mechanical arm, the first conveying belt, the packaging machine, the classification and identification mechanism and the second conveying belt are all connected with an external power supply through electric wires.
Preferably, the garbage treatment box is provided with four groups of discharge ports, and the four groups of discharge ports are transversely arranged.
Preferably, the first conveyor belt, the packaging machine, the classification recognition mechanism and the second conveyor belt are all provided with four groups, and the four groups of the first conveyor belts are all communicated with the opening of the discharge hole.
Preferably, the upper ends of the four groups of discharge ports are provided with a base, an electric rotating shaft and a manipulator, and the manipulator extends to the upper end of the first conveyor belt.
Preferably, the classification recognition mechanism is arranged opposite to the opening of the discharge hole, and the classification recognition mechanism is electrically connected with the electric rotating shaft and the manipulator.
Preferably, the classification recognition mechanism is a visual sensor, and the electric rotating shaft and the manipulator are both provided with position detection devices.
Compared with the prior art, the beneficial effects of the utility model are as follows:
(1) this kind of recoverable rubbish sorting device based on degree of depth study, through setting up the refuse treatment case, the refuse treatment case is handled rubbish, sort out categorised recoverable rubbish through the discharge gate of four group differences again, categorised recoverable rubbish is carried to packagine machine through first conveyer belt, pack categorised recoverable rubbish through packagine machine, carry out simple and convenient efficient compression to recoverable rubbish, carry the recoverable rubbish that packagine machine packed well through the second conveyer belt, conveniently carry out overall processing on next step, can improve labor efficiency, alleviate intensity of labour, practice thrift the manpower.
(2) Through setting up categorised recognition mechanism, categorised recognition mechanism comprises visual sensor, general visual sensor can the at utmost imitate people's eyes, can discern the object of difference, categorised recognition mechanism scans the discernment to the object on the first conveyer belt, when discerning article classification error, send signal to electronic pivot and manipulator again, sort out through the object of electronic pivot and manipulator on with the first conveyer belt, and sort to the first conveyer belt on next door, rethread categorised recognition mechanism scans, until categorised correct, can classify the rubbish of categorised error, thereby be used for carrying out accurate letter sorting to the material, make categorised more accurate.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings that are required to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present invention, and therefore should not be considered as limiting the scope, and for those skilled in the art, other related drawings can be obtained according to the drawings without inventive efforts.
Fig. 1 is a schematic view of the overall structure of the present invention.
Fig. 2 is the schematic view of the electric rotating shaft and the mechanical arm concrete connection structure of the present invention.
Fig. 3 is a schematic view of the connection structure between the first conveyor belt and the packaging machine according to the present invention.
In the figure: 1-a garbage disposal bin; 2-a feed hopper; 3-unloading bucket; 4-a support column; 5-a base; 6-electric rotating shaft; 7-a manipulator; 8-a first conveyor belt; 9-packaging machine; 10-a classification recognition mechanism; 11-a second conveyor belt; 101-discharge hole.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention.
Example (b):
as shown in figures 1-3;
the embodiment provides a recyclable garbage sorting device based on deep learning, which comprises a garbage processing box 1, a feeding hopper 2, a discharging hopper 3, a supporting column 4, a base 5, an electric rotating shaft 6, a mechanical arm 7, a first conveying belt 8, a packing machine 9, a classification recognition mechanism 10 and a second conveying belt 11, wherein a discharging port 101 is formed in the side surface of the garbage processing box 1, the feeding hopper 2 is arranged at the upper end of the left side of the garbage processing box 1, the discharging hopper 3 is arranged at the upper end of the left side of the feeding hopper 2 of the garbage processing box 1, the supporting column 4 is arranged at the bottom of the discharging hopper 3, the base 5 is arranged at the right side of the garbage processing box 1, the electric rotating shaft 6 is arranged at the upper end of the base 5, the mechanical arm 7 is arranged on the front side of the electric rotating shaft 6, the first conveying belt 8 is arranged on the side surface of the garbage processing box 1, the packing machine 9 is arranged at the other end of the first conveying belt 8, the upper end of the packaging machine 9 is provided with a classification recognition mechanism 10, and the other end of the packaging machine 9 is provided with a second conveyor belt 11.
Further, the garbage disposal box 1, the electric rotating shaft 6, the mechanical arm 7, the first conveyor belt 8, the packaging machine 9, the classification recognition mechanism 10 and the second conveyor belt 11 are all connected with an external power supply through electric wires, and the external power supply provides a power source for the garbage disposal box 1, the electric rotating shaft 6, the mechanical arm 7, the first conveyor belt 8, the packaging machine 9, the classification recognition mechanism 10 and the second conveyor belt 11 to ensure normal operation of the garbage disposal box;
and the PLC controller is used for carrying out control in a unified way.
Further, the garbage disposal box 1 is provided with four groups of discharge ports 101, the four groups of discharge ports 101 are transversely arranged, and the four groups of discharge ports 101 can sort the classified recyclable garbage through the four groups of different discharge ports 101.
Further, four groups of first conveyor belts 8, the packaging machine 9, the classification recognition mechanism 10 and the second conveyor belts 11 are arranged, and the four groups of first conveyor belts 8 are communicated with the opening of the discharge hole 101.
Further, the upper ends of the four discharge ports 101 are provided with a base 5, an electric rotating shaft 6 and a manipulator 7, the manipulator 7 extends to the upper end of the first conveyor belt 8, and objects on the first conveyor belt 8 are sorted out through the electric rotating shaft 6 and the manipulator 7.
Further, the opening part of categorised identification mechanism 10 and discharge gate 101 is relative setting, and categorised identification mechanism 10 is electric connection with electric rotating shaft 6 and manipulator 7, and categorised identification mechanism 10 scans the discernment to the object on the first conveyer belt 8, when discerning article classification error, sends the signal again to electric rotating shaft 6 and manipulator 7.
Further, the classification recognition mechanism 10 is a visual sensor, and the electric spindle 6 and the manipulator 7 are equipped with position detection devices, and when the electric spindle 6 and the manipulator 7 perform actions, whether the actions are in place is detected through the corresponding position detection devices.
When the garbage truck is used, the recyclable garbage recycled by the garbage truck is unloaded through the unloading hopper 3, the recyclable garbage is guided into the feeding hopper 2 through the unloading hopper 3 and enters the garbage treatment box 1 through the feeding hopper 2 for treatment, the garbage treatment box 1 treats the garbage, the classified recyclable garbage is sorted out through four different discharge ports 101, the classified recyclable garbage is conveyed to the packing machine 9 through the first conveying belt 8, the classified recyclable garbage is packed through the packing machine 9, the recyclable garbage is simply and efficiently compressed and packed, the packed recyclable garbage is conveyed through the second conveying belt 11, the next step of overall treatment is facilitated, the labor efficiency can be improved, the labor intensity is reduced, and the manpower is saved;
through setting up categorised recognition mechanism 10, categorised recognition mechanism 10 is relative setting with the opening part of discharge gate 101, categorised recognition mechanism 10 comprises visual sensor, general visual sensor can the furthest imitate people's eyes, can discern the object of difference, categorised recognition mechanism 10 scans the discernment to the object on the first conveyer belt 8, when discerning article classification error, signal again to electronic pivot 6 and manipulator 7, sort out the object on the first conveyer belt 8 through electronic pivot 6 and manipulator 7, and sort to the first conveyer belt 8 on next door, scan through categorised recognition mechanism 10, until categorised correctly, can classify the rubbish of categorised mistake, thereby be used for carrying out accurate letter sorting to the material, make categorised more accurate.
The above is only the preferred embodiment of the present invention, and it should be noted that, for those skilled in the art, without departing from the concept of the present invention, several modifications and improvements can be made, which should also be regarded as the protection scope of the present invention, and these will not affect the effect of the implementation of the present invention and the practicability of the patent.
Claims (7)
1. Recoverable garbage sorting device based on deep learning comprises a garbage processing box (1), a feed hopper (2), an unloading hopper (3), support columns (4), a base (5), an electric rotating shaft (6), a mechanical arm (7), a first conveying belt (8), a packing machine (9), a classification recognition mechanism (10) and a second conveying belt (11), and is characterized in that a discharge port (101) is arranged on the side surface of the garbage processing box (1), the feed hopper (2) is arranged at the upper end of the left side of the garbage processing box (1), the unloading hopper (3) is arranged at the upper end of the left side of the feed hopper (2) of the garbage processing box (1), the support columns (4) are arranged at the bottom of the unloading hopper (3), the base (5) is arranged at the right side of the feed hopper (2) of the garbage processing box (1), the electric rotating shaft (6) is arranged at the upper end of the base (5), the front side of the electric rotating shaft (6) is provided with a mechanical arm (7), the side face of the garbage disposal box (1) is provided with a first conveying belt (8), the other end of the first conveying belt (8) is provided with a packing machine (9), the upper end of the packing machine (9) is provided with a classification recognition mechanism (10), and the other end of the packing machine (9) is provided with a second conveying belt (11).
2. The recyclable waste sorting device based on deep learning of claim 1, characterized in that the waste processing bin (1), the electric rotating shaft (6), the manipulator (7), the first conveyor belt (8), the packing machine (9), the classification recognition mechanism (10) and the second conveyor belt (11) are all connected with an external power supply through wires.
3. The apparatus for sorting recyclable waste based on deep learning of claim 1, characterized in that the waste processing bin (1) is provided with four sets of outlets (101) and the four sets of outlets (101) are arranged in a transverse direction.
4. The recyclable waste sorting device based on deep learning of claim 1 or 3, wherein the first conveyor belt (8), the packing machine (9), the classification recognition mechanism (10) and the second conveyor belt (11) are provided with four sets, and the four sets of the first conveyor belt (8) are communicated with the opening of the discharge hole (101).
5. The recyclable waste sorting device based on deep learning of claim 1, wherein the four sets of outlets (101) are each provided with a base (5), an electric spindle (6) and a robot (7) at the upper end, and the robot (7) extends to the upper end of the first conveyor belt (8).
6. The recyclable waste sorting device based on deep learning of claim 1, wherein the classification recognition mechanism (10) is disposed opposite to the opening of the discharging hole (101), and the classification recognition mechanism (10) is electrically connected to the electric rotating shaft (6) and the mechanical arm (7).
7. The recyclable waste sorting device based on deep learning of claim 1, characterized in that the classification recognition mechanism (10) is a visual sensor and the motorized spindle (6) and the robot (7) are equipped with position detection means.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202022614892.8U CN215031272U (en) | 2020-11-12 | 2020-11-12 | Recoverable rubbish sorting device based on degree of depth study |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202022614892.8U CN215031272U (en) | 2020-11-12 | 2020-11-12 | Recoverable rubbish sorting device based on degree of depth study |
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| Publication Number | Publication Date |
|---|---|
| CN215031272U true CN215031272U (en) | 2021-12-07 |
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| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202022614892.8U Expired - Fee Related CN215031272U (en) | 2020-11-12 | 2020-11-12 | Recoverable rubbish sorting device based on degree of depth study |
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| CN (1) | CN215031272U (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114313966A (en) * | 2021-12-27 | 2022-04-12 | 河北省冀信环保科技有限公司 | Garbage classification sorting system |
-
2020
- 2020-11-12 CN CN202022614892.8U patent/CN215031272U/en not_active Expired - Fee Related
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114313966A (en) * | 2021-12-27 | 2022-04-12 | 河北省冀信环保科技有限公司 | Garbage classification sorting system |
| CN114313966B (en) * | 2021-12-27 | 2023-08-01 | 河北省冀信环保科技有限公司 | Garbage sorting system |
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| GR01 | Patent grant | ||
| GR01 | Patent grant | ||
| CF01 | Termination of patent right due to non-payment of annual fee |
Granted publication date: 20211207 |