Multi-stage screening system for garbage regeneration treatment
Through the combination of freezing treatment and infrared imaging technology combined with image recognition technology, the difference in thermal conductivity of garbage is used for classification, which solves the problem of low screening accuracy of traditional multi-stage screening systems, and achieves efficient and accurate garbage classification and automated screening.
Patent Information
- Application Number
- CN202510476220.X
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-04-16
- Publication Date
- 2025-06-13
AI Technical Summary
Traditional multi-stage screening systems for garbage regeneration treatment have low screening accuracy and are difficult to effectively classify complex and changeable garbage.
Refrigeration treatment is combined with infrared imaging technology and image recognition technology to sort garbage through thermal conductivity distribution map. The hardened garbage is frozen and the thermal conductivity differences of different materials are used. The infrared imager generates a thermal conductivity distribution map. The data processing module analyzes and generates a grab point map. The mechanical jaws accurately capture and classify the point map according to the point map.
It significantly improves the accuracy and efficiency of garbage classification, reduces classification errors caused by changes in garbage shape, and realizes a highly automated screening process, reducing manual intervention and costs.
Smart Images
Figure CN120133180A_ABST
Abstract
Description
Technical Field
[0001] The invention belongs to the technical field of garbage classification, and in particular is a multi-stage screening system for garbage recycling. Background Art
[0002] With the acceleration of urbanization and the continuous growth of population, the amount of garbage generated has increased dramatically. Traditional garbage disposal methods, such as landfill and incineration, can no longer meet the needs of sustainable development. Therefore, garbage recycling, that is, converting garbage into resources through classification, recycling and reuse, has become an important way to solve the garbage problem.
[0003] In order to meet the challenges of garbage disposal, technological innovation continues to promote the development of garbage disposal technology. As a representative of them, the multi-stage screening system realizes efficient and accurate classification and treatment of garbage through various technical means such as physical separation, mechanical screening, and intelligent identification. This system not only improves the efficiency of garbage disposal, but also promotes the recycling of resources and reduces environmental pollution. However, the composition of garbage is complex and varied, including plastics, paper, metals, glass, kitchen waste and other types. These garbage have significant differences in physical and chemical properties, which brings great challenges to the design and operation of multi-stage screening systems.
[0004] In summary, the low screening accuracy of the traditional multi-stage screening system for waste recycling has become a problem that the technicians in this field need to solve urgently. Therefore, it is necessary to propose a multi-stage screening system for waste recycling. Summary of the invention
[0005] In order to solve the above problems, the purpose of the present invention is to provide a multi-stage screening system for garbage recycling and processing, which can classify various renewable garbage according to the different thermal conductivity coefficients of various types of garbage after freezing.
[0006] In order to achieve the above-mentioned purpose, the technical scheme of the present invention is as follows: a multi-stage screening system for garbage recycling, comprising a scatterer for scattering, crushing and leveling garbage; a freezer for freezing the input garbage scattered by the scatterer; a belt conveyor group for conveying the garbage from the scatterer to the freezer; a chain conveyor group for transporting the frozen garbage; a plurality of classification conveyor belts for classifying and centralizing the garbage; a dust collection box for collecting dusty garbage missed by the chain conveyor group; characterized in that it also includes:
[0007] Infrared imager is used to generate thermal conductivity distribution map of the scattered garbage, which reflects the difference in thermal conductivity of different materials in the garbage.
[0008] The data processing module is used to extract the color block areas representing different temperatures in the thermal conductivity distribution diagram based on image recognition and generate a capture point map based on the distribution of the color block areas.
[0009] A number of mechanical grippers configured with positioning and grasping functions are used to classify the garbage by color block areas according to the grasping point map generated by the data processing module, and grasp the classified garbage onto the corresponding classified conveyor belt for screening.
[0010] Furthermore, the mechanical grippers all analyze the grasping point map through a preset positioning algorithm and grasping mode recognition technology to obtain an operation decision, and perform the screening action according to this operation decision.
[0011] Furthermore, the algorithms and image recognition technologies preset in the data processing module include convolutional neural network and edge detection technology.
[0012] Furthermore, the grasping point map is comprehensively generated by the data processing module according to the thermal conductivity distribution map of the infrared imager, combined with a preset algorithm and image recognition technology. The grasping point map marks the specific positions and priority orders that the mechanical grippers should grasp.
[0013] Furthermore, the positioning algorithm preset in the mechanical gripper includes laser positioning.
[0014] Furthermore, the grasping mode recognition technology includes shape recognition. The mechanical gripper can distinguish and grasp garbage of different shapes, and at the same time avoid objects beyond the grasping distance.
[0015] Furthermore, the data processing module also includes a parallel processing unit. The parallel processing unit can simultaneously process the thermal conductivity distribution map data of the infrared imager and generate a grasping point map frame by frame for multiple mechanical grippers to perform parallel operations.
[0016] Furthermore, the data processing module also includes a thermal conductivity database. The thermal conductivity coefficients of different types of garbage are preset in the thermal conductivity database. The thermal conductivity database is used to compare the thermal conductivity distribution map to judge the priority order.
[0017] Furthermore, a suction head for increasing the grasping adsorption force is connected to the bottom of the mechanical gripper.
[0018] Furthermore, the adjacent chain spacing of the chain conveyor group is 1 cm.
[0019] After adopting the above scheme, the following principles and beneficial effects are achieved:
[0020] 1. The present invention is deeply optimized in image recognition and processing technology, and does not rely on the shape characteristics of garbage for accurate classification. For example, the vegetable leaves in kitchen waste. When such garbage is untreated, it often deforms severely in the mixed garbage due to its soft texture, and even breaks into small pieces, making it difficult for traditional shape recognition technology to work. This screening system cleverly introduces a freezing treatment link, and its multiple functions significantly improve the classification accuracy and efficiency of garbage.
[0021] The freezing treatment makes use of the significant differences in the thermal conductivity of different materials. By means of infrared imaging technology, a thermal conductivity distribution map of the garbage is directly obtained, which is used as the direct basis for material classification without relying on features such as shape and color that are easily interfered by external factors. This innovation greatly broadens the scope of application of garbage classification and improves the accuracy of classification. The freezing treatment also effectively solves the problem of garbage deformation. After freezing, easily deformable substances such as vegetable leaves will become stiff, which not only facilitates the precise grasping by mechanical grippers but also reduces the classification error caused by the change in the shape of the garbage. The freezing treatment also has a certain freshness preservation effect. For organic substances such as kitchen waste, freezing can delay the corruption process and maintain the freshness of the garbage, providing more favorable conditions for subsequent green treatment, resource recovery and other links.
[0022] 2. In the present invention, before the garbage enters the screening system, it first undergoes dispersion and freezing treatment. Freezing can harden the garbage to facilitate subsequent grasping, and at the same time, significant differences will be caused by the thermal conductivity coefficients of different types of garbage. Because the materials of each garbage are different, and then the thermal conductivity coefficients of the materials are different, the temperatures after freezing are different. The temperature of the material with good thermal conductivity is low, and the temperature of the material with poor thermal conductivity is high. This difference provides the basis for subsequent infrared imaging and classification. The frozen garbage is scanned by an infrared imager to generate a thermal conductivity distribution map of the garbage. The thermal conductivity distribution map visually shows the differences in the thermal conductivity performance of different materials in the garbage, providing data support for subsequent automatic classification. Finally, through the freezing treatment and infrared imaging technology, combined with intelligent algorithms and mechanical operations, the efficient and precise classification of renewable garbage is achieved.
[0023] 3. In the present invention, the data processing module uses preset algorithms such as machine learning algorithms, convolutional neural networks and image recognition technologies such as edge detection technology to analyze the thermal conductivity distribution map generated by the infrared imager and generate a grasping point map. This point map details the specific positions and priority orders that the mechanical gripper should grasp. The entire screening process is highly automated, reducing manual intervention and improving work efficiency and accuracy.
[0024] 4. In the present invention, the mechanical gripper configured with a positioning and grasping function screens the garbage according to the grasping point map generated by the data processing module through a preset positioning algorithm such as laser positioning. The mechanical gripper can distinguish and grasp garbage of different shapes while avoiding objects beyond the grasping distance, and has strong adaptability.
[0025] 5. In the present invention, the parallel processing unit in the data processing module can simultaneously process the image data of the infrared imager and generate a grasping point map frame by frame for multiple mechanical grippers to perform parallel operations, greatly improving the screening efficiency. The entire screening process is highly automated, reducing manual intervention, lowering labor costs, and at the same time improving work efficiency.
[0026] 6. The reasonable design of the chain transmission group of the present invention, such as the adjacent chain spacing of 1 cm, and the multiple functions of the mechanical gripper, such as the suction head design, enable the screening system to show good adaptability and stability when facing different forms and properties of garbage. Finally, through precise screening, renewable garbage and non-renewable garbage can be separated more effectively, providing convenience for subsequent resource recovery and reuse, which conforms to the environmental protection concept. Description of the Drawings
[0027] Figure 1 It is a flowchart of an embodiment of the present invention.
[0028] Figure 2 It is a schematic diagram of an embodiment of the present invention.
[0029] The reference numerals in the accompanying drawings of the specification include: 1. Mechanical gripper; 2. Infrared imager; 3. Refrigerator; 4. Disintegrator; 5. Belt transmission group; 6. Dust collection box; 7. Chain transmission group. Detailed Description of the Embodiment
[0030] The following is a further detailed description through specific embodiments:
[0031] The embodiment is basically as shown in the attached... Figure 1 and the attached... Figure 2 As shown: A multi-stage screening system for garbage regeneration and treatment includes a disintegrator 4 for disintegrating garbage, crushing and leveling the garbage; a refrigerator 3 for freezing the input garbage disintegrated by the disintegrator 4; a belt transmission group 5 for transporting the garbage from the disintegrator 4 to the refrigerator 3; a chain transmission group 7 for transporting the frozen garbage, and the adjacent chain spacing of the chain transmission group 7 is 1 cm; several classification conveyor belts for classifying and centrally processing the garbage; a dust collection box 6 for collecting the dust garbage leaked from the chain transmission group 7.
[0032] An infrared imager 2 for generating a thermal conductivity distribution map of the frozen garbage, which reflects the thermal conductivity performance differences of different materials in the garbage.
[0033] A data processing module for extracting the color block areas representing different temperatures in the thermal conductivity distribution map based on image recognition and generating a grasping position map based on the distribution of the color block areas; the algorithms and image recognition technologies preset in the data processing module include convolutional neural network and edge detection technology. The data processing module also includes a thermal conductivity database, in which the thermal conductivity coefficients of different garbage types are preset, and the thermal conductivity database is used to compare the thermal conductivity distribution map to determine the priority order.
[0034] The grasping point map is comprehensively generated by the data processing module based on the thermal conductivity distribution map of the infrared imager 2, in combination with a preset algorithm and image recognition technology. The grasping point map marks the specific positions and priority orders that the mechanical gripper 1 should grasp. The data processing module also includes a parallel processing unit, which can simultaneously process the image data of the infrared imager 2 and generate a grasping point map frame by frame for multiple mechanical grippers 1 to perform parallel operations.
[0035] A number of mechanical grippers 1 configured with positioning and grasping functions are used to grasp the classified garbage to the corresponding classification conveyor belt for screening by classifying with color block areas according to the grasping point map generated by the data processing module. The bottom of the mechanical gripper 1 is connected with a suction head for increasing the grasping adsorption force. The mechanical grippers 1 all adopt a preset positioning algorithm. The preset positioning algorithm in the mechanical gripper 1 includes laser positioning. The mechanical grippers 1 all analyze the grasping point map through the preset positioning algorithm and grasping mode recognition technology to obtain an operation decision, and perform the screening action according to this operation decision. The preset positioning algorithm includes laser positioning. The grasping mode recognition technology includes shape recognition. The mechanical gripper 1 can distinguish and grasp garbage of different shapes, and at the same time avoid objects beyond the grasping distance.
[0036] Specific implementation steps:
[0037] Suppose a waste treatment center in a certain city receives a large amount of mixed waste, including kitchen waste, metal cans, plastic bottles and paper. In order to efficiently realize the recycling treatment of these wastes, the center adopts the above multi-stage screening system.
[0038] The waste is first sent to the shredder 4. The shredder 4 prevents the waste from freezing into large pieces after being frozen by the freezer 3 by shredding the waste, and then linearly transports and levels the waste surface through the belt conveyor group 5 for subsequent processing. The shredded waste is then sent to the freezer 3 for rapid freezing treatment. The freezing treatment causes significant differences in the physical properties of different types of waste, especially the change in temperature. The frozen waste is sent to the chain conveyor group 7 through the belt conveyor group 5. The chain conveyor group 7 stably conveys the waste at an adjacent chain spacing of 1 cm, ensuring that the waste will not be squeezed or stacked with each other during the movement. At the same time, the unfrozen dust waste falls into the dust collection box 6 through the chain conveyor group 7.
[0039] When the garbage passes through the infrared imager 2, the infrared imager 2 quickly generates a thermal conductivity distribution map of the garbage. This image clearly shows the differences in the thermal conductivity properties of different materials in the garbage, such as the high thermal conductivity of metals and the relatively low thermal conductivity of plastics, paper, and vegetable leaves. This difference in thermal conductivity properties provides key data support for subsequent classification. The data processing module then receives the image data transmitted by the infrared imager 2 and analyzes it using preset machine learning algorithms, convolutional neural networks, and edge detection techniques. At the same time, the data processing module also refers to the preset data in the thermal conductivity database and compares it with the thermal conductivity distribution map to determine the priority order of various materials in the garbage.
[0040] The data processing module synthesizes the above information to generate a grasping point map. This map details the specific positions and priority order that the mechanical gripper 1 should grasp, ensuring efficient and accurate completion of the screening task. To improve processing efficiency, the parallel processing unit in the data processing module simultaneously processes the motion image data transmitted by the infrared imager 2 and generates a grasping point map frame by frame for multiple mechanical grippers 1 to perform parallel operations.
[0041] The mechanical gripper 1 configured with the positioning and grasping function screens the garbage on the chain conveyor group 7 according to the grasping point map generated by the data processing module. The mechanical gripper 1 accurately moves to the specified grasping position through laser positioning and visual tracking technologies. The mechanical gripper 1 has the ability to recognize shapes and can grasp garbage of different shapes. The suction head at the bottom of the mechanical gripper 1 will contact and tightly suck the garbage to increase the adsorption force. During the screening process, the mechanical gripper 1 also operates according to the preset grasping spacing to ensure that objects beyond the spacing are not grasped, thus avoiding mechanical failures or misoperations.
[0042] The garbage screened by the mechanical gripper 1 is sent to different classification conveyors respectively. Different types of garbage, such as metals, plastics, paper, and gelatinous waste, are effectively classified and centrally processed, providing convenience for subsequent resource recovery and reuse.
[0043] The above are only embodiments of the present invention. Specific structures and common knowledge such as characteristics that are well-known in the art are not described in detail herein. Those of ordinary skill in the art know all the common general technical knowledge in the technical field to which the invention pertains before the filing date or the priority date, can learn all the existing technologies in this field, and have the ability to apply the conventional experimental means before this date. Those of ordinary skill in the art can, under the inspiration given in this application, complete and implement this solution in combination with their own abilities. Some typical well-known structures or well-known methods should not become obstacles for those of ordinary skill in the art to implement this application. It should be noted that for those skilled in the art, without departing from the structure of the present invention, several deformations and improvements can be made, which should also be regarded as the protection scope of the present invention, and these will not affect the implementation effect of the present invention and the practicality of the patent. The protection scope required by this application should be based on the content of its claims, and the specific implementation manners described in the specification can be used to interpret the content of the claims.
Claims
1. A multi-stage screening system for waste recycling, comprising: A scattering machine (4) is used to scatter, crush and level the garbage; A freezer (3) is used to freeze the input garbage that has been broken up by the break-up machine (4); A belt conveyor group (5) for conveying garbage from the scatterer (4) to the freezer (3); A chain conveyor group (7) for transporting the frozen garbage; Several sorting conveyor belts are used to sort and centrally process garbage; A dust collection box (6) is used to collect dust and garbage leaked by the chain conveyor group (7); It is characterized by further comprising: An infrared imager (2) is used to generate a thermal conductivity distribution map of the garbage after freezing, wherein the thermal conductivity distribution map reflects the difference in thermal conductivity properties of different materials in the garbage; A data processing module, used for extracting color block areas representing different temperatures in the thermal conductivity distribution map based on image recognition and generating a grab point map based on the distribution of the color block areas; A plurality of mechanical grippers (1) equipped with positioning and grasping functions are used to grasp the classified garbage and place it on a corresponding classification conveyor belt for screening by classifying it according to the color block area according to the grasping point map generated by the data processing module.
2. The multi-stage screening system for waste recycling according to claim 1, characterized in that: The mechanical grippers (1) analyze the grasping point map through a preset positioning algorithm and grasping pattern recognition technology to obtain an operation decision, and perform a screening action based on the operation decision.
3. The multi-stage screening system for waste recycling according to claim 2 is characterized in that: The preset algorithms and image recognition technologies of the data processing module include convolutional neural networks and edge detection technology.
4. The multi-stage screening system for waste recycling according to claim 3 is characterized in that: The grasping point map is generated by the data processing module based on the thermal conductivity distribution map of the infrared imager (2) in combination with a preset algorithm and image recognition technology. The grasping point map marks the specific positions and priority order that the mechanical gripper (1) should grasp.
5. The multi-stage screening system for waste recycling according to claim 4 is characterized in that: The preset positioning algorithm in the mechanical gripper (1) includes laser positioning.
6. The multi-stage screening system for waste recycling according to claim 5, characterized in that: The grasping pattern recognition technology includes shape recognition, and the mechanical gripper (1) can distinguish and grasp garbage of different shapes, and avoid objects that exceed the grasping distance.
7. The multi-stage screening system for waste recycling according to claim 6, characterized in that: The data processing module also includes a parallel processing unit, which is capable of simultaneously processing the thermal conductivity distribution map data of the infrared imager (2) and generating a grasping point map frame by frame for parallel operation of multiple mechanical grippers (1).
8. The multi-stage screening system for waste recycling according to claim 7, characterized in that: The data processing module also includes a thermal conductivity database, in which thermal conductivity coefficients of different types of garbage are preset. The thermal conductivity database is used to compare the thermal conductivity coefficient distribution map to determine the priority order.
9. The multi-stage screening system for waste recycling according to claim 8, characterized in that: The bottom of the mechanical gripper (1) is connected to a suction head for increasing the gripping and adsorption force.
10. The multi-stage screening system for waste recycling according to claim 9, characterized in that: The distance between adjacent chains of the chain conveyor group (7) is 1 cm.