A waste tire sorting and conveying system and a pyrolysis product recovery process thereof

Abstract

The application discloses a kind of waste and old tire sorting conveying system and its cracking production recovery process, system contains tire classification module, tire surface defect judging unit, repair priority processing module and tire priority conveying module, wherein tire classification module is divided according to tire diameter data size, and material quality is classified in combination with cord magnetic attraction characteristic;Tire surface defect judging unit refers to tire repair index database, analyzes and judges tire surface defect data;Repair priority processing module constructs multidimensional evaluation matrix, and obtains tire repair priority;Tire priority conveying module is according to repair priority score, determines and allocates conveying queue, realizes the transformation of waste and old tire from "extensive recovery" to "fine classification, high value utilization", both solve the problem of low efficiency, high error rate of traditional manual sorting, also provide key support for the scale, intelligent operation of waste and old tire recycling economic industry chain, guarantee the raw material quality and processing efficiency of subsequent resource process.

Description

Technical Field

[0001] This invention relates to the field of waste tire sorting and conveying, specifically to a waste tire sorting and conveying system and its pyrolysis gas recovery process. Background Technology

[0002] The waste tire sorting and conveying system is a core industrial equipment system connecting waste tire recycling and resource utilization. With "precise grading, efficient conveying, and directional diversion" as its core objectives, it integrates mechanical conveying, intelligent detection, data decision-making, and automated control technologies to construct a complete operation system from tire entry to directional allocation. Tires are orderly conveyed to the pre-processing stage to remove impurities through the feeding unit. Then, relying on the three-level sorting logic, combined with machine learning algorithms to optimize the rhythm and dynamically adjust equipment parameters to adapt to different tires, the system ultimately realizes the transformation of waste tires from "extensive recycling" to "refined classification and high-value utilization." This not only solves the problems of low efficiency and high missorting rate of traditional manual sorting, but also provides key support for the large-scale and intelligent operation of the waste tire circular economy industrial chain, ensuring the raw material quality and processing efficiency of subsequent resource utilization processes.

[0003] Currently, the process algorithms of waste tire sorting and conveying systems are designed with the core goal of automating the "from entry to diversion" of tires. Most of them are built on preset standardized rules and basic data processing logic. In actual industrial applications, they exhibit obvious scenario dependence and functional limitations. They usually rely on sensors to collect the physical properties of tires and equipment operating parameters, and then complete the coarse and fine sorting of tires through simple threshold judgment or basic classification algorithms. Subsequently, they combine the preset capacity allocation diversion path of the back-end processing line. Threshold judgment includes setting size ranges to distinguish between passenger car tires and truck tires, and judging the degree of damage based on the length of surface cracks. Basic classification algorithms include decision trees, support vector machines, etc. Physical properties include size, weight, and surface morphology. Equipment operating parameters include conveyor belt speed and diversion mechanism status.

[0004] Currently, the process algorithms of waste tire sorting and conveying systems have significant drawbacks in industrial applications. They lack adaptability to complex working conditions, and most are built based on standardized scenarios. When encountering irregular shapes of recycled tires, residual impurities, or temporary equipment fluctuations, detection deviations and sorting delays easily occur, leading to an increased missorting rate. The data integration and collaboration capabilities are weak. Data from primary coarse sorting, secondary fine sorting, and tertiary sorting are often processed independently, lacking cross-linking. The planned sorting paths do not fully consider the real-time load of the backend, easily causing branch line accumulation and idleness, reducing system efficiency. The self-optimization and adaptive capabilities are limited, relying heavily on manually preset rules. It is difficult to dynamically adjust the decision logic based on historical data. When the source, specifications, or attributes of tires change, parameters need to be manually calibrated, increasing maintenance costs and causing response delays. There is insufficient identification and handling of special risk tires. There is a lack of specialized models for trace heavy metals and hidden internal damage, which can easily lead to environmental hazards or equipment damage. Furthermore, the ability to respond to sudden anomalies and replan paths under multi-path sorting is weak, easily causing congestion on the main conveyor line and disrupting the sorting rhythm. Summary of the Invention

[0005] This application provides a waste tire sorting and conveying system to address the technical problems in existing technologies, such as weak data integration and collaboration capabilities, limited self-optimization and self-adaptation capabilities, and insufficient identification and processing of tires with special risks.

[0006] In view of the above problems, this application provides a waste tire sorting and conveying system and its pyrolysis gas recovery process.

[0007] The first aspect of this application provides a waste tire sorting and conveying system, the system comprising: a tire classification module for classifying tires by size based on tire diameter data and classifying tire cord material based on whether the cords can be magnetically attracted; a tire surface defect judgment unit for analyzing and judging tire surface defect data based on a tire repair index database; a repair priority processing module for constructing a multi-dimensional evaluation matrix to obtain tire repair priorities; and a tire priority conveying module for analyzing and judging the conveying queue based on the repair priority score.

[0008] A second aspect of this application provides a process for recovering gas generated from waste tire pyrolysis. The method is applied to a system and includes: obtaining tire particles; thermally pyrolyzing the tire particles to obtain pyrolyzed oil and gas and solid residue; cooling the pyrolyzed oil and gas through a condenser to separate pyrolyzed oil and non-condensable gas; passing the non-condensable gas into a gas purification device to remove pollutants and obtain purified gas; and compressing the purified gas through a compression device and storing it in a gas storage tank, or directly supplying it to a combustion device for use as fuel.

[0009] One or more technical solutions provided in this application have at least the following technical effects or advantages:

[0010] This application embodiment utilizes a tire classification module to classify tires by diameter and a tire cord material based on magnetic attraction. A tire surface defect judgment unit analyzes and judges tire surface defect data using a tire repair index database. A repair priority processing module constructs a multi-dimensional evaluation matrix to obtain tire repair priorities. A tire priority conveying module analyzes and judges the conveying queue based on repair priority scores. This achieves a transformation from "extensive recycling" to "refined classification and high-value utilization" of waste tires, solving the problems of low efficiency and high missorting rate in traditional manual sorting. It also provides crucial support for the large-scale and intelligent operation of the waste tire circular economy industrial chain, ensuring the raw material quality and processing efficiency of subsequent resource recovery processes.

[0011] The above description is only an overview of the technical solution of this application. In order to better understand the technical means of this application, and to make the above and other objects, features and advantages of this application more obvious and understandable, specific embodiments of this application are given below. Attached Figure Description

[0012] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0013] Figure 1 This application provides a waste tire sorting and conveying system and its pyrolysis gas recovery process; Detailed Implementation

[0014] This application provides a waste tire sorting system to address the technical problems in existing technologies, such as weak data integration and collaboration capabilities, limited self-optimization and self-adaptation capabilities, and insufficient identification and processing of tires with special risks.

[0015] To address the aforementioned technical problems, the overall approach of the technical solution provided in this application is as follows:

[0016] This application embodiment includes a tire classification module for classifying tires by diameter and a tire cord material based on whether the cords can be magnetically attracted. A tire surface defect judgment unit analyzes and judges tire surface defect data based on a tire repair index database. A repair priority processing module constructs a multi-dimensional evaluation matrix to obtain tire repair priorities. A tire priority delivery module analyzes and judges the delivery queue based on the repair priority score. This addresses the technical problems in existing technologies, such as weak data integration and collaboration capabilities, limited self-optimization and adaptive capabilities, and insufficient handling of tires with special risks.

[0017] After introducing the basic principles of this application, the technical solutions of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of the embodiments of this application. It should be understood that this application is not limited to the exemplary embodiments described herein. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application. It should also be noted that, for ease of description, only the parts related to this application are shown in the accompanying drawings, not all of them.

[0018] Example 1

[0019] like Figure 1 As shown, this application provides a waste tire sorting system and its pyrolysis gas recovery process, including:

[0020] The tire classification module is used to classify tires by diameter and tire cord material by whether the cords can be magnetically attracted.

[0021] The tire sorting module is a key unit in the waste tire sorting system, enabling the initial separation of tires into major categories. Its core function is to complete two basic sorting tasks using automated detection methods. First, it collects tire diameter data through sensors and accurately classifies tires by size according to preset size ranges, providing a basis for subsequent planning of conveying paths and adaptation of processing technology for tires of different sizes. Second, it uses a magnetic detection device to determine whether the tire cords have magnetic properties, thereby distinguishing between steel cord tires and non-steel cord tires, clarifying the core material properties of the tires, and providing a key reference for the selection of processes in the subsequent recycling stage. Overall, these two sorting methods transform tires from a chaotic recycling state to a preliminary orderly classification, laying the foundation for subsequent refined sorting and directional conveying.

[0022] The tire classification module includes: a waste tire cleaning module for cleaning impurities from waste tires; a tire diameter measurement module for receiving tire diameter data; a database preset unit for presetting a tire size classification database, which includes small tire diameter ranges, medium tire diameter ranges, and large tire diameter ranges; a model analysis unit for classifying tire models based on tire diameter data; a model judgment unit for sorting tires as small tires if the measured tire diameter data falls within the small tire diameter range, as medium tires if the measured tire diameter data falls within the medium tire diameter range, and as large tires if the measured tire diameter data falls within the large tire diameter range; an acquisition of a size parameter set for obtaining tire model repair time data; a cord judgment unit for magnetically determining the tire cord material; and a cord material analysis and judgment unit for classifying tires as steel cord tires if they can be attracted by a magnet, and as fiber cord tires if they cannot be attracted by a magnet.

[0023] The waste tire cleaning module, as a pre-processing step, uses high-pressure spraying and rotating brushes to wash the tire surface, along with a vibrating screen to separate impurities such as mud, sand, and metal fragments, ensuring the accuracy of subsequent testing data. The tire diameter measurement module collects data after cleaning using laser rangefinders on both sides of the conveyor line, calculates and transmits the actual tire diameter. The database pre-setting unit pre-builds and stores a tire size classification database, clearly defining small, medium, and large diameter ranges to provide a standard for classification. The model analysis unit receives the diameter data and performs matching analysis using the database ranges; the model judgment unit then classifies the tire into the corresponding size category. The cord judgment unit uses a magnetic detection device to determine whether the tire cords can be magnetically attracted; the cord material analysis judgment unit classifies attractable cords as steel cord tires and non-attractable cords as fiber cord tires. For example, a tire with a diameter of 65 cm after cleaning is determined to be a medium-sized tire, and since it shows no magnetic attraction, it is ultimately classified as a medium-sized fiber cord tire.

[0024] The tire surface defect judgment unit is used to analyze and judge tire surface defect data based on the tire repair index database.

[0025] The tire surface defect judgment unit is a key link connecting "defect detection" and "repair decision-making" in the refined sorting of waste tires. Its core function is to systematically analyze and match the tire surface defect data collected by the previous detection module based on a pre-built tire repair index database. By comparing the defect data with the preset repair qualification threshold in the database, it determines whether the tire surface defect has repair value. If the defect data does not exceed the repairable range set in the database, it is judged as a "repairable tire," and the appropriate repair process direction is output simultaneously. If the defect data exceeds the repairable threshold, it is judged as an "unrepairable tire," and it is classified into the corresponding processing path such as reclaimed rubber raw materials or pyrolysis raw materials. Ultimately, it provides accurate defect judgment basis for the subsequent targeted diversion of tires, ensuring efficient allocation of repair resources and avoiding ineffective repair costs.

[0026] The tire surface defect judgment unit includes: a repair index database preset unit, used to preset the tire repair index database and obtain the tire repair index data range; a tire 3D scanning and modeling module, used to scan the tire surface to create a model and identify tire surface defect data based on the model; a defect data analysis unit, used to analyze and judge the tire surface defect data based on the tire repair index database; and a defect data analysis and judgment unit, used to enter the repair stage if the tire surface defect data has corresponding repair index data in the tire repair index data range, and generate a defect parameter sequence number and the corresponding quantitative repair cost; if the tire surface defect data does not have corresponding repair index data in the tire repair index data range, it does not enter the repair stage and is directly judged to have no retreading value.

[0027] The tire repair index database preset unit needs to be built and stored in the system in advance. This database will specify the repairable data range for common tire surface defect types such as tread cracks, sidewall bulges, shoulder scratches, and tread wear, such as tread crack length ≤ 5 cm, sidewall bulge diameter ≤ 3 cm, and tread wear depth ≤ 2 mm. It will also include quantitative repair cost parameters for each repairable defect, such as a repair cost of 80-120 yuan for a crack length of 3-5 cm and a repair cost of 100-150 yuan for a bulge diameter of 1-3 cm, for subsequent... The system provides a standard basis for defect assessment and cost accounting. The tire 3D scanning and modeling module uses a laser 3D scanner installed above the conveyor line to perform a comprehensive scan of the cleaned tire, quickly constructing a 3D model. Then, image recognition algorithms extract and mark the location, type, and specific data of defects on the tire surface from the model, transmitting this defect data to the subsequent analysis unit in real time. Upon receiving the defect data from the 3D scanning and modeling module, the defect data analysis unit immediately calls up preset data from the repair index database, comparing the actual defect data with the repairable defects in the database. The system performs a comparative analysis of each defect interval to determine whether each defect falls within the repairable range. The defect data analysis and judgment unit then makes a final judgment based on the comparison results of the defect data analysis unit. If all defect data on the tire surface can be found in the tire repair index database, the tire is determined to have repair value and enters the repair stage. At the same time, a unique defect parameter number and the corresponding quantitative total repair cost are automatically generated. If there are defect data on the tire surface that exceed the repairable range in the database, resulting in no corresponding repair index data in the database, the tire is determined to have no repair value and will not enter the repair stage. It will be directly classified as a tire with no retreading value and will be guided to the recycled rubber production or pyrolysis processing path. For example, after a 3D scan, a recycled tire is found to have a 4.5 cm tread crack length and no other defects on the sidewall. The defect data analysis unit compares the data with the database and finds that the 4.5 cm tread crack is within the repairable range. The defect data analysis and judgment unit then determines that it enters the repair stage, generates a defect parameter number and a quantitative repair cost. Another tire, however, is scanned and found to have a sidewall bulge diameter that exceeds the repairable range in the database, so it is directly determined to have no retreading value.

[0028] The repair priority processing module is used to construct a multi-dimensional evaluation matrix to obtain tire repair priorities.

[0029] The repair priority processing module is a core component in the waste tire retreading process, enabling efficient resource allocation. Its core function is to construct a multi-dimensional evaluation matrix based on the actual value and feasibility of tire repair. The matrix dimensions typically cover the tire's basic attributes, surface defect status and type, defect quantity, defect severity, repair costs and benefits such as quantified repair costs, expected service life after repair, market recycling price, and the burden on backend repair resources. By assigning scientific weight coefficients to each dimension, the module quantifies and scores each indicator of the tire to be repaired, calculates a comprehensive score, and then sorts the tires from highest to lowest comprehensive score to determine the repair priority of each tire. Tires with high comprehensive scores are prioritized for repair, avoiding the waste of high-quality repair resources on low-value tires. This balances repair efficiency and cost-benefit, ensuring that the entire retreading process is orderly and efficient.

[0030] The repair priority processing module includes: a matrix construction unit for constructing a multi-dimensional evaluation matrix; and a scoring formula construction unit for constructing a repair priority scoring formula, which incorporates quantified repair costs, tire model repair time, defect parameter number, parameter weight, and parameter score into a weighted total score formula to obtain a repair priority score; the weighted total score formula is as follows:

[0031] ;

[0032] in To fix the priority total score, To quantify repair costs, The basic repair time for the tire model. This is the defect parameter number. For the first The weight of each defect, For the first The rating of each defect It is the repair time for the i-th defect. This is the batch repair adjustment parameter for the i-th defect. The repair priority output unit is used to analyze and determine the tire repair priority based on the total repair priority score.

[0033] The matrix construction unit builds a multi-dimensional evaluation matrix around the core elements affecting tire repair priority. The matrix explicitly includes: quantified repair costs reflecting the economic investment in repair; standard repair time for different tire models without specific defects; defect parameter numbers used to associate specific tire defect types and related record codes; weights and scoring weights for each defect, preset based on the defect's impact on tire performance (e.g., tread cracks have a weight of 0.3, sidewall bulges have a weight of 0.25); scoring based on defect data (e.g., a 3cm crack length corresponds to a score of 8, a 1.5cm bulge diameter corresponds to a score of 7.5); specific processing time for individual defects; and batch repair adjustment parameters. This ensures the matrix comprehensively covers key indicators influencing repair priority. Simultaneously, a total repair priority score formula is constructed, integrating all the above parameters to quantify repair costs and reflect the economic investment. The input includes the tire model's basic repair time, reflecting the inherent repair difficulty of the model; the defect parameter number, associated with specific defect information; the weight and score of the i-th defect, jointly measuring the importance and severity of the defect; the repair time of the i-th defect, supplementing the processing time of a single defect; and batch repair adjustment parameters, adapting to the fine-tuning needs of batch processing scenarios. If the calculated total repair priority score equals 0, it indicates that the tire repair investment is too high or the defect cannot be improved through repair, and is therefore deemed prohibited from repair. The repair priority judgment unit receives the various parameters output by the matrix construction unit and the calculated total repair priority score, and sorts the tire repair priorities according to the score. The higher the score, the higher the comprehensive value of the tire repair, and the higher the priority. For example, according to the calculation of the repair priority processing module, the quantitative repair cost of a certain tire to be repaired is 150 yuan, and its basic repair time is 20 minutes. This tire has two defects: tread cracks and sidewall bulges. The tread cracks have a weight of 0.3, a score of 5, and a repair time of 8 minutes; the sidewall bulges have a weight of 0.25, a score of 4, and a repair time of 10 minutes. The batch repair adjustment parameter for both defects is 1.0. After substituting into the repair priority scoring formula, the total score is approximately 3.88 points. This low score indicates that the overall value of the tire repair is not high, and the repair priority judgment unit will place it at a relatively low position in the repair queue. If compared with other tire scores later, its ranking will be lower than tires with higher scores. However, since its score is not close to zero, repair can still be arranged and it does not fall within the scope of prohibited repairs.

[0034] The tire priority delivery module is used to analyze and determine the delivery queue based on the repair priority score;

[0035] The tire priority delivery module analyzes the repair priority score of each tire, intelligently determines and optimizes the order of the delivery queue, and ensures that high-priority tires enter the processing flow first, thereby improving warehouse management efficiency and the timeliness of repair operations.

[0036] The tire priority delivery module includes: an inventory area parameter acquisition unit, used to collect a set of tire inventory area parameters, including remaining space volume, total warehouse volume, occupied storage volume, and minimum reserved volume; an admission standard preset unit, which presets manually set high-value standards and obtains the average repair priority score of stored tires based on repair priority scores; and a score model calculation unit, which constructs an admission score calculation model by inputting the collected tire inventory area parameter set, manually preset high-value standards, and the average repair priority score of stored tires into the above calculation model.

[0037] The calculation model is as follows:

[0038] ;

[0039] in For dynamic access standards, The remaining space volume, The total warehouse volume Pre-set high-value standards for artificial intelligence. The average score of the stored tire repair priority. The weighting coefficients are as follows: The admission score judgment unit uses the high-value standard as the admission score if the remaining space is less than or equal to the minimum reserved volume, and the dynamic admission standard as the admission score if the remaining space is greater than the minimum reserved volume; the delivery queue judgment unit assigns a vehicle to the delivery queue if the repair priority score is greater than the admission score, and assigns it to the fragmentation queue if the repair priority score is less than the admission score.

[0040] The tire inventory management system collects parameters such as remaining space volume, total warehouse volume, occupied storage volume, and minimum reserved volume through the inventory area parameter acquisition unit. The admission standard preset unit sets a high-value standard and calculates the average score of the repair priority of stored tires. The score model calculation unit uses these parameters and weight coefficients to construct a dynamic admission standard model and calculates the admission score. When the remaining space is less than or equal to the minimum reserved volume, the high-value standard is used as the admission score; otherwise, the dynamic admission standard is used. The delivery queue judgment unit compares the tire's repair priority score with the admission score. Tires with higher admission scores are assigned to the delivery queue, and those with lower admission scores are assigned to the dismantling queue. For example, the total warehouse volume is 1000 cubic meters, the remaining space is 300 cubic meters, the minimum reserved volume is 200 cubic meters, the high-value standard is 80, the average priority is 70, and the weight coefficient is 0.6. Because the remaining space is greater than the minimum reserved volume, the calculated dynamic admission score is 56. A certain tire has a repair priority score of 60, which is higher than the admission score, so it is assigned to the delivery queue.

[0041] Example 2

[0042] This application provides a process for recovering gas generated from the pyrolysis of waste tires, including:

[0043] Tire particles are thermally pyrolyzed to obtain pyrolyzed oil and gas and solid residue.

[0044] The cracked oil and gas are cooled by a condenser, and the cracked oil and non-condensable gas are separated by condensation.

[0045] Non-condensable gas is passed into a gas purification device to remove pollutants and obtain purified gas.

[0046] The purified gas is compressed by a compression device and stored in a gas storage tank, or directly delivered to a combustion device for use as fuel.

[0047] The tire pyrolysis treatment system first pyrolyzes tire particles to generate pyrolyzed oil and gas and solid residue. Then, the pyrolyzed oil and gas are cooled by a condenser to separate pyrolyzed oil and non-condensable gas. The non-condensable gas then enters a gas purification device to remove pollutants, resulting in purified gas. The purified gas is then compressed by a compression device and can be stored in a gas storage tank or directly supplied to a combustion device for use as fuel. For example, a factory pyrolyzes 100 kg of tire particles to obtain 20 liters of pyrolyzed oil and a large amount of non-condensable gas. After purification and compression, part of the purified gas is stored in a gas storage tank, and the remainder is directly used to power the combustion device, thus efficiently realizing resource recovery and utilization.

[0048] The steps of the methods or algorithms described in this application can be directly embedded in hardware, software units executed by a processor, or a combination of both. Exemplarily, a storage medium can be connected to a processor so that the processor can read information from and write information to the storage medium. Optionally, the storage medium can also be integrated into the processor. Optionally, the processor and the storage medium can also be located in different components within a terminal. These computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable apparatus for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0049] Although this application has been described in conjunction with specific features and embodiments, it is obvious that various modifications and combinations can be made thereto without departing from the spirit and scope of this application. Accordingly, this specification and drawings are merely illustrative examples of this application and are considered to cover any and all modifications, variations, combinations, or equivalents within the scope of this application. Clearly, those skilled in the art can make various alterations and modifications to this application without departing from its scope. Thus, if such modifications and modifications fall within the scope of this application and its equivalents, this application intends to include such modifications and modifications.

Claims

1. A waste tire sorting and conveying system, characterized in that, The system includes: The tire classification module is used to classify tires by diameter and tire cord material by whether the cords can be magnetically attracted. The tire surface defect judgment unit is used to analyze and judge tire surface defect data based on the tire repair index database. The repair priority processing module is used to construct a multi-dimensional evaluation matrix to obtain tire repair priorities; The tire priority delivery module is used to analyze and determine the delivery queue based on the repair priority score; The repair priority processing module is used to construct a multi-dimensional evaluation matrix to obtain tire repair priorities, including: Matrix building unit, used to construct multi-dimensional evaluation matrices; The scoring formula construction unit is used to construct the repair priority scoring formula. It inputs the quantitative repair cost, tire model repair time, defect parameter number, parameter weight, and parameter score into the weighted total score formula to obtain the repair priority score. The formula for the total weighted score is as follows: ； in To fix priority scores, To quantify repair costs, The basic repair time for the tire model. This is the defect parameter number. For the first The weight of each defect, For the first The rating of each defect It is the repair time for the i-th defect. These are the batch repair adjustment parameters for the i-th defect; The repair priority output unit is used to analyze and determine the tire repair priority based on the total repair priority score.

2. The system according to claim 1, characterized in that, The tire classification module is used to classify tires by size based on tire diameter data and by tire cord material based on whether the cords can be magnetically attracted, including: Waste tire cleaning module, used to clean impurities from waste tires; The tire diameter measurement module is used to receive the tire diameter and obtain tire diameter data; The database preset unit is used to preset the tire size classification database, which includes the diameter range of small tires, the diameter range of medium tires, and the diameter range of large tires. The model analysis unit is used to classify tire models based on tire diameter data; The model determination unit is used to sort tires as small tires if the measured tire diameter data is within the range of small tire diameters, as medium tires if the measured tire diameter data is within the range of medium tire diameters, and as large tires if the measured tire diameter data is within the range of large tire diameters. The size parameter acquisition unit acquires a set of size parameters and obtains tire model repair time data based on the set of size parameters. Cord detection unit, used for magnetically detecting the material of tire cords; The cord material analysis and judgment unit is used to classify tires as steel cord tires if they can be attracted by a magnet, and as fiber cord tires if they cannot be attracted by a magnet.

3. The system according to claim 1, characterized in that, The tire surface defect judgment unit is used to analyze and judge tire surface defect data based on the tire repair index database, including: The tire repair index database preset unit is used to preset the tire repair index database and obtain the tire repair index data range. The tire 3D scanning and modeling module is used to scan the tire surface to create a model and identify tire surface defect data based on the model. The defect data analysis unit is used to analyze and judge tire surface defect data based on the tire repair index database. The defect data analysis and judgment unit is used to enter the repair stage if the tire surface defect data has corresponding repair index data in the tire repair index data range, and to generate the defect parameter sequence number and the corresponding quantitative repair cost. If the tire surface defect data does not have corresponding repair index data in the tire repair index data range, it will not enter the repair stage and will be directly judged as having no retreading value.

4. The system according to claim 3, characterized in that, The tire priority delivery module is used to analyze and determine the delivery queue based on the repair priority score, including: The inventory area parameter acquisition unit is used to collect a set of parameters for the tire inventory area, including remaining space volume, total warehouse volume, occupied storage volume, and minimum reserved volume. The access standard preset unit presets high-value standards and obtains the average value of the stored tire repair priority scores based on the repair priority scores. The score model calculation unit constructs an access score calculation model by taking the collected tire inventory area parameter set, manually preset high-value standards, and the average of the stored tire repair priority scores, and inputting them into the above calculation model. The calculation model is as follows: ； in For dynamic access standards, The remaining space volume, The total warehouse volume Pre-set high-value standards for artificial intelligence. The average score of the stored tire repair priority. These are the weighting coefficients; The admission score determination unit is used to determine the admission score if the remaining space is less than or equal to the minimum reserved volume, and to determine the admission score if the remaining space is greater than the minimum reserved volume. If the repair priority score is greater than the admission score, the unit in the delivery queue will assign the item to the delivery queue; otherwise, it will assign the item to the pyrolysis queue.

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