A regenerated sand cleaning and grading system based on three-screen normal distribution

Abstract

The application discloses a kind of based on three sieve normal distribution's recycled sand selection and grading system, belong to solid material screening technical field, it includes obtaining the feed characteristic parameter of recycled sand raw material;Recycled sand raw material is transported to three sieve screening device and based on the feed characteristic parameter executes classification screening process, generates three sieve grading data;Auxiliary separation is generated by introducing directional airflow, and airflow auxiliary separation recycled sand is generated;Collect the particle size information of airflow auxiliary separation recycled sand, and generate particle size distribution measurement result;Normal distribution fitting processing is executed, and normal distribution fitting result is generated;Grading control parameter is calculated, and dynamic adjustment is carried out, and optimization grading recycled sand is generated.The application realizes the dynamic optimization of recycled sand selection and grading by intelligent parameter acquisition, three sieve classification transportation, airflow auxiliary separation, particle size distribution acquisition, normal distribution fitting and grading optimization control function, and improves the uniformity of recycled sand product particle size distribution.

Description

Technical Field

[0001] This invention relates to the field of solid material screening technology, and in particular to a recycled sand selection and gradation system based on a three-screen normal distribution. Background Technology

[0002] Recycled sand is an artificial aggregate formed from construction waste through crushing, screening, and other processes. It can replace natural sand in the production of building materials such as concrete and mortar. One of the key quality indicators is particle size distribution, which is the proportion of particles of different sizes. Good gradation ensures the density, strength, and workability of building materials. Therefore, effective selection and gradation adjustment of recycled sand is a core step in realizing its high-value resource utilization, which usually involves using screening equipment to separate particles by size.

[0003] In existing technologies, the production of recycled sand typically employs multi-stage vibrating screens for mechanical screening to control its particle size range. The production line is equipped with screens of different aperture sizes to separate the crushed mixture into coarse, medium, and fine products according to their dimensions. Some processes are supplemented with simple air classification equipment, using airflow to remove some dust and light impurities. Most parameters throughout the production process, such as the amplitude and frequency of the vibrating screen and the airflow of the blower, are preset to fixed values ​​during equipment commissioning or manually adjusted by operators based on experience.

[0004] However, the aforementioned existing technical solutions have the following drawbacks: Due to the complex and varied sources of construction waste, the moisture content, impurity content, and particle hardness of recycled sand raw materials fluctuate in real time. Fixed screening and air separation parameters are difficult to adapt to these changes, resulting in unstable product gradation and poor quality consistency. Furthermore, simple open-loop control or manual adjustment has a lag in response and low precision, failing to accurately shape the product gradation. Simultaneously, traditional screening processes are ineffective in removing lightweight impurities similar in size to sand particles, affecting the final quality of the recycled sand. Summary of the Invention

[0005] To address the aforementioned issues, this invention provides a recycled sand selection and gradation system based on a three-screen normal distribution. Through intelligent parameter acquisition, three-screen grading and conveying, airflow-assisted separation, particle size distribution acquisition, normal distribution fitting, and gradation optimization control functions, the system achieves dynamic optimization of recycled sand selection and gradation, thereby improving the uniformity of particle size distribution in recycled sand products.

[0006] The above objectives can be achieved through the following approach:

[0007] A recycled sand selection and gradation system based on a three-screen normal distribution includes: acquiring feed characteristic parameters of recycled sand raw materials; conveying the recycled sand raw materials to a three-screen screening device and performing grading screening based on the feed characteristic parameters to generate three-screen gradation data; introducing directional airflow for auxiliary separation to generate airflow-assisted separated recycled sand; collecting particle size information of the airflow-assisted separated recycled sand to generate particle size distribution measurement results; performing normal distribution fitting processing to generate normal distribution fitting results; calculating gradation control parameters and dynamically adjusting them to generate optimized gradation recycled sand.

[0008] Furthermore, the parameter acquisition module includes: a raw material basic data generation unit, an impurity identification and analysis unit, and a characteristic parameter calculation unit; wherein, the raw material basic data generation unit is used to acquire the moisture content information and initial composition information of the recycled sand raw material to generate raw material basic data; the impurity identification and analysis unit is connected to the raw material basic data generation unit and is used to perform impurity identification and analysis processing on the raw material basic data to generate impurity identification results; the characteristic parameter calculation unit is connected to the impurity identification and analysis unit and is used to calculate the feed characteristic parameters based on the raw material basic data and the impurity identification results.

[0009] Furthermore, the three-screen grading and conveying module includes: a coarse screening separation unit, a medium screening separation unit, a fine screening separation unit, and a three-screen gradation data integration unit; wherein, the coarse screening separation unit is connected to the characteristic parameter calculation unit, and is used to sequentially pass the recycled sand raw material through the coarse screen to perform coarse particle separation based on the feed characteristic parameters, generating coarse screening separation data; the medium screening separation unit is connected to the coarse screening separation unit, and is used to receive the material discharged from the coarse screen, adjust the medium screen operating conditions according to the coarse screening separation data, and perform medium particle screening, generating medium screen separation data; the fine screening separation unit is connected to the medium screen separation unit, and is used to receive the material discharged from the medium screen, adjust the fine screen operating conditions according to the medium screen separation data, and perform fine particle screening, generating fine screening separation data; the three-screen gradation data integration unit is connected to the coarse screening separation unit, the medium screening separation unit, and the fine screening unit respectively, and is used to integrate the coarse screening separation data, the medium screening separation data, and the fine screening separation data to generate three-screen gradation data.

[0010] Furthermore, the airflow-assisted separation module includes: an airflow matching control unit, an airflow density classification unit, and a product collection unit; wherein, the airflow matching control unit is connected to the three-screen gradation data integration unit, and is used to adjust the airflow pressure, velocity, and injection angle according to the three-screen gradation data to generate airflow control commands for matching and grading states; the airflow density classification unit is connected to the airflow matching control unit, and is used to perform gas-solid two-phase flow density classification on the three-screen graded recycled sand raw material according to the airflow control commands to generate intermediate classification products; the product collection unit is connected to the airflow density classification unit, and is used to collect the intermediate classification products and integrate them to obtain airflow-assisted separated recycled sand.

[0011] Furthermore, the particle size distribution acquisition module includes: a real-time scanning unit, a noise filtering unit, and a distribution data integration unit; wherein, the real-time scanning unit is connected to the product collection unit and is used to perform real-time scanning of the airflow-assisted separation regenerated sand to generate raw scanning data; the noise filtering unit is connected to the real-time scanning unit and is used to filter measurement noise in the raw scanning data to generate filtered particle size data; the distribution data integration unit is connected to the noise filtering unit and is used to integrate the filtered particle size data to obtain particle size distribution measurement results.

[0012] Furthermore, the normal distribution fitting module includes: a distribution feature value extraction unit, a particle size fitting calculation unit, and a fitting result verification and output unit; wherein, the distribution feature value extraction unit is connected to the distribution data integration unit and is used to extract the distribution feature values ​​of the particle size distribution measurement results to generate a distribution feature dataset; the particle size fitting calculation unit is connected to the distribution feature value extraction unit and is used to perform curve fitting operations on the distribution feature dataset to generate a fitting intermediate curve; the fitting result verification and output unit is connected to the particle size fitting calculation unit and is used to verify the fitting intermediate curve and output the normal distribution fitting result.

[0013] Furthermore, the gradation optimization control module includes: a gradation deviation comparison unit, a gradation control parameter calculation unit, and a control execution unit; wherein, the gradation deviation comparison unit is connected to the fitting result verification and output unit, and is used to compare the normal distribution fitting result with the preset target gradation shape to generate a deviation correction value; the gradation control parameter calculation unit is connected to the gradation deviation comparison unit, and is used to calculate the gradation control parameters based on the deviation correction value; the control execution unit is connected to the gradation control parameter calculation unit, and is used to synchronously adjust the screen parameters of the three-screen screening device and the intensity parameters of the airflow-assisted separation process using the gradation control parameters to generate optimized gradation recycled sand.

[0014] Furthermore, the parameter acquisition module also includes a characteristic parameter calibration unit; wherein the characteristic parameter calibration unit is connected to the characteristic parameter calculation unit and is used to acquire the temperature information and particle hardness information of the recycled sand raw material, and to perform temperature compensation and hardness correction on the calculated feed characteristic parameters.

[0015] Furthermore, the gradation optimization control module also includes: a fitting deviation feedback unit; wherein, the fitting deviation feedback unit is connected to the gradation deviation comparison unit, and is used to identify the substandard particle size portion in the optimized gradation regenerated sand, generate substandard portion data; feed the substandard portion data back to the inlet end of the three-screen sieving device to generate a cyclic processing instruction; perform repeated sieving and airflow-assisted separation operations based on the cyclic processing instruction and update the particle size distribution measurement results to generate secondary optimized gradation regenerated sand.

[0016] Compared with the prior art, the present invention has the following advantages:

[0017] This invention achieves intelligent control of the recycled sand production process by constructing a complete closed-loop control loop that includes raw material characteristic parameter acquisition, three-screen classification, airflow-assisted separation, real-time particle size monitoring, and normal distribution fitting. The system can dynamically adjust screening and air separation parameters based on real-time fluctuations in raw material conditions, ensuring the stability of the production process under complex operating conditions. This overcomes the limitations of traditional methods that rely on fixed parameters or manual experience, improving the automation level of the production line and its adaptability to recycled sand raw materials from different sources.

[0018] This invention introduces the normal distribution as the core mathematical model for gradation evaluation and optimization, simplifying the complex particle distribution problem into the control of two key parameters: expectation and model standard deviation. This method not only makes the evaluation of gradation quality more scientific and accurate, but also makes the control objectives clearer. The system can continuously optimize the product gradation towards the ideal form, thereby improving the quality uniformity and performance reliability of recycled sand products, making them more in line with the requirements of high-standard building materials.

[0019] This invention solves the industry-wide problem of removing lightweight impurities with similar particle sizes but large density differences from recycled sand by organically combining and synergistically controlling two physical separation methods: three-screen mechanical sieving and airflow-assisted separation. Airflow separation, as a fine purification method, further purifies the sand based on sieving, reducing the impurity content in the final product and improving the purity of the recycled sand. This is crucial for the application of recycled sand in fields such as high-performance concrete.

[0020] Other features and advantages of the invention will be set forth in the description which follows, and will be apparent in part from the description, or may be learned by practicing the invention. The objects and other advantages of the invention may be realized and obtained by means of the structures pointed out in the description, claims and drawings. Attached Figure Description

[0021] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0022] Figure 1 This is a framework diagram of a recycled sand selection and gradation system based on a three-screen normal distribution according to an embodiment of the present invention;

[0023] Figure 2 This is a schematic diagram of a recycled sand beneficiation and gradation system based on a three-screen normal distribution according to an embodiment of the present invention;

[0024] Figure 3 This is a flowchart of the normal distribution fitting module in an embodiment of the present invention. Detailed Implementation

[0025] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0026] Reference Figure 1 One embodiment of the present invention proposes a recycled sand selection and gradation system based on a three-screen normal distribution. Through intelligent parameter acquisition, three-screen grading and conveying, airflow-assisted separation, particle size distribution acquisition, normal distribution fitting and gradation optimization control functions, the system realizes dynamic optimization of recycled sand selection and gradation, and improves the uniformity of particle size distribution of recycled sand products.

[0027] like Figure 2 As shown, the system in this embodiment specifically includes: a parameter acquisition module, a three-screen grading and conveying module, an airflow-assisted separation module, a particle size distribution acquisition module, a normal distribution fitting module, and a gradation optimization control module; wherein,

[0028] S1, Parameter Acquisition Module, used to acquire the feeding characteristic parameters of recycled sand raw materials;

[0029] Furthermore, the parameter acquisition module includes: a raw material basic data generation unit, an impurity identification and analysis unit, and a characteristic parameter calculation unit; among which,

[0030] The raw material basic data generation unit is used to obtain the moisture content information and initial composition information of the recycled sand raw material and generate the raw material basic data.

[0031] The impurity identification and analysis unit is connected to the raw material basic data generation unit and is used to perform impurity identification and analysis processing on the raw material basic data to generate impurity identification results.

[0032] The characteristic parameter calculation unit is connected to the impurity identification and analysis unit and is used to calculate the feed characteristic parameters based on the raw material basic data and impurity identification results.

[0033] Specifically, the raw material basic data generation unit performs the acquisition of physical state data of the recycled sand raw material. The purpose is to obtain two core initial conditions affecting screening efficiency and impurity separation: moisture content and particle composition. This unit typically deploys a non-contact sensor array above the feed conveyor belt. For example, a near-infrared spectral sensor is used to monitor the moisture content of the material flow in real time, with a measurement frequency set between 10-50Hz to capture dynamic changes in material moisture. Simultaneously, a vision system based on laser contour scanning and a high-speed industrial camera continuously scans the material on the conveyor belt. Image processing algorithms are used to analyze the initial particle size range, shape factor, and basic color texture characteristics of the recycled sand; this information collectively constitutes the initial composition information. The unit ultimately outputs a data stream containing timestamps, real-time moisture content, and preliminary particle size distribution characteristics—the raw material basic data.

[0034] The impurity identification and analysis unit performs in-depth processing on the aforementioned raw material baseline data. Its purpose is to accurately identify and quantify the content of non-aggregate impurities in the complex recycled sand mixture. This unit receives the data stream from the raw material baseline data generation unit and uses a pre-trained machine learning model, such as a convolutional neural network (CNN), for image recognition. Impurity identification analysis is based on the differences in color, texture, and shape between recycled sand aggregate and common impurities. For example, sawdust exhibits a fibrous texture, while plastic fragments have specific reflective properties. The model analyzes each image frame, calculates the pixel area ratio of various impurities in the material, and combines this with thickness information obtained from laser scanning to estimate the volume percentage, thereby generating the impurity identification result. This result not only represents the total amount of impurities but also provides a statistical classification of various impurities, offering crucial input for the subsequent fine-tuning of airflow separation parameters.

[0035] The characteristic parameter calculation unit integrates and processes all collected and analyzed data. The aim is to transform multi-source, heterogeneous raw data into a set of standardized feed characteristic parameters that can be directly used to control downstream equipment. This unit receives basic raw material data and impurity identification results, and calculates the final feed characteristic parameters using a pre-set comprehensive evaluation model. These parameters are typically vectors, and one of their key components, such as the screening efficiency adjustment coefficient, can be calculated using the following formula:

[0036] ,

[0037] in, This represents the final calculated screening efficiency adjustment coefficient, which is a core part of the output of the feed characteristic parameters. It is a baseline operating condition coefficient, which is usually calibrated based on the equipment model and standard sand sample. The weighting factor for the influence of moisture content was obtained by fitting experimental data and is used to correct for the particle adhesion effect caused by moisture. The real-time moisture content measured by the raw material basic data generation unit. This is the reference moisture content under ideal working conditions. The impurity impact weighting factor reflects the combined effect of impurities on screen clogging and material flowability. This represents the total volume percentage of impurities output by the impurity identification and analysis unit. The adjustment factor is adjusted as moisture content and impurity content increase. The coefficient will decrease accordingly and will be used to dynamically adjust the vibration frequency, amplitude or feeding speed of the three-screen screening device to compensate for the negative impact of raw material fluctuations on the screening effect and ensure the stable operation of the entire system.

[0038] For example, the real-time moisture content of the recycled sand raw material is measured by a near-infrared spectral sensor above the feed conveyor belt by the raw material basic data generation unit. The initial particle size distribution characteristics are obtained using a vision system, generating basic raw material data including timestamps. After receiving this data, the impurity identification and analysis unit uses a convolutional neural network model to identify the pixel area of ​​wood chips and plastic fragments, and estimates the total volume percentage of impurities by combining this with laser scanning thickness information. The value is 5%, which is used as the impurity identification result. The characteristic parameter calculation unit integrates the above multi-source data and sets the baseline operating condition coefficient. The weighting factor for moisture content is 0.95. The ideal operating condition reference moisture content is 0.12. The weighting factor is 3%, which is the effect of impurities. The value is 0.8. Substituting this into the formula, the calculation is... The original screening efficiency adjustment coefficient was obtained. It is 0.9065.

[0039] Furthermore, the parameter acquisition module also includes: a characteristic parameter calibration unit; wherein,

[0040] The characteristic parameter calibration unit, connected to the characteristic parameter calculation unit, is used to obtain the temperature and particle hardness information of the recycled sand raw material, and to perform temperature compensation and hardness correction on the calculated feed characteristic parameters.

[0041] Specifically, the unit acquires the temperature information of the recycled sand raw material in real time through an infrared temperature sensor deployed at the feed inlet. For example, when the detected material temperature is much higher or lower than the reference temperature of the calibrated operating conditions, it means that the material may be dry due to exposure to the sun or agglomerated due to low temperature, which will cause the screening efficiency adjustment coefficient based on moisture content to deviate.

[0042] This unit assesses the particle hardness of the material flow using online acoustic or microwave sensors. Recycled sand has a complex origin, potentially mixing high-strength concrete aggregate with low-strength brick slag, resulting in significant differences in hardness. High-hardness particles bounce more easily on the vibrating screen, leading to higher screening efficiency, while low-hardness particles may break during screening, altering their original particle size distribution. After acquiring temperature and particle hardness information, the characteristic parameter calibration unit applies a calibration model to fine-tune the calculated feed characteristic parameters. This calibration model can be an empirical formula or a lookup table. For example, temperature compensation and hardness correction are applied to the screening efficiency adjustment coefficient A, resulting in a corrected coefficient... It can be represented as:

[0043] ,

[0044] in, It is the calibrated screening efficiency adjustment coefficient. It is the original screening efficiency adjustment coefficient output by the characteristic parameter calculation unit. It is the temperature compensation coefficient, a dimensionless constant calibrated experimentally, used to quantify the degree of influence of temperature deviation on screening efficiency. It is the material temperature measured in real time. This is the system's reference operating temperature. It is the hardness correction coefficient, which is also a dimensionless constant calibrated in experiments, reflecting the influence of particle hardness changes on sieving behavior. It is a real-time assessment index of the average hardness of particles. This is the reference hardness of the recycled sand under calibration conditions. Through this calibration process, the system can more accurately predict the behavior of materials in subsequent processing stages, and the generated feed characteristic parameters are more reliable. This makes the control of the entire selection and gradation system more precise, especially when processing recycled sand raw materials with unstable sources and large fluctuations in operating conditions, thus improving its robustness and product quality stability.

[0045] For example, the characteristic parameter calibration unit measures the real-time material temperature of the current recycled sand raw material using an infrared temperature sensor deployed at the feed inlet. 10 Meanwhile, the average hardness index of this batch of particles was obtained through online evaluation using acoustic or microwave sensors. The value is 38. The system's preset reference operating temperature is known. For 20 Reference hardness The temperature compensation coefficient is 40, and it was obtained through experimental calibration. The hardness correction factor is 0.002. The value is 0.005. This unit receives the original screening efficiency adjustment coefficient calculated from the preceding steps. Its current value is 0.9065. A correction calculation is performed; the specific calculation process is as follows: The calibrated parameters eliminate the impact of material agglomeration due to low temperature and easy breakage due to low hardness on screening efficiency, ensuring the accuracy of amplitude and frequency adjustment of the subsequent three-screen screening device.

[0046] S2, Three-screen grading conveying module, is used to convey recycled sand raw materials to the three-screen screening device and perform grading screening based on the feed characteristic parameters to generate three-screen gradation data;

[0047] Furthermore, the three-screen grading and conveying module includes: a coarse screening separation unit, a medium screening separation unit, a fine screening separation unit, and a three-screen gradation data integration unit; among which,

[0048] The coarse screening and separation unit is connected to the characteristic parameter calculation unit. It is used to perform coarse particle separation by passing the recycled sand raw material through the coarse screen in sequence based on the feed characteristic parameters, and to generate coarse screening separation data.

[0049] The intermediate screening separation unit is connected to the coarse screening separation unit. It is used to receive the material discharged from the coarse screening, adjust the operating conditions of the intermediate screening unit according to the coarse screening separation data, perform intermediate particle screening, and generate intermediate screening separation data.

[0050] The fine screening separation unit is connected to the medium screening separation unit. It is used to receive the material discharged from the medium screening unit, adjust the fine screening conditions according to the medium screening separation data, perform fine particle screening, and generate fine screening separation data.

[0051] The three-screen gradation data integration unit is connected to the coarse screening separation unit, the medium screening separation unit, and the fine screening separation unit, respectively, and is used to integrate the coarse screening separation data, the medium screening separation data, and the fine screening separation data to generate three-screen gradation data.

[0052] Specifically, the coarse screening unit removes large particles. The purpose is to remove oversized aggregates, unbroken concrete blocks, and large debris from the recycled sand raw material to protect the subsequent medium and fine screens from impact damage. This unit receives feed characteristic parameters from the parameter acquisition module and dynamically adjusts the operating status of the vibrating screen accordingly. For example, when the screening efficiency adjustment coefficient A in the feed characteristic parameters is low, the system automatically reduces the feed speed or increases the amplitude of the vibrating screen, such as from 4 mm to 6 mm, to ensure sufficient dispersion and residence time of the material on the screen surface and prevent screen clogging. The screen aperture of the coarse screen is typically set between 5.0 and 10.0 mm. The material that passes through the screening enters the next stage, while the retained coarse particles are treated as waste or processed separately. A key action in this process is the use of weighing sensors installed on the under-screen conveyor belt to monitor the mass flow rate of the material passing through the screen in real time; the generated data stream is the coarse screening separation data.

[0053] The intermediate screening unit performs secondary separation on the material that has passed through the coarse screen. Its purpose is to separate the main aggregate component in the recycled sand, namely medium-sized sand particles. This unit receives the undersize material from the coarse screening unit, and its vibrating screen mesh size is typically set to 2.0-2.5 mm. Similar to the coarse screening unit, its operating parameters are also affected by the initial settings of the feed characteristic parameters. This unit separates the material into oversize and undersize. Similarly, mass flow meters deployed at the outlets of the oversize and undersize materials continuously acquire the mass information of both material streams, thereby generating intermediate screening separation data.

[0054] The fine screening unit performs the final mechanical screening. Its purpose is to separate fine sand from harmful components such as fine powder and dust, a crucial step in improving the quality of recycled sand. This unit processes the undersize material from the medium screening unit, using screens with smaller apertures, such as 0.15-0.30 mm. Due to the fine particle size and high powder content of the processed material, this unit is more sensitive to feed characteristic parameters, especially when the raw material has a high moisture content, requiring the activation of an auxiliary screen cleaning device to maintain screening efficiency. This unit also generates fine screening separation data through mass flow monitoring, recording the fine sand output and waste powder discharge.

[0055] The three-screen gradation data integration unit performs data aggregation and calculation. Its purpose is to integrate the discrete data generated from the first three separation steps into a structured data package that comprehensively reflects the current particle size distribution of the material. This unit does not perform physical operations but acts as a data processing center. It simultaneously receives coarse, medium, and fine screen separation data, which are essentially the real-time mass flow rates of materials in each particle size range. The mass percentage of each particle size is calculated using the following formula to generate the three-screen gradation data:

[0056] ,

[0057] in, This represents the final output three-sieve gradation data vector. This refers to the mass flow rate of granular sand in the oversize material generated by the intermediate screening unit. The mass flow rate of fine sand particles on the screen produced by the fine screening separation unit. This refers to the mass flow rate of the undersize powder generated by the fine screening separation unit. The total mass flow rate of material entering the three-screen grading and conveying module is equal to , , The sum of the mass flow rates of the material on the coarse screen and the coarse screen is precisely obtained through the weighing feeder at the inlet. This three-screen gradation data accurately describes the initial particle size distribution of the recycled sand after mechanical screening, serving as a core input to guide the precise control of the next stage airflow-assisted separation module.

[0058] For example, the coarse screening separation unit receives feed characteristic parameters from the parameter acquisition module, and when the calibrated screening efficiency adjustment coefficient is detected... When the feed rate is 0.957, the system reduces the feed speed to ensure sufficient material dispersion on the screen surface. At this point, the screen aperture of the coarse screen is set to 5.0 mm. The coarse screen separation data, i.e., the material mass flow rate, is monitored in real time by a weighing sensor installed on the under-screen conveyor belt. Next, the intermediate screen separation unit receives the under-screen material and performs secondary separation using a 2.0 mm aperture screen. The mass flow rate of the sand particles in the over-screen material is measured by a mass flow meter at the outlet. The system operates at a rate of 45 tons per hour, generating separation data for the medium-sized screen. Subsequently, the fine-screen separation unit performs final mechanical sieving on the material passing through the medium-sized screen, separating fine sand from micro-powder using a 0.15 mm mesh screen. The mass flow rate of the fine sand particles on the oversize screen is then monitored. The flow rate is 30 tons per hour, and the mass flow rate of the undersize powder is... At a rate of 15 tons per hour, fine screening separation data is generated. The three-screen gradation data integration unit synchronously receives the above flow information and obtains the total material mass flow rate measured by the weighing feeder at the inlet. At 100 tons per hour, the total amount is equal to and and The sum of the mass flow rates of large particles retained by the coarse screen. Substitute these values ​​into the formula for gradation calculation. The specific calculation process is as follows: The final output is a three-sieve gradation data vector. =[45,30,15], this data precisely describes the mass percentage of each particle size range after mechanical screening, which is used to guide the precise control of the subsequent airflow-assisted separation module.

[0059] S3, Airflow-assisted separation module, is used to generate airflow-assisted separated regenerated sand by introducing directional airflow based on three-screen gradation data.

[0060] Furthermore, the airflow-assisted separation module includes: an airflow matching control unit, an airflow density classification unit, and a product collection unit; wherein,

[0061] The airflow matching control unit is connected to the three-screen gradation data integration unit. It is used to adjust the airflow pressure, velocity and injection angle according to the three-screen gradation data, and generate airflow control commands for matching gradation status.

[0062] The airflow density classification unit is connected to the airflow matching control unit and is used to perform gas-solid two-phase flow density classification on the recycled sand raw material after three-screen classification according to the airflow control command, and generate classification intermediate products.

[0063] The product collection unit is connected to the airflow density classification unit and is used to collect intermediate products from the classification and integrate them to obtain airflow-assisted separation regenerated sand.

[0064] Specifically, the airflow matching control unit performs the decision-making and generation of airflow parameters. The purpose is to transform the three-sieve gradation data provided by the preceding modules into precise control commands for the airflow system. This unit receives real-time three-sieve gradation data from the three-sieve gradation data integration unit, which describes the mass percentage of each component—medium, fine, and powder. Based on this data, the control unit dynamically calculates the required airflow pressure, velocity, and injection angle using a multivariate control model. For example, when the three-sieve gradation data shows a high content of fine particles and powder, the system will appropriately reduce the airflow velocity to prevent valuable fine sand from being excessively blown away; conversely, if the content of medium particles and impurities is high, the airflow pressure and velocity will be increased to ensure sufficient separation kinetic energy. One of its core control commands, the target airflow velocity, can be calibrated and calculated using the following formula:

[0065] ,

[0066] in, To calculate the target flow velocity in the generated airflow control command. The preset reference flow rate is calibrated under standard operating conditions based on the equipment's processing capacity and the target sand type, for example, 8 meters per second. These represent the mass percentages of coarse, medium, and fine particles in the three-sieve gradation data. To correspond to the velocity influence weighting coefficients for each particle size class, these dimensionless coefficients were derived through regression analysis of extensive experimental data to quantify the impact of different particle size components on the required separation airflow intensity. The unit ultimately outputs standardized airflow control commands containing parameters such as target velocity, wind pressure, and injection angle.

[0067] The airflow density classification unit performs physical separation operations according to instructions. The purpose is to construct a stable gas-solid two-phase flow field, forcing particles of different densities to differentiate their trajectories within this flow field, thereby achieving separation. This unit is typically an air classifier or fluidized bed structure. The recycled sand raw material, after three-screen classification, enters the separation chamber at a controllable rate. Instructions generated by the airflow matching control unit are sent to the high-pressure blower and nozzle angle actuator, which introduce directional airflow according to the instructions. Inside the chamber, the denser recycled sand particles with faster settling velocities are less affected by the airflow and fall along the direction of gravity or move at the bottom of the chamber. Lighter impurities, whose settling velocity is less than the airflow velocity, are carried upwards by the airflow or blown to one side, forming two or more clearly separated material flows, i.e., the intermediate products of classification.

[0068] The product collection unit efficiently captures and integrates the separated materials. Its purpose is to collect the intermediate products from the classification process in a categorized manner and integrate them into the final product stream. This unit has collection systems installed at different outlets of the airflow density classification unit. Typically, a finished sand collection hopper is located below the classification chamber to collect the purified, high-quality regenerated sand. Downstream or laterally, cyclone separators and bag filters are installed to capture light impurities and dust carried away by the airflow. The collected high-quality regenerated sand is then converged and conveyed to form a unified material stream—airflow-assisted separation regenerated sand—and sent to the next stage for particle size distribution analysis.

[0069] For example, the airflow matching control unit receives a real-time three-sieve gradation data vector from the three-sieve gradation data integration unit. The mass percentages of coarse, medium, and fine particles are respectively To achieve precise separation, the system sets a reference flow rate. The velocity is 8 meters per second, and the influence weighting coefficient is determined based on experimental data. Substitute the values ​​into the formula to perform the decision calculation. The specific calculation process is as follows: Meters per second. Subsequently, the airflow density classification unit, based on instructions including the target flow velocity, corresponding wind pressure, and injection angle, performs gas-solid two-phase flow density classification on the regenerated sand raw material entering the separation chamber. Directional airflow causes lighter impurities to rise, while higher-density sand particles fall along the direction of gravity due to their faster settling velocity, thus generating intermediate products for classification. The product collection unit captures the purified sand particles in the finished sand collection hopper below the classification chamber, while simultaneously using a lateral cyclone separator to collect the blown-away light impurities and dust. Finally, the high-quality sand stream is integrated to obtain airflow-assisted separation regenerated sand, which is then sent to the particle size distribution collection stage.

[0070] S4, Particle size distribution acquisition module, is used to acquire particle size information of airflow-assisted separation regenerated sand and generate particle size distribution measurement results;

[0071] Furthermore, the particle size distribution acquisition module includes: a real-time scanning unit, a noise filtering unit, and a distribution data integration unit; wherein,

[0072] The real-time scanning unit, connected to the product collection unit, is used to perform real-time scanning of the airflow-assisted separation regenerated sand and generate raw scanning data.

[0073] The noise filtering unit, connected to the real-time scanning unit, is used to filter measurement noise in the raw scanning data and generate filtered particle size data.

[0074] The distribution data integration unit, connected to the noise filtering unit, is used to integrate the filtered particle size data to obtain particle size distribution measurement results.

[0075] Specifically, a real-time scanning unit performs continuous particle image capture. The aim is to acquire the instantaneous morphological information of high-speed regenerated sand particles flowing through the monitoring point without omission. This unit typically deploys a dynamic image analysis system. As the airflow-assisted separated regenerated sand passes through a free-fall channel with a stable background light source or on a uniformly moving conveyor belt, a high-frame-rate linear industrial camera continuously captures images at a frequency of thousands of times per second. The camera's optical resolution is typically set at the 10-micron level to ensure clear differentiation of fine sand particles. This process is triggered by a signal from a material flow sensor; once material is detected, scanning immediately begins, continuously generating a raw data stream containing numerous two-dimensional projection images of particles—the raw scan data.

[0076] The noise filtering unit purifies the massive amount of raw scan data. Its purpose is to remove invalid data caused by environmental interference, particle overlap, defocus blur, and other factors, extracting clear and independent information about individual particles. This unit receives the image stream from the real-time scanning unit and executes a series of image processing algorithms. The initial step is to apply an adaptive thresholding algorithm to binarize the image, separating the particles from the background. Next, median filtering or Gaussian filtering algorithms are used to smooth particle edges and remove random electrical noise. A crucial step is to use the watershed algorithm or connected component analysis to segment adhered and overlapping particles. Finally, based on preset validity criteria, such as roundness, aspect ratio, and pixel area range, image objects that do not meet the requirements, such as fragments, bubbles, or incompletely segmented particle clusters, are filtered out. After processing, the system calculates key dimensional parameters such as the equivalent circular diameter and maximum Feret diameter for each valid particle, forming a clean dataset containing the size information of all qualified particles—the filtered particle size data.

[0077] The distribution data integration unit statistically summarizes the filtered discrete data. The aim is to transform the size information of individual particles into a statistical distribution result that macroscopically describes the particle size composition of the entire batch of material. This unit receives the filtered particle size data and, according to preset particle size grading standards, such as 0.15 mm, 0.30 mm, and 0.60 mm sieve standards, assigns the particle data to corresponding particle size intervals. By calculating the total volume of particles falling into each interval and comparing it with the total volume of all measured particles, the mass percentage of each particle size interval is obtained, ultimately generating the particle size distribution measurement result. The mass percentage of each particle size interval can be calculated using the following formula:

[0078] ,

[0079] in, Representing the The mass percentage of each particle size range. It is calculated in the noise filtering unit and falls into the first... The first particle size range The volume of a particle is typically estimated based on its equivalent circular diameter and assumed to be sphere. This represents the total volume of all effective particles within this measurement cycle. The particle size distribution measurement result output by this unit is a standardized data table or vector that accurately reflects the particle size composition of the current product, serving as direct input to the normal distribution fitting module in the next stage.

[0080] For example, the real-time scanning unit captures two-dimensional projection images of particles at a frequency of thousands of times per second using a high-frame-rate linear industrial camera as the airflow-assisted separated regenerated sand passes through the free-fall channel, generating raw scan data containing a large amount of instantaneous morphological information. After receiving this image stream, the noise filtering unit removes environmental interference through an adaptive thresholding algorithm and median filtering, and segments adhered particles using a watershed algorithm. Subsequently, it calculates the equivalent circle diameter of each qualified particle, forming filtered particle size data. The distributed data integration unit divides this data into multiple intervals according to a preset standard, with the first interval being... Taking the nth particle size range as an example, if the nth particle size range detected in this range Particle volume If the particle sizes are 0.04 cubic millimeters, 0.05 cubic millimeters, and 0.06 cubic millimeters respectively, then the total volume of particles in this range is... The volume is 0.15 cubic millimeters. The total volume of all effective particles during this measurement period is known. The value is 1.0 cubic millimeters. This unit is substituted into the formula to perform statistical summarization. The specific calculation process is as follows: The mass percentage of this particle size range is obtained. The percentage is 15%. By performing the above calculations on all particle size ranges, the system ultimately integrates and generates standardized particle size distribution measurement results, providing accurate macroscopic particle size description data for subsequent normal distribution fitting.

[0081] S5, Normal Distribution Fitting Module, is used to perform normal distribution fitting processing on the particle size distribution measurement results and generate normal distribution fitting results;

[0082] Furthermore, the workflow of the normal distribution fitting module is as follows: Figure 3 As shown, the normal distribution fitting module includes: a distribution feature value extraction unit, a particle size fitting calculation unit, and a fitting result verification and output unit; wherein,

[0083] The distribution feature value extraction unit, connected to the distribution data integration unit, is used to extract the distribution feature values ​​of the particle size distribution measurement results and generate a distribution feature dataset;

[0084] The particle size fitting calculation unit is connected to the distribution feature value extraction unit and is used to perform curve fitting calculations on the distribution feature dataset to generate intermediate fitting curves.

[0085] The fitting result verification and output unit is connected to the particle size fitting calculation unit and is used to verify the fitting intermediate curve and output the normal distribution fitting result.

[0086] Specifically, the distribution feature extraction unit performs initial data analysis. Its purpose is to calculate key parameters describing the core statistical characteristics of the particle size distribution from the raw particle size distribution measurements. This unit receives particle size distribution measurements from the distribution data integration unit, i.e., a set of data pairs containing each particle size interval and its corresponding mass percentage. Based on this data, the unit calculates the weighted average particle size and the population standard deviation. The weighted average particle size reflects the central tendency of particle size, while the population standard deviation quantifies the dispersion or distribution width of particle size. These calculation results constitute the distribution feature dataset, and the calculation method for its core parameters is as follows:

[0087] ,

[0088] ,

[0089] in, This represents the calculated weighted average particle size. The standard deviation is the population standard deviation. For the first The center particle size value for each particle size range, for example, for the range of 0.15-0.30 mm. 0.225 mm is acceptable. It corresponds to the first The mass percentage of each particle size range is directly provided by the particle size distribution measurement results. These two characteristic values... and This forms the basis for subsequent fitting calculations.

[0090] The particle size fitting calculation unit performs the core mathematical fitting. Its purpose is to generate a normal distribution curve that best approximates the actual particle size distribution measurement results using the distribution feature dataset. This unit extracts the weighted average particle size... and population standard deviation As two core parameters of the normal distribution probability density function, namely expectation and model standard deviation The initial estimated values ​​are obtained. Based on the center particle size and corresponding mass percentage of each particle size interval, a weighted calculation is performed to obtain the measured average particle size and the overall standard deviation of the particle size. The average particle size is used as the initial value of the expected value of the normal distribution, and the overall standard deviation is used as the initial value of the model standard deviation. Then, the two parameters are iteratively optimized using a nonlinear least squares method, and the values ​​are continuously corrected to minimize the error between the fitted distribution curve and the actual detected particle size distribution. After the iteration is completed, the final expected value is determined. and model standard deviation The expected particle size represents the concentrated particle size of the recycled sand, and the standard deviation reflects the dispersion of particle size distribution. These two parameters are used to compare with the preset target gradation ratio, thereby adjusting the operating parameters of the screening and air separation equipment. Optimization algorithms, such as the Levenberg-Marquardt algorithm, are employed using nonlinear least squares methods to minimize the sum of squared residuals between the generated normal distribution curve and the actual measured mass percentage of each particle size interval. This process ultimately determines a set of optimal... and The value was calculated, and a continuous curve representing the current particle size distribution of the recycled sand was generated, i.e., the fitted intermediate curve.

[0091] The fitting result verification and output unit evaluates the effectiveness of the fit and outputs the final result. The aim is to ensure that the generated intermediate fitting curve accurately reflects the actual particle size distribution and is output in a standardized form. This unit compares the intermediate fitting curve with the original particle size distribution measurement results and calculates a goodness-of-fit index, such as the coefficient of determination. .like If the value is higher than the preset threshold, the fit is considered valid, and the particle size distribution of the recycled sand is considered to conform to a normal distribution. At this point, the unit will be the optimal... and The parameters, along with the judgment results, are packaged into a normal distribution fitting result. This result highly condenses complex particle size information, enabling the subsequent gradation optimization control module to perform efficient comparisons and decisions based on these two simple parameters. If the particle size distribution is below the threshold, the system may trigger an alarm, indicating that the particle size distribution of the current recycled sand is abnormal and not suitable for description by a single normal distribution.

[0092] For example, the distribution feature value extraction unit receives particle size distribution measurement results from the distribution data integration unit, which includes center particle size values ​​for multiple particle size intervals. With the corresponding mass percentage Assume the center particle size of three typical intervals. 0.225 mm 0.45 mm It is 0.75 mm, and its corresponding mass percentage 20% 50%, The value is 30%. Substitute this value into the formula to calculate the weighted average particle size. The specific calculation process is as follows: Then the population standard deviation is calculated, the specific process is as follows: This generates a distribution feature dataset. The particle size fitting calculation unit will... and As expected from the normal distribution and model standard deviation The initial values ​​are iteratively optimized using a nonlinear least squares method to generate a fitted intermediate curve. The fitting result is verified by comparing this curve with the original measurement results in the output unit, and the coefficient of determination is calculated. The value was 0.98, which was higher than the preset threshold, so the fit was deemed effective, and the final output package contained the optimal parameters. and The normal distribution fitting results provide an efficient decision-making basis for the subsequent gradation optimization control module.

[0093] S6, Gradation Optimization Control Module, is used to calculate gradation control parameters based on the normal distribution fitting results, and to dynamically adjust the three-screen screening device and airflow-assisted separation process to generate optimized gradation recycled sand.

[0094] Furthermore, the gradation optimization control module includes: a gradation deviation comparison unit, a gradation control parameter calculation unit, and a control execution unit; wherein,

[0095] The gradation deviation comparison unit is connected to the fitting result verification and output unit. It is used to compare the normal distribution fitting result with the preset target gradation shape and generate deviation correction value.

[0096] The gradation control parameter calculation unit is connected to the gradation deviation comparison unit and is used to calculate the gradation control parameters based on the deviation correction value.

[0097] The control execution unit is connected to the gradation control parameter calculation unit. It is used to synchronously adjust the screen parameters of the three-screen screening device and the intensity parameters of the airflow-assisted separation process using the gradation control parameters to generate optimized gradation recycled sand.

[0098] Specifically, the gradation deviation comparison unit performs the state assessment. The purpose is to quantify the difference between the current product gradation and the target gradation. This unit receives the normal distribution fitting result from the normal distribution fitting module, which represents the expected particle size distribution of the actual product. and model standard deviation Meanwhile, the system pre-stores one or more target gradation patterns, which are also represented by a set of target expectations. and the standard deviation of the target model To define, for example, the gradation of medium sand determined according to the standard for construction sand. Approximately 0.4 mm, Approximately 0.15 mm. This unit will measure the parameters. With target parameters ( A direct comparison is performed to calculate the expected deviation and the model standard deviation deviation. These two deviation values ​​constitute the deviation correction value, which precisely indicates the difference between the current gradation and the target in terms of central tendency and distribution width.

[0099] The gradation control parameter calculation unit makes decisions based on the deviation. The goal is to transform abstract deviation correction values ​​into executable physical equipment adjustment commands. This unit receives the deviation correction value and uses a PID control algorithm or a more complex fuzzy logic control model to calculate the gradation control parameters that need to be adjusted in the next cycle. For example, when the actual average particle size is detected... Smaller than the target average particle size At this point, it means the product is too fine, and the control algorithm will generate instructions to reduce the proportion of fine particles and increase the proportion of medium particles. This process can be driven by the following logic:

[0100] ,

[0101] ,

[0102] in, It refers to the change in the equivalent screen parameters of the fine screen in the three-screen screening device that needs to be adjusted. These are the intensity parameters of the airflow-assisted separation process that need to be adjusted, such as the change in flow velocity at this point. and These are the expected deviation and the model standard deviation deviation, respectively. To adjust the proportional gain coefficient for fine sieving, To adjust the integral gain coefficient for fine sieving, This represents the integral of the expected deviation over time, which is the total amount of particle size that is consistently coarser or finer over a period of time. This is the proportional gain coefficient corresponding to the airflow velocity adjustment. This refers to the integral gain coefficient corresponding to airflow velocity adjustment. The integral of the standard deviation over time represents the cumulative long-term particle dispersion offset. All four coefficients were determined through equipment calibration and field testing, and are used to quantify the adjustment range of gradation deviation on sieving and airflow parameters. The calculated... and These equal values ​​together constitute the gradation control parameters used to regulate the production process.

[0103] The control execution unit implements the calculated parameters. The purpose is to materialize the gradation control parameters into actual operations on the production equipment, completing closed-loop adjustments. This unit receives the gradation control parameters and converts them into control signals for the underlying hardware. For example, a positive... This could translate into instructions to increase the vibration frequency of the fine screen or replace it with a screen with a slightly larger aperture, in order to reduce the output of fine sand. A positive This can translate into an instruction to increase the fan speed, thereby enhancing the intensity of the airflow-assisted separation process, blowing away more fine powder and light impurities, and indirectly increasing the average particle size. By simultaneously adjusting the screen parameters of the three-screen sieving device and the intensity parameters of the airflow-assisted separation process, the system can achieve refined and multi-dimensional control over the final gradation of the recycled sand. After this series of actions, the newly produced recycled sand is optimized gradation recycled sand, whose particle size distribution will be closer to the preset target gradation, thus forming a continuously adaptive and optimized closed-loop production process.

[0104] For example, the gradation deviation comparison unit receives the measured expectation from the normal distribution fitting module. The value is 0.495 mm and the standard deviation of the measured model. The value is 0.187, and the system's pre-stored target expectation for medium sand is also obtained. For 0.4 mm and the standard deviation of the target model The value is 0.15, and a deviation correction value including the expected deviation and standard deviation is generated through direct comparison. The gradation control parameter calculation unit activates the control model based on these deviations and sets the proportional gain coefficient for the fine sieve. The integral gain coefficient is 1.5. The value is 0.1, and the proportional gain coefficient is based on airflow intensity. The integral gain coefficient is 2.0. The value is 0.2, which is substituted into the formula for decision-making. When the integral term is temporarily disregarded within the current period, the specific calculation process is as follows: Simultaneously calculate The control execution unit materializes the instructions into hardware signals based on the hierarchical control parameters, and then transmits them via a positive... Increase the vibration frequency of the fine screen to reduce fine sand output, and according to the positive... Increasing the fan speed enhances the airflow intensity, thereby blowing away more fine powder. By simultaneously adjusting the screen parameters of the three-screen sieving device and the intensity parameters of the airflow-assisted separation process, the system ultimately produces optimized graded recycled sand with a particle size distribution closer to the preset target.

[0105] Furthermore, the gradation optimization control module also includes: a fitting deviation feedback unit; wherein,

[0106] The fitting deviation feedback unit, connected to the gradation deviation comparison unit, is used to identify the non-compliant particle size portion in the optimized gradation recycled sand and generate data on the non-compliant portion.

[0107] The data that does not meet the standards is fed back to the inlet of the three-screening device to generate a cyclic processing instruction;

[0108] Based on the cyclic processing command, repeated screening and airflow-assisted separation operations are performed, and the particle size distribution measurement results are updated to generate secondary optimized gradation recycled sand.

[0109] Specifically, the fitting deviation feedback unit performs physical interception and quantitative identification of non-conforming material flow. The aim is to accurately cut out excess components causing gradation deviations from the initially processed product. This unit receives the comparison residual sequence from the gradation deviation comparison unit in real time. Once it detects that the actual mass percentage of a specific screen range, such as the 0.15 to 0.30 mm fine sand range, exceeds the set upper limit threshold of the product tolerance zone, the system immediately triggers the pneumatic reversing flap on the terminal unloading chute. This flap action intercepts and separates these excessively aggregated particles from the main stream; the stripped material flow is the portion with substandard particle size. Simultaneously, the system uses a belt scale on the branch conveyor belt to measure the return mass rate of this portion, establishing and saving an engineering combination of the corresponding particle size range and return mass characteristics, generating data for the substandard portion. The interception mass rate required for this interception process is calculated and defined using the following control formula:

[0110] ,

[0111] in This represents the target reflux quality rate that needs to be captured. It is the measured total output mass rate of materials that currently exceeds the standard particle size range. It is the percentage constant of the actual area occupied by this particle size range, calculated by the gradation deviation comparison unit. It is the baseline mass percentage constant for this range under ideal conditions. The tolerance for quality percentage deviation is set to a constant value such as 0.02. The formula is only activated and drives the flip-board action when the difference between the actual percentage and the baseline percentage exceeds the tolerance.

[0112] The fitting deviation feedback unit drives the equipment to initiate material return transmission and translates the substandard data into equipment collaborative control information. The purpose is to safely and uniformly return the stripped defective bulk material to the process starting point for reprocessing. This unit converts the calculated return data sequence into inverter control signals, first instructing a dedicated high-angle belt conveyor to start, which then lifts and pours the physically extracted bulk material to the inlet of the first-stage three-screen screening device. Simultaneously, a data packet containing a combination of belt speed control codes and feed port opening limits is issued to form a cyclic processing instruction. This instruction forces the primary quantitative feeder at the source to reduce the input quota of new raw materials, precisely compensating for the equipment processing space occupied by the returned material, thus avoiding the equipment protection risk of shutdown due to feed overload.

[0113] The execution layer performs a physical rotation closed-loop operation based on feedback commands and outputs the target results. The purpose is to integrate materials that fail to meet the standard on the first attempt into the new sand flow and subject them to mechanical vibration and aerodynamic filtration layer by layer to approximate the normal distribution standard. The returned mixed particles are subjected to vibration and scattering on a multi-layer screen and directional flow field shearing separation according to the issued recycling instructions. This superimposed processing completely changes the previously incomplete microscopic distribution, forcing the downstream particle size distribution acquisition module camera to capture a refreshed image of the sand and gravel array. Its underlying algorithm automatically erases the old registered data from the previous second to reflect the current situation, thereby updating the particle size distribution measurement results. The sand body that is finally released after this double or even multiple refinements and corrections is discharged into the main storage silo. Its physical composition is precisely fitted into the normal building aggregate gradation template, and the transformed result flow that meets all the rigid settings becomes the secondary optimized gradation recycled sand.

[0114] For example, the fitting deviation feedback unit performs physical interception of the non-conforming material flow when the gradation deviation comparison unit detects the actual mass percentage constant in the 0.15 to 0.30 mm fine sand range. It is 0.25, while the ideal reference mass percentage constant is... The tolerance for quality percentage deviation is 0.18. When the deviation is 0.02, the system triggers the pneumatic reversing flap action because the deviation exceeds the threshold. At this time, the measured total output mass rate of material within the current particle size range is... With a target recirculation mass rate of 20 tons per hour, this unit is used to calculate the required intercepted mass rate using the formula. The specific calculation process is as follows: The target reflux quality rate was obtained. At a rate of 1 ton per hour, this portion represents the substandard particle size and generates substandard data. Subsequently, the intercepted bulk material is returned to the inlet of the three-screening device via a high-angle belt conveyor, and a circulation processing command containing a belt speed control code is issued. This command instructs the source feeder to reduce the input of new raw material to compensate for the return space. Based on this command, the execution layer drives the material to undergo oscillating and scattering through multiple layers of screens and directional flow field vortex shearing separation, forcing the particle size distribution acquisition module to capture a refreshed image of the gravel and update the particle size distribution measurement results.

[0115] It should be noted that the electrical connections between the various units described above do not necessarily represent direct or indirect connections. Any indirect connection method can be applied to the embodiments of the present invention as long as it achieves the purpose of the present invention. The above descriptions are merely exemplary embodiments of the present invention and should not be construed as limiting the scope of the present invention.

[0116] All equivalent changes and modifications made in accordance with the teachings of this invention are still within the scope of this invention. Those skilled in the art will readily conceive of other embodiments of this invention upon considering the specification and the disclosure of practical truth. This application is intended to cover any variations, uses, or adaptations of this invention that follow the general principles of this invention and include common knowledge or conventional techniques in the art not described herein.

Claims

1. A recycled sand beneficiation and gradation system based on a three-screen normal distribution, characterized in that, The system includes: a parameter acquisition module, a three-screen grading and conveying module, an airflow-assisted separation module, a particle size distribution acquisition module, a normal distribution fitting module, and a gradation optimization control module; wherein... The parameter acquisition module is used to acquire the feed characteristic parameters of the recycled sand raw material. The parameter acquisition module includes: a raw material basic data generation unit, an impurity identification and analysis unit, and a characteristic parameter calculation unit. The raw material basic data generation unit acquires the moisture content and initial composition information of the recycled sand raw material to generate raw material basic data. The impurity identification and analysis unit, connected to the raw material basic data generation unit, performs impurity identification and analysis on the raw material basic data to generate impurity identification results. The characteristic parameter calculation unit, connected to the impurity identification and analysis unit, calculates the feed characteristic parameters based on the raw material basic data and the impurity identification results. The three-screen grading and conveying module is used to convey recycled sand raw materials to the three-screen screening device and perform grading and screening processing based on the feed characteristic parameters to generate three-screen gradation data. The three-screen grading and conveying module includes: a coarse screening separation unit, a medium screening separation unit, a fine screening separation unit, and a three-screen gradation data integration unit. The coarse screening separation unit is connected to the characteristic parameter calculation unit and is used to sequentially pass the recycled sand raw materials through the coarse screen to perform coarse particle separation based on the feed characteristic parameters, generating coarse screening separation data. The medium screening separation unit is connected to the coarse screening separation unit. The system comprises three sieve separation units: a coarse sieve separation unit (connected to the coarse sieve separation unit), a fine ... medium sieve separation unit), and a fine sieve separation unit (connected to the fine sieve separation unit), and a fine sieve separation unit (connected to the coarse sieve separation unit), a medium sieve separation unit, and a fine sieve separation unit, and a fine sieve separation unit (connected to the coarse sieve separation unit), a medium sieve separation unit, and a fine sieve separation unit, and a fine sieve separation unit, respectively, to integrate the coarse sieve separation data, the medium sieve separation data, and the fine sieve separation data to generate three-screen gradation data. The airflow-assisted separation module is used to assist separation by introducing directional airflow based on the three-screen gradation data to generate airflow-assisted separated regenerated sand. The airflow-assisted separation module includes: an airflow matching control unit, an airflow density classification unit, and a product collection unit. The airflow matching control unit is connected to the three-screen gradation data integration unit and is used to adjust the airflow pressure, velocity, and injection angle according to the three-screen gradation data to generate airflow control commands for matching the grading state. The airflow density classification unit is connected to the airflow matching control unit and is used to perform gas-solid two-phase flow density classification on the three-screen graded regenerated sand raw material according to the airflow control commands to generate intermediate classification products. The product collection unit is connected to the airflow density classification unit and is used to collect the intermediate classification products and integrate them to obtain airflow-assisted separated regenerated sand. The particle size distribution acquisition module is used to acquire particle size information of the airflow-assisted separation regenerated sand and generate particle size distribution measurement results. The particle size distribution acquisition module includes: a real-time scanning unit, a noise filtering unit, and a distribution data integration unit. The real-time scanning unit, connected to the product collection unit, is used to perform real-time scanning of the airflow-assisted separation regenerated sand and generate raw scanning data. The noise filtering unit, connected to the real-time scanning unit, is used to filter measurement noise in the raw scanning data and generate filtered particle size data. The distribution data integration unit, connected to the noise filtering unit, is used to integrate the filtered particle size data to obtain the particle size distribution measurement results. The normal distribution fitting module is used to perform normal distribution fitting processing on the particle size distribution measurement results to generate normal distribution fitting results. The normal distribution fitting module includes: a distribution feature value extraction unit, a particle size fitting calculation unit, and a fitting result verification and output unit. The distribution feature value extraction unit, connected to the distribution data integration unit, is used to extract the distribution feature values ​​of the particle size distribution measurement results to generate a distribution feature dataset. The particle size fitting calculation unit, connected to the distribution feature value extraction unit, is used to perform curve fitting operations on the distribution feature dataset to generate an intermediate fitting curve. The fitting result verification and output unit, connected to the particle size fitting calculation unit, is used to verify the intermediate fitting curve and output the normal distribution fitting result. The gradation optimization control module is used to calculate gradation control parameters based on the normal distribution fitting results and dynamically adjust the three-screen sieving device and the airflow-assisted separation process to generate optimized gradation recycled sand. The gradation optimization control module includes: a gradation deviation comparison unit, a gradation control parameter calculation unit, and a control execution unit. The gradation deviation comparison unit, connected to the fitting result verification and output unit, is used to compare the normal distribution fitting results with a preset target gradation shape and generate a deviation correction value. The gradation control parameter calculation unit, connected to the gradation deviation comparison unit, is used to calculate the gradation control parameters based on the deviation correction value. The control execution unit, connected to the gradation control parameter calculation unit, is used to synchronously adjust the screen parameters of the three-screen sieving device and the intensity parameters of the airflow-assisted separation process using the gradation control parameters to generate optimized gradation recycled sand.

2. The recycled sand selection and gradation system based on a three-screen normal distribution according to claim 1, characterized in that, The parameter acquisition module further includes: a characteristic parameter calibration unit; wherein... The characteristic parameter calibration unit is connected to the characteristic parameter calculation unit and is used to obtain the temperature information and particle hardness information of the recycled sand raw material, and to perform temperature compensation and hardness correction on the calculated feed characteristic parameters.

3. The recycled sand selection and gradation system based on a three-screen normal distribution according to claim 1, characterized in that, The gradation optimization control module further includes: a fitting deviation feedback unit; wherein... The fitting deviation feedback unit is connected to the gradation deviation comparison unit and is used to identify the non-compliant particle size portion in the optimized gradation recycled sand and generate non-compliant portion data. The data of the substandard portion is fed back to the inlet of the three-screen sieving device to generate a cyclic processing instruction; Based on the cyclic processing instructions, repeated screening and airflow-assisted separation operations are performed, and the particle size distribution measurement results are updated to generate secondary optimized gradation recycled sand.

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