Building solid waste recycled aggregate production line control method and system

Abstract

The embodiment of the invention provides a building solid waste recycled aggregate production line control method and system, and relates to the technical field of building solid waste recycling, the method comprises the following steps: obtaining a first operation parameter of crushing equipment, and identifying a first characteristic of the crushing equipment influenced by a viscous material according to the first operation parameter; acquiring a second operation parameter of the screening equipment, and identifying a second feature of the screening equipment influenced by the viscous material according to the second operation parameter; acquiring a conveying state of the conveying equipment, and identifying a third feature of the conveying equipment influenced by the viscous material according to the conveying state; performing correlation analysis on the first feature, the second feature and the third feature to obtain a viscous state judgment result of the viscous material; generating a material viscosity index according to the viscosity state judgment result; and according to the material viscosity index, the operation parameters of the crushing equipment, the screening equipment and the conveying equipment are adjusted. The production efficiency and the product quality of the recycled aggregate can be improved, and equipment abrasion and energy consumption are reduced.

Description

Technical Field

[0001] This application relates to the field of construction solid waste recycling technology, and in particular to a method and system for controlling a construction solid waste recycled aggregate production line. Background Technology

[0002] In related technologies, production lines for recycled aggregates from construction solid waste transform demolished concrete, bricks, and other waste materials into reusable building materials. These lines typically include a feed hopper, a primary jaw crusher, a secondary cone crusher, a multi-layer vibrating screen, and a conveying and stockpiling system. The central control unit monitors the operating information of each piece of equipment, such as current, speed, and material level, and adjusts the conveyor belt speed, crusher discharge port gap, and vibrating screen vibration frequency and amplitude to achieve optimal production efficiency and aggregate quality. However, existing production line control methods face significant challenges when the moisture and viscosity of sticky materials change significantly, such as when a large amount of moist soil or clay is mixed in. Summary of the Invention

[0003] This application aims to address at least one of the technical problems existing in the prior art. To this end, this application proposes a method and system for controlling a production line of recycled aggregates from construction solid waste, aiming to improve the production efficiency and product quality of recycled aggregates, and reduce equipment wear and energy consumption.

[0004] In a first aspect, the embodiments of this application provide a method for controlling a production line of recycled aggregates from construction solid waste, comprising:

[0005] Obtain the first operating parameters of the crushing equipment, and identify the first characteristic of the crushing equipment affected by sticky materials based on the first operating parameters;

[0006] The second operating parameters of the screening equipment are obtained, and a second characteristic of the screening equipment affected by the viscous material is identified based on the second operating parameters.

[0007] The conveying status of the conveying equipment is obtained, and a third characteristic of the conveying equipment being affected by the viscous material is identified based on the conveying status.

[0008] A correlation analysis is performed on the first feature, the second feature, and the third feature to obtain the viscous state judgment result of the viscous material;

[0009] Based on the viscosity state judgment result, a material viscosity index is generated;

[0010] Adjust the operating parameters of the crushing equipment, the screening equipment, and the conveying equipment according to the material viscosity index.

[0011] According to some embodiments of this application, the step of performing correlation analysis on the first feature, the second feature, and the third feature to obtain the viscous state judgment result of the viscous material further includes:

[0012] The main motor speed of the crushing equipment is increased or the eccentric stroke of the crushing equipment is finely adjusted according to a preset cycle.

[0013] When the main motor speed of the crushing equipment is increased or the eccentric stroke of the crushing equipment is finely adjusted, the instantaneous flow rate of the conveying equipment is monitored within a preset response observation window;

[0014] The state of the viscous material is obtained based on the change in instantaneous flow rate;

[0015] Based on the state of the viscous material, the first feature, the second feature, and the third feature are correlated to obtain the viscous state judgment result of the viscous material.

[0016] According to some embodiments of this application, the step of performing correlation analysis on the first feature, the second feature, and the third feature based on the state of the viscous material to obtain the viscous state judgment result of the viscous material includes:

[0017] Obtain information on the compositional changes of the viscous material, the material viscosity index, and the actual operating index of the production line;

[0018] Based on the deviation between the material viscosity index and the actual operating index of the production line, the material viscosity index evaluation deviation information is obtained;

[0019] Based on the component change information or the material viscosity index evaluation deviation information, adjust the weights used to generate the material viscosity index to obtain the target weights;

[0020] Based on the target weight and the state of the viscous material, a correlation analysis is performed on the first feature, the second feature, and the third feature to obtain the viscous state judgment result of the viscous material.

[0021] According to some embodiments of this application, obtaining the component change information of the viscous material includes:

[0022] The changes in the concentration of active components detected at multiple preset component monitoring points for the same batch of viscous material were obtained;

[0023] Based on the changes in the concentration of the active component, the real-time concentration of the active component when the viscous material enters the crushing equipment is predicted.

[0024] Based on the real-time concentration of the active component, the compositional change information of the viscous material is obtained.

[0025] According to some embodiments of this application, adjusting the operating parameters of the crushing equipment, the screening equipment, and the conveying equipment based on the material viscosity index includes:

[0026] The mutual influence relationship among the crushing equipment, the screening equipment, and the conveying equipment is evaluated, and the mutual influence relationship evaluation results are obtained.

[0027] Based on the material viscosity index and the evaluation results of the mutual influence relationship, the parameter adjustment priorities of the crushing equipment, the screening equipment, and the conveying equipment are determined;

[0028] Adjust the priority based on the parameters, and adjust the operating parameters of the crushing equipment, the screening equipment, and the conveying equipment.

[0029] According to some embodiments of this application, the assessment of the mutual influence relationship among the crushing equipment, the screening equipment, and the conveying equipment, and the obtaining of the mutual influence relationship assessment result, includes:

[0030] Initial monitoring data is obtained by real-time monitoring of key operating parameters of the crushing equipment, the screening equipment, and the conveying equipment, and target monitoring data is obtained by outlier detection and missing value filling of the initial monitoring data.

[0031] The target monitoring data is subjected to time-series correlation analysis to identify synchronous change patterns and lag response patterns.

[0032] Based on the synchronous change mode and the hysteresis response mode, construct an inter-process influence relationship matrix;

[0033] Based on the inter-process influence matrix, the mutual influence relationships among the crushing equipment, the screening equipment, and the conveying equipment are evaluated to obtain the mutual influence relationship evaluation results.

[0034] According to some embodiments of this application, determining the parameter adjustment priority of the crushing equipment, the screening equipment, and the conveying equipment based on the material viscosity index and the evaluation results of the mutual influence relationship includes:

[0035] Assess the frequency and amplitude of fluctuations in the viscosity index of the material, as well as the confidence level in the assessment results of the interaction relationship;

[0036] Based on the fluctuation frequency and amplitude or the confidence level, a steady-state priority determination mode is obtained;

[0037] Obtain the real-time operating margins of the crushing equipment, the screening equipment, and the conveying equipment;

[0038] Based on the real-time operating margin, adjust the parameters of the crushing equipment, the screening equipment, and the conveying equipment to adjust the urgency level.

[0039] Based on the steady-state priority determination mode and the urgency of parameter adjustment, the parameter adjustment priorities of the crushing equipment, the screening equipment, and the conveying equipment are determined.

[0040] According to some embodiments of this application, the assessment of the fluctuation frequency and amplitude of the material viscosity index, and the confidence level in the assessment results of the mutual influence relationship, further includes:

[0041] Obtain vibration spectrum characteristic information of the crushing equipment, the screening equipment, and the conveying equipment;

[0042] The correlation between the fluctuation frequency and amplitude of the material viscosity index and the vibration spectrum characteristic information is analyzed to obtain the correlation analysis results;

[0043] When the correlation analysis results match the preset analysis results, the correlation between the fluctuation frequency and amplitude of the material viscosity index and the preset failure mode is identified, and the correlation identification results are obtained.

[0044] Based on the correlation identification results, adjust the confidence level in the mutual influence relationship assessment results.

[0045] According to some embodiments of this application, determining the parameter adjustment priorities of the crushing equipment, the screening equipment, and the conveying equipment based on the steady-state priority determination mode and the urgency of parameter adjustment includes:

[0046] The degree of fluctuation in the viscosity index of the material is obtained;

[0047] Based on the fluctuation of the material viscosity index and the evaluation results of the mutual influence relationship, an adjustment smoothing factor is obtained;

[0048] The parameter adjustment priorities of the crushing equipment, the screening equipment, and the conveying equipment are determined based on the steady-state priority determination mode, the urgency of parameter adjustment, and the adjustment smoothing factor.

[0049] Secondly, embodiments of this application provide a control system for a recycled aggregate production line from construction solid waste, comprising:

[0050] The first acquisition module is used to acquire the first operating parameters of the crushing equipment and identify the first feature of the crushing equipment affected by sticky materials based on the first operating parameters.

[0051] The second acquisition module is used to acquire the second operating parameters of the screening equipment, and identify the second characteristic of the screening equipment affected by the viscous material based on the second operating parameters;

[0052] The third acquisition module is used to acquire the conveying status of the conveying equipment and identify a third feature of the conveying equipment being affected by the viscous material based on the conveying status.

[0053] The analysis module is used to perform correlation analysis on the first feature, the second feature, and the third feature to obtain the viscous state judgment result of the viscous material;

[0054] The generation module is used to generate the material viscosity index based on the viscosity state judgment result;

[0055] The adjustment module is used to adjust the operating parameters of the crushing equipment, the screening equipment, and the conveying equipment according to the viscosity index of the material.

[0056] According to the technical solution of the embodiments of this application, at least the following beneficial effects are achieved: The embodiments of this invention obtain first operating parameters of a crushing device and identify a first characteristic of the crushing device being affected by viscous materials based on the first operating parameter values; obtain second operating parameters of a screening device and identify a second characteristic of the screening device being affected by the viscous materials based on the second operating parameters; obtain the conveying state of a conveying device and identify a third characteristic of the conveying device being affected by the viscous materials based on the conveying state; perform correlation analysis on the first characteristic, the second characteristic, and the third characteristic to obtain a viscous state judgment result of the viscous material; generate a material viscosity index based on the viscous state judgment result; and adjust the operating parameters of the crushing device, the screening device, and the conveying device based on the material viscosity index. The embodiments of this application can improve the production efficiency and product quality of recycled aggregates, and reduce equipment wear and energy consumption.

[0057] Additional aspects and advantages of this application will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of this application. Attached Figure Description

[0058] The accompanying drawings are used to provide a further understanding of the technical solutions of this application and constitute a part of the specification. They are used together with the embodiments of this application to explain the technical solutions of this application and do not constitute a limitation on the technical solutions of this application.

[0059] Figure 1 A schematic flowchart of a method for controlling a production line of recycled aggregates from construction solid waste provided in one embodiment of this application;

[0060] Figure 2 This is a schematic diagram of a control system for a construction solid waste recycled aggregate production line provided in one embodiment of this application. Detailed Implementation

[0061] To make the objectives, technical methods, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0062] It should be noted that the meaning of "multiple" (or "more than") in the description of the embodiments of this application refers to two or more, and "greater than," "less than," "exceeding," etc. are understood to exclude the number itself, while "above," "below," "within," etc. are understood to include the number itself. If "first," "second," etc. are used in the description, they are only for the purpose of distinguishing technical features and should not be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated or the order of the technical features indicated.

[0063] In this application embodiment, "at least one" refers to one or more, and "more than one" refers to two or more. "And / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent the existence of A alone, the simultaneous existence of A and B, or the existence of B alone. A and B can be singular or plural. The character " / " generally indicates that the preceding and following related objects are in an "or" relationship. "At least one of the following" and similar expressions refer to any combination of these items, including any combination of singular or plural items. For example, at least one of a, b, and c can represent: the existence of a alone, the existence of b alone, the existence of c alone, the simultaneous existence of a and b, the simultaneous existence of a and c, the simultaneous existence of b and c, or the simultaneous existence of a, b, and c, where a, b, and c can be single or multiple.

[0064] In the description of this application, unless otherwise expressly defined, terms such as "setup," "installation," and "connection" should be interpreted broadly, and those skilled in the art can reasonably determine the specific meaning of the above terms in this application in conjunction with the specific content of the technical solution.

[0065] Based on the above, this application proposes a method and system for controlling a production line of recycled aggregates from construction solid waste, which aims to improve the production efficiency and product quality of recycled aggregates, and reduce equipment wear and energy consumption.

[0066] The method for controlling a recycled aggregate production line from construction solid waste provided in this application can be applied to a terminal, a server, or software running on either a terminal or a server. In some embodiments, the terminal can be a smartphone, tablet, laptop, desktop computer, etc.; the server can be configured as an independent physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server providing basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, content delivery networks (CDN), and big data and artificial intelligence platforms; the software can be an application that implements the method for controlling a recycled aggregate production line from construction solid waste, but is not limited to the above forms.

[0067] This application can be used in numerous general-purpose or special-purpose computer system environments or configurations. Examples include: personal computers, server computers, handheld or portable devices, tablet devices, multiprocessor systems, microprocessor-based systems, set-top boxes, programmable consumer electronics, network PCs, minicomputers, mainframe computers, and distributed computing environments including any of the above systems or devices. This application can be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc., that perform specific tasks or implement specific abstract data types. This application can also be practiced in distributed computing environments where tasks are performed by remote processing devices connected via communication networks. In distributed computing environments, program modules can reside in local and remote computer storage media, including storage devices. It should be noted that in various specific embodiments of this invention, when processing is required based on data related to the characteristics of an object (e.g., a user's attribute information or a set of attribute information), permission or consent from the corresponding object is obtained first, and the collection, use, and processing of this data comply with relevant laws and standards. Furthermore, when the embodiments of the present invention need to obtain the attribute information of an object, they will obtain the separate permission or separate consent of the corresponding object through pop-up windows or redirection to a confirmation page. After obtaining the separate permission or separate consent of the corresponding object, they will then obtain the relevant data of the object necessary for the embodiments of the present invention to operate normally.

[0068] See Figure 1 , Figure 1This is a flowchart illustrating a method for controlling a recycled aggregate production line from construction solid waste, as provided in one embodiment of this application. The method for controlling a recycled aggregate production line from construction solid waste, as provided in this embodiment, includes, but is not limited to, steps S110 to S160, which will be described in detail below.

[0069] Step S110: Obtain the first operating parameters of the crushing equipment, and identify the first characteristic of the crushing equipment affected by sticky materials based on the first operating parameters;

[0070] Step S120: Obtain the second operating parameters of the screening equipment, and identify the second characteristic of the screening equipment affected by sticky materials based on the second operating parameters;

[0071] Step S130: Obtain the conveying status of the conveying equipment, and identify the third characteristic of the conveying equipment affected by viscous materials based on the conveying status;

[0072] Step S140: Perform correlation analysis on the first feature, the second feature, and the third feature to obtain the viscous state judgment result of the viscous material;

[0073] Step S150: Generate the material viscosity index based on the viscosity state judgment result;

[0074] Step S160: Adjust the operating parameters of the crushing equipment, screening equipment, and conveying equipment according to the material viscosity index.

[0075] It should be noted that crushing equipment refers to mechanical equipment used for primary and secondary crushing of construction solid waste, such as jaw crushers, cone crushers, or impact crushers. The first operating parameter may include, but is not limited to, motor current, spindle speed, discharge port gap, vibration frequency, bearing temperature, and liner wear. The first characteristic refers to specific operational anomalies or trends exhibited by the crushing equipment when affected by sticky materials, such as increased motor current fluctuations, increased risk of crushing chamber blockage, and poor discharge. Screening equipment is used to classify the particle size of crushed materials, such as vibrating screens and drum screens. Its "second operating parameter" may include screen vibration frequency, amplitude, material accumulation height on the screen surface, undersize material flow rate, and oversize material particle size distribution. The second characteristic refers to anomalies that occur when the screening equipment processes sticky materials, such as screen clogging, decreased screening efficiency, and excessive fineness of undersize material. Conveying equipment typically refers to equipment used to transfer materials between different processes in a production line, such as belt conveyors and screw conveyors. The conveying status can include conveyor belt speed, motor load, instantaneous material flow rate, conveyor belt deviation, and material accumulation. The third characteristic is the abnormalities that occur when the conveying equipment is conveying viscous materials, such as conveyor belt slippage, material adhesion, blockage, and deviation. Viscous materials are those containing high moisture content and fine particles (such as mud and clay), which are prone to agglomeration and adhesion under pressure or vibration. The material viscosity index is a quantitative indicator used to comprehensively assess the viscosity of viscous materials; the higher the index, the greater the material viscosity and the more significant the impact on production line operation.

[0076] In one embodiment, the operating current and power consumption of the crushing equipment can be monitored in real time by installing a current sensor and a power meter on the main motor. When sticky materials enter the crushing chamber, the crushing load changes due to material adhesion and blockage, causing abnormal fluctuations or continuous increases in motor current and power. Vibration sensors can also be installed to monitor the vibration spectrum of the crushing equipment. Sticky materials may impede material flow within the crushing chamber, thus causing changes in the equipment's vibration mode. By analyzing these parameters, primary characteristics such as decreased crushing efficiency and accelerated liner wear can be identified.

[0077] In one embodiment, a laser rangefinder or visual recognition system can be installed above the screen surface of the vibrating screen to monitor the accumulation height and distribution of material on the screen surface in real time. When the screen mesh becomes clogged, material will accumulate abnormally on the screen surface. Simultaneously, a particle size analyzer or flow meter can be installed at the outlet of the undersize material to monitor the particle size distribution and flow rate of the undersize material in real time. Clogged pores caused by sticky materials will reduce the amount of fine material undersize and introduce fine powder into the coarse material, resulting in abnormal particle size distribution or a decrease in flow rate. By comprehensively analyzing these parameters, secondary characteristics such as screen mesh clogging and reduced screening efficiency can be identified.

[0078] In one embodiment, a current sensor can be installed on the drive motor of the conveyor belt to monitor its load current. When viscous material adheres to the conveyor belt or causes material accumulation, it increases the conveying load, thereby causing the motor current to rise. Alternatively, belt misalignment sensors can be installed on both sides of the conveyor belt to monitor the degree of belt misalignment in real time. Uneven distribution or adhesion of viscous material may lead to uneven stress on the conveyor belt, causing misalignment. By analyzing these parameters, a third characteristic such as conveyor belt slippage, material adhesion, and blockage can be identified. A multivariate analysis model can be established, taking the first characteristic of the crushing equipment, the second characteristic of the screening equipment, and the third characteristic of the conveying equipment as inputs. By analyzing the synchronicity, lag, and mutual influence relationships between these characteristics, a comprehensive judgment can be made on whether the current viscous material has high viscosity and the degree of influence of viscosity on various stages of the production line.

[0079] In one embodiment, the viscosity state judgment result can be quantified into an index from 0 to 100 based on the correlation analysis results. For example, when the judgment result shows that the material viscosity is low, the material viscosity index may be 20; when the judgment result shows that the material viscosity is extremely high and has seriously affected the production line, the material viscosity index may be 90. The generation of this index can be based on a preset rule base or machine learning model. By training on historical data, the system can automatically generate the corresponding material viscosity index based on the current viscosity state judgment result. When the material viscosity index is high, the system can automatically adjust the discharge port gap of the crushing equipment, appropriately increasing the gap to reduce the risk of blockage; at the same time, it can adjust the vibration frequency and amplitude of the screening equipment to enhance the screening effect and reduce clogging; it can also adjust the speed of the conveyor belt to adapt to the conveying characteristics of viscous materials and avoid slippage and accumulation.

[0080] It is worth noting that the embodiments of this application can acquire multi-dimensional operating parameters of crushing, screening, and conveying equipment, identify their characteristics affected by viscous materials, and then perform correlation analysis on these characteristics to comprehensively and in real-time grasp the viscous state of the viscous materials. As a result, the system can generate a quantified material viscosity index, providing a precise basis for subsequent parameter adjustments. Based on this material viscosity index, the system can intelligently adjust the operating parameters of the crushing, screening, and conveying equipment, thereby improving the production efficiency and product quality of recycled aggregates, and reducing equipment wear and energy consumption.

[0081] It should be noted that periodically increasing the main motor speed of the crushing equipment or fine-tuning the eccentric stroke of the crushing equipment according to a preset cycle allows the system to periodically apply a controlled disturbance to the crushing equipment. The main motor speed can be increased by a preset amount (e.g., 5% to 10%) or the eccentric stroke of the crushing equipment can be slightly adjusted at regular intervals (e.g., every few minutes or hours). This active mechanical disturbance makes the adhesion, agglomeration, or flow obstruction characteristics of sticky materials more apparent within the crushing chamber or as they pass through the crushing equipment, thus providing clearer signals for subsequent monitoring.

[0082] In one embodiment, assuming that during the operation of the construction solid waste recycled aggregate production line, the system automatically triggers a detection mechanism every 10 minutes. The main motor speed of the crushing equipment is briefly increased by 5% (e.g., from 1000 rpm to 1050 rpm) for 5 seconds. During this period and within the subsequent 10-second response observation window, the instantaneous flow sensor of the conveying equipment continuously monitors the material flow data. If a significant decrease in instantaneous flow is observed after the speed increase, and the flow recovers slowly after the speed returns to normal, or if there is increased flow fluctuation, it can be determined that the current viscous material has a high viscosity. If the instantaneous flow drops from the normal value of 200 tons / hour to 150 tons / hour and fails to recover to above 190 tons / hour within 10 seconds, the system will identify it as a "high viscosity" state. This "high viscosity" state information is then input into the correlation analysis module for comprehensive analysis with the first characteristic of the crushing equipment, the second characteristic of the screening equipment, and the third characteristic of the conveying equipment, thereby obtaining a more accurate viscosity state judgment result.

[0083] It should be noted that the compositional change information for viscous materials can include changes in key components such as moisture content, clay content, fine powder content, and organic matter content. This information can be obtained through online sensors, spectrometers, or periodic sampling and testing. The material viscosity index is a quantitative indicator used to characterize the degree of material viscosity, obtained from the aforementioned steps. Actual operating indices of the production line may include, but are not limited to, energy consumption of crushing equipment, main motor current, vibration frequency, clogging frequency and screen wear of screening equipment, and instantaneous flow rate, belt slippage, and material accumulation height of conveying equipment. These indices can reflect the real-time operating status of the production line when processing the current material. The deviation between the material viscosity index and the actual operating index of the production line can be understood as the difference between the system's predicted value of the material viscosity (material viscosity index) and the actual performance of the production line (actual operating index of the production line). If the material viscosity index predicts a low viscosity, but the actual operating index of the production line shows abnormally high equipment load or frequent clogging, it indicates a significant assessment deviation. This deviation information is used to indicate the accuracy of the current viscosity judgment model.

[0084] It should be noted that adjusting the weights of the generated material viscosity index to obtain the target weights involves dynamically adjusting the proportions of each feature (first feature, second feature, and third feature) in the correlation analysis based on information about component changes or material viscosity index assessment deviations. When a significant increase in the mud content of the material is detected, the weights of features such as crushing equipment energy consumption or screening equipment clogging frequency in viscosity judgment can be increased. When the assessment deviation is large, the weights of each feature can be adaptively adjusted according to the direction and magnitude of the deviation to make the judgment result closer to reality. The target weights are the adjusted set of weights used for more accurate correlation analysis. Therefore, based on the target weights and the state of the viscous material, correlation analysis is performed on the first, second, and third features to obtain the viscosity state judgment result of the viscous material. This means that in the final viscosity state judgment, fixed weights are no longer used, but target weights that have been adjusted and optimized in real time are used, so that the judgment result can better reflect the current true viscosity state of the material and the actual operation of the production line.

[0085] In one embodiment, during a production process, the system detects through online sensors that the soil content in the construction solid waste entering the crushing equipment is significantly higher than in regular batches. Simultaneously, based on the current material viscosity index, the system predicts a moderate viscosity level. However, in actual operation, the main motor current of the crushing equipment (part of the actual operating index of the production line) remains consistently high, and the screens of the screening equipment show signs of partial blockage. At this point, the system identifies a significant assessment deviation between the material viscosity index and the actual operating index of the production line. Based on this, the control system dynamically adjusts the weights of the generated material viscosity index according to the component changes due to increased soil content and the assessment deviation information. The system may increase the weights of the main motor current of the crushing equipment and the blockage frequency of the screening equipment in the viscosity state correlation analysis, while appropriately reducing the weights of other features. In this way, the system can obtain a target weight that more accurately reflects the current situation. Subsequently, using this target weight, the system re-correlates the first feature of the crushing equipment, the second feature of the screening equipment, and the third feature of the conveying equipment to obtain a more accurate judgment result reflecting the true viscosity state of the material with high soil content. For example, the judgment result may be adjusted from "medium viscosity" to "high viscosity". Based on this more accurate judgment result, the system can adjust the operating parameters of the crushing equipment, the vibration frequency of the screening equipment, or the belt speed of the conveyor in a timely manner to effectively cope with the challenges posed by high viscosity materials, avoid equipment blockage, and ensure the continuous and stable operation of the production line.

[0086] It should be noted that the change in active component concentration refers to the change in the concentration of specific components (e.g., moisture content, clay mineral content, fine powder content, or organic matter content) in viscous materials over time or space that may lead to increased viscosity. These active components may vary significantly between different batches of construction solid waste, and their concentration directly affects the material's adhesiveness and flowability. Multiple pre-set component monitoring points can be deployed at different locations at the feed end of the production line, such as in the raw material stockpile, at the entrance of the primary conveyor belt, or in the pretreatment area before entering the crushing equipment. These sensors may include, but are not limited to, near-infrared spectrometers, humidity sensors, and X-ray fluorescence analyzers, for real-time or near-real-time detection of the active component concentration in the material.

[0087] In one embodiment, the real-time concentration of active components when viscous material enters the crushing equipment is predicted based on changes in the concentration of active components. The prediction process aims to overcome the lag caused by the physical distance between the sensor location and the crushing equipment, as well as the material transport time. Time series analysis models (such as ARIMA, LSTM, etc.) or prediction algorithms based on physical models can be used, combining historical data and current monitoring point readings to accurately estimate the concentration of active components when the material arrives at the crushing equipment. This yields a dynamic, real-time active component concentration reflecting the current material characteristics. Finally, based on the real-time active component concentration, information on the compositional changes of the viscous material is obtained. This can be a specific concentration value, a concentration change trend, a viscosity risk level, or a comprehensive description of the material's characteristics. This compositional change information will serve as input for subsequent correlation analysis to more accurately determine the viscosity state of the viscous material.

[0088] It should be noted that assessing the interrelationships between crushing, screening, and conveying equipment aims to quantify the degree of interaction between different devices during operation. Changes in the feed rate or crushing intensity of the crushing equipment can directly affect the load of downstream screening equipment, thereby impacting the conveying efficiency of the conveying equipment. This interrelationship assessment can be modeled based on historical operating data, using methods such as time-series analysis, correlation analysis, or causal inference to identify synchronous change patterns and lag response patterns between devices. The purpose is to provide a global perspective for subsequent parameter adjustments, avoiding overall performance degradation due to local optimization. Specifically, determining parameter adjustment priorities based on the material viscosity index and the interrelationship assessment results requires the system to intelligently determine which parameters of which equipment should be adjusted first, and by how much, when facing changes in material viscosity. When the material viscosity index is high, it may be necessary to prioritize adjusting the speed or stroke of the crushing equipment to reduce the risk of clogging. Simultaneously, if the assessment results indicate that adjusting the crushing equipment would significantly impact the screening equipment, then the parameter adjustment strategy for the screening equipment must also be considered when adjusting the crushing equipment parameters. This priority can be dynamically generated based on preset rules, optimization algorithms, or machine learning models, with the aim of ensuring the effectiveness of the adjustment and minimizing the negative impact on production line stability.

[0089] In one embodiment, it is assumed that the production line detects a continuous increase in the viscosity index of the material, indicating a significant increase in the viscosity of the viscous material. The system first initiates an assessment of the interrelationships between the crushing equipment, screening equipment, and conveying equipment. By analyzing historical data and real-time sensor information, the system identifies that: when the main motor speed of the crushing equipment is too high, it may increase the risk of screen blockage in the screening equipment; while when the vibration frequency of the screening equipment is too low, it will exacerbate the load on the conveying equipment. Based on this interrelationship assessment, the system, combined with the current condition of the highly viscous material, determines the priority of parameter adjustments. The priority may be set as follows: first, moderately increase the main motor speed of the crushing equipment to enhance crushing capacity, while closely monitoring the load of the screening equipment and the instantaneous flow rate of the conveying equipment; if the screening equipment shows signs of blockage, then prioritize adjusting the vibration frequency of the screening equipment, and may simultaneously fine-tune the belt speed of the conveying equipment to match the processing capacity. Through this prioritized and interconnected adjustment method, the production line can efficiently handle viscous materials, avoid the negative chain reactions that may be caused by adjusting a single piece of equipment, and ensure the smoothness and efficiency of the entire production process.

[0090] It should be noted that key operating parameters may include, but are not limited to, the equipment's motor current, vibration frequency, bearing temperature, material flow rate, screen clogging level, and conveyor belt tension. These parameters can directly or indirectly reflect the equipment's operating status and material characteristics. Real-time monitoring refers to continuously acquiring the instantaneous values ​​of these parameters through sensors, industrial control systems, or data acquisition and monitoring systems. Initial monitoring data may be affected by environmental interference, sensor malfunctions, or communication anomalies during the acquisition process, leading to outliers (such as spikes or outliers) or missing values. Therefore, preprocessing of the initial monitoring data is necessary. Outlier detection can employ statistical methods (such as Z-scores and IQR) or machine learning algorithms (such as isolated forests) to identify, remove, or correct unreasonable data points. Missing value imputation can use interpolation methods (such as linear interpolation and spline interpolation), mean imputation, or prediction based on historical data to complete the data, thereby obtaining high-quality target monitoring data and ensuring the accuracy of subsequent analysis.

[0091] It is worth noting that the inter-process influence matrix is ​​a quantitative representation used to describe the degree and direction of mutual influence between different equipment (i.e., different processes) in a production line. Each element of the matrix can represent the strength of one piece of equipment's influence on another, the type of influence (positive / negative), and the response time (for a delayed response mode). The rows and columns in the matrix represent crushing equipment, screening equipment, and conveying equipment, respectively, and the values ​​in the matrix represent the influence coefficients of the row equipment on the column equipment. This matrix can be constructed by quantifying the results of time-series correlation analysis, mapping indicators such as correlation coefficients, causal strength, or response delays to the matrix elements. Assessment refers to the comprehensive judgment and analysis of the complex interactions between various equipment in the entire production line based on the constructed inter-process influence matrix. This includes identifying key influence paths, determining dominant influencing factors, and predicting potential chain reactions. The results of the mutual influence assessment can be a detailed report containing information such as the quantitative influence values ​​between each piece of equipment, the influence mode (synchronous or delayed), the direction of influence (positive or negative), and the confidence level. This result provides data support and decision-making basis for subsequent parameter adjustment priorities.

[0092] It should be noted that a steady-state priority determination model can be derived based on the confidence level of the fluctuation frequency and amplitude of the material viscosity index or the evaluation results of the interaction relationship. This model aims to ensure the overall stability of the production line operation, especially when the material viscosity index fluctuates significantly or the confidence level of the interaction relationship evaluation results is low. It prioritizes parameter adjustments with less impact on production line stability or adopts a more conservative adjustment strategy. When the material viscosity index fluctuates drastically, the system may tend to choose parameter adjustment schemes with less impact on the production line to avoid new instability caused by over-adjustment. Furthermore, obtaining the real-time operating margin of crushing, screening, and conveying equipment involves obtaining the difference between the current operating state of each piece of equipment and its design limits or safe operating range. For motors, the operating margin can be the difference between its current load rate and rated load rate; for screening equipment, it can be the difference between its screen clogging degree and the maximum clogging threshold. Real-time operating margins reflect the current adjustability and potential risks of the equipment. Based on the real-time operating margins, the urgency of parameter adjustments for crushing, screening, and conveying equipment can be determined. When equipment has a small operating margin, indicating that it is approaching its operating limit or facing potential risks, the urgency of parameter adjustments will be increased to prompt the system to take measures as soon as possible to avoid equipment overload or failure. Conversely, when the operating margin is sufficient, the urgency of parameter adjustments can be appropriately reduced, allowing for more flexible adjustment strategies.

[0093] In one embodiment, if the system detects a high frequency and large amplitude fluctuation in the material viscosity index over a certain period, and historical data analysis reveals a relatively low confidence level in the assessment of the interaction between the crushing and screening equipment under current operating conditions, the system will prioritize a steady-state-first priority determination mode. Even if the material viscosity index indicates a need for significant adjustment, the system will tend to choose an adjustment scheme with less impact on the production line and lower risk, prioritizing fine-tuning the conveyor speed to smooth the feed rather than immediately and drastically adjusting the main motor speed of the crushing equipment. Simultaneously, if the system detects a low real-time operating margin for the main motor of the crushing equipment (e.g., the motor load rate is close to 90%), the system will increase the urgency of adjusting the crushing equipment parameters, but will still combine this with the steady-state-first mode, choosing to make small, gradual adjustments while ensuring stability, or prioritizing adjustments to other equipment with sufficient operating margins to avoid overloading the crushing equipment. Through this comprehensive consideration, the system can more intelligently balance production line efficiency and stability, ensuring that the production line maintains a highly efficient and stable operating state even under complex and changing operating conditions.

[0094] It should be noted that obtaining vibration spectrum characteristics of crushing, screening, and conveying equipment refers to deploying vibration sensors at key components of these devices (such as motors, bearings, and transmission mechanisms) to collect vibration signals in real time. These raw vibration signals are then processed using spectral analysis methods such as Fourier transform to extract their vibration spectrum characteristics, such as vibration amplitude at specific frequencies, harmonic components, and resonant frequencies. These characteristics can reflect the operational stability of the equipment and whether there are mechanical faults or abnormal operating conditions such as imbalance, misalignment, bearing wear, or poor gear meshing.

[0095] In one embodiment, it is assumed that in a construction solid waste recycled aggregate production line, when the viscosity of viscous materials suddenly increases, the frequency and amplitude of fluctuations in the material viscosity index also increase. Simultaneously, the vibration sensor of the crushing equipment detects a significant increase in amplitude at a specific frequency (e.g., a frequency associated with bearing wear) in the vibration spectrum of its main motor. The system analysis reveals a strong correlation between this fluctuation in the material viscosity index and the anomaly in this specific vibration spectrum, and this anomaly matches a preset "crushing equipment bearing wear" fault mode. Based on this correlation identification result, the system determines that the current assessment of the interaction between the crushing equipment, screening equipment, and conveying equipment may be uncertain due to the potential failure risk of the crushing equipment. Therefore, the system lowers the confidence level in the interaction assessment results. This adjustment will cause subsequent parameter adjustment priority determination processes to be more inclined to protect the crushing equipment. For example, even if increasing the crushing equipment's speed is necessary to improve output, the system may choose a more conservative adjustment strategy due to the lower confidence level, or prioritize triggering maintenance warnings for the crushing equipment, thereby avoiding accelerated equipment damage due to excessive pursuit of output.

[0096] It is worth noting that by introducing the volatility of the material viscosity index and an adjustment smoothing factor, the problems of oversensitivity or insufficient smoothness that may exist in existing methods when determining parameter adjustment priorities are effectively solved. The volatility of the material viscosity index provides a more macroscopic and comprehensive perspective for assessing the stability of the material's viscous state, avoiding misjudgments that may be caused by focusing only on the frequency and amplitude of local fluctuations. It is precisely because of the consideration of the overall volatility that the system can more accurately determine whether a large-scale or urgent adjustment is needed. On this basis, by combining the volatility with the evaluation results of the interaction relationship, an adjustment smoothing factor is dynamically generated. This smoothing factor can flexibly handle the final parameter adjustment priority. When the system is in a relatively stable state or the fluctuation is small, the smoothing factor will promote a more gentle adjustment, thereby avoiding unnecessary frequent adjustments, reducing equipment wear and energy consumption; while when the fluctuation is severe and a rapid response is required, the smoothing factor allows for a more aggressive adjustment. This mechanism ensures that parameter adjustments can respond promptly to changes in viscous materials while also taking into account the steady-state operation requirements of the production line. Especially in the steady-state priority determination mode, the smoothing factor can better achieve a smooth transition and continuous optimization.

[0097] In one embodiment, the system detects that the material viscosity index exhibits small but frequent fluctuations over a certain period. First, the system assesses the degree of fluctuation in the material viscosity index. For example, this can be done by calculating the standard deviation of the material viscosity index over the past 5 minutes; if the standard deviation is less than a preset threshold, the fluctuation is considered small. Second, based on this small fluctuation and the assessment of the interaction relationships (e.g., a high confidence level in the impact of the crushing equipment on the screening equipment), the system calculates a large adjustment smoothing factor, such as 0.8. This means the system tends to make smoother adjustments.

[0098] Finally, this larger adjustment smoothing factor will be applied when determining the priority of parameter adjustments for crushing, screening, and conveying equipment. If the priority model and parameter adjustment urgency are determined based on steady-state priority, and the originally calculated priority for adjusting the main motor speed of the crushing equipment is medium, then after applying a smoothing factor of 0.8, the actual adjustment priority may be reduced to low-medium, or the adjustment range may be limited to a smaller range. This means that even if some fluctuations exist, the system will not immediately make large adjustments, but will choose a more moderate approach to maintain the overall steady-state operation of the production line. Conversely, if the material viscosity index fluctuates significantly (e.g., the standard deviation exceeds a high threshold), and the interaction relationship assessment results show a significant cascading effect between equipment, the system may calculate a smaller adjustment smoothing factor, such as 0.2. In this case, when determining the priority of parameter adjustments, this smaller smoothing factor will allow for faster and more aggressive adjustments to quickly address severe viscosity problems and prevent production line blockages or shutdowns.

[0099] See Figure 2 , Figure 2 This is a schematic diagram of a construction solid waste recycled aggregate production line control system according to one embodiment of this application. The construction solid waste recycled aggregate production line control system 200 includes:

[0100] The first acquisition module 210 is used to acquire the first operating parameters of the crushing equipment and identify the first feature of the crushing equipment affected by sticky materials based on the first operating parameters.

[0101] The second acquisition module 220 is used to acquire the second operating parameters of the screening equipment and identify the second characteristics of the screening equipment affected by sticky materials based on the second operating parameters.

[0102] The third acquisition module 230 is used to acquire the conveying status of the conveying equipment and identify the third feature of the conveying equipment affected by viscous materials based on the conveying status.

[0103] Analysis module 240 is used to perform correlation analysis on the first feature, the second feature and the third feature to obtain the viscous state judgment result of the viscous material;

[0104] The generation module 250 is used to generate the material viscosity index based on the viscosity state judgment result;

[0105] The adjustment module 260 is used to adjust the operating parameters of the crushing equipment, screening equipment, and conveying equipment according to the material viscosity index.

[0106] It should be noted that the information interaction and execution process between the above modules are based on the same concept as the method embodiments of this application. For details on their specific functions and technical effects, please refer to the method embodiments section, which will not be repeated here.

[0107] It will be understood by those skilled in the art that all or some of the steps and systems in the methods disclosed above can be implemented as software, firmware, hardware, and suitable combinations thereof. Some or all of the physical components can be implemented as software executed by a processor, such as a central processing unit, digital signal processor, or microprocessor, or as hardware, or as an integrated circuit, such as an application-specific integrated circuit. Such software can be distributed on a computer-readable medium, which can include computer storage media (or non-transitory media) and communication media (or transient media). As is known to those skilled in the art, the term computer storage media includes volatile and non-volatile, removable and non-removable media implemented in any method or technology for storing information (such as computer-readable instructions, data structures, program modules, or other data). Computer storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or other memory technologies, CD-ROM, digital versatile disc (DVD) or other optical disc storage, magnetic cartridges, magnetic tape, disk storage or other magnetic storage devices, or any other medium that can be used to store desired information and is accessible to a computer. Furthermore, as is known to those skilled in the art, communication media typically include computer-readable instructions, data structures, program modules, or other data in modulated data signals such as carrier waves or other transmission mechanisms, and may include any information delivery medium.

[0108] The foregoing has provided a detailed description of the preferred embodiments of this application. However, this application is not limited to the above-described embodiments. Those skilled in the art can make various equivalent modifications or substitutions without departing from the spirit of this application. All such equivalent modifications or substitutions are included within the scope defined in this application.

Claims

1. A method for controlling the production line of recycled aggregate from construction solid waste, characterized in that, include: Obtain the first operating parameters of the crushing equipment, and identify the first characteristic of the crushing equipment affected by sticky materials based on the first operating parameters; The second operating parameters of the screening equipment are obtained, and a second characteristic of the screening equipment affected by the viscous material is identified based on the second operating parameters. The conveying status of the conveying equipment is obtained, and a third characteristic of the conveying equipment being affected by the viscous material is identified based on the conveying status. A correlation analysis is performed on the first feature, the second feature, and the third feature to obtain the viscous state judgment result of the viscous material; Based on the viscosity state judgment result, a material viscosity index is generated; Adjust the operating parameters of the crushing equipment, the screening equipment, and the conveying equipment according to the material viscosity index.

2. The method according to claim 1, characterized in that, The step of performing correlation analysis on the first feature, the second feature, and the third feature to obtain the viscous state judgment result of the viscous material further includes: The main motor speed of the crushing equipment is increased or the eccentric stroke of the crushing equipment is finely adjusted according to a preset cycle. When the main motor speed of the crushing equipment is increased or the eccentric stroke of the crushing equipment is finely adjusted, the instantaneous flow rate of the conveying equipment is monitored within a preset response observation window; The state of the viscous material is obtained based on the change in instantaneous flow rate; Based on the state of the viscous material, the first feature, the second feature, and the third feature are correlated to obtain the viscous state judgment result of the viscous material.

3. The method according to claim 1, characterized in that, The step of performing correlation analysis on the first feature, the second feature, and the third feature based on the state of the viscous material to obtain the viscous state judgment result of the viscous material includes: Obtain information on the compositional changes of the viscous material, the material viscosity index, and the actual operating index of the production line; Based on the deviation between the material viscosity index and the actual operating index of the production line, the material viscosity index evaluation deviation information is obtained; Based on the component change information or the material viscosity index evaluation deviation information, adjust the weights used to generate the material viscosity index to obtain the target weights; Based on the target weight and the state of the viscous material, a correlation analysis is performed on the first feature, the second feature, and the third feature to obtain the viscous state judgment result of the viscous material.

4. The method according to claim 3, characterized in that, The step of obtaining the component change information of the viscous material includes: The changes in the concentration of active components detected at multiple preset component monitoring points for the same batch of viscous material were obtained; Based on the changes in the concentration of the active component, the real-time concentration of the active component when the viscous material enters the crushing equipment is predicted. Based on the real-time concentration of the active component, the compositional change information of the viscous material is obtained.

5. The method according to claim 1, characterized in that, The step of adjusting the operating parameters of the crushing equipment, the screening equipment, and the conveying equipment according to the material viscosity index includes: The mutual influence relationship among the crushing equipment, the screening equipment, and the conveying equipment is evaluated, and the mutual influence relationship evaluation results are obtained. Based on the material viscosity index and the evaluation results of the mutual influence relationship, the parameter adjustment priorities of the crushing equipment, the screening equipment, and the conveying equipment are determined; Adjust the priority based on the parameters, and adjust the operating parameters of the crushing equipment, the screening equipment, and the conveying equipment.

6. The method according to claim 5, characterized in that, The evaluation of the mutual influence among the crushing equipment, the screening equipment, and the conveying equipment, and the resulting mutual influence evaluation results, include: Initial monitoring data is obtained by real-time monitoring of key operating parameters of the crushing equipment, the screening equipment, and the conveying equipment, and target monitoring data is obtained by outlier detection and missing value filling of the initial monitoring data. The target monitoring data is subjected to time-series correlation analysis to identify synchronous change patterns and lag response patterns. Based on the synchronous change mode and the hysteresis response mode, construct an inter-process influence relationship matrix; Based on the inter-process influence matrix, the mutual influence relationships among the crushing equipment, the screening equipment, and the conveying equipment are evaluated to obtain the mutual influence relationship evaluation results.

7. The method according to claim 5, characterized in that, The step of determining the parameter adjustment priority of the crushing equipment, the screening equipment, and the conveying equipment based on the material viscosity index and the evaluation results of the mutual influence relationship includes: Assess the frequency and amplitude of fluctuations in the viscosity index of the material, as well as the confidence level in the assessment results of the interaction relationship; Based on the fluctuation frequency and amplitude or the confidence level, a steady-state priority determination mode is obtained; Obtain the real-time operating margins of the crushing equipment, the screening equipment, and the conveying equipment; Based on the real-time operating margin, adjust the parameters of the crushing equipment, the screening equipment, and the conveying equipment to adjust the urgency level. Based on the steady-state priority determination mode and the urgency of parameter adjustment, the parameter adjustment priorities of the crushing equipment, the screening equipment, and the conveying equipment are determined.

8. The method according to claim 7, characterized in that, The assessment of the fluctuation frequency and amplitude of the material viscosity index, and the confidence level in the assessment results of the interaction relationship, also includes: Obtain vibration spectrum characteristic information of the crushing equipment, the screening equipment, and the conveying equipment; The correlation between the fluctuation frequency and amplitude of the material viscosity index and the vibration spectrum characteristic information is analyzed to obtain the correlation analysis results; When the correlation analysis results match the preset analysis results, the correlation between the fluctuation frequency and amplitude of the material viscosity index and the preset failure mode is identified, and the correlation identification results are obtained. Based on the correlation identification results, adjust the confidence level in the mutual influence relationship assessment results.

9. The method according to claim 7, characterized in that, The step of determining the parameter adjustment priorities of the crushing equipment, the screening equipment, and the conveying equipment based on the steady-state priority determination mode and the urgency of parameter adjustment includes: The degree of fluctuation in the viscosity index of the material is obtained; Based on the fluctuation of the material viscosity index and the evaluation results of the mutual influence relationship, an adjustment smoothing factor is obtained; The parameter adjustment priorities of the crushing equipment, the screening equipment, and the conveying equipment are determined based on the steady-state priority determination mode, the urgency of parameter adjustment, and the adjustment smoothing factor.

10. A control system for a production line of recycled aggregates from construction solid waste, characterized in that, include: The first acquisition module is used to acquire the first operating parameters of the crushing equipment and identify the first feature of the crushing equipment affected by sticky materials based on the first operating parameters. The second acquisition module is used to acquire the second operating parameters of the screening equipment, and identify the second characteristic of the screening equipment affected by the viscous material based on the second operating parameters; The third acquisition module is used to acquire the conveying status of the conveying equipment and identify a third feature of the conveying equipment being affected by the viscous material based on the conveying status. The analysis module is used to perform correlation analysis on the first feature, the second feature, and the third feature to obtain the viscous state judgment result of the viscous material; The generation module is used to generate the material viscosity index based on the viscosity state judgment result; The adjustment module is used to adjust the operating parameters of the crushing equipment, the screening equipment, and the conveying equipment according to the viscosity index of the material.

Images