Carbon emission reduction working system based on subway shield muck in-situ machine-made sandstone production and reuse

Abstract

The invention belongs to the technical field of building engineering green construction and resource utilization, and particularly relates to a carbon emission reduction working system based on subway shield muck in-situ machine-made gravel production and reuse. Comprising a data acquisition module, a data transmission and preprocessing module, a data storage and analysis module, a carbon emission reduction strategy generation module, a real-time monitoring and feedback module and a visual display module, through mutual cooperation of all the modules, different scheme optimization is generated for soil layers with different water contents, and original data is collected; and accurate data is provided for carbon transaction.

Description

Technical Field

[0001] This invention belongs to the field of green construction and resource utilization technology in building engineering, specifically involving a carbon emission reduction system based on the in-situ production and reuse of manufactured sand and gravel from subway tunnel excavation. Background Technology

[0002] During the construction of underground projects such as subways and intercity railways, shield tunneling generates a large amount of excavated soil. Traditional methods of handling this soil mainly involve transporting it to spoil heaps or disposal sites. This not only involves long transportation distances, high energy consumption, and large carbon emissions, but also occupies a large amount of land resources and may cause secondary dust pollution. Currently available manufactured sand and gravel production equipment is mostly fixed-site type, requiring raw materials to be transported to the production site for further processing, which cannot meet the needs of on-site processing and reuse during shield tunneling construction. At the same time, in water-rich areas in the south, the soil moisture content is high, and existing technologies cannot effectively adjust the construction process according to the soil moisture content ratio. Furthermore, existing resource utilization systems lack real-time monitoring and data management of carbon emission reduction effects, making it difficult to provide direct evidence for carbon trading and green construction certification. Therefore, a carbon emission reduction system based on the on-site production and reuse of manufactured sand and gravel from subway shield tunneling excavated soil was designed. Summary of the Invention

[0003] To address the aforementioned shortcomings in the existing technology, this invention provides a carbon emission reduction system based on in-situ manufactured sand and gravel production and reuse of subway tunnel excavation soil, in order to solve the problems mentioned in the background technology.

[0004] To solve the above-mentioned technical problems, the present invention adopts the following technical solution: A carbon emission reduction system based on in-situ production and reuse of manufactured sand and gravel from subway tunnel boring machine excavation is characterized by the following steps: S1: Use the data acquisition module to collect soil layer data, soil moisture content, and equipment data during the subway construction process; S2: The collected data is processed, cleaned and pre-analyzed through the data transmission and preprocessing module. The data is then sorted according to the geological division table by geological section number. Data of the same soil layer is marked and all data is then transmitted to the data storage and analysis module. S3: In the data storage and analysis module, the energy consumption data and carbon emission data of the equipment in each in-situ processing system and the moisture content of the soil in the feeding system are calculated separately. Then, using the soil moisture content, energy consumption data and carbon emission data of the same soil layer in the past 15 days, a model is established to show the impact of soil moisture content on equipment carbon emissions. Correlation analysis is performed on each piece of equipment through soil moisture content to clarify the impact of soil moisture content on the energy consumption of each piece of equipment. The carbon emission value of each piece of equipment in the soil layer today is estimated through historical data. Then, the carbon emission of each piece of equipment today is calculated based on the soil moisture content today. If the carbon emission of a certain piece of equipment today does not exceed the predicted threshold, the data is stored according to the geological section number. If the carbon emission of a certain piece of equipment today exceeds the predicted threshold, the data in the analysis module is transferred to the carbon emission reduction strategy generation module. S4: After receiving the data, the carbon emission reduction strategy generation module determines whether the soil layer data information of today has changed compared with the soil layer data information of the past. If the soil layer information has changed, it will be adapted and adjusted according to the database established by the soil layer data information in the corresponding project. If the soil layer information has not changed, it will be optimized by prioritizing emission reduction potential, cost control and feasibility, and combined with construction constraints in source control, process optimization and equipment power consumption time adjustment, and finally output the strategy combination with the least carbon emissions. S5: The real-time monitoring and feedback module monitors the implementation of the strategy. It calculates the deviation value by comparing the actual carbon emissions and the predicted value under the same soil layer. When the deviation value exceeds the set threshold, it automatically triggers the model and strategy adjustment mechanism and feeds the monitoring data back to the data storage and analysis module, thereby readjusting the strategy combination. S6: Presents various data, analysis results, and carbon reduction strategies to users through a visualization module.

[0005] Preferably, in step S3, the unit carbon emission intensity of each device is calculated in the same soil geological model, and the formula is as follows: , For equipment power, The unit earthwork processing time Let Q be the carbon emission factor for electricity, and Q be the volume of earthwork processed per unit time. The correlation calculation formula is as follows: , where n is the historical sample size, ∑xy is the sum of the products of moisture content and carbon emission intensity of the equipment in all samples of the equipment, and ∑x is the moisture content of all samples of the equipment. The sum, ∑y represents the carbon emission intensity of all samples from this device. The sum, The product of the total moisture content of the equipment and the total carbon emission intensity is calculated. The numerator measures the degree of covariance between the moisture content of the soil and the carbon emissions of the equipment, while the first part of the denominator measures the dispersion of the moisture content itself, and the second part measures the dispersion of the carbon emission intensity itself. The larger the absolute value of the calculated value, the more significantly the carbon emissions of the equipment are affected by the moisture content. Then, based on today's soil moisture content, the carbon emissions of the equipment today are estimated using the following formula: ,in This represents the average carbon emissions of the device over historical data. These represent the standard deviations of the equipment's carbon emissions and the moisture content of the soil residue, respectively. This indicates the moisture content of today's soil residue. Based on this, the system compares today's carbon emissions from the equipment with the predicted value of 1.1 times to determine whether to pass the data to the carbon reduction strategy generation module.

[0006] Preferably, in step S4, the construction constraints include schedule constraints, cost constraints, and equipment constraints.

[0007] Preferably, the correlation This indicates that the carbon emissions of the equipment are strongly correlated with the moisture content of the soil residue. For the relevant purposes, The correlation is weak; the stronger the correlation, the higher the regulatory priority.

[0008] A carbon emission reduction system based on in-situ production and reuse of manufactured sand and gravel from subway tunnel boring machine excavation, characterized in that it includes: The data acquisition module is used to collect various types of data during the subway construction process; The data transmission and preprocessing module is used to organize, clean, and perform preliminary analysis on all data; The data storage and analysis module is used to store processed data according to the geological section number and to analyze the data using artificial intelligence algorithms. The carbon emission reduction strategy generation module establishes geological models for different geological sections based on the survey, which is used to map the transmitted geological section number to the geological model and generate carbon emission reduction strategies based on the model analysis data. The real-time monitoring and feedback module is used to monitor the implementation effect of carbon emission reduction strategies in real time and feed the monitoring data back to the data storage and analysis module so as to adjust and optimize the carbon emission reduction strategies. The visualization module is used to present various data, analysis results, and carbon reduction strategies to users in an intuitive visual interface, making it convenient for users to view and manage. Preferably, the data acquisition module is installed on the in-situ processing system, which includes: Feeding system: Used to receive the excavated soil discharged by the tunnel boring machine. It adopts a combination of adjustable speed conveyor and hopper to adapt to different soil moisture contents and excavation rhythms. Screening system: Equipped with a vibrating screen to classify the slag according to particle size and remove large pieces of debris and unusable waste; Conveying system: Composed of belt conveyors and screw conveyors, it enables continuous material transport between different process sections; Cleaning system: High-pressure spraying combined with cyclone separation to remove mud and harmful impurities from the slag; Sedimentation system: Set up sedimentation tanks and circulating water pumps to settle and purify cleaning wastewater, and reuse the purified water to achieve closed-loop water resource circulation; Filter press system: dewaters the sludge at the bottom of the sedimentation tank to form reusable sludge cake; Discharge system: The finished manufactured sand and gravel are directly transported to the on-site concrete mixing plant for immediate use.

[0009] Preferably, the feeding system, screening system, conveying system, cleaning system, sedimentation system, filter press system, and discharge system are all modularly designed and move via tracks.

[0010] Compared with the prior art, the present invention has the following advantages: 1. By setting up data transmission and preprocessing modules, data storage and analysis modules, carbon emission reduction strategy generation modules, real-time monitoring and feedback modules, and visualization display modules, comprehensive real-time data capture of the feeding system, screening system, conveying system, cleaning system, sedimentation system, filter press system, and discharge system is achieved. The data transmission and preprocessing module sorts the data according to the geological division table, marks the data information of the same soil layer, and then transmits all data to the data storage and analysis module. The data storage and analysis module analyzes the impact of soil moisture content on the carbon emissions of each piece of equipment in the feeding system, screening system, conveying system, cleaning system, sedimentation system, filter press system, and discharge system using a model, clarifying the impact of soil moisture content on the carbon emissions of each piece of equipment. The impact of equipment energy consumption is assessed by extrapolating the carbon emissions of each piece of equipment in the soil layer today based on historical data. Then, the carbon emissions of each piece of equipment today are calculated based on the soil moisture content today. If the carbon emissions of a certain piece of equipment exceed the predicted threshold today, the data in the analysis module is transmitted to the carbon emission reduction strategy generation module. After receiving the data, the carbon emission reduction strategy generation module judges the soil layer data information today based on the database, and then optimizes the strategy by prioritizing emission reduction potential, cost control, and feasibility, combined with construction constraints, source control, process optimization, and equipment power consumption time adjustment. Finally, it outputs the strategy combination with the lowest carbon emissions, thus achieving the output of the strategy combination with the lowest carbon emissions based on the soil moisture content ratio, and at the same time providing a direct basis for carbon trading and green construction certification. 2. An in-situ treatment system is set up, which includes a feeding system, a screening system, a conveying system, a washing system, a sedimentation system, a filter press system, and a discharge system. This system is modularly designed and moved via tracks, allowing for easy adjustment of the positions of each system according to the tunnel boring machine's (TBM) excavation speed. The screening module removes impurities from the excavated soil. The washing module uses a combination of high-pressure spraying and cyclone separation to remove mud, powder, and harmful impurities from the screened excavated soil. The sedimentation system settles and purifies the washing wastewater, allowing for water reuse and achieving a closed-loop water resource cycle. The filter press system dewaters the sedimentation tank bottom mud, forming reusable mud cakes. The washed sand and gravel are directly transported to the concrete mixing plant via the discharge system, and the processed material is reused in the tunnel shotcrete, achieving self-production and self-use. Attached Figure Description

[0011] Figure 1 This is a framework diagram of a carbon emission reduction system based on the in-situ production and reuse of manufactured sand and gravel from subway tunnel excavation, according to the present invention. Figure 2 The present invention provides a flowchart of the in-situ treatment system for a carbon emission reduction system based on the in-situ production and reuse of manufactured sand and gravel from subway tunnel excavation. Detailed Implementation

[0012] To enable those skilled in the art to better understand the present invention, the technical solution of the present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0013] The accompanying drawings are for illustrative purposes only and are schematic diagrams, not actual images. They should not be construed as limiting the scope of this patent. To better illustrate the embodiments of the present invention, some parts in the drawings may be omitted, enlarged, or reduced, and do not represent the actual dimensions of the product. It is understandable to those skilled in the art that some well-known structures and their descriptions may be omitted in the drawings.

[0014] In the accompanying drawings of the embodiments of the present invention, the same or similar reference numerals correspond to the same or similar components. In the description of the present invention, it should be understood that if terms such as "upper," "lower," "left," "right," "inner," and "outer" indicate the orientation or positional relationship based on the orientation or positional relationship shown in the drawings, they are only for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, the terms used to describe positional relationships in the drawings are only for illustrative purposes and should not be construed as limiting the present patent. For those skilled in the art, the specific meaning of the above terms can be understood according to the specific circumstances.

[0015] In the description of this invention, unless otherwise explicitly specified and limited, the term "connection" or similar designation indicating a connection between components should be interpreted broadly. For example, it can refer to a fixed connection, a detachable connection, or an integral part; it can be a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium; it can refer to the internal communication between two components or the interaction between two components. Those skilled in the art can understand the specific meaning of the above terms in this invention based on the specific circumstances.

[0016] Example 1: like Figure 1-2 The carbon emission reduction system shown includes the following steps: In-situ production and reuse of manufactured sand and gravel from subway tunnel boring machine excavation. S1: Use the data acquisition module to collect soil layer data, soil moisture content, and equipment data during the subway construction process; S2: The collected data is processed, cleaned and pre-analyzed through the data transmission and preprocessing module. The data is then sorted according to the geological division table by geological section number. Data of the same soil layer is marked and all data is then transmitted to the data storage and analysis module. S3: In the data storage and analysis module, the energy consumption data and carbon emission data of the equipment in each in-situ processing system and the moisture content of the soil in the feeding system are calculated separately. Then, using the soil moisture content, energy consumption data and carbon emission data of the same soil layer in the past 15 days, a model is established to show the impact of soil moisture content on equipment carbon emissions. Correlation analysis is performed on each piece of equipment through soil moisture content to clarify the impact of soil moisture content on the energy consumption of each piece of equipment. The carbon emission value of each piece of equipment in the soil layer today is estimated through historical data. Then, the carbon emission of each piece of equipment today is calculated based on the soil moisture content today. If the carbon emission of a certain piece of equipment today does not exceed the predicted threshold, the data is stored according to the geological section number. If the carbon emission of a certain piece of equipment today exceeds the predicted threshold, the data in the analysis module is transferred to the carbon emission reduction strategy generation module. S4: After receiving the data, the carbon emission reduction strategy generation module determines whether the soil layer data information of today has changed compared with the soil layer data information of the past. If the soil layer information has changed, it will be adapted and adjusted according to the database established by the soil layer data information in the corresponding project. If the soil layer information has not changed, it will be optimized by prioritizing emission reduction potential, cost control and feasibility, and combined with construction constraints in source control, process optimization and equipment power consumption time adjustment, and finally output the strategy combination with the least carbon emissions. S5: The real-time monitoring and feedback module monitors the implementation of the strategy. It calculates the deviation value by comparing the actual carbon emissions and the predicted value under the same soil layer. When the deviation value exceeds the set threshold, it automatically triggers the model and strategy adjustment mechanism and feeds the monitoring data back to the data storage and analysis module, thereby readjusting the strategy combination. S6: Presents various data, analysis results, and carbon reduction strategies to users through a visualization module.

[0017] In step S3, the unit carbon emission intensity of each device is calculated in the same soil geological model, and the formula is as follows: , For equipment power, The unit earthwork processing time Let Q be the carbon emission factor for electricity, and Q be the volume of earthwork processed per unit time. The correlation calculation formula is as follows: , where n is the historical sample size, ∑xy is the sum of the products of moisture content and carbon emission intensity of the equipment in all samples of the equipment, and ∑x is the moisture content of all samples of the equipment. The sum, ∑y represents the carbon emission intensity of all samples from this device. The sum, The product of the total moisture content of the equipment and the total carbon emission intensity is calculated. The numerator measures the degree of covariance between the moisture content of the soil and the carbon emissions of the equipment, while the first part of the denominator measures the dispersion of the moisture content itself, and the second part measures the dispersion of the carbon emission intensity itself. The larger the absolute value of the calculated value, the more significantly the carbon emissions of the equipment are affected by the moisture content. Then, based on today's soil moisture content, the carbon emissions of the equipment today are estimated using the following formula: ,in This represents the average carbon emissions of the device over historical data. These represent the standard deviations of the equipment's carbon emissions and the moisture content of the soil residue, respectively. This indicates the moisture content of today's soil residue. Based on this, the system compares today's carbon emissions from the equipment with the predicted value of 1.1 times to determine whether to pass the data to the carbon reduction strategy generation module.

[0018] In step S4, the construction constraints include schedule constraints, cost constraints, and equipment constraints.

[0019] The correlation This indicates that the carbon emissions of the equipment are strongly correlated with the moisture content of the soil residue. For the relevant purposes, The correlation is weak; the stronger the correlation, the higher the regulatory priority.

[0020] A carbon emission reduction system based on in-situ production and reuse of manufactured sand and gravel from subway tunnel boring machine excavation, characterized in that it includes: The data acquisition module is used to collect various types of data during the subway construction process; The data transmission and preprocessing module is used to organize, clean, and perform preliminary analysis on all data; The data storage and analysis module is used to store processed data according to the geological section number and to analyze the data using artificial intelligence algorithms. The carbon emission reduction strategy generation module establishes geological models for different geological sections based on the survey, which is used to map the transmitted geological section number to the geological model and generate carbon emission reduction strategies based on the model analysis data. The real-time monitoring and feedback module is used to monitor the implementation effect of carbon emission reduction strategies in real time and feed the monitoring data back to the data storage and analysis module so as to adjust and optimize the carbon emission reduction strategies. The visualization module is used to present various data, analysis results, and carbon reduction strategies to users in an intuitive visual interface, making it convenient for users to view and manage. The data acquisition module is installed on the in-situ processing system, which includes: Feeding system: Used to receive the excavated soil discharged by the tunnel boring machine. It adopts a combination of adjustable speed conveyor and hopper to adapt to different soil moisture contents and excavation rhythms. Screening system: Equipped with a vibrating screen to classify the slag according to particle size and remove large pieces of debris and unusable waste; Conveying system: Composed of belt conveyors and screw conveyors, it enables continuous material transport between different process sections; Cleaning system: High-pressure spraying combined with cyclone separation to remove mud and harmful impurities from the slag; Sedimentation system: Set up sedimentation tanks and circulating water pumps to settle and purify cleaning wastewater, and reuse the purified water to achieve closed-loop water resource circulation; Filter press system: dewaters the sludge at the bottom of the sedimentation tank to form reusable sludge cake; Discharge system: The finished manufactured sand and gravel are directly transported to the on-site concrete mixing plant for immediate use.

[0021] The feeding system, screening system, conveying system, cleaning system, sedimentation system, filter press system, and discharge system are all modularly designed and move via tracks.

[0022] Before construction, the concrete strength requirements of the construction area should be clearly defined, and the soil characteristics of the construction area should be investigated to determine the requirements for the reuse of manufactured sand and gravel, and to clarify the sand and gravel particle size standards for the tunnel initial support and concrete mixing.

[0023] Determine the tunnel boring machine's construction parameters, daily excavation volume and advance speed, take on-site samples to determine soil moisture content, and the proportions of sand, gravel, and clay. Determine the location of the concrete mixing plant, the average daily demand for sand and gravel, and the transportation route.

[0024] Site planning and modular layout design: A compact area is designated around the tunnel boring machine (TBM) construction site, and the in-situ processing system is laid out using a track-mounted mobile layout. The distance between the feeding system and the TBM's exit point is controlled at 5-6 meters to reduce the energy required for transporting excavated soil. Then, a screening system, a washing / sedimentation system, a filter press system, a discharge system, and a concrete mixing plant are installed in sequence. The distance between the screening system and the concrete mixing plant is controlled at 60-70 meters to reduce energy loss during the transport of finished aggregates. Furthermore, each module can move along the track to ensure that the transport route is not too long, thus preventing an increase in carbon emissions.

[0025] The tunnel boring machine (TBM) is equipped with a progress schedule, allowing for project progress tracking by date. It can also be matched with a geological classification table to pinpoint the current geological section. The feeding system consists of an adjustable-speed conveyor with a variable-frequency motor. The conveyor is equipped with a weighing sensor, a moisture content meter, and a hopper. The hopper capacity is designed to be 1.2 times the TBM's daily excavation output, and a level sensor inside the hopper ensures the hopper discharge matches the TBM's output, preventing overflow and idle running. The screening system includes multi-stage vibrating screens with apertures determined before construction and connected to vibrating motors. The conveying system includes belt conveyors with an inclination angle ≤15° between the screening and washing systems, and between the washing and discharge systems, to prevent material slippage. Screw conveyors are added at key points for materials with higher moisture content. The system features high-efficiency material conveying; a high-pressure spray system with pressure sensors, a hydrocyclone separator with flow sensors, and a sedimentation system with multiple 4-stage sedimentation tanks designed for a total volume 1.5 times the daily water consumption. It includes circulating water pumps and water quality sensors to monitor turbidity and ensure the wastewater's turbidity after sedimentation is reusable. The filter press and discharge system uses a plate and frame filter press to treat the sedimentation tank bottom, connects to a sludge pump, and is equipped with a production sensor and moisture content meter to determine the sludge cake output and ensure its moisture content meets backfill / brick-making requirements. The discharge system uses a belt conveyor to the concrete mixing plant's silo, with weighing sensors installed at the bottom of the silo. Power sensors are also installed on all electrical equipment to calculate energy consumption based on operating time. By installing GPS and load sensors on transport vehicles, carbon emissions can be calculated based on the transport distance. , The carbon emission factor for diesel fuel can be calculated by measuring the carbon emissions of transport vehicles, which can then be used to determine the cost of purchasing fuel. Weather stations, carbon emission monitoring instruments, and industrial servers are deployed in the work area.

[0026] Once the system is started, the weighing sensors and moisture content detectors in the conveyor detect the soil volume and moisture content of the tunnel boring machine. The pressure sensor in the cleaning system detects the cleaning water pressure. The flow sensor in the hydrocyclone separator detects the total water consumption of the cleaning system. The water quality sensor in the sedimentation system detects the turbidity of the water in the sedimentation tank. The output sensor and moisture content detector in the filter press system detect the output and moisture content of the mud cake. The weighing sensor in the discharge system detects the output of finished sand and gravel. The GPS on the vehicle collects the vehicle's travel route. The load sensor collects the output of sand and gravel transported by the vehicle. The weather station and carbon emission monitor in the work area collect the weather station temperature and the total carbon emissions, respectively, and transmit all the collected data to the preprocessing module. The preprocessing module uses the mean. The system identifies and removes outliers to ensure data accuracy. Redundant data is removed using timestamps. Short-term missing data is often filled using linear interpolation, while long-term missing data triggers an alarm and marks the relevant sensor for worker inspection. Finally, the data is standardized: heterogeneous data is unified into industry-standard units, with energy consumption data... Water consumption is Carbon emissions are The data of different magnitudes are normalized and mapped to the 0~1 interval to eliminate the difference in magnitude. The geological segment where the process is located is labeled.

[0027] Data storage and analysis module: During the initial operation, the parameter library was debugged using a reference table of similar projects to ensure the analysis module could be used normally in new projects. Database technology was used to store all data collected daily, and data exceeding three months was packaged and compressed into an industrial server. Then, using soil moisture content, energy consumption, and carbon emission data from similar soil layers over the past 15 days, a model was established to assess the impact of soil moisture content on equipment carbon emissions under different soil layers. The unit carbon emission intensity of each piece of equipment was calculated using the same soil layer geological model; the formula is as follows: , For equipment power, The unit earthwork processing time Let Q be the carbon emission factor for electricity, and Q be the volume of earthwork processed per unit time. The correlation calculation formula is as follows: , where n is the historical sample size, ∑xy is the sum of the products of the moisture content of all samples of the equipment and the carbon emission intensity of the equipment, and ∑x is the moisture content of all samples of the equipment. The sum, ∑y represents the carbon emission intensity of all samples from this device. The sum, The product of the total moisture content of the equipment and the total carbon emission intensity is calculated. The numerator measures the degree of covariance between the moisture content of the soil and the carbon emissions of the equipment, while the first part of the denominator measures the dispersion of the moisture content itself, and the second part measures the dispersion of the carbon emission intensity itself. The larger the absolute value of the calculated value, the more significantly the carbon emissions of the equipment are affected by the moisture content. Then, based on today's soil moisture content, the carbon emissions of the equipment today are estimated using the following formula: ,in This represents the average carbon emissions of the device over historical data. These represent the standard deviations of the equipment's carbon emissions and the moisture content of the soil residue, respectively. This indicates the moisture content of today's soil residue. Based on this, the carbon emissions of the equipment today are compared to 1.1 times the predicted value to determine whether to transmit the data to the carbon reduction strategy generation module. If transmission is required, the equipment is marked according to the correlation. This indicates that the carbon emissions of the equipment are strongly correlated with the moisture content of the soil residue. For the relevant purposes, The correlation is weak; the stronger the correlation, the higher the control priority, thus identifying the equipment that should be controlled first in process optimization. Carbon emission reduction strategy generation module: Based on past construction experience, a strategy database is established. After receiving data, the module determines whether the soil layer data for today's soil layer has changed compared to previous data. If the soil layer information has changed, the correlation is recalculated based on the changed information to identify new strong, medium, and weak correlations. A new strategy is generated based on the new correlations and data from the database built using soil layer data from suitable projects. If the soil layer information has not changed, the emission reduction potential of the equipment is determined through correlation; the stronger the correlation, the greater the emission reduction potential. Then, weights are allocated based on cost control and feasibility. The dynamic adjustment of emission reduction potential, cost control, and feasibility is carried out at different project stages. For example, when rushing to meet deadlines, the feasibility weight can be higher, reducing the emission reduction potential and accelerating the implementation of the strategy. This accelerates the construction period; during the stable operation period, the weight of emission reduction potential is increased and costs are reduced. By controlling the progress constraints of the minimum daily processing of construction waste, the cost constraints of the annual net cost budget, and the equipment constraints that the adjustment of a single piece of equipment cannot exceed the safe range of the equipment, strategies are combined from the source, such as adding drying devices, process optimization, such as extending the cleaning time when the moisture content is greater than 35% and reducing the cleaning pressure and extending the cleaning time when the moisture content is less than 35%, and adjusting the power consumption time of equipment, such as extending the operating time of high-energy-consuming equipment during off-peak hours and reducing the peak hours. These strategies are adjusted according to the project constraints. If the daily processing volume of construction waste cannot be reduced when rushing the construction period, process optimization is restricted to avoid the impact of special periods on the project. By combining multiple strategies and evaluating each combination to determine the emission reduction potential, cost control and feasibility score of the combination, the final strategy combination is output.

[0028] Real-time monitoring and feedback module: The real-time monitoring and feedback module performs data analysis on the carbon emission reduction strategy generation module. It calculates the deviation value by comparing the actual carbon emissions with the predicted value. When the deviation value exceeds the set threshold, it automatically triggers the model and strategy adjustment mechanism and feeds the monitoring data back to the data storage and analysis module, thereby readjusting the strategy combination. At the same time, the data storage and analysis module stores the data and strengthens its algorithm. Visualization module: Employing diverse visualization formats to present various data, analysis results, and carbon reduction strategies to users: using bar charts to display changes in carbon emissions during the construction period, intuitively reflecting the effectiveness of emission reduction; using line charts to present the trend of equipment energy consumption optimization, comparing the energy consumption differences before and after the implementation of strategies; using maps to mark sand and gravel recycling routes and transportation optimization schemes, demonstrating emission reduction measures in the transportation process; and displaying the carbon emission reduction calculation results in real time.

[0029] The sand, gravel, and clay processed by the washing system are transported from the discharge system to the concrete mixing plant. After mixing, they are used for tunnel support, achieving self-production and self-use. The wastewater from the washing process enters the sedimentation system, which settles and purifies the wastewater. When the turbidity of the wastewater drops to a specified value, the sediment is compressed into mud cakes through a filter press system. The mud cakes are then used for foundation backfilling.

[0030] Meanwhile, the system's equipment health monitoring function identifies potential faults by monitoring fluctuations in the power sensor and data from the vibration sensor in the screening system, and promptly replaces the filter cloth of the plate and frame filter press to prevent material jamming.

[0031] Example 2: On the 120th day of tunnel boring machine construction in a certain subway section, we are currently in the K2 sandy soil section. The geological section label has been marked by the preliminary survey. The daily plan is to process 300m³ of excavated soil. The current construction stage is the stable period.

[0032] According to the initial data collected by each sensor: Conveyor weighing sensor: Current hourly soil output is 38m³, cumulative daily soil output is 304m³, progress is normal; Moisture content meter: Initial moisture content of the slag soil is 42%; Cleaning system pressure sensor: Current pressure 3.8MPa, close to the equipment's safe upper limit of 4MPa; Flow sensor for hydrocyclone separator: Total water consumption 12 m³ / h; Filter press system: cake production 15 m³ / h, cake moisture content 38%; Carbon emission monitor: Current hourly carbon emission is 280 kg CO2, which translates to a carbon emission intensity of 11.2 kg CO2 / m³.

[0033] The construction constraints during the stable period are a daily processing capacity of ≥300m³, an annual cost of <500,000 RMB, and equipment parameters within a safe range. Based on the historical moisture content range of 20%–50% for the sandy soil section, the preprocessing module standardized the data units, mapping moisture content (%), water consumption (m³ / h), and carbon emissions (kgCO2 / m³) to... If the threshold is exceeded, extract data from the sandy soil section for the past 15 days and calculate the correlation coefficient between carbon emissions and moisture content for each piece of equipment. ,according to The calculated carbon emission intensity of the cleaning system is 5.6, conveying is 3.9, filtration is 3.5, and screening is 1.2, totaling 14.2 kg CO2 / m³. The threshold determined based on the predicted values ​​is 12.5 kg CO2 / m³. The carbon emission reduction strategy generation module detects no change in the soil layer and generates strategies. Strategies are selected from a database built on past experience, prioritizing those affecting daily processing capacity. Then, the cleaning system with strong correlation is used to select a solution, resulting in three combinations: 1. Extend cleaning time by 20% and maintain pressure at 3.5 MPa; increase the proportion of valley operation in the cleaning / filtration system to 70%; 2. Use hot air drying to reduce moisture content to 35%; match conveying speed to feed rate; 3. Combine options 1 and 2, with weighted allocation: emission reduction potential 50%, cost 20%, feasibility 30%. The final option 1: emission reduction potential reduced to 10.5, annual net cost -80,000 yuan, comprehensive score 0.5 × (3.7 / 4.5 × 10) + 0.2 × 10 + 0.3 × 9 = 8.9; Option 2: Emission reduction potential reduced to 8.8, annual net cost of 75,000 yuan, overall score of 8.5; Option 3: Emission reduction potential reduced to 7.0, annual net cost of 70,000 yuan, overall score of 8.7. In summary, Option 1 is selected during the stable period. The cleaning system is then adjusted as follows: the cleaning time is extended by 20%, the pressure is reduced to 3.5 MPa, and the power supply is adjusted so that the cleaning system and the filter press system operate during the off-peak period from 22:00 to 6:00, and only the basic load is maintained during the peak period from 8:00 to 22:00.

[0034] The above are merely embodiments of the present invention. The circuits, electronic components, and modules involved are all prior art, fully achievable by those skilled in the art, and require no further explanation. The scope of protection in this application does not involve improvements to the software and methods. Commonly known structures and characteristics in the solutions are not described in detail here. Those skilled in the art are aware of all common technical knowledge in the field prior to the application date or priority date, are aware of all prior art in that field, and have the ability to apply conventional experimental methods prior to that date. Those skilled in the art can, under the guidance of this application, improve and implement this solution in combination with their own capabilities. Some typical known structures or methods should not be obstacles for those skilled in the art to implement this application. It should be noted that those skilled in the art can make several modifications and improvements without departing from the structure of the present invention. These should also be considered within the scope of protection of the present invention, and will not affect the effectiveness of the implementation of the present invention or the practicality of the patent.

Claims

1. A carbon emission reduction system based on in-situ production and reuse of manufactured sand and gravel from subway tunnel boring machine excavation, characterized in that, Includes the following steps: S1: Use the data acquisition module to collect soil layer data, soil moisture content, and equipment data during the subway construction process; S2: The collected data is processed, cleaned and pre-analyzed through the data transmission and preprocessing module. The data is then sorted according to the geological division table by geological section number. Data of the same soil layer is marked and all data is then transmitted to the data storage and analysis module. S3: In the data storage and analysis module, the energy consumption data and carbon emission data of the equipment in each in-situ processing system and the moisture content of the soil in the feeding system are calculated separately. Then, using the soil moisture content, energy consumption data and carbon emission data of the same soil layer in the past 15 days, a model is established to show the impact of soil moisture content on equipment carbon emissions. Correlation analysis is performed on each piece of equipment through soil moisture content to clarify the impact of soil moisture content on the energy consumption of each piece of equipment. The carbon emission value of each piece of equipment in the soil layer today is estimated through historical data. Then, the carbon emission of each piece of equipment today is calculated based on the soil moisture content today. If the carbon emission of a certain piece of equipment today does not exceed the predicted threshold, the data is stored according to the geological section number. If the carbon emission of a certain piece of equipment today exceeds the predicted threshold, the data in the analysis module is transferred to the carbon emission reduction strategy generation module. S4: After receiving the data, the carbon emission reduction strategy generation module determines whether the soil layer data information of today has changed compared with the soil layer data information of the past. If the soil layer information has changed, it will be adapted and adjusted according to the database established by the soil layer data information in the corresponding project. If the soil layer information has not changed, it will be optimized by prioritizing emission reduction potential, cost control and feasibility, and combined with construction constraints in source control, process optimization and equipment power consumption time adjustment, and finally output the strategy combination with the least carbon emissions. S5: The real-time monitoring and feedback module monitors the implementation of the strategy. It calculates the deviation value by comparing the actual carbon emissions and the predicted value under the same soil layer. When the deviation value exceeds the set threshold, it automatically triggers the model and strategy adjustment mechanism and feeds the monitoring data back to the data storage and analysis module, thereby readjusting the strategy combination. S6: Presents various data, analysis results, and carbon reduction strategies to users through a visualization module.

2. The carbon emission reduction system for in-situ manufactured sand and gravel production and reuse based on subway tunnel excavation waste as described in claim 1, characterized in that: In step S3, the unit carbon emission intensity of each device is calculated in the same soil geological model, and the formula is as follows: , For equipment power, The unit earthwork processing time Let Q be the carbon emission factor for electricity, and Q be the volume of earthwork processed per unit time. The correlation calculation formula is as follows: , where n is the historical sample size, ∑xy is the sum of the products of the moisture content of all samples of the equipment and the carbon emission intensity of the equipment, and ∑x is the moisture content of all samples of the equipment. The sum, ∑y represents the carbon emission intensity of all samples from this device. The sum, The product of the total moisture content of the equipment and the total carbon emission intensity is calculated. The numerator measures the degree of covariance between the moisture content of the soil and the carbon emissions of the equipment, while the first part of the denominator measures the dispersion of the moisture content itself, and the second part measures the dispersion of the carbon emission intensity itself. The larger the absolute value of the calculated value, the more significantly the carbon emissions of the equipment are affected by the moisture content. Then, based on today's soil moisture content, the carbon emissions of the equipment today are estimated using the following formula: ,in This represents the average carbon emissions of the device over historical data. These represent the standard deviations of the equipment's carbon emissions and the moisture content of the soil residue, respectively. This indicates the moisture content of today's soil residue. Based on this, the system compares today's carbon emissions from the equipment with the predicted value of 1.1 times to determine whether to pass the data to the carbon reduction strategy generation module.

3. The carbon emission reduction system for in-situ manufactured sand and gravel production and reuse based on subway tunnel excavation waste as described in claim 1, characterized in that: In step S4, the construction constraints include schedule constraints, cost constraints, and equipment constraints.

4. A carbon emission reduction system for in-situ manufactured sand and gravel production and reuse based on subway tunnel excavation waste as described in claim 2, characterized in that: The correlation This indicates that the carbon emissions of the equipment are strongly correlated with the moisture content of the soil residue. For the relevant purposes, The correlation is weak; the stronger the correlation, the higher the regulatory priority.

5. A carbon emission reduction system based on in-situ production and reuse of manufactured sand and gravel from subway tunnel boring machine excavation, characterized in that: include: The data acquisition module is used to collect various types of data during the subway construction process; The data transmission and preprocessing module is used to organize, clean, and perform preliminary analysis on all data; The data storage and analysis module is used to store processed data according to the geological section number and to analyze the data using artificial intelligence algorithms. The carbon emission reduction strategy generation module establishes geological models for different geological sections based on the survey, which is used to map the transmitted geological section number to the geological model and generate carbon emission reduction strategies based on the model analysis data. The real-time monitoring and feedback module is used to monitor the implementation effect of carbon emission reduction strategies in real time and feed the monitoring data back to the data storage and analysis module so as to adjust and optimize the carbon emission reduction strategies. The visualization module is used to present various data, analysis results, and carbon reduction strategies to users in an intuitive visual interface, making it convenient for users to view and manage.

6. A carbon emission reduction system for in-situ manufactured sand and gravel production and reuse based on subway tunnel excavation waste as described in claim 5, characterized in that: The data acquisition module is installed on the in-situ processing system, which includes: Feeding system: Used to receive the excavated soil discharged by the tunnel boring machine. It adopts a combination of adjustable speed conveyor and hopper to adapt to different moisture contents of the excavated soil and the excavation rhythm. Screening system: Equipped with a vibrating screen to classify the slag according to particle size and remove large pieces of debris and unusable waste; Conveying system: Composed of belt conveyors and screw conveyors to realize continuous material transportation between various process sections; Cleaning system: High-pressure spraying combined with cyclone separation to remove mud and harmful impurities from the slag; Sedimentation system: Set up sedimentation tanks and circulating water pumps to settle and purify cleaning wastewater, and reuse the purified water to achieve closed-loop water resource circulation; Filter press system: dewaters the sludge at the bottom of the sedimentation tank to form reusable sludge cake; Discharge system: The finished manufactured sand and gravel are directly transported to the on-site concrete mixing plant for immediate use.

7. A carbon emission reduction system for in-situ manufactured sand and gravel production and reuse based on subway tunnel excavation waste as described in claim 6, characterized in that: The feeding system, screening system, conveying system, cleaning system, sedimentation system, filter press system, and discharge system are all modularly designed and move via tracks.

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