Digital twinning management system and method for railway construction

Abstract

The invention relates to the technical field of railway construction, and particularly discloses a digital twinborn management system and method for railway construction, and the system comprises a model building unit which is used for building a railway construction digital twinborn model based on railway construction project information, according to an analogue simulation result of the digital twinborn model, determining a carbon emission prediction value of each stage of railway construction; the stage clustering unit is used for clustering each construction stage according to the carbon emission predicted value of each stage of railway construction; the emission calculation unit is used for determining a carbon emission allowable value according to the historical carbon emission of each construction stage; and the emission early warning unit is used for determining a carbon emission deviation value according to the real-time carbon emission of the current construction stage and carrying out real-time carbon emission early warning according to the carbon emission deviation value. According to the invention, real-time monitoring and early warning are carried out on the carbon emission in each stage of railway construction based on the digital twinborn model, and the green and low-carbon management requirements in the railway construction process are met.

Description

Technical Field

[0001] The present application relates to the technical field of railway construction, and more specifically, to a digital twin management system and method for railway construction. Background Art

[0002] According to statistics, carbon emissions from the construction industry account for about 40% of the total carbon emissions of the whole society, and carbon emissions during the construction phase account for about 12% of the total carbon emissions during the entire life cycle of the building. At present, most of the research on railway carbon emissions is about its carbon emissions and energy consumption during the entire life cycle, as well as the electricity consumption during the operation and maintenance phase. However, most of them study the carbon emissions of high-speed railways from the perspective of the entire life cycle, and there are fewer studies on carbon emissions during the construction period of high-speed railways. However, carbon emissions during the construction period account for a large proportion, and its carbon reduction potential should not be ignored. Compared with the operation period, the construction period is characterized by a large consumption of energy and resources. Therefore, accurate measurement of carbon emissions during this period and management of carbon emissions during the entire life cycle of railway construction are key links in achieving energy conservation and emission reduction.

[0003] Digital twin technology integrates cutting-edge technology applications such as 5G, big data, cloud computing, AI, and converged communications, organically combining information technology, equipment, and management needs, and uses digital twin technology to map various types of information on the physical construction site to the virtual space in real time. The system integrates a variety of data collection tools such as sensors, Internet of Things (IoT) devices, and drones to monitor important parameters such as construction progress, equipment status, and environmental conditions in real time. Through this system, managers can fully understand the situation on the construction site in a virtual environment and promptly discover and solve potential problems. Therefore, how to apply digital twin technology to the entire life cycle of railway construction and realize carbon emission management throughout the life cycle of railway construction has become a technical problem that needs to be solved in this field. Summary of the invention

[0004] The present invention provides a digital twin management system and method for railway construction, which is used to solve the problem of applying digital twin technology to the whole life cycle process of railway construction in the prior art and realizing carbon emission management of the whole life cycle process of railway construction, including:

[0005] A model building unit, used to obtain railway construction project information, build a railway construction digital twin model based on the railway construction project information, determine a carbon emission factor prediction value according to a simulation result of the digital twin model, and determine a carbon emission prediction value at each stage of railway construction according to the carbon emission factor prediction value;

[0006] The stage clustering unit is used to cluster each construction stage according to the predicted carbon emission value of each stage of railway construction, and divide each construction stage into corresponding cluster partitions according to the clustering results;

[0007] An emission calculation unit, used to obtain the historical carbon emissions of each construction stage and determine the carbon emission allowable value based on the historical carbon emissions of each construction stage;

[0008] The emission warning unit is used to obtain the real-time carbon emissions of the current construction stage, determine the carbon emission deviation value according to the real-time carbon emissions of the current construction stage, and make a real-time carbon emission warning according to the carbon emission deviation value.

[0009] Furthermore, the model building unit determines the predicted value of carbon emissions at each stage of railway construction according to the predicted value of carbon emission factor, including:

[0010] Obtain the historical carbon emission factor change data and the corresponding carbon emissions during the construction phase, and establish a carbon emission sample set based on the historical carbon emission factor change data and the corresponding carbon emissions during the construction phase;

[0011] An initial carbon emission prediction model is established according to the carbon emission sample set and the initial carbon emission prediction model is trained to obtain a final carbon emission prediction model;

[0012] The predicted value of the carbon emission factor in the construction phase is obtained, and the predicted value of the carbon emission factor in the construction phase is input into the final carbon emission prediction model to obtain the predicted value of carbon emissions.

[0013] Furthermore, the model building unit builds a railway construction digital twin model based on the railway construction project information, and determines a predicted value of a carbon emission factor according to a simulation result of the digital twin model, including:

[0014] Acquire railway construction project information, and divide the railway construction project information into multiple construction stages according to a preset construction period;

[0015] Obtaining construction site data at each construction stage, determining the construction cost of each railway station based on the construction site data, and determining the weight value of each railway station based on the construction cost;

[0016] Obtain the preset central site, build a construction site topology network based on the minimum tree generation algorithm and the weight value of each railway site, and establish a railway construction digital twin model based on the topological association of the site topology network and the construction site data;

[0017] Simulate each construction phase based on the railway construction digital twin model, and determine the predicted value of the carbon emission factor in the construction phase based on the simulation results;

[0018] A carbon emission prediction model is established, and based on the carbon emission prediction model, the predicted value of carbon emissions during the construction phase is determined according to the predicted value of the carbon emission factor.

[0019] Furthermore, the stage clustering unit clusters each construction stage according to the predicted carbon emission value of each railway construction stage, and divides each construction stage into corresponding cluster partitions according to the clustering result, including:

[0020] A carbon emission data set is established based on the average carbon emission prediction values ​​of each construction stage, and k initial clustering centers of the carbon emission data set are randomly selected;

[0021] Calculate the Euclidean distance from the average carbon emission prediction value in the carbon emission data set to the initial cluster center, and divide each construction stage into corresponding cluster partitions according to the Euclidean distance from the average carbon emission prediction value in the carbon emission data set to the initial cluster center;

[0022] Calculate the average of the average carbon emission prediction values ​​in each cluster partition, and recalculate the cluster center according to the average of the average carbon emission prediction values ​​in each cluster partition;

[0023] The above steps are repeated until the cluster center no longer changes or the number of iterations reaches the preset maximum number of iterations, and each construction stage is divided into the corresponding final cluster partition according to the clustering results.

[0024] Furthermore, the emission calculation unit determines the carbon emission allowable value according to the historical carbon emission of each construction stage in combination with the corresponding cluster partition, including:

[0025] Obtain the cluster center value of the cluster partition to which the construction stage belongs, and determine the carbon emission exceeding standard threshold value according to the cluster center value of the cluster partition to which the construction stage belongs;

[0026] Obtain the historical carbon emission change data of each construction stage, and draw the historical carbon emission change curve based on the historical carbon emission change data;

[0027] Screen out the historical carbon emissions that exceed the carbon emission exceeding standard threshold in the historical carbon emission change curve, and determine the exceeding standard frequency of the historical carbon emissions according to the historical carbon emissions that exceed the carbon emission exceeding standard threshold;

[0028] The allowable value of carbon emissions is determined based on the frequency of historical carbon emissions exceeding the standard.

[0029] Furthermore, the step of determining the carbon emission exceeding standard threshold according to the cluster center value of the cluster partition to which the construction stage belongs includes:

[0030] Obtain the sum of the cluster center values ​​of all construction stages, calculate the ratio of the cluster center value of each construction stage to the sum of the cluster center values ​​of all construction stages, and obtain the carbon emission ratio coefficient of each construction stage;

[0031] Obtain the preset full-cycle carbon emission exceeding standard threshold, multiply the carbon emission proportion coefficient of each construction stage by the preset full-cycle carbon emission exceeding standard threshold, and obtain the carbon emission exceeding standard threshold of each construction stage.

[0032] Furthermore, the determination of the permissible value of carbon emissions according to the frequency of exceeding the standard of historical carbon emissions includes:

[0033] The allowable value of carbon emissions is calculated based on the frequency of exceeding the standard in historical carbon emissions according to the allowable value calculation formula. The allowable value calculation formula is specifically:

[0034]

[0035] Among them, P is the allowable value of carbon emissions, P α is the preset initial carbon emission allowable value, C α is the preset frequency standard value of exceeding the standard, C is the frequency of exceeding the standard of historical carbon emissions, and R is the preset range coefficient.

[0036] Furthermore, the emission warning unit determines the carbon emission deviation value according to the real-time carbon emission in the current construction phase, including:

[0037] Draw a real-time carbon emission change curve according to the real-time carbon emission change in the current construction phase, and divide the real-time carbon emission change curve into several sub-change curves according to the preset sliding time window;

[0038] Count the average carbon emissions of each sub-change curve, and draw an average change curve based on the average carbon emissions of each sub-change curve;

[0039] Calculate the absolute values ​​of slopes of adjacent average values ​​in the average value change curve, and determine the average value of all absolute values ​​of slopes according to the absolute values ​​of slopes of adjacent average values ​​in the average value change curve;

[0040] The average of the absolute values ​​of all slopes is normalized to obtain the carbon emission fluctuation coefficient;

[0041] Calculate the difference between the real-time carbon emissions in the current construction phase and the allowable carbon emissions value, multiply the carbon emission fluctuation coefficient by the corresponding difference between the real-time carbon emissions and the allowable carbon emissions value, and obtain the carbon emission deviation value.

[0042] Furthermore, the emission warning unit performs real-time carbon emission warning according to the carbon emission deviation value, including:

[0043] Establish a preset carbon emission information database, and obtain the carbon emission grade parameters corresponding to each carbon emission deviation range in the carbon emission information database;

[0044] Match the carbon emission deviation value with each carbon emission deviation range in the carbon emission information database, and determine the carbon emission grade parameter corresponding to the carbon emission deviation value according to the matching result;

[0045] The carbon emission level parameter corresponding to the carbon emission deviation value is compared with the preset carbon emission allowable parameter. If the carbon emission level parameter corresponding to the carbon emission deviation value is greater than the preset carbon emission allowable parameter, a carbon emission warning is issued.

[0046] In order to achieve the above object, the present invention also provides a digital twin management method for railway construction, comprising:

[0047] Obtain railway construction project information, establish a railway construction digital twin model based on the railway construction project information, determine the carbon emission factor prediction value according to the simulation results of the digital twin model, and determine the carbon emission prediction value of each stage of railway construction according to the carbon emission factor prediction value;

[0048] Cluster each construction stage according to the predicted carbon emissions at each stage of railway construction, and divide each construction stage into corresponding cluster partitions according to the clustering results;

[0049] Obtain the historical carbon emissions of each construction stage and determine the allowable carbon emissions value based on the historical carbon emissions of each construction stage;

[0050] Obtain the real-time carbon emissions of the current construction phase, determine the carbon emissions deviation value based on the real-time carbon emissions of the current construction phase, and issue a real-time carbon emissions warning based on the carbon emissions deviation value.

[0051] The beneficial effects of the present invention are:

[0052] By applying the above technical scheme, the present invention simulates each construction stage of railway construction by establishing a digital twin model, and predicts the carbon emissions of each construction stage based on the simulation results of the digital twin model, thereby effectively improving the accuracy of carbon emissions prediction during railway construction. At the same time, by zoning each construction stage and performing real-time monitoring and early warning of real-time carbon emissions in each zone, the green and low-carbon management requirements during railway construction are met. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For those skilled in the art, other drawings can be obtained based on these drawings without creative work.

[0054] Figure 1 A schematic diagram of the structure of a digital twin management system for railway construction proposed in an embodiment of the present invention is shown;

[0055] Figure 2 An overall flow chart of a digital twin management method for railway construction proposed in an embodiment of the present invention is shown. DETAILED DESCRIPTION

[0056] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0057] The present application embodiment provides a digital twin management system for railway construction, such as Figure 1 As shown, it includes: a model building unit, which is used to obtain railway construction project information, establish a railway construction digital twin model based on the railway construction project information, determine the carbon emission factor prediction value according to the simulation results of the digital twin model, and determine the carbon emission prediction value of each stage of railway construction according to the carbon emission factor prediction value; a stage clustering unit, which is used to cluster each construction stage according to the carbon emission prediction value of each stage of railway construction, and divide each construction stage into corresponding cluster partitions according to the clustering results; an emission calculation unit, which is used to obtain the historical carbon emissions of each construction stage, and determine the carbon emission allowable value according to the historical carbon emissions of each construction stage; an emission warning unit, which is used to obtain the real-time carbon emissions of the current construction stage, determine the carbon emission deviation value according to the real-time carbon emissions of the current construction stage, and make a real-time carbon emission warning according to the carbon emission deviation value.

[0058] In this embodiment, the carbon emissions of each stage of railway construction are predicted through the digital twin model of railway construction, each construction stage is divided into corresponding cluster partitions according to the carbon emission prediction value, and the carbon emission allowable value is calculated based on the cluster partition to which each construction stage belongs, so as to achieve accurate distinction of each construction stage in the railway construction process, and perform segmented comparison of the carbon emissions of each construction stage to obtain more accurate carbon emission warning data, and obtain the carbon emission deviation value through the current real-time carbon emissions and the carbon emission allowable value, and make carbon emission warning based on the carbon emission deviation value, which can effectively meet the green and low-carbon management requirements in the railway construction process.

[0059] In some embodiments of the present application, the carbon emission prediction model is established, and the carbon emission prediction value of the construction phase is determined based on the carbon emission prediction model according to the carbon emission factor prediction value, including: obtaining historical carbon emission factor change data and the corresponding carbon emissions of the construction phase, and establishing a carbon emission sample set according to the historical carbon emission factor change data and the corresponding carbon emissions of the construction phase; establishing an initial carbon emission prediction model according to the carbon emission sample set and training the initial carbon emission prediction model to obtain a final carbon emission prediction model; obtaining the carbon emission factor prediction value of the construction phase, and inputting the carbon emission factor prediction value of the construction phase into the final carbon emission prediction model to obtain the carbon emission prediction value.

[0060] In this embodiment, an initial carbon emission prediction model is established according to the carbon emission sample set based on the deep learning neural network model. The initial carbon emission prediction model is trained through the carbon emission sample set to obtain the final carbon emission prediction model. The accurate prediction of carbon emissions during the railway construction phase is achieved through the simulation prediction data of the carbon emission factors.

[0061] In some embodiments of the present application, the model building unit builds a digital twin model of railway construction based on railway construction project information, and determines a predicted value of a carbon emission factor according to the simulation results of the digital twin model, including: obtaining railway construction project information, and dividing the railway construction project information into multiple construction stages according to a preset construction period; obtaining construction site data of each construction stage, determining the construction cost of each railway station based on the construction site data, and determining a weight value of each railway station based on the construction cost; obtaining a preset central station, constructing a construction site topological network based on a minimum tree generation algorithm combined with the weight value of each railway station, and establishing a digital twin model of railway construction based on the topological association of the site topological network combined with the construction site data; simulating each construction stage according to the digital twin model of railway construction, and determining a predicted value of a carbon emission factor for the construction stage according to the simulation results; establishing a carbon emission prediction model, and determining a predicted value of carbon emissions for the construction stage based on the carbon emission prediction model according to the predicted value of the carbon emission factor.

[0062] In this embodiment, the construction site data specifically includes the on-site layout, production materials, construction machinery and construction personnel of the railway construction site. The corresponding weight value is determined by the construction cost of each railway station. The higher the construction cost, the smaller the corresponding weight value. Based on the minimum tree generation algorithm, starting from the central station, a predetermined random strategy is used to select an edge to join the network each time. The weight value of each edge is obtained by the weight value corresponding to each railway station. The smaller the weight value, the greater the possibility of being selected. Iterate until all railway stations are connected to the network to obtain a construction site topological network. The digital twin model of railway construction is established by combining the construction site topological network with the construction site data to realize the simulation of each stage of railway construction, simulate the structure, electromechanical, personnel, geographical location and other on-site three-dimensional models of the construction site, model the railway construction site as a digital image, predict the material consumption and energy consumption of the construction site, and then simulate the carbon emission factors of each construction stage, and predict the carbon emissions of each construction stage according to the carbon emission factors based on the carbon emission prediction model.

[0063] In some embodiments of the present application, the stage clustering unit clusters each construction stage according to the predicted carbon emissions of each stage of railway construction, and divides each construction stage into a corresponding cluster partition according to the clustering result, including: establishing a carbon emission data set according to the average predicted carbon emissions of each construction stage, and randomly selecting k initial clustering centers of the carbon emission data set; calculating the Euclidean distance from the average carbon emission predicted value in the carbon emission data set to the initial clustering center, and dividing each construction stage into a corresponding cluster partition according to the Euclidean distance from the average carbon emission predicted value in the carbon emission data set to the initial clustering center; calculating the average value of the average carbon emission predicted value in each cluster partition, and recalculating the cluster center according to the average value of the average carbon emission predicted value in each cluster partition; repeatedly iterating the above steps until the cluster center no longer changes or the number of iterations reaches a preset maximum number of iterations, and dividing each construction stage into a corresponding final cluster partition according to the clustering result. In this embodiment, the k value is set to 4, and each construction stage is clustered according to the carbon emission prediction value based on the k-means clustering algorithm. Each construction stage is divided into 4 cluster partitions, and the carbon emission allowable value is calculated based on the cluster partition to which each construction stage belongs. This achieves accurate distinction between the construction stages in the railway construction process, and compares the carbon emissions of each construction stage in sections to obtain more accurate carbon emission warning data.

[0064] In some embodiments of the present application, the emission calculation unit determines the allowable carbon emission value based on the historical carbon emissions of each construction stage in combination with the corresponding cluster partition, including: obtaining the cluster center value of the cluster partition to which the construction stage belongs, and determining the carbon emission exceeding threshold value based on the cluster center value of the cluster partition to which the construction stage belongs; obtaining the historical carbon emission change data of each construction stage, and drawing a historical carbon emission change curve based on the historical carbon emission change data; screening out the historical carbon emissions that exceed the carbon emission exceeding threshold value in the historical carbon emission change curve, and determining the frequency of historical carbon emissions exceeding the carbon emission exceeding threshold value based on the historical carbon emissions that exceed the carbon emission exceeding threshold value; determining the allowable carbon emission value based on the frequency of historical carbon emissions exceeding the standard.

[0065] In this embodiment, historical carbon emission change data corresponding to the entire construction phase is obtained and a historical carbon emission change curve is drawn, and the number of historical carbon emissions that exceed the carbon emission excess threshold in the historical carbon emission change curve is determined as the excess frequency of historical carbon emissions.

[0066] In some embodiments of the present application, the carbon emission exceeding standard threshold is determined according to the cluster center value of the cluster partition to which the construction stage belongs, including: obtaining the sum of the cluster center values ​​of all construction stages, calculating the ratio of the cluster center value of each construction stage to the sum of the cluster center values ​​of all construction stages, and obtaining the carbon emission proportion coefficient of each construction stage; obtaining a preset full-cycle carbon emission exceeding standard threshold, multiplying the carbon emission proportion coefficient of each construction stage by the preset full-cycle carbon emission exceeding standard threshold, and obtaining the carbon emission exceeding standard threshold of each construction stage.

[0067] In this embodiment, the ratio of the cluster center value of each construction stage to the sum of the cluster center values ​​of all construction stages is calculated to obtain the proportion of the cluster center of each construction stage to all cluster centers. The preset full-cycle carbon emission exceeding threshold is divided into each construction stage through the carbon emission proportion coefficient to obtain the carbon emission exceeding threshold of each construction stage.

[0068] In some embodiments of the present application, determining the allowable value of carbon emissions according to the frequency of exceeding the standard of historical carbon emissions includes: calculating the allowable value of carbon emissions according to the allowable value calculation formula based on the frequency of exceeding the standard of historical carbon emissions, and the allowable value calculation formula is specifically:

[0069]

[0070] Among them, P is the allowable value of carbon emissions, P α is the preset initial carbon emission allowable value, C α is the preset frequency standard value of exceeding the standard, C is the frequency of exceeding the standard of historical carbon emissions, and R is the preset range coefficient.

[0071] In this embodiment, the allowable carbon emissions value is determined by the frequency of historical carbon emissions exceeding the standard. The greater the frequency of historical carbon emissions exceeding the standard, the lower the set allowable carbon emissions value is, and the lower the tolerance for carbon emissions during the construction phase is.

[0072] In some embodiments of the present application, the emission warning unit determines the carbon emission deviation value based on the real-time carbon emissions in the current construction stage, including: drawing a real-time carbon emission change curve according to the real-time carbon emissions change in the current construction stage, and dividing the real-time carbon emission change curve into several sub-change curves according to a preset sliding time window; counting the average carbon emissions of each sub-change curve, and drawing a mean value change curve according to the average carbon emissions of each sub-change curve; calculating the absolute values ​​of the slopes of adjacent mean values ​​in the mean value change curve, and determining the average value of all the absolute slope values ​​according to the absolute values ​​of the slopes of adjacent mean values ​​in the mean value change curve; normalizing the average values ​​of all the absolute slope values ​​to obtain a carbon emission fluctuation coefficient; calculating the difference between the real-time carbon emissions in the current construction stage and the allowable carbon emission value, and multiplying the carbon emission fluctuation coefficient by the difference between the corresponding real-time carbon emissions and the allowable carbon emission value to obtain a carbon emission deviation value.

[0073] In this embodiment, the carbon emissions changes in the current construction phase are monitored in real time according to the digital twin model of railway construction and a real-time carbon emissions change curve is drawn. The average value of the absolute values ​​of all slopes is normalized to limit the range of the average values ​​of the absolute values ​​of all slopes to [1, 2], thereby obtaining the carbon emissions fluctuation coefficient. The carbon emissions fluctuation coefficient represents the fluctuation of carbon emissions. The larger the carbon emissions fluctuation coefficient, the higher the corresponding carbon emissions deviation value, which facilitates the subsequent accurate early warning of real-time carbon emissions.

[0074] In some embodiments of the present application, the emission warning unit performs real-time carbon emission warning based on the carbon emission deviation value, including: establishing a preset carbon emission information library, obtaining the carbon emission grade parameters corresponding to each carbon emission deviation range in the carbon emission information library; matching the carbon emission deviation value with each carbon emission deviation range in the carbon emission information library, and determining the carbon emission grade parameters corresponding to the carbon emission deviation value according to the matching result; comparing the carbon emission grade parameters corresponding to the carbon emission deviation value with the preset carbon emission allowable parameters, and if the carbon emission grade parameters corresponding to the carbon emission deviation value are greater than the preset carbon emission allowable parameters, a carbon emission warning is performed.

[0075] In this embodiment, the carbon emission deviation value of the current construction stage is used to provide a real-time carbon emission warning, which facilitates project management personnel to take different emission reduction measures according to different warning levels, thus meeting the green and low-carbon management requirements during railway construction.

[0076] Based on the same technical concept, such as Figure 2As shown, the present invention also provides a digital twin management method for railway construction, comprising:

[0077] S101, obtaining railway construction project information, establishing a railway construction digital twin model based on the railway construction project information, determining a carbon emission factor prediction value according to a simulation result of the digital twin model, and determining a carbon emission prediction value at each stage of railway construction according to the carbon emission factor prediction value;

[0078] S102, clustering each construction stage according to the predicted carbon emission value of each railway construction stage, and dividing each construction stage into corresponding cluster partitions according to the clustering result;

[0079] S103, obtaining the historical carbon emissions of each construction stage, and determining the allowable carbon emissions value according to the historical carbon emissions of each construction stage;

[0080] S104, obtaining the real-time carbon emissions of the current construction phase, determining the carbon emissions deviation value according to the real-time carbon emissions of the current construction phase, and performing real-time carbon emissions warning according to the carbon emissions deviation value.

[0081] By applying the above technical scheme, the present invention uses a model building unit to obtain railway construction project information, establishes a railway construction digital twin model based on the railway construction project information, determines the carbon emission factor prediction value according to the simulation results of the digital twin model, and determines the carbon emission prediction value of each stage of railway construction according to the carbon emission factor prediction value; a stage clustering unit is used to cluster each construction stage according to the carbon emission prediction value of each stage of railway construction, and divides each construction stage into corresponding cluster partitions according to the clustering result; an emission calculation unit is used to obtain the historical carbon emissions of each construction stage, and determine the carbon emission allowable value according to the historical carbon emissions of each construction stage; an emission warning unit is used to obtain the real-time carbon emissions of the current construction stage, determine the carbon emission deviation value according to the real-time carbon emissions of the current construction stage, and perform real-time carbon emission warning according to the carbon emission deviation value. The present invention performs real-time monitoring and warning of carbon emissions at each stage of railway construction based on the digital twin model, meeting the green and low-carbon management requirements during railway construction.

[0082] Through the description of the above implementation methods, those skilled in the art can clearly understand that the present invention can be implemented by hardware, or by means of software plus a necessary general hardware platform. Based on such an understanding, the technical solution of the present invention can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, a USB flash drive, a mobile hard disk, etc.), including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each implementation scenario of the present invention.

[0083] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit it. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A digital twin management system for railway construction, characterized in that: include: A model building unit, used to obtain railway construction project information, build a railway construction digital twin model based on the railway construction project information, determine a carbon emission factor prediction value according to a simulation result of the digital twin model, and determine a carbon emission prediction value at each stage of railway construction according to the carbon emission factor prediction value; The stage clustering unit is used to cluster each construction stage according to the predicted carbon emission value of each stage of railway construction, and divide each construction stage into corresponding cluster partitions according to the clustering results; The emission calculation unit is used to obtain the historical carbon emissions of each construction stage, and determine the carbon emission allowable value according to the historical carbon emissions of each construction stage combined with the corresponding cluster partition; The emission warning unit is used to obtain the real-time carbon emissions of the current construction stage, determine the carbon emission deviation value according to the real-time carbon emissions of the current construction stage, and make a real-time carbon emission warning according to the carbon emission deviation value.

2. The digital twin management system for railway construction according to claim 1, characterized in that: The model building unit determines the predicted value of carbon emissions at each stage of railway construction according to the predicted value of carbon emission factor, including: Obtain the historical carbon emission factor change data and the corresponding carbon emissions during the construction phase, and establish a carbon emission sample set based on the historical carbon emission factor change data and the corresponding carbon emissions during the construction phase; An initial carbon emission prediction model is established according to the carbon emission sample set and the initial carbon emission prediction model is trained to obtain a final carbon emission prediction model; The predicted value of the carbon emission factor in the construction phase is obtained, and the predicted value of the carbon emission factor in the construction phase is input into the final carbon emission prediction model to obtain the predicted value of carbon emissions.

3. The digital twin management system for railway construction according to claim 2, characterized in that: The model building unit builds a railway construction digital twin model based on the railway construction project information, and determines a carbon emission factor prediction value according to a simulation result of the digital twin model, including: Acquire railway construction project information, and divide the railway construction project information into multiple construction stages according to a preset construction period; Acquire construction site data of each construction stage, determine the construction cost of each railway station according to the construction site data, and determine the weight value of each railway station according to the construction cost of each railway station; Obtain the preset central site, build a construction site topology network based on the minimum tree generation algorithm and the weight value of each railway site, and establish a railway construction digital twin model based on the topological association of the site topology network and the construction site data; Simulating each construction stage according to the railway construction digital twin model, obtaining simulation results, and determining a predicted value of the carbon emission factor in the construction stage according to the simulation results; A carbon emission prediction model is established, and based on the carbon emission prediction model, the predicted value of carbon emissions during the construction phase is determined according to the predicted value of the carbon emission factor.

4. The digital twin management system for railway construction according to claim 3, characterized in that: The stage clustering unit clusters each construction stage according to the predicted carbon emission value of each stage of railway construction, and divides each construction stage into corresponding cluster partitions according to the clustering result, including: A carbon emission data set is established based on the average carbon emission prediction values ​​of each construction stage, and k initial clustering centers of the carbon emission data set are randomly selected; Calculate the Euclidean distance from the average carbon emission prediction value in the carbon emission data set to the initial cluster center, and divide each construction stage into corresponding cluster partitions according to the Euclidean distance from the average carbon emission prediction value in the carbon emission data set to the initial cluster center; Calculate the average of the average carbon emission prediction values ​​in each cluster partition, and recalculate the cluster center according to the average of the average carbon emission prediction values ​​in each cluster partition; The above steps are repeated until the cluster center no longer changes or the number of iterations reaches the preset maximum number of iterations, and each construction stage is divided into the corresponding final cluster partition according to the clustering results.

5. The digital twin management system for railway construction according to claim 4, characterized in that: The emission calculation unit determines the carbon emission allowable value according to the historical carbon emission of each construction stage in combination with the corresponding cluster partition, including: Obtain the cluster center value of the cluster partition to which the construction stage belongs, and determine the carbon emission exceeding standard threshold value according to the cluster center value of the cluster partition to which the construction stage belongs; Obtain the historical carbon emission change data of each construction stage, and draw the historical carbon emission change curve based on the historical carbon emission change data; Screen out the historical carbon emissions that exceed the carbon emission exceeding standard threshold in the historical carbon emission change curve, and determine the exceeding standard frequency of the historical carbon emissions according to the historical carbon emissions that exceed the carbon emission exceeding standard threshold; The allowable value of carbon emissions is determined based on the frequency of historical carbon emissions exceeding the standard.

6. The digital twin management system for railway construction according to claim 5, characterized in that: The step of determining the carbon emission exceeding standard threshold according to the cluster center value of the cluster partition to which the construction stage belongs includes: Obtain the sum of the cluster center values ​​of all construction stages, calculate the ratio of the cluster center value of each construction stage to the sum of the cluster center values ​​of all construction stages, and obtain the carbon emission ratio coefficient of each construction stage; Obtain the preset full-cycle carbon emission exceeding standard threshold, multiply the carbon emission proportion coefficient of each construction stage by the preset full-cycle carbon emission exceeding standard threshold, and obtain the carbon emission exceeding standard threshold of each construction stage.

7. The digital twin management system for railway construction according to claim 6, characterized in that: Determining the permissible value of carbon emissions based on the frequency of exceeding the standard of historical carbon emissions includes: The allowable value of carbon emissions is calculated based on the frequency of exceeding the standard in historical carbon emissions according to the allowable value calculation formula. The allowable value calculation formula is specifically: Among them, P is the allowable value of carbon emissions, P α is the preset initial carbon emission allowable value, C α is the preset frequency standard value of exceeding the standard, C is the frequency of exceeding the standard of historical carbon emissions, and R is the preset range coefficient.

8. The digital twin management system for railway construction according to claim 1, characterized in that: The emission warning unit determines the carbon emission deviation value according to the real-time carbon emission in the current construction phase, including: Draw a real-time carbon emission change curve according to the real-time carbon emission change in the current construction phase, and divide the real-time carbon emission change curve into several sub-change curves according to the preset sliding time window; Count the average carbon emissions of each sub-change curve, and draw an average change curve based on the average carbon emissions of each sub-change curve; Calculate the absolute values ​​of slopes of adjacent average values ​​in the average value change curve, and determine the average value of all absolute values ​​of slopes according to the absolute values ​​of slopes of adjacent average values ​​in the average value change curve; The average of the absolute values ​​of all slopes is normalized to obtain the carbon emission fluctuation coefficient; Calculate the difference between the real-time carbon emissions in the current construction phase and the allowable carbon emissions value, multiply the carbon emission fluctuation coefficient by the corresponding difference between the real-time carbon emissions and the allowable carbon emissions value, and obtain the carbon emission deviation value.

9. The digital twin management system for railway construction according to claim 8, characterized in that: The emission warning unit performs a real-time carbon emission warning according to the carbon emission deviation value, including: Establish a preset carbon emission information database, and obtain the carbon emission grade parameters corresponding to each carbon emission deviation range in the carbon emission information database; Match the carbon emission deviation value with each carbon emission deviation range in the carbon emission information database, and determine the carbon emission grade parameter corresponding to the carbon emission deviation value according to the matching result; The carbon emission level parameter corresponding to the carbon emission deviation value is compared with the preset carbon emission allowable parameter. If the carbon emission level parameter corresponding to the carbon emission deviation value is greater than the preset carbon emission allowable parameter, a carbon emission warning is issued.

10. A digital twin management method for railway construction, characterized in that: include: Obtain railway construction project information, establish a railway construction digital twin model based on the railway construction project information, determine the carbon emission factor prediction value according to the simulation results of the digital twin model, and determine the carbon emission prediction value of each stage of railway construction according to the carbon emission factor prediction value; Cluster each construction stage according to the predicted carbon emissions at each stage of railway construction, and divide each construction stage into corresponding cluster partitions according to the clustering results; Obtain the historical carbon emissions of each construction stage and determine the allowable carbon emissions value based on the historical carbon emissions of each construction stage; Obtain the real-time carbon emissions of the current construction phase, determine the carbon emissions deviation value based on the real-time carbon emissions of the current construction phase, and issue a real-time carbon emissions warning based on the carbon emissions deviation value.

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