CN-122022182-A - BIM-based engineering carbon bank monitoring method, system, equipment and medium

CN122022182ACN 122022182 ACN122022182 ACN 122022182ACN-122022182-A

Abstract

The application relates to a BIM-based engineering carbon bank monitoring method, a system, equipment and a medium. The method comprises the steps of expanding attribute information for each component in a BIM model based on a construction resource allocation plan to obtain a carbon row association attribute reference model, carrying out identity matching on real-time data streams of the Internet of things and corresponding objects based on the carbon row association attribute reference model to obtain dynamic activity data streams, calculating carbon emission of each event based on the dynamic activity data streams to obtain a carbon emission event record set, carrying out aggregation on the carbon emission event record set based on a space grid and a time window to obtain a carbon row intensity space-time matrix, and carrying out thermodynamic diagram color rendering on the carbon row intensity space-time matrix based on a preset color mapping rule and the time window to obtain a time sequence carbon emission force diagram. The method can be used for finely and dynamically capturing the carbon emission, and effectively meets the requirement of real-time carbon management.

Inventors

FENG WEIJIANG
RUAN QI
KE TENGFEI
WANG ZEPU

Assignees

宁波财经学院

Dates

Publication Date: 20260512
Application Date: 20260209

Claims (9)

1. A method for monitoring engineering carbon banks based on BIM, the method comprising: Performing attribute information expansion on each component in the BIM based on the construction resource allocation plan to obtain a carbon row associated attribute reference model; Based on the carbon-row-associated attribute reference model, carrying out identity matching on the real-time data stream of the Internet of things and a corresponding object to obtain a dynamic activity data stream, wherein the object comprises at least one of the components, the transportation tasks and the equipment; Calculating the carbon emission of each event based on the dynamic activity data stream to obtain a carbon emission event record set, wherein the events comprise transportation events and energy consumption events; Based on a space grid and a time window, aggregating the carbon emission event record set to obtain a carbon emission intensity space-time matrix; Performing thermodynamic diagram color rendering on the carbon row intensity space-time matrix based on a preset color mapping rule and the time window to obtain a time sequence carbon exhaust diagram, wherein the time sequence carbon exhaust diagram is used for representing the carbon row intensities of the space grids corresponding to different times.
2. The method of claim 1, wherein calculating the carbon emissions for each event based on the dynamic activity data stream results in a carbon emissions event record set comprising: distributing the dynamic activity data stream to the corresponding event based on the activity type identifier of the dynamic activity data stream to obtain a transportation event data set and an energy consumption event data set; Calculating the actual driving distance and the load of each transportation task based on the transportation event data set to obtain a transportation task list; Calculating the transportation carbon emission based on the transportation task list to obtain a transportation carbon emission event record set; Wherein, the formula of transportation carbon emission is: Wherein, the For transport carbon emissions, i is the transport sector index, n is the sector number, For the load of the ith transport section, For the actual distance travelled by the ith transport section, A transport carbon emission factor for the ith transport section; based on the energy consumption event data set, aggregating the discrete energy consumption of the same equipment in one calculation period into total energy consumption to obtain an energy consumption summary table; And calculating the energy consumption carbon emission amount based on the energy consumption summary table to obtain an energy consumption carbon emission event record set, and integrating the energy consumption carbon emission event record set and the transportation carbon emission event record set to obtain the carbon emission event record set.
3. The method of claim 2, wherein calculating the energy consumption carbon emission based on the energy consumption summary table results in a record set of energy consumption carbon emission events, comprising: Based on the energy types of the energy consumption events, distributing the energy consumption events to the corresponding energy event types to obtain electric power energy consumption events, fuel energy consumption events and mixed energy consumption events; Calculating the electric power energy consumption event through an electric power consumption carbon emission calculation formula to obtain electric power consumption carbon emission; Wherein, the electric power consumption carbon emission calculation formula is: Wherein, the For the purpose of power consumption and carbon emission, As the total amount of power consumption, Carbon emission factors of regional power grids; calculating the fuel energy consumption event through a fuel consumption carbon emission calculation formula to obtain the fuel consumption carbon emission; wherein, the fuel consumption carbon emission calculation formula is: Wherein, the For the purpose of fuel consumption and carbon emission, In order to achieve a fuel consumption volume, Is a fuel carbon emission factor; Calculating the mixed energy consumption event through a mixed carbon consumption emission calculation formula to obtain mixed carbon consumption emission; and integrating the electric power consumption carbon emission amount, the fuel consumption carbon emission amount and the mixed consumption carbon emission amount to obtain the energy consumption carbon emission event record set.
4. The method according to claim 2, characterized in that the transport carbon emission factor is obtained by the following method: inquiring a reference carbon emission factor corresponding to the vehicle from a database based on the basic attribute of the vehicle to obtain a reference emission factor comparison table of the vehicle; performing feature extraction based on the vehicle reference emission factor comparison table and the historical transportation route to obtain a vehicle route feature set; the actual emission factor of the travel is used as a label and added into the travel feature set of the vehicle to obtain a travel data set; training a machine learning model by taking the travel data set as a training set to obtain an emission factor difference coefficient prediction model, wherein the emission factor difference coefficient prediction model is used for predicting the deviation degree of the actual emission factor of the travel relative to the reference carbon emission factor; And inputting the characteristics of the planned transportation task into the emission factor difference coefficient prediction model to obtain a difference coefficient, and adjusting the reference emission factor corresponding to the planned transportation task based on the difference coefficient to obtain the transportation carbon emission factor.
5. The method of claim 1, wherein aggregating the carbon emission event record set based on a spatial grid and a time window to obtain a carbon emission intensity spatiotemporal matrix comprises: based on the horizontal projection plane of the BIM model, carrying out space grid division to obtain the space grid; Based on the space grid, distributing each record in the carbon emission event record set into a corresponding grid unit to obtain a space event record set; Dividing each record in the carbon emission time record set into a corresponding time window based on the time window to obtain a time event record set; Summing the records which are positioned in the same space grid and are positioned in the same time window based on the space event record set and the time event record set to obtain an aggregate carbon emission scale; And calculating the carbon emission amount in unit time and unit area based on the polymerized carbon emission scale to obtain the carbon emission intensity space-time matrix.
6. The method of claim 1, wherein performing thermodynamic diagram color rendering on the carbon row intensity spatiotemporal matrix based on a preset color mapping rule and the time window to obtain a time-series carbon dioxide diagram comprises: Mapping each space grid in the carbon row intensity space-time matrix into the BIM model, and aligning the time window with the time scale of the progress time axis to obtain a space-time alignment data layer; Inquiring from the time-space alignment data layer based on the time pointed by the progress time axis to obtain a corresponding carbon emission intensity value of the time window; mapping the carbon emission intensity value into a corresponding color based on the color mapping rule to obtain grid piece metadata; and superposing and rendering the grid piece metadata on a three-dimensional space position corresponding to the BIM model to obtain the time sequence carbon heat extraction map.
7. A BIM-based engineered carbon black monitoring system, the system comprising: the reference module is used for carrying out attribute information expansion on each component in the BIM based on the construction resource allocation plan to obtain a carbon row associated attribute reference model; The matching module is used for carrying out identity matching on the real-time data stream of the Internet of things and a corresponding object based on the carbon-row-associated attribute reference model to obtain a dynamic activity data stream, wherein the object comprises at least one of the component, the transportation task and the equipment; The calculation module is used for calculating the carbon emission of each event based on the dynamic activity data flow to obtain a carbon emission event record set, wherein the events comprise transportation events and energy consumption events; The aggregation module is used for aggregating the carbon emission event record set based on the space grid and the time window to obtain a carbon emission intensity space-time matrix; And the rendering module is used for performing thermodynamic diagram color rendering on the carbon row intensity space-time matrix based on a preset color mapping rule and the time window to obtain a time sequence carbon exhaust diagram, wherein the time sequence carbon exhaust diagram is used for representing the carbon row intensities of the space grids corresponding to different times.
8. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor implements the steps of the method of any of claims 1 to 6 when the computer program is executed.
9. A computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the steps of the method of any of claims 1 to 6.

Description

BIM-based engineering carbon bank monitoring method, system, equipment and medium Technical Field The invention belongs to the field of engineering monitoring, and particularly relates to a BIM-based engineering carbon bank monitoring method, system, equipment and medium. Background With the deep development of green low-carbon transformation in the building industry, building carbon emission accounting and evaluation technologies appear, and the core characteristics of the building carbon emission accounting and evaluation technologies are that greenhouse gases generated in the whole life cycle of a building are systematically quantified. This leads to the current mainstream engineering carbon management approach, i.e. post-hoc accounting based on statistics and inventory after the project ends or at a fixed reporting period. In the traditional technology, paper receipts, invoices and standing accounts are collected manually, the consumption, transportation mileage and various energy consumption data of main building materials are collected and counted, and then are input into a preset electronic form, and the total carbon emission is calculated by multiplying a fixed emission factor. The whole process is mainly characterized by manual, offline and summarizing statistics. However, this approach currently has significant problems. The method has the advantages of coarse data granularity, poor real-time performance, incapability of capturing dynamic and discrete carbon emission activities in the construction process, management lag, high aggregation of accounting results, difficulty in positioning specific construction links, spatial positions or responsibility bodies, incapability of realizing accurate traceability and process optimization of carbon emission, and difficulty in meeting the modern requirements of refined and real-time carbon management due to the fact that the mode is seriously dependent on subsequent data arrangement, lack of transparent and reliable data chain support. Disclosure of Invention Based on the above, it is necessary to provide a BIM-based engineering carbon bank monitoring method, system, device and medium capable of dynamically capturing carbon banks at high frequency, fine and real time. In a first aspect, the present application provides a BIM-based engineering carbon bank monitoring method, including: Performing attribute information expansion on each component in the BIM based on the construction resource allocation plan to obtain a carbon row associated attribute reference model; based on the carbon-row-associated attribute reference model, carrying out identity matching on the real-time data stream of the Internet of things and the corresponding object to obtain a dynamic activity data stream, wherein the object comprises at least one of a component, a transportation task and equipment; calculating the carbon emission of each event based on the dynamic activity data flow to obtain a carbon emission event record set, wherein the events comprise transportation events and energy consumption events; Based on the space grid and the time window, aggregating the carbon emission event record set to obtain a carbon emission intensity space-time matrix; Performing thermodynamic diagram color rendering on the carbon row intensity space-time matrix based on a preset color mapping rule and a time window to obtain a time sequence carbon-hydrogen diagram, wherein the time sequence carbon-hydrogen diagram is used for representing the carbon row intensity of the space grid corresponding to different time. Further, based on the dynamic activity data stream, calculating the carbon emission amount of each event to obtain a carbon emission event record set, including: distributing the dynamic activity data stream to corresponding events based on the activity type identifier of the dynamic activity data stream to obtain a transportation event data set and an energy consumption event data set; calculating the actual driving distance and the load of each transportation task based on the transportation event data set to obtain a transportation task list; calculating the emission amount of transportation carbon based on the transportation task list to obtain a transportation carbon emission event record set; Wherein, the formula of transportation carbon emission is: Wherein, the For transport carbon emissions, i is the transport sector index, n is the sector number,For the load of the ith transport section,For the actual distance travelled by the ith transport section,A transport carbon emission factor for the ith transport section; based on the energy consumption event data set, aggregating the discrete energy consumption of the same equipment in one calculation period into total energy consumption to obtain an energy consumption summary table; and calculating the energy consumption carbon emission amount based on the energy consumption summary table to obtain an energy consumption carbon emissi