Green building whole cycle data intelligent processing method, device and equipment and medium

Abstract

The application discloses a green building full-cycle data intelligent processing method, device, equipment and medium, first, current building data set and current building data stage identifier are acquired; then, if the identifier is a design stage identifier, a design stage grading evaluation result corresponding to the current building data set is determined; if the identifier is a construction stage identifier, a construction stage collection data set is acquired, construction consistency verification is performed on the construction stage collection data set, and a current construction consistency verification result is obtained; if the identifier is a completion acceptance stage identifier and the corresponding current construction consistency verification result is a verification pass result, a current completion acceptance index set is automatically generated, a current actual completion acceptance index set is acquired, automatic comparison is performed on the current actual completion acceptance index set, and a current completion acceptance test result is obtained. The embodiment of the application can intelligently process full-life cycle data corresponding to the design stage, the construction stage and the completion acceptance stage of a green building, improve the utilization rate of relevant data at each link, avoid data islands, and cannot provide data guidance for each stage of the green building.

Description

Technical Field

[0001] This invention relates to the field of green building design technology, and in particular to intelligent processing methods, devices, equipment and media for the entire life cycle of green building data. Background Technology

[0002] Currently, green building evaluation systems are used to assess building safety and durability, health and comfort, resource conservation, and environmental livability. Current green building evaluations primarily focus on reviewing drawings or models during the design phase, using simulations, drawings, and document verification as the main evaluation criteria to achieve green building certification.

[0003] For example, in the patent with publication number CN117828378A, the design rating of the intelligent green building is obtained by clustering after acquiring various data of the intelligent green building. That is, only the design data of the green building is rated, and no related processing is performed on the building data in other stages after the rating. In the patent with publication number CN119783183A, after acquiring the green building rating data, error correction suggestions are made for data that does not meet the requirements, but no related processing is performed on the building data in other stages after the rating.

[0004] It is evident that existing assessment models generally fail to process building data at other stages after design simulation performance in order to more comprehensively acquire and store green building lifecycle data and assessment indicators. Summary of the Invention

[0005] This invention provides a method, apparatus, equipment, and medium for intelligent processing of green building full-lifecycle data. It aims to solve the problem in the prior art that green building data processing relies on simulation of drawings or models during the design phase to obtain design rating data, without processing the building data in other stages, in order to more comprehensively acquire and store green building full-lifecycle data and evaluation indicators.

[0006] In a first aspect, embodiments of the present invention provide a method for intelligent processing of green building lifecycle data, comprising: In response to data processing instructions for green buildings, obtain the current building dataset and the corresponding current building data stage identifier; If the current building data stage identifier is determined to be the design stage identifier, then the current building dataset is obtained, and the design stage classification assessment result corresponding to the current building dataset is determined according to the preset green building classification assessment strategy. If it is determined that the current building data stage identifier is a construction stage identifier and the design stage classification evaluation result of the corresponding current building dataset is the same as the preset green building level expected result, then the construction stage collection dataset is obtained, and the construction stage collection dataset is verified based on the preset construction consistency verification strategy to obtain the current construction consistency verification result. If the current building data stage identifier is determined to be the completion and acceptance stage identifier and the corresponding current construction consistency verification result is a verification pass result, then the current completion and acceptance indicator set is automatically generated, and the current actual completion and acceptance indicator set is obtained based on the current completion and acceptance indicator set and automatically compared and matched to obtain the current completion and acceptance inspection result.

[0007] Secondly, embodiments of the present invention also provide a green building full-lifecycle data intelligent processing device, which includes: The stage identifier acquisition unit is used to obtain the current building dataset and the corresponding current building data stage identifier in response to the data processing instructions for green buildings; The first processing unit is configured to, if the current building data stage identifier is determined to be a design stage identifier, obtain the current building dataset and determine the design stage classification assessment result corresponding to the current building dataset according to a preset green building classification assessment strategy. The second processing unit is configured to, if it is determined that the current building data stage identifier is a construction stage identifier and the design stage classification evaluation result of the corresponding current building dataset is the same as the preset green building level expected result, obtain the construction stage collection dataset, and verify the construction stage collection dataset based on the preset construction consistency verification strategy to obtain the current construction consistency verification result. The third processing unit is used to automatically generate the current completion and acceptance indicator set if it is determined that the current building data stage identifier is the completion and acceptance stage identifier and the corresponding current construction consistency verification result is a verification pass result, and obtain the current actual completion and acceptance indicator set according to the current completion and acceptance indicator set and automatically compare and match it to obtain the current completion and acceptance inspection result.

[0008] Thirdly, embodiments of the present invention also provide a computer device, which includes a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the method described in the first aspect above.

[0009] Fourthly, embodiments of the present invention also provide a computer-readable storage medium storing a computer program, the computer program including program instructions that, when executed by a processor, can implement the method described in the first aspect above.

[0010] This invention provides a method, apparatus, device, and medium for intelligent processing of green building lifecycle data. The method includes: responding to a green building data processing instruction, acquiring a current building dataset and a corresponding current building data stage identifier; if the current building data stage identifier is determined to be a design stage identifier, acquiring the current building dataset and determining a design stage grading assessment result corresponding to the current building dataset according to a preset green building grading assessment strategy; if the current building data stage identifier is determined to be a construction stage identifier and the corresponding current building dataset's design stage grading assessment result is the same as a preset green building grade expected result, acquiring a construction stage collection dataset and verifying the construction stage collection dataset based on a preset construction consistency verification strategy to obtain a current construction consistency verification result; if the current building data stage identifier is determined to be a completion and acceptance stage identifier and the corresponding current construction consistency verification result is a verification pass result, automatically generating a current completion and acceptance indicator set, acquiring the current actual completion and acceptance indicator set according to the current completion and acceptance indicator set, and automatically comparing and matching it to obtain the current completion and acceptance inspection result. The embodiments of the present invention can intelligently process the full life cycle data corresponding to the design, construction and completion acceptance stages of green buildings, improve the utilization rate of relevant data in each stage, avoid data silos and provide data guidance for each stage of green building. Attached Figure Description

[0011] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the following description of the embodiments will be briefly introduced. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0012] Figure 1 This is a schematic diagram illustrating an application scenario of the intelligent data processing method for the entire lifecycle of green buildings provided in this embodiment of the invention. Figure 2 A flowchart illustrating the intelligent processing method for the entire lifecycle data of green buildings provided in this embodiment of the invention; Figure 3 A schematic diagram of the first sub-process of the intelligent processing method for full-cycle data of green buildings provided in an embodiment of the present invention; Figure 4 This is a schematic diagram of the second sub-process of the intelligent processing method for full-cycle data of green buildings provided in an embodiment of the present invention; Figure 5 A schematic diagram of the third sub-process of the intelligent processing method for full-cycle data of green buildings provided in an embodiment of the present invention; Figure 6 A schematic block diagram of the intelligent data processing device for the entire life cycle of green buildings provided in this embodiment of the invention; Figure 7 A schematic block diagram of a computer device provided for an embodiment of the present invention. Detailed Implementation

[0013] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0014] It should be understood that, when used in this specification and the appended claims, the terms "comprising" and "including" indicate the presence of the described features, integrals, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or collections thereof.

[0015] It should also be understood that the terminology used in this specification is for the purpose of describing particular embodiments only and is not intended to limit the invention. As used in this specification and the appended claims, the singular forms “a,” “an,” and “the” are intended to include the plural forms unless the context clearly indicates otherwise.

[0016] It should also be further understood that the term "and / or" as used in this specification and the appended claims refers to any combination of one or more of the associated listed items and all possible combinations, and includes such combinations.

[0017] Please also refer to Figure 1 and Figure 2 ,in Figure 1 This is a schematic diagram illustrating an application scenario of the intelligent data processing method for the entire lifecycle of green buildings according to an embodiment of the present invention. Figure 2 This is a flowchart illustrating the intelligent data processing method for the entire lifecycle of green buildings provided in this embodiment of the invention. Figure 1 As shown in the figure, the intelligent processing method for green building full-cycle data provided in this embodiment of the invention is applied to server 10, which is an edge server or cloud server. Server 10 is connected to user terminal 20, which is a smartphone, tablet computer, laptop computer, desktop computer, etc. used by the user.

[0018] like Figure 2 As shown, the method includes the following steps S110-S140.

[0019] S110. In response to the data processing instructions for green buildings, obtain the current building dataset and the corresponding current building data stage identifier.

[0020] In this embodiment, the technical solution is described with the server as the execution entity. A green building full-lifecycle data intelligent processing platform is deployed on the server. After logging into this platform using a user terminal and their username and password, users can first import or select locally stored building data as the analysis object on the user interface. For example, users can retrieve candidate building datasets that meet the input search criteria (such as building project name, geographical region, unique building project number, etc.) from the locally stored building data. Then, users select the current building dataset to be used as the analysis object from the candidate datasets. Generally, different building projects are at different stages in the current time period. To perform more accurate intelligent analysis, it is also necessary to obtain the corresponding current building data stage identifier. The current building data stage identifier includes at least the design stage identifier, construction stage identifier, completion and acceptance stage identifier, and operation and management stage identifier (and may also include renovation, demolition, etc.), corresponding to different stages throughout the building's lifecycle.

[0021] S120. If the current building data stage identifier is determined to be the design stage identifier, then the current building dataset is obtained, and the design stage classification assessment result corresponding to the current building dataset is determined according to the preset green building classification assessment strategy.

[0022] In this embodiment, the design phase grading assessment result corresponds to either being the same as or different from the preset green building grade expectation result. If the design phase grading assessment result is determined to be the same as the preset green building grade expectation result, then based on the preset carbon simulation strategy, the operational carbon simulation dataset and implicit carbon simulation dataset of the current BIM model data in the current building dataset are obtained. Based on the matching results of the operational carbon simulation dataset and the implicit carbon simulation dataset with the preset building life-cycle carbon emission accounting conditions, corresponding labeling operations or suggested data output operations are performed. When the current building data phase identifier corresponding to the current building dataset selected by the user is the design phase identifier, it indicates that the corresponding target building to be analyzed has not yet started construction and is only in the design phase. At this time, the current building dataset mainly contains BIM model data (BIM stands for Building Information Modeling). Through the green building grading assessment strategy, the key model data can be extracted first and then used as input parameters to the green building grading assessment strategy to obtain the design phase grading assessment result.

[0023] In one embodiment, such as Figure 3 As shown, step S120 includes: S121. Obtain the current BIM model data from the current building dataset; S122. Based on the BIM model parameter extraction sub-strategy in the green building classification assessment strategy, obtain the amount of recyclable materials used, building materials used, window area, wall area, underground building area, land area, permeable pavement area and hard pavement area for each BIM component from the current building dataset. S123. Based on the current building dataset, obtain the recyclable material usage, building material usage, window area, wall area, underground building area, land area, permeable pavement area, and hard pavement area for each BIM component, and determine the recyclable material utilization rate, window-to-wall ratio, underground space utilization rate, and permeable pavement rate corresponding to the current building dataset; wherein, the recyclable material utilization rate is equal to the ratio between the sum of the recyclable material usage of each BIM component and the sum of the building material usage of each BIM component; the window-to-wall ratio of the current building dataset is equal to the ratio between the sum of the window areas of each BIM component and the sum of the wall areas of each BIM component; the underground space utilization rate is equal to the ratio between the sum of the underground building areas of each BIM component and the sum of the land areas of each BIM component; the permeable pavement rate is equal to the ratio between the sum of the permeable pavement areas of each BIM component and the sum of the hard pavement areas of each BIM component. S124. Based on the green building assessment sub-strategy in the green building grading assessment strategy, obtain and sum the index scores for the recyclable material utilization rate, the window-to-wall ratio, the underground space utilization rate and the permeable pavement rate to obtain the current assessment score. S125. Obtain multiple preset design stage classification levels and corresponding score ranges, determine the target score range to which the current evaluation score belongs in the multiple score ranges, and use the design stage classification level corresponding to the target score range as the design stage classification evaluation result.

[0024] In this embodiment, since the current BIM model data in the current building dataset includes a large number of BIM components, and each BIM component has multiple parameters, obtaining the complete parameters of each BIM component in the form of full acquisition of all parameters would result in the acquisition of irrelevant parameters. In this case, a sub-strategy can be extracted from the BIM model parameters in the green building grading assessment strategy to obtain the amount of recyclable materials used, building materials used, window area, wall area, underground building area, land area, permeable pavement area, and hard pavement area for each BIM component from the current building dataset. Other parameters of each BIM component do not need to be acquired at this stage.

[0025] Subsequently, following the specific calculation methods corresponding to the green building assessment sub-strategy, the following are used: the recyclable material utilization rate is equal to the ratio between the sum of the recyclable material usage of each BIM component and the sum of the building material usage of each BIM component; the window-to-wall ratio of the current building dataset is equal to the ratio between the sum of the window areas of each BIM component and the sum of the wall areas of each BIM component; the underground space utilization rate is equal to the ratio between the sum of the underground building areas of each BIM component and the sum of the land areas of each BIM component; and the permeable pavement rate is equal to the ratio between the sum of the permeable pavement areas of each BIM component and the sum of the hard pavement areas of each BIM component. After determining the recyclable material utilization rate, the window-to-wall ratio, the underground space utilization rate, and the permeable pavement rate, they are then directly summed or weighted summed to quickly determine the current assessment score.

[0026] Finally, since the green building grading assessment strategy also presets multiple design stage grading levels and corresponding score ranges, after determining the current assessment score corresponding to the current building dataset, it is matched with the score ranges corresponding to the multiple design stage grading levels to determine the target score range to which the current assessment score belongs in the multiple score ranges. The design stage grading level corresponding to the target score range is used as the design stage grading assessment result. Among them, the multiple design stage grading levels include one-star, two-star, and three-star levels. The score range corresponding to one-star is [60, 70), the score range corresponding to two-star is [70, 85), and the score range corresponding to three-star is [85, 100].

[0027] Of course, the design phase grading assessment results obtained from the current building dataset are merely simulation assessment results of the green building design phase grading assessment conducted by the user through the green building full-cycle data intelligent processing platform. They serve as an initial judgment on whether the current building dataset meets the user's expected green building rating for the current building, rather than being the final green building rating determination result. If the current building dataset does not meet the user's expected green building rating for the current building, it indicates that the BIM components of the current BIM model data can be adjusted and optimized accordingly, allowing for repeated acquisition of the current assessment score. Through continuous optimization and adjustment, the target green building rating for the current building can be achieved.

[0028] In one embodiment, the method further includes the following after step S125: If it is determined that the design phase grading assessment result is different from the preset green building grade expectation result, then the current optimization suggestion data and the corresponding current optimization suggestion construction difficulty dataset are obtained according to the locally pre-built green building optimization knowledge base, which are the design phase grading assessment result and the current BIM model data.

[0029] In this embodiment, if it is determined that the design stage grading assessment result is different from the preset green building level expected result, it is generally because the current assessment score corresponding to the design stage grading assessment result is lower than the lower limit score corresponding to the green building level expected result. At this time, it is necessary to find indicators that can be further optimized from factors such as the utilization rate of recyclable materials, the window-to-wall ratio, the utilization rate of underground space, and the permeable pavement rate.

[0030] For example, if at least one of the four parameters—recyclable material utilization rate, window-to-wall ratio, underground space utilization rate, and permeable pavement rate—is lower than the corresponding preset standard value or outside the preset standard value range, such as recyclable material utilization rate being lower than the preset recyclable material utilization rate, window-to-wall ratio not being within the preset window-to-wall ratio standard value range, or underground space utilization rate being lower than the preset underground space utilization rate, the specific adjustment method is as follows: If the recyclable material utilization rate is lower than the preset recyclable material utilization rate, then priority should be given to adjusting the material properties of BIM components such as beams, slabs, columns, and steel structures to improve the recyclability of steel, aluminum, etc. Material proportions; if the window-to-wall ratio is not within the preset standard range, more specifically, if the window-to-wall ratio is lower than the lower limit of the preset standard range, it will result in insufficient lighting. In this case, the window area in BIM components with window structures can be increased, or window interfaces can be added to some BIM components that can have window structures added. If the window-to-wall ratio is higher than the upper limit of the preset standard range, it will result in increased building heating and cooling energy consumption. In this case, the window area in BIM components with window structures can be reduced. If it is determined that the underground space utilization rate is lower than the preset underground space utilization rate, the area of ​​BIM components and their building areas belonging to the underground building type in the current BIM model data can be increased accordingly.

[0031] If a low-scoring parameter (such as the utilization rate of recyclable materials, the utilization rate of underground space, and the permeable pavement rate) or a non-standard parameter (generally referring to the window-to-wall ratio) is determined among the four parameter indicators corresponding to the design stage grading assessment results, then the current optimization suggestion data and the corresponding current optimization suggestion construction difficulty dataset are obtained from the local green building optimization knowledge base, based on the design stage grading assessment results and the current BIM model data. Specifically, when it is determined that the utilization rate of recyclable materials, the utilization rate of underground space, or the permeable pavement rate is lower than the corresponding preset standard value, for example, taking the utilization rate of recyclable materials as lower than the preset recyclable material utilization rate, the current optimization suggestion data that can improve the utilization rate of recyclable materials (such as prioritizing the adjustment of the material properties of BIM components of beams, slabs, columns, and steel structures, and increasing the proportion of recyclable materials such as steel and aluminum) and the corresponding current optimization suggestion construction difficulty dataset (if there is a material change for the BIM component of the column, the corresponding increase in on-site construction difficulty description and provision of construction process suggestion video data, etc.) can be viewed by the user before the specific adjustment of the BIM component is determined.

[0032] In one embodiment, the step of performing corresponding tagging operations or suggested data output operations based on the matching results of the operational carbon simulation dataset and the implicit carbon simulation dataset with preset building life-cycle carbon emission accounting conditions includes: If it is determined that both the operational carbon simulation dataset and the implicit carbon simulation dataset meet the preset building life cycle carbon emission accounting conditions, then the estimated carbon emission compliance label will be automatically added to the current building dataset. If it is determined that the operational carbon simulation dataset and the implicit carbon simulation dataset do not meet the preset building life cycle carbon emission accounting conditions, then the current carbon emission optimization suggestion data corresponding to the current building dataset is obtained based on the locally pre-built green building carbon emission optimization knowledge base.

[0033] In this embodiment, if it is determined that the design stage grading assessment result is the same as the preset green building level expectation result, it means that the green building star rating corresponding to the current BIM model data is the same as the user's initial design expectation when evaluating the indicator scores of the recyclable material utilization rate, the window-to-wall ratio, the underground space utilization rate, and the permeable pavement rate. At this time, the operational carbon simulation dataset and implicit carbon simulation dataset of the current BIM model data can be further obtained according to the carbon simulation strategy.

[0034] Specifically, when obtaining the operational carbon simulation dataset and implicit carbon simulation dataset of the current BIM model data based on the carbon simulation strategy, taking the calculation of implicit carbon simulation data for one BIM component in the current BIM model data as an example, the calculation process is as follows: 1) Obtain the weight and material information of the BIM component; 2) Obtain the current material production carbon emission factor and the current material transportation carbon emission factor corresponding to the material information from the pre-built material production and transportation carbon emission factor library. Multiply the current material production carbon emission factor with the weight data corresponding to the weight information to determine the carbon emission data of the current material production stage. Multiply the current material transportation carbon emission factor, the transportation distance of the current material from the supplier to the construction site, and the weight data corresponding to the weight information to determine the carbon emission data of the current material transportation stage. 3) Obtain the current material carbon reduction factor corresponding to the material information from the pre-built material recycling carbon reduction factor library, and determine the current material recycling carbon reduction data by multiplying the current material carbon reduction factor with the weight data corresponding to the weight information; 4) The implicit carbon simulation data of the BIM component is determined by adding the carbon emission data of the current material production stage to the carbon emission data of the current material transportation stage and subtracting the carbon emission reduction data of the current material recycling stage.

[0035] Then, the implicit carbon simulation data of each BIM component in the current BIM model data can be summarized to obtain the implicit carbon simulation dataset, and the total implicit carbon simulation data corresponding to the current BIM model data can be obtained by summing the implicit carbon simulation data of each BIM component in the implicit carbon simulation dataset.

[0036] When acquiring the operational carbon simulation dataset based on the carbon simulation strategy using the current BIM model data, the current BIM model data can be directly input into a building energy consumption simulation tool (such as EnergyPlus, OpenStudio, PKPM-PBECA, etc.). It should be noted that if the entire current BIM model data is input into the building energy consumption simulation tool, a large number of component parameters from each BIM component that are not needed for energy consumption simulation will be input. Before this, parameter filtering processing can be performed on each BIM component in the current BIM model according to a preset BIM component energy consumption simulation highly relevant parameter filtering model to achieve data dimensionality reduction (e.g., filtering out the geometric parameters and structural thermal parameters of BIM components of the envelope type; filtering out the spatial area, floor height, and volume of BIM components of the room / space type; filtering out the capacity, air volume, flow rate, efficiency, etc. of BIM components of the electromechanical equipment type). Then, the data can be input into the building energy consumption simulation tool to obtain the operational carbon simulation dataset of the current BIM model data. This processing method effectively reduces the system resource consumption of the server during energy consumption simulation.

[0037] After obtaining the operational carbon simulation dataset and the implicit carbon simulation dataset of the current BIM model data, if it is further determined that both the operational carbon simulation dataset and the implicit carbon simulation dataset meet the preset carbon emission accounting conditions for the entire building life cycle, it means that the building corresponding to the current BIM model data meets the carbon emission standards for green and environmentally friendly buildings, and the estimated carbon emission compliance label can be automatically added to the current building dataset. If it is determined that the operational carbon simulation dataset and the implicit carbon simulation dataset do not meet the preset building life-cycle carbon emission accounting conditions, it means that the building corresponding to the current BIM model data does not meet the carbon emission standards for green and environmentally friendly buildings. Based on the locally pre-built green building carbon emission optimization knowledge base, current carbon emission optimization suggestions corresponding to the current building dataset are obtained. For example, using the building region, building function type, number of floors, and the unmet accounting conditions as filtering conditions, candidate knowledge sets for the same scenario are screened in the green building carbon emission optimization knowledge base. Inapplicable cross-building type and cross-regional solutions are filtered out. Then, for high-carbon-contributing components (concrete, steel, curtain wall, etc.) in the BIM components, low-carbon alternative building materials, component structure optimization, and reduction design schemes for the same component are retrieved from the green building carbon emission optimization knowledge base. For high-energy-consuming systems (air conditioning, lighting, water supply and drainage) in the operational carbon identification simulation of BIM components, corresponding equipment, control strategies, building envelope insulation, natural ventilation and lighting, and other operational carbon reduction schemes are retrieved from the green building carbon emission optimization knowledge base.

[0038] As can be seen, the above method of acquiring both operational carbon simulation datasets and implicit carbon simulation datasets for the current BIM model data, compared to the existing technology that only acquires the corresponding operational carbon simulation datasets for the current BIM model data, can more accurately obtain the building's full life cycle carbon emission data, so as to determine whether the current BIM model data needs to be adjusted.

[0039] S130. If it is determined that the current building data stage identifier is a construction stage identifier and the design stage classification evaluation result of the corresponding current building dataset is the same as the preset green building level expected result, then the construction stage collection dataset is obtained, and the construction stage collection dataset is verified based on the preset construction consistency verification strategy to obtain the current construction consistency verification result.

[0040] In this embodiment, if the current building data stage identifier is determined to be a construction stage identifier, it indicates that the corresponding target building to be analyzed has started construction but has not yet been completed. At this time, the purchase orders, material arrival inspection reports, and equipment selection parameters of the building materials used in the target building to be analyzed can be compared with the BIM model data determined in the design stage of the target building to achieve consistency verification. If the data set collected during the construction stage passes the consistency verification strategy, it indicates that no equipment or materials have been changed during the construction stage of the target building to be analyzed. If the data set collected during the construction stage fails the consistency verification strategy, it indicates that equipment or materials may have been changed during the construction stage of the target building to be analyzed, and corresponding consistency warning information needs to be generated in a timely manner.

[0041] In one embodiment, taking the verification of construction consistency of electromechanical equipment in BIM model data as an example, such as... Figure 4 As shown, step S130 includes: S131. Obtain the current list of equipment to be purchased that belongs to the electromechanical equipment type in the current BIM model data corresponding to the data set collected during the construction phase; S132. Obtain the list of currently inspected equipment that belongs to the electromechanical equipment type from the data collected during the construction phase. S133. If the construction consistency verification strategy determines that the current list of equipment to be verified is consistent with the current list of equipment to be procured, then the current construction consistency verification result for the type of electromechanical equipment is a verification pass result.

[0042] In this embodiment, taking the construction consistency verification of mechanical and electrical equipment (MEP) equipment on a specific floor in the BIM model data as an example, the current list of equipment to be procured for that floor can be determined by filtering the MEP equipment in the BIM model data. Since each piece of MEP equipment is recorded or registered upon entering the construction site (e.g., through image acquisition or barcode scanning), the current list of equipment to be verified on that floor can also be obtained. If the construction consistency verification strategy determines that the current list of equipment to be verified is consistent with the current list of equipment to be procured (i.e., completely identical), it indicates that no replacement of MEP equipment occurred during the construction phase of the target building being analyzed. If the construction consistency verification strategy determines that the current list of equipment to be verified is inconsistent with the current list of equipment to be procured, it indicates that replacement of MEP equipment may occur during the construction phase of the target building being analyzed, requiring timely early warning. It is evident that by verifying the construction consistency of the target building during its construction phase, we can accurately detect whether it is constructed in accordance with the green building scheme determined in the design phase, and provide timely warnings when inconsistencies occur.

[0043] S140. If the current building data stage identifier is determined to be the completion and acceptance stage identifier and the corresponding current construction consistency verification result is a verification pass result, then the current completion and acceptance indicator set is automatically generated, and the current actual completion and acceptance indicator set is obtained based on the current completion and acceptance indicator set and automatically compared and matched to obtain the current completion and acceptance inspection result.

[0044] In this embodiment, during the completion and acceptance phase of the target building to be analyzed, the green building full-cycle data intelligent processing platform can acquire the user's current actual completion and acceptance needs (such as completion and acceptance of building envelope, site and outdoor environment, electromechanical equipment system data, etc.) and generate a corresponding current completion and acceptance indicator set. The user then acquires the relevant indicators on-site to form the current actual completion and acceptance indicator set. Each current actual completion and acceptance indicator in the current actual completion and acceptance indicator set is compared and matched with the corresponding current completion and acceptance indicator in the current actual completion and acceptance indicator set. The result of the current completion and acceptance inspection is obtained by determining whether the two are consistent. For example, if the specific values ​​of each current actual completion and acceptance indicator in the current actual completion and acceptance indicator set are all within the normal acceptance range corresponding to the corresponding current completion and acceptance indicator in the current actual completion and acceptance indicator set, then the acceptance pass result is taken as the current completion and acceptance inspection result; otherwise, the acceptance fail result is taken as the current completion and acceptance inspection result.

[0045] In one embodiment, taking the final acceptance of electromechanical equipment in the target building to be analyzed as an example, such as... Figure 5As shown, step S140 includes: S141. Obtain the qualified range of the final acceptance energy efficiency ratio for each electromechanical equipment in the target building to be analyzed, and form a set of current final acceptance indicators for the electromechanical equipment. S142. Obtain the actual operating energy efficiency ratio of each electromechanical device in the target building to be analyzed, so as to form a set of current actual completion acceptance indicators for the electromechanical devices; S143. If it is determined that each current actual completion acceptance indicator in the current actual completion acceptance indicator set for electromechanical equipment is within the normal indicator acceptance range corresponding to the current completion acceptance indicator in the current completion acceptance indicator set, then the acceptance pass result shall be taken as the current completion acceptance inspection result for electromechanical equipment.

[0046] In this embodiment, taking the final acceptance of electromechanical equipment in the target building during the final acceptance phase as an example, the process begins by using a green building full-cycle data intelligent processing platform to obtain the acceptable range of energy efficiency ratios for each electromechanical device in the target building based on the user's current actual final acceptance requirements (e.g., final acceptance of all electromechanical equipment). This data is then used to form a current final acceptance indicator set for the electromechanical equipment. Next, after the electromechanical equipment in the target building has been running for a period of time (e.g., 24 hours, 48 ​​hours, etc.), the actual operating energy efficiency ratios for each electromechanical device are obtained, forming a current actual final acceptance indicator set for the electromechanical equipment. Only when each current actual final acceptance indicator in the current actual final acceptance indicator set for the electromechanical equipment is within the normal acceptance range corresponding to the current final acceptance indicator in the current final acceptance indicator set can the acceptance pass result be used as the current final acceptance inspection result for the electromechanical equipment; otherwise, the acceptance fail result is used as the current final acceptance inspection result for the electromechanical equipment.

[0047] It is evident that the implementation of this method can intelligently process the full lifecycle data corresponding to the design, construction, and completion acceptance stages of green buildings, improve the utilization rate of relevant data at each stage, avoid data silos, and prevent the inability to provide data guidance for each stage of green building.

[0048] Figure 6 This is a schematic block diagram of a green building full-lifecycle data intelligent processing device provided in an embodiment of the present invention. Figure 6 As shown, corresponding to the above-described intelligent processing method for green building lifecycle data, the present invention also provides an intelligent processing device 100 for green building lifecycle data. This intelligent processing device 100 includes a unit for executing the above-described intelligent processing method for green building lifecycle data. Please refer to... Figure 6The green building full-cycle data intelligent processing device 100 includes: a stage identification acquisition unit 110, a first processing unit 120, a second processing unit 130, and a third processing unit 140.

[0049] The stage identifier acquisition unit 110 is used to acquire the current building dataset and the corresponding current building data stage identifier in response to the data processing instructions for green buildings.

[0050] In this embodiment, the technical solution is described with the server as the execution entity. A green building full-lifecycle data intelligent processing platform is deployed on the server. After logging into this platform using a user terminal and their username and password, users can first import or select locally stored building data as the analysis object on the user interface. For example, users can retrieve candidate building datasets that meet the input search criteria (such as building project name, geographical region, unique building project number, etc.) from the locally stored building data. Then, users select the current building dataset to be used as the analysis object from the candidate datasets. Generally, different building projects are at different stages in the current time period. To perform more accurate intelligent analysis, it is also necessary to obtain the corresponding current building data stage identifier. The current building data stage identifier includes at least the design stage identifier, construction stage identifier, completion and acceptance stage identifier, and operation and management stage identifier (and may also include renovation, demolition, etc.), corresponding to different stages throughout the building's lifecycle.

[0051] The first processing unit 120 is configured to, if the current building data stage identifier is determined to be a design stage identifier, obtain the current building dataset and determine the design stage classification assessment result corresponding to the current building dataset according to a preset green building classification assessment strategy.

[0052] In this embodiment, the design phase grading assessment result corresponds to either being the same as or different from the preset green building grade expectation result. If the design phase grading assessment result is determined to be the same as the preset green building grade expectation result, then based on the preset carbon simulation strategy, the operational carbon simulation dataset and implicit carbon simulation dataset of the current BIM model data in the current building dataset are obtained. Based on the matching results of the operational carbon simulation dataset and the implicit carbon simulation dataset with the preset building life-cycle carbon emission accounting conditions, corresponding labeling operations or suggested data output operations are performed. When the current building data phase identifier corresponding to the current building dataset selected by the user is the design phase identifier, it indicates that the corresponding target building to be analyzed has not yet started construction and is only in the design phase. At this time, the current building dataset mainly contains BIM model data (BIM stands for Building Information Modeling). Through the green building grading assessment strategy, the key model data can be extracted first and then used as input parameters to the green building grading assessment strategy to obtain the design phase grading assessment result.

[0053] In one embodiment, the first processing unit 120 is specifically used for: Obtain the current BIM model data from the current building dataset; Based on the BIM model parameter extraction sub-strategy in the green building grading assessment strategy, the amount of recyclable materials used, building materials used, window area, wall area, underground building area, land area, permeable pavement area and hard pavement area are obtained from the current building dataset for each BIM component. Based on the current building dataset, the recyclable material usage, building material usage, window area, wall area, underground building area, land area, permeable pavement area, and hard pavement area are obtained for each BIM component. The recyclable material utilization rate, window-to-wall ratio, underground space utilization rate, and permeable pavement rate corresponding to the current building dataset are then determined. Specifically, the recyclable material utilization rate is equal to the ratio between the sum of the recyclable material usage of each BIM component and the sum of the building material usage of each BIM component; the window-to-wall ratio of the current building dataset is equal to the ratio between the sum of the window areas of each BIM component and the sum of the wall areas of each BIM component; the underground space utilization rate is equal to the ratio between the sum of the underground building areas of each BIM component and the sum of the land areas of each BIM component; and the permeable pavement rate is equal to the ratio between the sum of the permeable pavement areas of each BIM component and the sum of the hard pavement areas of each BIM component. Based on the green building assessment sub-strategy in the green building grading assessment strategy, the index scores of the recyclable material utilization rate, the window-to-wall ratio, the underground space utilization rate, and the permeable pavement rate are obtained and summed to obtain the current assessment score; Obtain multiple preset design stage classification levels and corresponding score ranges, determine the target score range to which the current evaluation score belongs in the multiple score ranges, and use the design stage classification level corresponding to the target score range as the design stage classification evaluation result.

[0054] In this embodiment, since the current BIM model data in the current building dataset includes a large number of BIM components, and each BIM component has multiple parameters, obtaining the complete parameters of each BIM component in the form of full acquisition of all parameters would result in the acquisition of irrelevant parameters. In this case, a sub-strategy can be extracted from the BIM model parameters in the green building grading assessment strategy to obtain the amount of recyclable materials used, building materials used, window area, wall area, underground building area, land area, permeable pavement area, and hard pavement area for each BIM component from the current building dataset. Other parameters of each BIM component do not need to be acquired at this stage.

[0055] Subsequently, following the specific calculation methods corresponding to the green building assessment sub-strategy, the following are used: the recyclable material utilization rate is equal to the ratio between the sum of the recyclable material usage of each BIM component and the sum of the building material usage of each BIM component; the window-to-wall ratio of the current building dataset is equal to the ratio between the sum of the window areas of each BIM component and the sum of the wall areas of each BIM component; the underground space utilization rate is equal to the ratio between the sum of the underground building areas of each BIM component and the sum of the land areas of each BIM component; and the permeable pavement rate is equal to the ratio between the sum of the permeable pavement areas of each BIM component and the sum of the hard pavement areas of each BIM component. After determining the recyclable material utilization rate, the window-to-wall ratio, the underground space utilization rate, and the permeable pavement rate, they are then directly summed or weighted summed to quickly determine the current assessment score.

[0056] Finally, since the green building grading assessment strategy also presets multiple design stage grading levels and corresponding score ranges, after determining the current assessment score corresponding to the current building dataset, it is matched with the score ranges corresponding to the multiple design stage grading levels to determine the target score range to which the current assessment score belongs in the multiple score ranges. The design stage grading level corresponding to the target score range is used as the design stage grading assessment result. Among them, the multiple design stage grading levels include one-star, two-star, and three-star levels. The score range corresponding to one-star is [60, 70), the score range corresponding to two-star is [70, 85), and the score range corresponding to three-star is [85, 100].

[0057] Of course, the design phase grading assessment results obtained from the current building dataset are merely simulation assessment results of the green building design phase grading assessment conducted by the user through the green building full-cycle data intelligent processing platform. They serve as an initial judgment on whether the current building dataset meets the user's expected green building rating for the current building, rather than being the final green building rating determination result. If the current building dataset does not meet the user's expected green building rating for the current building, it indicates that the BIM components of the current BIM model data can be adjusted and optimized accordingly, allowing for repeated acquisition of the current assessment score. Through continuous optimization and adjustment, the target green building rating for the current building can be achieved.

[0058] In one embodiment, the first processing unit 120 is further specifically used for: If it is determined that the design phase grading assessment result is different from the preset green building grade expectation result, then the current optimization suggestion data and the corresponding current optimization suggestion construction difficulty dataset are obtained according to the locally pre-built green building optimization knowledge base, which are the design phase grading assessment result and the current BIM model data.

[0059] In this embodiment, if it is determined that the design stage grading assessment result is different from the preset green building level expected result, it is generally because the current assessment score corresponding to the design stage grading assessment result is lower than the lower limit score corresponding to the green building level expected result. At this time, it is necessary to find indicators that can be further optimized from factors such as the utilization rate of recyclable materials, the window-to-wall ratio, the utilization rate of underground space, and the permeable pavement rate.

[0060] For example, if at least one of the four parameters—recyclable material utilization rate, window-to-wall ratio, underground space utilization rate, and permeable pavement rate—is lower than the corresponding preset standard value or outside the preset standard value range, such as recyclable material utilization rate being lower than the preset recyclable material utilization rate, window-to-wall ratio not being within the preset window-to-wall ratio standard value range, or underground space utilization rate being lower than the preset underground space utilization rate, the specific adjustment method is as follows: If the recyclable material utilization rate is lower than the preset recyclable material utilization rate, then priority should be given to adjusting the material properties of BIM components such as beams, slabs, columns, and steel structures to improve the recyclability of steel, aluminum, etc. Material proportions; if the window-to-wall ratio is not within the preset standard range, more specifically, if the window-to-wall ratio is lower than the lower limit of the preset standard range, it will result in insufficient lighting. In this case, the window area in BIM components with window structures can be increased, or window interfaces can be added to some BIM components that can have window structures added. If the window-to-wall ratio is higher than the upper limit of the preset standard range, it will result in increased building heating and cooling energy consumption. In this case, the window area in BIM components with window structures can be reduced. If it is determined that the underground space utilization rate is lower than the preset underground space utilization rate, the area of ​​BIM components and their building areas belonging to the underground building type in the current BIM model data can be increased accordingly.

[0061] If a low-scoring parameter (such as the utilization rate of recyclable materials, the utilization rate of underground space, and the permeable pavement rate) or a non-standard parameter (generally referring to the window-to-wall ratio) is determined among the four parameter indicators corresponding to the design stage grading assessment results, then the current optimization suggestion data and the corresponding current optimization suggestion construction difficulty dataset are obtained from the local green building optimization knowledge base, based on the design stage grading assessment results and the current BIM model data. Specifically, when it is determined that the utilization rate of recyclable materials, the utilization rate of underground space, or the permeable pavement rate is lower than the corresponding preset standard value, for example, taking the utilization rate of recyclable materials as lower than the preset recyclable material utilization rate, the current optimization suggestion data that can improve the utilization rate of recyclable materials (such as prioritizing the adjustment of the material properties of BIM components of beams, slabs, columns, and steel structures, and increasing the proportion of recyclable materials such as steel and aluminum) and the corresponding current optimization suggestion construction difficulty dataset (if there is a material change for the BIM component of the column, the corresponding increase in on-site construction difficulty description and provision of construction process suggestion video data, etc.) can be viewed by the user before the specific adjustment of the BIM component is determined.

[0062] In one embodiment, the first processing unit 120 is further specifically used for: If it is determined that both the operational carbon simulation dataset and the implicit carbon simulation dataset meet the preset building life cycle carbon emission accounting conditions, then the estimated carbon emission compliance label will be automatically added to the current building dataset. If it is determined that the operational carbon simulation dataset and the implicit carbon simulation dataset do not meet the preset building life cycle carbon emission accounting conditions, then the current carbon emission optimization suggestion data corresponding to the current building dataset is obtained based on the locally pre-built green building carbon emission optimization knowledge base.

[0063] In this embodiment, if it is determined that the design stage grading assessment result is the same as the preset green building level expectation result, it means that the green building star rating corresponding to the current BIM model data is the same as the user's initial design expectation when evaluating the indicator scores of the recyclable material utilization rate, the window-to-wall ratio, the underground space utilization rate, and the permeable pavement rate. At this time, the operational carbon simulation dataset and implicit carbon simulation dataset of the current BIM model data can be further obtained according to the carbon simulation strategy.

[0064] Specifically, when obtaining the operational carbon simulation dataset and implicit carbon simulation dataset of the current BIM model data based on the carbon simulation strategy, taking the calculation of implicit carbon simulation data for one BIM component in the current BIM model data as an example, the calculation process is as follows: 1) Obtain the weight and material information of the BIM component; 2) Obtain the current material production carbon emission factor and the current material transportation carbon emission factor corresponding to the material information from the pre-built material production and transportation carbon emission factor library. Multiply the current material production carbon emission factor with the weight data corresponding to the weight information to determine the carbon emission data of the current material production stage. Multiply the current material transportation carbon emission factor, the transportation distance of the current material from the supplier to the construction site, and the weight data corresponding to the weight information to determine the carbon emission data of the current material transportation stage. 3) Obtain the current material carbon reduction factor corresponding to the material information from the pre-built material recycling carbon reduction factor library, and determine the current material recycling carbon reduction data by multiplying the current material carbon reduction factor with the weight data corresponding to the weight information; 4) The implicit carbon simulation data of the BIM component is determined by adding the carbon emission data of the current material production stage to the carbon emission data of the current material transportation stage and subtracting the carbon emission reduction data of the current material recycling stage.

[0065] Then, the implicit carbon simulation data of each BIM component in the current BIM model data can be summarized to obtain the implicit carbon simulation dataset, and the total implicit carbon simulation data corresponding to the current BIM model data can be obtained by summing the implicit carbon simulation data of each BIM component in the implicit carbon simulation dataset.

[0066] When acquiring the operational carbon simulation dataset based on the carbon simulation strategy using the current BIM model data, the current BIM model data can be directly input into a building energy consumption simulation tool (such as EnergyPlus, OpenStudio, PKPM-PBECA, etc.). It should be noted that if the entire current BIM model data is input into the building energy consumption simulation tool, a large number of component parameters from each BIM component that are not needed for energy consumption simulation will be input. Before this, parameter filtering processing can be performed on each BIM component in the current BIM model according to a preset BIM component energy consumption simulation highly relevant parameter filtering model to achieve data dimensionality reduction (e.g., filtering out the geometric parameters and structural thermal parameters of BIM components of the envelope type; filtering out the spatial area, floor height, and volume of BIM components of the room / space type; filtering out the capacity, air volume, flow rate, efficiency, etc. of BIM components of the electromechanical equipment type). Then, the data can be input into the building energy consumption simulation tool to obtain the operational carbon simulation dataset of the current BIM model data. This processing method effectively reduces the system resource consumption of the server during energy consumption simulation.

[0067] After obtaining the operational carbon simulation dataset and the implicit carbon simulation dataset of the current BIM model data, if it is further determined that both the operational carbon simulation dataset and the implicit carbon simulation dataset meet the preset carbon emission accounting conditions for the entire building life cycle, it means that the building corresponding to the current BIM model data meets the carbon emission standards for green and environmentally friendly buildings, and the estimated carbon emission compliance label can be automatically added to the current building dataset. If it is determined that the operational carbon simulation dataset and the implicit carbon simulation dataset do not meet the preset building life-cycle carbon emission accounting conditions, it means that the building corresponding to the current BIM model data does not meet the carbon emission standards for green and environmentally friendly buildings. Based on the locally pre-built green building carbon emission optimization knowledge base, current carbon emission optimization suggestions corresponding to the current building dataset are obtained. For example, using the building region, building function type, number of floors, and the unmet accounting conditions as filtering conditions, candidate knowledge sets for the same scenario are screened in the green building carbon emission optimization knowledge base. Inapplicable cross-building type and cross-regional solutions are filtered out. Then, for high-carbon-contributing components (concrete, steel, curtain wall, etc.) in the BIM components, low-carbon alternative building materials, component structure optimization, and reduction design schemes for the same component are retrieved from the green building carbon emission optimization knowledge base. For high-energy-consuming systems (air conditioning, lighting, water supply and drainage) in the operational carbon identification simulation of BIM components, corresponding equipment, control strategies, building envelope insulation, natural ventilation and lighting, and other operational carbon reduction schemes are retrieved from the green building carbon emission optimization knowledge base.

[0068] As can be seen, the above method of acquiring both operational carbon simulation datasets and implicit carbon simulation datasets for the current BIM model data, compared to the existing technology that only acquires the corresponding operational carbon simulation datasets for the current BIM model data, can more accurately obtain the building's full life cycle carbon emission data, so as to determine whether the current BIM model data needs to be adjusted.

[0069] The second processing unit 130 is configured to, if it is determined that the current building data stage identifier is a construction stage identifier and the design stage classification evaluation result of the corresponding current building dataset is the same as the preset green building level expected result, obtain the construction stage collection dataset, and verify the construction stage collection dataset based on the preset construction consistency verification strategy to obtain the current construction consistency verification result.

[0070] In this embodiment, if the current building data stage identifier is determined to be a construction stage identifier, it indicates that the corresponding target building to be analyzed has started construction but has not yet been completed. At this time, the purchase orders, material arrival inspection reports, and equipment selection parameters of the building materials used in the target building to be analyzed can be compared with the BIM model data determined in the design stage of the target building to achieve consistency verification. If the data set collected during the construction stage passes the consistency verification strategy, it indicates that no equipment or materials have been changed during the construction stage of the target building to be analyzed. If the data set collected during the construction stage fails the consistency verification strategy, it indicates that equipment or materials may have been changed during the construction stage of the target building to be analyzed, and corresponding consistency warning information needs to be generated in a timely manner.

[0071] In one embodiment, taking the verification of construction consistency of electromechanical equipment in BIM model data as an example, the second processing unit 130 is specifically used for: Obtain the current list of equipment to be procured that belongs to the electromechanical equipment type from the current BIM model data corresponding to the data set collected during the construction phase; Obtain the list of currently inspected equipment belonging to the electromechanical equipment type from the data collected during the construction phase; If the construction consistency verification strategy determines that the current list of equipment to be verified is consistent with the current list of equipment to be procured, then the current construction consistency verification result for the electromechanical equipment type is a verification pass result.

[0072] In this embodiment, taking the construction consistency verification of mechanical and electrical equipment (MEP) equipment on a specific floor in the BIM model data as an example, the current list of equipment to be procured for that floor can be determined by filtering the MEP equipment in the BIM model data. Since each piece of MEP equipment is recorded or registered upon entering the construction site (e.g., through image acquisition or barcode scanning), the current list of equipment to be verified on that floor can also be obtained. If the construction consistency verification strategy determines that the current list of equipment to be verified is consistent with the current list of equipment to be procured (i.e., completely identical), it indicates that no replacement of MEP equipment occurred during the construction phase of the target building being analyzed. If the construction consistency verification strategy determines that the current list of equipment to be verified is inconsistent with the current list of equipment to be procured, it indicates that replacement of MEP equipment may occur during the construction phase of the target building being analyzed, requiring timely early warning. It is evident that by verifying the construction consistency of the target building during its construction phase, we can accurately detect whether it is constructed in accordance with the green building scheme determined in the design phase, and provide timely warnings when inconsistencies occur.

[0073] The third processing unit 140 is configured to, if it is determined that the current building data stage identifier is the completion and acceptance stage identifier and the corresponding current construction consistency verification result is a verification pass result, automatically generate the current completion and acceptance indicator set, obtain the current actual completion and acceptance indicator set based on the current completion and acceptance indicator set, and automatically compare and match it to obtain the current completion and acceptance inspection result.

[0074] In this embodiment, during the completion and acceptance phase of the target building to be analyzed, the green building full-cycle data intelligent processing platform can acquire the user's current actual completion and acceptance needs (such as completion and acceptance of building envelope, site and outdoor environment, electromechanical equipment system data, etc.) and generate a corresponding current completion and acceptance indicator set. The user then acquires the relevant indicators on-site to form the current actual completion and acceptance indicator set. Each current actual completion and acceptance indicator in the current actual completion and acceptance indicator set is compared and matched with the corresponding current completion and acceptance indicator in the current actual completion and acceptance indicator set. The result of the current completion and acceptance inspection is obtained by determining whether the two are consistent. For example, if the specific values ​​of each current actual completion and acceptance indicator in the current actual completion and acceptance indicator set are all within the normal acceptance range corresponding to the corresponding current completion and acceptance indicator in the current actual completion and acceptance indicator set, then the acceptance pass result is taken as the current completion and acceptance inspection result; otherwise, the acceptance fail result is taken as the current completion and acceptance inspection result.

[0075] In one embodiment, taking the final acceptance of electromechanical equipment in the target building to be analyzed as an example, the third processing unit 140 is specifically used for: Obtain the qualified range of the final acceptance energy efficiency ratio for each electromechanical equipment in the target building to be analyzed, and form a current final acceptance index set for the electromechanical equipment; Obtain the actual operating energy efficiency ratio of each electromechanical device in the target building to be analyzed, so as to form a set of current actual completion acceptance indicators for the electromechanical devices; If it is determined that each of the current actual completion acceptance indicators in the current actual completion acceptance indicator set for electromechanical equipment is within the normal indicator acceptance range corresponding to the current completion acceptance indicator in the current completion acceptance indicator set, then the acceptance pass result shall be taken as the current completion acceptance inspection result for the electromechanical equipment.

[0076] In this embodiment, taking the final acceptance of electromechanical equipment in the target building during the final acceptance phase as an example, the process begins by using a green building full-cycle data intelligent processing platform to obtain the acceptable range of energy efficiency ratios for each electromechanical device in the target building based on the user's current actual final acceptance requirements (e.g., final acceptance of all electromechanical equipment). This data is then used to form a current final acceptance indicator set for the electromechanical equipment. Next, after the electromechanical equipment in the target building has been running for a period of time (e.g., 24 hours, 48 ​​hours, etc.), the actual operating energy efficiency ratios for each electromechanical device are obtained, forming a current actual final acceptance indicator set for the electromechanical equipment. Only when each current actual final acceptance indicator in the current actual final acceptance indicator set for the electromechanical equipment is within the normal acceptance range corresponding to the current final acceptance indicator in the current final acceptance indicator set can the acceptance pass result be used as the current final acceptance inspection result for the electromechanical equipment; otherwise, the acceptance fail result is used as the current final acceptance inspection result for the electromechanical equipment.

[0077] It is evident that the implementation of this device enables intelligent processing of the entire lifecycle data corresponding to the design, construction, and completion acceptance stages of green buildings, improving the utilization rate of relevant data at each stage, avoiding data silos and providing data guidance for each stage of green building.

[0078] The aforementioned intelligent data processing device for the entire lifecycle of green buildings can be implemented as a computer program, which can, for example... Figure 7 It runs on the computer device shown.

[0079] Please see Figure 7 , Figure 7This is a schematic block diagram of a computer device provided in an embodiment of the present invention. This computer device integrates any of the intelligent data processing devices for the entire lifecycle of green buildings provided in this embodiment of the present invention.

[0080] See Figure 7 The computer device 400 includes a processor 402, a memory, and a network interface 405 connected via a system bus 401. The memory may include a storage medium 403 and internal memory 404.

[0081] The storage medium 403 may store an operating system 4031 and a computer program 4032. The computer program 4032 includes program instructions that, when executed, cause the processor 402 to perform a green building full-lifecycle data intelligent processing method.

[0082] The processor 402 provides computing and control capabilities to support the operation of the entire computer device.

[0083] The internal memory 404 provides an environment for the computer program 4032 in the storage medium 403 to run. When the computer program 4032 is executed by the processor 402, the processor 402 can execute the above-mentioned intelligent processing method for green building full-cycle data.

[0084] This network interface 405 is used for network communication with other devices. Those skilled in the art will understand that... Figure 7 The structure shown is merely a block diagram of a portion of the structure related to the present invention and does not constitute a limitation on the computer device to which the present invention is applied. A specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0085] The processor 402 is used to run the computer program 4032 stored in the memory to implement the intelligent data processing method for the entire life cycle of green buildings as described above.

[0086] It should be understood that, in this embodiment of the invention, the processor 402 may be a Central Processing Unit (CPU), or it may be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor.

[0087] It will be understood by those skilled in the art that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program includes program instructions and can be stored in a storage medium, which is a computer-readable storage medium. The program instructions are executed by at least one processor in the computer system to implement the process steps of the embodiments of the above methods.

[0088] Therefore, the present invention also provides a computer-readable storage medium. This computer-readable storage medium stores a computer program, wherein the computer program includes program instructions. When executed by a processor, the program instructions cause the processor to perform the intelligent data processing method for the entire lifecycle of green buildings as described above.

[0089] The storage medium can be any computer-readable storage medium that can store program code, such as a USB flash drive, external hard drive, read-only memory (ROM), magnetic disk, or optical disk.

[0090] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the components and steps of the various examples have been generally described in terms of functionality in the foregoing description. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0091] In the several embodiments provided by this invention, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative. For example, the division of each unit is merely a logical functional division, and there may be other division methods in actual implementation. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed.

[0092] The steps in the method of this invention can be adjusted, merged, or reduced in order according to actual needs. The units in the device of this invention can be merged, divided, or reduced according to actual needs. Furthermore, the functional units in the various embodiments of this invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0093] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, a terminal, or a network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention.

[0094] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in the present invention, and these modifications or substitutions should all be covered within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A method for intelligent processing of green building lifecycle data, characterized in that, include: In response to data processing instructions for green buildings, obtain the current building dataset and the corresponding current building data stage identifier; If the current building data stage identifier is determined to be a design stage identifier, then the current building dataset is obtained, and the design stage classification assessment result corresponding to the current building dataset is determined according to the preset green building classification assessment strategy; wherein, the design stage classification assessment result corresponds to either being the same as or different from the preset green building level expected result; if the design stage classification assessment result is determined to be the same as the preset green building level expected result, then the operational carbon simulation dataset and implicit carbon simulation dataset of the current BIM model data in the current building dataset are obtained based on the preset carbon simulation strategy, and corresponding labeling operations or suggested data output operations are performed based on the matching results of the operational carbon simulation dataset and the implicit carbon simulation dataset with the preset building life cycle carbon emission accounting conditions; If it is determined that the current building data stage identifier is a construction stage identifier and the design stage classification evaluation result of the corresponding current building dataset is the same as the preset green building level expected result, then the construction stage collection dataset is obtained, and the construction stage collection dataset is verified based on the preset construction consistency verification strategy to obtain the current construction consistency verification result. If the current building data stage identifier is determined to be the completion and acceptance stage identifier and the corresponding current construction consistency verification result is a verification pass result, then the current completion and acceptance indicator set is automatically generated, and the current actual completion and acceptance indicator set is obtained based on the current completion and acceptance indicator set and automatically compared and matched to obtain the current completion and acceptance inspection result.

2. The method according to claim 1, characterized in that, The step of determining the design phase classification assessment result corresponding to the current building dataset according to the preset green building classification assessment strategy includes: Obtain the current BIM model data from the current building dataset; Based on the BIM model parameter extraction sub-strategy in the green building grading assessment strategy, the amount of recyclable materials used, building materials used, window area, wall area, underground building area, land area, permeable pavement area and hard pavement area are obtained from the current building dataset for each BIM component. Based on the current building dataset, the recyclable material usage, building material usage, window area, wall area, underground building area, land area, permeable pavement area, and hard pavement area are obtained for each BIM component. The recyclable material utilization rate, window-to-wall ratio, underground space utilization rate, and permeable pavement rate corresponding to the current building dataset are then determined. Specifically, the recyclable material utilization rate is equal to the ratio between the sum of the recyclable material usage of each BIM component and the sum of the building material usage of each BIM component; the window-to-wall ratio of the current building dataset is equal to the ratio between the sum of the window areas of each BIM component and the sum of the wall areas of each BIM component; the underground space utilization rate is equal to the ratio between the sum of the underground building areas of each BIM component and the sum of the land areas of each BIM component; and the permeable pavement rate is equal to the ratio between the sum of the permeable pavement areas of each BIM component and the sum of the hard pavement areas of each BIM component. Based on the green building assessment sub-strategy in the green building grading assessment strategy, the index scores of the recyclable material utilization rate, the window-to-wall ratio, the underground space utilization rate, and the permeable pavement rate are obtained and summed to obtain the current assessment score; Obtain multiple preset design stage classification levels and corresponding score ranges, determine the target score range to which the current evaluation score belongs in the multiple score ranges, and use the design stage classification level corresponding to the target score range as the design stage classification evaluation result.

3. The method according to claim 2, characterized in that, After the steps of obtaining multiple preset design stage classification levels and corresponding score ranges, determining the target score range to which the current evaluation score belongs in the multiple score ranges, and using the design stage classification level corresponding to the target score range as the design stage classification evaluation result, the method further includes: If it is determined that the design phase grading assessment result is different from the preset green building grade expectation result, then the current optimization suggestion data and the corresponding current optimization suggestion construction difficulty dataset are obtained according to the locally pre-built green building optimization knowledge base, which are the design phase grading assessment result and the current BIM model data.

4. The method according to claim 2, characterized in that, The step of performing corresponding labeling operations or suggested data output operations based on the matching results of the operational carbon simulation dataset and the implicit carbon simulation dataset with the preset building life cycle carbon emission accounting conditions includes: If it is determined that both the operational carbon simulation dataset and the implicit carbon simulation dataset meet the preset building life cycle carbon emission accounting conditions, then the estimated carbon emission compliance label will be automatically added to the current building dataset. If it is determined that the operational carbon simulation dataset and the implicit carbon simulation dataset do not meet the preset building life cycle carbon emission accounting conditions, then the current carbon emission optimization suggestion data corresponding to the current building dataset is obtained based on the locally pre-built green building carbon emission optimization knowledge base.

5. The method according to claim 4, characterized in that, The implicit carbon simulation data is calculated and determined for each BIM component from the operational carbon simulation dataset and implicit carbon simulation dataset of the current BIM model data based on the preset carbon simulation strategy, including: Obtain the weight and material information of the BIM component; The carbon emission factors for current material production and current material transportation are obtained from the pre-built carbon emission factor library for material production and transportation, and the carbon emission data for the current material production stage is determined by multiplying the current material production carbon emission factor with the weight data corresponding to the weight information. The carbon emission data for the current material transportation stage is determined by multiplying the current material transportation carbon emission factor, the transportation distance of the current material from the supplier to the construction site, and the weight data corresponding to the weight information. The carbon emission reduction factor of the current material is obtained from the pre-built material recycling carbon reduction factor library and the carbon emission reduction factor of the current material is multiplied by the weight data corresponding to the weight information to determine the carbon emission reduction data of the current material recycling. The implicit carbon simulation data of the BIM component is determined by adding the carbon emission data of the current material production stage to the carbon emission data of the current material transportation stage and subtracting the carbon emission reduction data of the current material recycling stage.

6. The method according to claim 1, characterized in that, The method of verifying the data set collected during the construction phase based on a preset construction consistency verification strategy to obtain the current construction consistency verification result includes: Obtain the current list of equipment to be procured that belongs to the electromechanical equipment type from the current BIM model data corresponding to the data set collected during the construction phase; Obtain the list of currently inspected equipment belonging to the electromechanical equipment type from the data collected during the construction phase; If the construction consistency verification strategy determines that the current list of equipment to be verified is consistent with the current list of equipment to be procured, then the current construction consistency verification result for the electromechanical equipment type is a verification pass result.

7. The method according to claim 1, characterized in that, The step of obtaining the current actual completion and acceptance indicator set based on the current completion and acceptance indicator set and automatically comparing and matching it to obtain the current completion and acceptance inspection result includes: Obtain the qualified range of the final acceptance energy efficiency ratio for each electromechanical equipment in the target building to be analyzed, and form a current final acceptance index set for the electromechanical equipment; Obtain the actual operating energy efficiency ratio of each electromechanical device in the target building to be analyzed, so as to form a set of current actual completion acceptance indicators for the electromechanical devices; If it is determined that each of the current actual completion acceptance indicators in the current actual completion acceptance indicator set for electromechanical equipment is within the normal indicator acceptance range corresponding to the current completion acceptance indicator in the current completion acceptance indicator set, then the acceptance pass result shall be taken as the current completion acceptance inspection result for the electromechanical equipment.

8. A green building full-lifecycle data intelligent processing device, characterized in that, include: The stage identifier acquisition unit is used to obtain the current building dataset and the corresponding current building data stage identifier in response to the data processing instructions for green buildings; The first processing unit is configured to, if the current building data stage identifier is determined to be a design stage identifier, acquire the current building dataset and determine the design stage classification assessment result corresponding to the current building dataset according to a preset green building classification assessment strategy; wherein the design stage classification assessment result corresponds to either being the same as or different from the preset green building level expected result; if the design stage classification assessment result is determined to be the same as the preset green building level expected result, acquire the operational carbon simulation dataset and implicit carbon simulation dataset of the current BIM model data in the current building dataset based on a preset carbon simulation strategy, and perform corresponding labeling operations or suggested data output operations based on the matching results of the operational carbon simulation dataset and the implicit carbon simulation dataset with the preset building life cycle carbon emission accounting conditions; The second processing unit is configured to, if it is determined that the current building data stage identifier is a construction stage identifier and the design stage classification evaluation result of the corresponding current building dataset is the same as the preset green building level expected result, obtain the construction stage collection dataset, and verify the construction stage collection dataset based on the preset construction consistency verification strategy to obtain the current construction consistency verification result. The third processing unit is used to automatically generate the current completion and acceptance indicator set if it is determined that the current building data stage identifier is the completion and acceptance stage identifier and the corresponding current construction consistency verification result is a verification pass result, and obtain the current actual completion and acceptance indicator set according to the current completion and acceptance indicator set and automatically compare and match it to obtain the current completion and acceptance inspection result.

9. A computer device, characterized in that, The computer device includes a memory and a processor. The memory stores a computer program, and when the processor executes the computer program, it implements the intelligent data processing method for the entire life cycle of green buildings as described in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program, which includes program instructions that, when executed by a processor, can implement the intelligent processing method for green building full-cycle data as described in any one of claims 1-7.

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