Intelligent building engineering three-dimensional modeling system and method

Abstract

The application discloses a kind of intelligent building engineering three-dimensional modeling system and method, it is related to building engineering technical field, the method is by constructing building thermal effect prediction model, contains heat exchange efficiency algorithm model, humidity change algorithm model and air flow rate algorithm model, can extract real-time thermal gradient, temperature, humidity and air flow rate data from standard building data set, respectively calculate output heat exchange efficiency Ethe, humidity influence index Ehum and ventilation efficiency evaluation index Even.By comprehensive calculation obtained comprehensive thermal effect index Htotal, system can real-time evaluate the thermal effect state of building area, compared with the preset thermal effect threshold H1, generate maintenance prompt information.The method can quickly identify abnormal area of building thermal effect, for example, heat exchange is not good, moisture accumulation or low ventilation efficiency, and mark problem area through the visualization function of BIM system, provide clear maintenance adjustment suggestions for user.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of building engineering, in particular to an intelligent building engineering three-dimensional modeling system and method. BACKGROUND

[0002] With the rapid development of information technology, Internet of Things (IoT) and artificial intelligence, intelligent buildings have gradually become an important direction to improve building efficiency and use safety. In this context, three-dimensional modeling technology and Building Information Modeling (BIM) have become one of the core tools for intelligent building management. They can intuitively present the physical structure of the building and its internal components, and, combined with real-time sensor data, provide dynamic management throughout the building's life cycle. With the support of these technologies, the "intelligent building engineering three-dimensional modeling system" focuses on real-time analysis, predictive maintenance and optimization control of building thermal effects through modeling and data integration, providing a reliable solution to improve building performance, reduce energy consumption and ensure user comfort.

[0003] Although traditional building information management such as BIM systems have been widely used in building design, construction and maintenance, there are still many problems and deficiencies in actual operation. Traditional systems usually only provide storage of static models or historical data, but lack dynamic data and real-time monitoring functions, and cannot evaluate the thermal effects, humidity changes, ventilation status and other phenomena in the building operation process in real time. In addition, the maintenance and management of many buildings rely on manual inspection and experience-based judgment, which not only consumes time and effort, but also easily misses potential problems, leading to equipment failure, increased energy consumption and decreased user experience. At the same time, for thermal gradient changes, moisture accumulation, ventilation abnormalities and other phenomena in complex building structures, traditional management methods are difficult to quantify and analyze, and cannot generate effective maintenance decisions in a timely manner. SUMMARY

[0004] To overcome the deficiencies of the prior art, the present application provides an intelligent building engineering three-dimensional modeling system and method, which solves the problems mentioned in the background art.

[0005] To achieve the above purpose, the present application is implemented by the following technical solution:

[0006] S1, using a three-dimensional modeling tool to model a building in three dimensions, obtaining a three-dimensional model of the building, and importing the three-dimensional model of the building into a BIM system, while installing an intelligent sensor group inside the building to collect building data in real time, and integrating the building data with the three-dimensional model of the building to simulate the three-dimensional model of the building;

[0007] S2, real-time extraction of building data in the BIM system, preprocessing of the building data, obtaining of a standard building data set, construction of a cloud database, storage of the standard building data set in the cloud database through a wireless network, and

[0008] S3, a building thermal effect prediction model is constructed, the building thermal effect prediction model includes a heat exchange efficiency algorithm model, a humidity change algorithm model and an air flow rate algorithm model, and a standard building data set is extracted and input into the building thermal effect prediction model to calculate and output heat exchange efficiency Ethe, humidity influence index Ehum and ventilation efficiency evaluation index Even respectively;

[0009] S4, based on the obtained heat exchange efficiency Ethe, humidity influence index Ehum and ventilation efficiency evaluation index Even, a comprehensive thermal effect index Htotal is calculated and output, a thermal effect threshold H1 is set and compared with the comprehensive thermal effect index Htotal for preliminary evaluation, and maintenance prompt information is generated based on the evaluation result;

[0010] S5, if the preliminary comparison and evaluation generates maintenance prompt information, then based on the comprehensive thermal effect index Htotal, the overall thermal effect index Ztjk of the building is calculated, the overall thermal effect threshold H2 is preset and compared with the overall thermal effect index Ztjk of the building for secondary comparison and evaluation, the overall thermal effect state of the building is analyzed, and the maintenance execution time efficiency is prompted based on the evaluation result.

[0011] Preferably, the S1 includes S11 and S12;

[0012] S11, by using a three-dimensional modeling tool, a three-dimensional model of the building is obtained by three-dimensional modeling of each building component of the building according to the actual size, the building component includes walls, floors, pipes, facilities, air conditioning systems, elevators and doors and windows, the obtained building three-dimensional model is imported into a BIM system, and building historical data is imported into the BIM system, and each building component and building component attribute of the building is associated by the semantic function of the BIM system;

[0013] The building historical data includes equipment service life, maintenance records and construction documents;

[0014] The building component includes wall material properties, floor and load capacity, pipe and material and pressure rating;

[0015] S12, a plurality of sensor groups are installed in the actual building, the sensor groups are arranged in a grid format to obtain a sensor grid, each floor of the building is comprehensively covered, each floor is divided into different building areas, building data is collected in real time, the sensor groups are integrated and connected with the BIM system through wireless Internet of Things loT, the collected building data is transmitted to the BIM system, and the building three-dimensional model is virtually simulated through real-time building data;

[0016] The sensor group includes a temperature sensor, a humidity sensor, and an air flow meter;

[0017] The building data includes temperature T, humidity Sd, and air flow Ls.

[0018] Preferably, S2 includes S21 and S22;

[0019] S21, embedding the sensor grid in the building three-dimensional model in the BIM system, while receiving the building data in real time in the BIM system, and preprocessing the building data, the preprocessing including data cleaning, change degree calculation, timestamp unification, and normalization processing;

[0020] The data cleaning removes outliers and fills in missing values from the collected building data;

[0021] The change degree calculation calculates the output by the temperature difference and the physical distance of the adjacent temperature sensors, obtains the thermal gradient Rt, and the specific algorithm formula is: Where Rt(t) represents the thermal gradient at time t, T i+1 (t) represents the temperature collected by the i+1th building area sensor, T i (t) represents the temperature collected by the i building area, and △h represents the distance between adjacent temperature sensors.

[0022] The timestamp unification marks the timestamp of the building data collected in the same batch, and unifies the timestamps to the same time point;

[0023] The normalization processing performs Z-Score standardization processing method on the building data after data cleaning, and unifies the dimensions of all parameters in the building data;

[0024] The thermal gradient Rt and the building data are summarized to obtain the standard building data set;

[0025] The standard building data set includes the thermal gradient Rt(t) at time t, the temperature T(t) at time t, the humidity Sd(t) at time t, and the air flow Ls(t) at time t;

[0026] S22, constructing a cloud database and a wireless communication network, remotely connecting the BIM system and the cloud database, and storing the standard building data set into the cloud database.

[0027] Preferably, S3 includes S31, S32, and S33;

[0028] S31, by extracting the heat gradient Rt(t) at time t and the temperature T(t) at time t in the standard building data set, inputting into the heat exchange efficiency algorithm model, calculating and outputting the heat exchange efficiency Ethe, analyzing the heat insulation performance of the building and the trend of change over time;

[0029] The heat exchange efficiency Ethe is calculated and output by the following heat exchange efficiency algorithm model;

[0030]

[0031] Ethe = f (Rt(t), T(t)) i (t) represents the heat exchange efficiency of the building area i at time t, △T i (t) represents the temperature change of the building area i at time t, △t represents the time difference, Rt i (t) represents the heat gradient of the building area i at time t, hstart i represents the starting value of the building area i in the height of the building, hend i represents the end value of the building area i in the height of the building, and dh represents a small height increment.

[0032] Preferably, S32, by extracting the heat gradient Rt(t) at time t and the humidity Sd(t) at time t in the standard building data set, inputting into the humidity change algorithm model, calculating and outputting the humidity influence index Ehum, analyzing the trend of humidity change in the building;

[0033] The humidity influence index Ehum is calculated and output by the following humidity change algorithm model;

[0034]

[0035] Ehum = f (Rt(t), Sd(t)) i (t) represents the humidity influence index of the building area i at time t, △Sd i (t) represents the humidity change rate of the building area i at time t, Sd max represents the upper limit value of the humidity change rate in the building area.

[0036] Preferably, S33, by extracting the air flow rate Ls(t) at time t and the temperature T(t) at time t in the standard building data set, inputting into the air flow rate algorithm model, calculating and outputting the ventilation efficiency evaluation index Even, analyzing the air flow and structural stability in the building;

[0037] The ventilation efficiency evaluation index Even is calculated and output by the following air flow rate algorithm model;

[0038]

[0039] Even i (t) represents the ventilation efficiency evaluation index of the building area i at time t, Ls max represents the upper limit value of the air flow rate in the building area, Tref represents the reference temperature of the building, Ls i (t) represents the air flow rate of the building area i at time t.

[0040] Preferably, S4 comprises S41 and S42;

[0041] S41, by integrating the heat exchange efficiency Ethe, humidity influence index Ehum and ventilation efficiency evaluation index Even of the current building area i, outputting the comprehensive thermal effect index Htotal, and comprehensively analyzing the health condition of the current building area;

[0042] The comprehensive thermal effect index Htotal is calculated and output by the following algorithm formula;

[0043] Htotal i (t) = [(Ethe i (t)·a1)+(Ehum i (t)·a2)+(Even i (t)·a3)];

[0044] In the formula, Htotal i (t) represents the comprehensive thermal effect index of the building area i at time t, a1, a2 and a3 represent the preset weight values of the heat exchange efficiency Ethe, humidity influence index Ehum and ventilation efficiency evaluation index Even respectively, and a1+a2+a3=1, and the specific value is set by the user.

[0045] Preferably, S42, based on the thermal effect standard of different building areas, set the thermal effect threshold H1, and preliminarily compare and evaluate the thermal effect threshold H1 with the comprehensive thermal effect index Htotal i (t) of the building area i at time t, preliminarily analyze the health condition of the building area, and generate relevant prompt information based on the evaluation result, and the specific evaluation content is as follows;

[0046] When the comprehensive thermal effect index Htotal i (t) of the building area i at time t is greater than the thermal effect threshold H1, it indicates that the internal thermal effect of the current building area i is abnormal, at this time the current building area i on the sensor grid in the BIM system is automatically marked as red, and prompt information is generated through the BIM system for the user to maintain and adjust;

[0047] When the comprehensive thermal effect index Htotal of the building area i at time t i (t)≤thermal effect threshold H1, indicating that the internal thermal effect of the current building area i is normal, and no adjustment is needed to continue monitoring.

[0048] Preferably, S5 includes S51 and S52;

[0049] S51, when a preliminary comparative evaluation is generated to generate maintenance prompt information, then based on the comprehensive thermal effect index Htotal of all building areas in the building, the overall thermal effect index Ztjk of the building is calculated by summation, and the thermal load condition inside the building is comprehensively analyzed;

[0050] The overall thermal effect index Ztjk is calculated and output by the following algorithm formula;

[0051]

[0052] In the formula, n represents the total number of building areas;

[0053] S52, set the overall thermal effect threshold H2 based on the thermal energy standard of the overall building, and then compare and evaluate the overall thermal effect threshold H2 and the overall thermal effect index Ztjk again to analyze the overall thermal effect state of the building, and based on the evaluation result, analyze the timeliness of maintenance, and the specific evaluation content is as follows;

[0054] When the overall thermal effect index Ztjk is greater than the overall thermal effect threshold H2, it indicates that the overall thermal effect of the building is abnormal, and the current building area is marked as a first abnormal level, and the BIM system prompts to maintain within three days;

[0055] When the overall thermal effect index Ztjk is greater than or equal to twice the overall thermal effect threshold H2, it indicates that the overall thermal effect of the building is abnormal, and the current building area is marked as a second abnormal level, and the BIM system prompts to maintain immediately;

[0056] When the overall thermal effect index Ztjk is less than the overall thermal effect threshold H2, it indicates that the overall thermal effect of the building is normal, and for the abnormal building area, the BIM system prompts to maintain the current building area within seven days.

[0057] An intelligent building engineering three-dimensional modeling system, comprising a three-dimensional modeling acquisition module, a data processing module, a thermal effect analysis module, a building area thermal effect analysis module, and a maintenance timeliness analysis module;

[0058] The three-dimensional modeling acquisition module acquires a three-dimensional model of the building by using a three-dimensional modeling tool to model the building in three dimensions, imports the three-dimensional model of the building into a BIM system, simultaneously installs an intelligent sensor group in the building, acquires building data in real time, and integrates the building data with the three-dimensional model of the building to simulate the three-dimensional model of the building;

[0059] The data processing module extracts building data in real time in the BIM system, pre-processes the building data to obtain a standard building data set, simultaneously constructs a cloud database, and stores the standard building data set in the cloud database through a wireless network;

[0060] The thermal effect analysis module constructs a building thermal effect prediction model, which includes a heat exchange efficiency algorithm model, a humidity change algorithm model and an air flow rate algorithm model, extracts the standard building data set, inputs the standard building data set into the building thermal effect prediction model, and respectively calculates a heat exchange efficiency Ethe, a humidity influence index Ehum and a ventilation efficiency evaluation index Even.

[0061] The building area thermal effect analysis module performs comprehensive calculation on the basis of the heat exchange efficiency Ethe, the humidity influence index Ehum and the ventilation efficiency evaluation index Even to output a comprehensive thermal effect index Htotal, preliminarily compares and evaluates the thermal effect threshold H1 and the comprehensive thermal effect index Htotal, and generates maintenance prompt information based on the evaluation result;

[0062] The maintenance time effect analysis module, after generating the maintenance prompt information through the preliminary comparison and evaluation, calculates the overall thermal effect index Ztjk of the building based on the comprehensive thermal effect index Htotal, performs secondary comparison and evaluation of the overall thermal effect threshold H2 and the overall thermal effect index Ztjk of the building, analyzes the overall thermal effect state of the building, and prompts the maintenance execution time effect based on the evaluation result.

[0063] The present application provides a kind of intelligent building engineering three-dimensional modeling system and method.There is following beneficial effect:

[0064] (1) the method by using three-dimensional modeling tool and BIM system, the every component of building, such as wall, floor, pipeline, facility, air conditioning system, elevator, door and window, is accurately modeled, and its attribute, such as material, load capacity, pressure grade etc., is associated, and the digital model of building is constructed.Meanwhile, through sensor grid, temperature, humidity, air flow rate and other dynamic data are collected in real time, integrated with three-dimensional model, and the overall monitoring and simulation of building state are realized.This method integrates static historical data and dynamic sensor data, so that building information is visualized in BIM system and dynamically updated, and provides efficient and comprehensive data basis for building management.

[0065] (2) This method constructs a building thermal effect prediction model, which includes a heat exchange efficiency algorithm model, a humidity change algorithm model, and an air flow rate algorithm model. It can extract real-time thermal gradient, temperature, humidity, and air flow rate data from a standard building data set, and calculate the output heat exchange efficiency Ethe, humidity impact index Ehum, and ventilation efficiency evaluation index Even, respectively. Through the comprehensive thermal effect index Htotal obtained through comprehensive calculation, the system can evaluate the thermal effect status of the building area in real time, compare it with the preset thermal effect threshold H1, and generate maintenance prompt information. This method can quickly identify abnormal areas of building thermal effects, such as poor heat exchange, moisture accumulation, or low ventilation efficiency, and mark the problem areas through the visualization function of the BIM system, providing users with clear maintenance adjustment suggestions.

[0066] (3) This method calculates the overall thermal effect index Ztjk based on the comprehensive thermal effect index Htotal and compares it with the overall thermal effect threshold H2. The system can comprehensively analyze the thermal load and overall health status of the building. For building areas with abnormal thermal effects, the system generates maintenance prompts based on the abnormality level. Level 1 abnormality requires immediate maintenance, minor abnormalities require maintenance within three days, and normal conditions do not require adjustment but are continuously monitored. This hierarchical management maintenance strategy not only improves the accuracy and timeliness of building maintenance work and avoids excessive maintenance, but also optimizes resource allocation and reduces the energy consumption and failure rate of equipment in long-term operation, thereby effectively extending the service life of the building and improving user comfort. BRIEF DESCRIPTION OF THE DRAWINGS

[0067] Figure 1 This is a schematic diagram of the steps of a three-dimensional modeling method for intelligent building engineering according to the present invention;

[0068] Figure 2 The figure is a flow chart of an intelligent building engineering 3D modeling system according to the present invention. DETAILED DESCRIPTION

[0069] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0070] Example 1

[0071] See also Figure 1 The present invention provides a method for intelligent building engineering three-dimensional modeling. To achieve the above purpose, the present invention is implemented through the following technical solutions: comprising the following steps:

[0072] S1, using a three-dimensional modeling tool to model a building in three dimensions, obtaining a three-dimensional model of the building, importing the three-dimensional model of the building into a BIM system, simultaneously installing an intelligent sensor group in the building, collecting building data in real time, integrating the building data with the three-dimensional model of the building, and simulating the three-dimensional model of the building;

[0073] S2, extracting building data in real time in the BIM system, preprocessing the building data, obtaining a standard building data set, simultaneously constructing a cloud database, storing the standard building data set in the cloud database through a wireless network, and constructing a cloud database;

[0074] S3, constructing a building thermal effect prediction model, the building thermal effect prediction model including a heat exchange efficiency algorithm model, a humidity change algorithm model, and an air flow rate algorithm model, extracting the standard building data set, inputting the standard building data set into the building thermal effect prediction model, and calculating the heat exchange efficiency Ethe, the humidity influence index Ehum, and the ventilation efficiency evaluation index Even, respectively;

[0075] S4, based on the obtained heat exchange efficiency Ethe, humidity influence index Ehum, and ventilation efficiency evaluation index Even, performing comprehensive calculation to output a comprehensive thermal effect index Htotal, setting a thermal effect threshold H1, and preliminarily comparing and evaluating the comprehensive thermal effect index Htotal, and generating maintenance prompt information based on the evaluation result;

[0076] S5, if the preliminary comparison and evaluation generates maintenance prompt information, then based on the comprehensive thermal effect index Htotal, calculating the overall thermal effect index Ztjk of the building, pre-setting the overall thermal effect threshold H2, and performing secondary comparison and evaluation with the overall thermal effect index Ztjk of the building, analyzing the overall thermal effect state of the building, and based on the evaluation result, prompting the maintenance execution time efficiency.

[0077] In this embodiment, the method builds a digital three-dimensional model of the building by using a three-dimensional modeling tool to accurately model each component of the building, combining a BIM system, and integrating historical data with real-time sensor data to comprehensively cover the dynamic changes of the thermal effect inside the building, while realizing simulation of the building state. Secondly, the sensor grid data is extracted in real time in the BIM system, and after data cleaning, change calculation, timestamp unification and normalization processing, a standardized building data set is constructed, and stored in the cloud database, providing a standardized and real-time data basis for building thermal effect analysis. Based on the standard building data set, the system builds a building thermal effect prediction model, including a heat exchange efficiency algorithm model, a humidity change algorithm model and an air flow rate algorithm model, which respectively calculate and output heat exchange efficiency Ethe, humidity influence index Ehum and ventilation efficiency evaluation index Even, which can accurately analyze the building thermal insulation performance, humidity change trend and ventilation state. Then, by comprehensively calculating the thermal effect index Htotal and preliminarily comparing and evaluating it with the thermal effect threshold H1, the system generates specific maintenance prompt information; on this basis, the overall thermal effect index Ztjk of the building is further calculated, and the second comparison and evaluation with the overall thermal effect threshold H2 is performed, generating a graded maintenance time prompt, such as immediate maintenance, maintenance within three days or maintenance within seven days, realizing the refinement and dynamic of building maintenance management. The method realizes the transformation of building information from static management to dynamic analysis through accurate modeling and dynamic data monitoring.

[0078] Embodiment 2

[0079] Specifically, S1 includes S11 and S12;

[0080] S11, by using a three-dimensional modeling tool, three-dimensional modeling is performed on each building component of the building according to the actual size to obtain a three-dimensional model of the building, the building components including walls, floors, pipelines, facilities, air conditioning systems, elevators and doors and windows, the obtained three-dimensional model of the building is imported into the BIM system, and the building historical data is also imported into the BIM system, and through the semantic function of the BIM system, each building component of the building and the building component attributes are associated;

[0081] The building historical data includes equipment service life, maintenance records and construction documents;

[0082] The building components include wall material attributes, floor and load capacity, pipeline and material and pressure grade;

[0083] S12, install a plurality of sensor groups in the actual building, the sensor groups are arranged in a grid format, obtain a sensor grid, comprehensively cover each floor of the building, and divide each floor into different building areas, collect building data in real time, integrate and connect the sensor groups with the BIM system through wireless Internet of Things (loT), transmit the collected building data to the BIM system, and virtually simulate the building three-dimensional model through real-time building data;

[0084] The sensor group includes a temperature sensor, a humidity sensor, and an air flow meter;

[0085] The building data includes temperature T, humidity Sd, and air flow Ls.

[0086] In this embodiment, the method generates a building three-dimensional model by precisely modeling each component of the building according to the actual size using a three-dimensional modeling tool, and imports the model into the BIM system. At the same time, historical data of the building is imported, and the building components in the model are associated with their attributes by using the semantic function of the BIM system to build a comprehensive and dynamic semantic digital building model. In addition, by arranging sensor groups in a grid inside the building, comprehensive coverage of each floor and area of the building is achieved, each floor is divided into several building areas, and key building data is collected in real time. The sensor group is seamlessly integrated with the BIM system through wireless Internet of Things (loT), so that the collected data can be transmitted in real time and dynamically updated in the BIM system, further enriching the dynamic attributes of the digital building model. This method not only builds a precise three-dimensional building model, but also provides a reliable basis for monitoring and management of the building operation state through real-time data collection and dynamic updating. Through the combination of historical data and real-time sensor data, the completeness and dynamics of building information management are significantly improved.

[0087] Embodiment 3

[0088] Specifically, S2 includes S21 and S22;

[0089] S21, embed the sensor grid in the building three-dimensional model in the BIM system, and receive building data in real time in the BIM system, and preprocess the building data, which includes data cleaning, change degree calculation, timestamp unification, and normalization processing;

[0090] Data cleaning removes outliers and fills in missing values in the collected building data;

[0091] The change degree calculation calculates the temperature difference and physical distance of adjacent temperature sensors in real time to output a thermal gradient Rt, and the specific algorithm formula is: Wherein, Rt(t) represents the thermal gradient at time t, T i+1(t) represents the temperature collected by the i+1th building area sensor, T i (t) represents the temperature collected by the i+1th building area sensor, T

[0092] The timestamp is uniformly marked on the building data collected in the same batch, and the timestamps are unified to the same time point.

[0093] The normalization processing is performed on the building data after data cleaning by the Z-Score standardization processing method, and the dimensions of all parameters in the building data are unified.

[0094] The heat gradient Rt is collected and the standard building data set is obtained by summarizing the building data;

[0095] The standard building data set includes the heat gradient Rt(t) at time t, the temperature T(t) at time t, the humidity Sd(t) at time t, and the air flow rate Ls(t) at time t.

[0096] S22, constructing a cloud database and a wireless communication network, remotely connecting the BIM system and the cloud database, and storing the standard building data set into the cloud database.

[0097] In this embodiment, the method embeds the sensor grid into the building three-dimensional model in the BIM system, receives the collected building data in real time through the sensor group, and comprehensively preprocesses the data. The preprocessing includes: removing outliers and filling missing values through data cleaning to ensure the integrity and accuracy of the data; obtaining the heat gradient Rt of the adjacent area to provide a basis for analyzing the dynamic changes of the building thermal environment; the timestamp uniformly marks the same batch of data to ensure the synchronization of multi-point data; the normalization processing unifies the dimensions of different parameters by the Z-Score standardization method, and eliminates the dimension difference of the data. Finally, the standard building data set is summarized. On this basis, the standard building data set is remotely stored into the cloud database by constructing a cloud database and using a wireless communication network. This step realizes the seamless connection of the BIM system and the cloud database, and ensures that the data can be safely and quickly transmitted and stored.

[0098] Embodiment 4

[0099] Specifically, S3 includes S31, S32 and S33.

[0100] S31, by extracting the heat gradient Rt(t) at time t and the temperature T(t) at time t in the standard building data set, inputting into the heat exchange efficiency algorithm model, calculating the output heat exchange efficiency Ethe, analyzing the heat insulation performance of the building and the change trend with time, and identifying the area with poor heat exchange;

[0101] The heat exchange efficiency Ethe is calculated and output by the following heat exchange efficiency algorithm model;

[0102]

[0103] Where, Ethe i (t) represents the heat exchange efficiency of building area i at time t, ΔT i (t) represents the temperature change of building area i at time t, △t represents the time difference, Rt i (t) represents the thermal gradient of building area i at time t, hstart i Indicates the starting value of building area i at the height of the building, hend i represents the end value of building area i at the height occupied by the building, and dh represents a small height increment.

[0104] S32. Extract the thermal gradient Rt(t) at time t and the humidity Sd(t) at time t from the standard building dataset, input them into the humidity change algorithm model, calculate and output the humidity impact index Ehum, analyze the trend of humidity changes inside the building, and assess the moisture accumulation areas and possible mold problems in the building;

[0105] The humidity impact index Ehum is calculated and output by the following humidity change algorithm model;

[0106]

[0107] Where, Ehum i (t) represents the humidity impact index of building area i at time t, △Sd i (t) represents the humidity change rate of building area i at time t, Sd max Indicates the upper limit of the rate of change of humidity in the building area.

[0108] S33. Extracting the air flow velocity Ls(t) and the temperature T(t) at time t from the standard building dataset and inputting them into the air flow velocity algorithm model to calculate and output the ventilation efficiency evaluation index Even, thereby analyzing the air flow and structural stability inside the building.

[0109] The ventilation efficiency evaluation index Even is calculated and output by the following air flow rate algorithm model;

[0110]

[0111] In the formula, Even i (t) represents the ventilation efficiency evaluation index of building area i at time t, Ls maxrepresents the upper limit value of the air flow rate in the building area, Tref represents the reference temperature of the building, which is usually the standard temperature designed for the building, Ls i (t) represents the air flow rate of the building area i at time t.

[0112] In this embodiment, by extracting the heat gradient Rt and the temperature T in the standard building data set, the heat exchange efficiency Ethe is calculated by inputting the heat exchange efficiency algorithm model, the heat insulation performance of different areas of the building is quantitatively evaluated, and the change trend of the heat exchange efficiency with time is analyzed to quickly identify the areas with poor heat exchange. Subsequently, by the humidity change algorithm model, the heat gradient Rt and the humidity Sd in the building data set are extracted, the humidity influence index Ehum is calculated, the change trend of the humidity is accurately analyzed, the area of the building where the moisture accumulates is evaluated, and the possible mold problem or material corrosion risk is predicted. Finally, by the air flow rate algorithm model, the air flow rate Ls and the temperature T(t) in the building data set are extracted, the ventilation efficiency evaluation index Even is calculated, the air flow efficiency is quantitatively evaluated, the ventilation performance and structural stability inside the building are analyzed, and the basis for optimizing ventilation is provided. The method comprehensively and deeply analyzes the heat exchange, moisture accumulation and ventilation state of the building by constructing a multi-dimensional heat effect model. The output heat exchange efficiency Ethe, humidity influence index Ehum and ventilation efficiency evaluation index Even provide a scientific basis for identifying potential problem areas, and effectively improve the intelligent level of building thermal environment management. By accurately predicting the change trend of the heat effect, the method realizes the early discovery and active warning of the building environment problems, and further optimizes the building management efficiency, equipment operation performance and the safety and comfort of the use environment.

[0113] Embodiment 5

[0114] Specifically, S4 includes S41 and S42.

[0115] S41, by comprehensively calculating the heat exchange efficiency Ethe, the humidity influence index Ehum and the ventilation efficiency evaluation index Even of the current building area i, the comprehensive heat effect index Htotal is output, and the health condition of the current building area is comprehensively analyzed.

[0116] The comprehensive heat effect index Htotal is calculated and output by the following algorithm formula;

[0117] Htotal i (t)=[(Ethe i (t)·a1)+(Ehum i (t)·a2)+(Even i (t)·a3)];

[0118] In the formula, Htotal i(t) represents the comprehensive thermal effect index of the building area i at time t, a1, a2 and a3 represent preset weight values of the heat exchange efficiency Ethe, the humidity influence index Ehum and the ventilation efficiency evaluation index Even respectively, and a1+a2+a3=1, and the specific values are set by the user.

[0119] S42, set the thermal effect threshold H1 based on the thermal effect standards of different building areas, and preliminarily compare and evaluate the thermal effect threshold H1 and the comprehensive thermal effect index Htotal i (t) of the building area i at time t, preliminarily analyze the health of the building area, and generate relevant prompt information based on the evaluation result, and the specific evaluation content is as follows:

[0120] When the comprehensive thermal effect index Htotal i (t) of the building area i at time t is greater than the thermal effect threshold H1, it indicates that the internal thermal effect of the current building area i is abnormal, at this time the current building area i on the sensor grid in the BIM system is automatically marked as red, and prompt information is generated through the BIM system to guide the user to maintain and adjust, prompting the current building area to start cooling or ventilation measures, such as increasing the number of air conditioners or rebuilding windows, etc.

[0121] When the comprehensive thermal effect index Htotal i (t) of the building area i at time t is less than or equal to the thermal effect threshold H1, it indicates that the internal thermal effect of the current building area i is normal, and no adjustment is needed to continue monitoring.

[0122] In this embodiment, the method realizes the comprehensive analysis of the health status of the current building area by comprehensively calculating the heat exchange efficiency Ethe, the humidity influence index Ehum and the ventilation efficiency evaluation index Even of the building area, and outputting the comprehensive thermal effect index Htotal, and provides a quantitative health evaluation result. Subsequently, by setting the thermal effect threshold H1 of the building area, the thermal effect threshold H1 is preliminarily compared and evaluated with the comprehensive thermal effect index Htotal, and the abnormal condition of the building area is quickly identified. When the comprehensive thermal effect index Htotal i (t) of the building area i at time t is greater than the thermal effect threshold H1, the system judges that the internal thermal effect of the area is abnormal, and is marked as red on the sensor grid in the BIM system, and generates maintenance prompt information to guide the user to take adjustment operations such as increasing the number of air conditioners, optimizing ventilation measures or rebuilding windows; when the comprehensive thermal effect index Htotal i(t) When the thermal effect is less than the threshold value H1, the system determines that the thermal effect in the region is normal, and no adjustment is needed. The method effectively improves the monitoring efficiency and problem identification ability of the building thermal environment through comprehensive calculation and preliminary evaluation. The system can quickly locate abnormal areas and provide intuitive visual markers, combined with maintenance prompt information, to provide scientific decision support for users. Ultimately, the method optimizes the intelligent level of building operation and management, reduces equipment damage and energy waste caused by thermal effect abnormalities, improves the comfort and safety of the building internal environment, and realizes precise resource allocation and maintenance planning.

[0123] Embodiment 6

[0124] Specifically, S5 includes S51 and S52.

[0125] S51, when the preliminary comparative evaluation generates a maintenance prompt information, the overall thermal effect index Ztjk of the building is calculated based on the comprehensive thermal effect index Htotal of all building regions in the building, and the thermal load situation in the building is analyzed comprehensively.

[0126] The overall thermal effect index Ztjk is calculated and output by the following algorithm formula:

[0127]

[0128] In the formula, n represents the total number of building regions, that is, the total number of grids divided by the sensor group.

[0129] S52, the overall thermal effect threshold H2 is set based on the thermal energy standard of the building, and the overall thermal effect threshold H2 is compared with the overall thermal effect index Ztjk for secondary comparative evaluation to analyze the overall thermal effect state of the building. Based on the evaluation result, the timeliness of analysis and maintenance is analyzed, and the specific evaluation content is as follows.

[0130] When the overall thermal effect index Ztjk is greater than the overall thermal effect threshold H2, it indicates that the overall thermal effect of the building is abnormal, and at this time, the first abnormal level is marked, and the BIM system prompts to maintain the current building region within three days.

[0131] When the overall thermal effect index Ztjk is greater than twice the overall thermal effect threshold H2, it indicates that the overall thermal effect of the building is abnormal, and at this time, the second abnormal level is marked, and the BIM system prompts to immediately maintain the current building region.

[0132] When the overall thermal effect index Ztjk is less than the overall thermal effect threshold H2, it indicates that the overall thermal effect of the building is normal, and at this time, the BIM system prompts to maintain the current building region within seven days for the abnormal building region.

[0133] In this embodiment, the method sums up the comprehensive thermal effect index Htotal of all areas of the building based on the preliminary comparative evaluation of the maintenance prompt information, and outputs the overall thermal effect index Ztjk of the building. By averaging the thermal effect indexes of all areas, the overall thermal load of the building is quantitatively evaluated, and a global analysis of the thermal environment state of the building is formed. Then, based on the overall thermal energy standard of the building, the overall thermal effect threshold H2 is set, and a secondary comparative evaluation is performed between the overall thermal effect index Ztjk and the overall thermal effect threshold H2 to determine the overall thermal effect state of the building and generate a graded maintenance time prompt. When the overall thermal effect index Ztjk is greater than the overall thermal effect threshold H2, the system determines that there is a major abnormality in the overall thermal effect of the building, and marks it as a first abnormality level, prompting the user to perform emergency maintenance within three days; when the overall thermal effect index Ztjk is greater than or equal to the overall thermal effect threshold H2, it is prompted to immediately maintain the current building area; when the overall thermal effect index Ztjk is less than the overall thermal effect threshold H2, it is determined that the overall thermal effect of the building is normal, and only the abnormal area identified previously is prompted to complete maintenance within seven days. All evaluation results and maintenance plans are visualized and prompted through the BIM system to ensure the scientificity and operability of the maintenance work. This method improves the accuracy and timeliness of building maintenance through global and regional thermal effect evaluation. The introduction of the overall thermal effect index Ztjk provides a quantitative basis for comprehensive control of the building operation state; the graded management strategy optimizes resource allocation and maintenance efficiency, avoiding excessive repair and delayed problem handling.

[0134] Embodiment 7

[0135] Referring to Figure 1 and Figure 2 An intelligent building engineering three-dimensional modeling system, comprising a three-dimensional modeling acquisition module, a data processing module, a thermal effect analysis module, a building area thermal effect analysis module, and a maintenance time analysis module.

[0136] The three-dimensional modeling acquisition module acquires a three-dimensional model of the building by using a three-dimensional modeling tool to model the building in three dimensions, imports the three-dimensional model of the building into a BIM system, simultaneously installs an intelligent sensor group inside the building, collects building data in real time, integrates the building data with the three-dimensional model of the building, and simulates the three-dimensional model of the building.

[0137] The data processing module extracts building data in real time in the BIM system, pre-processes the building data, acquires a standard building data set, constructs a cloud database, and stores the standard building data set in the cloud database through a wireless network.

[0138] The heat effect analysis module constructs a building heat effect prediction model, the building heat effect prediction model includes heat exchange efficiency algorithm model, humidity change algorithm model and air flow rate algorithm model, and extracts a standard building data set, inputs the building heat effect prediction model, and respectively calculates and outputs heat exchange efficiency Ethe, humidity influence index Ehum and ventilation efficiency evaluation index Even;

[0139] The building area heat effect analysis module performs comprehensive calculation and outputs a comprehensive heat effect index Htotal based on the obtained heat exchange efficiency Ethe, humidity influence index Ehum and ventilation efficiency evaluation index Even, preliminarily compares and evaluates the comprehensive heat effect index Htotal with a heat effect threshold H1, and generates maintenance prompt information based on the evaluation result;

[0140] The maintenance time effect analysis module, after generating the maintenance prompt information through the preliminary comparison and evaluation, calculates a building overall heat effect index Ztjk based on the comprehensive heat effect index Htotal, performs secondary comparison and evaluation of the building overall heat effect index Ztjk with a preset overall heat effect threshold H2, analyzes the overall heat effect state of the building, and prompts the maintenance execution time effect based on the evaluation result.

[0141] Although the embodiments of the present application have been shown and described, it will be understood by those of ordinary skill in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the present application.

Claims

1. A method for intelligent construction engineering 3D modeling, characterized in that: The method comprises the following steps: S1, using a three-dimensional modeling tool to model a building in three dimensions, obtaining a three-dimensional model of the building, importing the three-dimensional model of the building into a BIM system, simultaneously installing an intelligent sensor group in the building, collecting building data in real time, integrating the building data with the three-dimensional model of the building, and simulating the three-dimensional model of the building; S2, extracting building data in real time in the BIM system, preprocessing the building data, obtaining a standard building data set, simultaneously constructing a cloud database, and storing the standard building data set in the cloud database through a wireless network; S3, constructing a building thermal effect prediction model, the building thermal effect prediction model comprising a heat exchange efficiency algorithm model, a humidity change algorithm model and an air flow rate algorithm model, and extracting the standard building data set and inputting the standard building data set into the building thermal effect prediction model for separate calculation to output heat exchange efficiency Ethe, humidity influence index Ehum and ventilation efficiency evaluation index Even; The S3 comprises S31, S32 and S33; S31, inputting the thermal gradient Rt(t) at time t and the temperature T(t) at time t in the standard building data set into the heat exchange efficiency algorithm model to calculate and output the heat exchange efficiency Ethe, and analyze the thermal insulation performance of the building and the change trend over time; The heat exchange efficiency Ethe is calculated and output by the following heat exchange efficiency algorithm model: where Ethe i (t) represents the heat exchange efficiency of the building region i at time t, ΔT i (t) represents the temperature change amount of the building region i at time t, Δt represents the time difference, Rt i (t) represents the heat gradient of the building region i at time t, hstart i represents the starting value of the building region i at the height of the building, hend i represents the ending value of the building region i at the height of the building, dh represents a small height increment; S32, inputting the thermal gradient Rt(t) at time t and the humidity Sd(t) at time t in the standard building data set into the humidity change algorithm model to calculate and output the humidity influence index Ehum, and analyze the trend of humidity change in the building; The humidity influence index Ehum is calculated and output by the following humidity change algorithm model: where Ehum i (t) represents the time humidity influence index of the building area i at time t, ΔSd i (t) represents the humidity change rate of the building area i at time t, Sd max represents the upper limit value of the humidity change rate in the building area; S33, inputting the air flow rate Ls(t) at time t and the temperature T(t) at time t in the standard building data set into the air flow rate algorithm model to calculate and output the ventilation efficiency evaluation index Even, and analyze the air flow in the building and the structural stability; The ventilation efficiency evaluation index Even is calculated and output by the following air flow rate algorithm model: wherein Even i (t) denotes the ventilation efficiency evaluation index of the building area i at the time t, Ls max denotes the upper limit value of the air flow rate in the building area, Tref denotes the reference temperature of the building, Ls i (t) denotes the air flow rate of the building area i at the time t. S4, based on the obtained heat exchange efficiency Ethe, humidity influence index Ehum and ventilation efficiency evaluation index Even, comprehensively calculating and outputting a comprehensive thermal effect index Htotal, preliminarily comparing and evaluating the thermal effect threshold H1 with the comprehensive thermal effect index Htotal, and generating maintenance prompt information based on the evaluation result; S5, if the maintenance prompt information is generated after the preliminary comparison and evaluation, based on the comprehensive thermal effect index Htotal, calculating the overall thermal effect index Ztjk of the building, and presetting the overall thermal effect threshold H2 to perform secondary comparison and evaluation with the overall thermal effect index Ztjk of the building, analyzing the overall thermal effect state of the building, and prompting the maintenance execution time efficiency based on the evaluation result.

2. The intelligent building engineering three-dimensional modeling method according to claim 1, characterized in that: The S1 comprises S11 and S12; S11, by using a three-dimensional modeling tool, three-dimensional modeling is performed on each building component of the building according to the actual size, and a three-dimensional model of the building is obtained, the building component includes walls, floors, pipes, facilities, air conditioning systems, elevators and doors and windows, the obtained three-dimensional model of the building is imported into the BIM system, and the building historical data is also imported into the BIM system, and each building component and the building component attribute of the building are associated through the semantic function of the BIM system; The building historical data includes equipment service life, maintenance records and construction documents; The building component includes wall material properties, floor and load capacity, pipe and material, and pressure rating; S12, a plurality of sensor groups are installed in the actual building, the sensor groups are arranged in a grid format, a sensor grid is obtained, each floor of the building is comprehensively covered, and each floor is divided into different building areas, building data is collected in real time, the sensor groups are integrated and connected with the BIM system through wireless Internet of Things loT, the collected building data is transmitted to the BIM system, and the three-dimensional model of the building is virtually simulated through real-time building data; The sensor group includes a temperature sensor, a humidity sensor and an air flow meter; The building data includes temperature T, humidity Sd and air flow Ls.

3. The intelligent building engineering three-dimensional modeling method according to claim 2, characterized in that: The S2 includes S21 and S22; S21, the sensor grid is embedded in the three-dimensional model of the building in the BIM system, and the building data is received in real time in the BIM system, and the building data is preprocessed, the preprocessing includes data cleaning, change degree calculation, timestamp unification and normalization processing; The data cleaning removes outliers and fills missing values from the collected building data; The change degree calculation is calculated by the temperature difference of the real-time acquisition of the adjacent temperature sensor and the physical distance, obtains the thermal gradient Rt, and the specific algorithm formula is: Wherein, Rt(t) represents the thermal gradient at t moment, T i+1 (t) represents the temperature collected by the i+1 building area sensor, T i (t) represents the temperature collected by the i building area, and △h represents the distance between adjacent temperature sensors. The timestamp unification marks the timestamp of the building data collected in the same batch, and unifies the timestamp to the same time point; The normalization processing unifies the dimensions of all parameters in the building data through Z-Score standardization processing method of the building data after data cleaning; The heat gradient Rt is summarized with the building data to obtain a standard building data set; The standard building data set includes heat gradient Rt(t) at time t, temperature T(t) at time t, humidity Sd(t) at time t and air flow Ls(t) at time t; S22, a cloud database and a wireless communication network are constructed, the BIM system is remotely connected with the cloud database, and the standard building data set is stored in the cloud database.

4. The intelligent building engineering three-dimensional modeling method according to claim 1, characterized in that: The S4 includes S41 and S42; S41, the heat exchange efficiency Ethe, the humidity influence index Ehum and the ventilation efficiency evaluation index Even of the current building area i are comprehensively calculated to output the comprehensive thermal effect index Htotal, and the health condition of the current building area is comprehensively analyzed; The comprehensive thermal effect index Htotal is calculated and output through the following algorithm formula; Htotal i (t) = [(Ethe i (t) · a1) + (Ehum i (t) · a1) + (Even i (t) · a1)]; Htotal = Hout + Hadd i (t) represents the comprehensive thermal effect index of the building area i at time t, a1, a2 and a3 represent preset weight values of the heat exchange efficiency Ethe, the humidity influence index Ehum and the ventilation efficiency evaluation index Even respectively, and a1+a2+a3=1, and the specific values are set by the user.

5. The intelligent building engineering three-dimensional modeling method according to claim 4, characterized in that: S42, set the thermal effect threshold H1 based on the thermal effect standard of different building areas, and preliminarily compare and evaluate the comprehensive thermal effect index Htotal of the building area i at time t with the thermal effect threshold H1, preliminarily analyze the health condition of the building area, and generate relevant prompt information based on the evaluation result, and the specific evaluation content is as follows: i (t), and preliminarily compare and evaluate, preliminarily analyze the health condition of the building area, and generate relevant prompt information based on the evaluation result, and the specific evaluation content is as follows; When the comprehensive thermal effect index Htotal of the building area i at time t i When (Htotal(t) > thermal effect threshold H1), it indicates that the internal thermal effect of the current building area i is abnormal, at this time the current building area i on the sensor grid in the BIM system is automatically marked as red, and prompt information is generated through the BIM system to prompt the user to maintain and adjust. When the comprehensive thermal effect index Htotal of the building area i at time t i (t)≤ thermal effect threshold H1, it indicates that the internal thermal effect of the current building area i is normal, and no adjustment is needed to continue monitoring.

6. The intelligent building engineering three-dimensional modeling method according to claim 5, characterized in that: The S5 includes S51 and S52; S51, if the maintenance prompt information is generated, the overall thermal effect index Ztjk of the building is calculated based on the comprehensive thermal effect index Htotal of all building areas in the building, and the thermal load condition inside the building is comprehensively analyzed; The overall thermal effect index Ztjk is calculated and output by the following algorithm formula: In the formula, n represents the total number of building areas; S52, the overall thermal effect threshold H2 is set based on the thermal energy standard of the building as a whole, and the overall thermal effect threshold H2 is compared with the overall thermal effect index Ztjk for secondary comparison and evaluation, the overall thermal effect state of the building is analyzed, and the timeliness of maintenance is analyzed based on the evaluation result, and the specific evaluation content is as follows: When the overall thermal effect index Ztjk is greater than the overall thermal effect threshold H2, it indicates that the overall thermal effect of the building is abnormal, and the current building area is marked as a first abnormal level, and the BIM system prompts to maintain within three days; When the overall thermal effect index Ztjk is greater than twice the overall thermal effect threshold H2, it indicates that the overall thermal effect of the building is abnormal, and the current building area is marked as a second abnormal level, and the BIM system prompts to maintain immediately; When the overall thermal effect index Ztjk is less than the overall thermal effect threshold H2, it indicates that the overall thermal effect of the building is normal, and the BIM system prompts to maintain the current building area within seven days.

7. An intelligent building engineering three-dimensional modeling system applied to the intelligent building engineering three-dimensional modeling method of any one of claims 1-6, characterized in that: It comprises a three-dimensional modeling acquisition module, a data processing module, a thermal effect analysis module, a building area thermal effect analysis module and a maintenance timeliness analysis module. The three-dimensional modeling acquisition module acquires a three-dimensional model of the building by using a three-dimensional modeling tool, imports the three-dimensional model of the building into a BIM system, installs an intelligent sensor group inside the building, collects building data in real time, integrates the building data with the three-dimensional model of the building, and simulates the three-dimensional model of the building; The data processing module extracts building data in real time in the BIM system, pre-processes the building data, acquires a standard building data set, constructs a cloud database, and stores the standard building data set in the cloud database through a wireless network; The thermal effect analysis module constructs a building thermal effect prediction model, which comprises a heat exchange efficiency algorithm model, a humidity change algorithm model and an air flow rate algorithm model, extracts a standard building data set, inputs the standard building data set into the building thermal effect prediction model, and calculates and outputs the heat exchange efficiency Ethe, the humidity influence index Ehum and the ventilation efficiency evaluation index Even, respectively; The building area thermal effect analysis module calculates and outputs the comprehensive thermal effect index Htotal based on the heat exchange efficiency Ethe, the humidity influence index Ehum and the ventilation efficiency evaluation index Even, preliminarily compares and evaluates the thermal effect threshold H1 and the comprehensive thermal effect index Htotal, and generates maintenance prompt information based on the evaluation result; After the maintenance prompt information is generated by the preliminary comparison and evaluation, the maintenance time-effect analysis module calculates the overall thermal effect index Ztjk of the building based on the comprehensive thermal effect index Htotal, and performs secondary comparison and evaluation between the overall thermal effect threshold H2 and the overall thermal effect index Ztjk of the building, analyzes the overall thermal effect state of the building, and prompts the maintenance execution time-effect based on the evaluation result.

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