Fire-fighting pipe network inspection management system based on BIM and CIM

Abstract

The invention discloses a fire-fighting pipe network inspection management system based on BIM (Building Information Modeling) and CIM (Common Information Modeling), and aims to solve the technical problems that a current fire-fighting pipe network inspection management system cannot realize three-dimensional visualization of a fire-fighting pipe network and is low in management efficiency and fault positioning accuracy, and the fire-fighting pipe network inspection management system comprises a multi-dimensional model data integration unit which is used for building a BIM platform model and expanding a CIM platform; the real-time monitoring and dynamic updating unit is used for acquiring operation data in real time and transmitting the operation data to the BIM / CIM platform, and realizing synchronous updating of a physical pipe network state and a digital model and model parameter adjustment; the intelligent analysis and decision support unit is used for fire-fighting pipe network fault diagnosis and prediction; and the visualization and collaborative management unit is used for displaying the full view of the pipe network and supporting 360-degree view angle switching, attribute query and simulation drilling. Through integration of BIM and CIM technologies, the system realizes three-dimensional visualization of the fire-fighting pipe network, so that information such as pipe network layout and equipment installation positions is clear at a glance, and the management efficiency and the fault positioning accuracy are greatly improved.

Description

Technical Field

[0001] The present invention relates to the technical field of fire management systems, and in particular to a fire pipe network inspection management system based on BIM and CIM. Background Art

[0002] In modern urban management, fire protection pipe networks are an important part of urban infrastructure, and their effective management and maintenance are directly related to public safety. However, traditional fire protection pipe network management methods face many challenges.

[0003] Firstly, the layout of the fire protection pipeline network is complex, involving the connection between a large number of internal pipelines in buildings and urban underground pipelines. Traditional two-dimensional drawings are difficult to intuitively display the overall picture of the pipeline network and its spatial relationship with the surrounding environment, resulting in low management efficiency and difficulty in fault location.

[0004] Secondly, with the development of Internet of Things technology, real-time monitoring data of fire protection pipeline networks are becoming increasingly abundant, but the data processing capabilities are lagging behind and the system response speed is slow, making it difficult to meet the needs of real-time warning and rapid response.

[0005] In addition, the data formats between different systems are incompatible, and the data island phenomenon is serious, which hinders the integration and sharing of information and limits the scalability of the management system. Therefore, a new technical solution needs to be designed to solve this problem. Summary of the invention

[0006] The purpose of the present invention is to provide a fire pipe network inspection and management system based on BIM and CIM to solve the technical problems that the current fire pipe network inspection and management system cannot realize three-dimensional visualization of the fire pipe network and has low management efficiency and fault location accuracy.

[0007] To achieve the above object, the present invention provides the following technical solution: a fire pipe network inspection management system based on BIM and CIM, comprising:

[0008] Multi-dimensional model data integration unit: used for BIM platform model construction and CIM platform expansion;

[0009] Real-time monitoring and dynamic update unit: used to collect operation data in real time and transmit it to the BIM / CIM platform, and to synchronize the physical pipe network status with the digital model and adjust the model parameters;

[0010] Intelligent analysis and decision support unit: used for fire protection pipe network fault diagnosis and prediction;

[0011] Visualization and collaborative management unit: used to display the overall picture of the pipeline network, supporting 360-degree viewing angle switching, attribute query and simulation drills, and the design, construction, operation and maintenance and fire departments can access authority data through a unified platform.

[0012] As a preferred embodiment of the present invention, the multi-dimensional model data integration unit includes:

[0013] 3D model construction module: used to integrate the parametric model of building components in BIM and the urban geographic information model in CIM to achieve three-dimensional visual expression of the spatial topological relationship of the pipe network;

[0014] IoT data access module: used to integrate the real-time monitoring data of the fire pipe network sensors, and realize data preprocessing and outlier filtering through the edge computing node;

[0015] Geographic information integration module: used to fuse the urban-level GIS data in the CIM platform and perform three-dimensional coordinate conversion and multi-scale spatial analysis;

[0016] Equipment parameter management module: establish a meta-database of the fire pipe network equipment, record the attributes of model, material and installation time, associate the equipment maintenance records with the BIM component information, and realize the full life cycle management;

[0017] Dynamic monitoring and early warning module: combine the real-time monitoring data with the BIM model threshold parameters to automatically trigger the early warning events of pipe network leakage and pressure abnormality;

[0018] Version and historical data management module: used to record the model modification records and the historical versions of the pipe network transformation, support version backtracking and difference comparison, store the annual inspection reports and maintenance logs, and form a structured historical database;

[0019] Cross-system collaboration interface module: provide a standardized API interface to dock with external systems such as the fire alarm system and the emergency command platform.

[0020] As a preferred embodiment of the present invention, the real-time monitoring and dynamic update unit includes:

[0021] IoT sensor monitoring module: used to deploy sensors such as pressure, flow and temperature, collect the real-time operation data of the fire pipe network in real time, and track the real-time status of the fire fighting equipment through RFID or wireless sensing technology;

[0022] Environmental risk perception module: used to integrate smoke and temperature and humidity sensors to realize early fire warning and environmental abnormality monitoring;

[0023] 3D visualization monitoring module: based on the BIM model, display the spatial distribution of the pipe network and the equipment location, overlay the real-time operation data to form a dynamic 3D view, and integrate the urban-level geographic information through the CIM platform to realize the collaborative visualization of the pipe network and the urban infrastructure;

[0024] Intelligent analysis and early warning module: use big data analysis of real-time data to predict the pipe network failure risk and generate an early warning report;

[0025] Model dynamic update module: Automatically corrects the BIM model parameters according to real-time monitoring data to keep the model consistent with the physical pipe network;

[0026] Data transmission and processing module: Implements low-latency transmission of monitoring data using 5G / Internet of Things protocols and preprocesses massive monitoring data through edge computing.

[0027] As a preferred embodiment of the present invention, the intelligent analysis and decision support unit includes:

[0028] Three-dimensional visualization analysis module: Used for three-dimensional visualization display of the pipe network topology structure and conducts spatial positioning, collision detection, and water flow dynamic simulation analysis;

[0029] Risk assessment and early warning module: Based on historical inspection data and real-time monitoring information, evaluates the risk levels of pipe network corrosion and blockage through machine learning algorithms;

[0030] Operation and maintenance decision optimization module: Used to provide the function of prioritizing equipment maintenance, generates preventive maintenance plans by combining data such as equipment life cycle and failure frequency;

[0031] Emergency response simulation module: Used to simulate the matching degree between the water supply capacity of the pipe network and the fire demand, automatically recommends valve opening and closing schemes, links to the emergency plan library, and generates comprehensive disposal suggestions including elements such as personnel evacuation and fire truck traffic restrictions;

[0032] Data intelligent linkage module: Used to realize the automatic correlation analysis of alarm signals and pipe network status and conduct multi-system data fusion analysis;

[0033] Knowledge base management module: Uses natural language processing technology to achieve intelligent matching of similar faults and push solutions, integrates the fire protection code database, automatically verifies whether the inspection results meet the standard requirements of GB50974, and generates compliance reports.

[0034] As a preferred embodiment of the present invention, the visualization and collaborative management unit includes:

[0035] Model visualization module: Builds a three-dimensional space model of the fire protection pipe network based on BIM technology, integrates geometric attributes, physical parameters, and equipment operation and maintenance information, realizes component-level data interaction and attribute query, and embeds the pipe network model into the urban geographic information scene in combination with the CIM platform to achieve seamless switching between macro and micro perspectives;

[0036] Three-dimensional interaction engine: Used for inspection path simulation, equipment operation training, fault location, and multi-terminal access;

[0037] Real-time monitoring dashboard: Dynamically displays key parameters such as pipe network pressure, flow rate, and valve status;

[0038] Task collaboration module: used for multi-role task assignment and progress tracking;

[0039] Data integration and sharing module: used to achieve data interconnection with the fire alarm system and the energy consumption monitoring platform;

[0040] Collision detection and simulation analysis module: automatically detect spatial conflicts between pipe networks and other pipelines through the BIM model, and generate optimization plans.

[0041] As a preferred embodiment of the present invention, the three-dimensional model construction module includes:

[0042] BIM and GIS data conversion module: convert the component attributes of the BIM model into a spatial data format recognizable by GIS, and attach topological attributes;

[0043] Multi-source data unified management module: use a spatial database to store BIM component parameters, GIS geographical information, and pipe network topological relationships, support spatial queries and dynamic updates, and aggregate BIM micro-data and GIS macro-data through the CIM platform to form a unified three-dimensional model covering the internal pipe network of the building and the urban geographical environment;

[0044] Model lightweight processing module: perform LOD optimization on the BIM model, retain key pipe network topological attributes, reduce rendering load, use distributed computing technology to process urban-level massive data, and achieve efficient loading and interaction of the pipe network model in the CIM platform;

[0045] Topological relationship dynamic mapping module: based on GIS spatial analysis algorithms, identify the connection relationships between pipe network nodes, generate topological network diagrams, and combine with BIM parametric attributes to dynamically display the operating status of the pipe network in the three-dimensional scene in the form of colors and animations.

[0046] As a preferred embodiment of the present invention, the edge computing includes:

[0047] Preprocessing algorithm:

[0048] Sliding window mean filtering

[0049] Used to eliminate sensor noise, and the formula is:

[0050]

[0051] Among them, N is the window size, x i is the original data point, x t is the smoothed data;

[0052] Z-score based standardization processing

[0053] Unify the data dimension, and the formula is:

[0054] z = (x - μ) / σ

[0055] μ is the data mean, σ is the standard deviation, and z is the standardized output.

[0056] As a preferred implementation manner of the present invention, the edge computing includes:

[0057] Outlier detection algorithm:

[0058] Dynamic threshold method

[0059] Adaptive adjustment of the threshold range in combination with historical data, and the formula is:

[0060] T upper = μ t + k * σ t T lower = μ t - k * σ t ;

[0061] k is an adjustment coefficient (usually taken as 2 - 3), μ t and σ t are the mean and standard deviation of the current window;

[0062] Outlier identification based on quantiles (IQR)

[0063] Applicable to non-Gaussian distribution data, and the formula is:

[0064] Outlier range = [Q1 - 1.5 * IQR, Q3 + 1.5 * IQR]

[0065] where Q1 and Q3 are the first and third quartiles, and IQR = Q3 - Q1 is the interquartile range;

[0066] Time series prediction

[0067] Predict the data at the next moment and compare it with the measured value. The formula is:

[0068] y t+1 = αy t + (1 - α)y t

[0069] α is a smoothing factor (0 < α < 1). If the deviation exceeds the preset threshold, it is determined as an anomaly;

[0070] y t represents the predicted value of the t-th period, and y t is the actual value.

[0071] As a preferred embodiment of the present invention, the distributed computing technology for processing urban-level massive data includes data partitioning and hash allocation, and task decomposition and parallel computing.

[0072] As a preferred embodiment of the present invention, the data partitioning and hash allocation uses a distributed hash table (DHT) to achieve data sharding, and the formula is:

[0073] h(k) = hash(k) mod N

[0074] where k is the data key value and N is the total number of nodes. Through this formula, the massive data is evenly distributed to different computing nodes to ensure load balancing;

[0075] Task decomposition and parallel computing

[0076] The total task T is decomposed into K subtasks, and the computational load of each node is:

[0077] FLOP si = Total_FLOP s / K

[0078] Each node independently processes the allocated sub-dataset, and uses parallel computing to accelerate the overall processing speed.

[0079] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0080] 1. Through the integration of BIM and CIM technologies, the system of the present invention realizes the three-dimensional visualization of the fire protection pipe network, making information such as the pipe network layout and the installation positions of equipment clear at a glance, greatly improving the management efficiency and the accuracy of fault location, and supporting seamless switching from the macroscopic urban geographic information to the microscopic internal pipe network of buildings, helping managers to comprehensively grasp the pipe network status at different scales.

[0081] 2. The present invention adopts advanced technologies such as edge computing and distributed computing, improving the data processing ability and the system response speed. At the same time, it supports the import and export of open data formats such as IFC and CityGML, facilitating data exchange and integration with other systems, and having good scalability. BRIEF DESCRIPTION OF THE DRAWINGS

[0082] By reading the following detailed description of the non-limiting embodiments with reference to the accompanying drawings, other features, objects, and advantages of the present invention will become more apparent:

[0083] Figure 1 It is a flowchart of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0084] The technical solutions in the embodiments of the present invention will be described clearly and completely below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments.

[0085] Example 1: A fire protection pipe network inspection management system based on BIM and CIM, see Figure 1 ,include:

[0086] Multi-dimensional model data integration unit: used for BIM platform model construction and CIM platform expansion;

[0087] Real-time monitoring and dynamic update unit: used to collect operation data in real time and transmit it to the BIM / CIM platform, and to synchronize the physical pipe network status with the digital model and adjust the model parameters;

[0088] Intelligent analysis and decision support unit: used for fire protection pipe network fault diagnosis and prediction;

[0089] Visualization and collaborative management unit: used to display the overall picture of the pipeline network, supporting 360-degree viewing angle switching, attribute query and simulation drills, and the design, construction, operation and maintenance and fire departments can access authority data through a unified platform.

[0090] In summary, through the integration of BIM and CIM technologies, the system has realized the three-dimensional visualization of the fire protection pipe network, making the pipe network layout, equipment installation location and other information clear at a glance, greatly improving the management efficiency and the accuracy of fault location, and supporting the seamless switching from the macro urban geographic information to the micro internal pipe network of the building, helping managers to fully grasp the status of the pipe network at different scales. Through the integration of BIM and CIM technologies, the system has realized the three-dimensional visualization of the fire protection pipe network, making the pipe network layout, equipment installation location and other information clear at a glance, greatly improving the management efficiency and the accuracy of fault location, and supporting the seamless switching from the macro urban geographic information to the micro internal pipe network of the building, helping managers to fully grasp the status of the pipe network at different scales.

[0091] Specifically, the multi-dimensional model data integration unit includes:

[0092] 3D model construction module: Integrate BIM's parametric model of building components with CIM's urban geographic information model to achieve 3D visualization of the spatial topological relationship of the pipe network, including static model data such as building structure, pipe network layout, and equipment installation location;

[0093] IoT data access module: Integrates real-time monitoring data of fire pipe network sensors (such as pressure, flow, and temperature sensors), supports spatial binding of RFID tags and BIM models, and implements data preprocessing and outlier filtering through edge computing nodes;

[0094] Geographic Information Integration Module: Integrate urban-level GIS data in the CIM platform, including spatial information such as underground pipeline distribution, surrounding building density, and traffic road network, and support 3D coordinate conversion and multi-scale spatial analysis;

[0095] Equipment Parameter Management Module: Establish a meta-database for fire protection network equipment (such as valves, pumps, fire hydrants), record attributes such as model, material, installation time, etc., associate equipment maintenance records with BIM component information, and achieve full life cycle management;

[0096] Dynamic Monitoring and Early Warning Module: Combine real-time monitoring data with BIM model threshold parameters to automatically trigger early warning events such as pipeline leakage and abnormal pressure, and support the visual positioning of early warning information in the 3D scene;

[0097] Version and Historical Data Management Module: Record model modification records and historical versions of pipeline network renovations, support version backtracking and difference comparison, store annual inspection reports and maintenance logs, and form a structured historical database;

[0098] Cross-System Collaboration Interface Module: Provide standardized API interfaces to connect to external systems such as fire alarm systems and emergency command platforms, achieve two-way data interaction, and support the import and export of open data formats such as IFC and CityGML.

[0099] Furthermore, the real-time monitoring and dynamic update unit includes:

[0100] Internet of Things Sensor Monitoring Module: Deploy sensors such as pressure, flow, and temperature to collect real-time operation data of the fire protection pipeline network (such as water pressure, valve status, leakage situation), and track the real-time status of fire protection equipment (fire hydrants, sprinkler systems) through RFID or wireless sensing technology;

[0101] Environmental Risk Perception Module: Integrate sensors such as smoke, temperature, and humidity to achieve early fire warning and environmental anomaly monitoring, combine with cameras for image analysis, and identify potential safety hazards around the pipeline network;

[0102] 3D Visualization Monitoring Module: Based on the BIM model, display the spatial distribution of the pipeline network and equipment positioning, overlay real-time operation data to form a dynamic 3D view, and integrate urban-level geographic information through the CIM platform to achieve the collaborative visualization of the pipeline network and urban infrastructure;

[0103] It should be noted that the 3D model construction module includes:

[0104] BIM and GIS Data Conversion Module: Convert the component attributes of the BIM model (such as pipe diameter, material) into a spatial data format recognizable by GIS (such as GeoJSON, CityGML), and attach topological attributes. Achieve the standardized integration of BIM and GIS data through the IFC protocol or spatial database technology to ensure that the model's spatial positioning is consistent with the GIS coordinate system;

[0105] Multi-source Data Unified Management Module: Use a spatial database (such as PostGIS) to store BIM component parameters, GIS geographic information, and pipe network topological relationships, support spatial queries and dynamic updates. Aggregate BIM micro-data and GIS macro-data through the CIM platform to form a unified 3D model covering the internal pipe network of buildings and the urban geographical environment;

[0106] Model Lightweight Processing Module: Optimize the BIM model in terms of LOD (Level of Detail), retain key pipe network topological attributes, reduce rendering load, and use distributed computing technology to process urban-scale massive data to achieve efficient loading and interaction of the pipe network model in the CIM platform;

[0107] Topological Relationship Dynamic Mapping Module: Based on GIS spatial analysis algorithms (such as network analysis, buffer analysis), identify the connection relationships between pipe network nodes, generate a topological network diagram, and combine BIM parametric attributes (such as flow rate, pressure) to dynamically display the operation status of the pipe network in the 3D scene in the form of colors, animations, etc.;

[0108] It is worth introducing that the processing of urban-scale massive data by distributed computing technology includes data partitioning and hash distribution and task decomposition and parallel computing;

[0109] Data partitioning and hash distribution use a distributed hash table (DHT) to achieve data sharding. The formula is:

[0110] h(k) = hash(k) mod N

[0111] where k is the data key value and N is the total number of nodes. Through this formula, the massive data is evenly distributed to different computing nodes to ensure load balancing;

[0112] Task decomposition and parallel computing

[0113] The total task T is decomposed into K sub-tasks, and the computational amount of each node is:

[0114] FLOP si = Total_FLOP s / K

[0115] Each node independently processes the assigned sub-dataset and uses parallel computing to accelerate the overall processing speed;

[0116] Intelligent Analysis and Early Warning Module: Utilize big data analysis to analyze real-time data, predict the risk of pipeline network failures, generate early warning reports, provide decision-making suggestions through AI models (such as anomaly pattern recognition), and automatically trigger emergency response plans;

[0117] Model Dynamic Update Module: Automatically correct the parameters of the BIM model according to real-time monitoring data, maintain the consistency between the model and the physical pipeline network, update the equipment life cycle information in combination with inspection and maintenance records, and support the optimization of operation and maintenance strategies;

[0118] Data Transmission and Processing Module: Adopt 5G / Internet of Things protocols to achieve low-latency transmission of monitoring data, support local caching and synchronization in a network-disconnected environment, and preprocess massive monitoring data through edge computing to improve the system response efficiency;

[0119] It should be emphasized that edge computing includes:

[0120] Preprocessing algorithms:

[0121] Moving window mean filtering

[0122] Used to eliminate sensor noise, and the formula is:

[0123]

[0124] where N is the window size, x i is the original data point, and x t is the smoothed data;

[0125] Z-score based standardization processing

[0126] Unify the data dimension, and the formula is:

[0127] z = (x - μ) / σ

[0128] μ is the data mean, σ is the standard deviation, and z is the standardized output;

[0129] Edge computing includes:

[0130] Outlier detection algorithms:

[0131] Dynamic threshold method

[0132] Adaptive adjustment of the threshold range in combination with historical data, and the formula is:

[0133] T upper = μ t + k * σ t , T lower = μ t - k * σ t ;

[0134] k is the adjustment coefficient (usually taken as 2 - 3), μt and σ t are the mean and standard deviation of the current window;

[0135] Outlier identification based on the interquartile range (IQR)

[0136] Applicable to non-Gaussian distributed data, the formula is:

[0137] Outlier range = [Q1 - 1.5 * IQR, Q3 + 1.5 * IQR]

[0138] where Q1 and Q3 are the first and third quartiles, and IQR = Q3 - Q1 is the interquartile range;

[0139] Time series prediction

[0140] Predict the data at the next moment and compare it with the measured value. The formula is:

[0141] y t+1 = αy t + (1 - α)y t

[0142] α is the smoothing factor (0 < α < 1). If the deviation exceeds the preset threshold, it is determined as an anomaly;

[0143] y t represents the predicted value at the t-th period, while y t is the actual value.

[0144] In summary, advanced technologies such as edge computing and distributed computing are adopted to improve the data processing ability and system response speed. At the same time, it supports the import and export of open data formats such as IFC and CityGML, facilitating data exchange and integration with other systems, and has good scalability.

[0145] Furthermore, the intelligent analysis and decision support unit includes:

[0146] 3D visualization analysis module: Integrate the building pipe network model of BIM and the city-level spatial data of CIM to realize the 3D visualization display of the pipe network topology structure, support spatial positioning, collision detection, and water flow dynamic simulation analysis, and map the sensor data (such as pressure, flow rate, valve status) to the model in real time to form a digital twin to assist in quickly locating abnormal areas;

[0147] Risk assessment and early warning module: Automatically correct the BIM model parameters according to the real-time monitoring data to keep the model consistent with the physical pipe network. Based on the historical inspection data and real-time monitoring information, evaluate the risk levels of pipe network corrosion and blockage through machine learning algorithms, generate a dynamic risk heat map, establish a multi-parameter early warning threshold library (such as pressure mutation, leakage index), trigger hierarchical alarms and push them to the management terminal;

[0148] Operation and Maintenance Decision Optimization Module: Provide the function of sorting the priority of equipment maintenance, generate preventive maintenance plans by combining data such as equipment life cycle and failure frequency, support the optimization of emergency resource scheduling paths, integrate GIS maps to calculate the shortest repair routes, and simulate the pipe network carrying capacity under different working conditions;

[0149] Emergency Response Simulation Module: Built-in fire scene simulation engine, which can simulate the matching degree between the water supply capacity of the pipe network and the fire field demand, automatically recommend the optimal valve opening and closing plan, link with the emergency plan library, and generate comprehensive disposal suggestions including elements such as personnel evacuation and fire truck traffic restrictions;

[0150] Data Intelligent Linkage Module: Connect to the fire protection Internet of Things platform, realize the automatic correlation analysis of alarm signals and pipe network status (such as automatically retrieving the pressure data of surrounding fire hydrants when a smoke detector alarms), support the fusion analysis of multi-system data, including cross-platform data interaction with the municipal water supply system and power monitoring system;

[0151] Knowledge Base Management Module: Build a fire protection pipe network failure case library, use natural language processing technology to realize the intelligent matching of similar failures and push solution, integrate the fire protection code database, automatically verify whether the inspection results meet the standard requirements such as GB50974, and generate compliance reports.

[0152] It should be noted that the visualization and collaborative management unit includes:

[0153] Model Visualization Module: Build a three-dimensional space model of the fire protection pipe network based on BIM technology, integrate geometric attributes, physical parameters and equipment operation and maintenance information, support the lightweight engine to quickly load large-scale models, realize component-level data interaction and attribute query, and embed the pipe network model into the urban geographic information scene in combination with the CIM platform to achieve seamless switching between macro and micro perspectives;

[0154] Three-dimensional Interaction Engine: Provide virtual reality (VR) and augmented reality (AR) functions, support inspection path simulation, equipment operation training and fault location, support multi-terminal access, and optimize the model loading efficiency of mobile terminals through hierarchical transmission technology;

[0155] Real-time Monitoring Dashboard: Dynamically display key parameters such as pipe network pressure, flow rate, and valve status, trigger visual warnings for abnormal data, integrate video monitoring and sensor data, and realize the real-time overlay display of the operation status of fire protection equipment;

[0156] Task Collaboration Module: Support multi-role task assignment and progress tracking, such as issuing inspection work orders and approving maintenance processes, built-in instant messaging tools, allowing inspection personnel to share on-site photos or videos with the command center in real time;

[0157] Version and Change Management Module: Automatically record the design change history, realize the version traceability of drawings and models through systems such as SVN, and trigger an early warning mechanism when the design change exceeds the threshold to prevent the use of expired data on site;

[0158] Data Integration and Sharing Module: Establish a central database to store full-cycle data such as design drawings, inspection reports, and construction logs, support the retrieval of component information by scanning QR codes, and have standardized data interfaces to achieve data interconnection with fire alarm systems and energy consumption monitoring platforms;

[0159] Collision Detection and Simulation Analysis Module: Automatically detect spatial conflicts between pipe networks and other pipelines through BIM models and generate optimization plans;

[0160] Patrol Route Optimization Module: Recommend the optimal patrol route based on historical data and real-time status to reduce repetitive operations.

[0161] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. For those skilled in the art, it is obvious that the present invention is not limited to the details of the above-described exemplary embodiments, and without departing from the spirit or basic characteristics of the present invention, the present invention can be implemented in other specific forms. Therefore, in any regard, the embodiments should be regarded as exemplary and non-limiting. The scope of the present invention is defined by the appended claims rather than the above description. Therefore, it is intended to embrace all changes falling within the meaning and scope of the equivalent elements of the claims in the present invention. Any reference signs in the claims should not be construed as limiting the claimed invention.

[0162] In addition, it should be understood that although this specification is described in terms of embodiments, not every embodiment only contains an independent technical solution. This narrative manner of the specification is only for clarity. Those skilled in the art should regard the specification as a whole, and the technical solutions in each embodiment can also be appropriately combined to form other embodiments that can be understood by those skilled in the art.

Claims

1. A fire protection pipe network inspection management system based on BIM and CIM, characterized by: include: Multi-dimensional model data integration unit: used for BIM platform model construction and CIM platform expansion; Real-time monitoring and dynamic update unit: used to collect operation data in real time and transmit it to the BIM / CIM platform, and to synchronize the physical pipe network status with the digital model and adjust the model parameters; Intelligent analysis and decision support unit: used for fire protection pipe network fault diagnosis and prediction; Visualization and collaborative management unit: used to display the overall picture of the pipeline network, supporting 360-degree viewing angle switching, attribute query and simulation drills, and the design, construction, operation and maintenance and fire departments can access authority data through a unified platform.

2. According to the BIM and CIM-based fire protection pipe network inspection management system of claim 1, it is characterized by: The multi-dimensional model data integration unit comprises: 3D model building module: used to integrate BIM's building component parametric model and CIM's urban geographic information model to achieve 3D visualization of the spatial topological relationship of the pipe network; IoT data access module: used to integrate real-time monitoring data of fire pipe network sensors, and implement data preprocessing and outlier filtering through edge computing nodes; Geographic information integration module: used to integrate city-level GIS data in the CIM platform and perform three-dimensional coordinate conversion and multi-scale spatial analysis; Equipment parameter management module: establishes a metadata database for fire protection pipe network equipment, records the attributes of model, material and installation time, associates equipment maintenance records with BIM component information, and realizes full life cycle management; Dynamic monitoring and early warning module: Combines real-time monitoring data with BIM model threshold parameters to automatically trigger early warning events of pipe network leakage and pressure anomalies; Version and historical data management module: used to record model modification records and historical versions of pipe network transformation, support version backtracking and difference comparison, store inspection reports and maintenance logs over the years, and form a structured historical database; Cross-system collaborative interface module: provides a standardized API interface to connect to external systems such as the fire alarm system and the emergency command platform.

3. According to the BIM and CIM-based fire protection pipe network inspection management system of claim 1, it is characterized by: The real-time monitoring and dynamic updating unit comprises: IoT sensor monitoring module: used to deploy pressure, flow, temperature and other sensors to collect real-time fire pipe network operation data and track the real-time status of fire equipment through RFID or wireless sensor technology; Environmental risk perception module: used to integrate smoke and temperature and humidity sensors to achieve early warning of fire and monitoring of environmental anomalies; 3D visualization monitoring module: Based on the BIM model, it displays the spatial distribution of the pipeline network and the location of equipment, superimposes real-time operation data to form a dynamic 3D view, integrates city-level geographic information through the CIM platform, and realizes the coordinated visualization of the pipeline network and urban infrastructure; Intelligent analysis and early warning module: Use big data to analyze real-time data, predict pipeline network failure risks and generate early warning reports; Model dynamic update module: automatically correct BIM model parameters based on real-time monitoring data to maintain consistency between the model and the physical pipe network; Data transmission and processing module: 5G / IoT protocol is used to achieve low-latency transmission of monitoring data, and edge computing is used to pre-process massive monitoring data.

4. According to the BIM and CIM-based fire protection pipe network inspection and management system of claim 1, it is characterized by: The intelligent analysis and decision support unit includes: 3D visualization analysis module: used for 3D visualization of pipe network topology, spatial positioning, collision detection and water flow dynamic simulation analysis; Risk assessment and early warning module: Based on historical inspection data and real-time monitoring information, the risk level of pipeline corrosion and blockage is assessed through machine learning algorithms; Operation and maintenance decision optimization module: used to provide equipment maintenance priority sorting function, and generate preventive maintenance plans based on data such as equipment life cycle and failure frequency; Emergency response simulation module: used to simulate the matching degree between the water supply capacity of the pipe network and the fire demand, automatically recommend valve opening and closing schemes, link the emergency plan library, and generate comprehensive disposal suggestions including elements of personnel evacuation and fire truck access restrictions; Data intelligent linkage module: used to realize automatic correlation analysis between alarm signals and pipe network status, and fusion analysis of multi-system data; Knowledge base management module: uses natural language processing technology to achieve intelligent matching of similar faults and push solutions, integrates the fire protection specification database, automatically verifies whether the inspection results meet the standard requirements of GB50974, and generates compliance reports.

5. According to the BIM and CIM-based fire protection pipe network inspection and management system of claim 1, it is characterized by: The visualization and collaborative management unit includes: Model visualization module: Build a three-dimensional spatial model of the fire protection pipe network based on BIM technology, integrate geometric attributes, physical parameters and equipment operation and maintenance information, realize component-level data interaction and attribute query, and embed the pipe network model into the urban geographic information scene in combination with the CIM platform to achieve seamless switching between macro and micro perspectives; 3D interactive engine: used for inspection route simulation, equipment operation training, fault location and multi-terminal access; Real-time monitoring dashboard: Dynamically displays key parameters of pipe network pressure, flow and valve status; Task collaboration module: used for multi-role task allocation and progress tracking; Data integration and sharing module: used to achieve data intercommunication with fire alarm system and energy consumption monitoring platform; Collision detection and simulation analysis module: automatically detects spatial conflicts between the pipeline network and other pipelines through the BIM model and generates optimization solutions.

6. According to the BIM and CIM-based fire protection pipe network inspection and management system of claim 2, it is characterized by: The three-dimensional model building module includes: BIM and GIS data conversion module: converts the component attributes of the BIM model into a spatial data format recognizable by GIS, and adds topological attributes; Multi-source data unified management module: uses spatial database to store BIM component parameters, GIS geographic information and pipe network topology, supports spatial query and dynamic update, and aggregates BIM micro data and GIS macro data through CIM platform to form a unified 3D model covering the internal pipe network of the building and the urban geographical environment; Model lightweight processing module: optimizes the LOD of the BIM model, retains key pipe network topology attributes, reduces rendering load, uses distributed computing technology to process massive city-level data, and realizes efficient loading and interaction of pipe network models in the CIM platform; Topological relationship dynamic mapping module: Based on GIS spatial analysis algorithm, it identifies the connection relationship between pipeline network nodes, generates a topological network diagram, and combines BIM parametric attributes to dynamically display the pipeline network operation status in the form of color and animation in a three-dimensional scene.

7. The fire protection pipe network inspection management system based on BIM and CIM according to claim 2 is characterized in that: The edge computing includes: Preprocessing algorithm: Sliding window mean filter Used to eliminate sensor noise, the formula is: Among them, N is the window size, x i is the original data point, x t is the smoothed data; Standardization based on Z-score Unify the data dimensions, the formula is: z=x-μ / σ μ is the data mean, σ is the standard deviation, and z is the standardized output.

8. The fire protection pipe network inspection management system based on BIM and CIM according to claim 2 is characterized in that: The edge computing includes: Outlier Detection Algorithm: Dynamic Threshold Method Combine historical data to adaptively adjust the threshold range. The formula is: T upper =μ t +k*s t ,T lower =μ t -k*s t ; k is the adjustment coefficient (usually 2 to 3), μ t and σ t is the mean and standard deviation of the current window; IQR-based outlier detection Applicable to non-Gaussian distribution data, the formula is: Outlier range = [Q1-1.5*IQR, Q3+1.5*IQR] Among them, Q1 and Q3 are the first and third quartiles, and IQR = Q3-Q1 is the interquartile range; Time Series Forecasting Predict the data at the next moment and compare it with the measured value. The formula is: y t+1 ay t +(1-α)y t α is the smoothing factor (0<α<1), and the deviation is considered abnormal if it exceeds the preset threshold; y t represents the predicted value of period t, and y t is the actual value.

9. The fire protection pipe network inspection management system based on BIM and CIM according to claim 6, characterized in that: The distributed computing technology for processing city-level massive data includes data partitioning and hash distribution and task decomposition and parallel computing.

10. The fire protection pipe network inspection management system based on BIM and CIM according to claim 9, characterized in that: The data partitioning and hash distribution adopts a distributed hash table (DHT) to realize data sharding, and the formula is: h(k)=hash(k)modN Among them, k is the data key value, and N is the total number of nodes. This formula can evenly distribute massive data to different computing nodes to ensure load balancing; Task decomposition and parallel computing The total task T is decomposed into K subtasks, and the computational effort of each node is: FLOP si =Total_FLOP s / K Each node processes the assigned sub-dataset independently, using parallel computing to accelerate the overall processing speed.

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