Pipeline collision emergency processing system for BIM operation and maintenance

Abstract

The application relates to the field of building information modeling and intelligent operation and maintenance, in particular to a pipeline collision emergency processing system for BIM operation and maintenance; the system comprises a data fusion module, a risk simulation module, a guided execution module and an optimization learning module; the data fusion module receives an emergency event and acquires real-time operation data of the emergency event; the risk simulation module constructs a fault propagation model based on the real-time operation data and generates a processing instruction sequence based on the fault propagation model; the guided execution module disassembles the processing instruction sequence into sequentially executed guided steps and executes the guided steps through context verification and locking mechanism; the optimization learning module constructs an emergency event library and performs case matching in the emergency event library when a new emergency event occurs; the application realizes dynamic simulation of fault propagation and operation guidance of emergency processing, improves the accuracy of emergency decision, reduces the human operation risk in the emergency environment, and guarantees the safety of operation personnel and equipment.

Description

Technical Field

[0001] This application relates to the fields of building information modeling and intelligent operation and maintenance technology, specifically to a pipeline collision emergency handling system for BIM operation and maintenance. Background Technology

[0002] In the wave of deep integration between new-generation information technology and the real economy, the field of building facility operation and maintenance is undergoing a fundamental transformation from passive response to proactive prediction, and from experience-driven to data-driven. Among these transformations, Building Information Modeling (BIM), with its core advantages of visualization, parametric design, and full lifecycle management, has broken through the application boundaries of the traditional design and construction stages. It has deeply coupled with cutting-edge technologies such as the Internet of Things, artificial intelligence, big data, and cloud computing, giving rise to intelligent operation and maintenance platforms—a new type of facility management carrier—which has become a core support for improving the operation and maintenance level of complex facilities such as factories, industrial parks, and large public buildings.

[0003] In the operation and maintenance system of various complex facilities, the pipeline system is the lifeline that ensures the normal operation of the facilities. Its operation and maintenance safety is directly related to the overall operational stability of the facilities, the safety of personnel and property, and is the core and top priority of operation and maintenance work.

[0004] Traditional pipeline system operation and maintenance work mainly relies on a response model of consulting two-dimensional drawings, manual inspection and troubleshooting, and experience-based judgment. This response model has gradually revealed many limitations in the face of the operational and maintenance needs of modern complex facilities: First, traditional two-dimensional drawings suffer from low visualization and fragmented information. Maintenance personnel must rely on their own experience to interpret the drawings and spatial imagination, which is not only time-consuming and labor-intensive but also prone to misjudgment due to misunderstandings. Second, after a fault or emergency occurs, personnel must first be dispatched with drawings to the site for troubleshooting and location before a response plan can be formulated. This entire process is cumbersome and slow, often missing the optimal response time and causing the impact of the fault to further expand. Third, the reliance on manual experience... The judgment method is highly subjective, and the location of the fault and the formulation of the handling plan lack scientific data support, which is prone to judgment errors. This may not only lead to poor handling results, but may even cause secondary disasters due to improper handling. Fourth, the emergency environment is complex and changeable, such as the flammable and explosive environment after a gas leak. In the traditional mode, maintenance personnel have to carry out emergency operations under incomplete information and uncertain environment. However, two-dimensional drawings cannot provide real-time operating data and risk warning information. Relying on experience to make judgments is prone to operational errors, which may not only aggravate the fault hazards, but also directly threaten the life safety of maintenance personnel. At the same time, it is difficult to avoid damage to the surrounding normally operating equipment due to misoperation, which further expands property losses.

[0005] The information disclosed in this background section is intended only to enhance the understanding of the overall background of this application and should not be construed as an admission or in any way implying that the information constitutes prior art known to those skilled in the art. Summary of the Invention

[0006] The purpose of this application is to provide a pipeline collision emergency handling system for BIM operation and maintenance, which can solve the problems raised in the background technology to a certain extent, improve the accuracy of emergency decision-making, and ensure the safety of personnel and equipment.

[0007] To achieve the above objectives, this application provides the following technical solution:

[0008] This application provides a pipeline collision emergency handling system for BIM operation and maintenance, including a data fusion module, a risk simulation module, a guided execution module, and an optimization learning module;

[0009] The data fusion module is used to receive emergency events and locate the collision location based on the emergency events; the data fusion module is also used to synchronously acquire real-time operational data of the collision location;

[0010] The risk simulation module constructs a fault propagation model based on the real-time operating data and generates a collision impact diagram based on the fault propagation model; the risk simulation module also generates a sequence of processing instructions based on the collision impact diagram;

[0011] The guidance execution module breaks down the processing instruction sequence into sequentially executed guidance steps, and executes the guidance steps through context verification and locking mechanisms;

[0012] The optimization learning module is used to build an emergency event database and, when a new emergency event occurs, to perform case matching in the database to obtain the corresponding fault propagation model.

[0013] As a preferred embodiment of the pipeline collision emergency handling system for BIM operation and maintenance described in this application, the risk simulation module is configured with a fault propagation model construction strategy; the fault propagation model construction strategy specifically includes:

[0014] The specific equipment or pipeline segment corresponding to the collision location is marked as the fault source, and a network traversal of limited depth is performed in the BIM model with the fault source as the center, based on the upstream and downstream logical connection relationship, to obtain the local analysis network.

[0015] The fault type of the fault source is identified based on the alarm signal from the sensor and the attribute information of the component corresponding to the collision location, and the corresponding simulation analysis model is selected based on the fault type.

[0016] Based on the real-time operating data and simulation analysis model, numerical simulation calculations are performed in the local analysis network to obtain the dynamic propagation results of the fault.

[0017] The dynamic propagation results include: a predicted sequence of state parameters of each component in the local analysis network changing over time, key influencing devices identified based on the predicted sequence, and the expected impact time.

[0018] As a preferred embodiment of the pipeline collision emergency handling system for BIM operation and maintenance described in this application, the fault propagation model construction strategy further includes, when a hydraulic calculation model is selected, the step of performing numerical simulation calculations based on real-time operating data specifically includes:

[0019] Configure computing nodes, including pipe nodes, boundary nodes, and leak nodes;

[0020] Initial conditions are determined based on real-time operational data, and boundary conditions are set for the local analysis network.

[0021] The pressure value of the boundary node with constant pressure in the local analysis network is used as the pressure boundary value, and the flow value of the boundary node with constant flow is used as the flow boundary value; the pressure and flow of the leaking node are acquired in real time, and the relationship between the pressure and flow of the leaking node is calculated to obtain the boundary of the leaking point.

[0022] The water hammer equation is constructed based on the laws of conservation of mass and momentum. The water hammer equation is then discretized along the direction of the characteristic line to obtain the compatibility equations, namely the C+ equation and the C- equation, which propagate along the positive and negative characteristic lines, respectively.

[0023] As a preferred embodiment of the pipeline collision emergency response system for BIM operation and maintenance described in this application, when a hydraulic calculation model is selected, the step of performing numerical simulation calculations based on real-time operating data further includes:

[0024] From the discretized water hammer equation, the compatibility equation of each pipe node in the local analysis network is obtained, and the solution equation set of the pipe node is obtained.

[0025] If the boundary node is connected to an upstream pipeline, the C+ equation of the corresponding boundary node is obtained from the discretized water hammer equation, and the boundary value of the corresponding boundary node is combined with the C- equation of the pipeline node connected to the boundary node to obtain the C- equation of the boundary node.

[0026] If the boundary node is connected to a downstream pipeline, the C-equation of the corresponding boundary node is obtained from the discretized water hammer equation, and the boundary value of the corresponding boundary node is combined with the C+ equation of the pipeline node connected to the boundary node to obtain the C+ equation of the boundary node.

[0027] Extract the C- equation of the pipeline node upstream of the leak node and the C+ equation of the pipeline node downstream of the leak node, and then combine the boundary of the leak point with the C- equation and the C+ equation to obtain the solution equation system for the corresponding leak node.

[0028] As a preferred embodiment of the pipeline collision emergency response system for BIM operation and maintenance described in this application, when a hydraulic calculation model is selected, the step of performing numerical simulation calculations based on real-time operating data further includes:

[0029] Set the computation time step, and iteratively solve the system of equations within each computation time step to obtain the predicted values ​​of pressure and flow rate of each computing node within the corresponding computation time step.

[0030] In the calculation within each calculation time step, the predicted values ​​of pressure and flow of each calculation node obtained in the previous calculation time step are used as the initial conditions for the current calculation time step, and the solution equation system is updated based on the initial conditions.

[0031] The predicted pressure value obtained in each calculation time step is compared with the preset safe pressure threshold in real time, and the calculation node whose predicted pressure value is earliest less than the safe pressure threshold is identified.

[0032] The computing nodes are marked as key impact devices, and the computing time corresponding to the corresponding computing time step is used as the expected impact time.

[0033] As a preferred embodiment of the pipeline collision emergency handling system for BIM operation and maintenance described in this application, the fault propagation model construction strategy further includes: when using a gas flow and diffusion model, the specific steps of performing numerical simulation calculations based on real-time operating data include:

[0034] Construct a set of governing equations; determine initial conditions based on real-time runtime data, and set boundary constraints;

[0035] Based on the initial conditions and boundary constraints, the control equations are discretized, and the control equations are solved within each computation time step to obtain the flow prediction values ​​of all computation nodes.

[0036] Centered on the leak node, the area that can be affected is delineated in the BIM model; real-time meteorological data of the area that can be affected is obtained, and a Gaussian diffusion model is established in combination with the building outline of the BIM model;

[0037] Based on the Gaussian diffusion model, the predicted flow rate of each computing node is used as input to calculate the predicted gas concentration at each spatial location within the affected area at different times.

[0038] The predicted gas concentration is compared with a preset safe concentration threshold in real time to identify the spatial region where the predicted gas concentration is earliest greater than the safe concentration threshold, thus obtaining the dangerous diffusion area, and the corresponding calculation time is used as the expected impact time.

[0039] As a preferred embodiment of the pipeline collision emergency handling system for BIM operation and maintenance described in this application, the risk simulation module is configured with a collision impact diagram generation strategy; the collision impact diagram generation strategy specifically includes:

[0040] The predicted sequence of the state parameters of each component in the local analysis network changing over time is associated with the spatial coordinates of the BIM model to obtain spatiotemporal data points;

[0041] Based on the spatiotemporal data points, the BIM model is divided into different impact level areas and visualized; the danger diffusion area or key impact equipment and its surrounding preset area are designated as the core leakage area, and the core leakage area is filled with red in the BIM model.

[0042] In the outer region of the core leakage zone, calculation nodes with predicted pressure values ​​less than the safe pressure threshold, or spatial regions with predicted gas concentration values ​​greater than the safe concentration threshold, are extracted to obtain secondary influence nodes or secondary influence regions.

[0043] As a preferred embodiment of the pipeline collision emergency handling system for BIM operation and maintenance described in this application, the collision impact diagram generation strategy further includes:

[0044] Calculate the difference between the calculation time and the initial calculation time corresponding to the secondary affected node or secondary affected area to obtain the first time difference, and calculate the difference between the expected impact time and the initial calculation time to obtain the second time difference;

[0045] Calculate the ratio of the first time difference to the second time difference. If the ratio is greater than a preset multiple threshold, mark the secondary influence area or secondary influence node and its surrounding preset area as a secondary protection zone, and fill the secondary protection zone with orange in the BIM model.

[0046] Extract the computational nodes whose predicted pressure values ​​are always greater than or equal to the safe pressure threshold, or the spatial regions whose predicted gas concentration values ​​are always less than the safe concentration threshold; mark the corresponding spatial regions or computational nodes and their surrounding regions in the local analysis network as safety buffers, and fill the safety buffers with green in the BIM model.

[0047] As a preferred embodiment of the pipeline collision emergency handling system for BIM operation and maintenance described in this application, the guided execution module is configured with a guided step decomposition and execution strategy; the guided step decomposition and execution strategy specifically includes:

[0048] A command decomposition library was built based on standard operating procedures, equipment operation manuals and expert experience in the field of operation and maintenance.

[0049] Based on the operation target and operation action corresponding to any processing instruction, the corresponding decomposition template is matched from the instruction decomposition library to obtain the target template; based on the corresponding processing instruction, the target template is instantiated to obtain the guiding steps corresponding to the processing instruction.

[0050] The guidance steps are pushed to the AR glasses terminal worn by the on-site maintenance personnel. After the on-site maintenance personnel arrive at the corresponding task area, the context verification and locking mechanism guides the on-site maintenance personnel to execute each guidance step in sequence.

[0051] As a preferred embodiment of the pipeline collision emergency handling system for BIM operation and maintenance described in this application, the context verification and locking mechanism specifically includes:

[0052] Before performing the bootstrapping steps, a temporary virtual latching signal is sent to the IoT controller of each target device;

[0053] Based on the 3D BIM spatial information corresponding to the current guidance step, the target device specified in the current guidance step is highlighted in the form of a guide arrow;

[0054] When the visual sensor built into the AR glasses terminal detects the target device, it prompts on-site maintenance personnel to scan the identification code attached to the target device for identity verification.

[0055] When the target device passes authentication, an interactive interface is used on the AR glasses terminal to confirm the authentication and an unlocking signal is sent to the target device.

[0056] When the target device receives the unlock signal, it executes the guidance step according to the step action code of the current guidance step, through the operation guide displayed on the AR glasses terminal.

[0057] Compared with the prior art, the beneficial effects achieved by the present invention are as follows:

[0058] By receiving emergency events and locking collision locations based on these events, while simultaneously acquiring real-time operational data of the collision locations, a fault propagation model is constructed based on the real-time operational data, and a collision impact diagram is generated based on the fault propagation model. This achieves forward-looking dynamic simulation of fault propagation, improving the accuracy of emergency decision-making. A processing instruction sequence is generated based on the collision impact diagram, and this sequence is broken down into sequentially executed guiding steps. These guiding steps are executed through context verification and locking mechanisms, reducing the risk of human error in emergency environments and ensuring the safety of maintenance personnel and equipment. An emergency event database is constructed, and when a new emergency event occurs, cases are matched within the database to obtain the corresponding fault propagation model, shortening emergency response time and improving overall emergency response efficiency and safety. Attached Figure Description

[0059] To more clearly illustrate the technical solutions of the embodiments of this application, the drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort. Wherein:

[0060] Figure 1 A structural diagram of the pipeline collision emergency handling system for BIM operation and maintenance provided in this application;

[0061] Figure 2 A flowchart illustrating the breakdown and execution strategy of the guiding steps provided for this application. Detailed Implementation

[0062] The technical solution of this application will be described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the embodiments and specific features in the embodiments are detailed descriptions of the technical solution of this application, rather than limitations thereof. In the absence of conflict, the embodiments and technical features in the embodiments can be combined with each other.

[0063] like Figure 1 As shown in the figure, this embodiment introduces a pipeline collision emergency handling system for BIM operation and maintenance, including a data fusion module, a risk simulation module, a guided execution module and an optimization learning module;

[0064] The data fusion module is used to receive emergency events and locate the collision location based on the emergency events; the data fusion module is also used to synchronously acquire real-time operating data of the collision location; the emergency event refers to an alarm signal that is automatically triggered by the sensor or manually triggered by the operation and maintenance personnel, which is used to indicate that the pipeline has experienced an abnormal collision or fault.

[0065] In this embodiment, different sensors, such as leak sensors, temperature sensors, pressure sensors, flow counters, and current sensors, are deployed at key locations along the pipeline to receive sensor data in real time. Based on the sensor data, an alarm signal is triggered using a threshold comparison method. For example, leak sensors are installed in key areas such as pipe racks, equipment rooms, and under floors to detect pipe ruptures, steam leaks, or condensate accumulation. When the leak sensor detects humidity exceeding a preset humidity threshold, such as 80%, an alarm signal is triggered. Current sensors are installed at distribution cabinets, busbars, or important cable joints to monitor the current value of the electrical circuit in real time. When the current sensor detects a current value exceeding a preset current threshold, such as 150% of the rated current, an alarm signal is triggered.

[0066] Optionally, the emergency events can also be submitted by maintenance personnel via mobile terminals; when submitting an emergency event, basic information about the emergency event must be filled in, including: the time of the event, a description of the approximate location, and preliminary on-site observations.

[0067] The method for locking the collision location is as follows:

[0068] If the emergency event is an alarm signal from a sensor, the sensor's coordinate information is extracted as the initial positioning point, and pipeline components within a preset area around the initial positioning point are obtained through a pre-built BIM model; for example, pipeline components within a 10-meter straight-line distance from the initial positioning point are obtained; the BIM model includes complete three-dimensional geometric and semantic information of the pipeline system, and is constructed externally, such as by the design party, construction party, or a third party, and is not generated in real time by this emergency handling system; combined with the sensor's installation location and the physical connection relationship of the pipeline, the collision location corresponding to the alarm signal is located in the BIM model; for example, when the sensor is installed at the midpoint of a pipe segment, the coordinates of the midpoint of the pipe segment are used as the location point of the collision location in the BIM model; for example, when the alarming sensor is installed at the midpoint of a DN100 water supply pipe segment K12-K13, the coordinates of the midpoint in the BIM model (X=126.1m, Y=87.2m, Z=-3.5m) are used as the location point of the collision location in the BIM model;

[0069] If the emergency event is submitted by maintenance personnel via a mobile terminal, the location area of ​​the emergency event in the BIM model is located based on the approximate location description filled in by the maintenance personnel. The maintenance personnel then select and confirm the pipeline components in the location area on the mobile terminal to obtain the final location of the collision position corresponding to the emergency event in the BIM model.

[0070] The real-time operational data includes static attribute data, dynamic operational data, and spatial constraint data. Specifically, static attribute data such as pipeline material, specifications, design pressure, and upstream and downstream logical connection relationships at the collision location are extracted from the BIM model. Dynamic operational data, including pressure, flow rate, medium temperature, valve opening, pump or fan start / stop status, circuit on / off status, and current value of the associated pipeline, are obtained in real time from the equipment control system related to the collision location through an IoT gateway. Spatial constraint data, including pipeline burial depth, wall penetration location, pipe gallery number, cross-sectional dimensions, internal pipeline layout, and inspection port location, are extracted from the BIM model.

[0071] The risk simulation module constructs a fault propagation model based on the real-time operational data and generates a collision impact diagram based on the fault propagation model; the risk simulation module also generates a sequence of processing instructions based on the collision impact diagram; the fault propagation model is constructed as follows:

[0072] The specific equipment or pipeline segment corresponding to the collision location is marked as the fault source, and a network traversal of limited depth is performed in the BIM model with the fault source as the center, based on the upstream and downstream logical connection relationship, to obtain the local analysis network.

[0073] Specifically, the network traversal method is as follows: In the BIM model, with the fault source as the center, a breadth-first search is performed along the upstream and downstream directions respectively; in the upstream direction, when a component marked as an isolation valve is found, or when the source component of the system is found, the breadth-first search in the upstream direction is stopped; in the downstream direction, when a component marked as an isolation valve is found, or when the end device is found, the breadth-first search in the downstream direction is stopped; all components and their connection relationships accessed during the breadth-first search are merged to obtain the local analysis network;

[0074] For example, the DN100 water supply pipe segment K12-K13 is taken as the fault source, and a breadth-first search is performed along the upstream and downstream logical connection relationship with this fault source as the center: the upstream search reaches the isolation valve V-101 located at the end of the K11-K12 pipe segment, and the downstream search reaches the isolation valve V-102 located at the beginning of the K13-K14 pipe segment, to obtain the final local analysis network; the local analysis network includes the DN150 pipe segments K10-K11, DN150 pipe segments K11-K12, DN100 pipe segments K12-K13, DN80 pipe segments K13-K14, KDN80 pipe segments 14-K15, valves V-101, valves V-102, and valve V-103 located in the KDN80 pipe segments 14-K15;

[0075] The fault type of the fault source is identified based on the alarm signal from the sensor and the attribute information of the component corresponding to the collision location, and the corresponding simulation analysis model is selected based on the fault type; the attribute information includes the system classification and media type.

[0076] In this embodiment, the fault type identification method is as follows: Analyze the signal type of the alarm signal; if the signal type is a physical quantity characterizing the presence of liquid or a sudden pressure change, the fault type is initially determined to be fluid medium leakage; when the initially determined fault type is fluid medium leakage, if the system classification of the component belongs to water supply and drainage system or fire water system, the fault type is finally determined to be water pipe leakage; if the fault type is water pipe leakage, a hydraulic calculation model is selected; if the fault type is gas pipeline leakage, a gas flow and diffusion model is selected.

[0077] Based on the real-time operating data and simulation analysis model, numerical simulation calculations are performed in the local analysis network to obtain the dynamic propagation results of the fault. The dynamic propagation results include: a predicted sequence of the state parameters of each component in the local analysis network changing over time, key influencing devices identified based on the predicted sequence, and the expected impact time. In this embodiment, if a hydraulic calculation model is selected, the state parameters are pressure; if a gas flow and diffusion model is selected, the state parameters are flow rate and gas concentration.

[0078] The hydraulic calculation model is a numerical calculation framework based on the laws of mass and momentum conservation in fluid mechanics, used to simulate the unsteady flow of liquid when leakage occurs in a pressure pipeline network. Specifically, the hydraulic calculation model is constructed and numerical simulation calculations are performed based on the real-time operating data as follows:

[0079] The computational nodes are set up, including pipe nodes, boundary nodes, and leakage nodes. Specifically, each pipe segment in the local analysis network is uniformly divided into different pipe segments along its length, and the geometric center of each pipe segment is taken as a pipe node. For example, a 50-meter-long pipe is uniformly divided into 50 1-meter-long pipe segments. Each device in the local analysis network, such as a water pump, water tank, or water source, that is connected to only one pipe is taken as a boundary node, and the pipe node corresponding to the collision position is taken as a leakage node.

[0080] Initial conditions are determined based on real-time operating data: the pipe nodes corresponding to the locations of each pressure sensor and flow counter are identified, and the pressure read by the pressure sensor is used as the initial pressure of the corresponding pipe node, while the flow rate read by the flow counter is used as the initial flow rate of the corresponding pipe node; based on the initial pressure and initial flow rate of the pipe nodes, linear interpolation is used to calculate the initial pressure and initial flow rate of other pipe nodes; the other pipe nodes are: pipe nodes corresponding to pipe sections without pressure sensors or flow counters installed.

[0081] Set the boundary conditions of the local analysis network: use the pressure value of the boundary node with constant pressure in the local analysis network as the pressure boundary value, such as the free liquid level of the high-level water tank, the outlet pressure setting value of the pressure stabilizing pump, etc., and use the flow value of the boundary node with constant flow as the flow boundary value, such as the rated water intake of the water-using equipment; obtain the pressure and flow of the leakage node in real time, and calculate the relationship between the pressure and flow of the leakage node to obtain the boundary of the leakage point.

[0082] The water hammer equation is constructed based on the laws of conservation of mass and momentum. The water hammer equation is then discretized along the direction of the characteristic line to obtain two sets of compatibility equations that propagate along the positive and negative characteristic lines, namely the C+ equation and the C- equation.

[0083] A set of solution equations is established for each computational node in the local analysis network: From the discretized water hammer equations, the compatibility equations for each pipe node in the local analysis network are obtained, resulting in a set of solution equations for the pipe nodes. Since boundary nodes are connected to only one pipe, each boundary node has only one compatibility equation in the discretized water hammer equations. If the boundary node is connected to an upstream pipe, the C+ equation for the corresponding boundary node is obtained from the discretized water hammer equations, and the boundary values ​​of the corresponding boundary node are combined with the C- equations of the pipe nodes connected to the boundary node to obtain the C- equation for the boundary node. If the boundary node is connected to a downstream pipeline, the C-equation of the corresponding boundary node is obtained from the discretized water hammer equation, and the boundary value of the corresponding boundary node is combined with the C+ equation of the pipeline node connected to the boundary node to obtain the C+ equation of the boundary node; the C+ equation and the C-equation of the boundary node constitute the solution equation system of the corresponding boundary node; the C-equation of the pipeline node upstream of the leak node and the C+ equation of the pipeline node downstream of the leak node are extracted, and the boundary of the leak point is combined with the C-equation and the C+ equation respectively to obtain the bivariate nonlinear equation system of the corresponding leak node, that is, the solution equation system;

[0084] Set a computation time step, such as 0.001s, and within each computation time step, use Newton's iteration method to solve the system of equations to obtain the predicted values ​​of pressure and flow rate of each computing node within the corresponding computation time step. The computation time step must satisfy the Courant condition to ensure numerical stability. In the computation within each computation time step, the predicted values ​​of pressure and flow rate of each computing node obtained in the previous computation time step are used as the initial conditions for the current computation time step, and the system of equations is updated based on the initial conditions.

[0085] The predicted pressure value obtained within each calculation time step is compared with the preset safe pressure threshold in real time, and the calculation node whose predicted pressure value is earliest less than the safe pressure threshold is identified; the safe pressure threshold is set according to the minimum operating pressure of the equipment; the calculation node is marked as a critically affected equipment, and the calculation time corresponding to the corresponding calculation time step is used as the expected impact time.

[0086] For example, the pipe segments in the local analysis network are divided into different pipe segments with a length of 1m, and the geometric center of each pipe segment is taken as a pipe node. This includes: dividing the 8m long DN150 pipe segment K11-K12 into 8 pipe segments, and denoting the corresponding pipe nodes as N1-N8; dividing the 6m long DN100 pipe segment K12-K13 into 6 pipe segments, and denoting the corresponding pipe nodes as N9-N14; dividing the 5m long DN80 pipe segment K13-K14 into 5 pipe segments, and denoting the corresponding pipe nodes as N15-N19; and dividing the 7m long DN80 pipe segment K14 into 6 pipe segments. - Pipeline K15 is divided into 7 segments, and the corresponding pipeline nodes are designated as N20-N26. The water pump at the starting point of the DN150 pipeline segment K11-K12 is designated as the boundary node, denoted as B1, and the water-using equipment at the ending point of the DN80 pipeline segment K14-K15 is designated as the boundary node, denoted as B2. The node N12 corresponding to the collision location is designated as the leakage node, with a real-time pressure of 0.8MPa. A pressure sensor is installed at pipeline node N8, with a real-time pressure of 0.85MPa; therefore, the initial pressure of pipeline node N8 is 0.85MPa. A flow counter is installed at pipeline node N15, with a real-time flow rate of 15m³ / h. 3 / h, therefore the initial flow rate of pipe node N15 is 15m³ / h. 3 / h; the initial pressure and initial flow rate of other pipe nodes are obtained by linear interpolation; boundary node B1 is the pump outlet, with a constant pressure of 1.0MPa, therefore the pressure boundary is 1.0MPa; boundary node B2 is the water equipment inlet, with a constant flow rate of 12m³ / h. 3 / h, therefore the flow boundary is 12m 3 / h; Connecting the upstream pipe node N1 to boundary node B1, the C+ equation of boundary node B1, the C- equation of pipe node N1, and the pressure boundary of 1.0 MPa are combined to obtain the C- equation of boundary node B1; Combining the C- equation of upstream pipe node N11 and the C+ equation of downstream pipe node N13 to the leakage point boundary, the solution equations for the leakage node are obtained; The calculation time step is set to 0.001 s; In the first calculation time step, taking leakage node N12 as an example, based on the initial pressure and initial flow rate of leakage node N12, the predicted pressure value of leakage node N12 is calculated to be 0.78 MPa, and the predicted flow rate value is 14.8 m³ / s. 3 / h; In the second calculation time step, using the pressure and flow prediction values ​​obtained in the first calculation time step as initial conditions, the equations are updated, and the predicted pressure value for leakage node N12 is 0.75 MPa, and the predicted flow rate is 14.5 m³ / h. 3 / h; Based on the minimum operating pressure of the equipment, the safety pressure threshold is set to 0.3MPa; The predicted pressure value obtained in each calculation time step is compared with the safety pressure threshold in real time. When iterating to the 120th calculation time step, the predicted pressure value of pipeline node N14 drops to 0.29MPa for the first time. Pipeline node N14 is marked as a critically affected device, and the product of the calculation time step of 0.001s and 120, 0.12s, is taken as the expected impact time.

[0087] Obtain the calculation time step when the predicted pressure value corresponding to all computing nodes is less than the safe pressure threshold, and use the calculation time corresponding to the calculation time step as the expected impact time of the corresponding computing node.

[0088] The gas flow and diffusion model is a composite model that couples the transient flow of compressible gas inside the pipe with its diffusion in the atmosphere after leakage. It is used to simulate pressure wave propagation and flow rate changes within the pipe, and to predict the spatial distribution of leaked gas concentration under the influence of ambient wind. The specific method for constructing the gas flow and diffusion model and performing numerical simulation calculations based on the real-time operating data is as follows:

[0089] Construct a set of governing equations, including: a continuity equation based on the law of conservation of mass, a momentum equation based on the law of conservation of momentum, an energy equation based on the law of conservation of energy, and an ideal gas equation of state.

[0090] Initial conditions are determined based on real-time operating data: The pipe nodes corresponding to the locations of each temperature sensor, pressure sensor, and flow counter are identified; the medium temperature read by the temperature sensor is used as the initial temperature of the corresponding pipe node, the pressure read by the pressure sensor is used as the initial pressure of the corresponding pipe node, and the flow rate read by the flow counter is used as the initial flow rate of the corresponding pipe node; based on the initial temperature, initial pressure, and initial flow rate of the pipe nodes, linear interpolation is used to calculate the initial temperature, initial pressure, and initial flow rate of other pipe nodes; these other pipe nodes are those corresponding to pipe sections without temperature sensors, pressure sensors, or flow counters installed; based on the initial temperature of each pipe node, the initial density of each pipe node is calculated using the ideal gas law; the pipe diameter corresponding to each pipe node is obtained, and the initial flow velocity of each pipe node is calculated based on the pipe diameter and the initial flow rate of each pipe node;

[0091] Set boundary constraints: Determine the starting and ending points of the medium flow based on the flow direction of the medium in the local analysis network, and use the pressure and temperature values ​​of the boundary nodes corresponding to the starting point as the upstream boundary, and use the pressure and flow values ​​of the boundary nodes corresponding to the gas-using equipment or pipeline interface at the ending point as the downstream boundary; obtain the pressure, temperature and flow of the leaking node, and calculate the relationship between pressure, temperature and flow to obtain the boundary of the leaking point;

[0092] Based on the initial conditions and boundary constraints, the finite volume method is used to discretize the control equations, and the control equations are solved in each computation time step to obtain the flow prediction values ​​of all computation nodes.

[0093] Centered on the leak node, an affected area is delineated in the BIM model. The affected area includes all spaces and surrounding buildings within a preset downwind distance, such as all spaces and surrounding buildings within 2 kilometers downwind of the leak node. Real-time meteorological data of the affected area, including wind speed, wind direction, and atmospheric stability level, is acquired, and a Gaussian diffusion model is established based on the building outlines of the BIM model. Based on the Gaussian diffusion model, the predicted flow rates of each calculation node are used as input to calculate the predicted gas concentration values ​​at different times for each spatial location within the affected area.

[0094] For example, the industry-standard Pasquale-Turner classification method is used to determine atmospheric stability, and the straight-line distance between any calculation node and the leakage node in the x-direction of the BIM model is calculated, i.e., the diffusion distance; based on the atmospheric stability and diffusion distance, the diffusion coefficient is obtained by looking up the atmospheric diffusion coefficient table; the flow prediction value of each calculation node is used as the input of the Gaussian diffusion model, and the values ​​are substituted into the Gaussian diffusion model point by point to obtain the gas concentration prediction value of each spatial location at different times;

[0095] The predicted gas concentration is compared in real time with a preset safe concentration threshold to identify the spatial region where the predicted gas concentration first exceeds the safe concentration threshold, thus obtaining the hazardous diffusion area. The corresponding calculation time is used as the estimated impact time. The safe concentration threshold is related to the type of leaked gas; for example, the safe concentration threshold for methane is set to 0.04 kg / m³. 3 ;

[0096] The calculation time step for obtaining the predicted gas concentration value of the space region that is greater than the safe concentration threshold is used as the calculation time corresponding to the calculation time step as the expected impact time of the corresponding space region.

[0097] The collision impact map is generated as follows:

[0098] The predicted sequence of state parameters of each component in the local analysis network changing over time is associated with the spatial coordinates of the BIM model to obtain spatiotemporal data points. Specifically, for water pipe leaks, the predicted pressure value of each calculation node at each calculation time step is bound to the spatial coordinates of the corresponding calculation node in the BIM model; for gas pipeline leaks, the predicted flow rate value of each calculation node at each calculation time step is bound to the spatial coordinates of the corresponding calculation node in the BIM model, and at the same time, the predicted gas concentration values ​​at each spatial location in the affected area at each calculation time step are bound to the corresponding spatial coordinates.

[0099] Based on the spatiotemporal data points, the BIM model is divided into different impact level areas and then visualized and rendered.

[0100] In this embodiment, the hazardous diffusion area or critically affected equipment and its surrounding preset area, such as the pipeline section directly connected to the critically affected equipment, is designated as the core leakage area, and the core leakage area is filled with red in the BIM model.

[0101] In the outer region of the core leakage zone, calculation nodes with predicted pressure values ​​less than the safe pressure threshold, or spatial regions with predicted gas concentration values ​​greater than the safe concentration threshold, are extracted to obtain secondary impact nodes or secondary impact areas. The difference between the calculation time corresponding to the secondary impact node or secondary impact area and the initial calculation time is calculated to obtain a first time difference, and the difference between the expected impact time and the initial calculation time is calculated to obtain a second time difference. The ratio of the first time difference to the second time difference is calculated. If the ratio is greater than a preset multiple threshold, the secondary impact area or secondary impact node and its surrounding preset area, such as the pipeline segment corresponding to the secondary impact node and its adjacent calculation node, are marked as secondary protection zones, and the secondary protection zones are filled with orange in the BIM model. The multiple threshold is greater than 1 and is set according to the risk propagation time gradient. For example, setting the multiple threshold to 2 means that when the ratio is greater than 2, the corresponding area has relatively sufficient emergency buffer time.

[0102] Extract the computational nodes whose predicted pressure values ​​are always greater than or equal to the safe pressure threshold, or the spatial regions whose predicted gas concentration values ​​are always less than the safe concentration threshold; mark the corresponding spatial regions or computational nodes and their surrounding regions in the local analysis network as safety buffers, and fill the safety buffers with green in the BIM model.

[0103] The processing instruction sequence is generated in the following way:

[0104] Based on the collision impact map, in the local analysis network, valve component sets located upstream and downstream of the core leakage area, and functioning as isolation valves, are retrieved respectively; the isolation valve with the shortest connection path to the core leakage area is selected from the upstream valve component set as the upstream control valve, and the isolation valve with the shortest connection path to the core leakage area is selected from the downstream valve component set as the downstream control valve; the upstream and downstream control valves are taken as the primary operation targets, and a processing command with closure as the operation action is generated;

[0105] The difference between the estimated impact time and the current time for all computing nodes or spatial regions within the secondary protection zone is calculated to obtain a third time difference set. All third time differences in the third time difference set are sorted in ascending order, and computing nodes or spatial regions corresponding to third time differences less than a preset emergency response time threshold are selected to obtain emergency targets. The emergency response time threshold is used to select emergency targets that must be intervened in a very short time. It is based on the minimum response cycle of the automatic control system and the human-machine collaboration limit. For example, in a high-speed transient flow scenario, the pressure wave propagation speed is about 1000m / s. If it is predicted that any critical node will exceed the limit after 0.2 seconds, manual operation is no longer possible. The processing instruction corresponding to the critical node must be placed at the beginning of the processing instruction sequence. Therefore, the emergency response time threshold is set to 0.2s.

[0106] For each emergency target, in the local analysis network, the valve that can control the flow or pressure of the emergency target and functions as an isolation valve is located, the secondary operation target of the corresponding emergency target is obtained, and the processing command with the operation action of closing or regulating is generated.

[0107] Based on the media flow direction of the local analysis network, the processing instructions corresponding to the primary operation target and the processing instructions corresponding to the emergency target are sorted and prioritized in a safe manner to obtain a processing instruction sequence. Specifically, the processing instructions corresponding to the primary operation target are executed first, and the downstream control valve is closed first, followed by the upstream control valve. For the processing instructions corresponding to the emergency target, their execution order is consistent with the ascending order of the third time difference.

[0108] The guidance execution module breaks down the processing instruction sequence into sequentially executed guidance steps, and executes the guidance steps through context verification and locking mechanisms;

[0109] like Figure 2 As shown, the specific method for breaking down the processing instruction sequence into sequentially executed bootstrapping steps and executing the bootstrapping steps through context verification and locking mechanisms is as follows:

[0110] An instruction decomposition library is constructed based on standard operating procedures, equipment operation manuals, and expert experience in the field of operation and maintenance. This library consists of mapping records of different operations and steps, with each mapping record serving as a decomposition template. Each decomposition template includes an operation action and a sequence of sub-steps. Each sub-step in the sequence includes: a step action code, a step description, expected results, safety tips, and equipment requirements, such as the need to wear insulating gloves. The step action code is a standardized action identifier used for program invocation, such as verifying equipment identity. The step description is a readable operational instruction for operation and maintenance personnel.

[0111] Based on the operation target and operation action corresponding to any processing instruction, the corresponding decomposition template is matched from the instruction decomposition library to obtain the target template; based on the corresponding processing instruction, the target template is instantiated to obtain the guiding steps corresponding to the processing instruction.

[0112] The bootstrap steps corresponding to each processing instruction are sorted according to the order of the processing instruction sequence to obtain the bootstrap steps to be executed sequentially.

[0113] Optionally, the specific method for matching the corresponding decomposition template from the instruction decomposition library is as follows: using the operation action as the primary search key and the device type corresponding to the operation target as the secondary search key, a joint query is performed in the instruction decomposition library to filter out decomposition templates with the same operation action and completely identical device type, which are then used as the target template; the specific method for instantiating the target template is as follows: reading the operation sub-step sequence in the target template and dynamically binding each operation sub-step in the operation sub-step sequence with the processing instruction and real-time running data.

[0114] The guidance steps and related 3D BIM spatial information are simultaneously pushed to the AR glasses terminal worn by the on-site maintenance personnel; the on-site maintenance personnel arrive at the corresponding task area according to the guidance steps and 3D BIM spatial information, and begin to execute the guidance steps in sequence.

[0115] Specifically, the AR glasses terminal guides on-site maintenance personnel to perform each guidance step through a context verification and locking mechanism; the context verification and locking mechanism is as follows:

[0116] For devices that support remote control, a temporary virtual lockout signal is sent through the IoT controller of each target device before the boot process is executed, so as to ensure that the local manual control panel of the device is temporarily disabled.

[0117] In the AR glasses terminal, based on the 3D BIM spatial information corresponding to the current guidance step, the target device specified by the current guidance step is highlighted in the form of a guide arrow; the target device refers to the operation object of the current guidance step; when the visual sensor built into the AR glasses terminal captures the target device, it reminds the on-site maintenance personnel to scan the identification code attached to the target device, such as a QR code or barcode, to verify identity and confirm that the current gaze focus is consistent with the identity of the target device.

[0118] When the target device passes authentication, extract the security prompts and equipment requirements in the current guidance step, the real-time operating data of the target device, and the estimated impact time of the target device, and confirm them with the on-site maintenance personnel through an interactive interface on the AR glasses terminal, such as please confirm that the device identifier is V-101 and the estimated impact time is 50 seconds, and at the same time send an unlocking signal to the target device.

[0119] When the target device receives the unlocking signal, it executes the guided step according to the step action code of the current guided step, through the operation guidance displayed on the AR glasses terminal; for example, for the action of closing the valve, the AR glasses terminal dynamically displays the direction and number of rotations of the valve's handwheel;

[0120] After each guided step is completed, the on-site maintenance personnel select the completion status through the AR glasses terminal based on the expected results and record the actual completion time of the guided step.

[0121] The optimization learning module is used to build an emergency event database and, when a new emergency event occurs, perform case matching in the emergency event database to obtain the corresponding fault propagation model.

[0122] Specifically, the emergency event database is used to store the entire chain of data for each emergency event response process, forming a queryable and analyzable structured emergency case. Each structured emergency case includes at least: event feature information, including the three-dimensional coordinates of the collision location in the BIM model and the fault type; input data snapshots, i.e., the real-time operational data on which the fault propagation model was built; simulation process data, including the fault propagation model used, key parameters, prediction results, and the generated sequence of processing instructions; and on-site execution data, including the actual completion time and completion status of each guiding step.

[0123] When a new emergency occurs, the optimization learning module initiates a case matching process: extracting the fault type and collision location from the new emergency, and matching all emergency events with the same fault type from the emergency event database to obtain a candidate event set;

[0124] Calculate the spatial similarity between each candidate event in the candidate event set and the new emergency event, and extract the maximum spatial similarity value; take the candidate event corresponding to the maximum spatial similarity value as the best matching event;

[0125] In this embodiment, the spatial similarity is calculated as follows: the area of ​​the overlapping region between the local analysis network corresponding to the candidate event and the local analysis network corresponding to the new emergency event is counted, and the sum of the area of ​​the local analysis network corresponding to the candidate event and the area of ​​the local analysis network corresponding to the new emergency event is calculated; the ratio of the area of ​​the overlapping region to the sum of the areas of the local analysis networks is used as the spatial similarity.

[0126] If the maximum spatial similarity value is greater than the preset similarity threshold, such as 0.8, then the corresponding fault propagation model and the corresponding processing instruction sequence are directly used as the new fault propagation model and the corresponding processing instruction sequence for the emergency event.

[0127] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0128] The embodiments of this application have been described above with reference to the accompanying drawings. However, this application is not limited to the specific embodiments described above. The specific embodiments described above are merely illustrative and not restrictive. Those skilled in the art can make many other forms under the guidance of this application without departing from the spirit and scope of protection of this application, and these forms are all within the protection scope of this application.

Claims

1. A pipeline collision emergency handling system for BIM operation and maintenance, characterized in that, It includes a data fusion module, a risk simulation module, a guided execution module, and an optimization learning module; The data fusion module is used to receive emergency events and locate the collision location based on the emergency events; The data fusion module is also used to synchronously acquire real-time operational data at the collision location; The risk simulation module constructs a fault propagation model based on the real-time operating data and generates a collision impact diagram based on the fault propagation model; the risk simulation module also generates a sequence of processing instructions based on the collision impact diagram; The guidance execution module breaks down the processing instruction sequence into sequentially executed guidance steps, and executes the guidance steps through context verification and locking mechanisms; The optimization learning module is used to build an emergency event database and, when a new emergency event occurs, perform case matching in the emergency event database to obtain the corresponding fault propagation model. The specific method for constructing the fault propagation model is as follows: The specific equipment or pipeline segment corresponding to the collision location is marked as the fault source, and a network traversal of limited depth is performed in the BIM model with the fault source as the center, based on the upstream and downstream logical connection relationship, to obtain the local analysis network. The fault type of the fault source is identified based on the alarm signal from the sensor and the attribute information of the component corresponding to the collision location, and the corresponding simulation analysis model is selected based on the fault type. Based on the real-time operating data and simulation analysis model, numerical simulation calculations are performed in the local analysis network to obtain the dynamic propagation results of the fault. The dynamic propagation results include: a predicted sequence of the state parameters of each component in the local analysis network changing over time, key influencing devices identified based on the predicted sequence, and the expected impact time. The collision impact map is generated as follows: the predicted sequence of the state parameters of each component in the local analysis network changing over time is associated with the spatial coordinates of the BIM model to obtain spatiotemporal data points; based on the spatiotemporal data points, the BIM model is divided into different impact level regions and then visualized and rendered. The boot execution module is configured with a boot step decomposition and execution strategy; the boot step decomposition and execution strategy specifically includes: A command decomposition library was built based on standard operating procedures, equipment operation manuals and expert experience in the field of operation and maintenance. Based on the operation target and operation action corresponding to any processing instruction, the corresponding decomposition template is matched from the instruction decomposition library to obtain the target template; based on the corresponding processing instruction, the target template is instantiated to obtain the guiding steps corresponding to the processing instruction. The guidance steps are pushed to the AR glasses terminal worn by the on-site maintenance personnel, and after the on-site maintenance personnel arrive at the corresponding task area, the on-site maintenance personnel are guided to execute each guidance step in sequence through context verification and locking mechanism; The context verification and locking mechanism specifically includes: Before performing the bootstrapping steps, a temporary virtual latching signal is sent to the IoT controller of each target device; Based on the 3D BIM spatial information corresponding to the current guidance step, the target device specified in the current guidance step is highlighted in the form of a guide arrow; When the visual sensor built into the AR glasses terminal detects the target device, it prompts on-site maintenance personnel to scan the identification code attached to the target device for identity verification. When the target device passes authentication, an interactive interface is used on the AR glasses terminal to confirm the authentication and an unlocking signal is sent to the target device. When the target device receives the unlock signal, it executes the guidance step according to the step action code of the current guidance step, through the operation guide displayed on the AR glasses terminal.

2. The pipeline collision emergency handling system for BIM operation and maintenance as described in claim 1, characterized in that, The fault propagation model construction strategy also includes, when a hydraulic calculation model is selected, the specific steps of performing numerical simulation calculations based on real-time operational data include: Configure computing nodes, including pipe nodes, boundary nodes, and leak nodes; Initial conditions are determined based on real-time operational data, and boundary conditions are set for the local analysis network. The pressure value of the boundary node with constant pressure in the local analysis network is used as the pressure boundary value, and the flow value of the boundary node with constant flow is used as the flow boundary value; the pressure and flow of the leaking node are acquired in real time, and the relationship between the pressure and flow of the leaking node is calculated to obtain the boundary of the leaking point. The water hammer equation is constructed based on the laws of conservation of mass and momentum. The water hammer equation is then discretized along the direction of the characteristic line to obtain the compatibility equations, namely the C+ equation and the C- equation, which propagate along the positive and negative characteristic lines, respectively.

3. The pipeline collision emergency handling system for BIM operation and maintenance as described in claim 2, characterized in that, When selecting a hydraulic calculation model, the steps for numerical simulation based on real-time operational data also include: From the discretized water hammer equation, the compatibility equation of each pipe node in the local analysis network is obtained, and the solution equation set of the pipe node is obtained. If the boundary node is connected to an upstream pipeline, the C+ equation of the corresponding boundary node is obtained from the discretized water hammer equation, and the boundary value of the corresponding boundary node is combined with the C- equation of the pipeline node connected to the boundary node to obtain the C- equation of the boundary node. If the boundary node is connected to a downstream pipeline, the C-equation of the corresponding boundary node is obtained from the discretized water hammer equation, and the boundary value of the corresponding boundary node is combined with the C+ equation of the pipeline node connected to the boundary node to obtain the C+ equation of the boundary node. Extract the C- equation of the pipeline node upstream of the leak node and the C+ equation of the pipeline node downstream of the leak node, and then combine the boundary of the leak point with the C- equation and the C+ equation to obtain the solution equation system for the corresponding leak node.

4. The pipeline collision emergency handling system for BIM operation and maintenance as described in claim 3, characterized in that, When selecting a hydraulic calculation model, the steps for numerical simulation based on real-time operational data also include: Set the computation time step, and iteratively solve the system of equations within each computation time step to obtain the predicted values ​​of pressure and flow rate of each computing node within the corresponding computation time step. In the calculation within each calculation time step, the predicted values ​​of pressure and flow of each calculation node obtained in the previous calculation time step are used as the initial conditions for the current calculation time step, and the solution equation system is updated based on the initial conditions. The predicted pressure value obtained in each calculation time step is compared with the preset safe pressure threshold in real time, and the calculation node whose predicted pressure value is earliest less than the safe pressure threshold is identified. The computing nodes are marked as key impact devices, and the computing time corresponding to the corresponding computing time step is used as the expected impact time.

5. The pipeline collision emergency handling system for BIM operation and maintenance as described in claim 4, characterized in that, The fault propagation model construction strategy also includes, when using a gas flow and diffusion model, the specific steps of numerical simulation calculation based on real-time operating data include: Construct a set of governing equations; determine initial conditions based on real-time runtime data, and set boundary constraints; Based on the initial conditions and boundary constraints, the control equations are discretized, and the control equations are solved within each computation time step to obtain the flow prediction values ​​of all computation nodes. Centered on the leak node, the area that can be affected is delineated in the BIM model; real-time meteorological data of the area that can be affected is obtained, and a Gaussian diffusion model is established in combination with the building outline of the BIM model; Based on the Gaussian diffusion model, the predicted flow rate of each computing node is used as input to calculate the predicted gas concentration at each spatial location within the affected area at different times. The predicted gas concentration is compared with a preset safe concentration threshold in real time to identify the spatial region where the predicted gas concentration is earliest greater than the safe concentration threshold, thus obtaining the dangerous diffusion area, and the corresponding calculation time is used as the expected impact time.

6. The pipeline collision emergency handling system for BIM operation and maintenance as described in claim 1, characterized in that, The risk simulation module is configured with a collision impact diagram generation strategy; The collision impact map generation strategy includes: The hazardous diffusion area or the critically affected equipment and its surrounding pre-defined area are designated as the core leakage area, and the core leakage area is filled with red in the BIM model; In the outer region of the core leakage zone, calculation nodes with predicted pressure values ​​less than the safe pressure threshold, or spatial regions with predicted gas concentration values ​​greater than the safe concentration threshold, are extracted to obtain secondary influence nodes or secondary influence regions.

7. The pipeline collision emergency handling system for BIM operation and maintenance as described in claim 6, characterized in that, The collision impact map generation strategy also includes; Calculate the difference between the calculation time and the initial calculation time corresponding to the secondary affected node or secondary affected area to obtain the first time difference, and calculate the difference between the expected impact time and the initial calculation time to obtain the second time difference; Calculate the ratio of the first time difference to the second time difference. If the ratio is greater than a preset multiple threshold, mark the secondary influence area or secondary influence node and its surrounding preset area as a secondary protection zone, and fill the secondary protection zone with orange in the BIM model. Extract the computational nodes whose predicted pressure values ​​are always greater than or equal to the safe pressure threshold, or the spatial regions whose predicted gas concentration values ​​are always less than the safe concentration threshold; mark the corresponding spatial regions or computational nodes and their surrounding regions in the local analysis network as safety buffers, and fill the safety buffers with green in the BIM model.

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