Railway sand table model three-dimensional visualization system based on BIM

Abstract

The invention relates to the technical field of railway sand table models, in particular to a BIM-based railway sand table model three-dimensional visualization system, which comprises a data acquisition module, a collaborative modeling module, a weather simulation module, an interaction module, a data management module and a fault diagnosis module. According to the system, key node information is extracted through image recognition and data driving, modeling precision is optimized, multi-line collaborative modeling and linkage are achieved through a uniform interface, weather simulation is built in to analyze extreme environmental influences, multi-view switching and intelligent navigation functions are provided, and real-time data updating and exception handling are supported. According to the method, the three-dimensional modeling precision, the cooperation capability and the user interaction experience can be remarkably improved, and comprehensive technical support is provided for railway design optimization, risk assessment and training demonstration.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of railway sand table model, in particular to a railway sand table model three-dimensional visualization system based on BIM. BACKGROUND

[0002] In the prior art, railway sand table model realizes three-dimensional visualization display of railway line, station yard and related facilities through BIM technology, providing intuitive reference for engineering planning, construction simulation and training. The existing sand table system mainly relies on manual modeling or static data import, can perform basic display on the line and equipment, and realize simulation of train running path.

[0003] However, the existing railway sand table model still has certain limitations in actual application. First, the three-dimensional modeling precision needs to be improved, and the presentation of key structure nodes such as turnout, curve and slope change point is not accurate enough, affecting the realism of simulation. Secondly, the collaborative modeling and linkage display capability of multiple lines is insufficient, and the data sharing and interaction support between outer loop test line, urban rail test line and calibration test line and other multiple lines is limited. In addition, the simulation capability of the existing system for the influence of railway facilities under extreme weather conditions is weak, especially the simulation of the electric performance of the catenary under rain and snow weather and the electric connection state of the train pantograph is not perfect. At the same time, the user interaction experience of the sand table system has certain limitations, lacks multi-view switching, intelligent navigation and free observation functions, affecting the operation convenience and decision-making assistance effect.

[0004] Therefore, it is urgent to develop a railway sand table three-dimensional visualization system that can improve three-dimensional modeling precision, support multi-line collaboration and data interaction, have railway facility simulation capability under extreme weather conditions, and provide flexible multi-view switching and intelligent navigation function, to meet the needs of modern railway engineering design, experimental verification and training application. SUMMARY

[0005] Therefore, the present application proposes a railway sand table model three-dimensional visualization system based on BIM, aiming to solve the problems of insufficient three-dimensional modeling precision, limited multi-line collaborative modeling capability, imperfect extreme weather simulation and insufficient user interaction experience of the current railway sand table model.

[0006] The present application proposes a railway sand table model three-dimensional visualization system based on BIM, comprising: The acquisition module is configured to obtain key node information and structure feature data of the railway line, and perform geometric enhancement and texture optimization processing on the key nodes; The modeling module is electrically connected with the acquisition module, and the modeling module is configured to determine data sharing and operation linkage between multiple lines based on a unified data interface and model association mechanism; The weather simulation module is electrically connected with the modeling module, and is configured to simulate the influence of different environmental conditions on the railway facilities, and analyze the change of the catenary conductive performance and the electrical connection state of the train pantograph; The interaction module is electrically connected with the weather simulation module, and is configured to provide multi-view switching and intelligent navigation functions, and determine the key areas locked by the user in the sand table; The data management module is electrically connected with the interaction module, and is configured to realize centralized storage and real-time update of BIM model data, measured data and simulation results; The fault diagnosis module is electrically connected with the data management module, and is configured to monitor the running state of the system, and trigger the fault handling mechanism when an abnormality is detected.

[0007] Further, the acquisition module is also configured to extract key node information of turnout, curve, slope change point, bridge and tunnel from BIM model or measured line data based on image recognition technology or data driven method; The acquisition module is also configured to adjust the geometric shape of the key node and optimize the texture details.

[0008] Further, the acquisition module is also configured to bridge bearing characteristics, tunnel ventilation conditions and station layout parameters as key node information; The acquisition module is also configured to generate structure feature data in combination with track material properties and catenary installation height.

[0009] Further, the modeling module is also configured to synchronously update the running state information of the outer loop test line, the urban rail test line and the calibration test line based on the model association mechanism; The modeling module is also configured to determine the running parameters of multiple lines for comparison by the user on the same interface.

[0010] Further, the weather simulation module is configured with a physical model; The weather simulation module is also configured to simulate the influence of rainy, snowy, icy and high temperature conditions on the railway facilities, and analyze the change of the catenary conductive performance and the electrical connection state of the train pantograph through parameterized simulation method.

[0011] Further, the weather simulation module is also configured to simulate the influence of thunderstorm weather on the signal system and the interference of sandstorm weather on the visibility, and dynamically display the simulation results on the sand table interface.

[0012] Further, the interaction module is configured with first person, third person, top view and bird's eye view; The interaction module is also configured to realize the automatic focusing function of key nodes in combination with path planning algorithm.

[0013] Further, the interaction module is also configured with a virtual reality device interface; The interaction module is also configured to operate the sand table model based on the VR device.

[0014] Further, the data management module is also configured to build a unified data management platform; The data management module is also configured to store BIM model data, measured data, simulation results and user operation records; The data management module is also configured to fuse and version control multi-source data.

[0015] Further, the fault diagnosis module is also configured to monitor the running state of the system in real time, wherein, When data loss or simulation result deviation exceeds the preset range is detected, the fault diagnosis module triggers the fault handling mechanism of disconnecting the abnormal module connection, generating a fault report and attempting to reload the data.

[0016] Compared with the prior art, the beneficial effects of the present application are that: through the automatic collection and geometric enhancement, texture optimization of the key nodes and structural feature data of the railway line by the collection module, the accuracy and realism of the sand table model are improved, the key nodes such as turnout, curve and slope of the railway line can be accurately presented in the three-dimensional visualization system, thereby enhancing the simulation reliability and engineering reference value. Secondly, the modeling module is electrically connected with the collection module, and through a unified data interface and model association mechanism, data sharing and running linkage of multiple lines are realized, supporting simultaneous modeling and simulation of multiple lines such as outer loop test line, urban rail test line, calibration test line, etc., so that the sand table system can perform multi-line collaborative display and dynamic analysis, and the application ability of the system in comprehensive experiment, line optimization and dispatching research is improved. In addition, the weather simulation module can simulate the influence of rain, snow, icing and other environmental conditions on railway facilities, and analyze the contact net conductive performance and the electric connection state of the train pantograph, thereby enhancing the simulation capability of the sand table system in extreme weather environment, and providing a scientific basis for railway facility design and risk assessment. Further, the interaction module provides multi-view switching and intelligent navigation functions, so that users can freely observe and lock key areas in the sand table, improving operation convenience and interaction experience, facilitating engineering design verification, experimental demonstration and training use. At the same time, the data management module realizes centralized storage and real-time update of BIM model data, measured data and simulation results, ensuring the consistency of the sand table model and the actual line information, and providing reliable guarantee for the long-term operation and data tracing of the system. Finally, the fault diagnosis module can monitor the running state of the system in real time, and trigger the fault handling mechanism when an abnormality is detected, thereby improving the stability and reliability of the system, and ensuring the safety and continuity of the three-dimensional sand table visualization system in long-term operation. BRIEF DESCRIPTION OF DRAWINGS

[0017] Various other advantages and benefits will become apparent to those of ordinary skill in the art upon reading the following detailed description of the preferred embodiments with reference made to the accompanying drawings. The drawings are for purposes of illustration only and are not intended to be limiting in Figure 1 A functional block diagram of a BIM-based railway sand table model three-dimensional visualization system according to an embodiment of the present application is provided. Figure 2 A flowchart of a BIM-based railway sand table model three-dimensional visualization system according to an embodiment of the present application is provided. DETAILED DESCRIPTION

[0018] Exemplary embodiments of the present disclosure will be described in detail with reference to the accompanying drawings. Although exemplary embodiments of the present disclosure are shown in the drawings, it is understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments set forth herein. Rather, these embodiments are provided so that the present disclosure can be more thoroughly understood, and the scope of the present disclosure can be accurately conveyed to those skilled in the art. It should be noted that the embodiments in the present application and the features in the embodiments can be combined with each other without conflict. The present application will be described in detail below with reference to the accompanying drawings and in conjunction with the embodiments.

[0019] As shown in Figures 1-2 In some embodiments of the present application, the present embodiment provides a BIM-based railway sand table model three-dimensional visualization system, which comprises a collection module, a modeling module, a weather simulation module, an interaction module, a data management module, and a fault diagnosis module.

[0020] Specifically, the collection module is configured to obtain key node information and structural feature data of the railway line, and to perform geometric enhancement and texture optimization processing on the key nodes.

[0021] Specifically, the collection module is further configured to extract key node information of turnouts, curves, slope change points, bridges, and tunnels from BIM models or measured line data based on image recognition technology or data-driven methods; the collection module is further configured to perform geometric shape adjustment and texture detail optimization on the key nodes.

[0022] Specifically, the collection module is further configured to take bridge load-bearing characteristics, tunnel ventilation conditions, and station layout parameters as key node information; the collection module is further configured to generate structural feature data in combination with track material properties and catenary installation height.

[0023] It can be understood that the key node information of the railway line is automatically extracted from the BIM model or the measured line data by image recognition technology or data-driven method. The key nodes include structural elements such as turnout, curve, slope change point, bridge, tunnel and station layout. The module first pre-processes the input BIM model data or measured data, including coordinate standardization, noise filtering and data format conversion, to ensure the compatibility and availability of data from different sources. Then, based on image recognition or feature extraction algorithm, the key nodes are automatically recognized, and the geometric coordinates, direction, curvature and related attribute information of the nodes in three-dimensional space are extracted, realizing accurate positioning of complex line structure. Secondly, after the identification of the key nodes, the geometry of the nodes is optimized and adjusted by the collection module. Specifically, for turnouts and curves, the system corrects the shape according to the curve radius, slope change and track gauge requirements; for bridge nodes, the three-dimensional model geometry is adjusted according to the load-bearing characteristics and bridge structure type; for tunnel nodes, the three-dimensional model structure is optimized according to the ventilation conditions and cross-section shape. At the same time, the module optimizes the details of the node texture, including track material, catenary height and texture rendering of auxiliary facilities, making the model more realistic in vision and reflecting the real engineering information in structural characteristics. Finally, the collection module generates structural feature data combining track material properties, catenary installation height, bridge load-bearing capacity, tunnel ventilation conditions and station layout parameters. These structural feature data not only describe the geometric shape of the nodes, but also include physical properties, engineering constraints and operating characteristics, providing basic data support for simulation analysis, multi-line coordination and extreme environment simulation of the sand table system. For example, the bridge load-bearing characteristic data can be used to analyze the load distribution when the train passes through the bridge; the catenary installation height data can be used to calculate the electrical contact state between the pantograph and the catenary; and the station layout parameters can be used for train dispatching simulation and operation analysis.

[0024] It can be seen that the collection module can integrate the key node information, geometric shape, texture details and structural feature data of the railway line into a high-precision, simulative three-dimensional data model, providing accurate and reliable basic data for the modeling module, ensuring the authenticity, precision and operability of the railway sand table model in three-dimensional visualization, simulation analysis and multi-line coordination.

[0025] Specifically, the modeling module is electrically connected with the collection module, and the modeling module is configured to determine data sharing and operation linkage between multiple lines based on a unified data interface and model association mechanism Specifically, the modeling module is also configured to synchronize the update of the running state information of the outer loop test line, the urban rail test line and the calibration test line based on the model association mechanism; the modeling module is also configured to determine the comparison of the running parameters of multiple lines by the user on the same interface.

[0026] It can be understood that the modeling module receives the key node information and structural feature data of the railway line through electrical connection with the acquisition module, and uniformly processes and manages the data. In order to realize the collaborative modeling of multiple lines, the modeling module first performs standardized processing on the data from different lines, including coordinate unification, attribute field alignment, unit conversion and format conversion, to ensure that the loop test line, urban rail test line and calibration test line and other line models are represented in a unified three-dimensional coordinate system and data structure. This standardized processing not only ensures the compatibility of the data, but also provides a basis for subsequent model association and operation linkage. Secondly, based on the standardized data, the modeling module uses the model association mechanism to realize the dynamic association and synchronous update between multiple line models. Specifically, the key nodes and operation parameters in each line model are mapped to the corresponding nodes in the associated model, and when the train position, speed, track state or key node information of a certain line changes, the system automatically synchronizes the changes to other related line models through the association mechanism, ensuring that the state information of each line is consistent, and realizing the linkage simulation of multiple lines. In addition, the modeling module also realizes the visualization comparison function of the operation parameters of multiple lines. The system superimposes and displays the operation parameters of different lines on the same interface through data query and parameter mapping, supports the comparison and analysis of speed curves, train position, track state and key node information. Users can select a single line or multiple lines for dynamic observation in the interface, and the system can adjust the display content and perspective in real time according to user operations, facilitating comparison and analysis, scheduling optimization and experimental verification. Finally, the core technology of the modeling module also includes data synchronization logic and state update mechanism. The system uses a combination of event triggering and timed refreshing to ensure the real-time performance and data consistency of the line model. In the event triggering mode, when the acquisition module or user operation causes a state change, the association mechanism immediately triggers the update of the corresponding line model; in the timed refreshing mode, the system synchronously checks and updates all line states at a predetermined period to prevent data loss or delay. Through this mechanism, the sand table system can maintain high-precision, real-time and reliable data interaction in multi-line collaborative simulation.

[0027] It can be seen that the modeling module realizes the collaborative modeling and dynamic linkage of multiple railway lines through unified data interface, model association mechanism, real-time state synchronization and multi-line visualization comparison. The technical principle not only improves the simulation accuracy and data consistency of the sand table system, but also supports users to comprehensively analyze the operation state of multiple lines, providing complete data and visualization support for railway line optimization, experimental verification and scheduling research.

[0028] Specifically, the weather simulation module is electrically connected with the modeling module, and the weather simulation module is configured to simulate the influence of different environmental conditions on railway facilities and analyze the change of catenary conductive performance and the electrical connection state of the train pantograph.

[0029] Specifically, the weather simulation module is configured with a physical model; the weather simulation module is also configured to simulate the effects of rainy weather, snowy weather, icing conditions, and high-temperature conditions on railway facilities, and to analyze changes in the contact net conductive performance and the electrical connection state of the train pantograph through a parameterized simulation method.

[0030] Specifically, the weather simulation module is also configured to simulate the effects of thunderstorm weather on the signal system and the interference of sand and dust weather on visibility, and to dynamically display the simulation results on the sand table interface.

[0031] It can be understood that the weather simulation module, through electrical connection with the modeling module, obtains the three-dimensional model and operating state data of the railway line and key facilities, providing dynamic simulation capability under environmental conditions for the railway sand table system. The module has a built-in physical model for describing the mechanism of different environmental conditions on railway facilities, including force, conductivity, resistance, and visibility, etc. multi-dimensional effects, providing basic physical support for train operation and line equipment simulation. Secondly, in the simulation process, the weather simulation module uses a parameterized simulation method to convert different weather conditions such as rain, snow, icing, and high temperature into parameters affecting line and facility performance. For example, rain and snow weather simulates changes in electrical connection by reducing the conductivity coefficient of the contact net, icing weather analyzes the contact state of the pantograph and the contact net by increasing the friction resistance and changing the conductive contact area, and high-temperature weather evaluates the stability of the track and structural facilities through thermal expansion and material performance changes. This parameterization can reflect the changes in train operating state and line performance in real time in the three-dimensional sand table model, making the simulation results highly correspond to actual engineering conditions. In addition, the weather simulation module can also simulate the electromagnetic interference of thunderstorm weather on the signal system and the effects of sand and dust weather on visibility. Through dynamic calculation of signal transmission performance and visual visibility parameters, the system can adjust train operation simulation and sand table visualization in real time, allowing users to intuitively observe the potential impact of extreme weather on train operation safety and line facilities. Finally, the simulation results are dynamically displayed through the sand table interface, supporting real-time interaction and multi-angle observation. The system integrates environmental conditions, line status, and train operation into a unified visualization interface, allowing users to observe changes in weather impact and train operation parameters simultaneously, thereby providing scientific basis for railway line design optimization, operation safety assessment, and emergency response planning.

[0032] Specifically, the interaction module is electrically connected with the weather simulation module, and the interaction module is configured to provide multi-angle switching and intelligent navigation functions to determine the user's locking of key areas in the sand table.

[0033] Specifically, the interaction module is configured with first-person, third-person, overhead, and bird's-eye view angles; the interaction module is also configured with an automatic focusing function for key nodes in combination with path planning algorithms.

[0034] Specifically, the interaction module is further configured with a virtual reality device interface; the interaction module is further configured to operate the sand table model based on the VR device.

[0035] It can be understood that the interaction module, through electrical connection with the weather simulation module, obtains the three-dimensional model and dynamic simulation state data of the railway line and facilities in the sand table, providing users with interactive three-dimensional observation and operation functions. Through the multi-view switching function, including first-person, third-person, overhead, and bird's eye view, the module realizes free observation of the sand table model by the user, enabling the user to comprehensively understand the line structure, key nodes, and train operation state from different angles and distances, thereby improving the intuitiveness of observation and the comprehensiveness of analysis. Secondly, the interaction module combines with the path planning algorithm to realize the automatic focusing function of key nodes. When the user selects a specific line, device, or operation state, the system can automatically plan the observation path, quickly focus the view to the key node, and dynamically adjust the view angle and zoom ratio, enabling the user to intuitively locate and analyze the key area. This automatic focusing mechanism not only improves the operation efficiency, but also ensures the user operation accuracy in the complex sand table environment with multiple lines and nodes. Finally, the interaction module is configured with a virtual reality (VR) device interface and supports operation of the sand table model based on the VR device. Through the VR device, the user can realize immersive three-dimensional interaction, including translating, rotating, and zooming the sand table model, and even "roaming" inside the model to observe the line structure, bridges, tunnels, and station layout at close range. This virtual reality interaction not only enhances the user experience, but also provides an intuitive operation environment for training, demonstration, and experimental verification.

[0036] Specifically, the data management module is electrically connected with the interaction module, and the data management module is configured to realize centralized storage and real-time update of BIM model data, measured data, and simulation results Specifically, the data management module is further configured to build a unified data management platform; the data management module is further configured to store BIM model data, measured data, simulation results, and user operation records; the data management module is further configured to fuse and version control multiple sources of data.

[0037] It can be understood that the data management module, as the data core management unit of the railway sand table system, is electrically connected with the interaction module and is responsible for centralized storage, integration and real-time updating of BIM model data, measured data, simulation results and user operation records from various modules. The module first builds a unified data management platform to standardize the multi-source data accessed to the system, including field alignment, unit conversion, coordinate system unification and data format conversion, so as to ensure the compatibility and processability of data from different modules and sensors under the same platform. The data management module classifies and structures the data. The BIM model data includes three-dimensional structure information and attribute data of track geometry, turnout, bridge, tunnel, station and related facilities; the measured data includes train running state, track detection data, catenary parameter and environmental monitoring data; the simulation results include weather influence simulation, line operation state, pantograph contact situation and multi-line linkage state; the user operation records include view switching, navigation operation and key node focusing behavior. The module realizes fast access and management of different types of data by establishing a multi-level data index and label system. To ensure the consistency and availability of multi-source data, the data management module uses data fusion technology to align, merge and logically check the data from the BIM model, measured collection and simulation module. During the fusion process, the module removes duplicate data, integrates conflict data through a pre-set priority or weighting algorithm, and performs error correction and rationalization processing on key parameters, thereby generating a unified data set that can be used for modeling, simulation and interactive operation. In addition, the data management module also provides version control and historical data management functions. Each data update or user operation generates data changes, and the system generates a new version record, including update time, data source, change content and associated module information. Through version control, the system can realize data traceability, rollback and comparison analysis, ensuring the consistency and reliability of data in multi-module parallel operation and long-period operation. Finally, the data management module supports real-time updating mechanism. Through the combination of event triggering and timing refreshing, the BIM model, measured data and simulation results are dynamically updated. When the collection module or weather simulation module generates new data, the event triggering mechanism immediately synchronizes the update to the data management platform; the timing refreshing mechanism checks the global data for consistency to prevent data delay or loss. The module also provides unified interface management functions, allowing the modeling module, interaction module and fault diagnosis module to call the latest data at any time, realizing multi-module collaborative operation and dynamic visualization.

[0038] Specifically, the fault diagnosis module is electrically connected with the data management module, and the fault diagnosis module is configured to monitor the running state of the system and trigger a fault handling mechanism when an abnormality is detected.

[0039] In particular, the fault diagnosis module is further configured to monitor the running state of the system in real time, wherein when data loss or simulation result deviation beyond the preset range is detected, the fault diagnosis module triggers the fault handling mechanism of disconnecting the abnormal module connection, generating a fault report, and attempting to reload the data.

[0040] It can be understood that the fault diagnosis module is electrically connected with the data management module to form a safety monitoring and self-recovery unit for system operation. The core technical principle is to monitor and intelligently diagnose the running state of the railway sand table system in real time to ensure the stability and reliability of the BIM model data, simulation results and interactive operation. Secondly, at the level of operation monitoring, the fault diagnosis module continuously collects the running state parameters of each module of the system, including the acquisition module, the modeling module, the weather simulation module, the interactive module and the data management module. These parameters include data refresh frequency, model loading time, storage response delay, network communication delay and CPU / GPU resource occupancy, etc. The module uses multi-dimensional state indicators to establish a running health evaluation model, and identifies potential abnormalities in system operation in real time through a combination of threshold comparison and trend analysis. In addition, at the level of anomaly detection, the fault diagnosis module adopts a dual detection mechanism based on threshold and adaptive deviation analysis. When the system detects that the key data packet is lost, the simulation result deviation exceeds the preset range, the model loading fails or the data delay exceeds the allowed threshold, the module automatically determines that the system is in an abnormal state. The deviation detection algorithm calculates the deviation ratio based on the comparison between the historical baseline model and the real-time running result, and dynamically adjusts the threshold through a sliding window method, thereby distinguishing between short-term fluctuations and persistent abnormalities and avoiding false positives. Further, at the level of fault location and processing, the module has a modularized abnormality positioning mechanism built-in, which automatically determines the source of the fault (such as data interface anomaly, model rendering error, storage delay or communication interruption) by monitoring the log files and call chains of different modules. After confirming the source of the anomaly, the system automatically executes a multi-level fault handling strategy: mild anomaly handling: including automatically reloading data, restarting related module threads, flushing cache areas and checking data integrity; moderate anomaly handling: when detecting simulation result distortion or data synchronization failure, the system temporarily disconnects the abnormal module from the main control module to prevent the spread of anomalies; severe anomaly handling: when the system experiences continuous data loss or core module crashes, the module triggers an emergency protection mechanism, generates a detailed fault report and stores the error information in the log database, and notifies the management terminal for manual intervention. In addition, at the level of data recovery and system self-healing, the fault diagnosis module, in combination with the version control function of the data management module, quickly rolls back and reconstructs the latest valid data version. Based on the timestamp and data integrity hash verification mechanism, the module can locate the last normal running data snapshot and perform recovery operations. After system recovery, the module re-verifies the simulation results and data consistency, and records the recovery status in the fault database for subsequent system performance evaluation and optimization learning. Finally, the fault diagnosis module also supports fault trend analysis function. By statistically analyzing historical fault records and combining time series model to predict possible high-risk operation stages of the system, the module can issue early warnings and adjust module running parameters, thereby forming a proactive defense mechanism.This prediction and feedback-based cyclic diagnosis principle effectively improves the stability and self-healing ability of the railway sand table system.

[0041] To better enable those skilled in the relevant art to fully understand and implement the present application, the specific implementation principles of the present application are further supplemented below in conjunction with a specific application scenario.

[0042] In the practical application of railway engineering design optimization, the key node information and structural feature data of the target line are first obtained through the acquisition module. Specifically, the acquisition module uses image recognition technology to extract key nodes such as turnouts, curves, and slope change points from the BIM model, and performs geometric enhancement processing in combination with measured data. For example, when extracting the load-bearing characteristics of a bridge, the acquisition module calculates the carrying capacity of the bridge according to its design parameters, and generates a high-precision three-dimensional model in combination with the track material properties. Subsequently, these data are transmitted to the modeling module through a unified data interface, providing basic support for subsequent multi-line collaborative modeling.

[0043] After receiving the data from the acquisition module, the modeling module integrates it into the models of multiple lines such as the outer ring test line, the urban rail test line, and the calibration test line. In this process, the modeling module ensures the synchronous updating of state information of different line models through a model association mechanism. For example, when the user adjusts the slope of a section of track in the outer ring test line, the modeling module will automatically synchronize this change to other related line models, and display the running conditions of multiple lines on a single sand table interface. This design allows users to observe the running conditions of multiple lines simultaneously and compare changes in line parameters, thereby meeting the needs of comprehensive experiments and line optimization.

[0044] The weather simulation module simulates the impact of extreme weather conditions on railway facilities based on the line model state information provided by the modeling module. For example, under simulated rainy conditions, the weather simulation module calculates the degree of wet slip on the track surface according to the amount of rainfall and analyzes the changes in the contact net conductive performance. At the same time, the weather simulation module has built-in physical models that calculate the pantograph contact force fluctuation, train traction efficiency, and electrical connection reliability in real time, and dynamically display the simulation results on the sand table interface. Users can select different weather conditions through the interactive interface to observe their impact on the operation of railway facilities. For example, when simulating thunderstorm weather, the weather simulation module analyzes the impact of lightning strikes on the signal system and generates a corresponding risk assessment report.

[0045] The interactive module provides multi-perspective switching and intelligent navigation functions for users, supporting users to freely observe and quickly locate key areas in the sand table. In actual operation, users can freely switch between first-person, third-person, overhead, and bird's-eye perspectives through the interactive interface. For example, in the first-person perspective, users can simulate the perspective of a train driver to observe the line operation; and in the bird's-eye perspective, users can comprehensively understand the layout of the entire sand table model. In addition, the interactive module realizes the automatic focusing function of key nodes in combination with the path planning algorithm, and users can quickly locate the key areas or equipment nodes of the line by clicking on specific nodes. The interactive module also supports the access of virtual reality devices, and users can immerse themselves in the operation process of the sand table model through VR devices.

[0046] The data management module is responsible for centralized storage and real-time updating of BIM model data, measured data, and simulation results. In actual application, the data management module constructs a unified data management platform for storing data from the acquisition module, modeling module, and weather simulation module. For example, when storing BIM model data, the data management module will mark different versions of the model and record the time and content of each update. Through the real-time updating mechanism, the data management module synchronizes the latest railway line information to the sand table model, avoiding errors caused by data lag. In addition, the data management module can also interface with railway engineering design software, simulation analysis platforms, and monitoring systems to form a complete railway sand table visualization solution.

[0047] The fault diagnosis module monitors the running state of the system in real time and triggers the fault handling mechanism when detecting abnormalities. For example, when detecting data loss or simulation result deviation exceeding the preset range, the fault diagnosis module will disconnect the connection of the abnormal module, generate a fault report, and attempt to reload the data. According to the fault type, users can choose manual or automatic recovery of system operation to ensure the stability and reliability of the sand table model. The fault diagnosis module is connected to the acquisition module through a feedback loop to restart the data acquisition process after fault handling is completed.

[0048] Through the close cooperation of the above steps, the system realizes high-precision dynamic display of railway lines, stations, and related facilities, supports multi-line collaborative modeling, extreme weather impact simulation, and intelligent interactive operation, and provides complete technical support for railway engineering design optimization, test verification, and training demonstration.

[0049] In the above embodiments, the acquisition module automatically collects and geometrically enhances and optimizes the key nodes and structural features of railway lines, improving the accuracy and realism of the sand table model. This allows key nodes such as turnouts, curves, and gradients of the railway lines to be accurately presented in the 3D visualization system, thereby enhancing the simulation reliability and engineering reference value. Secondly, the modeling module is electrically connected to the acquisition module, enabling data sharing and operational linkage among multiple lines through a unified data interface and model association mechanism. This supports simultaneous modeling and simulation of multiple lines, including outer ring test lines, urban rail test lines, and calibration test lines, allowing the sand table system to perform collaborative display and dynamic analysis of multiple lines, enhancing its application capabilities in comprehensive experiments, line optimization, and scheduling research. Furthermore, the weather simulation module can simulate the impact of different environmental conditions such as rain, snow, and icing on railway facilities, and analyze the conductivity of the contact network and the electrical connection status of the train pantograph, enhancing the sand table system's simulation capabilities in extreme weather environments and providing a scientific basis for railway facility design and risk assessment. Furthermore, the interactive module provides multi-view switching and intelligent navigation functions, allowing users to freely observe and lock key areas within the sand table, improving operational convenience and interactive experience, and facilitating engineering design verification, experimental demonstrations, and training. Simultaneously, the data management module enables centralized storage and real-time updates of BIM model data, measured data, and simulation results, ensuring consistency between the sand table model and actual route information, while providing reliable assurance for long-term system operation and data traceability. Finally, the fault diagnosis module can monitor the system's operating status in real time and trigger fault handling mechanisms when anomalies are detected, improving system stability and reliability, and ensuring the safety and continuity of the 3D sand table visualization system during long-term operation.

[0050] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program goods. 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 goods 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.

[0051] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program goods according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart...Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0052] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0053] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0054] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific implementation of the present invention. Any modifications or equivalent substitutions that do not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A BIM-based 3D visualization system for railway sand table models, characterized in that, include: The acquisition module is configured to acquire key node information and structural feature data of the railway line, and to perform geometric enhancement and texture optimization on the key nodes; The modeling module is electrically connected to the acquisition module. The modeling module is configured to determine data sharing and operational linkage between multiple lines based on a unified data interface and model association mechanism. The weather simulation module is electrically connected to the modeling module. The weather simulation module is configured to simulate the impact of different environmental conditions on railway facilities and analyze the changes in the conductivity of the overhead contact line and the electrical connection status of the train pantograph. The interactive module is electrically connected to the weather simulation module. The interactive module is configured to provide multi-view switching and intelligent navigation functions to help users locate key areas in the sandbox. The data management module is electrically connected to the interaction module. The data management module is configured to realize centralized storage and real-time updating of BIM model data, measured data and simulation results. The fault diagnosis module is electrically connected to the data management module. The fault diagnosis module is configured to monitor the operating status of the system and trigger the fault handling mechanism when an anomaly is detected.

2. The BIM-based 3D visualization system for railway sand table models as described in claim 1, characterized in that, The acquisition module is also configured to extract key node information of turnouts, curves, gradient change points, bridges and tunnels from BIM models or measured line data based on image recognition technology or data-driven methods. The acquisition module is also configured to perform geometric adjustments and texture detail optimizations on key nodes.

3. The BIM-based 3D visualization system for railway sand table models as described in claim 2, characterized in that, The data acquisition module is also configured to use bridge load-bearing characteristics, tunnel ventilation conditions, and station layout parameters as key node information. The acquisition module is also configured to generate structural feature data by combining track material properties and catenary installation height.

4. The BIM-based 3D visualization system for railway sand table models as described in claim 1, characterized in that, The modeling module is also configured to synchronously update the operating status information of the outer ring test line, urban rail test line, and calibration test line based on the model association mechanism; The modeling module is also configured to determine the operating parameters of multiple lines when a user compares them on the same interface.

5. The BIM-based 3D visualization system for railway sand table models as described in claim 1, characterized in that, The weather simulation module is equipped with a physical model; The weather simulation module is also configured to simulate the impact of rain, snow, icing, and high temperature conditions on railway facilities, and to analyze the changes in the conductivity of the overhead contact line and the electrical connection status of the train pantograph through parametric simulation methods.

6. The BIM-based 3D visualization system for railway sand table models as described in claim 5, characterized in that, The weather simulation module is also configured to simulate the impact of thunderstorms on signal systems and the interference of sandstorms on visibility, and dynamically display the simulation results on the sand table interface.

7. The BIM-based 3D visualization system for railway sand table models as described in claim 1, characterized in that, The interactive module is configured with first-person, third-person, top-down, and bird's-eye view perspectives; The interactive module is also configured to automatically focus on key nodes by combining path planning algorithms.

8. The BIM-based 3D visualization system for railway sand table models as described in claim 7, characterized in that, The interactive module is also configured with a virtual reality device interface; The interaction module is also configured to allow users to operate the sand table model using VR devices.

9. The BIM-based 3D visualization system for railway sand table models as described in claim 1, characterized in that, The data management module is also configured to build a unified data management platform; The data management module is also configured to store BIM model data, measured data, simulation results, and user operation records; The data management module is also configured to integrate and version control data from multiple sources.

10. The BIM-based 3D visualization system for railway sand table models as described in claim 1, characterized in that, The fault diagnosis module is also configured to monitor the system's operating status in real time, among which, When data loss or simulation result deviation exceeds the preset range is detected, the fault diagnosis module triggers a fault handling mechanism that disconnects the abnormal module, generates a fault report, and attempts to reload the data.

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