A water conservancy project safety monitoring system based on VR technology

Abstract

The present invention discloses a water conservancy project safety monitoring system based on VR technology, which relates to the field of safety monitoring technology. The system realizes multi-level risk assessment through a preliminary risk positioning module and a deep risk analysis module, combined with a dam safety factor SF and a deep safety factor SFD. When the system detects that the dam safety factor SF is lower than the preliminary risk threshold T1, it will highlight the abnormal area in the three-dimensional virtual model, start the deep analysis, and conduct a more accurate risk assessment on the relevant monitoring points. In further analysis, the deep safety factor SFD is output through the attenuation coefficient and the coupling model, and compared with the deep risk threshold T2 to ensure that when potential abnormalities occur in the dam, the system can issue an early warning and prompt the management personnel to conduct VR inspections or on-site inspections. Based on this early warning mechanism, the work efficiency is greatly improved compared to manual monitoring, thereby ensuring the long-term stable operation of the dam.

Description

Technical Field

[0001] The present invention relates to the technical field of safety monitoring, and in particular to a water conservancy project safety monitoring system based on VR technology. Background Art

[0002] With the continuous advancement of science and technology and the expansion of application fields, virtual reality VR technology has gradually penetrated into multiple industries, especially in engineering, construction, transportation and other fields. As part of the national infrastructure, water conservancy projects play a vital role in ensuring the safety and stability of water conservancy facilities. Specifically, when it comes to the safety monitoring of water conservancy projects such as dams and levees, traditional monitoring methods have problems such as poor timeliness and difficulty in real-time processing and analysis of data. Therefore, combined with advanced virtual reality technology, using its powerful three-dimensional modeling, real-time rendering and immersive experience advantages, a water conservancy project safety monitoring system based on VR technology has been developed to achieve accurate, safe and efficient monitoring and management of water conservancy projects.

[0003] At present, the lag and insufficient data analysis capabilities of traditional water conservancy project monitoring methods often fail to detect possible structural problems or potential safety risks of the dam in a timely manner. For example, when key parameters such as the settlement, soil moisture or stress of the dam change, the traditional system may not be able to effectively track these changes and conduct a comprehensive analysis, resulting in the related risks being ignored or delayed response. As a result, the maintenance and repair of dams often rely on regular inspections, which are often carried out before a crisis breaks out. Such a delayed response mechanism may lead to more serious engineering accidents and may even cause large-scale floods or other structural disasters, causing immeasurable economic losses and casualties. By introducing real-time monitoring and data visualization based on VR technology, these blind spots can be effectively eliminated, the real-time monitoring capabilities of dam safety can be improved, and the process of risk identification and decision-making response can be accelerated. Summary of the invention

[0004] In view of the deficiencies in the prior art, the present invention provides a water conservancy project safety monitoring system based on VR technology, which solves the problems mentioned in the background technology.

[0005] To achieve the above objectives, the present invention is implemented through the following technical solutions: including a data acquisition module, a three-dimensional visualization module, a data coupling analysis module, a preliminary risk positioning module and a deep risk analysis module;

[0006] The data acquisition module collects the environmental operation data of the dam in real time by setting up several monitoring points around the dam and installing sensor groups in the monitoring points, and transmits the collected environmental operation data to the three-dimensional visualization module through wireless network technology;

[0007] The three-dimensional visualization module constructs a three-dimensional virtual model of the dam based on the physical data of the dam, merges the environmental operation data with the three-dimensional virtual model, and integrates VR technology to perform virtual inspection and data visualization; at the same time, the environmental operation data is preprocessed in the three-dimensional virtual model to obtain a standard data set, and a SQL Server database is constructed and stored in the SQL Server database;

[0008] The data coupling analysis module extracts the standard data set and uses a coupling nonlinear model, which includes a stress-vibration coupling model, a temperature-thermal expansion coupling model, a humidity-water-level coupling model, and a settlement-friction coupling model to calculate the output stress and vibration coupling influence coefficients R y，fvib , Temperature and thermal expansion coupling influence coefficient R thermal , soil moisture and water level coupling influence coefficient R S，hgw and the coupling coefficient R of the sedimentation and friction coefficient friction ;

[0009] The preliminary risk positioning module outputs the dam body safety factor SF by comprehensively calculating the output results of the data coupling analysis module, and at the same time presets the preliminary risk threshold T1 and the dam body safety factor SF, performs preliminary comparative evaluation, and locates the safety abnormality monitoring point based on the preliminary comparative evaluation results;

[0010] The deep risk analysis module performs a deep analysis on the located safety anomaly monitoring points. The deep analysis extracts the standard data set of the current monitoring point and inputs it into the deep algorithm formula to calculate and output the deep safety factor SFD. A secondary comparative evaluation is performed between the preset depth risk threshold T2 and the depth safety factor SFD, and an early warning mechanism is generated based on the secondary comparative evaluation results. At the same time, a response is generated in the three-dimensional virtual model through VR technology.

[0011] Preferably, the data acquisition module includes a monitoring point setting unit and a data transmission unit;

[0012] The monitoring point setting unit is used to set monitoring points around the dam at intervals of 5 meters by 5 meters. The monitoring points are installed on the dam body in a covering manner, and sensor groups are installed in the monitoring points to collect environmental operation data of the dam in real time;

[0013] The sensor group includes a displacement sensor, a stress sensor, an acceleration sensor, a temperature sensor, a soil moisture sensor, a settlement sensor and a groundwater level sensor;

[0014] The environmental operation data include dam body displacement L, dam body stress propagation velocity Vwave, dam body vibration frequency fvib, dam body temperature T, dam body soil moisture S, dam body settlement Hsettle and groundwater level hgw;

[0015] The data transmission unit sets up a 5G communication network based on the communication module inside each sensor in the sensor group to wirelessly connect the communication module of the sensor group with the three-dimensional virtual model, and transmits the environmental operation data collected by the sensor group to the three-dimensional virtual model.

[0016] Preferably, the three-dimensional visualization module includes a three-dimensional virtual model unit, a data processing unit and a data storage unit;

[0017] The three-dimensional virtual model unit constructs a three-dimensional model of the dam by using a geographic information system (GIS) in combination with physical data of the dam, wherein the physical data includes geometric dimensions of the dam body, dimensions of the cross-section and profile of the dam body, and surface features of the dam body, obtains high-definition images of the dam and the surrounding environment through satellite images, and performs a three-dimensional terrain model, integrates the three-dimensional dam model and the three-dimensional terrain model to obtain a three-dimensional model, collects water environment data in real time through water body detection equipment, and combines the environmental operation data to embed the three-dimensional model into the three-dimensional model using three-dimensional rendering software;

[0018] Based on the three-dimensional model, a virtual environment of the dam is constructed through the visualization VR engine technology, and then the virtual environment of the dam is integrated with the visualization monitoring data chart to generate a three-dimensional virtual model. The visualization detection data chart includes color coding, three-dimensional dynamic chart and heat map.

[0019] Preferably, the data processing unit receives the environmental operation data in the three-dimensional virtual model and pre-processes the environmental operation data to obtain a standard data set, wherein the pre-processing includes data cleaning, data standardization and data fusion;

[0020] The data cleaning is to smooth the environmental operation data through Kalman filtering, remove the noise of the environmental operation data through wavelet transform, and use data difference and fitting to process the missing data and fill the gaps between the data;

[0021] The data standardization uses Z-score standardization technology to map data of different dimensions in the environmental operation data into the same range for standardization processing;

[0022] The data fusion is used to perform fusion calculation on the standardized environmental operation data to obtain a standard data set;

[0023] The standard data set includes dam body micro stress y, dam body thermal stress Ry, dam body vibration frequency fvib, dam body soil moisture S, dam body settlement Hsettle and groundwater level hgw;

[0024] The micro stress y is calculated and output by combining the dam body stress propagation velocity Vwave with the dam body vibration frequency fvib. The specific algorithm formula is: In the formula, π represents the circumference of a circle, which is 3.14, and △L represents the displacement difference of the dam body, which is obtained by calculating the difference of the dam body displacement L at two time points;

[0025] The thermal stress Ry of the dam body is calculated by the temperature difference change of the dam body temperature T and the thermal expansion of the dam body material. The specific algorithm formula is: Ry = E·α therm ·△T, where E represents the elastic modulus of the dam material, α therm represents the expansion coefficient, △T represents the temperature difference;

[0026] The data storage unit constructs a SQL Server database and sets a transmission port, and writes the standard data set into the SQL Server database through the transmission port for data storage.

[0027] Preferably, the data coupling analysis module includes a stress and vibration coupling unit, a thermal stress influence unit, a soil moisture and water level coupling unit, and a settlement and friction coupling unit;

[0028] The stress and vibration coupling unit extracts the micro stress y and the dam body vibration frequency fvib in the standard data set of each monitoring point in real time through the transmission port, inputs them into the stress and vibration coupling model, and calculates and outputs the stress and vibration coupling influence coefficient R y，fvib , analyze the concentration of stress caused by vibration of the dam body caused by external force;

[0029] The stress and vibration coupling influence coefficient R y，fvib The output is calculated using the following stress-vibration coupling model;

[0030]

[0031] In the formula, Keff represents the effective anti-vibration coefficient of the dam body;

[0032] The thermal stress influence unit extracts the dam body thermal stress Ry in the standard data set of each monitoring point in real time through the transmission port, inputs it into the temperature and thermal expansion coupling model, and calculates and outputs the temperature and thermal expansion coupling influence coefficient R thermal , analyze the temperature characteristics of the dam under temperature difference changes;

[0033] The thermal expansion coupling influence coefficient R thermal The output is calculated using the following temperature and thermal expansion coupling model;

[0034]

[0035] In the formula, Ry max Indicates the upper limit of the thermal stress that the dam material can withstand.

[0036] Preferably, the soil moisture and water level coupling unit extracts the dam body soil moisture S and groundwater level hgw in the standard data set of each monitoring point in real time through the transmission port, inputs them into the moisture and water level coupling model, and calculates and outputs the soil moisture and water level coupling influence coefficient R S，hgw , analyze the impact of soil moisture changes on dam stability;

[0037] The soil moisture and water level coupling influence coefficient R S，hgw The output is calculated by the following moisture-water level coupling model;

[0038]

[0039] In the formula, S0 represents the reference soil moisture, β represents the sensitivity coefficient of the dam soil moisture S and the groundwater level hgw, S max Indicates the upper limit of soil moisture;

[0040] The settlement and friction coupling unit extracts the dam settlement Hsettle in the standard data set of each monitoring point in real time through the transmission port, inputs it into the settlement friction coupling model, and calculates and outputs the coupling coefficient R of the settlement and friction coefficient. friction , analyze the impact of soil moisture changes on dam stability;

[0041] The coupling coefficient R of the settlement and friction coefficient friction The output is calculated by the following settlement friction coupling model;

[0042] R friction =μ·P effective ·Hsettle;

[0043] Where μ represents the friction coefficient between the dam body and the foundation surface, P effective Represents the effective load of the dam body.

[0044] Preferably, the preliminary analysis and positioning module includes a preliminary risk analysis unit and a preliminary risk assessment unit;

[0045] The preliminary risk analysis unit combines the stress and vibration coupling influence coefficient R y，fvib , Temperature and thermal expansion coupling influence coefficient R thermal, soil moisture and water level coupling influence coefficient R S，hgw and the coupling coefficient R of the sedimentation and friction coefficient friction , perform comprehensive calculation to output the dam body safety factor SF, and conduct a preliminary analysis of the dam body safety status;

[0046] The dam body safety factor SF is calculated and output by the following algorithm formula:

[0047]

[0048] Where a1, a2, a3 and a4 represent the stress and vibration coupling influence coefficients R y，fvib , Temperature and thermal expansion coupling influence coefficient R thermal , soil moisture and water level coupling influence coefficient R S，hgw and the coupling coefficient R of the sedimentation and friction coefficient friction The weight value is a1+a2+a3+a4=1, and the specific data value is preliminarily set by the user.

[0049] Preferably, the preliminary analysis and evaluation unit presets a preliminary risk threshold T1 based on the dam design standard, and then performs preliminary comparative evaluation on the preliminary risk threshold T1 and the dam body safety factor SF, and locates the abnormal position of the dam through all monitoring points. The specific evaluation content is as follows;

[0050] When the dam body safety factor SF ≤ the initial risk threshold T1, it means that the current dam body monitoring point is in a safe state, and monitoring should continue;

[0051] When the dam safety factor SF is greater than the preliminary risk threshold T1, it indicates that there is an abnormality in the current dam monitoring point. At this time, it is fed back to the three-dimensional virtual model, and the dam sections on both sides of the current monitoring point are marked in red through color coding, and in-depth analysis is performed at the same time.

[0052] Preferably, the in-depth risk analysis module includes a in-depth analysis unit and a in-depth assessment unit;

[0053] The depth analysis unit performs a depth analysis when an abnormality occurs at a monitoring point on the dam body. The depth analysis extracts the stress and vibration coupling influence coefficient R y，fvib , Temperature and thermal expansion coupling influence coefficient R thermal , soil moisture and water level coupling influence coefficient R S，hgw and the coupling coefficient R of the sedimentation and friction coefficient friction , combined with the attenuation coefficient, calculate and output the deep safety factor SFD, and deeply analyze the safety situation of the current monitoring point;

[0054] The depth safety factor SFD is calculated and output by the following algorithm formula;

[0055]

[0056] In the formula, e - represents an exponential decay function.

[0057] Preferably, the depth assessment unit performs an average calculation to output a depth risk threshold T2 by analyzing 20 groups of depth safety factors SFD when the dam body is abnormal in stability based on the user, and performs a depth analysis of the abnormal situation of the abnormal monitoring point of the dam body. The specific assessment thresholds are as follows;

[0058] When the depth safety factor SFD> the depth risk threshold T2, it means that the current abnormal monitoring point of the dam is normal. At this time, an inspection warning is sent to prompt the user to wear a VR helmet to access the three-dimensional virtual model, inspect the abnormal monitoring point, and perform planned maintenance;

[0059] When the depth safety factor SFD ≤ the depth risk threshold T2, it indicates that there is an abnormality at the current abnormal monitoring point of the dam body. At this time, a maintenance warning is sent to prompt the user to immediately conduct on-site monitoring and maintenance of the current monitoring point.

[0060] The present invention provides a water conservancy project safety monitoring system based on VR technology. It has the following beneficial effects:

[0061] (1) The system can collect environmental operation data of the dam in real time by setting up multiple monitoring points around the dam and installing sensor groups, including key parameters such as displacement, stress, vibration, temperature, humidity, settlement and groundwater level. The collected data is transmitted to the three-dimensional visualization module through a wireless network. A highly accurate three-dimensional virtual model of the dam is constructed by combining the physical data and environmental data of the dam, and VR technology is integrated for virtual inspection. Through this system, managers can intuitively view the real-time status of the dam in a virtual environment and quickly discover and locate any abnormalities. This technology greatly improves the real-time and accuracy of monitoring, helps to identify possible risks of the dam in advance, and ensures that countermeasures are taken in a timely manner.

[0062] (2) The system uses a variety of nonlinear analysis methods such as stress and vibration coupling model, temperature and thermal expansion coupling model, soil moisture and water level coupling model, and settlement and friction coupling model through the data coupling analysis module to conduct in-depth coupling analysis on various environmental operation data of the dam. These models can comprehensively consider the changes and interactions of the dam body under different environmental conditions and output multiple coupling influence coefficients, such as the stress and vibration coupling influence coefficient R y，fvib , Temperature and thermal expansion coupling influence coefficient R thermal , soil moisture and water level coupling influence coefficient R S，hgwEtc. These coupling influence coefficients provide important quantitative basis for further risk positioning and safety assessment, effectively improving the comprehensiveness and accuracy of dam safety monitoring and ensuring the accuracy of risk assessment.

[0063] (3) The system realizes multi-level risk assessment through the preliminary risk positioning module and the deep risk analysis module, combined with the dam safety factor SF and the deep safety factor SFD. When the system detects that the dam safety factor SF is lower than the preliminary risk threshold T1, it will highlight the abnormal area in the three-dimensional virtual model and start the deep analysis to conduct a more accurate risk assessment of the relevant monitoring points. In further analysis, the deep safety factor SFD is output through the attenuation coefficient and the coupling model, and compared with the deep risk threshold T2 to ensure that when there is a potential abnormality in the dam, the system can issue an early warning and prompt the management personnel to conduct inspections or on-site inspections. Based on this early warning mechanism, the system can automatically generate a maintenance plan, improve work efficiency, reduce human operation errors, and thus ensure the long-term stable operation of the dam. BRIEF DESCRIPTION OF THE DRAWINGS

[0064] Figure 1 The figure is a flow chart of a water conservancy project safety monitoring system based on VR technology according to the present invention. DETAILED DESCRIPTION

[0065] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0066] Example 1

[0067] See also Figure 1 , the present invention provides a water conservancy project safety monitoring system based on VR technology. To achieve the above purpose, the present invention is implemented through the following technical solutions: including a data acquisition module, a three-dimensional visualization module, a data coupling analysis module, a preliminary risk positioning module and a deep risk analysis module;

[0068] The data acquisition module sets up several monitoring points around the dam and installs sensor groups in the monitoring points to collect the environmental operation data of the dam in real time, and transmits the collected environmental operation data to the three-dimensional visualization module through wireless network technology;

[0069] The 3D visualization module builds a 3D virtual model of the dam based on the physical data of the dam, integrates the environmental operation data with the 3D virtual model, and integrates VR technology to perform virtual inspection and data visualization; at the same time, the environmental operation data is preprocessed in the 3D virtual model to obtain a standard data set, and a SQL Server database is built and stored in the SQL Server database;

[0070] The data coupling analysis module extracts the standard data set and uses the coupled nonlinear model, which includes the stress-vibration coupling model, the temperature-thermal expansion coupling model, the humidity-water-level coupling model, and the settlement-friction coupling model, to calculate the output stress and vibration coupling influence coefficients R respectively. y，fvib , Temperature and thermal expansion coupling influence coefficient R thermal , soil moisture and water level coupling influence coefficient R S，hgw and the coupling coefficient R of the sedimentation and friction coefficient friction ;

[0071] The preliminary risk location module outputs the dam body safety factor SF by comprehensively calculating the output results of the data coupling analysis module, and presets the preliminary risk threshold T1 and the dam body safety factor SF for preliminary comparative evaluation. Based on the preliminary comparative evaluation results, the safety abnormality monitoring points are located;

[0072] The deep risk analysis module conducts in-depth analysis on the located safety anomaly monitoring points. The deep analysis extracts the standard data set of the current monitoring point and inputs it into the deep algorithm formula to calculate and output the deep safety factor SFD. A secondary comparative evaluation is performed between the preset depth risk threshold T2 and the depth safety factor SFD, and an early warning mechanism is generated based on the results of the secondary comparative evaluation. At the same time, a response is generated in the three-dimensional virtual model through VR technology.

[0073] In this embodiment, the system deploys monitoring points around the dam through the data acquisition module, installs multiple sensor groups, collects environmental operation data in real time and transmits it to the three-dimensional visualization module through a wireless network. In the three-dimensional visualization module, an accurate three-dimensional virtual dam model is constructed by combining the physical data and environmental operation data of the dam, and VR technology is integrated for virtual inspection and data visualization, helping managers to more intuitively grasp the real-time status of the dam. The data coupling analysis module uses multiple nonlinear coupling models to perform in-depth analysis on the collected standard data sets, calculates and outputs multiple key coupling influence coefficients, and further quantifies the stability of the dam under different environmental conditions. Based on these output results, the preliminary risk positioning module can comprehensively calculate the dam body safety factor SF, and quickly locate possible safety abnormal monitoring points by comparing it with the preset preliminary risk threshold T1. When an abnormality is detected, the deep risk analysis module extracts the standard data set of the monitoring point, combines the deep algorithm to calculate the deep safety factor SFD, and compares it with the preset deep risk threshold T2 for a second time, so as to further accurately evaluate the risk level of the dam. The system generates an early warning mechanism based on these in-depth analysis results, generates responses in the three-dimensional virtual model through VR technology, and provides managers with detailed safety assessments and maintenance recommendations. Through the implementation of this system, dam safety monitoring and assessment have become more efficient, accurate and intelligent. The combination of real-time data acquisition and three-dimensional virtual environment not only improves the real-time nature of monitoring, but also improves the intuitiveness and accuracy of inspections through VR technology. The introduction of coupling analysis and risk positioning modules makes risk assessment not limited to a single monitoring point, but takes into account the interactive effects between multiple environmental factors, greatly improving the comprehensiveness and accuracy of safety assessments. Ultimately, through in-depth risk analysis and intelligent early warning mechanisms, the system can detect potential safety hazards in advance, provide more accurate decision-making basis for dam maintenance and management, ensure the long-term stable operation of the dam, reduce errors in human operations, and significantly improve the level of dam safety protection.

[0074] Example 2

[0075] This embodiment is explained in Example 1, please refer to Figure 1 ,Specifically: the data acquisition module includes a monitoring point setting unit and a data transmission unit;

[0076] The monitoring point setting unit is used to set monitoring points around the dam at intervals of 5 meters by 5 meters. The monitoring points are installed on the dam body in a covering manner, and sensor groups are installed in the monitoring points to collect environmental operation data of the dam in real time;

[0077] The sensor group includes a displacement sensor, a stress sensor, an acceleration sensor, a temperature sensor, a soil moisture sensor, a settlement sensor, and a groundwater level sensor;

[0078] Environmental operation data include dam displacement L, dam stress propagation velocity Vwave, dam vibration frequency fvib, dam temperature T, dam soil moisture S, dam settlement Hsettle and groundwater level hgw;

[0079] The data transmission unit sets up a 5G communication network based on the communication module inside each sensor in the sensor group to wirelessly connect the communication module of the sensor group with the three-dimensional virtual model, and transmits the environmental operation data collected by the sensor group to the three-dimensional virtual model.

[0080] In this embodiment, the system collects the environmental operation data of the dam in real time by setting up covering monitoring points around the dam and installing a variety of sensors through the data acquisition module. The data collected by the sensor is transmitted to the three-dimensional virtual model through the 5G network to realize real-time transmission and processing of data. Through comprehensive monitoring and fast data transmission, this module improves the coverage and accuracy of dam monitoring and ensures real-time monitoring of key areas. The diversity of sensors makes the monitoring data more comprehensive and improves the efficiency and accuracy of dam safety monitoring. At the same time, the 5G communication network ensures the fast and stable transmission of data, providing a reliable basis for subsequent data analysis and decision-making.

[0081] Example 3

[0082] This embodiment is explained in Example 2. Please refer to Figure 1 ,Specifically: 3D visualization module includes 3D virtual model unit, data ,processing unit and data storage unit;

[0083] The three-dimensional virtual model unit uses the geographic information system GIS and combines the physical data of the dam to build a three-dimensional model of the dam. The physical data includes the geometric dimensions of the dam body, the cross-section and profile dimensions of the dam body, and the surface characteristics of the dam body. The high-definition images of the dam and the surrounding environment are obtained through satellite effects, and a three-dimensional terrain model is made. The three-dimensional model of the dam and the three-dimensional terrain model are integrated to obtain a three-dimensional model. The water environment data is collected in real time through water body detection equipment, and combined with the environmental operation data, the three-dimensional rendering software is used to embed the three-dimensional model, and the three-dimensional model is dynamically updated in real time.

[0084] Water environment data and water detection equipment include environmental monitoring sensors to collect temperature, humidity, wind speed and precipitation; water level and water flow monitoring equipment to monitor water level changes and water flow conditions, and earthquake and vibration sensors to monitor earthquake fluctuations and vibrations of the dam body;

[0085] Based on the three-dimensional model, a virtual environment of the dam is constructed through the visualization VR engine technology. The virtual environment of the dam is then integrated with the visualization monitoring data charts to generate a three-dimensional virtual model. The visualization detection data charts include color coding, three-dimensional dynamic charts and heat maps.

[0086] The data processing unit receives the environmental operation data in the three-dimensional virtual model and pre-processes the environmental operation data to obtain a standard data set. The pre-processing includes data cleaning, data standardization and data fusion.

[0087] Data cleaning uses Kalman filtering to smooth the environmental operation data, and then uses wavelet transform to remove the noise of the environmental operation data. It also uses data difference and fitting to process missing data and fill in the gaps between data.

[0088] Data standardization uses Z-score standardization technology to map data of different dimensions in environmental operation data to the same range for standardization;

[0089] Data fusion is used to perform fusion calculation on the standardized environmental operation data to obtain a standard data set;

[0090] The standard data set includes dam body micro-stress y, dam body thermal stress Ry, dam body vibration frequency fvib, dam body soil moisture S, dam body settlement Hsettle and groundwater level hgw;

[0091] The micro stress y is calculated and output through the dam body stress propagation velocity Vwave combined with the dam body vibration frequency fvib. The specific algorithm formula is: In the formula, π represents the circumference of a circle, which is 3.14, and △L represents the displacement difference of the dam body, which is obtained by calculating the difference of the dam body displacement L at two time points;

[0092] The thermal stress Ry of the dam body is calculated by the temperature difference change of the dam body temperature T and the thermal expansion of the dam body material. The specific algorithm formula is: Ry=E·α therm ·△T, where E represents the elastic modulus of the dam material, α therm represents the expansion coefficient, △T represents the temperature difference;

[0093] The data storage unit constructs a SQL Server database and sets a transmission port, writes the standard data set into the SQL Server database through the transmission port, and performs data storage.

[0094] In this embodiment, the system uses GIS technology and dam physical data to construct a 3D model of the dam through a 3D visualization module, and integrates water environment data and high-definition images of the surrounding environment to form a dynamically updated 3D virtual model. The module combines the real-time collected environmental operation data with the 3D model, uses VR engine technology to generate a virtual environment of the dam, and displays it through visual monitoring data such as color coding and dynamic charts. The data processing unit is responsible for preprocessing the collected environmental data, cleaning and standardizing the data using methods such as Kalman filtering and wavelet transform, and finally generating a standard data set by fusion calculation and storing it in the SQL Server database. The module provides intuitive and real-time dam monitoring and analysis means through high-precision 3D modeling and dynamic visualization technology. Through data cleaning, standardization and fusion processing, the data quality and consistency are improved, making subsequent analysis more accurate. At the same time, the integration of 3D virtual models and visual charts improves users' understanding of the dam's operating status and decision-making efficiency. The storage and management of data are effectively guaranteed in the SQL Server database, providing a solid foundation for subsequent data analysis and risk assessment, and optimizing the management and decision-making process of dam monitoring.

[0095] Example 4

[0096] This embodiment is explained in Example 3, please refer to Figure 1 ,Specifically: the data coupling analysis module includes stress and vibration coupling unit, ,thermal stress influence unit, soil moisture and water level coupling unit, and ,sedimentation and friction coupling unit;

[0097] The stress and vibration coupling unit extracts the micro stress y and dam body vibration frequency fvib in the standard data set of each monitoring point in real time through the transmission port, inputs them into the stress and vibration coupling model, and calculates and outputs the stress and vibration coupling influence coefficient R y，fvib , analyze the concentration of stress caused by vibration of the dam body caused by external force;

[0098] Stress and vibration coupling influence coefficient R y，fvib The output is calculated using the following stress-vibration coupling model;

[0099]

[0100] In the formula, Keff represents the effective anti-vibration coefficient of the dam body, reflecting the overall stiffness and stability of the dam body. It is initially set according to the dam body structure and materials. The significance of the formula is: by analyzing the coupling relationship between stress and vibration, when the dam body is vibrated by external force or water flow, it may cause stress concentration, thereby leading to crack expansion or material damage;

[0101] The thermal stress influence unit extracts the dam body thermal stress Ry in the standard data set of each monitoring point in real time through the transmission port, inputs it into the temperature and thermal expansion coupling model, and calculates and outputs the temperature and thermal expansion coupling influence coefficient R thermal , analyze the temperature characteristics of the dam under temperature difference changes;

[0102] Thermal expansion coupling influence coefficient R thermal The output is calculated using the following temperature and thermal expansion coupling model;

[0103]

[0104] In the formula, Ry max It represents the upper limit of the thermal stress that the dam material can withstand. The significance of the formula is that the coupling relationship between the temperature gradient of the dam body and the thermal expansion coefficient of the material affects the stability of the dam body under temperature changes.

[0105] The soil moisture and water level coupling unit extracts the dam body soil moisture S and groundwater level hgw in the standard data set of each monitoring point in real time through the transmission port, inputs them into the moisture-water level coupling model and the settlement friction coupling model, and calculates and outputs the soil moisture and water level coupling influence coefficient R S，hgw , the coupling coefficient R of the settlement and friction coefficient friction , analyze the impact of soil moisture changes on dam stability;

[0106] Soil moisture and water level coupling influence coefficient R S，hgw The output is calculated by the following moisture-water level coupling model;

[0107]

[0108] In the formula, S0 represents the reference soil moisture, β represents the sensitivity coefficient of the dam soil moisture S and the groundwater level hgw, S max It represents the upper limit of soil moisture. The meaning of the formula is that when the groundwater level rises, the soil moisture may increase, thereby reducing the friction of the dam foundation, thus affecting the stability of the dam foundation;

[0109] The settlement and friction coupling unit extracts the dam settlement Hsettle in the standard data set of each monitoring point in real time through the transmission port, inputs it into the settlement friction coupling model, and calculates and outputs the coupling coefficient R of settlement and friction coefficient. friction , analyze the impact of soil moisture changes on dam stability;

[0110] Coupling coefficient R of sedimentation and friction coefficient friction The output is calculated by the following settlement friction coupling model;

[0111] R friction =μ·Peffective ·Hsettle;

[0112] Where μ represents the friction coefficient between the dam body and the foundation surface, P effective It represents the effective load of the dam body. The meaning of the formula is that friction is an important resistance between the dam body and the foundation, which directly affects the stability of the dam body such as slippage and overturning. The change of friction caused by settlement may change the stability of the dam body, and this change needs to be evaluated through calculation and monitoring. If settlement leads to a decrease in friction, it may cause relative movement between the dam body and the foundation, and then cause problems such as slippage or instability.

[0113] In this embodiment, the data coupling analysis module of the system accurately analyzes the mutual influence between various physical phenomena during the operation of the dam through the collaborative work of multiple sub-units. Each sub-unit extracts the standard data set of the monitoring point in real time and inputs it into the corresponding coupling model to calculate a series of coupling influence coefficients, such as the stress and vibration coupling influence coefficient R y，fvib , Temperature and thermal expansion coupling influence coefficient R thermal , soil moisture and water level coupling influence coefficient R S，hgw And the coupling coefficient R of the settlement and friction coefficient friction . These coupling coefficients reveal the stability and safety of the dam under the influence of external forces, temperature difference changes, soil moisture, groundwater level, and settlement. Through the output of these coupling models, the risks of crack expansion, material damage, and stability reduction that may occur in the dam under complex external conditions can be analyzed. By coupling and analyzing multiple physical factors, this module can comprehensively evaluate the performance and stability of the dam under different environmental conditions, providing accurate data support for risk prediction and early warning. Stress and vibration coupling analysis helps evaluate the structural risk of the dam under the influence of vibration, thermal stress analysis can reveal the material deformation problem caused by temperature difference in the dam, and the coupling analysis of soil moisture and water level reveals the possible impact of rising water levels on the stability of the dam, while settlement and friction coupling analysis focuses on the stability of the dam foundation. Combining these analysis results, it is possible to fully grasp the operating status of the dam, identify potential risks in a timely manner, and provide decision makers with accurate monitoring data, thereby effectively improving the ability of dam safety management and risk control.

[0114] Example 5

[0115] This embodiment is explained in Example 4. Please refer to Figure 1 ,Specifically: the preliminary analysis and positioning module includes a preliminary risk ,analysis unit and a preliminary risk assessment unit;

[0116] The preliminary risk analysis unit couples the stress and vibration influence coefficient R y，fvib , Temperature and thermal expansion coupling influence coefficient Rthermal , soil moisture and water level coupling influence coefficient R S，hgw and the coupling coefficient R of the sedimentation and friction coefficient friction , perform comprehensive calculation to output the dam body safety factor SF, and conduct a preliminary analysis of the dam body safety status;

[0117] The dam safety factor SF is calculated and output by the following algorithm formula;

[0118]

[0119] Where a1, a2, a3 and a4 represent the stress and vibration coupling influence coefficients R y，fvib , Temperature and thermal expansion coupling influence coefficient R thermal , soil moisture and water level coupling influence coefficient R S，hgw and the coupling coefficient R of the sedimentation and friction coefficient friction The weight value is a1+a2+a3+a4=1, and the specific data value is preliminarily set by the user.

[0120] The preliminary analysis and assessment unit presets a preliminary risk threshold T1 based on the dam design standard, and then conducts a preliminary comparative assessment of the preliminary risk threshold T1 and the dam safety factor SF, traversing all monitoring points to locate abnormal positions of the dam. The specific assessment contents are as follows;

[0121] When the dam body safety factor SF ≤ the initial risk threshold T1, it means that the current dam body monitoring point is in a safe state, and monitoring should continue;

[0122] When the dam safety factor SF is greater than the preliminary risk threshold T1, it indicates that there is an abnormality in the current dam monitoring point. At this time, it is fed back to the three-dimensional virtual model, and the dam sections on both sides of the current monitoring point are marked in red through color coding, and in-depth analysis is performed at the same time.

[0123] In this embodiment, the preliminary analysis and positioning module of the system generates a dam safety factor SF through comprehensive calculation of multiple coupling influence coefficients, and performs preliminary risk analysis. The module determines whether there are safety hazards in the dam by combining the dam safety factor SF with the preset preliminary risk threshold T1. When the dam safety factor SF is less than or equal to the preliminary risk threshold T1, it means that the dam is in a normal and safe state and continues to carry out routine monitoring; when the dam safety factor SF is greater than the preliminary risk threshold T1, the system will trigger an alarm and mark the abnormal monitoring point, and then highlight the abnormal area in the three-dimensional virtual model through color coding. The implementation of this module effectively quantifies and analyzes complex environmental data and dam structural safety. By comparing the calculation of the dam safety factor with the preset risk threshold T1, the potential safety problems and abnormal states of the dam can be identified in real time. Through early positioning and real-time feedback of abnormalities, the dam body section of the abnormal monitoring point can be accurately positioned, significantly improving the safety management efficiency and response speed of the dam.

[0124] Example 6

[0125] This embodiment is explained in Example 5. Please refer to Figure 1 ,Specifically: the deep risk analysis module includes a deep analysis unit and a deep ,assessment unit;

[0126] The depth analysis unit performs depth analysis when there is an abnormality in the dam monitoring point. The depth analysis extracts the stress and vibration coupling influence coefficient R y，fvib , Temperature and thermal expansion coupling influence coefficient R thermal , soil moisture and water level coupling influence coefficient R S，hgw and the coupling coefficient R of the sedimentation and friction coefficient friction , combined with the attenuation coefficient, calculate and output the deep safety factor SFD, and deeply analyze the safety situation of the current monitoring point;

[0127] The deep safety factor SFD is calculated and output by the following algorithm formula;

[0128]

[0129] In the formula, e - represents an exponential decay function, By considering the temperature, stress and vibration of the dam body, the risk of structural damage or crack propagation in the dam body can be assessed. Used to evaluate the combined effect of dam settlement and water level changes on dam stability. The friction force on the surface of the dam foundation may decrease due to changes in temperature, humidity, settlement and other factors, thereby affecting the stability of the dam.

[0130] The depth assessment unit analyzes 20 groups of dam body depth safety factors SFD when the stability is abnormal based on the user, calculates the average value and outputs the depth risk threshold T2, and deeply analyzes the abnormal situation of the abnormal monitoring point of the dam body. The specific assessment thresholds are as follows;

[0131] When the depth safety factor SFD> the depth risk threshold T2, it means that the current abnormal monitoring point of the dam body is normal. At this time, a patrol warning is sent to prompt the user to wear a VR helmet to access the three-dimensional virtual model, inspect the abnormal monitoring point, and perform planned maintenance. This means that the current monitoring point abnormality is within the acceptable range. The current monitoring point can be maintained during the planned time period by monitoring the abnormal situation with a VR helmet.

[0132] When the depth safety factor SFD ≤ the depth risk threshold T2, it indicates that there is an abnormality at the current abnormal monitoring point of the dam body. At this time, a maintenance warning is sent to prompt the user to immediately conduct on-site monitoring and maintenance of the current monitoring point.

[0133] In this embodiment, the deep risk analysis module of the system further improves the safety monitoring and risk management capabilities of the dam by deeply analyzing and evaluating the abnormal monitoring points of the dam. The deep analysis unit calculates the deep safety factor SFD by combining multiple factors such as stress and vibration coupling, temperature and thermal expansion coupling, soil moisture and water level coupling. The calculation of the deep safety factor SFD takes into account the exponential decay function, which further improves the sensitivity to the change of dam stability. In the deep evaluation unit, the deep safety factor SFD of 20 groups of dam bodies when the stability is abnormal is calculated to generate a deep risk threshold T2 as a standard for evaluating abnormal monitoring points of the dam body. When SFD is greater than the deep risk threshold T2, the system sends an inspection warning and recommends that the user conduct inspections and planned maintenance of the abnormal points through VR technology; when SFD is less than or equal to T2, the system issues a maintenance warning, prompting immediate on-site monitoring and repair to ensure that risks are controlled in a timely manner. The implementation of this module significantly enhances the depth and accuracy of dam risk analysis, so that after the initial identification of dam abnormalities, further in-depth analysis can be used to quantify potential risks and predict possible structural damage or instability in the future. By generating a deep safety factor in real time and performing comparative analysis with the threshold value T2, the module can make timely inspection or maintenance recommendations to ensure that the dam can be maintained at the most appropriate time, thereby extending its service life and reducing the risk of accidents. Through the integration of VR technology, users can not only obtain a real-time virtual inspection experience, but also more intuitively understand the actual conditions of abnormal monitoring points, provide support for decision-making, and thus improve the response speed and decision-making efficiency to sudden risks. The application of the deep risk analysis module makes the safety management of the dam more accurate and intelligent, and can provide effective early warnings and repair recommendations when potential risks occur, thus improving the overall safety assurance capabilities of the dam.

[0134] While the embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that many changes, modifications, substitutions and variations can be made to the embodiments without departing from the principles and spirit of the invention.

Claims

1. A water conservancy project safety monitoring system based on VR technology, characterized by: It includes data acquisition module, 3D visualization module, data coupling analysis module, preliminary risk location module and in-depth risk analysis module; The data acquisition module collects the environmental operation data of the dam in real time by setting up several monitoring points around the dam and installing sensor groups in the monitoring points, and transmits the collected environmental operation data to the three-dimensional visualization module through wireless network technology; The three-dimensional visualization module constructs a three-dimensional virtual model of the dam based on the physical data of the dam, merges the environmental operation data with the three-dimensional virtual model, and integrates VR technology to perform virtual inspection and data visualization; at the same time, the environmental operation data is preprocessed in the three-dimensional virtual model to obtain a standard data set, and a SQL Server database is constructed and stored in the SQL Server database; The data coupling analysis module extracts the standard data set and uses a coupling nonlinear model, which includes a stress-vibration coupling model, a temperature-thermal expansion coupling model, a humidity-water-level coupling model, and a settlement-friction coupling model to calculate the output stress and vibration coupling influence coefficients R y，fvib , Temperature and thermal expansion coupling influence coefficient R thermal , soil moisture and water level coupling influence coefficient R S，hgw and the coupling coefficient R of the sedimentation and friction coefficient friction ; The preliminary risk positioning module outputs the dam body safety factor SF by comprehensively calculating the output results of the data coupling analysis module, and at the same time presets the preliminary risk threshold T1 and the dam body safety factor SF, performs preliminary comparative evaluation, and locates the safety abnormality monitoring point based on the preliminary comparative evaluation results; The deep risk analysis module performs a deep analysis on the located safety anomaly monitoring points. The deep analysis extracts the standard data set of the current monitoring point and inputs it into the deep algorithm formula to calculate and output the deep safety factor SFD. A secondary comparative evaluation is performed between the preset depth risk threshold T2 and the depth safety factor SFD, and an early warning mechanism is generated based on the secondary comparative evaluation results. At the same time, a response is generated in the three-dimensional virtual model through VR technology.

2. According to claim 1, a water conservancy project safety monitoring system based on VR technology is characterized in that: The data acquisition module includes a monitoring point setting unit and a data transmission unit; The monitoring point setting unit is used to set monitoring points around the dam at intervals of 5 meters by 5 meters. The monitoring points are installed on the dam body in a covering manner, and sensor groups are installed in the monitoring points to collect environmental operation data of the dam in real time; The sensor group includes a displacement sensor, a stress sensor, an acceleration sensor, a temperature sensor, a soil moisture sensor, a settlement sensor and a groundwater level sensor; The environmental operation data include dam body displacement L, dam body stress propagation velocity Vwave, dam body vibration frequency fvib, dam body temperature T, dam body soil moisture S, dam body settlement Hsettle and groundwater level hgw; The data transmission unit sets up a 5G communication network based on the communication module inside each sensor in the sensor group to wirelessly connect the communication module of the sensor group with the three-dimensional virtual model, and transmits the environmental operation data collected by the sensor group to the three-dimensional virtual model.

3. According to claim 2, a water conservancy project safety monitoring system based on VR technology is characterized in that: The three-dimensional visualization module includes a three-dimensional virtual model unit, a data processing unit and a data storage unit; The three-dimensional virtual model unit constructs a three-dimensional model of the dam by using a geographic information system (GIS) in combination with physical data of the dam, wherein the physical data includes geometric dimensions of the dam body, dimensions of the cross-section and profile of the dam body, and surface features of the dam body, obtains high-definition images of the dam and the surrounding environment through satellite images, and performs a three-dimensional terrain model, integrates the three-dimensional dam model and the three-dimensional terrain model to obtain a three-dimensional model, collects water environment data in real time through water body detection equipment, and combines the environmental operation data to embed the three-dimensional model into the three-dimensional model using three-dimensional rendering software; Based on the three-dimensional model, a virtual dam environment is constructed through visual VR engine technology, and then the virtual dam environment is integrated with visual monitoring data charts to generate a three-dimensional virtual model. The visual detection data charts include color coding, three-dimensional dynamic charts and heat maps.

4. According to claim 3, a water conservancy project safety monitoring system based on VR technology is characterized in that: The data processing unit receives the environmental operation data in the three-dimensional virtual model and pre-processes the environmental operation data to obtain a standard data set, wherein the pre-processing includes data cleaning, data standardization and data fusion; The data cleaning is to smooth the environmental operation data through Kalman filtering, remove the noise of the environmental operation data through wavelet transform, and use data difference and fitting to process the missing data and fill the gaps between the data; The data standardization uses Z-score standardization technology to map data of different dimensions in the environmental operation data into the same range for standardization processing; The data fusion is used to perform fusion calculation on the standardized environmental operation data to obtain a standard data set; The standard data set includes dam body micro stress y, dam body thermal stress Ry, dam body vibration frequency fvib, dam body soil moisture S, dam body settlement Hsettle and groundwater level hgw; The micro stress y is calculated and output by combining the dam body stress propagation velocity Vwave with the dam body vibration frequency fvib. The specific algorithm formula is: In the formula, π represents the circumference of a circle, which is 3.14, and △L represents the displacement change difference of the dam body; The thermal stress Ry of the dam body is calculated by the temperature difference change of the dam body temperature T and the thermal expansion of the dam body material. The specific algorithm formula is: Ry = E·α therm ·△T, where E represents the elastic modulus of the dam material, α therm represents the expansion coefficient, △T represents the temperature difference; The data storage unit constructs a SQL Server database and sets a transmission port, and writes the standard data set into the SQL Server database through the transmission port for data storage.

5. The water conservancy project safety monitoring system based on VR technology according to claim 1 is characterized by: The data coupling analysis module includes a stress and vibration coupling unit, a thermal stress influence unit, a soil moisture and water level coupling unit, and a settlement and friction coupling unit; The stress and vibration coupling unit extracts the micro stress y and the dam body vibration frequency fvib in the standard data set of each monitoring point in real time through the transmission port, inputs them into the stress and vibration coupling model, and calculates and outputs the stress and vibration coupling influence coefficient R y，fvib , analyze the concentration of stress caused by vibration of the dam body caused by external force; The stress and vibration coupling influence coefficient R y，fvib The output is calculated using the following stress-vibration coupling model; In the formula, Keff represents the effective anti-vibration coefficient of the dam body; The thermal stress influence unit extracts the dam body thermal stress Ry in the standard data set of each monitoring point in real time through the transmission port, inputs it into the temperature and thermal expansion coupling model, and calculates and outputs the temperature and thermal expansion coupling influence coefficient R thermal , analyze the temperature characteristics of the dam under temperature difference changes; The thermal expansion coupling influence coefficient R thermal The output is calculated using the following temperature and thermal expansion coupling model; In the formula, Ry max Indicates the upper limit of the thermal stress that the dam material can withstand.

6. The water conservancy project safety monitoring system based on VR technology according to claim 5 is characterized by: The soil moisture and water level coupling unit extracts the dam body soil moisture S and groundwater level hgw in the standard data set of each monitoring point in real time through the transmission port, inputs them into the moisture and water level coupling model, and calculates and outputs the soil moisture and water level coupling influence coefficient R S，hgw , analyze the impact of soil moisture changes on dam stability; The soil moisture and water level coupling influence coefficient R S，hgw The output is calculated by the following moisture-water level coupling model; In the formula, S0 represents the reference soil moisture, β represents the sensitivity coefficient of the dam soil moisture S and the groundwater level hgw, S max Indicates the upper limit of soil moisture; The settlement and friction coupling unit extracts the dam settlement Hsettle in the standard data set of each monitoring point in real time through the transmission port, inputs it into the settlement friction coupling model, and calculates and outputs the coupling coefficient R of the settlement and friction coefficient. friction , analyze the impact of soil moisture changes on dam stability; The coupling coefficient R of the settlement and friction coefficient friction The output is calculated by the following settlement friction coupling model; R friction =μ·P effective ·Hsettle; Where μ represents the friction coefficient between the dam body and the foundation surface, P effective Represents the effective load of the dam body.

7. The water conservancy project safety monitoring system based on VR technology according to claim 1 is characterized by: The preliminary analysis and positioning module includes a preliminary risk analysis unit and a preliminary risk assessment unit; The preliminary risk analysis unit combines the stress and vibration coupling influence coefficient R y，fvib , Temperature and thermal expansion coupling influence coefficient R thermal , soil moisture and water level coupling influence coefficient R S，hgw and the coupling coefficient R of the sedimentation and friction coefficient friction , perform comprehensive calculation to output the dam body safety factor SF, and conduct a preliminary analysis of the dam body safety status; The dam body safety factor SF is calculated and output by the following algorithm formula: Where a1, a2, a3 and a4 represent the stress and vibration coupling influence coefficients R y，fvib , Temperature and thermal expansion coupling influence coefficient R thermal , soil moisture and water level coupling influence coefficient R S，hgw and the coupling coefficient R of the sedimentation and friction coefficient friction The weight value is a1+a2+a3+a4=1, and the specific data value is preliminarily set by the user.

8. The water conservancy project safety monitoring system based on VR technology according to claim 1 is characterized by: The preliminary analysis and evaluation unit presets a preliminary risk threshold T1 based on the dam design standard, and then performs a preliminary comparative evaluation of the preliminary risk threshold T1 and the dam body safety factor SF, and locates the abnormal position of the dam through all monitoring points. The specific evaluation content is as follows; When the dam body safety factor SF ≤ the initial risk threshold T1, it means that the current dam body monitoring point is in a safe state, and monitoring should continue; When the dam safety factor SF is greater than the preliminary risk threshold T1, it indicates that there is an abnormality in the current dam monitoring point. At this time, it is fed back to the three-dimensional virtual model, and the dam sections on both sides of the current monitoring point are marked in red through color coding, and in-depth analysis is performed at the same time.

9. The water conservancy project safety monitoring system based on VR technology according to claim 8 is characterized by: The in-depth risk analysis module includes a in-depth analysis unit and a in-depth assessment unit; The depth analysis unit performs a depth analysis when an abnormality exists at a monitoring point of the dam body. The depth analysis extracts the stress and vibration coupling influence coefficient R y，fvib , Temperature and thermal expansion coupling influence coefficient R thermal , soil moisture and water level coupling influence coefficient R S，hgw and the coupling coefficient R of the sedimentation and friction coefficient friction , combined with the attenuation coefficient, calculate and output the deep safety factor SFD, and deeply analyze the safety situation of the current monitoring point; The depth safety factor SFD is calculated and output by the following algorithm formula; In the formula, e - represents an exponential decay function.

10. The water conservancy project safety monitoring system based on VR technology according to claim 9 is characterized in that: The depth assessment unit performs an average calculation and outputs a depth risk threshold T2 by analyzing 20 groups of depth safety factors SFD of the dam body when the stability is abnormal based on the user, and performs a depth analysis of the abnormal situation of the abnormal monitoring point of the dam body. The specific assessment thresholds are as follows; When the depth safety factor SFD> the depth risk threshold T2, it means that the current abnormal monitoring point of the dam is normal. At this time, an inspection warning is sent to prompt the user to wear a VR helmet to access the three-dimensional virtual model, inspect the abnormal monitoring point, and perform planned maintenance; When the depth safety factor SFD ≤ the depth risk threshold T2, it indicates that there is an abnormality at the current abnormal monitoring point of the dam body. At this time, a maintenance warning is sent to prompt the user to immediately conduct on-site monitoring and maintenance of the current monitoring point.

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