A multi-source data fusion monitoring system for geological disaster control engineering

Abstract

This invention belongs to the field of geological disaster engineering supervision technology. Specifically, it discloses a multi-source data fusion supervision system for geological disaster control projects. By realizing real-time data acquisition, multi-protocol parsing, high-precision time synchronization, advanced noise reduction, missing value imputation, outlier filtering, and preliminary feature extraction at the data source end, this invention significantly improves data quality and real-time performance, and reduces the processing burden on the central platform. Through real-time state mapping between the physical world and virtual space, and the identification and correction scheme matching of abnormal results in disaster control projects, it realizes multi-level early warning linkage and automatic emergency plan matching, and provides intuitive and comprehensive visualization and decision support. This greatly improves supervision efficiency, early warning accuracy, and emergency response speed, providing reliable technical support for the safe and stable operation of geological disaster control projects, and effectively reducing disaster risks and economic losses.

Description

Technical Field

[0001] This invention belongs to the field of geological disaster engineering supervision technology, specifically relating to a multi-source data fusion supervision system for geological disaster control projects. Background Technology

[0002] With the intensification of global climate change and the increasing frequency of human engineering activities, the frequency and severity of geological disasters are constantly rising, posing a serious threat to people's lives and property and infrastructure. To effectively address these challenges, the planning, implementation, and long-term monitoring of geological disaster mitigation projects have become particularly crucial, their complexity and importance increasingly prominent, prompting the continuous development of related monitoring technologies. Among these challenges, the monitoring of geological disaster mitigation projects faces the challenge of massive amounts of heterogeneous data, involving diverse information sources such as environmental monitoring, geological exploration, engineering construction, satellite remote sensing, and IoT sensors. Effectively integrating and deeply analyzing this scattered data to form a unified and comprehensive situational awareness capability is of decisive significance for improving monitoring efficiency, early warning accuracy, and the scientific nature of decision-making.

[0003] In existing technologies, monitoring systems for geological disaster control projects mostly adopt a single data source or a simple multi-source data overlay model, failing to fully address the issues of data heterogeneity, spatiotemporal differences, and inherent correlations between data. Various monitoring devices and platforms operate independently, with inconsistent data collection standards, resulting in severe data silos and hindering efficient data sharing and deep integration.

[0004] In addition, traditional analysis methods often focus on static threshold judgment or qualitative assessment based on historical experience, which are insufficient in identifying subtle changes and potential risks in the evolution of geological disasters and lack dynamic and real-time comprehensive judgment capabilities.

[0005] Furthermore, when processing massive amounts of multi-source data, the existing systems' fusion algorithms are usually computationally intensive and difficult to adapt to complex and ever-changing geological environments, resulting in low information utilization efficiency and poor early warning timeliness, which in turn restricts the level of precision in supervision and the timeliness of emergency response. Summary of the Invention

[0006] In view of this, in order to solve the problems mentioned in the background technology, a multi-source data fusion monitoring system for geological disaster control projects is proposed.

[0007] The objective of this invention can be achieved through the following technical solution: This invention provides a multi-source data fusion monitoring system for geological disaster control projects, including: a data acquisition module, a digital twin construction module, a working condition simulation module, a control project anomaly identification module, and an interactive decision support module.

[0008] The data acquisition module is connected to the digital twin construction module, the digital twin construction module is connected to the working condition simulation module, the working condition simulation module is connected to the governance project anomaly identification module and the interactive decision support module, and the governance project anomaly identification module is connected to the interactive decision support module.

[0009] The data acquisition module collects basic geological parameters, real-scene perception parameters, dynamic monitoring parameters, and engineering management parameters of the target geological disaster management area, and then merges them after standardization to obtain a multi-source dataset.

[0010] The digital twin construction module uses real-world perception parameters from multi-source datasets as a basis to construct a digital twin of the geological disaster body and the governance engineering structure.

[0011] The working condition simulation module simulates the evolution process of geological disasters under various working conditions in a digital twin and records the structural response parameters in key procedures of geological disaster control projects in real time.

[0012] The anomaly identification module for disaster mitigation projects compares the structural response parameters with the BIM model parameters in the digital twin to identify and output anomalies in the disaster mitigation project.

[0013] The interactive decision support module matches multiple corrective measures for disaster management projects based on abnormal results, compares the effects of simulation data, and displays the results through a 3D visualization interface.

[0014] Compared with the prior art, the beneficial effects of the present invention are as follows: 1. The present invention significantly improves data quality and real-time performance and reduces the processing burden of the central platform by realizing real-time data acquisition, multi-protocol parsing, high-precision time synchronization, advanced noise reduction, missing value imputation, outlier filtering and preliminary feature extraction at the data source end.

[0015] 2. This invention achieves multi-level early warning linkage and automatic emergency plan matching by real-time state mapping between the physical world and virtual space, as well as the identification and correction scheme matching of abnormal results in disaster management projects. It also provides intuitive and comprehensive visualization and decision support, which greatly improves the efficiency of supervision, the accuracy of early warning and the speed of emergency response. It provides reliable technical support for the safe and stable operation of geological disaster management projects and effectively reduces disaster risks and economic losses. Attached Figure Description

[0016] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0017] Figure 1 This is a schematic diagram of the system module connections of the present invention. Detailed Implementation

[0018] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0019] Please see Figure 1 As shown, this invention provides a multi-source data fusion monitoring system for geological disaster control projects, with the following specific module distribution: data acquisition module, digital twin construction module, working condition simulation module, control project anomaly identification module, and interactive decision support module.

[0020] The data acquisition module is connected to the digital twin construction module, the digital twin construction module is connected to the working condition simulation module, the working condition simulation module is connected to the governance project anomaly identification module and the interactive decision support module, and the governance project anomaly identification module is connected to the interactive decision support module.

[0021] The data acquisition module collects basic geological parameters, real-scene perception parameters, dynamic monitoring parameters, and engineering management parameters of the target geological disaster management area, and then merges them after standardization to obtain a multi-source dataset.

[0022] In a preferred feasible example of the present invention, the parameter acquisition in the data acquisition module specifically includes the following: acquiring acoustic emission signal data of the geological body inside the target geological disaster treatment area through a piezoelectric acoustic emission sensor, and recording it as basic geological parameters; acquiring visual data of the target geological disaster treatment area through one or more image acquisition devices, such as a high-definition video camera and a UAV-borne high-resolution camera, and recording it as real-scene perception data; acquiring displacement data of the engineering structure and strata in the target geological disaster treatment area through one or more displacement sensors, such as a GNSS receiver, tilt sensor, deflection sensor, and crack sensor, and recording it as dynamic monitoring parameters; and acquiring geological treatment project progress data, personnel and equipment data, and key process construction data of the target geological disaster treatment area through one or more methods, such as engineering construction ledger records, personnel and equipment management platform, and on-site testing equipment, collectively referred to as engineering management parameters.

[0023] In a preferred feasible example of the present invention, the specific content of the multi-source dataset obtained after standardization processing includes: protocol parsing and format conversion of the basic geological parameters, real-scene perception parameters, dynamic monitoring parameters and engineering management parameters of the target geological disaster management area.

[0024] In one specific embodiment of the above scheme, the protocol parsing and format conversion includes receiving Modbus or RS485 protocol data from displacement sensors, environmental sensors, and acoustic sensors through an industrial bus interface and parsing it into structured data frames; receiving data streams from high-definition video cameras through an Ethernet interface and encoding them into MPEG or H.264 format video streams; and receiving image data from UAV-borne high-resolution cameras through a wireless communication module and converting it into JPEG or PNG format image files.

[0025] The converted basic geological parameters, real-scene perception parameters, dynamic monitoring parameters, and engineering management parameters are time-stamped and data aligned.

[0026] In one specific embodiment of the above scheme, the timestamp synchronization and data alignment processing includes obtaining a high-precision timestamp through the global positioning system timing module and attaching it to each monitoring data, and resampling the data of different sensor sampling frequencies according to a preset sampling frequency using Lagrange interpolation or cubic spline interpolation methods to achieve alignment in the time dimension.

[0027] The basic geological parameters, real-scene perception parameters, dynamic monitoring parameters, and engineering management parameters after timestamp synchronization and data alignment are denoised, missing value imputed, and outlier filtered.

[0028] In a specific embodiment of the above scheme, the denoising, missing value imputation, and outlier filtering include denoising the sensor data using Kalman filtering or wavelet transform, imputing missing values ​​using linear interpolation, cubic spline interpolation, or a prediction model based on historical data, and identifying and removing outliers using statistical thresholds or isolated forest algorithms.

[0029] The processed data is standardized and its features are initially extracted to generate standardized preprocessed basic geological parameters, real-scene perception parameters, dynamic monitoring parameters and engineering management parameters with unified dimensions and scales. These parameters are then integrated to obtain a multi-source dataset.

[0030] This invention significantly improves data quality and real-time performance and reduces the processing burden on the central platform by enabling real-time data acquisition, multi-protocol parsing, high-precision time synchronization, advanced noise reduction, missing value imputation, outlier filtering, and preliminary feature extraction at the data source end.

[0031] The digital twin construction module uses real-world perception parameters from multi-source datasets as a basis to construct a digital twin of the geological disaster body and the governance engineering structure.

[0032] In a preferred feasible example of the present invention, the specific content of constructing a digital twin of the geological disaster body and the treatment engineering structure includes: using the real-scene perception parameters as a base, generating a three-dimensional mesh model of the disaster body and the engineering area using the LiDAR point cloud or oblique photography point cloud therein, and retaining key features including surface cracks, dangerous rock outlines, and valley morphology, as well as restoring the real appearance of the disaster body, and simplifying and optimizing the three-dimensional mesh model to balance model accuracy and rendering efficiency.

[0033] In a specific example, the restoration of the true appearance of the disaster body includes the following: using preprocessed oblique photogrammetric images as texture maps, attaching them to the surface of a 3D mesh model using UV mapping technology to restore the true appearance of the disaster body, such as the color of the soil and rock, vegetation cover, and surface texture of the engineering structure. Basic geographic elements such as topographic contour lines, roads, and administrative boundaries are added to construct an integrated real-world 3D base scene of the disaster body, engineering structure, and surrounding environment, and the output is in a format that supports real-time rendering, such as 3DTiles.

[0034] The generated 3D mesh model can be achieved through Poisson reconstruction or greedy projection triangulation algorithms.

[0035] The hazardous bodies include, but are not limited to, landslides, unstable rock masses, and debris flow gullies.

[0036] It should be noted that the simplification and optimization can be achieved through LOD hierarchical modeling, that is, using a low-precision mesh for distant models and a high-precision mesh for nearby and critical areas.

[0037] The basic geological parameters, dynamic monitoring parameters, and engineering management parameters are used as correlation parameters for adaptation processing. A refined model of the internal structure of the disaster body and the engineering structure is superimposed on the optimized and simplified three-dimensional mesh model to achieve a complete mapping of surface morphology and internal properties.

[0038] Construct a one-to-one correspondence table between physical entity IDs and virtual model IDs. Simultaneously, based on the logical relationship between geological disaster elements, monitoring equipment, and engineering structures, construct a unified data model, such as an object-oriented geographic data model, and establish a real-time transmission link to realize the construction of data access and update links.

[0039] It should be noted that the construction of the one-to-one correspondence table between physical entity ID and virtual model ID can be achieved by defining association rules through ontology or graph database.

[0040] For example, the association rule is as follows: displacement data of GNSS monitoring points of GNSS-005 → position update of virtual landslide points of corresponding Point-LP-005 → association with the overall stability calculation model of the landslide body.

[0041] The specific example of constructing a one-to-one correspondence table between physical entity ID and virtual model ID is as follows: binding an anti-slide pile with ID HP-001 in the physical world to an anti-slide pile component with ID Model-HP-001 in the virtual model; binding a GNSS monitoring point with ID GNSS-005 in the physical world to the corresponding coordinate point on the surface of the landslide body with ID Point-LP-005 in the virtual model.

[0042] It should also be noted that the specific method of constructing a unified data model based on the logical relationship between geological disaster elements, monitoring equipment and engineering structure is as follows: (1) Core fields include entity type such as disaster body or engineering component or monitoring equipment, spatial attributes such as coordinates and boundaries, state attributes such as displacement, stress and moisture content, time attributes such as data acquisition time and update time, and association ID such as associated physical entity ID and model ID; (2) Dynamic monitoring data such as GNSS displacement and seepage pressure, and engineering management data such as construction parameters are written into the unified data model in real time. Historical status is stored in a time series database such as InfluxDB, and spatial attributes are stored in a geospatial database such as PostGIS to ensure the efficiency of data retrieval.

[0043] The established real-time transmission link is as follows: monitoring equipment → edge computing unit → unified data model → virtual model.

[0044] In one specific example, monitoring devices such as GNSS receivers and piezometers transmit real-time data to an edge computing unit via 5G / LoRa / satellite communication. After data cleaning, the data is pushed to a unified data model. Data-driven update rules are set for the virtual model. For example, when the displacement value of "GNSS-005" in the unified data model exceeds 0.5 mm / day, the position coordinates of "Point-LP-005" in the virtual model are automatically updated, and the morphology of the landslide mesh model, such as the increase in crack width, is updated simultaneously. This achieves update delays of "millisecond-second" and can be adjusted according to scenario requirements. For example, monitoring of unstable rocks requires millisecond-level updates, while overall landslide monitoring can be updated in seconds, ensuring real-time synchronization of physical and virtual states.

[0045] The working condition simulation module simulates the evolution process of geological disasters under various working conditions in a digital twin and records the structural response parameters in key procedures of geological disaster control projects in real time.

[0046] In a preferred feasible example of the present invention, the various working conditions include, but are not limited to, natural extreme working conditions, geological dynamic working conditions, engineering disturbance working conditions, and composite risk working conditions.

[0047] It needs to be explained that the natural extreme working conditions mentioned refer to the scenarios caused by sudden, high-intensity natural events that may directly aggravate the risk of geological disasters. The core is that the natural external force breaks through the bearing limit of the geological body or engineering structure. Common manifestations include: (1) Extreme precipitation: such as continuous rainstorms with a daily rainfall of ≥50mm and torrential rainstorms with a daily rainfall of ≥250mm, which will cause the soil moisture content to rise sharply and the groundwater level to rise sharply, thereby softening the rock and soil, reducing the shear strength, and inducing landslides and debris flows; (2) Extreme earthquakes: such as earthquakes of magnitude 3 or above on the Richter scale, especially shallow earthquakes with a focal depth of <70km, which transmit vibration energy through seismic waves, causing unstable rock masses to collapse and landslides to slide as a whole; (3) Other extreme weather: such as strong typhoons (wind force ≥12) causing slope wind erosion and load changes, and snowstorms causing additional load accumulation on slopes, which may impact engineering structures such as slope protection and retaining dams.

[0048] The geological dynamic working conditions mentioned refer to the long-term and slow dynamic changes of the geological body itself. The core is the stability decrease caused by the gradual change of geological properties. Common manifestations include: (1) Creep of rock and soil: such as the slow deformation of landslide body under its own weight, i.e., the daily displacement of 0.1-1mm, and the slow cracking of dangerous rock mass along the fissure. Although the short-term changes are not obvious, the long-term accumulation will break through the safety threshold; (2) Dynamic changes of groundwater level: seasonal rise and fall of groundwater level, such as rise in the rainy season and fall in the dry season, and changes in the seepage field of the bank slope caused by fluctuations in the water level of surrounding water sources such as reservoirs and rivers, which in turn affect the pore water pressure of rock and soil and change the stability of the slope; (3) Small activities of geological structure: fault creep, such as annual displacement of a few millimeters to a few centimeters, will continuously disturb the surrounding rock and soil structure, causing changes in the stress distribution of the original treatment project such as anchor cables and anti-slide piles.

[0049] The engineering disturbance scenario refers to the interference caused by human activities to the geological body or existing structure during the construction of geological disaster control projects. The core is that the construction behavior breaks the original geological balance. Common manifestations are directly related to the engineering procedures: (1) Excavation disturbance: Excavation of foundation pits in anti-slide pile construction, such as depth ≥5m, and graded excavation of slope, such as single excavation height ≥3m, will remove part of the rock and soil, change the original slope stress state, and may induce local collapse; (2) Construction vibration: Anchor cable tensioning, such as tension control force ≥100kN, driving (2) Vibration waves generated by pile construction, such as impact pile driving, will disturb the surrounding soil and rock, which may lead to the expansion of existing cracks; (3) Load disturbance: The temporary stacking of construction materials such as sand, gravel and steel at the top of the slope, such as stacking height ≥2m, and the movement of construction machinery such as excavators and cranes in the project area will increase the additional load on the geological body and affect stability; (4) Drainage disturbance: The temporary blockage of the original drainage channel during the construction of the retaining dam will cause rainwater to accumulate in the area, or the excavation of the drainage channel will destroy the underground seepage path, causing the local groundwater level to rise.

[0050] The composite risk scenario refers to a complex scenario in which two or more single working scenarios are superimposed, resulting in a risk of 1+1>2. The core is that multiple factors work together to exacerbate the degree of disaster. Common combinations and manifestations include: (1) Natural extremes + engineering disturbances, such as slope excavation during rainstorms. The softening of the soil and rock caused by the rainstorm and the stress release brought by the excavation will greatly increase the probability of landslides, which is higher than the risk of a single rainstorm or a single excavation; (2) Geological dynamics + natural extremes, such as a landslide that has been creeping for a long time encountering a short-term rainstorm. The creep has brought the landslide close to the critical state of instability. The rainstorm further reduces the shear strength and may directly trigger a landslide; (3) Engineering disturbances + geological dynamics, such as the seasonal rise in the groundwater level during the construction of anti-slide piles. The construction excavation changes the stress and the rise in the water level increases the pore water pressure, which will lead to abnormal stress on the pile body.

[0051] The key processes include, but are not limited to, anti-slide pile construction, anchor cable and anchor rod construction, retaining dam and drainage channel construction, slope protection, and general management parameters.

[0052] In a preferred embodiment of the above steps, the structural response parameters for anti-slide pile construction include pile stress and deformation parameters, foundation stability parameters, concrete parameters, and concrete performance parameters.

[0053] The pile stress and deformation parameters include pile bending moment and shear force, and pile top horizontal displacement. The foundation stability parameters include pile bottom reaction force and retaining wall base slippage. The concrete performance parameters include early strength growth and crack propagation.

[0054] The structural response parameters for the construction of anchor cables and anchor rods include the stress state parameters of anchor rods and anchor cables, the mechanical response parameters of the anchorage section, and the deformation parameters of the surrounding rock and soil.

[0055] The stress state of the anchor bolt and anchor cable includes tension control force and prestress loss rate; the mechanical response parameters of the anchoring section include grout strain and shear stress at the interface between the anchor bolt and the soil; the deformation parameters of the surrounding soil include anchor bolt orifice displacement.

[0056] The structural response parameters for the construction of the retaining dam and drainage channel include drainage efficiency parameters, seepage pressure change parameters, and structural durability parameters.

[0057] The drainage efficiency parameters include single-hole drainage volume and intercepting ditch water level; the seepage pressure variation parameters include groundwater level depth and pore water pressure in the soil and rock mass; and the structural durability parameters include concrete impermeability grade.

[0058] The structural response parameters of the slope protection include excavated slope displacement parameters, slope stress variation parameters, and temporary support reaction force parameters.

[0059] The excavation slope displacement parameters include horizontal displacement and vertical settlement; the slope stress variation parameters include principal stress direction and magnitude and crack propagation rate; and the temporary support reaction force parameters include soil nail axial force.

[0060] The general management parameters include schedule parameters, personnel and equipment parameters, and environmental parameters.

[0061] The progress parameters include the start and end times of the work process and the deviation between the actual and planned construction periods; the personnel and equipment parameters include the qualification numbers of the construction personnel, the equipment numbers, and the equipment calibration times; and the environmental parameters include the temperature and rainfall during construction.

[0062] In a preferred feasible example of the present invention, the specific content of simulating the geological disaster evolution process under multiple working conditions in the digital twin includes: inputting corresponding quantitative parameters under multiple working conditions into the digital twin and setting boundary constraints, thereby obtaining the simulation environment of multiple working conditions in the digital twin.

[0063] For the above preferred example, for natural extreme working conditions, such as rainstorm working conditions, the input rainfall is as follows: if the daily rainfall is ≥50mm, it is rainstorm; if it is ≥250mm, it is torrential rainstorm; the rainfall intensity curve is as follows: the rainfall intensity is 10mm / h in the first 2 hours and 20mm / h in the next 6 hours.

[0064] For engineering disturbance conditions, such as slope excavation, input the single excavation depth ≥3m and the excavation rate, such as excavating 1 layer per day, with each layer being 1.5m; for anchor cable tensioning, input the tensioning control force, such as the design value of 150kN, with a deviation ≤±5%.

[0065] The boundary constraint conditions set are intended to simulate the constraints of geological bodies and engineering structures in the real physical world, and to ensure that the simulation does not break through the objective physical laws. It refers to the "Design Code for Geological Disaster Prevention and Control Engineering" and is set in combination with the actual engineering scenario. Common types and examples are as follows: (1) Load boundary: Defines the external forces acting on the geological body / engineering structure, such as the construction material load at the top of the slope and the slope wind load under typhoon conditions; (2) Fixed constraint boundary: Defines a fixed area that will not move, such as the constraint condition of the complete rock layer at the bottom of the slope is displacement = 0, that is, the rock layer will not move horizontally / vertically; (3) Seepage boundary: Defines the range and change limit of the groundwater level, such as the upper limit of the groundwater level under the rainstorm condition does not exceed 0.5m below the slope excavation surface, to avoid rainwater infiltration leading to slope instability.

[0066] Select appropriate mechanical algorithms based on different types of geological hazards to simulate the evolution of geological hazards during their occurrence and ensure simulation accuracy.

[0067] In one preferred example described above, the different types of geological hazards include rockfall hazards, debris flow hazards, and landslide hazards.

[0068] The mechanical algorithm corresponding to the rockfall disaster can be the discrete element algorithm, which simulates the unstable trajectory of the rock and accurately reproduces the dynamic process of the rock expanding from cracks to overall collapse and fall under conditions such as earthquakes and rainstorms. It captures the movement path and collision effect of individual or group of rockfalls, ensuring the simulation accuracy of the rockfall evolution process.

[0069] The mechanical algorithm corresponding to the debris flow disaster can be the finite difference method, which calculates the debris flow velocity and accumulation range. By discretizing the debris flow movement area into a finite grid, the fluid dynamics control equation is solved to simulate the flow velocity and impact force changes of the debris flow in the valley, as well as the accumulation morphology and range in the flat area, providing data support for the impact resistance design of projects such as retaining dams and drainage channels.

[0070] The mechanical algorithm corresponding to the landslide disaster can be the limit equilibrium method, which analyzes the stability coefficient of the landslide body. By assuming that the landslide body slides along a certain potential sliding surface, the anti-sliding force and sliding force on the sliding surface are calculated to obtain the stability coefficient. This method can then be used to determine the instability risk of the landslide body under different working conditions and guide the parameter design of anti-sliding projects such as anti-sliding piles and anchor cables.

[0071] In the digital twin platform, multiple working conditions and simulation environments, as well as mechanical algorithms corresponding to different types of geological disasters, are superimposed. Parallel computing is initiated to simulate the evolution of disasters in real time and to record the structural response parameters in key processes of geological disaster control projects in real time.

[0072] The anomaly identification module for disaster mitigation projects compares the structural response parameters with the BIM model parameters in the digital twin to identify and output anomalies in the disaster mitigation project.

[0073] In a preferred feasible example of the present invention, the specific content of identifying and outputting abnormal results of disaster control engineering includes: comparing the structural response parameters of key processes in the geological disaster control engineering with the corresponding parameters of the BIM model in the digital twin to obtain the absolute deviation and relative deviation values ​​of the structural response parameters of key processes in the geological disaster control engineering with the parameters of the BIM model, and summing them according to preset weights to obtain the comprehensive stability index of the structural response parameters of key processes in the geological disaster control engineering.

[0074] It should be explained that the absolute deviation value is the absolute value of the difference between the actual value and the standard value; the relative deviation value is the ratio of the absolute deviation value to the standard value of the BIM model, which is then converted into a percentage.

[0075] It should be noted that the absolute deviation value needs to be normalized during the weighted summation process.

[0076] In one specific example, the preset weight of the absolute deviation value is 0.6, and the preset weight of the relative deviation value is 0.4.

[0077] It should be further explained that the purpose of weighting and summing the absolute and relative deviation values ​​through preset weights is to comprehensively evaluate the parameter deviation from both the absolute value and the relative proportion. Then, the weights are used to highlight the safety priority, ultimately achieving accurate identification of anomalies in key processes. This avoids ignoring the proportional risks of a single absolute deviation and also avoids ignoring the actual physical impact of a single relative deviation, which meets the safety supervision requirements of geological disaster control projects.

[0078] By comparing the structural response parameter process logic diagrams in key processes of geological disaster control engineering with the BIM model parameter process logic diagrams in the digital twin, the degree of difference between the structural response parameters in key processes of geological disaster control engineering and the BIM model parameter process logic diagrams is obtained.

[0079] A specific example is that the specific method for obtaining the difference of the process logic diagram is as follows: assign values ​​to the differences of the three comparison dimensions in the process logic diagram, where the full score is 100 points and the larger the difference, the lower the score): (1) Judge the completeness of the process nodes: if there are no missing nodes, get 100 points; if one key node is missing, deduct 20 points; (2) Judge the compliance of the process logic order: if the order is completely consistent, get 100 points; if the order is reversed, deduct 10 points; (3) Judge the rationality of the node parameter association: if the parameters are completely matched, get 100 points; if one parameter exceeds the standard range, deduct 15 points.

[0080] This yields the difference scores for the three comparative dimensions in the process logic diagram. The average of these scores is then calculated to obtain the difference degree of the process logic diagram.

[0081] In a preferred feasible example of the present invention, the specific content of identifying and outputting abnormal results of disaster control projects further includes: if the comprehensive stability index of a certain parameter of the structural response parameter in the construction of anti-slide piles or slope protection of geological disaster control projects does not fall within the corresponding safety threshold range, it indicates that there is an abnormal structural displacement in the geological disaster control project.

[0082] If the comprehensive stability index of a certain parameter of the structural response parameter in the construction of anchor cables and anchor rods in a geological disaster control project does not fall within the corresponding safety threshold range, it indicates that there is structural stress anomaly in the geological disaster control project.

[0083] If the comprehensive stability index of a certain parameter of the structural response parameter in the construction of the retaining dam and drainage channel of the geological disaster control project does not fall within the corresponding safety threshold range, it indicates that the drainage function of the geological disaster control project is abnormal.

[0084] If the difference in the process logic diagram does not fall within the corresponding safety threshold range, it indicates that there is an abnormality in the compliance of the construction technology and process of the geological disaster control project.

[0085] The above content is further recorded as an abnormal result of the disaster management project and output.

[0086] The interactive decision support module matches multiple corrective measures for disaster management projects based on abnormal results, compares the effects of simulation data, and displays the results through a 3D visualization interface.

[0087] In a preferred feasibility example of the present invention, the specific content of matching multiple governance engineering correction schemes based on the abnormal results of disaster governance engineering includes: matching the abnormal results of disaster governance engineering with the multiple governance engineering correction schemes corresponding to each abnormal result stored in the scheme library to obtain multiple governance engineering correction schemes corresponding to the abnormal results of disaster governance engineering.

[0088] It should be further noted that examples of the solution library are shown in Table 1 below.

[0089] Table 1 Examples of Solution Library

[0090]

[0091] In a preferred feasible example of the present invention, the specific content of comparing the effects of simulation data includes: inputting each matched correction scheme into the working condition simulation module of the digital twin, conducting simulation based on the current abnormal scenario, extracting the comparison scores of preset dimensions, and calculating the comprehensive score of multiple governance engineering correction schemes by weighted summation.

[0092] It should be noted that the preset dimensions specifically include the recovery degree of abnormal parameters after correction, the increase in engineering cost, the extension of construction period, and the long-term stability coefficient. Furthermore, the higher the overall score, the stronger the feasibility of the solution.

[0093] In one specific example, the weights corresponding to the abnormal parameter recovery degree, the incremental engineering cost, the extended construction period and the long-term stability coefficient can be 0.4, 0.2, 0.3 and 0.1, respectively.

[0094] Through an interactive 3D visualization interface, the system can intuitively display the 3D models of various remediation engineering modification schemes, the changes in key parameters after simulation, such as the displacement of the anti-slide piles decreasing from 18mm to 14mm after Scheme 1 modification, and decreasing to 13mm after Scheme 2 modification, as well as the comprehensive score ranking.

[0095] This invention achieves multi-level early warning linkage and automatic emergency plan matching by real-time state mapping between the physical world and virtual space, as well as the identification and correction scheme matching of abnormal results in disaster management projects. It also provides intuitive and comprehensive visualization and decision support, which greatly improves the efficiency of supervision, the accuracy of early warning and the speed of emergency response. It provides reliable technical support for the safe and stable operation of geological disaster management projects and effectively reduces disaster risks and economic losses.

[0096] The above embodiments can be implemented, in whole or in part, by software, hardware, firmware, or any other combination thereof. When implemented using software, the above embodiments can be implemented, in whole or in part, in the form of a computer program product.

[0097] Those skilled in the art will recognize that the algorithmic steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this application.

[0098] In addition, the functional modules in the various embodiments of this application can be integrated into one processing module, or each module can exist physically separately, or two or more modules can be integrated into one module.

[0099] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

[0100] Finally, the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A multi-source data fusion monitoring system for geological disaster control projects, characterized in that: include: The data acquisition module collects basic geological parameters, real-scene perception parameters, dynamic monitoring parameters, and engineering management parameters of the target geological disaster control area, and then merges them after standardization to obtain a multi-source dataset. The digital twin construction module uses real-scene perception parameters from multi-source datasets as a basis to construct a digital twin of the geological disaster body and the governance engineering structure. The working condition simulation module simulates the evolution process of geological disasters under various working conditions in a digital twin and records the structural response parameters in key procedures of geological disaster control projects in real time. The various working conditions include, but are not limited to, natural extreme working conditions, geological dynamic working conditions, engineering disturbance working conditions, and complex risk working conditions. The key processes include, but are not limited to, anti-slide pile construction, anchor cable and anchor rod construction, retaining dam and drainage channel construction, slope protection, and general management parameters; The specific content of simulating the evolution process of geological disasters under various working conditions in a digital twin includes: Input the corresponding quantization parameters for various working conditions into the digital twin and set boundary constraints to obtain the simulation environment of various working conditions in the digital twin; Select appropriate mechanical algorithms based on different types of geological hazards to simulate the evolution process of geological hazards during their occurrence; In the digital twin platform, multiple working conditions and simulation environments, as well as mechanical algorithms corresponding to different types of geological disasters, are superimposed, parallel computing is initiated, the disaster evolution process is simulated in real time, and the structural response parameters in key procedures of geological disaster control projects are recorded in real time. The anomaly identification module for disaster mitigation projects compares the structural response parameters with the BIM model parameters in the digital twin to identify and output anomalies in disaster mitigation projects. The interactive decision support module matches multiple corrective measures for disaster management projects based on abnormal results, compares the effects of simulation data, and displays the results through a 3D visualization interface.

2. The multi-source data fusion monitoring system for geological disaster control projects according to claim 1, characterized in that: The parameter acquisition in the data acquisition module specifically includes the following: Acoustic emission signal data of the geological body inside the target geological disaster treatment area are acquired using piezoelectric acoustic emission sensors and recorded as basic geological parameters; visual data of the target geological disaster treatment area are acquired using one or more image acquisition devices, including high-definition video cameras and UAV-borne high-resolution cameras, and recorded as real-scene perception data; displacement data of the engineering structure and strata in the target geological disaster treatment area are acquired using one or more displacement sensors, including GNSS receivers, tilt sensors, deflection sensors, and crack sensors, and recorded as dynamic monitoring parameters; and geological treatment project progress data, personnel and equipment data, and key process construction data of the target geological disaster treatment area are acquired using one or more methods, including engineering construction ledger records, personnel and equipment management platforms, and on-site testing equipment, and collectively referred to as engineering management parameters.

3. The multi-source data fusion monitoring system for geological disaster control projects according to claim 2, characterized in that: The specific content of the multi-source dataset obtained after standardization and fusion includes: Protocol parsing and format conversion are performed on the basic geological parameters, real-scene perception parameters, dynamic monitoring parameters, and engineering management parameters of the target geological disaster control area; The converted basic geological parameters, real-scene perception parameters, dynamic monitoring parameters, and engineering management parameters are time-stamped and data aligned. Denoising, missing value imputation, and outlier filtering are performed on the basic geological parameters, real-scene perception parameters, dynamic monitoring parameters, and engineering management parameters after timestamp synchronization and data alignment. The processed data is standardized and its features are initially extracted to generate standardized preprocessed basic geological parameters, real-scene perception parameters, dynamic monitoring parameters and engineering management parameters with unified dimensions and scales. These parameters are then integrated to obtain a multi-source dataset.

4. The multi-source data fusion monitoring system for geological disaster control projects according to claim 2, characterized in that: The specific content of the digital twin of the geological hazard body and the mitigation engineering structure includes: Using the real-scene perception parameters as a base, a three-dimensional mesh model of the disaster body and the engineering area is generated, retaining key features including surface cracks, dangerous rock outlines, and valley morphology, and restoring the true appearance of the disaster body. The three-dimensional mesh model is then simplified and optimized. The basic geological parameters, dynamic monitoring parameters and engineering management parameters are used as correlation parameters for adaptation processing. A refined model of the internal structure of the disaster body and the engineering structure is superimposed on the optimized and simplified three-dimensional mesh model to achieve a complete mapping of surface morphology and internal properties. A one-to-one correspondence table between physical entity IDs and virtual model IDs is constructed. At the same time, based on the logical relationship between geological disaster elements, monitoring equipment, and engineering structures, a unified data model is constructed, and a real-time transmission link is established to realize the construction of data access and update links.

5. The multi-source data fusion monitoring system for geological disaster control projects according to claim 1, characterized in that: The specific content of identifying and outputting abnormal results of disaster mitigation projects includes: The structural response parameters in the key processes of geological disaster control engineering are compared with the corresponding parameters in the BIM model in the digital twin to obtain the absolute and relative deviation values ​​of the structural response parameters in the key processes of geological disaster control engineering and the parameters in the BIM model. These values ​​are then weighted and summed according to preset weights to obtain the comprehensive stability index of the structural response parameters in the key processes of geological disaster control engineering. By comparing the structural response parameter process logic diagrams in key processes of geological disaster control engineering with the BIM model parameter process logic diagrams in the digital twin, the degree of difference between the structural response parameters in key processes of geological disaster control engineering and the BIM model parameter process logic diagrams is obtained.

6. The multi-source data fusion monitoring system for geological disaster control projects according to claim 5, characterized in that: The specific content of identifying and outputting abnormal results of disaster mitigation projects also includes: If the comprehensive stability index of a certain parameter in the construction of anti-slide piles or slope protection in geological disaster control projects does not fall within the corresponding safety threshold range, it indicates that there is structural displacement anomaly in the geological disaster control project. If the comprehensive stability index of a certain parameter of the structural response parameter in the construction of anchor cables and anchor rods in a geological disaster control project does not fall within the corresponding safety threshold range, it indicates that there is structural stress anomaly in the geological disaster control project. If the comprehensive stability index of a certain parameter of the structural response parameter in the construction of the retaining dam and drainage channel of the geological disaster control project does not fall within the corresponding safety threshold range, it indicates that the geological disaster control project has abnormal drainage function. If the difference in the process logic diagram does not fall within the corresponding safety threshold range, it indicates that there is an abnormality in the compliance of the construction technology and process of the geological disaster control project. The above content is further recorded as an abnormal result of the disaster management project and output.

7. The multi-source data fusion monitoring system for geological disaster control projects according to claim 1, characterized in that: The specific content of matching multiple remediation engineering correction schemes based on abnormal results of disaster remediation engineering includes: The abnormal results of disaster mitigation projects are matched with the various mitigation project correction schemes corresponding to each abnormal result stored in the scheme library to obtain the various mitigation project correction schemes corresponding to the abnormal results of disaster mitigation projects.

8. The multi-source data fusion monitoring system for geological disaster control projects according to claim 7, characterized in that: The specific content of the simulation data effect comparison includes: Each matched correction scheme is input into the working condition simulation module of the digital twin, and a simulation is carried out based on the current abnormal scenario. The comparison scores of preset dimensions are extracted, and the comprehensive score of multiple governance engineering correction schemes is calculated by weighted summation. Through an interactive 3D visualization interface, the system intuitively displays 3D models of various remediation engineering modification schemes, changes in key parameters after simulation, and comprehensive score rankings.

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