Geotechnical engineering stability early warning system and method combining slope deformation monitoring and numerical simulation

Abstract

The invention discloses a geotechnical engineering stability early warning system and method combining side slope deformation monitoring and numerical simulation, and relates to the technical field of geotechnical engineering safety monitoring and disaster early warning. Side slope deformation monitoring and numerical simulation are combined, and multi-source real-time monitoring data of side slope deformation and numerical simulation are fused; constructing a dynamically updated slope deformation evolution analysis system; performing dynamic partition identification on the slope deformation evolution process according to the multi-source real-time monitoring data, and identifying a slope deformation threshold value and abnormal evolution characteristics of rock and soil; and setting an automatic triggering grading early warning signal of a geotechnical engineering early warning index, and completing slope risk dynamic assessment and early warning output of the rock and soil. According to the invention, the automatic triggering of the grading early warning signal is realized, the response speed, the judgment accuracy and the risk assessment scientificity of the geotechnical engineering early warning system are obviously improved, and the intelligent, dynamic and systematic technical support is provided for the safety prevention and control of the side slope.

Description

Technical Field

[0001] The present invention relates to the technical field of geotechnical engineering safety monitoring and disaster early warning, and in particular to a geotechnical engineering stability early warning system method combining slope deformation monitoring and numerical simulation. Background Art

[0002] With the continuous advancement of my country's infrastructure construction, geotechnical engineering is increasingly used in transportation, water conservancy, mining and other fields, and engineering safety issues are receiving more and more attention. With the development of information technology, sensing technology and numerical simulation methods, geotechnical engineering early warning is evolving towards intelligence and digitalization. The future development trend is to combine multi-source monitoring data with numerical simulation analysis to build a more scientific and efficient early warning system.

[0003] At present, in the current geotechnical engineering early warning technology, slope deformation monitoring mostly relies on the collection of parameters such as displacement and stress at discrete points, which makes it difficult to achieve continuous and dynamic perception of the deformation state of the entire slope body. Numerical simulation analysis is usually based on the initial geological model and static parameters for prediction, and lacks effective linkage with on-site real-time monitoring data, resulting in a large deviation between the simulation results and the actual deformation trend. This fragmented data processing method makes the existing early warning system respond lag and lack judgment basis when facing complex geological conditions and sudden deformation evolution, which seriously affects the scientific nature and timeliness of the early warning. Summary of the Invention

[0004] In view of the problems existing in the existing geotechnical engineering stability early warning system method combining slope deformation monitoring and numerical simulation, the present invention is proposed.

[0005] Therefore, the problem to be solved by the present invention is how to achieve continuous dynamic perception of slope deformation in geotechnical engineering and real-time fusion feedback of numerical simulation to improve the response speed and judgment accuracy of the early warning system.

[0006] In order to solve the above technical problems, the present invention provides the following technical solutions:

[0007] In a first aspect, an embodiment of the present invention provides a geotechnical engineering stability early warning system method that combines slope deformation monitoring and numerical simulation, including: the geotechnical engineering early warning includes combining slope deformation monitoring and numerical simulation, and the combining of slope deformation monitoring and numerical simulation includes fusing multi-source real-time monitoring data of slope deformation with numerical simulation to construct a dynamically updated slope deformation evolution analysis system;

[0008] Based on the slope deformation evolution analysis system and multi-source real-time monitoring data, the slope deformation evolution process is dynamically partitioned and identified to identify the slope deformation threshold and abnormal evolution characteristics of rock and soil;

[0009] The identification results are used as the basis for geotechnical engineering early warning, and the automatic triggering of graded early warning signals of geotechnical engineering early warning indicators is set to complete the dynamic assessment of geotechnical slope risks and early warning output.

[0010] As a preferred solution of the geotechnical engineering stability early warning system method combining slope deformation monitoring and numerical simulation described in the present invention, obtaining multi-source real-time monitoring data of the slope deformation includes utilizing underground collaborative monitoring technology to scan the slope body and invert the internal structure through a multi-band ground-based interferometric radar array and electromagnetic wave detection equipment deployed around the slope to obtain information on slope surface deformation and internal medium parameter changes;

[0011] The underground collaborative monitoring technology refers to the fusion imaging technology of microwave interferometry and ground-based electromagnetic wave inversion;

[0012] The internal structure inversion includes a technique for inverting surface deformation by analyzing the phase difference between radar echoes using microwave interferometry;

[0013] Microwave interferometry refers to the use of microwave radar to transmit and receive electromagnetic wave signals and calculate the phase difference between radar echoes. The phase difference calculation formula is:

[0014]

[0015] in, represents the phase difference, represents the radar wavelength, Indicates the displacement of the ground surface along the radar line of sight;

[0016] A ground-based electromagnetic detection network is constructed by receiving electromagnetic wave signals, emitting electromagnetic waves to the underground rock and soil, recording the amplitude attenuation caused by the time delay of the electromagnetic wave reflection signal, and combining it with internal structure inversion to reconstruct the change information of the internal medium parameters of the underground rock and soil.

[0017] As a preferred solution of the geotechnical engineering stability early warning system method combining slope deformation monitoring and numerical simulation described in the present invention, the fusion of multi-source real-time monitoring data of slope deformation and numerical simulation includes uniformly mapping the two types of monitoring data, namely the phase difference and information on changes in parameters of the underground rock and soil internal medium, into a three-dimensional geological model as a basis for updating input parameters to complete the fusion process;

[0018] The fusion process includes dynamically adjusting the state of the 3D geological model, building a two-way interactive feedback mechanism for the 3D geological model, and establishing a process for fusing multi-source real-time monitoring data of slope deformation with numerical simulation;

[0019] The dynamic adjustment of the state of the three-dimensional geological model includes calculating the phase difference relationship between radar echoes using microwave interferometry to dynamically adjust the stress state and boundary displacement in the three-dimensional geological model;

[0020] The two-way interactive feedback mechanism for constructing the three-dimensional geological model includes dividing the numerical simulation into zones based on boundary displacement to complete a closed-loop two-way interactive feedback mechanism for the three-dimensional geological model;

[0021] When the 3D geological model is in a closed-loop two-way interactive feedback mechanism, an error identification module is introduced to compare the errors generated by the fusion of multi-source real-time monitoring data and numerical simulation to obtain the differences between the measured data;

[0022] When the deviation exceeds the set threshold At this time, a dynamically updated slope deformation evolution analysis system is constructed.

[0023] As a preferred solution of the geotechnical engineering stability early warning system method combining slope deformation monitoring and numerical simulation described in the present invention, the construction of a dynamically updated slope deformation evolution analysis system includes simulating and guiding the monitoring of phase differences and parameter changes of underground rock and soil internal media;

[0024] The construction of the dynamically updated slope deformation evolution analysis system also includes performing monitoring feedback simulation on the boundary position of the numerical simulation area and the shift closed-loop two-way interactive feedback mechanism.

[0025] As a preferred solution of the geotechnical engineering stability early warning system method combining slope deformation monitoring and numerical simulation described in the present invention, the dynamic zoning identification includes inputting multi-source real-time monitoring data into the process of slope deformation evolution analysis, the multi-source real-time monitoring data including rock surface deformation variables obtained by inverting phase difference information obtained by ground-based interferometric radar, using a multi-physical field feature fusion algorithm to normalize the simulation-guided monitoring and monitoring feedback simulation processes, and extracting the time series characteristics of the rock surface deformation variables and the spatial distribution characteristics of the rock underground medium;

[0026] The time series characteristics refer to the response of radar wavelengths in different time periods, and the spatial distribution characteristics of the rock and soil underground medium refer to the spatial distribution section A, section B or section C of the rock and soil underground medium corresponding to the zoning performed by the numerical simulation;

[0027] Feed the results of spatial distribution characteristics into the numerical simulation process to locally model different spatial distributions;

[0028] The local modeling includes:

[0029] The rock surface and underground synchronous deformation zone;

[0030] Hysteresis deformation zone of rock and soil surface;

[0031] The rock and soil underground medium changes suddenly but the surface is stable;

[0032] potential sliding path evolution zone of geotechnical areas;

[0033] The identification of slope deformation thresholds and abnormal evolution characteristics of rock and soil includes introducing graph neural networks for local modeling and identification;

[0034] The introduction of graph neural networks for local modeling and identification includes using microwave interferometry to calculate the phase difference relationship between radar echoes and dynamically adjust the boundaries of local modeling to ensure that the spatial distribution partition results of the rock and soil underground medium evolve synchronously with the actual deformation state of the slope;

[0035] Feeding the current distribution zoning results back to the numerical simulation process realizes closed-loop spatial distribution zoning of rock and soil underground media.

[0036] As a preferred embodiment of the geotechnical engineering stability early warning system method combining slope deformation monitoring and numerical simulation according to the present invention, the automatic triggering of the graded early warning signal includes, during the local modeling process, constructing an early warning indicator system based on the historical slope database and the currently identified deformation evolution characteristics. The early warning indicator system includes:

[0037] Surface deformation rate threshold;

[0038] Displacement acceleration change rate;

[0039] Sudden changes in underground medium parameter gradients;

[0040] Deviation of potential sliding path evolution trend;

[0041] Regional deformation pattern matching degree;

[0042] The spatial overlap between the stress concentration area and the deformation area;

[0043] The early warning indicator system is input into the learning fusion early warning decision model, which automatically determines the current risk level based on the current slope status and historical evolution path.

[0044] As a preferred solution of the geotechnical engineering stability early warning system method combining slope deformation monitoring and numerical simulation of the present invention, the step of automatically determining the current risk level is as follows:

[0045] When the comprehensive warning index value of a certain area exceeds the set first-level threshold, the system automatically triggers a yellow warning signal, marks the area as a focus area, and starts the high-frequency monitoring mode and local simulation update process;

[0046] When the comprehensive warning index value rises further and exceeds the secondary threshold, the system triggers an orange warning signal, marking the area as a critical deformation zone, and pushes the warning information to the slope management platform to activate the emergency response plan;

[0047] When the deformation evolution trend of a certain area continues to worsen and the comprehensive warning index value exceeds the third-level threshold, the system automatically triggers a red warning signal, marking the area as a high-risk area for instability, and links with a third-party emergency command system to push landslide path prediction results and emergency avoidance recommendations;

[0048] When the warning signal is triggered, the system generates a warning event log, recording the trigger time, trigger indicators, warning level, regional location and key parameters of simulation feedback information, and feeds the event back to the warning decision model to optimize model parameters and threshold settings, and complete the dynamic assessment of rock and soil slope risks and warning output.

[0049] In a second aspect, an embodiment of the present invention provides a geotechnical engineering early warning system, comprising:

[0050] S310: Fusion module, wherein the geotechnical engineering early warning includes combining slope deformation monitoring and numerical simulation, wherein the combining slope deformation monitoring and numerical simulation includes fusing multi-source real-time monitoring data of slope deformation with numerical simulation to construct a dynamically updated slope deformation evolution analysis system;

[0051] S320: Identification module, based on the slope deformation evolution analysis system and using multi-source real-time monitoring data, dynamically partitions and identifies the slope deformation evolution process, identifying the slope deformation threshold and abnormal evolution characteristics of the rock and soil;

[0052] S330: Early warning module, which uses the identification results as the basis for geotechnical engineering early warning, sets the automatic triggering of graded early warning signals for geotechnical engineering early warning indicators, and completes the dynamic assessment of geotechnical slope risks and early warning output.

[0053] In a third aspect, an embodiment of the present invention provides a computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: when the processor executes the computer program, it implements any step of the above-mentioned geotechnical engineering stability early warning system method combining slope deformation monitoring and numerical simulation.

[0054] In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein: when the computer program is executed by a processor, any step of the above-mentioned geotechnical engineering stability early warning system method combining slope deformation monitoring and numerical simulation is implemented.

[0055] The beneficial effects of the present invention are as follows: the present invention realizes continuous perception and intelligent identification of the evolution process of slope deformation by constructing a dynamic update system that integrates multi-source real-time monitoring data and numerical simulation, and adopts underground collaborative monitoring means that combines ground-based interferometric radar with electromagnetic wave detection technology, breaking through the limitations of traditional point monitoring, improving the ability to synchronously acquire surface and underground deformation characteristics, introducing graph neural networks for dynamic zoning identification, and establishing a closed-loop feedback mechanism between simulation and monitoring, thereby enhancing the model's adaptability to complex geological conditions and prediction accuracy; based on a multi-dimensional early warning indicator system and a fusion decision-making model, the present invention realizes the automatic triggering of graded early warning signals, significantly improving the response speed, judgment accuracy and scientific nature of risk assessment of geotechnical engineering early warning systems, and providing intelligent, dynamic and systematic technical support for slope safety prevention and control. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] To more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. Those skilled in the art can also derive other drawings based on these drawings without inventive effort. Among them:

[0057] Figure 1 A flow chart of a specific method of a geotechnical engineering stability early warning system method combining slope deformation monitoring and numerical simulation provided by one embodiment of the present invention.

[0058] Figure 2 A specific system flow chart of a geotechnical engineering stability early warning system method combining slope deformation monitoring and numerical simulation provided by one embodiment of the present invention. DETAILED DESCRIPTION

[0059] To make the above-mentioned objects, features, and advantages of the present invention more clearly understood, the following detailed description of the specific embodiments of the present invention is given in conjunction with the accompanying drawings. It is obvious that the described embodiments are only part of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in this field without creative work should fall within the scope of protection of the present invention.

[0060] In the following description, many specific details are set forth to facilitate a full understanding of the present invention. However, the present invention may also be implemented in other ways different from those described herein. Those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0061] Secondly, the term "one embodiment" or "embodiment" herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The phrase "in one embodiment" appearing in various places throughout this specification does not necessarily refer to the same embodiment, nor does it refer to a separate or selective embodiment that is mutually exclusive of other embodiments.

[0062] The present invention is described in detail with reference to schematic diagrams. For ease of illustration, cross-sectional views of device structures may be partially enlarged and not to scale when describing embodiments of the present invention. Furthermore, the schematic diagrams are merely illustrative and should not limit the scope of the present invention. Furthermore, in actual production, the three-dimensional dimensions of length, width, and depth should be included.

[0063] In the description of the present invention, it should be noted that the terms "upper, lower, inner, and outer" and other references to orientations or positional relationships are based on the orientations or positional relationships shown in the accompanying drawings and are intended solely to facilitate and simplify the description of the present invention. They are not intended to indicate or imply that the devices or components referred to must have, be constructed, or operate in a specific orientation, and therefore should not be construed as limitations on the present invention. Furthermore, the terms "first, second, or third" are used for descriptive purposes only and should not be construed as indicating or implying relative importance.

[0064] In this disclosure, unless otherwise specified or limited, the terms "mounted," "connected," and "connected" should be interpreted broadly. For example, they may refer to fixed, removable, or integral connections. They may also refer to mechanical, electrical, or direct connections, indirect connections through an intermediary, or internal communication between two components. Those skilled in the art will understand the specific meanings of these terms in this disclosure.

[0065] Example 1

[0066] Reference Figure 1 and Figure 2 , which is the first embodiment of the present invention, provides a geotechnical engineering stability early warning system method combining slope deformation monitoring and numerical simulation, including:

[0067] S1: Geotechnical engineering early warning includes combining slope deformation monitoring and numerical simulation. Combining slope deformation monitoring and numerical simulation includes fusing multi-source real-time monitoring data of slope deformation with numerical simulation to build a dynamically updated slope deformation evolution analysis system.

[0068] Acquiring multi-source real-time monitoring data on slope deformation involves utilizing underground collaborative monitoring technology. By deploying multi-band ground-based interferometric radar arrays and electromagnetic wave detection equipment around the slope, the slope body is scanned and its internal structure inverted to obtain information on slope surface deformation and changes in internal medium parameters.

[0069] Underground collaborative monitoring technology refers to the fusion imaging technology of microwave interferometry and ground-based electromagnetic wave inversion;

[0070] Internal structure inversion includes the technology of using microwave interferometry to invert surface deformation by analyzing the phase difference between radar echoes;

[0071] Microwave interferometry refers to the use of microwave radar to transmit and receive electromagnetic wave signals and calculate the phase difference between radar echoes. The phase difference calculation formula is:

[0072]

[0073] in, represents the phase difference, represents the radar wavelength, Indicates the displacement of the ground surface along the radar line of sight;

[0074] A ground-based electromagnetic detection network is constructed by receiving electromagnetic wave signals, emitting electromagnetic waves to the underground rock and soil, recording the amplitude attenuation caused by the time delay of the electromagnetic wave reflection signal, and combining it with internal structure inversion to reconstruct the change information of the internal medium parameters of the underground rock and soil.

[0075] S1.1: Fusion of multi-source real-time monitoring data of slope deformation with numerical simulations involves mapping two types of monitoring data, phase difference and underground rock and soil internal medium parameter change information, into a unified 3D geological model, which serves as the basis for input parameter updates to complete the fusion process.

[0076] The fusion process includes dynamically adjusting the state of the 3D geological model, building a two-way interactive feedback mechanism for the 3D geological model, and establishing a process for fusing multi-source real-time monitoring data of slope deformation with numerical simulations;

[0077] Dynamically adjusting the state of the three-dimensional geological model includes calculating the phase difference relationship between radar echoes using microwave interferometry and dynamically adjusting the stress state and boundary displacement in the three-dimensional geological model;

[0078] The two-way interactive feedback mechanism for constructing a three-dimensional geological model includes dividing the numerical simulation into zones based on boundary displacements, thus completing a closed-loop two-way interactive feedback mechanism for the three-dimensional geological model;

[0079] When the 3D geological model is in a closed-loop two-way interactive feedback mechanism, an error identification module is introduced to compare the errors generated by the fusion of multi-source real-time monitoring data and numerical simulation to obtain the differences between the measured data;

[0080] When the deviation exceeds the set threshold At this time, a dynamically updated slope deformation evolution analysis system is constructed.

[0081] Furthermore, in the present invention, the threshold values ​​set include multiple key parameters, which are used to determine whether the deviation between the multi-source real-time monitoring data and the numerical simulation results exceeds a reasonable range, thereby triggering the model update and early warning response, specifically including: when the deviation between the surface deformation monitoring value and the simulation prediction value exceeds ±5 mm and continues to exceed the standard for multiple consecutive time steps, it is determined to be a surface deformation anomaly; when the displacement acceleration deviation exceeds ±0.5 mm / d², it is identified as a sudden change in deformation trend; when the gradient variation of underground medium parameters (such as conductivity and dielectric constant) between adjacent areas exceeds ±10%, it is determined to be an abnormal underground structure evolution; at the same time, a weighted error identification module is introduced. When the comprehensive error index exceeds the set threshold (such as the error weight coefficient reaches above 0.7), it is determined that there is a significant deviation between the model prediction and the actual state, triggering the dynamic update of the three-dimensional geological model and the reconstruction of the slope deformation evolution analysis system. The above threshold setting combines engineering experience and actual monitoring accuracy, has good operability and practicality, and can effectively support the implementation of the model-monitoring two-way feedback mechanism in the present invention, improving the accuracy of slope deformation analysis and the timeliness of early warning response. The key threshold parameters used for the monitoring and simulation fusion feedback mechanism are shown in Table 1 below:

[0082] Table 1 Key threshold parameters for monitoring and simulation fusion feedback mechanism

[0083]

[0084] Table 1 sets multidimensional threshold parameters, including surface deformation deviation (±5 mm), displacement acceleration deviation (±0.5 mm / d²), underground medium parameter gradient change (±10%), and a comprehensive error threshold (weight coefficient ≥ 0.7). Combined with a continuous deviation time step (≥ 3 steps), this approach enables accurate identification of slope deformation states and dynamic model updates. This provides a quantitative basis for the integrated feedback mechanism of monitoring and numerical simulation, improving the real-time and accuracy of the early warning system.

[0085] S1.2: Construct a dynamically updated slope deformation evolution analysis system, including simulation-guided monitoring of phase differences and parameter changes of underground rock and soil internal media.

[0086] The construction of a dynamically updated slope deformation evolution analysis system also includes the boundary position of the numerical simulation zone and the closed-loop two-way interactive feedback mechanism for monitoring and feedback simulation.

[0087] S2: Based on the slope deformation evolution analysis system and multi-source real-time monitoring data, the slope deformation evolution process is dynamically partitioned and identified to identify the slope deformation threshold and abnormal evolution characteristics of rock and soil.

[0088] Dynamic zoning identification involves inputting multi-source real-time monitoring data into the slope deformation evolution analysis process. The multi-source real-time monitoring data includes rock surface deformation variables obtained by inverting phase difference information obtained by ground-based interferometric radar. The multi-physics field feature fusion algorithm is used to normalize the simulation-guided monitoring and monitoring feedback simulation processes to extract the time series characteristics of the rock surface deformation variables and the spatial distribution characteristics of the rock underground medium.

[0089] The time series characteristics refer to the response of radar wavelengths in different time periods. The spatial distribution characteristics of the rock and soil underground medium refer to the spatial distribution of the rock and soil underground medium in the A section, B section or C section corresponding to the numerical simulation.

[0090] Feed the results of spatial distribution characteristics into the numerical simulation process to locally model different spatial distributions;

[0091] Local modeling includes:

[0092] The rock surface and underground synchronous deformation zone;

[0093] Hysteresis deformation zone of rock and soil surface;

[0094] The rock and soil underground medium changes suddenly but the surface is stable;

[0095] potential sliding path evolution zone of geotechnical areas;

[0096] Identifying the slope deformation threshold and abnormal evolution characteristics of rock and soil includes introducing graph neural networks for local modeling and identification;

[0097] The introduction of graph neural networks for local modeling and identification involves using microwave interferometry to calculate the phase difference between radar echoes and dynamically adjust the boundaries of local modeling, so that the spatial distribution of the rock and soil underground medium evolves synchronously with the actual deformation state of the slope.

[0098] Feeding the current distribution zoning results back to the numerical simulation process realizes closed-loop spatial distribution zoning of rock and soil underground media.

[0099] Furthermore, the synchronous deformation zone of the rock surface and underground refers to the area where the surface deformation and the changing trend of the underground medium parameters are highly consistent. It is manifested as the surface displacement changes monitored by the ground-based interferometric radar and the underground medium parameters (such as conductivity and dielectric constant) identified by electromagnetic wave inversion occur significantly at the same time. This area usually reflects an obvious overall compression or sliding trend of the rock and soil body, which is an early manifestation of the overall instability risk of the slope. In the numerical simulation, this area is modeled using a unified constitutive model and material parameters, and its boundary displacement and stress state are dynamically updated through the fused monitoring data to predict its evolution path and potential sliding risk.

[0100] The rock and soil surface hysteresis deformation zone is characterized by surface deformation lagging behind changes in the underground medium. That is, electromagnetic wave detection identifies that the underground structure (such as weak interlayers and fracture zones) has undergone a mutation, but there has been no obvious displacement on the surface. This usually indicates that stress redistribution or plastic failure has occurred inside the rock and soil mass, and it is in the deformation incubation period. In numerical simulations, a time-dependent constitutive model (such as a viscoelastic-plastic model) is introduced into this area, and combined with the deformation evolution trend identified by the graph neural network, its surface response lag time and deformation release intensity are predicted, providing early signal input for the early warning model.

[0101] In areas where the ground is experiencing sudden changes in the underground medium but the surface is stable, surface monitoring data may be stable, but electromagnetic wave inversion may identify significant changes in underground medium parameters (such as conductivity and dielectric constant). This may indicate the expansion of underground fractures, the formation of aquifers, or the initial development of sliding surfaces. In numerical simulations, this area is identified as a "structural anomaly zone" and modeled using a localized inhomogeneous material model. A highly sensitive monitoring feedback mechanism is also implemented. If a surface response is observed in this area during subsequent monitoring, the model is immediately updated and the warning level is upgraded.

[0102] The potential sliding path evolution zone of geotechnical rocks is an area with sliding tendency identified by graph neural networks. It is usually characterized by a high degree of coupling between surface and underground deformation characteristics, increased displacement acceleration, and significant gradient changes in underground medium parameters. It is highly coincident with the stress concentration area output by numerical simulation. In numerical simulation, this area is used as a key warning area and is modeled using a sliding surface tracking algorithm (such as DDA and FLAC3D sliding surface identification module). The sliding path prediction results are dynamically updated in combination with multi-source monitoring data to provide a basis for triggering graded warning signals.

[0103] S3: Use the identification results as the basis for geotechnical engineering early warning, set the automatic triggering graded early warning signal of geotechnical engineering early warning indicators, and complete the dynamic assessment of geotechnical slope risk and early warning output.

[0104] The automatic triggering of graded warning signals involves building a warning indicator system based on the historical slope database and the currently identified deformation evolution characteristics during the local modeling process. The warning indicator system includes:

[0105] Surface deformation rate threshold;

[0106] Displacement acceleration change rate;

[0107] Sudden changes in underground medium parameter gradients;

[0108] Deviation of potential sliding path evolution trend;

[0109] Regional deformation pattern matching degree;

[0110] The spatial overlap between the stress concentration area and the deformation area;

[0111] The early warning indicator system is input into the learning fusion early warning decision model. The early warning decision model automatically determines the current risk level based on the current slope status and historical evolution path.

[0112] Furthermore, the surface deformation rate threshold, a metric used to characterize the rate of change in slope surface displacement per unit time, is obtained through phase difference inversion using ground-based interferometric radar. In this paper, the surface deformation rate threshold is set between 0.5 mm / d and 5 mm / d, with different thresholds corresponding to different warning levels. This metric serves as a key parameter for identifying the early stages of slope deformation. It is compared with the boundary displacement changes output by numerical simulations to determine whether the slope has entered the accelerated deformation stage and is an important basis for triggering a yellow warning.

[0113] The displacement acceleration rate reflects the changing trend of the surface deformation rate and is obtained through time series analysis of continuous monitoring data. This method uses the second-order displacement difference method to calculate acceleration, and sets the displacement acceleration rate change threshold to ±0.2 mm / d² to ±1.0 mm / d². When this indicator exceeds the set threshold, it indicates that the slope deformation has entered the acceleration phase from the stable phase. This is an important signal for determining whether the slope has entered the "critical instability period" and is often used to trigger an orange warning.

[0114] The underground medium parameter gradient mutation value identifies potential slip surfaces or fracture zones by analyzing the spatial gradient changes in underground medium parameters (such as conductivity and dielectric constant) obtained through ground-based electromagnetic wave detection inversion. In this invention, the medium parameter gradient change threshold is set at ±5% to ±15%. Areas exceeding this threshold are identified as areas of abnormal underground structural evolution. This indicator overcomes the limitations of traditional surface monitoring, enabling the system to proactively identify areas of potential risk of "surface stability and underground instability," providing a key basis for red alerts.

[0115] The potential sliding path evolution trend deviation is used to measure the degree of deviation between the potential sliding path identified by the graph neural network and the path predicted by numerical simulation. In this paper, the path deviation is calculated using a spatial matching algorithm, with a deviation threshold set between 10% and 30%. When the deviation exceeds the set value, it indicates that the actual deformation path of the slope has deviated from the model-predicted path, which may indicate a change in the sliding mechanism or a sudden change in the local structure. It is an important basis for the early warning system to determine whether the model needs to be updated.

[0116] Regional deformation pattern matching degree, this indicator is used to evaluate the degree of matching between the currently identified slope deformation pattern (such as synchronous deformation, lagged deformation, local mutation, etc.) and the historical typical deformation pattern. In this invention, a graph neural network is used to extract features and perform pattern recognition, and the matching threshold is set at 70% to 90%. The higher the matching degree, the more similar the current deformation evolution trend is to the historical instability pattern, and the more sufficient the judgment basis of the early warning system. This indicator is mainly used for intelligent judgment of the warning level and triggering of the model feedback mechanism.

[0117] The spatial overlap between stress concentration areas and deformation zones is determined by spatially superimposing the stress concentration areas identified by numerical simulation with the deformation areas identified by monitoring. This method quantifies this overlap using a spatial overlap index (such as the Jaccard similarity coefficient), with an overlap threshold set between 50% and 80%. A high overlap indicates that the deformation zone is in a critical stage of stress release, a precursor to increased slip risk. This metric is often used to trigger orange and red alerts and to optimize local modeling parameters.

[0118] Preferably, the steps for automatically determining the current risk level are as follows:

[0119] When the comprehensive warning index value of a certain area exceeds the set first-level threshold, the system automatically triggers a yellow warning signal, marks the area as a focus area, and starts the high-frequency monitoring mode and local simulation update process;

[0120] When the comprehensive warning index value rises further and exceeds the secondary threshold, the system triggers an orange warning signal, marking the area as a critical deformation zone, and pushes the warning information to the slope management platform to activate the emergency response plan;

[0121] When the deformation evolution trend of a certain area continues to worsen and the comprehensive warning index value exceeds the third-level threshold, the system automatically triggers a red warning signal, marking the area as a high-risk area for instability, and links with a third-party emergency command system to push landslide path prediction results and emergency avoidance recommendations;

[0122] When the warning signal is triggered, the system generates a warning event log, recording the trigger time, trigger indicators, warning level, regional location and key parameters of simulation feedback information, and feeds the event back to the warning decision model to optimize model parameters and threshold settings, and complete the dynamic assessment of rock and soil slope risks and warning output.

[0123] In a preferred embodiment, a geotechnical engineering stability early warning system that combines slope deformation monitoring and numerical simulation includes a fusion module, wherein the geotechnical engineering early warning includes combining slope deformation monitoring and numerical simulation, and combining slope deformation monitoring and numerical simulation includes fusing multi-source real-time monitoring data of slope deformation with numerical simulation to construct a dynamically updated slope deformation evolution analysis system; an identification module, which is based on the slope deformation evolution analysis system and dynamically partitions and identifies the slope deformation evolution process according to multi-source real-time monitoring data, and identifies the slope deformation threshold and abnormal evolution characteristics of the geotechnical engineering; an early warning module, which uses the identification results as the basis for geotechnical engineering early warning, sets the automatic triggering graded early warning signal of the geotechnical engineering early warning index, and completes the dynamic assessment of the slope risk of the geotechnical engineering and early warning output.

[0124] The above-mentioned unit modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the processor can call and execute the corresponding operations of the above-mentioned modules.

[0125] The computer device may be a terminal, comprising a processor, a memory, a communication interface, a display screen and an input device connected via a system bus. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device comprises a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner may be achieved through WIFI, an operator network, NFC (near field communication) or other technologies. The display screen of the computer device may be a liquid crystal display or an electronic ink display screen, and the input device of the computer device may be a touch layer covering the display screen, or a button, trackball or touchpad provided on the housing of the computer device, or an external keyboard, touchpad or mouse.

[0126] In summary, the present invention realizes continuous perception and intelligent identification of the slope deformation evolution process by constructing a dynamic update system that integrates multi-source real-time monitoring data and numerical simulation. It adopts underground collaborative monitoring means that combines ground-based interferometric radar with electromagnetic wave detection technology, breaks through the limitations of traditional point monitoring, and improves the ability to synchronously acquire surface and underground deformation characteristics. It introduces graph neural networks for dynamic zoning identification, and establishes a closed-loop feedback mechanism between simulation and monitoring, which enhances the model's adaptability and prediction accuracy to complex geological conditions. Based on the multi-dimensional early warning indicator system and the fusion decision-making model, it realizes the automatic triggering of graded early warning signals, which significantly improves the response speed, judgment accuracy and scientific nature of risk assessment of the geotechnical engineering early warning system, and provides intelligent, dynamic and systematic technical support for slope safety prevention and control.

[0127] Example 2

[0128] Reference Figure 1 and Figure 2 , which is the second embodiment of the present invention, provides a geotechnical engineering stability early warning system method that combines slope deformation monitoring and numerical simulation. In order to verify the beneficial effects of the present invention, scientific demonstration is carried out through simulation experiments.

[0129] The technical solution of the present invention has been successfully implemented in a high-slope project on a certain mountain highway. In this project, a multi-band ground-based interferometric radar array and a ground-based electromagnetic wave detection network were deployed to conduct all-weather, multi-dimensional monitoring of the slope, and obtain real-time information on surface deformation variables and underground medium parameter changes. By integrating the monitoring data with the numerical simulation results, a dynamically updated slope deformation evolution analysis system was constructed, and a graph neural network was used to dynamically partition and identify the slope deformation evolution process, identifying key areas such as the surface and underground synchronous deformation zone, the surface lagging deformation zone, the underground medium sudden change but surface stable zone, and the potential sliding path evolution zone. On this basis The system automatically analyzes a set early warning indicator system (including surface deformation rate, displacement acceleration, medium gradient change, sliding path deviation, etc.) and combines it with a multi-source data fusion decision-making model to achieve dynamic assessment and graded early warning of slope risks. After a heavy rainfall, the system successfully identified a sudden change in the underground medium in a certain area and that the sliding path evolution trend deviated from the simulation prediction, automatically triggering an orange warning. The management department then initiated an emergency response plan, effectively avoiding safety accidents caused by landslides. This fully verifies the scientific nature and practicality of the present invention's slope early warning under complex geological conditions. A comparison between the present invention and the existing technology is shown in Table 2 below:

[0130] Table 2 Comparison between the present invention and the prior art

[0131]

[0132] Table 2 reflects the significant improvement of the present invention in terms of technological advancement, system integration, and early warning intelligence, which helps reviewers or readers quickly understand the innovation and practical value of the present invention.

[0133] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A geotechnical engineering stability early warning system method combining slope deformation monitoring and numerical simulation, characterized by: include, The geotechnical engineering early warning system includes combining slope deformation monitoring and numerical simulation, wherein the combination of slope deformation monitoring and numerical simulation includes fusing multi-source real-time monitoring data of slope deformation with numerical simulation to construct a dynamically updated slope deformation evolution analysis system; Based on the slope deformation evolution analysis system and multi-source real-time monitoring data, the slope deformation evolution process is dynamically partitioned and identified to identify the slope deformation threshold and abnormal evolution characteristics of rock and soil; The identification results are used as the basis for geotechnical engineering early warning, and the automatic triggering of graded early warning signals of geotechnical engineering early warning indicators is set to complete the dynamic assessment of geotechnical slope risks and early warning output.

2. The geotechnical engineering stability early warning system method combining slope deformation monitoring and numerical simulation according to claim 1 is characterized by: Acquiring multi-source real-time monitoring data of slope deformation includes utilizing underground collaborative monitoring technology to scan the slope and invert its internal structure by deploying a multi-band ground-based interferometric radar array and electromagnetic wave detection equipment around the slope to obtain information on slope surface deformation and internal medium parameter changes; The underground collaborative monitoring technology refers to the fusion imaging technology of microwave interferometry and ground-based electromagnetic wave inversion; The internal structure inversion includes a technique for inverting surface deformation by analyzing the phase difference between radar echoes using microwave interferometry; Microwave interferometry refers to the use of microwave radar to transmit and receive electromagnetic wave signals and calculate the phase difference between radar echoes. The phase difference calculation formula is: ； in, represents the phase difference, represents the radar wavelength, Indicates the displacement of the ground surface along the radar line of sight; A ground-based electromagnetic detection network is constructed by receiving electromagnetic wave signals, emitting electromagnetic waves to the underground rock and soil, recording the amplitude attenuation caused by the time delay of the electromagnetic wave reflection signal, and combining it with internal structure inversion to reconstruct the change information of the internal medium parameters of the underground rock and soil.

3. The geotechnical engineering stability early warning system method combining slope deformation monitoring and numerical simulation according to claim 2 is characterized by: The fusion of multi-source real-time monitoring data of slope deformation and numerical simulation includes uniformly mapping the two types of monitoring data, namely, phase difference and underground rock and soil internal medium parameter change information, into a three-dimensional geological model as a basis for input parameter update to complete the fusion process; The fusion process includes dynamically adjusting the state of the 3D geological model, building a two-way interactive feedback mechanism for the 3D geological model, and establishing a process for fusing multi-source real-time monitoring data of slope deformation with numerical simulation; The dynamic adjustment of the state of the three-dimensional geological model includes calculating the phase difference relationship between radar echoes using microwave interferometry to dynamically adjust the stress state and boundary displacement in the three-dimensional geological model; The two-way interactive feedback mechanism for constructing the three-dimensional geological model includes dividing the numerical simulation into zones based on boundary displacement to complete a closed-loop two-way interactive feedback mechanism for the three-dimensional geological model; When the 3D geological model is in a closed-loop two-way interactive feedback mechanism, an error identification module is introduced to compare the errors generated by the fusion of multi-source real-time monitoring data and numerical simulation to obtain the differences between the measured data; When the deviation exceeds the set threshold At this time, a dynamically updated slope deformation evolution analysis system is constructed.

4. The geotechnical engineering stability early warning system method combining slope deformation monitoring and numerical simulation according to claim 3 is characterized by: The construction of the dynamically updated slope deformation evolution analysis system includes simulating and guiding the monitoring of phase difference and underground rock and soil internal medium parameter change information; The construction of the dynamically updated slope deformation evolution analysis system also includes performing monitoring feedback simulation on the boundary position of the numerical simulation area and the shift closed-loop two-way interactive feedback mechanism.

5. The geotechnical engineering stability early warning system method combining slope deformation monitoring and numerical simulation according to claim 4 is characterized in that: The dynamic zoning identification includes inputting multi-source real-time monitoring data into the slope deformation evolution analysis process. The multi-source real-time monitoring data includes rock surface deformation variables obtained by inverting phase difference information obtained by ground-based interferometric radar, and using a multi-physics field feature fusion algorithm to normalize the simulation-guided monitoring and monitoring feedback simulation processes to extract the time series characteristics of the rock surface deformation variables and the spatial distribution characteristics of the rock underground medium. The time series characteristics refer to the response of radar wavelengths in different time periods, and the spatial distribution characteristics of the rock and soil underground medium refer to the spatial distribution section A, section B or section C of the rock and soil underground medium corresponding to the zoning performed by the numerical simulation; Feed the results of spatial distribution characteristics into the numerical simulation process to locally model different spatial distributions; The local modeling includes: The rock surface and underground synchronous deformation zone; Hysteresis deformation zone of rock and soil surface; The rock and soil underground medium changes suddenly but the surface is stable; potential sliding path evolution zone of geotechnical areas; The identification of slope deformation thresholds and abnormal evolution characteristics of rock and soil includes introducing graph neural networks for local modeling and identification; The introduction of graph neural networks for local modeling and identification includes using microwave interferometry to calculate the phase difference relationship between radar echoes and dynamically adjust the boundaries of local modeling to ensure that the spatial distribution partition results of the rock and soil underground medium evolve synchronously with the actual deformation state of the slope; Feeding the current distribution zoning results back to the numerical simulation process realizes closed-loop spatial distribution zoning of rock and soil underground media.

6. The geotechnical engineering stability early warning system method combining slope deformation monitoring and numerical simulation according to claim 5 is characterized by: The automatic triggering of graded warning signals includes, during the local modeling process, constructing a warning indicator system based on the historical slope database and the currently identified deformation evolution characteristics. The warning indicator system includes: Surface deformation rate threshold; Displacement acceleration change rate; Sudden changes in underground medium parameter gradients; Deviation of potential sliding path evolution trend; Regional deformation pattern matching degree; The spatial overlap between the stress concentration area and the deformation area; The early warning indicator system is input into the learning fusion early warning decision model, which automatically determines the current risk level based on the current slope status and historical evolution path.

7. The geotechnical engineering stability early warning system method combining slope deformation monitoring and numerical simulation according to claim 6 is characterized by: The steps for automatically determining the current risk level are as follows: When the comprehensive warning index value of a certain area exceeds the set first-level threshold, the system automatically triggers a yellow warning signal, marks the area as a focus area, and starts the high-frequency monitoring mode and local simulation update process; When the comprehensive warning index value rises further and exceeds the secondary threshold, the system triggers an orange warning signal, marking the area as a critical deformation zone, and pushes the warning information to the slope management platform to activate the emergency response plan; When the deformation evolution trend of a certain area continues to worsen and the comprehensive warning index value exceeds the third-level threshold, the system automatically triggers a red warning signal, marking the area as a high-risk area for instability, and links with a third-party emergency command system to push landslide path prediction results and emergency avoidance recommendations; When the warning signal is triggered, the system generates a warning event log, recording the trigger time, trigger indicators, warning level, regional location and key parameters of simulation feedback information, and feeds the event back to the warning decision model to optimize model parameters and threshold settings, and complete the dynamic assessment of rock and soil slope risks and warning output.

8. A geotechnical engineering stability early warning system combining slope deformation monitoring and numerical simulation, based on the geotechnical engineering stability early warning system method combining slope deformation monitoring and numerical simulation according to any one of claims 1 to 7, characterized in that: include, A fusion module, wherein the geotechnical engineering early warning includes combining slope deformation monitoring and numerical simulation, wherein the combination of slope deformation monitoring and numerical simulation includes fusing multi-source real-time monitoring data of slope deformation with numerical simulation to construct a dynamically updated slope deformation evolution analysis system; The identification module is based on the slope deformation evolution analysis system and dynamically partitions the slope deformation evolution process based on multi-source real-time monitoring data to identify the slope deformation threshold and abnormal evolution characteristics of the rock and soil; The early warning module uses the identification results as the basis for geotechnical engineering early warning, sets the automatic triggering of graded early warning signals for geotechnical engineering early warning indicators, and completes the dynamic assessment of geotechnical slope risks and early warning output.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the geotechnical engineering stability early warning system method combining slope deformation monitoring and numerical simulation are implemented as described in any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the geotechnical engineering stability early warning system method combining slope deformation monitoring and numerical simulation as described in any one of claims 1 to 7 are implemented.

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