Foundation settlement prevention method and system

Abstract

The invention belongs to the technical field of foundation settlement prevention and control, and particularly relates to a foundation settlement prevention and control method and system. Through coarse positioning and fine positioning stage processing, preliminary data are obtained through a few sensors at key positions, updated data are obtained in a coarse positioning area in a targeted mode after a threshold value is triggered, and accurate positioning is achieved. Compared with a mode of large positioning error easily caused by sparse arrangement in the prior art, by dynamically focusing a high-risk area to maintain precision and starting dense monitoring only in an abnormal area, the energy consumption of the whole system is reduced, the service life of equipment is prolonged, and a precise positioning settlement area is obtained through settlement detection, so that the positioning accuracy is improved. And through pipeline risk assessment and early warning, compared with the prior art, the protection early warning of the underground pipeline is improved, so that the threat of foundation settlement to the underground pipeline is reduced.

Description

Technical Field

[0001] This invention belongs to the field of foundation settlement prevention and control technology, specifically relating to a foundation settlement prevention and control method and system. Background Technology

[0002] Ground settlement, a common engineering hazard in urban construction, poses a serious threat to underground pipeline systems. Natural factors (such as earthquakes, karst development, groundwater level changes, and heavy rainfall) and human factors (such as construction disturbances, groundwater over-extraction, and underground mining) alter the mechanical properties of the soil, causing localized or overall settlement and collapse. This leads to concentrated stress at pipeline connections, causing bending deformation and even rupture and leakage. The pipelines are subjected to multi-directional forces such as tension and compression, exacerbating the deformation and fracture risks of the pipe body and joints. The impact is particularly significant on brittle pipe materials or welded joints. The soil displacement caused by collapse disrupts the soil-pipe interaction balance, further amplifying pipeline stress and threatening the structural integrity of underground pipelines.

[0003] In existing technologies, although some prevention and control methods exist, most of these methods rely on setting up sensors at several locations with certain intervals to obtain settlement monitoring data. By analyzing the temporal changes of the data obtained from sensors at different locations, the location of the settlement point can be estimated. When the number of sensor locations is small, the estimated settlement location is prone to a large error compared with the actual settlement location. When the number of sensor locations is large, although the error between the estimated and actual settlement locations is reduced, the operation of more sensors also leads to higher power consumption and shorter lifespan. Furthermore, after estimating the location of the settlement point, there is a lack of protection and early warning for underground pipelines. Changes in the soil mechanical properties at the settlement location can easily threaten the structural integrity of underground pipelines. Summary of the Invention

[0004] The purpose of this invention is to provide a method and system for preventing and controlling foundation settlement, which can perform graded processing through coarse and fine positioning, activate intensive monitoring only in abnormal areas, reduce overall system energy consumption, extend equipment life, and improve protection and early warning for underground pipelines.

[0005] The specific technical solution adopted by this invention is as follows: A method for preventing foundation settlement includes: Obtain feature information of the target area and construct a BIM model of the target area; Based on the BIM model, preliminary settlement data of key locations within the target area are obtained, and settlement values ​​of key locations within a preset time period are obtained through BIM model processing. Determine whether the settlement value exceeds the preset threshold. If it does, based on the preliminary settlement data, use the BIM model to obtain a coarse location of the settlement area. Obtain the settlement update data of the coarsely located settlement area, and process it through the BIM model to obtain the finely located settlement area; Based on the precise location of the settlement area, the pipeline early warning area is determined by the BIM model, and the pipeline risk index is obtained; Determine whether the pipeline risk indicators exceed the preset risk indicators. If they do, generate pipeline early warning information.

[0006] In a preferred embodiment, obtaining the feature information of the target area and constructing a BIM model of the target area includes: The characteristic information of the target area is used to construct a multi-dimensional geological database by integrating ground-penetrating radar scanning data, geotechnical test parameters, historical settlement monitoring records, and groundwater level dynamic monitoring data. Based on a multidimensional geological database, a layer of stratum permeability coefficient distribution and a gradient map of soil compression modulus are embedded in the BIM model. By coupling the building load distribution model with the underground pipe network topology, a three-dimensional geomechanical model is generated, which includes soil pore water pressure cloud map and spatial location of potential weak interlayers.

[0007] In a preferred embodiment, the step of obtaining preliminary settlement data for key locations within the target area based on the BIM model, and processing the BIM model to obtain settlement values ​​for key locations within a preset time period, includes: Preliminary settlement data were collected in real time by a distributed fiber optic sensor array deployed at key locations, which collected data on soil micro-strain rate, tilt angle change, and vibration frequency response spectrum. By combining the time-domain reflectometry module built into the BIM model, real-time data is dynamically compared with the soil wave velocity model, and the settlement trend prediction curve and differential settlement heat map of key locations within a preset time period are output.

[0008] In a preferred embodiment, determining whether the settlement value exceeds a preset threshold, and if so, obtaining a coarse location of the settlement area based on preliminary settlement data through BIM model processing, includes: When the settlement value exceeds the preset threshold, an automatic early warning mechanism is triggered and the spatial overlay analysis function for coarsely locating the settlement area is activated. In the BIM model, high-precision grid cells are divided, the settlement gradient matrix and soil stress concentration factor of each cell are calculated, and the soil plastic strain distribution cloud map is generated by inverting the soil compression history data and the current load distribution state. By combining the results of groundwater flow direction simulation, abnormal seepage path areas are identified. The spatial topology analysis function of the BIM model is used to couple and match the stress concentration area with the distribution map of the geological weak layer, and output the boundary coordinates and depth range of the high-risk settlement area. By linking construction activity records with climate and environmental impact factors to exclude non-settlement disturbance sources, the range of coarsely located settlement areas that need to be prioritized for monitoring is marked through the model visualization interface.

[0009] In a preferred embodiment, obtaining the settlement update data of the coarsely located settlement area and processing it through a BIM model to obtain the finely located settlement area includes: Settlement update data is continuously collected by array of inclinometers and pore water pressure gauges deployed in the coarsely located settlement area to collect data on soil rebound, seepage dissipation rate and crack propagation direction. The data assimilation module of the BIM model iteratively calibrates the real-time data with the initial geomechanical model. The three-dimensional spatial morphology of the soil pore development zone was reconstructed using the finite element inverse analysis method, and the settlement core zone was accurately located by comparing the shear wave velocity anomalies of soil layers at different depths. The coordinates of the settlement area are precisely located by optimizing the boundary through the settlement probability matrix generated by fusing multi-source sensor data and machine learning algorithms, and outputting high-precision spatial coordinates of the settlement core area.

[0010] In a preferred embodiment, the output of high-precision spatial coordinates of the settlement core area includes: A multi-source data fusion strategy was adopted to import satellite synthetic aperture radar interferometry data and ground laser scanning point cloud into the BIM model; The vertical displacement vector field of the ground surface is calculated by differential interferometric phase analysis, and the micro-strain monitoring values ​​of distributed optical fiber sensors are fused to iteratively optimize the settlement boundary accuracy using a soil creep constitutive model.

[0011] In a preferred embodiment, the process of determining pipeline early warning areas based on precise location of settlement areas using a BIM model to obtain pipeline risk indicators includes: Extract the spatial intersection polygons of the settlement area and underground pipelines from the BIM model to identify the core risk section of the pipeline early warning area. Calculate the axial strain distribution of the pipeline, the misalignment at the interface, and the fatigue damage index of the pipe material. Combine the yield strength threshold and deformation tolerance limit in the pipeline material database to generate a leakage risk probability model. Based on the analysis of Young's modulus and Poisson's ratio of the pipe material in the pipeline early warning area using the BIM model, and combined with the anomaly value of soil shear wave velocity in the settlement area, the axial bending moment and circumferential stress concentration factor at the pipe joint are calculated. By simulating the attenuation curve of the friction coefficient at the pipe-soil interface, the probability of compression rebound failure of the pipe interface seal ring is predicted. The weighted combination of axial bending moment, circumferential stress concentration factor and seal failure probability is used as the core parameter of pipeline risk index.

[0012] In a preferred embodiment, determining whether the pipeline risk index exceeds a preset risk index includes: Integrate real-time monitoring data on groundwater level fluctuations with historical seepage field simulation results from the BIM model; By comparing the rate of change of the angle between the current seepage direction and the pipeline axis, the risk level of potential erosion of the soil around the pipe can be determined. Spatially correlate the latent corrosion risk level with the pipe section weld defect database, and automatically increase the risk index weight coefficient for pipe sections with incomplete fusion welds.

[0013] In a preferred embodiment, generating pipeline early warning information includes: Synchronously match the pipeline deformation compensation scheme library in the BIM model, and filter the installation angle parameters of the hydraulic rotary compensator and the axial expansion and contraction configuration of the bellows expansion joint; By combining construction machinery path planning algorithms to avoid high-risk pipeline areas, a set of coordinates for compensator deployment and machinery avoidance vector commands are generated.

[0014] The present invention also provides a foundation settlement prevention system, using the above-described foundation settlement prevention method, comprising: Information acquisition module, which is used to acquire feature information of the target area and construct a BIM model of the target area; The preliminary processing module is used to obtain preliminary settlement data of key locations within the target area based on the BIM model, and to obtain settlement values ​​of key locations within a preset time period through BIM model processing. The settlement judgment module is used to determine whether the settlement value exceeds a preset threshold. If it does, the settlement area is coarsely located based on the preliminary settlement data and processed by the BIM model. The secondary processing module is used to acquire the settlement update data of the coarsely located settlement area and obtain the finely located settlement area through BIM model processing. The pipeline processing module is used to determine the pipeline early warning area based on the precise location of the settlement area and the BIM model, and obtain the pipeline risk index. The pipeline early warning module is used to determine whether the pipeline risk indicators exceed the preset risk indicators. If they do, pipeline early warning information is generated.

[0015] The technical effects achieved by this invention are as follows: This invention employs a tiered approach of coarse and fine positioning. It first acquires preliminary data using a small number of sensors at key locations. Once a threshold is triggered, updated data is selectively acquired in the coarse positioning area to achieve precise positioning. Compared to existing technologies that rely on densely deployed sensors to ensure accuracy, which often leads to high power consumption and short lifespan, this invention reduces the number of sensors deployed at key points. Furthermore, compared to existing technologies that rely on sparse deployment, which often results in large positioning errors, this invention maintains accuracy by dynamically focusing on high-risk areas and only activating intensive monitoring in abnormal areas. This reduces overall system energy consumption and extends equipment lifespan. Additionally, it uses settlement detection to pinpoint settlement areas and then employs pipeline risk assessment and early warning systems. Compared to existing technologies, this improves the protection and early warning capabilities for underground pipelines, reducing the threat posed by foundation settlement to underground pipelines. Attached Figure Description

[0016] Figure 1 This is a schematic diagram of the method flow of the present invention; Figure 2 This is a schematic diagram of the system modules of the present invention. Detailed Implementation

[0017] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0018] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein, and those skilled in the art can make similar extensions without departing from the spirit of the invention. Therefore, the invention is not limited to the specific embodiments disclosed below.

[0019] Secondly, the term "an embodiment" or "embodiment" as used 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 a preferred embodiment" appearing in different places throughout this specification does not necessarily refer to the same embodiment, nor is it a single or selective embodiment that mutually excludes other embodiments.

[0020] Please see Figure 1 As shown, the present invention provides a method for preventing foundation settlement, comprising: Obtain feature information of the target area and construct a BIM model of the target area; Based on the BIM model, preliminary settlement data of key locations within the target area are obtained, and settlement values ​​of key locations within a preset time period are obtained through BIM model processing. Determine whether the settlement value exceeds the preset threshold. If it does, based on the preliminary settlement data, use the BIM model to obtain a coarse location of the settlement area. Obtain the settlement update data of the coarsely located settlement area, and process it through the BIM model to obtain the finely located settlement area; Based on the precise location of the settlement area, the pipeline early warning area is determined by the BIM model, and the pipeline risk index is obtained; Determine whether the pipeline risk indicators exceed the preset risk indicators. If they do, generate pipeline early warning information.

[0021] Secondly, acquire the feature information of the target area and construct a BIM model of the target area, including: The characteristic information of the target area is used to construct a multi-dimensional geological database by integrating ground-penetrating radar scanning data, geotechnical test parameters, historical settlement monitoring records, and groundwater level dynamic monitoring data. Based on a multidimensional geological database, a layer of stratum permeability coefficient distribution and a gradient map of soil compression modulus are embedded in the BIM model. By coupling the building load distribution model with the underground pipe network topology, a three-dimensional geomechanical model is generated, which includes soil pore water pressure cloud map and spatial location of potential weak interlayers.

[0022] Secondly, based on the BIM model, preliminary settlement data for key locations within the target area are obtained. The BIM model is then processed to obtain settlement values ​​for these key locations within a preset time period, including: Preliminary settlement data were collected in real time by a distributed fiber optic sensor array deployed at key locations, which collected data on soil micro-strain rate, tilt angle change, and vibration frequency response spectrum. By combining the time-domain reflectometry module built into the BIM model, real-time data is dynamically compared with the soil wave velocity model, and the settlement trend prediction curve and differential settlement heat map of key locations within a preset time period are output.

[0023] Secondly, it is determined whether the settlement value exceeds a preset threshold. If it does, based on the preliminary settlement data, the settlement area is coarsely located through BIM model processing, including: When the settlement value exceeds the preset threshold, an automatic early warning mechanism is triggered and the spatial overlay analysis function for coarsely locating the settlement area is activated. In the BIM model, high-precision grid cells are divided, the settlement gradient matrix and soil stress concentration factor of each cell are calculated, and the soil plastic strain distribution cloud map is generated by inverting the soil compression history data and the current load distribution state. By combining the results of groundwater flow direction simulation, abnormal seepage path areas are identified. The spatial topology analysis function of the BIM model is used to couple and match the stress concentration area with the distribution map of the geological weak layer, and output the boundary coordinates and depth range of the high-risk settlement area. By linking construction activity records with climate and environmental impact factors to exclude non-settlement disturbance sources, the range of coarsely located settlement areas that need to be prioritized for monitoring is marked through the model visualization interface.

[0024] Secondly, acquire the settlement update data of the coarsely located settlement area, and process it through the BIM model to obtain the finely located settlement area, including: Settlement update data is continuously collected by array of inclinometers and pore water pressure gauges deployed in the coarsely located settlement area to collect data on soil rebound, seepage dissipation rate and crack propagation direction. The data assimilation module of the BIM model iteratively calibrates the real-time data with the initial geomechanical model. The three-dimensional spatial morphology of the soil pore development zone was reconstructed using the finite element inverse analysis method, and the settlement core zone was accurately located by comparing the shear wave velocity anomalies of soil layers at different depths. The coordinates of the settlement area are precisely located by optimizing the boundary through the settlement probability matrix generated by fusing multi-source sensor data and machine learning algorithms, and outputting high-precision spatial coordinates of the settlement core area.

[0025] Secondly, it outputs high-precision spatial coordinates of the settlement core area, including: A multi-source data fusion strategy was adopted to import satellite synthetic aperture radar interferometry data and ground laser scanning point cloud into the BIM model; The vertical displacement vector field of the ground surface is calculated by differential interferometric phase analysis, and the micro-strain monitoring values ​​of distributed optical fiber sensors are fused to iteratively optimize the settlement boundary accuracy using a soil creep constitutive model.

[0026] Secondly, based on the precise location of the settlement area, the pipeline early warning area is determined through the BIM model, and pipeline risk indicators are obtained, including: Extract the spatial intersection polygons of the settlement area and underground pipelines from the BIM model to identify the core risk section of the pipeline early warning area. Calculate the axial strain distribution of the pipeline, the misalignment at the interface, and the fatigue damage index of the pipe material. Combine the yield strength threshold and deformation tolerance limit in the pipeline material database to generate a leakage risk probability model. Based on the analysis of Young's modulus and Poisson's ratio of the pipe material in the pipeline early warning area using the BIM model, and combined with the anomaly value of soil shear wave velocity in the settlement area, the axial bending moment and circumferential stress concentration factor at the pipe joint are calculated. By simulating the attenuation curve of the friction coefficient at the pipe-soil interface, the probability of compression rebound failure of the pipe interface seal ring is predicted. The weighted combination of axial bending moment, circumferential stress concentration factor and seal failure probability is used as the core parameter of pipeline risk index.

[0027] Secondly, determine whether the pipeline risk indicators exceed the preset risk indicators, including: Integrate real-time monitoring data on groundwater level fluctuations with historical seepage field simulation results from the BIM model; By comparing the rate of change of the angle between the current seepage direction and the pipeline axis, the risk level of potential erosion of the soil around the pipe can be determined. Spatially correlate the latent corrosion risk level with the pipe section weld defect database, and automatically increase the risk index weight coefficient for pipe sections with incomplete fusion welds.

[0028] Secondly, generate pipeline early warning information, including: Synchronously match the pipeline deformation compensation scheme library in the BIM model, and filter the installation angle parameters of the hydraulic rotary compensator and the axial expansion and contraction configuration of the bellows expansion joint; By combining construction machinery path planning algorithms to avoid high-risk pipeline areas, a set of coordinates for compensator deployment and machinery avoidance vector commands are generated.

[0029] Please see Figure 2 A foundation settlement prevention system, using the aforementioned foundation settlement prevention method, includes: Information acquisition module, which is used to acquire feature information of the target area and construct a BIM model of the target area; The preliminary processing module is used to obtain preliminary settlement data of key locations within the target area based on the BIM model, and to obtain settlement values ​​of key locations within a preset time period through BIM model processing. The settlement judgment module is used to determine whether the settlement value exceeds a preset threshold. If it does, the settlement area is coarsely located based on the preliminary settlement data and processed by the BIM model. The secondary processing module is used to acquire the settlement update data of the coarsely located settlement area and obtain the finely located settlement area through BIM model processing. The pipeline processing module is used to determine the pipeline early warning area based on the precise location of the settlement area and the BIM model, and obtain the pipeline risk index. The pipeline early warning module is used to determine whether the pipeline risk indicators exceed the preset risk indicators. If they do, pipeline early warning information is generated.

[0030] The execution of the foundation settlement prevention system in this embodiment is consistent with the process of the foundation settlement prevention method described above, and will not be repeated here.

[0031] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, apparatus, article, or method that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, apparatus, article, or method. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, apparatus, article, or method that includes that element.

[0032] The above description is merely a preferred embodiment of the present invention. It should be noted that those skilled in the art can make various improvements and modifications without departing from the principles of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention. Structures, devices, and operating methods not specifically described or explained in this invention are implemented according to conventional methods in the art unless otherwise specified or limited.

Claims

1. A method for preventing foundation settlement, characterized in that: include: Obtain feature information of the target area and construct a BIM model of the target area; Based on the BIM model, preliminary settlement data of key locations within the target area are obtained, and settlement values ​​of key locations within a preset time period are obtained through BIM model processing. Determine whether the settlement value exceeds the preset threshold. If it does, based on the preliminary settlement data, use the BIM model to obtain a coarse location of the settlement area. Obtain the settlement update data of the coarsely located settlement area, and process it through the BIM model to obtain the finely located settlement area; Based on the precise location of the settlement area, the pipeline early warning area is determined by the BIM model, and the pipeline risk index is obtained; Determine whether the pipeline risk indicators exceed the preset risk indicators. If they do, generate pipeline early warning information.

2. The method for preventing foundation settlement according to claim 1, characterized in that: The step of acquiring feature information of the target area and constructing a BIM model of the target area includes: The characteristic information of the target area is used to construct a multi-dimensional geological database by integrating ground-penetrating radar scanning data, geotechnical test parameters, historical settlement monitoring records, and groundwater level dynamic monitoring data. Based on a multidimensional geological database, a layer of stratum permeability coefficient distribution and a gradient map of soil compression modulus are embedded in the BIM model. By coupling the building load distribution model with the underground pipe network topology, a three-dimensional geomechanical model is generated, which includes soil pore water pressure cloud map and spatial location of potential weak interlayers.

3. The method for preventing foundation settlement according to claim 1, characterized in that: The process of obtaining preliminary settlement data for key locations within the target area based on the BIM model, and processing the BIM model to obtain settlement values ​​for key locations within a preset time period includes: Preliminary settlement data were collected in real time by a distributed fiber optic sensor array deployed at key locations, which collected data on soil micro-strain rate, tilt angle change, and vibration frequency response spectrum. By combining the time-domain reflectometry module built into the BIM model, real-time data is dynamically compared with the soil wave velocity model, and the settlement trend prediction curve and differential settlement heat map of key locations within a preset time period are output.

4. The method for preventing foundation settlement according to claim 1, characterized in that: The determination of whether the settlement value exceeds a preset threshold, and if so, based on preliminary settlement data, using BIM model processing to obtain a coarse location of the settlement area, includes: When the settlement value exceeds the preset threshold, an automatic early warning mechanism is triggered and the spatial overlay analysis function for coarsely locating the settlement area is activated. In the BIM model, high-precision grid cells are divided, the settlement gradient matrix and soil stress concentration factor of each cell are calculated, and the soil plastic strain distribution cloud map is generated by inverting the soil compression history data and the current load distribution state. By combining the results of groundwater flow direction simulation, abnormal seepage path areas are identified. The spatial topology analysis function of the BIM model is used to couple and match the stress concentration area with the distribution map of the geological weak layer, and output the boundary coordinates and depth range of the high-risk settlement area. By linking construction activity records with climate and environmental impact factors to exclude non-settlement disturbance sources, the range of coarsely located settlement areas that need to be prioritized for monitoring is marked through the model visualization interface.

5. The method for preventing foundation settlement according to claim 1, characterized in that: The process of obtaining settlement update data for the coarsely located settlement area and processing it through a BIM model to obtain the finely located settlement area includes: Settlement update data is continuously collected by array of inclinometers and pore water pressure gauges deployed in the coarsely located settlement area to collect data on soil rebound, seepage dissipation rate and crack propagation direction. The data assimilation module of the BIM model iteratively calibrates the real-time data with the initial geomechanical model. The three-dimensional spatial morphology of the soil pore development zone was reconstructed using the finite element inverse analysis method, and the settlement core zone was accurately located by comparing the shear wave velocity anomalies of soil layers at different depths. The coordinates of the settlement area are precisely located by optimizing the boundary through the settlement probability matrix generated by fusing multi-source sensor data and machine learning algorithms, and outputting high-precision spatial coordinates of the settlement core area.

6. The method for preventing foundation settlement according to claim 5, characterized in that: The output of high-precision spatial coordinates of the settlement core area includes: A multi-source data fusion strategy was adopted to import satellite synthetic aperture radar interferometry data and ground laser scanning point cloud into the BIM model; The vertical displacement vector field of the ground surface is calculated by differential interferometric phase analysis, and the micro-strain monitoring values ​​of distributed optical fiber sensors are fused to iteratively optimize the settlement boundary accuracy using a soil creep constitutive model.

7. The method for preventing foundation settlement according to claim 1, characterized in that: The pipeline early warning area is determined by using a BIM model based on the precise location of the settlement area, and pipeline risk indicators are obtained, including: Extract the spatial intersection polygons of the settlement area and underground pipelines from the BIM model to identify the core risk section of the pipeline early warning area. Calculate the axial strain distribution of the pipeline, the misalignment at the interface, and the fatigue damage index of the pipe material. Combine the yield strength threshold and deformation tolerance limit in the pipeline material database to generate a leakage risk probability model. Based on the analysis of Young's modulus and Poisson's ratio of the pipe material in the pipeline early warning area using the BIM model, and combined with the anomaly value of soil shear wave velocity in the settlement area, the axial bending moment and circumferential stress concentration factor at the pipe joint are calculated. By simulating the attenuation curve of the friction coefficient at the pipe-soil interface, the probability of compression rebound failure of the pipe interface seal ring is predicted. The weighted combination of axial bending moment, circumferential stress concentration factor and seal failure probability is used as the core parameter of pipeline risk index.

8. The method for preventing foundation settlement according to claim 1, characterized in that: The determination of whether the pipeline risk index exceeds the preset risk index includes: Integrate real-time monitoring data on groundwater level fluctuations with historical seepage field simulation results from the BIM model; By comparing the rate of change of the angle between the current seepage direction and the pipeline axis, the risk level of potential erosion of the soil around the pipe can be determined. Spatially correlate the latent corrosion risk level with the pipe section weld defect database, and automatically increase the risk index weight coefficient for pipe sections with incomplete fusion welds.

9. A method for preventing foundation settlement according to claim 1, characterized in that: The generation of pipeline early warning information includes: Synchronously match the pipeline deformation compensation scheme library in the BIM model, and filter the installation angle parameters of the hydraulic rotary compensator and the axial expansion and contraction configuration of the bellows expansion joint; By combining construction machinery path planning algorithms to avoid high-risk pipeline areas, a set of coordinates for compensator deployment and machinery avoidance vector commands are generated.

10. A foundation settlement prevention system according to claim 1, characterized in that, The system is used to implement the method as described in any one of claims 1 to 9, the system comprising: Information acquisition module, which is used to acquire feature information of the target area and construct a BIM model of the target area; The preliminary processing module is used to obtain preliminary settlement data of key locations within the target area based on the BIM model, and to obtain settlement values ​​of key locations within a preset time period through BIM model processing. The settlement judgment module is used to determine whether the settlement value exceeds a preset threshold. If it does, the settlement area is coarsely located based on the preliminary settlement data and processed by the BIM model. The secondary processing module is used to acquire the settlement update data of the coarsely located settlement area and obtain the finely located settlement area through BIM model processing. The pipeline processing module is used to determine the pipeline early warning area based on the precise location of the settlement area and the BIM model, and obtain the pipeline risk index. The pipeline early warning module is used to determine whether the pipeline risk indicators exceed the preset risk indicators. If they do, pipeline early warning information is generated.

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