Deep and large foundation pit monitoring method and system, program product and storage medium

Abstract

The invention provides a deep and large foundation pit monitoring method and system, a program product and a storage medium, and relates to the technical field of foundation pit detection. The GPS positioning device collects foundation pit slope crest displacement data, the monitoring sensor network collects deep horizontal displacement data, the two data types complement each other, comprehensive information of surface and internal deformation of the foundation pit is provided, and the generated deep horizontal displacement curve chart visually displays the displacement conditions of the supporting structure at all depths. A potential weak area can be identified, a foundation pit excavation response data acquisition device is arranged at the maximum stress part, response data of a key position is obtained, and the quantitative index of overall deformation is provided by measuring and monitoring the position change of a central point of a sensor network and calculating the deformation amount of the foundation pit. According to the multi-dimensional and multi-type data acquisition and integration method, the description comprehensiveness of the foundation pit environment is improved, potential risks can be judged more accurately, and limitation caused by a single data type is overcome.

Description

Technical Field

[0001] The present application relates to the technical field of foundation pit detection, and in particular to a method, system, program product and storage medium for monitoring a deep and large foundation pit. Background Art

[0002] With the acceleration of urbanization and the development and utilization of underground space, large-scale deep foundation pit projects are increasing. These projects often have the characteristics of large excavation depth, complex surrounding environment, and changeable geological conditions, which pose unprecedented challenges to monitoring technology.

[0003] At present, some foundation pit monitoring systems install strain gauges and other equipment on the surface of the support structure to measure the stress state of the support structure and determine whether it exceeds the warning value.

[0004] However, the data types obtained by relevant monitoring methods are limited, lacking a multi-dimensional description of the foundation pit environment. The singleness of this data type may lead to an incomplete judgment of potential risks. Summary of the invention

[0005] The present application provides a deep and large foundation pit monitoring method, system, program product and storage medium, which are used to improve the comprehensiveness of the description of the foundation pit environment and help to more accurately judge potential risks.

[0006] In the first aspect, the present application provides a method for monitoring a deep and large foundation pit, comprising: arranging GPS positioning devices around the foundation pit to collect displacement data of the top of the foundation pit slope; setting up a number of monitoring sensor networks on the foundation pit support structure to collect deep horizontal displacement data, the monitoring sensor network consisting of a number of monitoring sensors; generating a deep horizontal displacement curve graph based on the deep horizontal displacement data; wherein the deep horizontal displacement data of each monitoring sensor in the vertical direction is supplemented in the deep horizontal displacement curve graph; determining the maximum stress-bearing part of the foundation pit support structure, and setting up a foundation pit excavation response data acquisition device at the maximum stress-bearing part; using the foundation pit excavation response data acquisition device to collect response data; controlling each monitoring sensor network to transmit radio waves to measure the center point position of each monitoring sensor network; calculating the foundation pit deformation according to the change of the center point position; sending the foundation pit slope top displacement data, deep horizontal displacement data, deep horizontal displacement curve graph, foundation pit deformation, and response data to a cloud server.

[0007] By adopting the above technical solution, the GPS positioning device collects the displacement data of the top of the foundation pit slope, and the monitoring sensor network collects the deep horizontal displacement data. These two data types complement each other and provide comprehensive information on the surface and internal deformation of the foundation pit. The generated deep horizontal displacement curve diagram intuitively shows the displacement of the support structure at each depth, which is helpful to identify potential weak areas. The foundation pit excavation response data acquisition device is set at the maximum stress point to obtain the response data of the key position, which further enriches the type of monitoring data. By measuring the position change of the center point of the monitoring sensor network, the deformation of the foundation pit is calculated, and a quantitative indicator of the overall deformation is provided. Various types of data (displacement data, curve diagram, deformation, response data) are sent to the cloud server, which lays the foundation for subsequent comprehensive analysis and risk assessment. This multi-dimensional and multi-type data collection and integration method improves the comprehensiveness of the description of the foundation pit environment, helps to judge potential risks more accurately, and overcomes the limitations brought by a single data type.

[0008] In combination with some embodiments of the first aspect, in some embodiments, after the step of sending the foundation pit slope top displacement data, deep horizontal displacement data, deep horizontal displacement curve graph, foundation pit deformation, and response data to the cloud server, the method also includes: controlling each monitoring sensor network to transmit radio waves to measure the contour of the foundation pit; sending the contour to the cloud server; the cloud server establishes an initial three-dimensional geometric model of the foundation pit according to the contour; the cloud server maps the foundation pit slope top displacement data to the slope top edge of the initial three-dimensional geometric model; the cloud server generates a displacement vector field on the surface of the initial three-dimensional geometric model according to the deep horizontal displacement data and the deep horizontal displacement curve graph; the cloud server uses the foundation pit deformation to adjust the shape and position of the initial three-dimensional geometric model; the cloud server uses a three-dimensional interpolation algorithm to generate a continuous deformation field based on discrete foundation pit deformation; the cloud server deforms the initial three-dimensional geometric model according to the continuous deformation field to generate a deformed three-dimensional model; the cloud server adds a time dimension to the deformed three-dimensional model to obtain a BIM model of the foundation pit.

[0009] By adopting the above technical solution, by measuring the foundation pit contour and establishing an initial three-dimensional geometric model, a basic framework is provided for subsequent analysis. The displacement data of the foundation pit slope top is mapped to the edge of the model, which intuitively displays the surface deformation. A displacement vector field is generated on the model surface, which clearly presents the deformation trend and direction of the support structure. The shape and position of the model are adjusted using the foundation pit deformation to reflect the overall deformation status. A three-dimensional interpolation algorithm is used to generate a continuous deformation field, which improves the accuracy and continuity of the deformation description. The model is deformed and a time dimension is added to obtain a dynamic BIM model, which realizes three-dimensional visualization of the foundation pit status. By adding a time dimension, the monitoring results are made more intuitive and dynamic.

[0010] In combination with some embodiments of the first aspect, in some embodiments, after the cloud server adds a time dimension to the deformed three-dimensional model to obtain a BIM model of the foundation pit, the method also includes: the cloud server obtains the foundation pit change value according to the BIM model; the cloud server compares the foundation pit change value with the multi-level safety threshold; the multi-level safety threshold includes warning value, alarm value and danger value; the cloud server determines the safety status level of the foundation pit based on the comparison result; the cloud server generates a safety report based on the above-mentioned safety status level, the safety report includes an overview of the current foundation pit safety status and response suggestions for different safety status levels; the cloud server sends the safety report to relevant personnel according to the urgency of the safety status level.

[0011] By adopting the above technical solution, the cloud server obtains the foundation pit change value based on the BIM model, provides a quantitative evaluation basis, compares the change value with multi-level safety thresholds (warning value, alarm value and danger value), establishes a graded evaluation standard, and determines the safety status level of the foundation pit based on the comparison results. It realizes automated safety status judgment and generates a safety report containing an overview of the current status and response recommendations, providing a direct basis for decision-making.

[0012] In combination with some embodiments of the first aspect, in some embodiments, the step of generating a deep horizontal displacement curve graph based on deep horizontal displacement data specifically includes: sorting the deep horizontal displacement data according to the corresponding depth information; using a cubic spline interpolation algorithm to interpolate the sorted deep horizontal displacement data to generate a continuous displacement curve; creating a two-dimensional coordinate system, in which the horizontal axis represents the horizontal displacement and the vertical axis represents the depth; drawing a continuous displacement curve in the two-dimensional coordinate system to form a preliminary deep horizontal displacement curve graph; adding time information as the third dimension to the deep horizontal displacement curve graph to generate a three-dimensional surface graph; marking the time axis in the three-dimensional surface graph; generating a deep horizontal displacement curve graph, the deep horizontal displacement curve graph includes a two-dimensional profile graph and a three-dimensional surface graph.

[0013] By adopting the above technical solution, the deep horizontal displacement data are sorted by depth, providing an orderly data basis for subsequent analysis. The cubic spline interpolation algorithm is used for interpolation processing to generate a continuous displacement curve, which improves the accuracy and continuity of the data. The displacement curve is drawn in a two-dimensional coordinate system to intuitively display the horizontal displacement at different depths. The time dimension is added to generate a three-dimensional surface graph, which makes the change of displacement with time and depth more clearly visible. A comprehensive deep horizontal displacement curve graph containing a two-dimensional profile graph and a three-dimensional surface graph is generated, providing multi-angle data display.

[0014] In combination with some embodiments of the first aspect, in some embodiments, after the step of drawing a continuous displacement curve in a two-dimensional coordinate system to form a preliminary deep horizontal displacement curve diagram, the method also includes: using color coding to represent different degrees of deep horizontal displacement; marking the maximum displacement points and deformation rate mutation points; and adding contour lines.

[0015] By adopting the above technical solutions, the use of color coding and contour lines makes the displacement distribution clear at a glance, and the marking of the maximum displacement point and the deformation rate mutation point directly points out the areas that need to be focused on. This enhanced visualization method not only makes it easier for engineers to quickly understand the deformation status of the foundation pit, but also helps to identify potential risk areas, providing an intuitive basis for taking timely protective measures.

[0016] In combination with some embodiments of the first aspect, in some embodiments, the step of determining the maximum stress-bearing part of the foundation pit support structure specifically includes: setting multiple measuring points on the foundation pit support structure; collecting stress data of the multiple measuring points; based on the stress data, generating a stress curve of the stress distribution of the foundation pit support structure; and determining the maximum stress-bearing part of the foundation pit support structure according to the stress curve.

[0017] By adopting the above technical solution, multiple measuring points are set on the foundation pit support structure to ensure the comprehensiveness of data collection. Stress data of multiple measuring points are collected to obtain the actual stress condition of the support structure. A stress distribution curve is generated based on the stress data to intuitively display the stress state of the entire support structure. The maximum stress point is determined according to the stress curve, thus achieving precise positioning of key areas.

[0018] In combination with some embodiments of the first aspect, in some embodiments, the step of determining the maximum stress-bearing part of the foundation pit support structure according to the stress curve specifically includes: identifying the peak point on the stress curve; judging whether the peak point is located at the boundary of the stress curve; if not, determining the position corresponding to the peak point as the maximum stress-bearing part of the foundation pit support structure; if located, determining the boundary and its adjacent areas as the key stress-bearing parts of the foundation pit support structure, and adding measurement points at the boundary and its adjacent areas; collecting stress data of the additional measurement points; generating a local stress distribution curve based on the stress data of the additional measurement points; determining the maximum stress position of the foundation pit support structure at the key stress-bearing part according to the local stress distribution curve, and determining it as the maximum stress-bearing part of the foundation pit support structure.

[0019] By adopting the above technical solution, the peak point on the stress curve is identified, the possible maximum stress position is preliminarily determined, and it is judged whether the peak point is located at the boundary, thereby avoiding misjudgment caused by boundary effects. Special attention is paid to the boundary and adjacent areas, and additional measurement points are added to ensure the data accuracy of the boundary area. A local stress distribution curve is generated, providing a more detailed stress analysis of the boundary area, and the final maximum stress position is determined based on the local analysis, thereby improving the accuracy of positioning.

[0020] In the second aspect, the present application provides a deep and large foundation pit monitoring system, which includes: one or more processors and a memory; the memory is coupled to the one or more processors, the memory is used to store computer program code, the computer program code includes computer instructions, and the one or more processors call the computer instructions to enable the deep and large foundation pit monitoring system to execute the method described in the first aspect and any possible implementation method of the first aspect.

[0021] In a third aspect, the present application provides a computer program product comprising instructions, which, when executed on a deep and large foundation pit monitoring system, enables the deep and large foundation pit monitoring system to execute the method described in the first aspect and any possible implementation of the first aspect.

[0022] In a fourth aspect, the present application provides a computer-readable storage medium comprising instructions, which, when executed on a deep and large foundation pit monitoring system, enables the deep and large foundation pit monitoring system to execute the method described in the first aspect and any possible implementation of the first aspect.

[0023] One or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages: 1. The GPS positioning device collects displacement data on the top of the foundation pit slope, and the monitoring sensor network collects deep horizontal displacement data. These two data types complement each other and provide comprehensive information on the surface and internal deformation of the foundation pit. The generated deep horizontal displacement curve diagram intuitively shows the displacement of the support structure at each depth, which helps to identify potential weak areas. The foundation pit excavation response data acquisition device is set at the maximum stress point to obtain response data at key positions, further enriching the types of monitoring data. By measuring the position change of the center point of the monitoring sensor network, the foundation pit deformation is calculated, and a quantitative indicator of the overall deformation is provided. Various types of data (displacement data, curves, deformation, response data) are sent to the cloud server, laying the foundation for subsequent comprehensive analysis and risk assessment. This multi-dimensional and multi-type data collection and integration method improves the comprehensiveness of the description of the foundation pit environment, helps to more accurately judge potential risks, and overcomes the limitations of a single data type.

[0024] 2. By measuring the pit contour and establishing an initial three-dimensional geometric model, a basic framework is provided for subsequent analysis. The displacement data of the top of the pit slope is mapped to the edge of the model, which intuitively displays the surface deformation. A displacement vector field is generated on the model surface, which clearly presents the deformation trend and direction of the support structure. The shape and position of the model are adjusted using the pit deformation to reflect the overall deformation status. A three-dimensional interpolation algorithm is used to generate a continuous deformation field, which improves the accuracy and continuity of the deformation description. The model is deformed and a time dimension is added to obtain a dynamic BIM model, which realizes three-dimensional visualization of the pit status. By adding a time dimension, the monitoring results are made more intuitive and dynamic.

[0025] 3. The cloud server obtains the change value of the foundation pit based on the BIM model, provides a quantitative evaluation basis, compares the change value with the multi-level safety threshold (warning value, alarm value and danger value), establishes a graded evaluation standard, and determines the safety status level of the foundation pit based on the comparison results. It realizes automated safety status judgment and generates a safety report containing an overview of the current status and response recommendations, providing a direct basis for decision-making. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 It is a flow chart of a deep and large foundation pit monitoring method in an embodiment of the present application; Figure 2 This is another schematic flow chart of the deep and large foundation pit monitoring method in the embodiment of the present application; Figure 3 It is a schematic diagram of an exemplary hardware structure of a deep and large foundation pit monitoring system in an embodiment of the present application. DETAILED DESCRIPTION

[0027] The terms used in the following embodiments of the present application are only for the purpose of describing specific embodiments, and are not intended to be used as limitations to the present application. As used in the specification and appended claims of the present application, the singular expressions "one", "a kind of", "said", "above", "the" and "this" are intended to also include plural expressions, unless there is a clear indication to the contrary in the context. It should also be understood that the term "and / or" used in the present application refers to and includes any or all possible combinations of one or more listed items.

[0028] In the following, the terms "first" and "second" are used for descriptive purposes only and are not to be understood as suggesting or implying relative importance or implicitly indicating the number of the indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the features, and in the description of the embodiments of the present application, unless otherwise specified, "plurality" means two or more.

[0029] Figure 1It is a flow chart of a deep and large foundation pit monitoring method in an embodiment of the present application; S101, arranging GPS positioning devices around the foundation pit to collect displacement data of the foundation pit slope top; A foundation pit refers to a large hole excavated on the surface for the construction of the underground part of a building; the slope top refers to the top area at the edge of the foundation pit.

[0030] Before the excavation of the foundation pit begins, monitoring equipment needs to be deployed to ensure construction safety. In some embodiments, construction workers install GPS positioning devices at key locations around the foundation pit, especially in the top area of ​​the foundation pit slope. These GPS positioning devices are configured to continuously monitor the coordinate changes of their locations, thereby obtaining displacement data of the top of the foundation pit slope. These data reflect the deformation of the edge area of ​​the foundation pit and are important indicators for evaluating the stability of the foundation pit.

[0031] S102, setting up a plurality of monitoring sensor networks on the foundation pit support structure to collect deep horizontal displacement data, the monitoring sensor network consisting of a plurality of monitoring sensors; The foundation pit support structure refers to the engineering structure used to maintain the stability of the foundation pit, such as a retaining wall or an underground continuous wall; the monitoring sensor network refers to an interconnected system consisting of multiple sensors.

[0032] After the construction of the foundation pit support structure is completed, its stability needs to be continuously monitored. In some embodiments, engineers install multiple monitoring sensor networks at different depths and locations of the foundation pit support structure. Each network consists of multiple sensors that can measure horizontal displacement. Through these sensor networks, the horizontal displacement data of the support structure at different depths can be obtained, thereby comprehensively evaluating the deformation and stability of the support structure.

[0033] In some specific embodiments, first determine the key monitoring points on the support structure; then install inclinometers or displacement meters at these points; finally, connect these sensors into a network through wired or wireless means to centrally collect data, which is not limited here.

[0034] S103, generating a deep horizontal displacement curve graph according to the deep horizontal displacement data; wherein the deep horizontal displacement curve graph is supplemented with the deep horizontal displacement data of each monitoring sensor in the vertical direction; The deep horizontal displacement curve refers to a graph that shows the changes in horizontal displacement at different depths underground.

[0035] After acquiring the deep horizontal displacement data, it is necessary to visualize this data for easy analysis. In some embodiments, the system generates a graph based on the collected deep horizontal displacement data. This graph usually takes depth as the vertical axis and horizontal displacement as the horizontal axis. In order to provide more comprehensive information, the system also marks the vertical position of each monitoring sensor and its corresponding horizontal displacement data in the graph. This representation method can intuitively show the deformation of the support structure at different depths, which helps to identify potential weak areas.

[0036] In some embodiments, step S103 specifically includes: S1031, sorting the deep horizontal displacement data according to the corresponding depth information; Depth information refers to the position information of the measurement point in the vertical direction; S1032, using a cubic spline interpolation algorithm to interpolate the sorted deep horizontal displacement data to generate a continuous displacement curve; In some specific embodiments, the sorted deep horizontal displacement data are divided into two groups: depth values ​​(x) and corresponding horizontal displacement values ​​(y); For n data points, each point is represented by a depth value x i and the corresponding horizontal displacement value y i Composition, where i ranges from 1 to n, for these n data points, create n-1 cubic polynomial equations. Each equation represents the interpolation function between two adjacent data points; Each equation is of the form: S i (x) = a i +b i (xx i )+c i (xx i ) 2 +d i (xx i ) 3 ; In the formula, a i 、b i 、c i d i is the unknown coefficient, S i (x) is a cubic spline function.

[0037] According to the following constraint S i (x i )=y i , S i (x i+1 )=y i+1 , S ′ i (x i+1 )=S ′i+1 (x i+1 ), S i ″ (x i+1 )=S i ″ +1 (x i+1 ), establish a linear system of equations. Solving this system of equations will yield all the coefficients a i 、b i 、c i d i .

[0038] Once all coefficients are obtained, for any given value of x, we can determine the interval i in which it lies, and then use the corresponding S i (x) The function calculates the interpolation result.

[0039] S1033, creating a two-dimensional coordinate system, wherein the horizontal axis represents horizontal displacement and the vertical axis represents depth; S1034, drawing a continuous displacement curve in a two-dimensional coordinate system to form a preliminary deep horizontal displacement curve diagram; In some specific embodiments, the interpolated continuous displacement data is read; the data points are mapped to corresponding positions in the coordinate system; adjacent data points are connected using line segments to form a continuous curve; the color, line type and thickness of the curve are set; a legend is added to illustrate the meaning of the curve; and the graphic layout is adjusted to ensure that the curve is clearly visible.

[0040] In some embodiments, after step S1034, step S1038 or step S1035 may be directly executed.

[0041] S1038, use color coding to indicate different degrees of deep horizontal displacement; In some embodiments, the use of color coding can enhance the information expression ability of the deep horizontal displacement curve graph, allowing the observer to quickly identify the degree of displacement at different depths and locations. By reasonably selecting a color scheme, the distribution law and change trend of the displacement can be intuitively displayed, which helps engineers analyze data and make judgments more efficiently.

[0042] In some specific embodiments, the range and distribution of displacement data are determined; a suitable color scheme is selected, such as a gradient from blue (small displacement) to red (large displacement); the displacement values ​​are mapped to a color space; corresponding colors are applied to curves or areas; a color legend is added to illustrate the correspondence between color and displacement; and the color contrast is adjusted to ensure clear visual effects. No limitation is made here.

[0043] S1039, marking the maximum displacement point and the deformation rate mutation point; In some embodiments, marking key points can highlight important features in deep horizontal displacement, helping engineers quickly identify potential problem areas. Accurately marking the maximum displacement points and deformation rate mutation points can provide important basis for further geological analysis and risk assessment, and help formulate targeted monitoring and control plans.

[0044] In some specific embodiments, the displacement data is analyzed to determine the position and value of the maximum displacement point; the displacement rate is calculated to identify the rate mutation point; a striking annotation style is designed, such as an arrow or a circle; annotation symbols are added to the graph; and explanatory text is added to each annotation point, including depth and displacement information; this is not limited here.

[0045] S10310. Add contour lines.

[0046] In some embodiments, adding contour lines can further enhance the information expression capability of the deep horizontal displacement curve, allowing the observer to more intuitively understand the spatial characteristics of the displacement distribution. Contour lines can clearly show the gradient change of the displacement, help identify the concentrated area and diffusion trend of the displacement, and provide engineers with a more detailed spatial analysis basis.

[0047] In some specific embodiments, the interval and number of contour lines are determined; a continuous displacement field is generated using an interpolation algorithm; and contour line labels are added at appropriate locations to display specific displacement values; this is not limited here.

[0048] It can be seen that the use of color coding and contour lines makes the displacement distribution clear at a glance, and the marking of the maximum displacement point and the deformation rate mutation point directly points out the areas that need to be focused on. This enhanced visualization method not only makes it easier for engineers to quickly understand the deformation status of the foundation pit, but also helps to identify potential risk areas, providing an intuitive basis for taking timely protective measures. S1035, adding the time information as the third dimension to the deep horizontal displacement curve graph to generate a three-dimensional surface graph; S1036, marking the time axis in the three-dimensional surface graph; After generating a 3D surface graph, this step needs to be performed to improve the readability and information transmission effect of the graph. When the 3D surface graph already contains depth, displacement, and time information, in order to enable the observer to accurately identify and interpret the time dimension, it is necessary to add clear time marks on the corresponding axes. In some embodiments, it is necessary to first determine the appropriate time interval, such as monthly, quarterly, or annually, to avoid over- or under-labeling. Then, according to the time span of the data, select an appropriate date format, such as "YYYY-MM-DD" or "YYYY-MM". Next, set the scale positions on the time axis of the 3D graph and apply formatted time labels to these scales.

[0049] S1037. Generate a deep horizontal displacement curve graph, which includes a two-dimensional cross-sectional graph and a three-dimensional surface graph.

[0050] It can be seen that sorting the deep horizontal displacement data by depth provides an orderly data basis for subsequent analysis. The cubic spline interpolation algorithm is used for interpolation processing to generate a continuous displacement curve, which improves the accuracy and continuity of the data. The displacement curve is drawn in a two-dimensional coordinate system to intuitively display the horizontal displacement at different depths. The time dimension is added to generate a three-dimensional surface graph, which makes the change of displacement with time and depth more clearly visible. A comprehensive deep horizontal displacement curve graph containing a two-dimensional profile graph and a three-dimensional surface graph is generated, providing multi-angle data display.

[0051] S104, determining the maximum stress-bearing position of the foundation pit support structure, and setting a foundation pit excavation response data acquisition device at the maximum stress-bearing position; The maximum stress-bearing part refers to the position where the supporting structure is subjected to the maximum stress or pressure; After the foundation pit support structure is established, its weakest link needs to be determined for key monitoring. In some embodiments, the personnel determine the location where the support structure is most likely to bear the maximum force by analyzing the design of the support structure, the distribution of soil pressure and the existing monitoring data. Once this maximum force location is determined, a special data acquisition device is installed there. This device can collect multiple parameters, such as stress, displacement, pore water pressure, etc., to comprehensively monitor the response of this key location during the foundation pit excavation process.

[0052] In some specific embodiments, the maximum stress point is determined by field testing, such as using a plate load test or a pressure gauge test; the maximum stress point is selected based on the test results; and a fiber optic sensing system is installed at this point to monitor multiple parameters in real time, which are not limited here.

[0053] In some embodiments, step S104 specifically includes: S1041. Set up multiple measuring points on the foundation pit support structure; S1042, collecting stress data of multiple measuring points; S1043. Generate a stress curve of stress distribution of the foundation pit support structure based on the stress data; In some embodiments, a stress distribution curve is generated based on the collected stress data, which can intuitively display the stress state of the foundation pit support structure. By converting discrete measurement point data into a continuous curve representation, engineers can more easily identify stress concentration areas, stress gradient changes, and potential abnormal points.

[0054] S1044. Determine the maximum stress-bearing part of the foundation pit support structure based on the stress curve.

[0055] It can be seen that setting multiple measuring points on the foundation pit support structure ensures the comprehensiveness of data collection. By collecting stress data from multiple measuring points, the actual stress condition of the support structure is obtained, and a stress distribution curve is generated based on the stress data. The stress state of the entire support structure is intuitively displayed. The maximum stress point is determined according to the stress curve, and precise positioning of the key area is achieved.

[0056] In some embodiments, step S1044 specifically includes: S10441. Identify the peak point on the stress curve; In some embodiments, by comparing the stress values ​​at various points on the curve, local maximum values ​​can be found. These peak points may represent potential high stress areas, and further analysis is required to determine the true maximum stress location.

[0057] S10442, determining whether the peak point is located at the boundary of the stress curve; In some embodiments, this process involves a careful examination of the location of each identified peak point. By comparing the coordinates of the peak point with the start and end coordinates of the stress curve, it can be determined whether the peak point is at a boundary position. This judgment is crucial for subsequent analysis, because peaks at the boundary may require special treatment, such as adding measurement points or expanding the monitoring range. At the same time, this step also helps to identify abnormal peaks that may be caused by measurement errors or boundary effects.

[0058] S10443. If it is not located at, the position corresponding to the peak point is determined as the maximum stress-bearing position of the foundation pit supporting structure; S10444. If located at, the boundary and its adjacent areas shall be identified as the key stress-bearing parts of the foundation pit support structure, and additional measurement points shall be set at the boundary and its adjacent areas; In some embodiments, this process involves re-evaluating the boundary areas and adjusting the monitoring plan. By increasing the density of measurement points in these areas, higher resolution stress distribution data can be obtained, allowing more precise location of the maximum stress points. This is particularly important because boundary areas are often special locations in structural mechanics, where stress concentrations or discontinuities may exist and require more careful monitoring and analysis.

[0059] S10445, collecting stress data of the additional measuring points; generating a local stress distribution curve based on the stress data of the additional measuring points; S10446. Based on the local stress distribution curve, determine the maximum stress position of the foundation pit support structure at the key stress-bearing part, and determine it as the maximum stress position of the foundation pit support structure.

[0060] It can be seen that identifying the peak point on the stress curve, preliminarily determining the possible maximum stress position, and judging whether the peak point is located at the boundary can avoid misjudgment caused by boundary effects, focus on the boundary and adjacent areas, add measurement points, ensure the data accuracy of the boundary area, generate local stress distribution curves, provide more detailed stress analysis of the boundary area, determine the final maximum stress position based on local analysis, and improve positioning accuracy.

[0061] S105, collecting response data using a foundation pit excavation response data collection device; During the excavation of the foundation pit, it is necessary to continuously monitor the changes in various parameters at key locations. In some embodiments, the data acquisition device installed at the maximum stress point is activated and starts to continuously record various response data. These data may include the displacement of the support structure, etc. The frequency of acquisition may be adjusted according to the excavation progress and site conditions to ensure that rapidly changing conditions can be captured.

[0062] S106, controlling each monitoring sensor network to transmit radio waves, and measuring the center point position of each monitoring sensor network; the center point position represents the center of the geometric distribution of the sensor network.

[0063] During the pit monitoring process, it is necessary to regularly confirm whether the position of the sensor network has changed. In some embodiments, the system controls each monitoring sensor network to transmit radio waves of a specific frequency. These radio waves are captured by the surrounding receiving devices, and the center point position of each sensor network is calculated through triangulation or other positioning technologies.

[0064] In some specific embodiments, firstly, a plurality of fixed wireless signal receivers are arranged around the foundation pit; then, the wireless transmission module of each sensor network is activated; finally, the coordinates of the center point of the network are calculated by trilateration using the received signal strength and time difference, which is not limited here.

[0065] S107, calculating the deformation of the foundation pit according to the change of the center point position; After obtaining the change data of the center point position of the sensor network, it is necessary to convert this data into meaningful foundation pit deformation information. In some embodiments, the system compares the center point positions measured at different time points and calculates the displacement vector. Then, based on the size and direction of these displacement vectors, combined with the geometric characteristics of the foundation pit and the properties of the support structure, the overall deformation of the foundation pit is calculated through a specific algorithm. This deformation can reflect the changes in the foundation pit in the horizontal and vertical directions, providing an important reference for evaluating the stability of the foundation pit.

[0066] S108, sending the foundation pit slope top displacement data, deep horizontal displacement data, deep horizontal displacement curve graph, foundation pit deformation, and response data to the cloud server.

[0067] It can be seen that the GPS positioning device collects displacement data on the top of the foundation pit slope, and the monitoring sensor network collects deep horizontal displacement data. These two data types complement each other and provide comprehensive information on the surface and internal deformation of the foundation pit. The generated deep horizontal displacement curve diagram intuitively shows the displacement of the support structure at each depth, which is helpful to identify potential weak areas. A foundation pit excavation response data acquisition device is set at the maximum stress point to obtain response data at key positions, further enriching the types of monitoring data. By measuring the position change of the center point of the monitoring sensor network, the deformation of the foundation pit is calculated, and a quantitative indicator of the overall deformation is provided. Various types of data (displacement data, curves, deformation, response data) are sent to the cloud server, laying the foundation for subsequent comprehensive analysis and risk assessment. This multi-dimensional and multi-type data collection and integration method improves the comprehensiveness of the description of the foundation pit environment, helps to judge potential risks more accurately, and overcomes the limitations of a single data type.

[0068] Figure 2 This is another schematic flow chart of the deep and large foundation pit monitoring method in the embodiment of the present application; In some embodiments, after step S108, the method further includes: S201, controlling each monitoring sensor network to transmit radio waves to measure the contour of the foundation pit; After completing the basic monitoring data collection, it is necessary to obtain the overall shape information of the foundation pit. In some embodiments, the system controls the various monitoring sensor networks distributed around the foundation pit to simultaneously transmit radio waves of a specific frequency. These radio waves are reflected at the edge of the foundation pit and captured by the receiving device. By analyzing the received signals, the system can calculate the position of each point on the edge of the foundation pit, thereby depicting the outline of the foundation pit. This method can quickly obtain the planar shape information of the foundation pit without interfering with construction.

[0069] In some specific embodiments, the wireless transmission modules of all sensor networks are activated to transmit coded wireless signals; then the direct signal and reflected signal received by the receiving station are used to determine the location of the reflection point through time difference and signal strength analysis; finally, the foundation pit outline is generated by connecting these reflection points, which is not limited here.

[0070] S202, sending the outline to a cloud server; S203, the cloud server establishes an initial three-dimensional geometric model of the foundation pit according to the outline; S204, the cloud server maps the foundation pit slope top displacement data to the slope top edge of the initial three-dimensional geometric model; After the initial three-dimensional geometric model of the foundation pit is established, the actual monitored deformation data needs to be integrated into the model. In some embodiments, the cloud server first processes the previously uploaded foundation pit slope top displacement data to ensure that the data format is compatible with the three-dimensional model. The server then accurately locates the coordinates corresponding to the actual measurement points in the three-dimensional model. Next, the system associates the displacement data of each measurement point with the corresponding position in the model. This process may involve coordinate transformation and data interpolation to ensure that the displacement data can be accurately reflected on the slope top edge of the model.

[0071] In some specific embodiments, the coordinates corresponding to the actual measurement points are marked in the three-dimensional model; then a vector attribute is created for each marked point to store the displacement information; then the displacement data is imported and assigned to the corresponding marked point; finally, an interpolation algorithm, such as the Kriging method, is used to generate a continuous displacement field between the marked points, covering the entire top edge of the slope, which is not limited here.

[0072] S205, the cloud server generates a displacement vector field on the surface of the initial three-dimensional geometric model according to the deep horizontal displacement data and the deep horizontal displacement curve graph; After integrating the surface displacement data into the model, it is necessary to further represent the deformation inside the foundation pit. In some embodiments, the cloud server first analyzes the deep horizontal displacement data and the corresponding curve graph to extract the displacement information at each depth. Then, the server creates a grid on the surface of the three-dimensional model, and each grid point corresponds to a possible displacement point. Next, the system maps the extracted displacement data to this grid, and estimates the displacement of points without direct measurement data through interpolation methods. Finally, a vector representing the direction and magnitude of the displacement is generated at each grid point to form a displacement vector field covering the entire model surface. This representation method can intuitively display the deformation trend of the foundation pit support structure at various locations and depths.

[0073] In some specific embodiments, the deep horizontal displacement data is converted into a point set in a three-dimensional coordinate system; then a three-dimensional interpolation algorithm (such as trilinear interpolation) is used to generate a continuous displacement field on the entire model surface; then the sampling points are evenly distributed on the surface; finally, the displacement vector is calculated at each sampling point and represented by graphic symbols such as arrows, which are not limited here.

[0074] S206, the cloud server adjusts the shape and position of the initial three-dimensional geometric model using the deformation of the foundation pit; S207, the cloud server uses a three-dimensional interpolation algorithm to generate a continuous deformation field based on the discrete foundation pit deformation; After obtaining the discrete pit deformation data, it is necessary to create a model that can describe the deformation of the entire pit area. In some embodiments, the cloud server first collects all available discrete deformation data points, including surface and deep measurements. The server then selects a suitable three-dimensional interpolation algorithm, such as Kriging, radial basis function interpolation, or trilinear interpolation. Next, the system uses the selected algorithm to calculate the deformation values ​​in the entire three-dimensional space based on these discrete data points. This process generates a mathematical function or grid that can be used to estimate the deformation at any point in the pit. The resulting continuous deformation field can provide a comprehensive view of the pit deformation, including areas that are not directly measured.

[0075] In some specific embodiments, a three-dimensional grid containing all discrete data points is constructed; then an appropriate weight function is selected, such as an inverse distance weighted method; an interpolation algorithm is then applied to each point in the grid to calculate its deformation value; finally, a high-resolution continuous deformation field is obtained by mathematical function fitting or grid refinement, which is not limited here.

[0076] S208, the cloud server performs deformation processing on the initial three-dimensional geometric model according to the continuous deformation field to generate a deformed three-dimensional model; S209. The cloud server adds a time dimension to the deformed three-dimensional model to obtain a BIM model of the foundation pit.

[0077] After generating the deformed 3D model, the time factor needs to be integrated to show the dynamic changes of the foundation pit over time. In some embodiments, the cloud server first establishes a time series containing the timestamps of all monitoring data. The server then associates the deformation state at each time point with the corresponding 3D model. This may involve creating snapshots of the model at multiple time points, or defining a parametric model that changes over time.

[0078] It can be seen that by measuring the foundation pit contour and establishing the initial three-dimensional geometric model, a basic framework is provided for subsequent analysis. The displacement data of the foundation pit slope top is mapped to the edge of the model, which intuitively displays the surface deformation. A displacement vector field is generated on the model surface, which clearly presents the deformation trend and direction of the support structure. The shape and position of the model are adjusted using the foundation pit deformation to reflect the overall deformation condition. A three-dimensional interpolation algorithm is used to generate a continuous deformation field, which improves the accuracy and continuity of the deformation description. The model is deformed and the time dimension is added to obtain a dynamic BIM model, which realizes the three-dimensional visualization of the foundation pit status. By adding the time dimension, the monitoring results are made more intuitive and dynamic.

[0079] In some embodiments, after the step S209, the method further includes: S210, the cloud server obtains the foundation pit change value according to the BIM model; S211, the cloud server compares the foundation pit change value with the multi-level safety threshold; the multi-level safety threshold includes a warning value, an alarm value, and a danger value; In some specific embodiments, preset multi-level safety threshold data are read; the acquired foundation pit change value is compared with the warning value; if it exceeds the warning value, it is further compared with the alarm value; if it exceeds the alarm value, it is finally compared with the danger value; and the comparison results are recorded, including whether the thresholds at each level are exceeded and the degree of exceeding.

[0080] S212. The cloud server determines the safety status level of the foundation pit according to the comparison result; S213. The cloud server generates a safety report based on the safety status level, where the safety report includes an overview of the current foundation pit safety status and response suggestions for different safety status levels. In some specific embodiments, the current foundation pit safety status level and related data are extracted; a preset report template is used to fill in basic information and safety status data; corresponding response suggestions are selected from the knowledge base according to the safety status level; charts or graphs are generated to intuitively display the foundation pit change trend and current status; and all information is integrated to form a structured safety report document.

[0081] S214. The cloud server sends a security report to relevant personnel according to the urgency of the security status level.

[0082] It can be seen that the cloud server obtains the foundation pit change value based on the BIM model, provides a quantitative evaluation basis, compares the change value with the multi-level safety threshold (warning value, alarm value and danger value), establishes a graded evaluation standard, and determines the safety status level of the foundation pit based on the comparison results. It realizes automated safety status judgment and generates a safety report containing an overview of the current status and response recommendations, providing a direct basis for decision-making.

[0083] The following introduces an exemplary deep and large foundation pit monitoring system 300 provided in an embodiment of the present application. Figure 3 It is a schematic diagram of an exemplary hardware structure of a deep and large foundation pit monitoring system 300 provided in an embodiment of the present application.

[0084] In some embodiments, the deep and large foundation pit monitoring system 300 is a computer device or the deep and large foundation pit monitoring system 300 includes a computer device. The computer device includes a processor, a memory and a network interface connected by a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store data. The network interface of the computer device is used to communicate with other external terminals or servers through a network connection. In some embodiments, the network interface can be a wired network interface, and in some embodiments, the network interface can also be a wireless network interface. When the computer program is executed by the processor, the method in the embodiment of the present application is implemented.

[0085] Those skilled in the art will understand that Figure 3 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0086] As described above, the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present application.

[0087] As used in the above embodiments, the term "when..." may be interpreted to mean "if..." or "after..." or "in response to determining..." or "in response to detecting...", depending on the context. Similarly, the phrases "upon determining..." or "if (the stated condition or event) is detected" may be interpreted to mean "if determining..." or "in response to determining..." or "upon detecting (the stated condition or event)" or "in response to detecting (the stated condition or event)", depending on the context.

[0088] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware or any combination thereof. When implemented using software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from a website site, computer, server or data center by wired (e.g., coaxial cable, optical fiber, digital subscriber line) or wireless (e.g., infrared, wireless, microwave, etc.) mode to another website site, computer, server or data center. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that contains one or more available media integration. The available medium can be a magnetic medium, (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium (e.g., a solid-state hard disk), etc.

[0089] Those skilled in the art can understand that to implement all or part of the processes in the above-mentioned embodiments, the processes can be completed by computer programs to instruct related hardware, and the programs can be stored in computer-readable storage media. When the programs are executed, they can include the processes of the above-mentioned method embodiments. The aforementioned storage media include: ROM or random access memory RAM, magnetic disk or optical disk and other media that can store program codes.

Claims

1. A deep and large foundation pit monitoring method, characterized in that: include: GPS positioning devices are arranged around the foundation pit to collect displacement data of the top of the foundation pit slope; A plurality of monitoring sensor networks are arranged on the foundation pit support structure to collect deep horizontal displacement data, wherein the monitoring sensor network is composed of a plurality of monitoring sensors; Generate a deep horizontal displacement curve graph according to the deep horizontal displacement data; wherein the deep horizontal displacement curve graph is supplemented with the deep horizontal displacement data of each monitoring sensor in the vertical direction; Determine the maximum stress-bearing position of the foundation pit support structure, and set a foundation pit excavation response data acquisition device at the maximum stress-bearing position; Collecting response data using the foundation pit excavation response data collection device; Controlling each of the monitoring sensor networks to transmit radio waves and measuring the center point position of each of the monitoring sensor networks; Calculating the amount of foundation pit deformation according to the change in the position of the center point; The foundation pit slope top displacement data, the deep horizontal displacement data, the deep horizontal displacement curve graph, the foundation pit deformation, and the response data are sent to a cloud server.

2. The method according to claim 1, characterized in that After the step of sending the foundation pit slope top displacement data, the deep horizontal displacement data, the deep horizontal displacement curve graph, the foundation pit deformation, and the response data to the cloud server, the method further includes: Controlling each of the monitoring sensor networks to transmit radio waves to measure the contour of the foundation pit; sending the profile to the cloud server; The cloud server establishes an initial three-dimensional geometric model of the foundation pit according to the outline; The cloud server maps the foundation pit slope top displacement data to the slope top edge of the initial three-dimensional geometric model; The cloud server generates a displacement vector field on the surface of the initial three-dimensional geometric model according to the deep horizontal displacement data and the deep horizontal displacement curve graph; The cloud server adjusts the shape and position of the initial three-dimensional geometric model using the deformation of the foundation pit; The cloud server generates a continuous deformation field based on the discrete deformation of the foundation pit using a three-dimensional interpolation algorithm; The cloud server performs deformation processing on the initial three-dimensional geometric model according to the continuous deformation field to generate a deformed three-dimensional model; The cloud server adds a time dimension to the deformed three-dimensional model to obtain a BIM model of the foundation pit.

3. The method according to claim 2, characterized in that After the step of adding a time dimension to the deformed three-dimensional model by the cloud server to obtain a BIM model of the foundation pit, the method further includes: The cloud server obtains the foundation pit change value according to the BIM model; The cloud server compares the foundation pit change value with a multi-level safety threshold; the multi-level safety threshold includes a warning value, an alarm value, and a danger value; The cloud server determines the safety status level of the foundation pit according to the comparison result; The cloud server generates a safety report according to the generated safety status level, wherein the safety report includes an overview of the current foundation pit safety status and response suggestions for different safety status levels; The cloud server sends the security report to relevant personnel according to the urgency of the security status level.

4. The method according to claim 1, characterized in that: The step of generating a deep horizontal displacement curve graph according to the deep horizontal displacement data specifically includes: sorting the deep horizontal displacement data according to corresponding depth information; The sorted deep horizontal displacement data are interpolated using a cubic spline interpolation algorithm to generate a continuous displacement curve; Create a two-dimensional coordinate system, where the horizontal axis represents the horizontal displacement and the vertical axis represents the depth; Drawing the continuous displacement curve in the two-dimensional coordinate system to form a preliminary deep horizontal displacement curve diagram; Adding time information as a third dimension to the deep horizontal displacement curve graph to generate a three-dimensional surface graph; Marking a time axis in the three-dimensional surface graph; The deep horizontal displacement curve diagram is generated, and the deep horizontal displacement curve diagram includes a two-dimensional cross-sectional diagram and the three-dimensional surface diagram.

5. The method according to claim 4, characterized in that After the step of drawing the continuous displacement curve in the two-dimensional coordinate system to form a preliminary deep horizontal displacement curve diagram, the method further comprises: Using color coding to represent different degrees of said deep horizontal displacement; Mark the maximum displacement point and deformation rate mutation point; Add contour lines.

6. The method according to claim 1, characterized in that The step of determining the maximum stress-bearing position of the foundation pit supporting structure specifically includes: Setting a plurality of measuring points on the foundation pit supporting structure; collecting stress data of the plurality of measuring points; Based on the stress data, a stress curve of the stress distribution of the foundation pit support structure is generated; According to the stress curve, the maximum stress-bearing position of the foundation pit supporting structure is determined.

7. The method according to claim 6, characterized in that The step of determining the maximum stress-bearing position of the foundation pit support structure according to the stress curve specifically includes: identifying a peak point on the stress curve; Determining whether the peak point is located at the boundary of the stress curve; If not, the position corresponding to the peak point is determined as the maximum stress-bearing part of the foundation pit supporting structure; If located at, the boundary and its adjacent areas are determined as the key stress-bearing parts of the foundation pit support structure, and additional measurement points are set at the boundary and its adjacent areas; Collecting stress data of the additional measuring points; generating a local stress distribution curve based on the stress data of the additional measuring points; According to the local stress distribution curve, the maximum stress position of the foundation pit supporting structure at the key stress-bearing part is determined, and it is determined as the maximum stress position of the foundation pit supporting structure.

8. A deep and large foundation pit monitoring system, characterized in that: The deep and large foundation pit monitoring system includes: one or more processors and a memory; the memory is coupled to the one or more processors, the memory is used to store computer program code, the computer program code includes computer instructions, and the one or more processors call the computer instructions to enable the deep and large foundation pit monitoring system to execute the method described in any one of claims 1-7.

9. A computer program product comprising instructions, characterized in that When the computer program product runs on a deep and large foundation pit monitoring system, the deep and large foundation pit monitoring system is enabled to execute the method according to any one of claims 1 to 7.

10. A computer-readable storage medium comprising instructions, characterized in that: When the instruction is executed on a deep and large foundation pit monitoring system, the deep and large foundation pit monitoring system is caused to execute the method as described in any one of claims 1-7.

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