Monitoring and warning method and device for foundation pit and pile body in building construction

Abstract

Embodiments of the present disclosure disclose a monitoring and early warning method and device for building construction foundation pits and pile bodies. A specific implementation of the method includes: establishing a building area scene model; using pre-installed construction monitoring probes to capture images of a local construction area, and collecting a construction pile body data set through a preset data acquisition device component; performing local grid division on the underground geological layer of the building area scene model according to the local construction area image and the building area scene model to obtain the divided building area model; performing collapsibility analysis on the foundation pit area and the pile body area based on the construction pile body data set and the divided building area model to generate collapsibility distribution data of the pile body area; generating a collapsibility early warning heat map in the divided building area model, and sending the collapsibility early warning heat map to an early warning terminal for early warning operations. This implementation can perform collapsibility monitoring and early warning in a timely manner.

Description

Technical Field

[0001] Embodiments of the present disclosure relate to the field of computer technology and the field of building construction monitoring and early warning, and specifically relate to a method and device for monitoring and early warning of building construction foundation pits and piles. Background Art

[0002] With the development of China's construction industry, many large-scale construction projects need to be built on collapsible loess sites. The depth and difficulty of foundation treatment are increasing, and the existing foundation treatment methods are often restricted by certain conditions. Currently, the main technological methods for treating collapsible loess include pile foundations, replacement cushions, dynamic compaction, compaction piles, pre-soaking methods, deep mixing piles, etc. There are many methods for treating collapsible loess foundations. In different regions, different foundation treatment processes should be selected according to different foundation soil qualities and structures. Finally, long-term manual maintenance is required after construction to detect the degree of collapsibility change in the construction area.

[0003] However, when using the above methods, the following technical problems often exist:

[0004] When the construction area is large, more labor costs are required, and it is difficult to uniformly process a large amount of collected data, making it difficult to timely monitor and early warn the collapsibility of the foundation pit and pile areas.

[0005] The above information disclosed in this background art section is only used to enhance the understanding of the background of the inventive concept, and thus, it may include information that does not form the prior art known to those of ordinary skill in the art. Summary of the Invention

[0006] The content part of the present disclosure is used to briefly introduce the concepts, which will be described in detail in the following detailed implementation part. The content part of the present disclosure is not intended to identify the key features or essential features of the claimed technical solution, nor is it intended to limit the scope of the claimed technical solution.

[0007] Some embodiments of the present disclosure propose a method and device for monitoring and early warning of building construction foundation pits and piles to solve the technical problems mentioned in the above background art section.

[0008] In a first aspect, some embodiments of the present disclosure provide a monitoring and early warning method for a foundation pit and pile body in building construction. The method includes: in response to the completion of building construction, establishing a building area scene model through building construction geological acquisition data and a preset building construction simulation model. Among them, in the ground area of the above-mentioned building area scene model, there are marked: a foundation pit area, a pile body area, a greening area, and other areas. In the above-mentioned building area scene model, there are set foundation pit information, pile body information, and underground geological layer distribution data corresponding to the foundation pit area; using a pre-installed construction monitoring probe to capture an image of a local construction area, and through a preset data acquisition device component, collecting a construction pile body data set. Among them, the above-mentioned local construction area image is used to adjust the acquisition frequency of the data acquisition device component. Each construction pile body data in the construction pile body data set includes: a pile body serial number, a pile body coordinate, a pile body type identifier, and a pile body description information. Each construction pile body data corresponds to a pile body; according to the above-mentioned local construction area image and the above-mentioned building area scene model, performing local grid division on the underground geological layer of the above-mentioned building area scene model to obtain a divided building area model. Among them, the local grid division is centered on the foundation pit area. The above-mentioned local construction area image is also used to adjust the grid division range; based on the above-mentioned construction pile body data set and the above-mentioned divided building area model, performing collapsibility analysis on the foundation pit area and the pile body area to generate collapsibility distribution data of the pile body area; in response to determining that the above-mentioned collapsibility distribution data of the pile body area meets a preset early warning condition, generating a collapsibility early warning heat map in the above-mentioned divided building area model according to the above-mentioned collapsibility distribution data of the pile body area, and sending the above-mentioned collapsibility early warning heat map to an early warning terminal for early warning operations.

[0009] Second aspect, some embodiments of the present disclosure provide a monitoring and warning device for a foundation pit and a pile body in building construction. The device includes: a building unit configured to, in response to the completion of building construction, establish a building area scene model through building construction geological acquisition data and a preset building construction simulation model. In the ground area of the building area scene model, there are marked: a foundation pit area, a pile body area, a greening area, and other areas. In the building area scene model, there are set foundation pit information, pile body information, and underground geological layer distribution data corresponding to the foundation pit area; a collection unit configured to use a pre-installed construction monitoring probe to capture images of a local construction area, and collect a construction pile body data set through a preset data collection device component. The local construction area image is used to adjust the collection frequency of the data collection device component. Each construction pile body data in the construction pile body data set includes: a pile body serial number, a pile body coordinate, a pile body type identifier, and a pile body description information. Each construction pile body data corresponds to a pile body; a grid division unit configured to perform local grid division on the underground geological layer of the building area scene model according to the local construction area image and the building area scene model to obtain a divided building area model. The local grid division is centered on the foundation pit area. The local construction area image is also used to adjust the grid division range; a collapsibility analysis unit configured to perform collapsibility analysis on the foundation pit area and the pile body area based on the construction pile body data set and the divided building area model to generate collapsibility distribution data of the pile body area; a generation and warning unit configured to, in response to determining that the collapsibility distribution data of the pile body area meets a preset warning condition, generate a collapsibility warning heat map in the divided building area model according to the collapsibility distribution data of the pile body area, and send the collapsibility warning heat map to a warning terminal for warning operations.

[0010] Third aspect, some embodiments of the present disclosure provide an electronic device, including: one or more processors; a storage device on which one or more programs are stored. When the one or more programs are executed by the one or more processors, the one or more processors implement the method described in any implementation manner of the first aspect.

[0011] Fourth aspect, some embodiments of the present disclosure provide a computer-readable medium on which a computer program is stored. When the program is executed by a processor, the method described in any implementation manner of the first aspect is implemented.

[0012] The above-mentioned various embodiments of the present disclosure have the following beneficial effects: Through the monitoring and early warning method for building construction foundation pits and pile bodies in some embodiments of the present disclosure, it is possible to timely monitor and early warn of the collapsibility of the foundation pit and the area where the pile bodies are located. Specifically, the reasons for the difficulty in timely monitoring and early warning of the collapsibility of the foundation pit and the area where the pile bodies are located are as follows: When the construction area is large, it requires a large amount of labor costs, and it is difficult to uniformly process a large amount of collected data. Based on this, the monitoring and early warning method for building construction foundation pits and pile bodies in some embodiments of the present disclosure, in response to the completion of building construction, establishes a building area scene model through the building construction geological collection data and a preset building construction simulation model. Among them, in the ground area of the above-mentioned building area scene model, there are marked: foundation pit area, pile body area, greening area, and other areas. In the above-mentioned building area scene model, there are set foundation pit information, pile body information, and underground geological layer distribution data corresponding to the foundation pit area. Considering that it is difficult to uniformly process the construction area data, a building area scene model is thus established. This enables various collected data to be summarized based on the building area scene model, facilitating unified processing. Then, use the pre-installed construction monitoring probe to capture images of the local construction area, and collect the construction pile body data set through the preset data collection device components. Among them, the above-mentioned local construction area image is used to adjust the collection frequency of the data collection device components. Each construction pile body data in the construction pile body data set includes: pile body serial number, pile body coordinates, pile body type identifier, and pile body description information. Each construction pile body data corresponds to a pile body. Here, in order to reduce labor costs, the construction monitoring probe and the data collection device components are used to assist in data collection. After that, according to the above-mentioned local construction area image and the above-mentioned building area scene model, local grid division is performed on the underground geological layer of the above-mentioned building area scene model to obtain the divided building area model. Among them, the local grid division is centered on the foundation pit area, and the above-mentioned local construction area image is also used to adjust the grid division range. Here, through local grid division, it is convenient to quantify the data of the soil body under the construction area, so as to facilitate the analysis of the collapsibility degree. Then, based on the above-mentioned construction pile body data set and the above-mentioned divided building area model, collapsibility analysis is performed on the foundation pit area and the pile body area to generate the collapsibility distribution data of the pile body area. Here, through collapsibility analysis, the collapsibility distribution data of all areas within the building construction area can be uniformly generated. Thus, it is convenient to conduct collapsibility monitoring and early warning. Finally, in response to determining that the above-mentioned collapsibility distribution data of the pile body area meets the preset early warning conditions, according to the above-mentioned collapsibility distribution data of the pile body area, a collapsibility early warning heat map is generated in the above-mentioned divided building area model, and the above-mentioned collapsibility early warning heat map is sent to the early warning terminal for early warning operations. Thus, it is possible to timely monitor and early warn of the collapsibility of the foundation pit and the area where the pile bodies are located. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] In combination with the accompanying drawings and with reference to the following specific embodiments, the above and other features, advantages, and aspects of the embodiments of the present disclosure will become more apparent. Throughout the drawings, the same or similar reference numerals denote the same or similar elements. It should be understood that the drawings are schematic, and the elements and elements are not necessarily drawn to scale.

[0014] Figure 1 is a flowchart of some embodiments of a monitoring and early warning method for a building construction foundation pit and a pile body according to the present disclosure;

[0015] Figure 2 is a schematic diagram of the geological distribution in the pile body area;

[0016] Figure 3 is a schematic diagram of the geological structure stratification;

[0017] Figure 4 is a heat map for collapse warning;

[0018] Figure 5 is a schematic structural diagram of some embodiments of a monitoring and early warning device for a building construction foundation pit and a pile body according to the present disclosure;

[0019] Figure 6 is a schematic structural diagram of an electronic device suitable for implementing some embodiments of the present disclosure. Specific Embodiments

[0020] The embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although some embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure can be implemented in various forms and should not be construed as limited to the embodiments set forth herein. On the contrary, these embodiments are provided to more thoroughly and completely understand the present disclosure. It should be understood that the drawings and embodiments of the present disclosure are only for exemplary purposes and are not used to limit the protection scope of the present disclosure.

[0021] In addition, it should be noted that for the sake of convenience of description, only the parts related to the relevant invention are shown in the drawings. Without conflict, the embodiments in the present disclosure and the features in the embodiments can be combined with each other.

[0022] It should be noted that the concepts such as "first" and "second" mentioned in the present disclosure are only used to distinguish different devices, modules, or units, and are not used to limit the order or mutual dependence relationship of the functions performed by these devices, modules, or units.

[0023] It should be noted that the modifications of "one" and "multiple" mentioned in the present disclosure are illustrative rather than restrictive. Those skilled in the art should understand that unless otherwise clearly specified in the context, it should be understood as "one or more".

[0024] The names of the messages or information exchanged between multiple devices in the embodiments of the present disclosure are for illustrative purposes only and are not used to limit the scope of these messages or information.

[0025] The present disclosure will be described in detail below with reference to the accompanying drawings and in conjunction with embodiments.

[0026] Figure 1 Flow 100 of some embodiments of a monitoring and early warning method for a building construction foundation pit and pile body according to the present disclosure is shown. The monitoring and early warning method for a building construction foundation pit and pile body includes the following steps:

[0027] Step 101, in response to the completion of building construction, establish a building area scene model through building construction geological acquisition data and a preset building construction simulation model.

[0028] In some embodiments, the execution subject (e.g., an electronic device) of the monitoring and early warning method for a building construction foundation pit and pile body can, in response to the completion of building construction, establish a building area scene model through building construction geological acquisition data and a preset building construction simulation model. Among them, the ground area in the above-mentioned building area scene model is marked with: a foundation pit area, a pile body area, a pile body area, a greening area, and other areas. The above-mentioned building area scene model is provided with foundation pit information, pile body information, and underground geological layer distribution data corresponding to the foundation pit area. Here, the building area simulation model can be a three-dimensional building model constructed by simulating a building. For example, the building area simulation model can be a bridge simulation model, a house simulation model, a dam simulation model, etc. The building construction geological acquisition data can be data obtained from geological exploration of the construction area before building construction, and can include geological attributes and geological depths corresponding to each coordinate. For example, the surface soil layer is from 0 to 1.5 meters underground, the accumulated loess-like silt is from 1.5 to 3 meters, the collapsible loess-like silt or powdery clay is from 3 to 15 meters, and the non-collapsible silty clay is from 15 to 25 meters.

[0029] It should be noted that the above computing device can be hardware or software. When the computing device is hardware, it can be implemented as a distributed cluster composed of multiple servers or terminal devices, or can be implemented as a single server or a single terminal device. When the computing device is embodied as software, it can be installed in the above-listed hardware devices. It can be implemented as, for example, multiple software or software modules used to provide distributed services, or can be implemented as a single software or software module. No specific limitation is made here.

[0030] In some optional implementation manners of some embodiments, the above-mentioned execution subject building construction geological acquisition data is used to represent the underground geological distribution data of the construction area. The establishment of the building area scene model through the building construction geological acquisition data and the preset building construction simulation model includes:

[0031] First step, convert the preset building construction simulation model into the pre-established building area coordinate system, and convert the above-mentioned building construction geological acquisition data into the above-mentioned building area coordinate system according to the corresponding coordinates to obtain the initial building area scene model. Among them, the building area coordinate system can be established with any coordinate in the building area as the origin, the horizontal plane of the coordinate system is parallel to the ground, and the orientation is not limited. Thus, the building construction simulation model can be converted into the building area coordinate system according to the actual corresponding direction. The corresponding relationship between the building construction geological acquisition data and the building area coordinate system can be determined by means of coordinate transformation, so that the geological attributes and geological depths in the building construction geological acquisition data can be filled into the building area coordinate system in the form of digital identifiers. Thus, the initial building area scene model is obtained. Here, the initial building area scene model can be used to represent the geological distribution in the construction area after the building construction is completed. Thus, it can be used as a benchmark for the geological conditions in the construction area to facilitate the subsequent determination of the degree of land subsidence.

[0032] Second step, mark the corresponding ground area in the above-mentioned initial building area scene model according to the preset ground construction area data, and mark the corresponding foundation pit information and pile body information in the above-mentioned initial building area scene model according to the preset foundation pit pile body construction data to obtain the above-mentioned building area scene model. Among them, the ground construction area data can be the distribution characteristics of the ground area after building construction. It can include the distribution coordinates of each area. For example, it includes building areas, foundation pit areas, greening areas or other areas, etc. Other areas can be road areas. Here, considering that the water seepage degrees of surface water in different areas are different (for example, the water volume in the greening area is relatively large and the seepage is more), different area identifiers are introduced to facilitate subsequent reference factors for subsidence analysis. In addition, the foundation pit information can include information such as the scope and depth of the foundation pit. The pile body information can include information such as pile body serial number, pile body coordinates and pile body depth.

[0033] Step 102, use the pre-installed construction monitoring probe to take images of the local construction area, and collect the construction pile body data set through the preset data acquisition device components.

[0034] In some embodiments, the above-mentioned execution entity may use pre-installed construction monitoring probes to capture images of local construction areas, and collect a construction pile data set through a preset data acquisition device component. Among them, the above-mentioned local construction area image can be used to adjust the acquisition frequency of the data acquisition device component. Each construction pile data in the construction pile data set may include: pile number, pile coordinates, pile type identifier, and pile description information, and each construction pile data corresponds to a pile. The pile type identifier can represent the construction type of the pile. For example, soil compaction pile, deep mixing pile, etc. The pile description information may include pile attributes. For example, pile attributes may include edge piles or corner piles, etc.

[0035] In some alternative implementation manners of some embodiments, the data acquisition device component may include, but is not limited to, at least one of the following devices: pore water pressure gauge group, ground penetrating radar, total station, soil moisture content sensor group, and micro-earth pressure gauge group. Among them, the pore water pressure gauge, soil moisture sensor, and micro-earth pressure gauge are buried in the soil body of the foundation pit area.

[0036] The above-mentioned execution entity collects a construction pile data set through a preset data acquisition device component, which may include the following steps:

[0037] First step, perform rainfall recognition on the above-mentioned local construction area image to generate a rainfall level identifier. Among them, the above-mentioned rainfall level identifier is used to represent the rainfall accumulation degree of the local construction area. In practice, if only the weather forecast is used as the rainfall judgment standard, it is easy to cause misjudgment due to no rainfall in the local area, resulting in not only reduced effectiveness but also more computing resources and storage resources being occupied when randomly increasing the data acquisition frequency for collapsibility analysis. Therefore, by recognizing the image of the construction area to determine the actual rainfall degree, the rainfall level identifier can be determined more accurately. Here, a pre-trained rainfall recognition model can be used to perform precipitation recognition on the above-mentioned local construction area image to generate a rainfall level identifier.

[0038] As an example, the rainfall recognition model may include a feature extractor and a feature classifier. Among them, the feature extractor can be a convolutional neural network, composed of three convolutional layers and pooling layers. The feature classifier can be a fully connected neural network, composed of a flattening layer and two fully connected layers. The flattening layer flattens the feature map into a one-dimensional vector. The two fully connected layers are used to output the rainfall level identifier. In practice, the rainfall level can be divided into four levels: light rain, moderate rain, heavy rain, and rainstorm.

[0039] Second step, in response to determining rainfall in the building construction area, adjust the acquisition frequency of the data acquisition device component according to the rainfall level identifier. Among them, the acquisition frequency of the data acquisition device component can be adjusted according to the pre-set correspondence between the acquisition frequency and the rainfall level identifier.

[0040] As an example, the preset acquisition frequency can be once every 3 days. The acquisition frequency corresponding to the rainfall level identifier characterizing heavy rain can be once every 5 hours.

[0041] In the third step, according to the building construction completion time point and the current time point, the current monitoring time period is determined. Among them, multiple monitoring time periods can be pre-divided according to the building construction completion time point. For example, within one week after the construction is completed is the first time period, within 3 months is the second time period, and within 2 years is the third time period. Thus, the current monitoring time period can be determined according to the time period where the current time point is located (for example, the first time period, the second time period, or the third time period).

[0042] In the fourth step, in response to determining that the above current monitoring time period is within the first preset monitoring time period, use the above ground penetrating radar to detect the integrity of the pile bodies in the foundation pit area within the building construction area, and obtain a set of pile body integrity detection information. Among them, the detection instruction can be sent to a personal terminal (for example, the mobile phone terminal of a worker) to notify the worker to control the above ground penetrating radar to detect the integrity of the pile bodies in the foundation pit area within the building construction area, and obtain a set of pile body integrity detection information. Here, the pile body integrity detection is used to detect whether there are abnormal conditions such as "necking down" and "broken piles" in the pile bodies.

[0043] For example, if it is detected that a certain pile body has an abnormal condition of "broken pile", the pile body detection identifier representing the abnormality can be determined as the pile body integrity detection information.

[0044] In practice, due to the large void ratio, low water content, and relatively loose structure of the shallow collapsible soil mass, it is easy to have settlement after encountering seepage water. Therefore, the relative collapsibility degree is relatively large. Therefore, the ground penetrating radar can also be used to detect the geological structure of the shallow underground area within a certain range of the pile body (for example, within 10 meters), and obtain geological structure data. For example, different depths and corresponding geological properties. In addition, for the depth area above 10 meters, the geological structure can be determined by the method of drilling and sampling. Thus, the pile body integrity detection information can also include the geological data of the pile body area after detection.

[0045] In the fifth step, use the above total station to detect the pile tops of each pile body in the foundation pit area, and obtain a set of pile body displacement detection information. Among them, the total station is used to measure the horizontal displacement of the pile bodies (including side piles and corner piles). The total station detection instruction can be sent to a personal terminal for notifying the worker to control the above total station to detect the pile tops of each pile body in the foundation pit area, and obtain a set of pile body displacement detection information. Here, the pile body displacement detection information can include the horizontal displacement value of the pile top of the pile body.

[0046] Step 6: Use the pile integrity detection information and pile displacement detection information corresponding to the same pile in the above pile integrity detection information set and the above pile displacement detection information set as the construction pile data to obtain the construction pile data set.

[0047] Optionally, the above execution entity uses a pre-installed construction monitoring probe to capture an image of a local construction area, and collects the construction pile data set through a preset data acquisition device component. The method may further include the following steps:

[0048] Step 1: In response to determining that the current monitoring time period is within the second preset monitoring time period, use the above piezometer group to detect the water level data of the foundation pit area to obtain the water level data set. Among them, the water level data can represent the distance from the groundwater level to the bottom of the pile. Each piezometer corresponds to a pile.

[0049] Step 2: Use the above soil moisture sensors to detect the soil moisture content of the foundation pit area to obtain the soil moisture content set. Among them, each soil moisture sensor can correspond to a pile.

[0050] Step 3: Use the above micro-earth pressure gauges to detect the horizontal soil stress value between the corner piles and the retaining piles in the foundation pit area to obtain the horizontal soil stress value set. Among them, the micro-earth pressure gauges can be buried between two piles.

[0051] Step 4: Add the above water level data set, the above soil moisture content set, and the above horizontal soil stress value set to the above construction pile data set.

[0052] As an example, as Figure 2 shown in the schematic diagram of the geological distribution of the pile area. Figure 2 The left figure in it can be a distribution map established using the underground geological layer distribution data to represent the geological distribution of the area where the pile 201 is located after construction. Figure 2 The right figure in it can be a distribution map established based on the current geological data of the area where the pile 201 is located determined by combining ground penetrating radar and borehole sampling to represent the situation of geological subsidence after construction for a period of time.

[0053] Step 103: According to the local construction area image and the building area scene model, perform local grid division on the underground geological layer of the building area scene model to obtain the divided building area model.

[0054] In some embodiments, the above execution entity may perform local grid division on the underground geological layer of the above building area scene model according to the above local construction area image and the above building area scene model to obtain the divided building area model. Among them, the local grid division is centered on the foundation pit area, and the above local construction area image is also used to adjust the grid division range.

[0055] In some alternative implementation manners of some embodiments, the above-mentioned execution subject performs local grid division on the underground geological layer of the above-mentioned building area scene model according to the above-mentioned construction local area image and the above-mentioned building area scene model, and the obtained building area model after division may include the following steps:

[0056] First step, determine the grid sizes corresponding to the foundation pit area and the pile bodies in the above-mentioned building area scene model according to the rainfall grade identifier corresponding to the above-mentioned construction local area image. Among them, the current grid ratio can be determined according to the pre-set corresponding relationship between the rainfall grade identifier and the grid ratio. Then, the product of the basic grid size and the current grid ratio (for example, 0.5) can be determined as the adjusted grid size. Here, the overall grid size of the foundation pit area is different from the local grid size of each pile body.

[0057] In practice, considering that the seepage volume will increase after rainfall, if data collation is carried out with a fixed grid division, the grid division granularity of a larger grid size is larger. Therefore, reducing the grid size through the current grid ratio can be used for fine-grained grid division. Thus, it is convenient for the richness of subsequent soil body characteristics, so as to improve the accuracy of soil body collapsibility analysis.

[0058] Second step, determine the grid division ranges corresponding to the foundation pit area and the pile bodies in the above-mentioned building area scene model according to the rainfall grade identifier corresponding to the above-mentioned construction local area image. Among them, the current grid range ratio can be determined according to the pre-set corresponding relationship between the rainfall grade identifier and the grid division range. For example, the current grid range ratio can be 1.2. Then, the product of the basic division range and the current grid range ratio can be determined as the adjusted grid division range. Here, the grid division ranges of the foundation pit area and the pile bodies are different.

[0059] In practice, considering that the increase in seepage volume after rainfall will cause the soil body to sink faster and increase the degree of collapsibility. Therefore, in order to further observe the influence of soil body collapsibility on the pile bodies, the grid division range can be expanded. In this way, for the analysis of each pile body, related features can be increased, so as to improve the accuracy of collapsibility analysis.

[0060] Third step, use the grid sizes and grid division ranges corresponding to the foundation pit area and the pile body area to perform local grid division on the underground geological layer of the above-mentioned building area scene model, and obtain the building area model after division. Among them, the local grid division can be centered on each pile body, and within the corresponding grid division range, local grid division is performed according to the corresponding grid size to obtain the building area model after division.

[0061] In addition, the overall grid division can be carried out for the foundation pit area. Different grid divisions can be set on different layers to avoid conflicts.

[0062] Step 104: Based on the construction pile dataset and the divided building area model, conduct collapsibility analysis on the foundation pit area and the pile area to generate the collapsibility distribution data of the pile area.

[0063] In some embodiments, the above-mentioned execution entity can conduct collapsibility analysis on the foundation pit area and the pile area based on the above-mentioned construction pile dataset and the above-mentioned divided building area model to generate the collapsibility distribution data of the pile area.

[0064] In some optional implementation manners of some embodiments, for the above-mentioned execution entity to conduct collapsibility analysis on the foundation pit area and the pile area based on the above-mentioned construction pile dataset and the above-mentioned divided building area model to generate the collapsibility distribution data of the pile area, the following steps may be included:

[0065] First step: Using the above-mentioned construction pile dataset, conduct soil data interpolation on each grid corresponding to the foundation pit area and the pile area in the above-mentioned divided building area model to obtain the interpolated divided building area model. Among them, the soil data interpolation on each grid corresponding to the foundation pit area and the pile area in the above-mentioned divided building area model can be carried out through a preset interpolation algorithm to obtain the interpolated divided building area model. In addition, for the soil below the greening area and the area without a hard layer in the foundation pit area, since the infiltration volume of water will increase after rainfall, the soil moisture content can be increased according to a preset ratio after interpolation to make the interpolated data more conform to the actual scenario.

[0066] As an example, the interpolation algorithm can include but is not limited to at least one of the following: inverse distance weighted interpolation method, Kriging interpolation method, spline interpolation method, radial basis function interpolation method, etc.

[0067] Second step: Based on the above-mentioned interpolated divided building area model, conduct overall collapsibility prediction on the foundation pit area to generate an overall collapsibility prediction map. Among them, the overall collapsibility prediction on the foundation pit area can be carried out through a preset collapsibility prediction model to generate an overall collapsibility prediction map.

[0068] In practice, the collapsibility prediction model may include a three-dimensional feature extraction module and a fully connected module. Here, the three-dimensional feature extraction module may include multiple three-dimensional convolutional blocks. Each three-dimensional convolutional block may include a three-dimensional convolutional layer, a normalization layer, and a three-dimensional max pooling layer. Specifically, the convolutional kernel of the three-dimensional convolutional layer may be set to 3×3×3, and the output channels are 32. The pooling kernel of the three-dimensional max pooling layer may be set to 2×2×2, and the padding is 2. The fully connected module may include a flattening layer, a fully connected layer, and an output layer. The flattening layer is used to flatten the three-dimensional features into a one-dimensional vector. The fully connected layer may use the rectified linear unit activation function as the activation function, for example, there are 256 neurons. Additionally, first, the data within the foundation pit area can be processed. Here, it can be arranged according to the grids divided in the foundation pit area, and each grid corresponds to one piece of data to obtain three-dimensional feature data. Each piece of data may include: soil layer identifier, grid coordinates, soil moisture content, and soil horizontal stress value. Here, the soil layer identifier may be a numerical identifier. Then, the grid coordinates in the three-dimensional feature data can be normalized between [0, 1]. Finally, the soil moisture content and soil horizontal stress value in the three-dimensional feature data can be standardized to obtain the processed three-dimensional feature data. Thus, the processed three-dimensional feature data can be input into the collapsibility prediction model to generate an overall collapsibility prediction map.

[0069] Thirdly, based on the underground geological layer distribution data in the interpolated and divided building area model and the above-mentioned building area scene model, collapsibility analysis is carried out for each pile body area to generate a sequence of layered collapsibility curves, obtaining a set of sequences of layered collapsibility curves. Among them, each sequence of layered collapsibility curves in the above-mentioned set of sequences of layered collapsibility curves corresponds to a pile body area, and each layered collapsibility curve characterizes the collapsibility distribution characteristics of the soil body in the pile body area at the current moment. Secondly, the collapsibility analysis can be carried out through the following steps:

[0070] Firstly, the underground geological layer distribution data in the building area scene model can be stratified according to the divided grids to obtain the original stratified geological distribution data. Here, the original stratified geological distribution data may include multiple layers of geological data. Each layer of geological data can characterize the geological properties of the corresponding layer.

[0071] As an example, for a powdery clay layer with a depth of 3 - 10 meters, it can be divided into multiple layers according to the corresponding grids. If the grid height is 0.5 meters, then it can be divided into 14 layers.

[0072] Then, according to the layers in the above original stratified geological distribution data, the geological data of the pile body area detected by the ground penetrating radar can also be stratified to obtain the current stratified geological distribution data. Here, the number of layers in the current stratified geological distribution data can be the same as that in the original stratified geological distribution data. However, since the geological data measured currently is the data after the occurrence of collapsibility, the width of each layer in the current stratified geological distribution data is different from that in the original stratified geological distribution data. In addition, due to the different degrees of collapsibility at different positions, the widths of different positions in the same layer are also different.

[0073] As an example, as Figure 3 shown in the schematic diagram of geological structure stratification. Figure 3 The left figure in it can represent the result of stratifying the underground geological layer distribution data in the building area scene model. Figure 3 The right figure in it corresponds to the same number of layers and can represent the result of stratifying the geological data of the pile body area detected by the ground penetrating radar in the same way.

[0074] After that, in the above-mentioned interpolated and divided building area model, the data in the current stratified geological distribution data centered on the pile body and in the direction perpendicular to the line connecting the center of the pile body and the pile body can be extracted. The line connecting the pile bodies can be the line between two adjacent pile bodies. Finally, the data corresponding to the middle of each layer in the extracted data can be fitted into a stratified collapsibility curve to obtain a sequence of stratified collapsibility curves. Here, each stratified collapsibility curve in each sequence of stratified collapsibility curves is a curve with different depths arranged centered on the pile body, so as to characterize the collapsibility distribution characteristics in the direction perpendicular to the line connecting the pile bodies. The range of the stratified collapsibility curve can be within the grid division range corresponding to the pile body.

[0075] Fourthly, use the above sequence set of stratified collapsibility curves to adjust the collapsibility degree of the above overall collapsibility prediction map to obtain the collapsibility distribution data of the pile body area. Among them, the curvature of each coordinate position of the stratified collapsibility curve can be extracted. Then, according to the pre-set corresponding relationship between the curvature and the collapsibility degree adjustment ratio, the collapsibility degree adjustment ratio of each coordinate is determined. Finally, the collapsibility degree adjustment ratio can be multiplied by the collapsibility degree at the corresponding coordinate position in the overall collapsibility prediction map to obtain the collapsibility distribution data of the pile body area. Here, the collapsibility distribution data of the pile body area can be two-dimensional data, that is, the sum of the collapsibility degrees in the vertical direction corresponding to each coordinate position in the collapsibility distribution data of the pile body area is used as the collapsibility degree of this coordinate position.

[0076] As an example, the curvature of a certain coordinate point on the stratified collapsibility curve is 0.02. The corresponding collapsibility degree adjustment ratio is 1.1. Thus, the collapsibility degree at the corresponding coordinate position in the overall collapsibility prediction map can be adjusted.

[0077] In practice, in order to further improve the recognition accuracy of the collapsibility situation in the pile body area, thus, first, the collapsibility degree of the overall data in the foundation pit area is predicted. Then, considering the coupling in the pile body area during prediction and the difficulty in determining a high accuracy. Therefore, the soil in the pile body area is meshed and geologically stratified again. Thus, the collapsibility changes of the geological data before and after can be compared, and the corresponding stratified collapsibility curve is established to determine the collapsibility degree of the area where the pile body is located at a fine granularity. Thereby, by further adjusting the collapsibility degree at the corresponding coordinate positions in the overall collapsibility prediction map, the accuracy of the collapsibility distribution data in the pile body area is improved.

[0078] Step 105, in response to determining that the collapsibility distribution data in the pile body area meets the preset warning conditions, generate a collapsibility warning heat map in the divided building area model according to the collapsibility distribution data in the pile body area, and send the collapsibility warning heat map to the warning terminal for warning operations.

[0079] In some embodiments, the above-mentioned execution subject may, in response to determining that the collapsibility distribution data in the pile body area meets the preset warning conditions, generate a collapsibility warning heat map in the divided building area model according to the collapsibility distribution data in the pile body area, and send the collapsibility warning heat map to the warning terminal for warning operations.

[0080] In practice, for the water level data in the construction pile body data, when it is characterized that the corresponding groundwater level rises to within a range less than 1 meter from the pile bottom, the pre-laid foundation pit dewatering well can be opened for drainage. In addition, if it is detected that there is a horizontal displacement of the retaining pile exceeding the preset displacement threshold in the retaining pile displacement detection information, or the pile body detection information corresponding to the retaining pile includes a pile body detection mark indicating abnormality, the corresponding retaining pile serial number or mark can be used as a warning message for warning operations. In addition, if it is detected that there is a geological fault in the current stratified geological distribution data and the height of the fault exceeds the preset threshold, warning operations can also be carried out.

[0081] In some optional implementation manners of some embodiments, the above-mentioned execution subject generating a collapsibility warning heat map in the divided building area model according to the collapsibility distribution data in the pile body area may include the following steps:

[0082] First step, perform data conversion on the collapsibility distribution data in the pile body area to generate a sequence of collapsibility coordinate information. Among them, data conversion can be to convert the collapsibility distribution data in the pile body area into data in a target format. For example, convert it into a sequence of collapsibility coordinate information in csv format.

[0083] In the second step, data interpolation is performed on the above collapsible coordinate information sequence to obtain the interpolated collapsible coordinate information sequence. Among them, the cubic spline interpolation algorithm can be used to perform data interpolation on the above collapsible coordinate information sequence to obtain the interpolated collapsible coordinate information sequence.

[0084] In the third step, the above interpolated collapsible coordinate information sequence is rendered into the above partitioned building area model according to the coordinate order to generate a collapsible warning heat map. Among them, the above interpolated collapsible coordinate information sequence can be rendered into the above partitioned building area model according to the coordinate order through preset visualization code to generate a collapsible warning heat map. The visualization code can include a preset function and parameters for drawing the heat map.

[0085] As an example, such as Figure 4 the shown collapsible warning heat map. The scale on the right vertical axis represents the degree of collapsibility. The darker the color, the higher the collapsibility. The scale on the horizontal axis and the scale on the left vertical axis can represent the grid coordinates.

[0086] The above-mentioned various embodiments of the present disclosure have the following beneficial effects: Through the monitoring and early warning method for building construction foundation pits and pile bodies in some embodiments of the present disclosure, it is possible to timely monitor and early warn of the subsidence in the areas where the foundation pits and pile bodies are located. Specifically, the reasons for the difficulty in timely monitoring and early warning of the subsidence in the areas where the foundation pits and pile bodies are located are as follows: When the construction area is large, it requires a large amount of labor costs, and it is difficult to uniformly process a large amount of collected data. Based on this, the monitoring and early warning method for building construction foundation pits and pile bodies in some embodiments of the present disclosure, in response to the completion of building construction, establishes a building area scene model through the geological data collected during building construction and a preset building construction simulation model. Among them, in the ground area of the above-mentioned building area scene model, there are marked: foundation pit area, greening area, and other areas, and in the above-mentioned building area scene model, there are set foundation pit information, pile body information, and underground geological layer distribution data corresponding to the foundation pit area. Considering that it is difficult to uniformly process the data in the construction area, a building area scene model is thus established. This enables various collected data to be summarized based on the building area scene model, facilitating unified processing. Then, use the pre-installed construction monitoring probe to capture images of the local construction area, and collect the construction pile body data set through the preset data acquisition device component. Among them, the above-mentioned local construction area image is used to adjust the acquisition frequency of the data acquisition device component, and each construction pile body data in the construction pile body data set includes: pile body serial number, pile body coordinates, pile body type identifier, and pile body description information, and each construction pile body data corresponds to a pile body. Here, in order to reduce labor costs, the construction monitoring probe and the data acquisition device component are used to assist in data collection. After that, according to the above-mentioned local construction area image and the above-mentioned building area scene model, local grid division is performed on the underground geological layer of the above-mentioned building area scene model to obtain the divided building area model. Among them, the local grid division is centered on the foundation pit area, and the above-mentioned local construction area image is also used to adjust the grid division range. Here, through local grid division, it is convenient to quantify the data of the soil body under the construction area, so as to facilitate the analysis of the subsidence degree. Then, based on the above-mentioned construction pile body data set and the above-mentioned divided building area model, subsidence analysis is performed on the foundation pit area and the pile body area to generate the subsidence distribution data of the pile body area. Here, through subsidence analysis, the subsidence distribution data of all areas within the building construction area can be uniformly generated. Thus, it is convenient to conduct subsidence monitoring and early warning. Finally, in response to determining that the subsidence distribution data of the above-mentioned pile body area meets the preset early warning conditions, according to the above-mentioned subsidence distribution data of the pile body area, a subsidence early warning heat map is generated in the above-mentioned divided building area model, and the above-mentioned subsidence early warning heat map is sent to the early warning terminal for early warning operations. Thus, it is possible to timely monitor and early warn of the subsidence in the areas where the foundation pits and pile bodies are located.

[0087] Further reference Figure 5, as an implementation of the methods shown in the above figures, the present disclosure provides some embodiments of a monitoring and warning device for a foundation pit and a pile body in building construction. These device embodiments correspond to Figure 1 the method embodiments shown, and the monitoring and warning device for a foundation pit and a pile body in building construction can be specifically applied to various electronic devices.

[0088] As Figure 5 shown, a monitoring and warning device 500 for a foundation pit and a pile body in some embodiments includes: a building unit 501, a collection unit 502, a grid division unit 503, a collapsibility analysis unit 504, and a generation and warning unit 505. Among them, the building unit 501 is configured to, in response to the completion of building construction, establish a building area scene model through building construction geological acquisition data and a preset building construction simulation model. Among them, in the ground area of the above building area scene model, a foundation pit area, a greening area, and other areas are marked. In the above building area scene model, foundation pit information, pile body information, and underground geological layer distribution data corresponding to the foundation pit area are set; the collection unit 502 is configured to use a pre-installed construction monitoring probe to capture images of a local construction area, and collect a construction pile body data set through a preset data collection device component. Among them, the above local construction area image is used to adjust the collection frequency of the data collection device component. Each construction pile body data in the construction pile body data set includes: a pile body serial number, a pile body coordinate, a pile body type identifier, and a pile body description information, and each construction pile body data corresponds to a pile body; the grid division unit 503 is configured to perform local grid division on the underground geological layer of the above building area scene model according to the above local construction area image and the above building area scene model to obtain a divided building area model. Among them, the local grid division is centered on the foundation pit area, and the above local construction area image is also used to adjust the grid division range; the collapsibility analysis unit 504 is configured to perform collapsibility analysis on the foundation pit area and the pile body area based on the above construction pile body data set and the above divided building area model to generate pile body area collapsibility distribution data; the generation and warning unit 505 is configured to, in response to determining that the above pile body area collapsibility distribution data meets a preset warning condition, generate a collapsibility warning heat map in the above divided building area model according to the above pile body area collapsibility distribution data, and send the above collapsibility warning heat map to a warning terminal for warning operations.

[0089] It can be understood that the various units described in the monitoring and warning device 500 for a foundation pit and a pile body in building construction correspond to Figure 1 each step in the method described with reference to. Thus, the operations, features, and beneficial effects described above for the method also apply to the monitoring and warning device 500 for a foundation pit and a pile body in building construction and the units included therein, and will not be repeated here.

[0090] Reference is now made to Figure 6 , which shows a schematic structural diagram of an electronic device (such as a computing device) suitable for implementing some embodiments of the present disclosure. Figure 6 The illustrated electronic device is merely an example and should not impose any limitations on the functions and usage scope of the embodiments of the present disclosure. As Figure 6 shown, the computer device includes a processor, a memory, and a network interface connected via a system bus. Among them, the memory may include a non-volatile storage medium and an internal memory. The non-volatile storage medium can store an operating system and computer programs. The computer programs include program instructions, and when the program instructions are executed, the processor can execute any of the above methods. The processor is used to provide computing and control capabilities to support the operation of the entire computer device. The internal memory provides an environment for the operation of the computer programs in the non-volatile storage medium. When the computer programs are executed by the processor, the processor can execute any of the above methods. The network interface is used for network communication, such as sending assigned tasks, etc. Those skilled in the art can understand that Figure 6 the structure shown in

[0091] is merely a block diagram of some structures related to the solution of the present disclosure and does not constitute a limitation on the computer device to which the solution of the present disclosure is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0092] Among them, in one embodiment, the above-mentioned processor is used to run a computer program stored in the memory to implement the following steps: in response to the completion of building construction, establish a building area scene model through building construction geological acquisition data and a preset building construction simulation model. Among them, in the ground area of the above-mentioned building area scene model, there are marked: foundation pit area, greening area, and other areas. In the above-mentioned building area scene model, there are set foundation pit information, pile body information, and underground geological layer distribution data corresponding to the foundation pit area; use a pre-installed construction monitoring probe to capture images of the local construction area, and collect a construction pile body data set through a preset data acquisition device component. Among them, the above-mentioned local construction area image is used to adjust the acquisition frequency of the data acquisition device component. Each construction pile body data in the construction pile body data set includes: pile body serial number, pile body coordinates, pile body type identifier, and pile body description information. Each construction pile body data corresponds to a pile body; according to the above-mentioned local construction area image and the above-mentioned building area scene model, perform local grid division on the underground geological layer of the above-mentioned building area scene model to obtain a divided building area model. Among them, the local grid division is centered on the foundation pit area, and the above-mentioned local construction area image is also used to adjust the grid division range; based on the above-mentioned construction pile body data set and the above-mentioned divided building area model, perform collapsibility analysis on the foundation pit area and the pile body area to generate collapsibility distribution data of the pile body area; in response to determining that the above-mentioned collapsibility distribution data of the pile body area meets the preset warning conditions, generate a collapsibility warning heat map in the above-mentioned divided building area model according to the above-mentioned collapsibility distribution data of the pile body area, and send the above-mentioned collapsibility warning heat map to a warning terminal for warning operations.

[0093] The embodiments of the present disclosure also provide a computer-readable storage medium. A computer program is stored on the above-mentioned computer-readable storage medium. The above-mentioned computer program includes program instructions. The method implemented when the above-mentioned program instructions are executed can refer to the various embodiments of the above-mentioned method of the present disclosure.

[0094] Among them, the above-mentioned computer-readable storage medium may be an internal storage unit of the above-mentioned computer device in the foregoing embodiment, such as the hard disk or memory of the above-mentioned computer device. The above-mentioned computer-readable storage medium may also be an external storage device of the above-mentioned computer device, such as a plug-in hard disk equipped on the above-mentioned computer device, a smart media card (SmartMedia Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), etc.

[0095] It should be noted that, in this text, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, such that a process, method, article or system comprising a series of elements not only includes those elements but also includes other elements not expressly listed, or further includes elements inherent to such process, method, article or system. Without further limitation, an element defined by the statement "comprising one..." does not exclude the existence of additional identical elements in the process, method, article or system comprising such element.

[0096] The above description is only some preferred embodiments of the present disclosure and an explanation of the applied technical principles. Those skilled in the art should understand that the scope of the invention involved in the embodiments of the present disclosure is not limited to the technical solutions formed by the specific combination of the above technical features, but should also cover other technical solutions formed by any combination of the above technical features or their equivalent features without departing from the above inventive concept. For example, the technical solutions formed by mutually replacing the above features with the (but not limited to) technical features having similar functions disclosed in the embodiments of the present disclosure.

Claims

1. A monitoring and early warning method for building construction foundation pits and pile bodies, characterized in that, Including: In response to the completion of building construction, a building area scene model is established through building construction geological acquisition data and a preset building construction simulation model. Among them, in the ground area of the building area scene model, there are marked: foundation pit area, pile body area, greening area, and other areas. In the building area scene model, there are set foundation pit information, pile body information, and underground geological layer distribution data corresponding to the foundation pit area; The construction monitoring probes pre-erected are used to capture images of the local construction area, and a construction pile body data set is collected through a preset data acquisition device component. Among them, the local construction area image is used to adjust the acquisition frequency of the data acquisition device component. Each construction pile body data in the construction pile body data set includes: pile body serial number, pile body coordinates, pile body type identifier, and pile body description information. Each construction pile body data corresponds to a pile body; According to the local construction area image and the building area scene model, local grid division is performed on the underground geological layer of the building area scene model to obtain the divided building area model. Among them, the local grid division is centered on the foundation pit area, and the local construction area image is also used to adjust the grid division range; Based on the construction pile body data set and the divided building area model, collapsibility analysis is performed on the foundation pit area and the pile body area to generate collapsibility distribution data of the pile body area; In response to determining that the collapsibility distribution data of the pile body area meets the preset warning conditions, according to the collapsibility distribution data of the pile body area, a collapsibility warning heat map is generated in the divided building area model, and the collapsibility warning heat map is sent to the warning terminal for warning operations; The step of performing local grid division on the underground geological layer of the building area scene model according to the local construction area image and the building area scene model to obtain the divided building area model includes: Determining the grid size corresponding to the foundation pit area and the pile body area in the building area scene model according to the rainfall level identifier corresponding to the local construction area image; Determining the grid division range corresponding to the foundation pit area and the pile body area in the building area scene model according to the rainfall level identifier corresponding to the local construction area image; Using the grid size and grid division range corresponding to the foundation pit area and the pile body area, local grid division is performed on the underground geological layer of the building area scene model to obtain the divided building area model; The step of performing collapsibility analysis on the foundation pit area and the pile body area based on the construction pile body data set and the divided building area model to generate collapsibility distribution data of the pile body area includes: Using the construction pile body data set, performing soil body data interpolation on each grid corresponding to the foundation pit area and the pile body area in the divided building area model to obtain the interpolated divided building area model; Based on the interpolated and partitioned building area model, the overall collapsibility prediction of the foundation pit area is carried out to generate an overall collapsibility prediction map. Among them, through a preset collapsibility prediction model, the overall collapsibility prediction of the foundation pit area is carried out to generate an overall collapsibility prediction map. The collapsibility prediction model includes a three-dimensional feature extraction module and a fully connected module. The three-dimensional feature extraction module includes multiple three-dimensional convolutional blocks, and the fully connected module includes a flattening layer, a fully connected layer, and an output layer; Based on the interpolated and partitioned building area model and the underground geological layer distribution data in the building area scene model, the collapsibility analysis of each pile body area is carried out to generate a sequence of layered collapsibility curves, and a set of sequences of layered collapsibility curves is obtained. Among them, each sequence of layered collapsibility curves in the set of sequences of layered collapsibility curves corresponds to a pile body area, and each layered collapsibility curve characterizes the collapsibility distribution characteristics of the soil body in the pile body area at the current moment; The overall collapsibility prediction map is adjusted for the collapsibility degree by using the set of sequences of layered collapsibility curves to obtain the collapsibility distribution data of the pile body area.

2. The method according to claim 1, wherein, Among them, The building construction geological acquisition data is used to characterize the underground geological distribution of the construction area. By using the building construction geological acquisition data and a preset building construction simulation model, a building area scene model is established, including: Converting the preset building construction simulation model to the pre-constructed building area coordinate system, and converting the building construction geological acquisition data to the building area coordinate system according to the corresponding coordinates to obtain an initial building area scene model; Marking the corresponding ground area in the initial building area scene model according to the preset ground construction area data, and marking the corresponding foundation pit information and pile body information in the initial building area scene model according to the preset foundation pit pile body construction data to obtain the building area scene model.

3. The method according to claim 1, wherein The data acquisition equipment component includes at least one of the following devices: a pore water pressure gauge group, a ground penetrating radar, a total station, a soil moisture sensor group, and a micro-earth pressure gauge group. Among them, the pore water pressure gauge, the soil moisture sensor, and the micro-earth pressure gauge are buried in the soil body of the foundation pit area. By using the preset data acquisition equipment component, a construction pile body data set is collected, including: Identifying rainfall in the construction local area image to generate a rainfall level identifier, where the rainfall level identifier is used to characterize the rainfall ponding degree of the local construction area; In response to determining rainfall in the building construction area, adjusting the acquisition frequency of the data acquisition equipment component according to the rainfall level identifier; Determining the current monitoring time period according to the building construction completion time point and the current time point; In response to determining that the current monitoring time period is within the first preset monitoring time period, using the ground penetrating radar to detect the integrity of each pile body in the foundation pit area to obtain a set of pile body integrity detection information; Using the total station to detect the top of each pile body in the foundation pit area to obtain a set of pile body displacement detection information; Taking the pile body integrity detection information and the pile body displacement detection information corresponding to the same pile body in the set of pile body integrity detection information and the set of pile body displacement detection information as construction pile body data to obtain a construction pile body data set.

4. The method according to claim 3, wherein Taking images of a local construction area using pre-installed construction monitoring probes, and collecting a construction pile body data set through a preset data acquisition device assembly, further includes: In response to determining that the current monitoring time period is within a second preset monitoring time period, using the pore water pressure gauge group to detect the water level data of the foundation pit area to obtain a water level data set; Using the soil moisture sensor group to detect the soil moisture content of the foundation pit area to obtain a soil moisture content set; Using the micro earth pressure gauge group to detect the horizontal soil stress value between the corner piles and the retaining piles in the foundation pit area to obtain a set of horizontal soil stress values; Adding the water level data set, the soil moisture content set, and the set of horizontal soil stress values to the construction pile body data set.

5. The method according to claim 4, characterized in that, Generating a settlement warning heat map in the divided building area model according to the settlement distribution data of the pile body area, includes: Performing data conversion on the settlement distribution data of the pile body area to generate a sequence of settlement coordinate information; Performing data interpolation on the sequence of settlement coordinate information to obtain an interpolated sequence of settlement coordinate information; Rendering the interpolated sequence of settlement coordinate information into the divided building area model according to the coordinate order to generate a settlement warning heat map.

6. A monitoring and warning device for a building construction foundation pit and pile body, includes: A building unit, configured to, in response to the completion of building construction, establish a building area scene model through building construction geological acquisition data and a preset building construction simulation model, wherein in the ground area of the building area scene model, there are marked: a foundation pit area, a pile body area, a greening area, and other areas, and in the building area scene model, there are set foundation pit information, pile body information, and underground geological layer distribution data corresponding to the foundation pit area; A collection unit, configured to take images of a local construction area using pre-installed construction monitoring probes, and collect a construction pile body data set through a preset data acquisition device assembly, wherein the local construction area image is used to adjust the collection frequency of the data acquisition device assembly, and each construction pile body data in the construction pile body data set includes: a pile body serial number, a pile body coordinate, a pile body type identifier, and pile body description information, and each construction pile body data corresponds to a pile body; A grid division unit, configured to perform local grid division on the underground geological layer of the building area scene model according to the local construction area image and the building area scene model to obtain a divided building area model, wherein the local grid division is centered on the foundation pit area, and the local construction area image is also used to adjust the grid division range; A settlement analysis unit, configured to perform settlement analysis on the foundation pit area and the pile body area based on the construction pile body data set and the divided building area model to generate settlement distribution data of the pile body area; A generation and warning unit, configured to, in response to determining that the settlement distribution data of the pile body area meets a preset warning condition, generate a settlement warning heat map in the divided building area model according to the settlement distribution data of the pile body area, and send the settlement warning heat map to a warning terminal for warning operations; Performing local grid division on the underground geological layer of the building area scene model according to the construction local area image and the building area scene model, to obtain the divided building area model, including: Determining the grid sizes corresponding to the foundation pit area and the pile area in the building area scene model according to the rainfall level identifier corresponding to the construction local area image; Determining the grid division ranges corresponding to the foundation pit area and the pile area in the building area scene model according to the rainfall level identifier corresponding to the construction local area image; Using the grid sizes and grid division ranges corresponding to the foundation pit area and the pile area to perform local grid division on the underground geological layer of the building area scene model, to obtain the divided building area model; Performing collapsibility analysis on the foundation pit area and the pile area based on the construction pile data set and the divided building area model, to generate collapsibility distribution data of the pile area, including: Using the construction pile data set to perform soil data interpolation on each grid corresponding to the foundation pit area and the pile area in the divided building area model, to obtain the interpolated divided building area model; Performing overall collapsibility prediction on the foundation pit area based on the interpolated divided building area model, to generate an overall collapsibility prediction map, wherein, through a preset collapsibility prediction model, performing overall collapsibility prediction on the foundation pit area to generate an overall collapsibility prediction map, the collapsibility prediction model includes a three-dimensional feature extraction module and a fully connected module, the three-dimensional feature extraction module includes a plurality of three-dimensional convolutional blocks, and the fully connected module includes a flattening layer, a fully connected layer and an output layer; Performing collapsibility analysis on each pile area based on the interpolated divided building area model and the underground geological layer distribution data in the building area scene model to generate a sequence of layer-by-layer collapsibility curves, to obtain a set of sequences of layer-by-layer collapsibility curves, wherein each sequence of layer-by-layer collapsibility curves in the set of sequences of layer-by-layer collapsibility curves corresponds to a pile area, and each layer-by-layer collapsibility curve characterizes the collapsibility distribution characteristics of the soil body in the pile area at the current moment; Using the set of sequences of layer-by-layer collapsibility curves to adjust the collapsibility degree of the overall collapsibility prediction map, to obtain the collapsibility distribution data of the pile area.

7. An electronic device, including: One or more processors; A storage device, on which one or more programs are stored, When the one or more programs are executed by the one or more processors, enabling the one or more processors to implement the method as described in any one of claims 1-5.

8. A computer-readable medium having a computer program stored thereon, wherein, The program, when executed by the processor, implements the method as described in any one of claims 1-5.

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