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

Abstract

The embodiment of the invention discloses a monitoring and early warning method and device for a building construction foundation pit and a pile body. A specific embodiment of the method comprises the steps of establishing a building area scene model; a construction monitoring probe erected in advance is used for shooting a construction local area image, and a construction pile body data set is collected through a preset data collection equipment assembly; according to the construction local area image and the building area scene model, carrying out local grid division on an underground geological map layer of the building area scene model to obtain a divided building area model; based on the construction pile body data set and the divided building area model, performing collapsibility analysis on the foundation pit area and the pile body area to generate pile body area collapsibility distribution data; and generating a collapse early warning thermodynamic diagram in the divided building area model, and sending the collapse early warning thermodynamic diagram to an early warning terminal for early warning operation. According to the embodiment, collapse monitoring and early warning can be carried out in time.

Description

Technical Field

[0001] Embodiments of the present disclosure relate to the fields of computer technology and construction monitoring and early warning, and particularly 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. At present, the main technological methods for treating collapsible loess are 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: When the construction area is large, it requires a large amount of labor cost. At the same time, 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.

[0004] The above information disclosed in this background art section is only used to enhance the understanding of the background of the inventive concept, and therefore, it may include information that does not form the prior art known to those of ordinary skill in the art. Summary of the Invention

[0005] This section of the present disclosure is used to briefly introduce concepts that will be described in detail in the following detailed implementation section. This section 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.

[0006] 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.

[0007] 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 building area scene model, there are marked: a foundation pit area, a pile body area, a greening area, and other areas. In the above 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 pre-installed construction monitoring probes to capture images of a local construction area, and through a preset data acquisition device component, collecting a construction pile body data set. Among them, the above 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 local construction area image and the above building area scene model, performing local grid division on the underground geological layer of 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. The above local construction area image is also used to adjust the grid division range; based on the above construction pile body data set and the above 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 collapsibility distribution data of the above pile body area meets a preset early warning condition, according to the collapsibility distribution data of the above pile body area, generating a collapsibility early warning heat map in the above divided building area model, and sending the above collapsibility early warning heat map to an early warning terminal for early warning operations.

[0008] 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. Among them, in the ground area of the above building area scene model, there are marked: a foundation pit area, a pile body area, a greening area, and other areas. In the above 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 through a preset data acquisition device component, collect a construction pile body data set. Among them, the above 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; a grid division unit configured to, according to the above local construction area image and the above building area scene model, perform local grid division on the underground geological layer of the above building area scene model to obtain a divided building area model. Among them, the local grid division is performed with the foundation pit area as the center. The above local construction area image is also used to adjust the grid division range; a collapsibility analysis unit configured to, based on the above construction pile body data set and the above divided building area model, perform collapsibility analysis on the foundation pit area and the pile body area to generate pile body area collapsibility distribution data; a generation and warning unit 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.

[0009] 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 above first aspect.

[0010] Fourth aspect, some embodiments of the present disclosure provide a computer-readable medium on which a computer program is stored. Among them, when the program is executed by a processor, it implements the method described in any implementation manner of the above first aspect.

[0011] 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 piles according to some embodiments of the present disclosure, it is possible to timely monitor and early warn of the collapsibility of the area where the foundation pit and piles are located. Specifically, the reasons for the difficulty in timely monitoring and early warning of the collapsibility of the area where the foundation pit and piles are located are as follows: When the construction area is large, it requires a large amount of labor cost, 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 piles according to 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 all 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 component. Among them, the above-mentioned 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: 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 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 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 area where the foundation pit and piles are located. Description of the Drawings

[0012] In combination with the accompanying drawings and with reference to the following specific embodiments, the above and other features, advantages, and aspects of the various 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.

[0013] Figure 1 is a flowchart of some embodiments of a monitoring and early warning method for building construction foundation pits and pile bodies according to the present disclosure; Figure 2 is a schematic diagram of the geological distribution in the pile body area; Figure 3 is a schematic diagram of the geological structure stratification; Figure 4 is a heat map for collapsibility early warning; Figure 5 is a schematic structural diagram of some embodiments of a monitoring and early warning device for building construction foundation pits and pile bodies according to the present disclosure; Figure 6 is a schematic structural diagram of an electronic device suitable for implementing some embodiments of the present disclosure. Specific Embodiments

[0014] 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.

[0015] 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.

[0016] 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 interdependence relationship of the functions performed by these devices, modules, or units.

[0017] 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".

[0018] The names of the messages or information exchanged between multiple devices in the embodiments of the present disclosure are only for illustrative purposes and are not used to limit the scope of these messages or information. The present disclosure will be described in detail below with reference to the accompanying drawings and in conjunction with embodiments.

[0019] Figure 1 Flow 100 of some embodiments of a monitoring and early warning method for a foundation pit and pile body in building construction according to the present disclosure is shown. The monitoring and early warning method for a foundation pit and pile body in building construction includes the following steps: 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.

[0020] In some embodiments, the execution subject (e.g., an electronic device) of the monitoring and early warning method for a foundation pit and pile body in building construction 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, in the above building area scene model, the ground area is marked with: a foundation pit area, a pile body area, a pile body area, a greening area, and other areas. The above 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 the 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.

[0021] 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 for providing distributed services, or can be implemented as a single software or software module. No specific limitation is made here.

[0022] In some alternative implementation manners of some embodiments, the above 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: First step, convert the preset building construction simulation model into the pre-constructed building area coordinate system, and convert the above-mentioned building construction geological acquisition data to the above-mentioned building area coordinate system according to the corresponding coordinates, so as 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, so as to facilitate the subsequent determination of the degree of soil collapsibility.

[0023] 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, so as 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 the building construction. It can include the distribution coordinates of each area. For example, it includes the building area, the foundation pit area, the greening area or other areas, etc. Other areas can be the road area. Here, considering that the seepage degree of surface water in different areas is different (for example, the water volume in the greening area is relatively large and the seepage is more), different area identifiers are introduced, so as to be used as a reference factor for subsequent collapsibility 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 the pile body serial number, the pile body coordinates and the pile body depth.

[0024] 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.

[0025] In some embodiments, the above-mentioned execution subject can 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. Among them, the above-mentioned local construction area image can be used to adjust the acquisition frequency of the data acquisition device components. Each construction pile body data in the construction pile body data set can include: the pile body serial number, the pile body coordinates, the pile body type identifier and the pile body description information, and each construction pile body data corresponds to a pile body. The pile body type identifier can represent the construction type of the pile body, for example, rammed earth compaction pile, deep mixing pile, etc. The pile body description information can include the pile body attributes. For example, the pile body attributes can include side pile or corner pile, etc.

[0026] In some alternative implementations of some embodiments, the data acquisition device component may include, but is not limited to, at least one of the following devices: a pore water pressure gauge group, a ground penetrating radar, a total station, a soil moisture content sensor group, and a micro earth pressure gauge group. Among them, the pore water pressure gauges, soil moisture sensors, and micro earth pressure gauges are buried in the soil body of the foundation pit area.

[0027] The above-mentioned execution entity collects a construction pile body data set through a preset data acquisition device component, which may include the following steps: 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 characterize 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 a reduced effect 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.

[0028] 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, which consists of three convolutional layers and pooling layers. The feature classifier can be a fully connected neural network, which consists 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, namely light rain, moderate rain, heavy rain, and rainstorm.

[0029] 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.

[0030] As an example, the pre-set acquisition frequency can be once every 3 days. The acquisition frequency corresponding to the rainfall level identifier representing rainstorm can be once every 5 hours.

[0031] Third step, determine the current monitoring time period according to the building construction completion time point and the current time point. Among them, multiple monitoring time periods can be pre-divided according to the building construction completion time point. For example, within one week after construction completion 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).

[0032] Fourthly, in response to determining that the 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 construction area, and obtain a pile body integrity detection information set. Among them, a 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 construction area, and obtain a pile body integrity detection information set. Here, the pile body integrity detection is used to detect abnormal conditions such as "necking down" and "broken piles" of the pile bodies.

[0033] For example, if an abnormal condition of "broken pile" is detected in a certain pile body, the pile body detection identifier representing the abnormality can be determined as the pile body integrity detection information.

[0034] In practice, due to the large void ratio, low water content, and relatively loose structure of the shallow collapsible soil layer, it is prone to settlement when encountering water seepage. 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 (for example, within 10 meters) within a certain range of the pile body, and obtain geological structure data. For example, different depths and corresponding geological attributes. 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.

[0035] Fifthly, use the above total station to detect the pile tops of each pile body in the foundation pit area, and obtain a pile body displacement detection information set. 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 pile body displacement detection information set. Here, the pile body displacement detection information can include the horizontal displacement value of the pile top of the pile body.

[0036] Sixthly, use the pile body integrity detection information and the pile body displacement detection information corresponding to the same pile body in the above pile body integrity detection information set and the above pile body displacement detection information set as construction pile body data, and obtain a construction pile body data set.

[0037] Optionally, the above execution subject uses the pre-installed construction monitoring probe to capture images of the local construction area, and through the preset data acquisition device components, collects the construction pile body data set, which may further include the following steps: First, in response to determining that the current monitoring time period is within the second preset monitoring time period, use the above pore water pressure gauge group to detect the water level data of the foundation pit area, and obtain a 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 pore water pressure gauge corresponds to a pile body.

[0038] In the second step, use the above soil moisture sensors to detect the soil moisture content in the foundation pit area, and obtain a set of soil moisture contents. Each soil moisture sensor can correspond to a pile body.

[0039] In the third step, use the above micro earth pressure gauges to detect the horizontal soil stress values between the corner piles and the retaining piles in the foundation pit area, and obtain a set of horizontal soil stress values. The micro earth pressure gauges can be buried between two pile bodies.

[0040] In the fourth step, 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 body data set.

[0041] As an example, such as Figure 2 the schematic diagram of the geological distribution of the pile body area shown. Figure 2 The left figure in [Figure Reference] can be a distribution map established using the underground geological layer distribution data to characterize the geological distribution of the area where the pile body 201 is located after construction. Figure 2 The right figure in [Figure Reference] can be a distribution map established by combining the current geological data of the area where the pile body 201 is located determined by ground penetrating radar and borehole sampling to characterize the situation of geological subsidence after construction for a period of time.

[0042] Step 103: According to the construction local 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.

[0043] In some embodiments, the above execution entity can perform local grid division on the underground geological layer of the above building area scene model according to the above construction local 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 construction local area image is also used to adjust the grid division range.

[0044] In some optional implementation manners of some embodiments, the above execution entity performs local grid division on the underground geological layer of the above building area scene model according to the above construction local area image and the above building area scene model to obtain the divided building area model, which may include the following steps: In the first step, according to the rainfall level identifier corresponding to the above construction local area image, determine the grid size corresponding to the foundation pit area and the pile body in the above building area scene model. Among them, the current grid ratio can be determined according to the pre-set corresponding relationship between the rainfall level 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 and the local grid size of each pile body are different.

[0045] In practice, considering that the seepage volume increases 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 subsequent richness of soil characteristics, thereby improving the accuracy of soil collapsibility analysis.

[0046] In the second step, according to the rainfall level identifier corresponding to the above-mentioned construction local area image, determine the grid division range of the corresponding foundation pit area and pile body in the above-mentioned building area scene model. Among them, the current grid range ratio can be determined according to the pre-set corresponding relationship between the rainfall level identifier and the grid division range. For example, the current grid range ratio can be 1.2. Then, the product of the foundation 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 body are different.

[0047] 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 collapsibility on the pile body, the grid division range can be expanded. Thus, for the analysis of each pile body, related features can be increased, thereby improving the accuracy of collapsibility analysis.

[0048] In the third step, use the grid size and grid division range 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 to obtain the divided building area model. Among them, the local grid division can be centered on each pile body, within the corresponding grid division range, and perform local grid division according to the corresponding grid size to obtain the divided building area model.

[0049] In addition, the overall grid division of the foundation pit area can also be carried out. Different grid divisions can be set on different layers to avoid conflicts.

[0050] Step 104, based on the construction pile body data set and the divided building area model, perform collapsibility analysis on the foundation pit area and the pile body area to generate the collapsibility distribution data of the pile body area.

[0051] In some embodiments, the above-mentioned execution subject can perform collapsibility analysis on the foundation pit area and the pile body area based on the above-mentioned construction pile body data set and the above-mentioned divided building area model to generate the collapsibility distribution data of the pile body area.

[0052] In some optional implementation manners of some embodiments, the above-mentioned execution subject performs collapsibility analysis on the foundation pit area and the pile body area based on the above-mentioned construction pile body data set and the above-mentioned divided building area model to generate the collapsibility distribution data of the pile body area, which may include the following steps: First step, using the above-mentioned construction pile body dataset, perform soil data interpolation on each grid corresponding to the foundation pit area and the pile body area in the above-mentioned divided building area model to obtain the interpolated divided building area model. Among them, the soil data interpolation can be performed on each grid corresponding to the foundation pit area and the pile body area in the above-mentioned divided building area model 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 will increase after rainfall, therefore, after interpolation, the soil moisture content can be increased according to a preset ratio to make the interpolated data more conform to the actual scenario.

[0053] 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.

[0054] Second step, based on the above-mentioned interpolated divided building area model, perform overall collapsibility prediction on the foundation pit area to generate an overall collapsibility prediction map. Among them, the overall collapsibility prediction can be performed on the foundation pit area through a preset collapsibility prediction model to generate an overall collapsibility prediction map.

[0055] In practice, the collapsibility prediction model can include a three-dimensional feature extraction module and a fully connected module. Here, the three-dimensional feature extraction module can include multiple three-dimensional convolutional blocks. Each three-dimensional convolutional block can 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 can be set to 3×3×3, and the output channels are 32. The pooling kernel of the three-dimensional max pooling layer can be set to 2×2×2, and the padding is 2. The fully connected module can 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 can use the rectified linear unit activation function as the activation function, for example, there are 256 neurons. In addition, first, the data in 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 a piece of data to obtain three-dimensional feature data. Each piece of data can include: soil layer identifier, grid coordinates, soil moisture content, and soil horizontal stress value. Here, the soil layer identifier can 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.

[0056] In the third step, based on the distribution data of the underground geological layers in the above-mentioned interpolated and partitioned building area model and the above-mentioned building area scene model, a collapsibility analysis is carried out for each pile body area 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 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: First of all, the distribution data of the underground geological layers in the building area scene model can be stratified according to the divided grid 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 attributes of the corresponding level.

[0057] As an example, for the powdery clay layer with a depth of 3 - 10 meters, it can be divided into multiple levels according to the corresponding grid. If the grid height is 0.5 meters, then it can be divided into 14 levels.

[0058] Then, according to the levels in the above-mentioned original stratified geological distribution data, the geological data of the pile body area detected by the ground penetrating radar is also stratified to obtain the current stratified geological distribution data. Here, the number of layers in the current stratified geological distribution data may be the same as that in the original stratified geological distribution data. However, since the current measured geological data is the data after collapsibility occurs, the width of the 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 layer widths at different positions in the same layer are also different.

[0059] 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 distribution data of the underground geological layers in the building area scene model. Figure 3 The right figure corresponding to the same number of layers in it can represent the result of stratifying the geological data of the pile body area detected by the ground penetrating radar in the same way.

[0060] After that, in the above-mentioned interpolated and partitioned 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 level in the extracted data can be fitted into a layered collapsibility curve to obtain a sequence of layered collapsibility curves. Here, each layered collapsibility curve in each sequence of layered collapsibility curves is a curve with different depths arranged centered on the pile body to characterize the collapsibility distribution characteristics in the direction perpendicular to the line connecting the pile bodies. The range of the layered collapsibility curve can be within the grid division range corresponding to the pile body.

[0061] In the fourth step, the collapsibility degree of the overall collapsibility prediction map is adjusted by using the above-mentioned layered collapsibility curve sequence set to obtain the collapsibility distribution data of the pile body area. Among them, the curvature of each coordinate position of the layered collapsibility curve can be extracted. Then, according to the pre-set correspondence 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.

[0062] As an example, the curvature of a certain coordinate point on the layered 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.

[0063] In practice, in order to further improve the recognition accuracy of the collapsibility situation in the pile body area, therefore, 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 body in the pile body area is again divided into grids and geologically stratified. Thus, the collapsibility changes of the geological data before and after can be compared, and the corresponding layered collapsibility curves can be established to determine the collapsibility degree of the area where the pile body is located with fine granularity. Thus, by further adjusting the collapsibility degree at the corresponding coordinate position in the overall collapsibility prediction map, the accuracy of the collapsibility distribution data of the pile body area is improved.

[0064] Step 105, in response to determining that the collapsibility distribution data of 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 of the pile body area, and send the collapsibility warning heat map to the warning terminal for warning operations.

[0065] In some embodiments, the above-mentioned execution subject can, in response to determining that the 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 the warning terminal for warning operations.

[0066] In practice, for the water level data in the construction pile body data, when it is characterized that the corresponding underground water level rises to within a range less than 1 meter from the bottom of the pile, the pre-laid foundation pit dewatering well can be opened for drainage. In addition, if it is detected that the horizontal displacement of the retaining pile in the retaining pile displacement detection information exceeds the preset displacement threshold, 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 performed.

[0067] In some optional implementation manners of some embodiments, the above-mentioned execution subject generates 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, which may include the following steps: The first step is to perform data conversion on the above-mentioned collapsibility distribution data of the pile body area to generate a sequence of collapsibility coordinate information. Among them, the data conversion can be to convert the collapsibility distribution data of the pile body area into data in a target format. For example, it is converted into a sequence of collapsibility coordinate information in csv format.

[0068] The second step is to perform data interpolation on the above-mentioned sequence of collapsibility coordinate information to obtain an interpolated sequence of collapsibility coordinate information. Among them, the cubic spline interpolation algorithm can be used to perform data interpolation on the above-mentioned sequence of collapsibility coordinate information to obtain an interpolated sequence of collapsibility coordinate information.

[0069] The third step is to render the above-mentioned interpolated sequence of collapsibility coordinate information into the above-mentioned divided building area model according to the coordinate order to generate a collapsibility warning heat map. Among them, the above-mentioned interpolated sequence of collapsibility coordinate information can be rendered into the above-mentioned divided building area model according to the coordinate order through a preset visualization code to generate a collapsibility warning heat map. The visualization code can include a preset function and parameters for drawing the heat map.

[0070] As an example, such as Figure 4 the collapsibility warning heat map shown. The scale on the right vertical axis represents the degree of collapsibility. The darker the color, the higher the collapsibility degree. The scale on the horizontal axis and the scale on the left vertical axis can represent grid coordinates.

[0071] 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, wet subsidence monitoring and early warning can be carried out on the areas where the foundation pits and pile bodies are located in a timely manner. Specifically, the reasons for the difficulty in timely carrying out wet subsidence monitoring and early warning on the areas where the foundation pits and pile bodies are located are as follows: When the construction area is large, more labor costs are required, 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, 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 take 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, 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 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 degree of wet subsidence. Then, based on the above-mentioned construction pile body data set and the above-mentioned divided building area model, wet subsidence analysis is carried out on the foundation pit area and the pile body area to generate wet subsidence distribution data of the pile body area. Here, through wet subsidence analysis, wet subsidence distribution data of all areas within the building construction area can be uniformly generated. Thus, it is convenient to carry out wet subsidence monitoring and early warning. Finally, in response to determining that the wet subsidence distribution data of the above-mentioned pile body area meets the preset early warning conditions, according to the wet subsidence distribution data of the above-mentioned pile body area, a wet subsidence early warning heat map is generated in the above-mentioned divided building area model, and the above-mentioned wet subsidence early warning heat map is sent to the early warning terminal for early warning operations. Thus, wet subsidence monitoring and early warning can be carried out on the areas where the foundation pits and pile bodies are located in a timely manner. For 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 building construction foundation pits and piles, and these device embodiments correspond to Figure 1 the method embodiments shown, and the monitoring and warning device for building construction foundation pits and piles can be specifically applied to various electronic devices.

[0072] As Figure 5 shown, a monitoring and warning device 500 for building construction foundation pits and piles 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, there are marked: a foundation pit area, a greening area, and other areas. In the above 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 collection unit 502 is configured to use a pre-installed construction monitoring probe to capture an image of a local construction area, and through a preset data acquisition device component, collect a construction pile body data set. Among them, the above 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, and each construction pile body data corresponds to a pile body; the grid division unit 503 is configured to, according to the above local construction area image and the above building area scene model, perform local grid division on the underground geological layer of 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, based on the above construction pile body data set and the above divided building area model, perform collapsibility analysis on the foundation pit area and the pile body area 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.

[0073] It can be understood that the various units described in the monitoring and warning device 500 for building construction foundation pits and piles correspond to Figure 1 the respective steps 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 building construction foundation pits and piles and the units included therein, and will not be elaborated here. Reference will now be 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 shown electronic device is merely an example and should not impose any limitation 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, and 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 is only 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 some components, or have different component arrangements.

[0074] It should be understood that the processor may be a central processing unit (CPU), and the processor may also be other general-purpose processors, digital signal processors (DSPs), application specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. Among them, the general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc.

[0075] 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 the pre-installed construction monitoring probe to take 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 the 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, 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 the warning terminal for warning operations.

[0076] 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 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.

[0077] Among them, the above-mentioned computer-readable storage medium may be the 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 (SMC), a Secure Digital (SD) card, a Flash Card, etc.

[0078] It should be noted that, in this document, the terms "including", "comprising" 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 explicitly listed, or further includes elements inherent to such process, method, article or system. Without further limitation, an element defined by the statement "including one..." does not exclude the existence of additional identical elements in the process, method, article or system including such element.

[0079] 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, and 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 (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 foundation pits and piles in construction, characterized in that: include: In response to the completion of the building construction, a building area scene model is established through the building construction geological collection data and the preset building construction simulation model, wherein the ground area in the building area scene model is marked with: foundation pit area, pile area, green area and other areas, and the building area scene model is provided with foundation pit information, pile 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 using a preset data acquisition device component to collect a construction pile body data set, wherein the image of the local construction area 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: 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; According to the construction local area image and the building area scene model, the underground geological layer of the building area scene model is locally gridded to obtain a divided building area model, wherein the local grid division is performed with the foundation pit area as the center, and the construction local area image is also used to adjust the grid division range; Based on the construction pile data set and the divided building area model, performing a collapsibility analysis on the foundation pit area and the pile area to generate pile area collapsibility distribution data; In response to determining that the pile body area collapse distribution data meets the preset warning conditions, a collapse warning heat map is generated in the divided building area model according to the pile body area collapse distribution data, and the collapse warning heat map is sent to the warning terminal for warning operation.

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

3. The method according to claim 1, characterized in that: The data acquisition equipment assembly includes at least one of the following equipment: a pore water pressure gauge group, a ground penetrating radar, a total station, a soil moisture sensor group and a micro soil pressure gauge group, wherein the pore water pressure gauge, the soil moisture sensor and the micro soil pressure gauge are buried in the soil of the foundation pit area, and the construction pile body data set is collected through the preset data acquisition equipment assembly, including: Performing rainfall recognition on the local construction area image to generate a rainfall level mark, wherein the rainfall level mark is used to characterize the degree of rainfall water accumulation in the local construction area; In response to determining rainfall in the construction area, adjusting the collection frequency of the data collection device component according to the rainfall level indicator; Determine the current monitoring time period based on the completion time of the construction and the current time point; In response to determining that the current monitoring time period is in the first preset monitoring time period, using the ground penetrating radar to perform pile integrity detection on a foundation pit area within the construction area to obtain a pile integrity detection information set; Using the total station, the pile tops of the piles in the foundation pit area are detected to obtain a pile displacement detection information set; The pile integrity detection information and the pile displacement detection information corresponding to the same pile body in the pile integrity detection information set and the pile displacement detection information set are used as construction pile body data to obtain a construction pile body data set.

4. The method according to claim 3, characterized in that The method of using a pre-installed construction monitoring probe to capture images of a local construction area and using a preset data acquisition device component to collect a construction pile data set also includes: In response to determining that the current monitoring time period is in a second preset monitoring time period, using the pore water pressure gauge group to detect 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 in the foundation pit area, and obtaining a soil moisture content set; Using the micro earth pressure gauge group to detect the soil horizontal stress value between the corner piles and the support piles in the foundation pit area, and obtaining a soil horizontal stress value set; The water level data set, the soil moisture content set and the soil horizontal stress value set are added to the construction pile data set.

5. The method according to claim 4, characterized in that The method of 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 includes: Determining the grid size of the foundation pit area and the pile body in the building area scene model according to the rainfall level mark corresponding to the local construction area image; Determine the grid division range corresponding to the foundation pit area and the pile body in the building area scene model according to the rainfall level mark corresponding to the image of the local construction area; The underground geological layer of the building area scene model is locally meshed using the mesh size and mesh division range corresponding to the foundation pit area and the pile area to obtain a divided building area model.

6. The method according to claim 5, characterized in that The method of performing a 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 the pile area collapsibility distribution data includes: Using the construction pile data set, soil data interpolation is performed on each grid corresponding to the foundation pit area and the pile area in the divided building area model to obtain an interpolated divided building area model; Based on the interpolated and divided building area model, an overall collapse prediction is performed on the foundation pit area to generate an overall collapse prediction map; Based on the interpolated and divided building area model and the underground geological layer distribution data in the building area scene model, collapsibility analysis is performed on each pile area to generate a layered collapsibility curve sequence, and a layered collapsibility curve sequence set is obtained, wherein each layered collapsibility curve sequence in the layered collapsibility curve sequence set corresponds to a pile area, and each layered collapsibility curve represents the collapsibility distribution characteristics of the soil in the pile area at the current moment; The stratified collapsibility curve sequence set is used to adjust the collapsibility of the overall collapsibility prediction map to obtain the collapsibility distribution data of the pile area.

7. The method according to claim 6, characterized in that The method of generating a heat map for early warning of a subsidence in the divided building area model according to the subsidence distribution data of the pile area comprises: Performing data conversion on the pile area collapsibility distribution data to generate a collapsibility coordinate information sequence; performing data interpolation on the collapsible coordinate information sequence to obtain an interpolated collapsible coordinate information sequence; The interpolated collapsible coordinate information sequence is rendered into the divided building area model in coordinate order to generate a collapsible warning heat map.

8. A monitoring and early warning device for foundation pits and piles in construction, comprising: The establishment unit is configured to establish a building area scene model in response to the completion of the building construction by using the building construction geological collection data and the preset building construction simulation model, wherein the ground area in the building area scene model is marked with: foundation pit area, pile area, green area and other areas, and the building area scene model is provided with foundation pit information, pile information and underground geological layer distribution data corresponding to the foundation pit area; The acquisition unit is configured to use a pre-installed construction monitoring probe to capture an image of a local construction area, and to acquire a construction pile body data set through a preset data acquisition device component, wherein the image of the local construction area 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: 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; A grid division unit is configured to perform 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 a divided building area model, wherein the local grid division is performed with the foundation pit area as the center, and the construction local area image is also used to adjust the grid division range; A collapsibility analysis unit is configured to perform a collapsibility analysis on a foundation pit area and a pile area based on the construction pile data set and the divided building area model to generate pile area collapsibility distribution data; A generation and early warning unit is configured to generate a collapse early warning heat map in the divided building area model according to the collapse distribution data of the pile body area in response to determining that the collapse distribution data of the pile body area meets a preset early warning condition, and send the collapse early warning heat map to the early warning terminal for early warning operation.

9. An electronic device, comprising: one or more processors; a storage device having one or more programs stored thereon, When the one or more programs are executed by the one or more processors, the one or more processors implement the method according to any one of claims 1 to 7.

10. A computer readable medium having a computer program stored thereon, wherein: When the program is executed by a processor, the method according to any one of claims 1 to 7 is implemented.

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