A groundwater pressure monitoring method for basement super-long structure construction

Abstract

The application discloses a kind of groundwater pressure monitoring methods for basement super-long structure construction, it is related to water pressure monitoring field.The method includes: the physical model of construction structure is analyzed, and the set of predetermined monitoring point is formed;When the first real-time water pressure meets predetermined water pressure threshold value, first prediction instruction is generated;The first monitoring point is information collected by calling predetermined water pressure factor, and first factor information and construction structure water pressure prediction graph are obtained;The water pressure prediction anomaly area of construction structure water pressure prediction graph is obtained by spatial difference analysis to the construction structure water pressure prediction graph, and water pressure anomaly alarm is carried out.The technical problem that the precision and accuracy of groundwater pressure monitoring are insufficient in the prior art due to insufficient monitoring point arrangement, insufficient real-time monitoring capability, imperfect data processing and analysis method is solved by using the method, and the technical effect of improving the precision and accuracy of groundwater pressure detection is achieved by optimizing monitoring point and data processing method.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of water pressure monitoring, in particular to a groundwater pressure monitoring method for basement super-long structure construction. BACKGROUND

[0002] With the acceleration of urbanization process, basement super-long structures have been widely used in various large-scale construction projects, such as subway stations, large shopping centers, parking lots, etc. Due to the large span and depth, such structures are extremely sensitive to changes in geological environment and groundwater pressure. Therefore, accurate and timely monitoring of groundwater pressure is of great significance to ensure construction safety and structural stability. There are many types of groundwater pressure monitoring equipment and technology on the market, but many of them have deficiencies in terms of the special needs of basement super-long structure construction. The existing monitoring point arrangement scheme is often too simple or arbitrary, lacking scientificity and systematicness, resulting in deviations or omissions in the monitoring results. Some monitoring systems lack intelligent data processing functions and require manual processing of a large amount of tedious data, reducing work efficiency and accuracy.

[0003] In summary, the existing technology has the technical problem of insufficient precision and accuracy of groundwater pressure monitoring due to insufficient monitoring point arrangement, insufficient real-time monitoring capability, and imperfect data processing and analysis methods. SUMMARY

[0004] Therefore, it is necessary to provide a groundwater pressure monitoring method for basement super-long structure construction that can improve the precision and accuracy of groundwater pressure detection by optimizing the monitoring points and data processing methods.

[0005] In view of the above problems, the present application provides a groundwater pressure monitoring method for basement super-long structure construction.

[0006] In the aspect of the present application, a groundwater pressure monitoring method for basement super-long structure construction is provided, which comprises: analyzing a construction structure physical model constructed based on multi-dimensional structure characteristics of a basement super-long structure, and assembling a predetermined monitoring point set; when a first real-time water pressure of a first monitoring point meets a predetermined water pressure threshold, generating a first prediction instruction, wherein the first monitoring point is any one of the predetermined monitoring point set, and the first real-time water pressure is a water pressure monitored by a first water pressure sensor arranged at the first monitoring point in real time; collecting information of the first monitoring point based on the first prediction instruction by using a predetermined water pressure factor, to obtain first factor information; marking a first predicted water pressure obtained by analyzing the first factor information by using a water pressure prediction model to the construction structure physical model, to obtain a construction structure water pressure prediction graph; obtaining a water pressure prediction abnormal area according to a construction structure water pressure contour map obtained by spatial difference analysis on the construction structure water pressure prediction graph, and performing water pressure abnormality warning on the water pressure prediction abnormal area.

[0007] The groundwater pressure monitoring method for basement super-long structure construction described above solves the technical problem of insufficient precision and accuracy of groundwater pressure monitoring in the prior art due to insufficient monitoring point arrangement, insufficient real-time monitoring capability, and imperfect data processing and analysis method, and achieves the technical effect of improving the precision and accuracy of groundwater pressure detection by optimizing the monitoring point and the data processing method.

[0008] The above description is only a summary of the technical solutions of the present application. In order to enable one skilled in the art to better understand the technical means of the present application, the present application can be implemented according to the content of the specification, and in order to enable the above and other purposes, features and advantages of the present application to be more obvious and easy to understand, the following specific embodiments of the present application are described. BRIEF DESCRIPTION OF DRAWINGS

[0009] Figure 1 It is a flowchart of a groundwater pressure monitoring method for basement super-long structure construction in one embodiment;

[0010] Figure 2 It is a flowchart of predetermined monitoring point set acquisition of a groundwater pressure monitoring method for basement super-long structure construction in one embodiment. DETAILED DESCRIPTION

[0011] The embodiments of the present application provide a groundwater pressure monitoring method for basement super-long structure construction, which solves the technical problem of insufficient precision and accuracy of groundwater pressure monitoring in the prior art due to insufficient monitoring point arrangement, insufficient real-time monitoring capability, and imperfect data processing and analysis method.

[0012] With reference to the drawings of the embodiments of the present application, the technical solutions in the embodiments of the present application will be described clearly and completely. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments of the present application. Based on the embodiments in the present application, all the other embodiments obtained by a person of ordinary skill in the art without creative work fall within the scope of protection of the present application.

[0013] It should be noted that the terms "comprising" and "having" and any variations thereof are intended to cover not exclusively containing, for example, a process, method, system, product or server containing a series of steps or units does not have to be limited to those steps or units clearly listed, but can include other steps or modules that are not clearly listed or inherent to these processes, methods, products or devices.

[0014] As shown in Figure 1 The present application provides a groundwater pressure monitoring method for basement super-long structure construction, comprising:

[0015] Analyzing the construction structure physical model constructed based on the multi-dimensional structural characteristics of the basement super-long structure, and assembling a predetermined monitoring point set;

[0016] The basement super-long structure refers to a structural form with a super-long length in underground buildings. This type of structure is usually used to support underground tunnels, underground pipelines or underground passages and other projects. Due to its length exceeding the conventional range, special consideration needs to be given to the particularity of the underground environment, such as water pressure, soil stability and other factors, when designing and constructing. The present application aims to ensure the stability and safety of the underground structure during construction, and to timely discover and respond to risks that may be caused by changes in groundwater pressure. A groundwater pressure monitoring method for basement super-long structure construction is provided. Through this groundwater pressure monitoring method, changes in groundwater pressure during the construction of the basement super-long structure can be discovered and responded to in a timely manner, ensuring the safety and quality of the construction.

[0017] The basement super-long structure usually has complex structural characteristics, including length, depth, cross-sectional shape, material properties, support system and multiple dimensions, that is, the multi-dimensional structural characteristics of the basement super-long structure, which jointly determine the mechanical properties and stability of the structure. Specifically, for example, structural size analysis determines the key dimensions of the structure, such as length, width, height, and cross-sectional shape and size changes, which affect the stress performance and deformation characteristics of the structure. Material property analysis understands the physical properties of the materials used by the structure, such as material type, strength, and elastic modulus, which will determine the response and deformation capacity of the structure under stress. After analyzing the multi-dimensional structural characteristics, a construction structure physical model is constructed, which is established according to the geometric shape, material properties and boundary conditions of the basement super-long structure, obtains the corresponding mathematical model, and solves the stress, displacement and other parameters of the structure through calculation to obtain the construction structure physical model. The construction structure physical model accurately reflects the mechanical properties and stability of the structure. After constructing the construction structure physical model, a predetermined monitoring point set needs to be formed, which is composed of various monitoring points. The monitoring points will be used to monitor the groundwater pressure and other related parameters in the actual construction process, such as selecting the areas with stress concentration or large deformation in the key parts of the structure as monitoring points, or determining the areas where groundwater pressure changes may have a greater impact on the structure, and setting monitoring points in these areas. Through comprehensive consideration, a reasonable and effective predetermined monitoring point set is formed. These monitoring points will be used to monitor the changes of groundwater pressure and other related parameters in real time, providing important protection for the safety of the structure during construction.

[0018] As shown in Figure 2 , analyzing the construction structure physical model obtains a first initial monitoring point set satisfying a first predetermined monitoring constraint;

[0019] Extracting a first historical record in the historical construction groundwater pressure monitoring record of the basement super-long structure;

[0020] Based on the first groundwater pressure abnormal point in the first historical record, a second initial monitoring point set is formed;

[0021] Randomly extracting a first initial monitoring point from the first initial monitoring point set or the second initial monitoring point set;

[0022] Judging whether the first initial position of the first initial monitoring point meets a second predetermined monitoring constraint;

[0023] If it is satisfied, the first initial monitoring point is added to the predetermined monitoring point set.

[0024] The construction structure physical model is analyzed to obtain a first initial monitoring point set satisfying first predetermined monitoring constraints. The first predetermined monitoring constraints refer to monitoring points at locations such as corners, corners of the basement structure, and the like. Historical database of the basement super-long structure in the construction process is extracted, and the historical construction groundwater pressure monitoring record of the basement super-long structure is obtained. The groundwater pressure monitoring record contains information such as groundwater pressure change trend and abnormal points. The first historical record is extracted from the historical construction groundwater pressure monitoring record of the basement super-long structure, and the first historical record includes various information in the past time. According to the first historical record, the first groundwater pressure abnormal point is identified, which reflects some unstable factors in the construction process, i.e., the position where the water pressure anomaly occurred in the historical construction process. The second initial monitoring point set is composed according to the first groundwater pressure abnormal point. In order to increase the diversity and representativeness of the monitoring points, the monitoring points are randomly selected from the first initial monitoring point set and the second initial monitoring point set, so as to ensure that the finally selected monitoring points meet the constraints of the physical model and reflect the actual situation in the historical construction. After the monitoring points are selected, the positions thereof need to be further judged to see whether they meet the second predetermined monitoring constraints, including the spatial distribution of the monitoring points, the distance from the key structure, the safety requirements, and the like. In the present application, the second predetermined monitoring constraints include being away from the construction and water flow being active, so as to ensure that the sensor installation position is away from the construction activities and avoid the interference of construction vibration on the sensor. The sensor should be installed in the area where the groundwater flow is active, usually a distance of 1-2 meters from the building foundation bottom. If a certain initial monitoring point meets all the constraint conditions, it will be added to the predetermined monitoring point set. This set will finally contain all the monitoring points determined after screening and judgment, which are used for subsequent construction monitoring and data analysis. Through the above method, the constraint conditions of the construction structure physical model, the abnormal points in the historical construction record, and the spatial distribution of the monitoring points are comprehensively considered, aiming to select the most suitable monitoring points to achieve effective monitoring and data analysis of the construction process.

[0025] When the first real-time water pressure of the first monitoring point meets the predetermined water pressure threshold, a first prediction instruction is generated, wherein the first monitoring point is any one of the predetermined monitoring point set, and the first real-time water pressure is the water pressure monitored by the first water pressure sensor deployed at the first monitoring point in real time.

[0026] In the construction process, each monitoring point in the set of predetermined monitoring points is equipped with a corresponding water pressure sensor, such as a first water pressure sensor corresponding to a first monitoring point, etc. The water pressure sensor can collect and transmit real-time water pressure data at its location, i.e. the first real-time water pressure. The collected first real-time water pressure data is compared with the predetermined water pressure threshold. The water pressure threshold is usually set based on engineering requirements, safety standards and historical data analysis, aiming to ensure that the water pressure during construction is within a safe and controllable range. If the first real-time water pressure data exceeds or is lower than the predetermined water pressure threshold, the system will immediately identify this abnormal situation and generate a first prediction instruction. The first prediction instruction usually contains information such as the type, location and possible consequences of the abnormality, which is used to guide future water pressure prediction based on normal water pressure, so as to timely predict whether the future water pressure is normal and take timely measures. The first monitoring point is any one of the set of predetermined monitoring points, and the first real-time water pressure is the water pressure monitored by the first water pressure sensor deployed at the first monitoring point. According to the above method, through multiple links such as real-time monitoring, data analysis and prediction instruction generation, accurate control and timely response of the water pressure state during construction are realized, which provides strong technical support for construction safety and quality control.

[0027] Obtain a first monitoring optimization constraint;

[0028] Set a first monitoring optimization evaluation index;

[0029] Under the first monitoring optimization constraint, combined with the first monitoring optimization evaluation index, global optimization of monitoring frequency is carried out in a predetermined optimization space to obtain a first optimal monitoring frequency, wherein the predetermined optimization space refers to a first predetermined monitoring frequency range of the first water pressure sensor;

[0030] The first water pressure sensor performs real-time water pressure monitoring on the first monitoring point based on the first optimal monitoring frequency.

[0031] Before performing the monitoring frequency optimization, the constraint conditions in the optimization process need to be determined first, namely the first monitoring optimization constraint, including the working range of the sensor, the monitoring cost limit, the construction environment requirement, etc. These constraint conditions will be used as the limiting conditions in the subsequent optimization process to ensure that the optimization result meets the actual demand and feasibility. In order to measure the pros and cons of different monitoring frequencies, corresponding evaluation indexes need to be set, namely the first monitoring optimization evaluation index, including the accuracy, real-time performance, monitoring cost, etc. of the monitoring data. By comprehensively considering these indexes, the performance of different monitoring frequencies can be evaluated more comprehensively, so as to find the optimal solution. After determining the constraint conditions and evaluation indexes, global optimization needs to be performed in the predetermined optimization space. The predetermined optimization space refers to the first predetermined monitoring frequency range of the first water pressure sensor, i.e. finding the optimal monitoring frequency in this range. After global optimization, an optimal monitoring frequency that meets the constraint conditions and evaluation indexes will be obtained, namely the first optimal monitoring frequency. This frequency will be used as the benchmark for subsequent real-time monitoring to ensure that the accuracy and real-time performance of the monitoring data reach the optimal state. The first water pressure sensor will perform real-time water pressure monitoring on the first monitoring point according to the obtained first optimal monitoring frequency. This will ensure that accurate and real-time water pressure data is obtained under the optimal monitoring frequency, providing strong support for the monitoring and decision-making of the construction process. Through the above method, the constraint conditions are determined, the evaluation indexes are set, and the global optimization is performed, realizing the optimal selection of the monitoring frequency and improving the accuracy and real-time performance of the monitoring data, which provides an important basis for the control and decision-making of the construction process.

[0032] The first monitoring optimization constraint includes the real-time construction phase of the basement super-long structure, the first real-time environmental humidity of the first monitoring point, and the first spectral density obtained by analyzing the first historical monitoring water pressure time sequence of the first monitoring point.

[0033] The structural characteristics, load conditions, and construction methods of different construction stages will be different, and these differences will directly affect the distribution and changes of water pressure. Therefore, the real-time construction stage as one of the constraint conditions can ensure that the optimization of the monitoring frequency matches the characteristics of the current construction stage, so as to more accurately capture the dynamic changes of water pressure. Environmental humidity is an important factor affecting the performance of water pressure sensors and the accuracy of monitoring data. High humidity environment may cause internal condensation or corrosion of the sensor, thereby affecting its measurement accuracy and stability. Therefore, the first real-time environmental humidity as one of the constraint conditions can ensure that the influence of environmental factors on the performance of the sensor is considered when optimizing the monitoring frequency, thereby avoiding high-frequency monitoring in adverse environments and reducing data errors. The first spectral density is obtained by spectral analysis of historical monitoring water pressure time series data, which reflects the frequency characteristics of water pressure changes. Different frequency components of water pressure changes have different effects on structural safety, so by analyzing the spectral density, it can be determined which frequency components need to be focused on. The first spectral density as one of the constraint conditions can consider the frequency characteristics of water pressure changes when optimizing the monitoring frequency, thereby ensuring sufficient monitoring in the key frequency band and improving the relevance and effectiveness of the monitoring data. In summary, the constraint conditions comprehensively consider the characteristics of the construction stage, the influence of environmental factors, and the frequency characteristics of water pressure changes, providing comprehensive and accurate information for determining the optimal monitoring frequency. In the optimization process, these constraint conditions need to be considered comprehensively to find the optimal monitoring frequency that meets the actual demand and feasibility.

[0034] The first monitoring optimization evaluation index includes a first monitoring efficiency and a first monitoring quality, wherein the first monitoring efficiency is characterized by a first data change rate, and the first monitoring quality is characterized by a first data missing rate.

[0035] The first monitoring optimization evaluation index includes first monitoring efficiency and first monitoring quality. First monitoring efficiency is characterized by a first data change rate, reflecting the speed and ability to acquire effective monitoring data within a given time. The first data change rate is the ratio of the magnitude of data change to the frequency of change, reflecting the effectiveness of the monitoring data and the rationality of the monitoring frequency. First monitoring quality focuses on the accuracy and completeness of the monitoring data, characterized by a first data missing rate, which refers to the proportion of data missing due to various reasons. The lower the data missing rate, the better the monitoring stability and the higher the quality. A lower data missing rate means higher completeness and reliability of the monitoring data, providing strong support for construction decisions. Optimizing the monitoring frequency to match the data change rate can improve monitoring efficiency and ensure timely acquisition of effective monitoring data. When optimizing the monitoring frequency, it is necessary to consider how to reduce the data missing rate, such as by increasing sensor redundancy and optimizing communication protocols to improve data stability and reliability. First monitoring efficiency and first monitoring quality, as evaluation indexes, together constitute important bases for optimizing the monitoring frequency. By comprehensively considering these two indicators, we can ensure that optimizing the monitoring frequency can both improve the speed and capability of data acquisition and guarantee the accuracy and completeness of the data, thereby providing comprehensive and accurate information support for the control and decision-making of the construction process.

[0036] Read the predefined sensor loss analysis function;

[0037] The first real-time water pressure monitored by the first water pressure sensor is adjusted according to the predetermined sensor loss analysis function.

[0038] The expression for the predetermined sensor loss analysis function is as follows:

[0039] ;

[0040] This refers to the first real-time water pressure Adjustment results of the first real-time water pressure loss The predetermined sensor loss analysis function between, This refers to the construction vibration feedback coefficient of the aforementioned ultra-long basement structure. This refers to the construction environment feedback coefficient of the aforementioned ultra-long basement structure. This refers to the device accuracy feedback coefficient of the first water pressure sensor.

[0041] The predetermined sensor loss analysis function is pre-set based on factors such as sensor characteristics, historical data, and environmental conditions. Its purpose is to analyze potential data loss or errors that may occur during sensor monitoring, quantifying the extent of sensor data loss. After reading the loss analysis function, the system applies it to the first real-time water pressure data monitored by the first water pressure sensor. This aims to correct or compensate for the original monitoring data, eliminating or reducing the impact of sensor loss on the data. The specific method of loss adjustment depends on the definition and logic of the loss analysis function. For example, the function may perform linear or nonlinear transformations on the original data based on the distribution of sensor errors, or correct the data based on environmental conditions such as humidity and temperature. Through loss adjustment, the system can provide more accurate and reliable water pressure monitoring data, providing a more precise basis for construction management and decision-making. The expression of the predetermined sensor loss analysis function is as follows:

[0042] ;

[0043] This refers to the first real-time water pressure Adjustment results of the first real-time water pressure loss The predetermined sensor loss analysis function between, This refers to the construction vibration feedback coefficient of the aforementioned ultra-long basement structure. This refers to the construction environment feedback coefficient of the aforementioned ultra-long basement structure. This refers to the device accuracy feedback coefficient of the first water pressure sensor. Through the above method, customization and optimization are performed based on the actual application scenario and sensor characteristics to ensure the effectiveness of loss adjustment. This ensures the real-time nature and accuracy of the data.

[0044] Based on the first prediction instruction, a predetermined water pressure factor is retrieved to collect information from the first monitoring point, thereby obtaining the first factor information;

[0045] According to the specific content of the first prediction instruction, the predetermined water pressure factors are called, including geological dimension factors, climate dimension factors, construction dimension factors and material dimension factors, which are pre-determined and stored in the system so as to be quickly called when needed. After the predetermined water pressure factors are called, the system starts information collection for the first monitoring point, including various ways such as field measurement, sensor reading, historical data query, etc. The collected information aims to reflect the current water pressure condition of the first monitoring point and its interaction with the surrounding environment. Through information collection, the first factor information related to the first monitoring point is finally obtained, which is an important basis for subsequent analysis and decision-making, not only reflecting the current water pressure condition, but also revealing potential risks or trends. Through the above method, through preset rules and algorithms, the system can quickly respond to the prediction instruction, call appropriate water pressure factors, and effectively collect information. This helps to discover and handle water pressure abnormalities in time, ensuring the smooth progress of the construction process. The acquisition of the first factor information also provides a basis for subsequent data analysis and decision support. Through in-depth mining and processing of these information, the law and reason of water pressure change can be further understood, providing strong support for optimizing construction scheme and ensuring construction safety.

[0046] The predetermined water pressure factors include geological dimension factors, climate dimension factors, construction dimension factors and material dimension factors, wherein the geological dimension factors include soil water permeability and groundwater flow rate, the climate dimension factors include precipitation and environmental temperature, the construction dimension factors include construction vibration and construction drainage, and the material dimension factor refers to material waterproofness.

[0047] The predetermined water pressure factors include a geological dimension factor, a climate dimension factor, a construction dimension factor, and a material dimension factor. The geological dimension factor includes soil permeability and groundwater flow rate. Soil permeability is the permeability of soil to water, which directly affects the distribution and change of groundwater level, and in turn affects water pressure. Groundwater flow rate is the flow speed of groundwater, which can reflect the recharge and discharge of groundwater and has a direct impact on water pressure. The climate dimension factor includes precipitation and environmental temperature. Precipitation is one of the main sources of groundwater recharge, and the amount of precipitation directly determines the amount of groundwater recharge, thereby affecting water pressure. Temperature changes in the environmental temperature may affect the expansion and contraction of the soil, and in turn affect the flow of groundwater and water pressure. The construction dimension factor includes construction vibration and construction drainage. Vibration generated by construction activities such as excavation and piling may affect the soil structure and groundwater flow. Construction drainage is the drainage activity during the construction of the basement, which affects the groundwater level and water pressure. The material dimension factor refers to the water resistance of the building materials used. The water resistance of the building materials directly affects the penetration and accumulation of water in the structure, and in turn affects the water pressure. By comprehensively considering the above-mentioned predetermined water pressure factors, the change trend of water pressure can be predicted and analyzed more comprehensively and accurately, providing support for decision-making during construction. At the same time, it also provides an important reference for the subsequent optimization of monitoring frequency and the design of early warning mechanisms. In practical applications, these factors can be further refined and quantified according to specific circumstances to improve the accuracy of prediction and analysis.

[0048] The first predicted water pressure obtained by analyzing the first factor information through the water pressure prediction model is marked to the construction structure physical model to obtain a construction structure water pressure prediction map.

[0049] The water pressure prediction model predicts future water pressure changes based on input water pressure factor information, taking into account the interaction and influence between various factors. Through complex calculations and analyses, the model outputs a prediction result for future water pressure. After analyzing the first factor information, the water pressure prediction model outputs a predicted value, i.e., the first predicted water pressure, which represents the model's estimate and prediction of future water pressure changes and is an important basis for subsequent analysis and decision-making. The first predicted water pressure is marked to the construction structure physical model to visually demonstrate the relationship between the construction structure and water pressure distribution. By marking the predicted water pressure, abstract data can be converted into specific graphical displays. After marking and integrating, a construction structure water pressure prediction map is produced, which displays the morphology and characteristics of the construction structure. Different colors, lines, or other graphical elements are used to represent the distribution and changes of predicted water pressure, allowing technicians in the field to intuitively understand the water pressure conditions of the construction structure in different regions and at different time points, providing strong support for construction decision-making. Through the above method, the water pressure prediction model is continuously trained and optimized based on actual data and requirements to improve prediction accuracy and practicality.

[0050] extracting a first grid in a construction structure grid set obtained by meshing a construction structure water pressure prediction map, wherein the first grid corresponds to first coordinate information;

[0051] judging whether the first coordinate information corresponding to the first grid is deployed with a water pressure sensor;

[0052] if not, taking a first center point of the first grid as a first interpolation point to be interpolated;

[0053] obtaining a first search neighborhood of the first interpolation point to be interpolated based on a predetermined neighborhood scheme, the first search neighborhood including a plurality of neighborhood grids, and the plurality of neighborhood grids corresponding to a plurality of neighborhood grid prediction water pressures one by one;

[0054] obtaining first neighborhood coordinate information of a first neighborhood grid in the plurality of neighborhood grids, and calculating the first neighborhood coordinate information with the first coordinate information to obtain a first distance;

[0055] obtaining a first neighborhood grid prediction water pressure of the first neighborhood grid in the plurality of neighborhood grid prediction water pressures by traversing, and obtaining a first weighted water pressure by weighting the first distance;

[0056] taking a mean value of the first weighted water pressure as a first interpolation water pressure of the first interpolation point to be interpolated;

[0057] adding the first interpolation water pressure to the construction structure water pressure prediction map, and analyzing to obtain a construction structure water pressure contour map.

[0058] The construction structure water pressure prediction map is meshed to obtain a construction structure mesh set, which is a set of meshes obtained by meshing the construction structure water pressure prediction map. Meshing refers to the process of dividing the construction structure water pressure prediction map into multiple small units, such as rectangular mesh difference meshing, triangular finite element meshing, etc. The mesh size is set by a person skilled in the art in combination with historical data. A mesh is randomly extracted from the construction structure mesh set as a first mesh. The first mesh corresponds to first coordinate information, which is the position information of the first mesh in the construction structure water pressure prediction map. According to the first coordinate information, it is determined whether a water pressure sensor has been deployed at the position. If not, interpolation processing is needed. Interpolation processing is usually used to fill in the missing data area. If no water pressure sensor is deployed at the first mesh, the center point of the first mesh is determined as the first interpolation point. The selection of the interpolation point is usually based on the center point of the mesh, because it can represent the water pressure of the entire mesh to some extent. According to a predetermined neighborhood scheme, such as selecting a number of meshes closest to the interpolation point, a first search neighborhood of the first interpolation point is obtained. The first search neighborhood refers to a set of surrounding meshes of the first interpolation point, which is used for subsequent calculation. A neighborhood mesh, i.e. a first neighborhood mesh, is selected from the first search neighborhood, and its neighborhood coordinate information is obtained. The distance between the neighborhood coordinate information of the first neighborhood mesh and the first coordinate information is calculated to obtain a first distance. The first distance is used for subsequent weighted calculation. The closer the mesh point to the interpolation point, the greater the influence of the predicted water pressure on the interpolation result. The predicted water pressure of all neighborhood meshes in the first search neighborhood is traversed. For each neighborhood mesh, its predicted water pressure is weighted with the corresponding first distance to obtain the weighted water pressure of the mesh. The purpose of weighted calculation is to consider the difference in the influence of different neighborhood meshes on the water pressure of the interpolation point. The weighted water pressures of all neighborhood meshes are averaged to obtain the first interpolation water pressure of the first interpolation point. The first interpolation water pressure is obtained by weighted averaging based on the predicted water pressure of the neighborhood mesh, and can fill in the water pressure data of the area without deploying the sensor. The calculated first interpolation water pressure is added to the construction structure water pressure prediction map to fill in the missing data. According to the updated water pressure prediction map, the construction structure water pressure contour map is analyzed and generated. The contour map can directly show the distribution of water pressure in different areas, which is helpful for construction management and decision-making. Through the above method, through meshing, interpolation calculation and contour generation, the problem of missing water pressure data is effectively solved, the integrity and accuracy of water pressure monitoring are improved, and strong support is provided for water pressure management and risk control in the construction process.

[0059] The water pressure prediction abnormal area is obtained according to the construction structure water pressure contour map obtained by spatial difference analysis of the construction structure water pressure prediction map, and the water pressure abnormality alarm is performed on the water pressure prediction abnormal area.

[0060] The construction structure water pressure contour map is analyzed, the contour map is studied, the trend and change of water pressure distribution are observed, and the dense area or the area with sudden change in the contour map is noted, which indicates that there is a water pressure abnormality. Based on the water pressure change range and speed on the contour map, the area where the water pressure abnormality exists is determined. The abnormal area usually has the characteristics of dense contour lines, unequal intervals or sudden discontinuity. According to the characteristics of the construction structure, the design requirements and the historical water pressure data, a reasonable abnormal threshold is set. The abnormal threshold can be the absolute value of water pressure, the change rate or the relative difference with other areas, etc. According to the setting of the person skilled in the art, the set abnormal threshold is compared with the contour map, and the area where the water pressure exceeds or is lower than the threshold is identified as the determined water pressure prediction abnormal area. After the water pressure prediction abnormal area is determined, an alarm mechanism is triggered immediately, and relevant personnel are alarmed by sending a short message, an email notification, displaying warning information on a monitoring interface, etc. to remind necessary measures to be taken.

[0061] It should be noted that the above-mentioned sequence of the embodiments of the present application is only for description, and does not represent the advantages and disadvantages of the embodiments. Moreover, the above describes specific embodiments of the present application. In addition, the processes depicted in the drawings do not necessarily require the specific order and continuous order shown to achieve the desired results. In some embodiments, multi-task processing and parallel processing are also possible or can be advantageous.

[0062] The technical features of the above embodiments can be combined arbitrarily. In order to make the description concise, all possible combinations of the technical features in the above embodiments are not described, however, as long as the combination of the technical features does not exist contradictory, it should be considered as the scope of the present application.

[0063] The above-described embodiments only express several implementation manners of the present application, and the description is more specific and detailed, but it should not be understood as a limitation on the scope of the patent. It should be noted that for ordinary skilled persons in the art, without departing from the concept of the present application, some modifications and improvements can be made, which are within the scope of the present application.

Claims

1. A method for monitoring groundwater pressure for construction of an overlength structure of a basement, characterized by, The method comprises the following steps: analyzing a construction structure physical model based on multi-dimensional structural characteristics of a basement super-long structure, and establishing a predetermined monitoring point set; generating a first prediction instruction when a first real-time water pressure of a first monitoring point meets a predetermined water pressure threshold, wherein the first monitoring point is any one of the predetermined monitoring point set, and the first real-time water pressure is a water pressure monitored by a first water pressure sensor arranged at the first monitoring point in real time; collecting information of the first monitoring point based on a predetermined water pressure factor according to the first prediction instruction, to obtain first factor information; labeling a first predicted water pressure obtained by analyzing the first factor information through a water pressure prediction model to the construction structure physical model, to obtain a construction structure water pressure prediction graph; obtaining a water pressure prediction abnormal area according to a construction structure water pressure contour map obtained by spatial difference analysis of the construction structure water pressure prediction graph, and performing water pressure abnormality warning on the water pressure prediction abnormal area; the predetermined water pressure factor comprises a geological dimension factor, a climate dimension factor, a construction dimension factor and a material dimension factor, wherein the geological dimension factor comprises soil water permeability and underground water flow rate, the climate dimension factor comprises precipitation and environmental temperature, the construction dimension factor comprises construction vibration and construction drainage, and the material dimension factor refers to material waterproofness; before obtaining the water pressure prediction abnormal area according to the construction structure water pressure contour map obtained by spatial difference analysis of the construction structure water pressure prediction graph, the method comprises the following steps: extracting a first grid in a construction structure grid set obtained by grid division of the construction structure water pressure prediction graph, wherein the first grid corresponds to first coordinate information; judging whether the first coordinate information corresponding to the first grid is arranged with a water pressure sensor; if not, taking a first center point of the first grid as a first interpolation point; obtaining a first search neighborhood of the first interpolation point based on a predetermined neighborhood scheme, wherein the first search neighborhood comprises a plurality of neighborhood grids, and the plurality of neighborhood grids are in one-to-one correspondence with a plurality of neighborhood grid predicted water pressures; obtaining first neighborhood coordinate information of a first neighborhood grid in the plurality of neighborhood grids, and calculating the first neighborhood coordinate information with the first coordinate information to obtain a first distance; iterating through the plurality of neighborhood grid predicted water pressures to obtain a first neighborhood grid predicted water pressure of the first neighborhood grid, and weighting the first distance to obtain a first weighted water pressure; taking a mean value of the first weighted water pressure as a first interpolation water pressure of the first interpolation point; adding the first interpolation water pressure to the construction structure water pressure prediction graph, and analyzing to obtain the construction structure water pressure contour map.

2. The method of claim 1, wherein establishing a predetermined monitoring point set, comprising: analyzing the construction structure physical model to obtain a first initial monitoring point set meeting a first predetermined monitoring constraint; extracting a first historical record in a historical construction underground water pressure monitoring record of the basement super-long structure; establishing a second initial monitoring point set based on a first underground water pressure abnormal point in the first historical record; randomly extracting a first initial monitoring point from the first initial monitoring point set or the second initial monitoring point set; determining whether a first initial position of the first initial monitoring point meets a second predetermined monitoring constraint; if yes, adding the first initial monitoring point to the set of predetermined monitoring points.

3. The method of claim 1, wherein Further comprising: acquiring a first monitoring optimization constraint; setting a first monitoring optimization evaluation index; under the first monitoring optimization constraint, combining the first monitoring optimization evaluation index to perform global optimization of monitoring frequency in a predetermined optimization space to obtain a first optimal monitoring frequency, wherein the predetermined optimization space refers to a first predetermined monitoring frequency range of the first water pressure sensor; the first water pressure sensor performs real-time water pressure monitoring on the first monitoring point based on the first optimal monitoring frequency.

4. The method of claim 3, wherein The first monitoring optimization constraint includes a real-time construction phase of the super-long structure of the basement, a first real-time environmental humidity of the first monitoring point, and a first spectral density obtained by analyzing a first historical monitoring water pressure time sequence of the first monitoring point.

5. The method of claim 3, wherein the step of determining the water pressure comprises the steps of: determining a water pressure at the well site; and determining a water pressure at the well site using the water pressure at the well site. The first monitoring optimization evaluation index includes a first monitoring efficiency and a first monitoring quality, wherein the first monitoring efficiency is characterized by a first data change rate, and the first monitoring quality is characterized by a first data missing rate.

6. The method of claim 1, wherein, Further comprising: reading a predetermined sensor loss analysis function; loss adjusting the first real-time water pressure monitored by the first water pressure sensor in real time according to the predetermined sensor loss analysis function; wherein the expression of the predetermined sensor loss analysis function is as follows: ； is referred to as the first real-time water pressure and the first real-time water pressure loss adjustment result between the predetermined sensor loss analysis function, is referred to as the construction vibration feedback coefficient of the basement super-long structure, is referred to as the construction environment feedback coefficient of the basement super-long structure, is referred to as the equipment accuracy feedback coefficient of the first water pressure sensor.

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