Underground water pressure monitoring method for basement super-long structure construction

Abstract

The invention discloses an underground water pressure monitoring method for basement super-long structure construction, and relates to the field of water pressure monitoring. The method comprises the following steps: analyzing a construction structure physical model, and establishing a predetermined monitoring point set; when the first real-time water pressure meets a preset water pressure threshold value, a first prediction instruction is generated; calling a preset water pressure factor to perform information acquisition on the first monitoring point to obtain first factor information and a construction structure water pressure prediction map; and performing spatial difference analysis on the construction structure water pressure prediction map to obtain a water pressure prediction abnormal area of the construction structure water pressure contour map, and performing water pressure abnormity warning. By adopting the method, the technical problems of insufficient underground water pressure monitoring precision and accuracy caused by insufficient monitoring point arrangement, insufficient real-time monitoring capability and imperfect data processing and analysis methods in the prior art are solved, and the technical effect of improving the underground water pressure detection precision and accuracy is achieved by optimizing the monitoring points and the data processing method.

Description

Technical Field

[0001] The present application relates to the technical field of water pressure monitoring, and specifically to a method for monitoring underground water pressure for construction of ultra-long basement structures. Background Art

[0002] With the acceleration of urbanization, super-long basement structures have been widely used in various large-scale construction projects, such as subway stations, large shopping malls, parking lots, etc. Due to their large spans and deep depths, these 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 technologies on the market, but many equipment and technologies are insufficient to meet the special needs of super-long basement structure construction. Existing monitoring point layout schemes are often too simple or arbitrary, lack scientificity and systematicity, resulting in deviations or omissions in monitoring results. Some monitoring systems lack intelligent data processing functions, requiring manual labor to perform a large amount of tedious data processing, which reduces work efficiency and accuracy.

[0003] In summary, the prior art has technical problems such as insufficient precision and accuracy of groundwater pressure monitoring due to insufficient arrangement of monitoring points, insufficient real-time monitoring capabilities, and imperfect data processing and analysis methods. Summary of the invention

[0004] Based on this, it is necessary to provide a groundwater pressure monitoring method for the construction of super-long basement structures, which can improve the precision and accuracy of groundwater pressure detection by optimizing monitoring points and data processing methods, in response to the above-mentioned technical problems.

[0005] In view of the above problems, the present application provides a method for monitoring underground water pressure for construction of ultra-long basement structures.

[0006] In the disclosed aspect of the present application, a method for monitoring underground water pressure for construction of super-long basement structures is provided, the method comprising: analyzing a physical model of a construction structure constructed based on the multi-dimensional structural characteristics of the super-long basement structure, and forming a predetermined set of monitoring points; generating a first prediction instruction when a first real-time water pressure at a first monitoring point meets a predetermined water pressure threshold, wherein the first monitoring point is any one of the predetermined set of monitoring points, and the first real-time water pressure is the water pressure monitored in real time by a first water pressure sensor deployed at the first monitoring point; based on the first prediction instruction, a predetermined water pressure factor is retrieved to collect information on the first monitoring point to obtain first factor information; a first predicted water pressure obtained by analyzing the first factor information with a water pressure prediction model is marked on the physical model of the construction structure to obtain a water pressure prediction map of the construction structure; a water pressure prediction abnormal area is obtained based on a construction structure water pressure contour map obtained by performing a spatial difference analysis on the construction structure water pressure prediction map, and a water pressure abnormality alarm is issued for the water pressure prediction abnormal area.

[0007] The above-mentioned groundwater pressure monitoring method for the construction of super-long basement structures adopts this method to solve the technical problems in the prior art of insufficient precision and accuracy of groundwater pressure monitoring due to insufficient arrangement of monitoring points, insufficient real-time monitoring capabilities, and imperfect data processing and analysis methods. By optimizing the monitoring points and data processing methods, the technical effect of improving the precision and accuracy of groundwater pressure detection is achieved.

[0008] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0009] Figure 1 A schematic diagram of a flow chart of a method for monitoring underground water pressure in construction of an ultra-long basement structure in one embodiment; Figure 2 The present invention is a schematic diagram of a process for obtaining a set of predetermined monitoring points in a method for monitoring underground water pressure for construction of an ultra-long basement structure in an embodiment. DETAILED DESCRIPTION

[0010] The embodiments of the present application provide a groundwater pressure monitoring method for the construction of super-long basement structures, thereby solving the technical problems in the prior art of insufficient precision and accuracy of groundwater pressure monitoring due to insufficient arrangement of monitoring points, insufficient real-time monitoring capabilities, and imperfect data processing and analysis methods.

[0011] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of this application.

[0012] It should be noted that the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or server that includes a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or modules that are not explicitly listed or are inherent to these processes, methods, products or devices.

[0013] like Figure 1 As shown, the present application provides a method for monitoring underground water pressure for construction of ultra-long basement structures, comprising: Analyze the physical model of the construction structure based on the multi-dimensional structural characteristics of the super-long basement structure and establish a set of predetermined monitoring points; An extra-long basement structure refers to a structural form with an extra-long length in an underground building. This type of structure is usually used to support projects such as underground tunnels, underground pipelines or underground passages. Since its length exceeds the conventional range, the design and construction need to take into special consideration the particularities of the underground environment, such as water pressure, soil stability and other factors. This application aims to ensure the stability and safety of underground structures during construction, and promptly discover and respond to risks that may be caused by changes in groundwater pressure. It provides a groundwater pressure monitoring method for the construction of extra-long basement structures. Through this groundwater pressure monitoring method, it is possible to promptly discover and respond to groundwater pressure changes that may occur during the construction of extra-long basement structures, thereby ensuring the safety and quality of construction.

[0014] Super-long basement structures usually have complex structural features, including multiple dimensions such as length, depth, cross-sectional shape, material properties, and support system, that is, the multi-dimensional structural characteristics of super-long basement structures. The multi-dimensional structural characteristics jointly determine the mechanical properties and stability of the structure. Specifically, for example, structural dimension analysis determines the key dimensions of the structure such as length, width, and height, as well as 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 material type, strength, elastic modulus, etc. used in the structure, which will determine the response and deformation capacity of the structure when subjected to stress. After analyzing the multi-dimensional structural features, a construction structure physical model is constructed. The construction structure physical model is established according to the geometric shape, material properties and boundary conditions of the super-long basement structure, and the corresponding mathematical model is obtained. The stress, displacement and other parameters of the structure are calculated and solved to obtain the construction structure physical model. The construction structure physical model accurately reflects the mechanical properties and stability of the structure. After the construction structure physical model is constructed, a set of predetermined monitoring points needs to be established. The predetermined monitoring points are composed of multiple monitoring points. The monitoring points will be used to monitor groundwater pressure and other related parameters during the actual construction process. For example, areas with stress concentration or large deformation in key parts of the structure are selected as monitoring points, or areas where groundwater pressure changes may have a greater impact on the structure are determined, and monitoring points are set in these areas. Through comprehensive consideration, a reasonable and effective set of predetermined monitoring points is established. These monitoring points will be used to monitor the changes in groundwater pressure and other related parameters in real time, providing important guarantees for structural safety during the construction process.

[0015] like Figure 2 As shown, the construction structure physical model is analyzed to obtain a first initial monitoring point set that satisfies a first predetermined monitoring constraint; Extracting the first historical record from the historical construction groundwater pressure monitoring record of the super-long basement structure; forming a second initial monitoring point set based on the first groundwater 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 so, the first initial monitoring point is added to the predetermined monitoring point set.

[0016] The physical model of the construction structure is analyzed to obtain a first initial set of monitoring points that meet the first predetermined monitoring constraint, wherein the first predetermined monitoring constraint refers to monitoring points at the surroundings, the bottom, places where geological conditions change significantly, and corners. For example, a monitoring point is set at a certain distance, such as 20-50 meters, around the basement structure; at the bottom of the basement structure, monitoring points are evenly arranged according to the area and shape of the bottom; monitoring points are added in areas where geological conditions change significantly or where water pressure anomalies are expected; monitoring points are set at corners and corners of the basement structure because stress concentration may exist in these places; and groundwater pressure monitoring records of super-long basement structures during construction are extracted from the historical database, wherein the groundwater pressure monitoring records contain groundwater pressure. The first historical record is extracted from the historical construction groundwater pressure monitoring record of the super-long structure of the basement, wherein the first historical record includes various information in the construction process in the past; according to the extracted first historical record, the first groundwater pressure abnormal point is identified, and the first groundwater pressure abnormal point reflects certain unstable factors in the construction process, that is, the location where water pressure abnormality has occurred in the historical construction process, and the second initial monitoring point set is formed 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 to ensure that the finally selected monitoring points not only meet the constraints of the physical model, but also reflect the actual situation in the historical construction. After selecting the monitoring point, its position needs to be further judged to see whether it meets the second predetermined monitoring constraint, including the spatial distribution of the monitoring point, the distance from the key structure, safety requirements, etc. In this application, the second predetermined monitoring constraint includes being away from construction and active water flow, ensuring that the sensor installation position is away from construction activities to avoid interference to the sensor caused by construction vibration. The sensor should be installed in an area with active groundwater flow, usually at a certain distance from the bottom of the building foundation, such as 1-2 meters. If an initial monitoring point meets all the constraints, it will be added to the set of predetermined monitoring points. This set will eventually contain all the monitoring points that have been screened and determined for subsequent construction monitoring and data analysis. Through the above method, the constraints of the physical model of the construction structure, the abnormal points in the historical construction records, and the spatial distribution of the monitoring points are comprehensively considered to select the most appropriate monitoring points to achieve effective monitoring and data analysis of the construction process.

[0017] When a first real-time water pressure at a first monitoring point meets a 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 in real time by a first water pressure sensor deployed at the first monitoring point; During the construction process, each monitoring point deployed in the predetermined monitoring point set is equipped with a corresponding water pressure sensor, for example, the first water pressure sensor corresponds to the first monitoring point, etc. The water pressure sensor can collect and transmit the water pressure data of the location in real time, that is, the first real-time water pressure, and the collected first real-time water pressure data will be compared with the predetermined water pressure threshold. The water pressure threshold is usually set after comprehensive analysis of engineering requirements, safety standards and historical data, aiming to ensure that the water pressure during the construction process is within a safe and controllable range. If the first real-time water pressure data exceeds or falls below 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 the subsequent future water pressure prediction based on the normal water pressure, so as to timely predict whether the future water pressure is normal and take measures in time, wherein the first monitoring point is any monitoring point in the predetermined monitoring point set, and the first real-time water pressure is the water pressure monitored in real time by the first water pressure sensor deployed at the first monitoring point. According to the above method, through real-time monitoring, data analysis, prediction instruction generation and other links, accurate control and timely response of the water pressure status during the construction process are achieved, providing strong technical support for construction safety and quality control.

[0018] Obtain the first monitoring optimization constraint; Set the first monitoring and optimization evaluation index; Under the first monitoring optimization constraint, the monitoring frequency is globally optimized in a predetermined optimization space in combination with the first monitoring optimization evaluation index 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.

[0019] Before optimizing the monitoring frequency, it is necessary to first clarify the constraints in the optimization process, namely the first monitoring optimization constraints, including the working range of the sensor, monitoring cost restrictions, construction environment requirements, etc. These constraints will serve as constraints in the subsequent optimization process to ensure that the optimization results meet actual needs and feasibility. In order to measure the pros and cons of different monitoring frequencies, it is necessary to set corresponding evaluation indicators, namely the first monitoring optimization evaluation indicators, including the accuracy, real-time performance, and monitoring cost of the monitoring data. By comprehensively considering these indicators, the effectiveness of different monitoring frequencies can be more comprehensively evaluated to find the optimal solution. After determining the constraints and evaluation indicators, it is necessary to perform global optimization in the predetermined optimization space. The predetermined optimization space refers to the first predetermined monitoring frequency range of the first water pressure sensor, that is, to find the optimal monitoring frequency within this range. After global optimization, an optimal monitoring frequency that meets the constraints and evaluation indicators will be obtained, namely the first optimal monitoring frequency. This frequency will serve 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 first optimal monitoring frequency obtained. This will ensure that accurate and real-time water pressure data is obtained at the optimal monitoring frequency, providing strong support for monitoring and decision-making during the construction process. Through the above method, the constraints are clarified, the evaluation indicators are set, and the global optimization is performed, which realizes the optimal selection of the monitoring frequency, improves the accuracy and real-time nature of the monitoring data, and provides an important basis for the control and decision-making of the construction process.

[0020] The first monitoring optimization constraint includes the real-time construction stage of the super-long basement 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 series of the first monitoring point.

[0021] The structural characteristics, load conditions, construction methods, etc. of different construction stages will be different. These differences will directly affect the distribution and changes of water pressure. Therefore, the real-time construction stage as one of the constraints 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. Ambient humidity is an important factor affecting the performance of water pressure sensors and the accuracy of monitoring data. High humidity environment may cause condensation or corrosion inside the sensor, which in turn affects its measurement accuracy and stability. Therefore, taking the first real-time ambient humidity as one of the constraints can ensure that the impact of environmental factors on sensor performance is taken into account when optimizing the monitoring frequency, thereby avoiding high-frequency monitoring in unfavorable 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. The water pressure changes of different frequency components have different effects on structural safety. Therefore, by analyzing the spectral density, it can be determined which frequency components need to be focused on. Taking the first spectral density as one of the constraints can take into account the frequency characteristics of water pressure changes when optimizing the monitoring frequency, thereby ensuring sufficient monitoring in key frequency bands and improving the pertinence and effectiveness of monitoring data. In summary, the constraints 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 constraints need to be comprehensively considered to find the optimal monitoring frequency that meets actual needs and feasibility.

[0022] 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.

[0023] The first monitoring optimization evaluation index includes the first monitoring efficiency and the first monitoring quality. The first monitoring efficiency is characterized by the first data change rate. The first monitoring efficiency reflects the speed and ability to obtain effective monitoring data within a given time. The first data change rate refers to the ratio of the change amplitude of the monitoring data to the change frequency, which can reflect the effectiveness of the monitoring data and the rationality of the monitoring frequency. The first monitoring quality focuses on the accuracy and completeness of the monitoring data. The first monitoring quality is characterized by the first data missing rate. The first data missing rate 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 that the integrity and reliability of the monitoring data are higher, which can provide strong support for construction decisions. By optimizing the monitoring frequency to match the data change rate, the monitoring efficiency can be improved to ensure that effective monitoring data can be obtained in a timely manner. When optimizing the monitoring frequency, it is necessary to consider how to reduce the data missing rate, such as by increasing the redundancy of the sensor, optimizing the communication protocol, etc. to improve the stability and reliability of the data. As evaluation indicators, the first monitoring efficiency and the first monitoring quality together constitute an important basis for optimizing the monitoring frequency. By comprehensively considering these two indicators, it is possible to ensure that when optimizing the monitoring frequency, both the speed and ability of data acquisition can be improved, and the accuracy and completeness of the data can be guaranteed, thereby providing comprehensive and accurate information support for the control and decision-making of the construction process.

[0024] Reading a predetermined sensor loss analysis function; Performing loss adjustment on the first real-time water pressure monitored in real time by the first water pressure sensor according to the predetermined sensor loss analysis function; Wherein, the expression of the predetermined sensor loss analysis function is as follows: ; Refers to the first real-time water pressure With the first real-time water pressure loss adjustment results The predetermined sensor loss analysis function between It refers to the construction vibration feedback coefficient of the super-long basement structure. It refers to the construction environment feedback coefficient of the super-long basement structure. It refers to the equipment accuracy feedback coefficient of the first water pressure sensor.

[0025] The predetermined sensor loss analysis function is pre-set based on factors such as the characteristics of the sensor, historical data, and environmental conditions. The purpose is to analyze the data loss or error that may occur in the monitoring process of the sensor, and to quantify the loss of sensor data. After reading the loss analysis function, the system needs to apply it to the first real-time water pressure data monitored by the first water pressure sensor in real time, in order to correct or compensate the original monitoring data to eliminate or reduce 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 a linear or nonlinear transformation on the original data according to the distribution law of the sensor error, or correct the data according to environmental humidity, temperature and other conditions. Through loss adjustment, the system can provide more accurate and reliable water pressure monitoring data, and provide a more precise basis for construction management and decision-making. Among them, the expression of the predetermined sensor loss analysis function is as follows: ; Refers to the first real-time water pressure With the first real-time water pressure loss adjustment results The predetermined sensor loss analysis function between It refers to the construction vibration feedback coefficient of the super-long basement structure. It refers to the construction environment feedback coefficient of the super-long basement structure. Refers to the equipment accuracy feedback coefficient of the first water pressure sensor. Through the above method, customization and optimization are performed according to the actual application scenario and sensor characteristics to ensure the effectiveness of loss adjustment. It can ensure the real-time and accuracy of data.

[0026] Based on the first prediction instruction, a predetermined water pressure factor is retrieved to collect information on the first monitoring point to obtain first factor information; According to the specific content of the first prediction instruction, the predetermined water pressure factor is retrieved, and the water pressure factor includes geological dimension factor, climate dimension factor, construction dimension factor and material dimension factor, which are predetermined and stored in the system so that they can be quickly retrieved when needed. After retrieving the predetermined water pressure factor, the system starts to collect information for the first monitoring point, including field measurement, sensor reading, historical data query and other methods. The collected information is intended to reflect the current water pressure status 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. The first factor information is an important basis for subsequent analysis and decision-making, which not only reflects the current water pressure status, but also reveals potential risks or trends. Through the above method, through the preset rules and algorithms, the system can quickly respond to the prediction instruction, retrieve the appropriate water pressure factor, and effectively collect information. This helps to timely discover and deal with water pressure anomalies and ensure 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 this information, the laws and causes of water pressure changes can be further understood, providing strong support for optimizing construction plans and ensuring construction safety.

[0027] 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 permeability and groundwater flow rate, the climate dimension factors include precipitation and ambient temperature, the construction dimension factors include construction vibration and construction drainage, and the material dimension factors refer to material waterproofness.

[0028] The predetermined water pressure factors include geological dimension factors, climate dimension factors, construction dimension factors and material dimension factors. The geological dimension factors include soil permeability and groundwater flow rate. Soil permeability is the ability of soil to penetrate water, which directly affects the distribution and change of groundwater level, and thus 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 factors include precipitation and ambient temperature. Precipitation is one of the main sources of groundwater recharge. The amount of precipitation directly determines the amount of groundwater recharge, thus affecting water pressure; temperature changes in ambient temperature may affect the expansion and contraction of soil, thus affecting groundwater flow and water pressure; the construction dimension factors include construction vibration and construction drainage. The vibration generated by construction activities such as excavation and piling in construction vibration may affect soil structure and groundwater flow; construction drainage is the drainage activity during basement construction that will affect groundwater level and water pressure; the material dimension factors refer to the waterproofness of the material. The waterproof performance of the building materials used directly affects the penetration and accumulation of water in the structure, thus affecting water pressure. By combining the above-mentioned predetermined water pressure factors, the changing trend of water pressure can be predicted and analyzed more comprehensively and accurately, providing support for decision-making during the construction process. 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.

[0029] Marking a first predicted water pressure obtained by analyzing the first factor information through a water pressure prediction model to the physical model of the construction structure to obtain a water pressure prediction diagram of the construction structure; The water pressure prediction model predicts future water pressure changes based on the input water pressure factor information, considers the interaction and influence between various factors, and outputs the prediction results of future water pressure through complex calculations and analysis. After analyzing the first factor information, the water pressure prediction model will output a prediction value, namely the first predicted water pressure, which represents the model's estimation 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 physical model of the construction structure to intuitively display the relationship between the construction structure and the water pressure distribution. By marking the predicted water pressure, abstract data can be converted into a specific graphic display. After marking and integration, a construction structure water pressure prediction map is produced. The construction structure water pressure prediction map shows the morphology and characteristics of the construction structure, and also represents the distribution and changes of the predicted water pressure through different colors, lines or other graphic elements, so that technical personnel can intuitively understand the water pressure status of the construction structure in different areas and at different time points, providing strong support for construction decisions. Through the above method, the water pressure prediction model is continuously trained and optimized according to actual data and needs to improve the prediction accuracy and practicality.

[0030] Extracting a first grid from a construction structure grid set obtained by gridding the construction structure water pressure prediction map, wherein the first grid corresponds to first coordinate information; Determine whether a water pressure sensor is deployed in the first coordinate information corresponding to the first grid; If not deployed, taking the first center point of the first grid as the first point to be interpolated; Acquire a first search neighborhood of the first to-be-interpolated point based on a predetermined neighborhood scheme, wherein the first search neighborhood includes a plurality of neighborhood grids, and the plurality of neighborhood grids correspond one-to-one to the predicted water pressures of the plurality of neighborhood grids; Acquire first neighborhood coordinate information of a first neighborhood grid among the multiple neighborhood grids, and perform calculation with the first coordinate information to obtain a first distance; Traversing 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; Using the mean value of the first weighted water pressure as the first interpolation water pressure of the first point to be interpolated; The first interpolated water pressure is added to the construction structure water pressure prediction map, and the construction structure water pressure contour map is obtained through analysis.

[0031] The water pressure prediction map of the construction structure is meshed to obtain a construction structure mesh set, wherein the construction structure mesh set refers to a collection of meshes after the water pressure prediction map of the construction structure is meshed, wherein meshing refers to the process of dividing the water pressure prediction map of the construction structure into multiple small units, such as rectangular mesh difference meshing, finite element triangular meshing, etc., and the mesh size is set by technical personnel in this field 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, and the coordinate information is the position information of the first mesh in the water pressure prediction map of the construction structure; according to the first coordinate information, it is determined whether a water pressure sensor has been deployed at the location, and if not, interpolation processing is required, and interpolation processing is usually used to fill in areas where data is missing. If the water pressure sensor is not deployed at the first grid, then the center point of the first grid is determined as the first point to be interpolated. The selection of the interpolation point is usually based on the center point of the grid, because this can represent the water pressure situation of the entire grid to a certain extent. According to the predetermined neighborhood scheme, for example, several grids closest to the point to be interpolated are selected to obtain the first search neighborhood of the first point to be interpolated. The first search neighborhood refers to a set of grids around the first point to be interpolated, which is used for subsequent calculations; a neighborhood grid, namely the first neighborhood grid, 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 grid and the first coordinate information is calculated to obtain the first distance. The first distance is used for subsequent weighted calculations. The closer the grid point is to the point to be interpolated, the greater the impact of its predicted water pressure on the interpolation result should be. The predicted water pressure of all neighborhood grids in the first search neighborhood is traversed. For each neighborhood grid, the predicted water pressure and the corresponding first distance are weightedly calculated to obtain the weighted water pressure of the grid. The purpose of weighted calculation is to take into account the difference in the influence of different neighborhood grids on the water pressure of the interpolation point. The weighted water pressure of all neighborhood grids is 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 grid, which can fill the water pressure data of the area where the sensor is not deployed. The calculated first interpolation water pressure is added to the construction structure water pressure prediction map to fill the original 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 intuitively show the distribution of water pressure in different areas, which is helpful for construction management and decision-making. Through the above method, through gridding, interpolation calculation and contour line 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 during construction.

[0032] A water pressure prediction abnormal area is obtained based on a construction structure water pressure contour map obtained by performing spatial difference analysis on the construction structure water pressure prediction map, and a water pressure abnormality alarm is issued for the water pressure prediction abnormal area.

[0033] Analyze the water pressure contour map of the construction structure, study the contour map, observe the trend and change of water pressure distribution, pay attention to the dense areas or areas with sudden changes in the contour map, which indicate the existence of water pressure anomalies. Based on the range and speed of water pressure changes on the contour map, determine the area with water pressure anomalies. The abnormal area usually shows characteristics such as dense contour lines, unequal spacing or sudden interruption. According to the characteristics of the construction structure, design requirements and historical water pressure data, set a reasonable abnormal threshold. The abnormal threshold can be the absolute value of the water pressure, the rate of change or the relative difference with other areas, etc., which can be set by technicians in this field. Compare the set abnormal threshold with the contour map to identify the area where the water pressure exceeds or is lower than the threshold, which is the determined water pressure prediction abnormal area. Once the water pressure prediction abnormal area is determined, the alarm mechanism is triggered immediately, and the relevant personnel are warned by sending text messages, email notifications, displaying warning information on the monitoring interface, etc., to remind them to take necessary measures.

[0034] 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. And the above-mentioned specific embodiments of this specification are described. In addition, the processes depicted in the accompanying drawings do not necessarily require the specific order and continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0035] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0036] The above-mentioned embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the invention patent. It should be pointed out that, for ordinary technicians in this field, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application.

Claims

1. A method for monitoring underground water pressure in construction of ultra-long basement structures. It is characterized in that include: Analyze the physical model of the construction structure based on the multi-dimensional structural characteristics of the super-long basement structure and establish a set of predetermined monitoring points; When a first real-time water pressure at a first monitoring point meets a 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 in real time by a first water pressure sensor deployed at the first monitoring point; Based on the first prediction instruction, a predetermined water pressure factor is retrieved to collect information on the first monitoring point to obtain first factor information; Marking a first predicted water pressure obtained by analyzing the first factor information through a water pressure prediction model to the physical model of the construction structure to obtain a water pressure prediction diagram of the construction structure; A water pressure prediction abnormal area is obtained based on a construction structure water pressure contour map obtained by performing spatial difference analysis on the construction structure water pressure prediction map, and a water pressure abnormality alarm is issued for the water pressure prediction abnormal area.

2. According to the underground water pressure monitoring method of claim 1, It is characterized in that Establish a set of predetermined monitoring points, including: Analyzing the physical model of the construction structure to obtain a first initial monitoring point set that satisfies a first predetermined monitoring constraint; Extracting the first historical record from the historical construction groundwater pressure monitoring record of the super-long basement structure; forming a second initial monitoring point set based on the first groundwater 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 so, the first initial monitoring point is added to the predetermined monitoring point set.

3. According to the underground water pressure monitoring method of claim 1, It is characterized in that Also includes: Obtain the first monitoring optimization constraint; Set the first monitoring and optimization evaluation index; Under the first monitoring optimization constraint, the monitoring frequency is globally optimized in a predetermined optimization space in combination with the first monitoring optimization evaluation index 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. According to the underground water pressure monitoring method of claim 3, It is characterized in that The first monitoring optimization constraint includes the real-time construction stage of the super-long basement 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 series of the first monitoring point.

5. According to the underground water pressure monitoring method of claim 3, It is characterized in that 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 underground water pressure monitoring method according to claim 1, It is characterized in that Also includes: Reading a predetermined sensor loss analysis function; Performing loss adjustment on the first real-time water pressure monitored in real time by the first water pressure sensor according to the predetermined sensor loss analysis function; Wherein, the expression of the predetermined sensor loss analysis function is as follows: ； Refers to the first real-time water pressure With the first real-time water pressure loss adjustment results The predetermined sensor loss analysis function between It refers to the construction vibration feedback coefficient of the super-long basement structure. It refers to the construction environment feedback coefficient of the super-long basement structure. It refers to the equipment accuracy feedback coefficient of the first water pressure sensor.

7. The underground water pressure monitoring method according to claim 1, It is characterized in that 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 permeability and groundwater flow rate, the climate dimension factors include precipitation and ambient temperature, the construction dimension factors include construction vibration and construction drainage, and the material dimension factors refer to material waterproofness.

8. The underground water pressure monitoring method according to claim 1, It is characterized in that Before obtaining the water pressure prediction abnormal area according to the construction structure water pressure contour map obtained by performing spatial difference analysis on the construction structure water pressure prediction map, the method includes: Extracting a first grid in a construction structure grid set obtained by gridding the construction structure water pressure prediction map, wherein the first grid corresponds to first coordinate information; Determine whether a water pressure sensor is deployed in the first coordinate information corresponding to the first grid; If not deployed, taking the first center point of the first grid as the first point to be interpolated; Acquire a first search neighborhood of the first to-be-interpolated point based on a predetermined neighborhood scheme, wherein the first search neighborhood includes a plurality of neighborhood grids, and the plurality of neighborhood grids correspond one-to-one to the predicted water pressures of the plurality of neighborhood grids; Acquire first neighborhood coordinate information of a first neighborhood grid among the multiple neighborhood grids, and perform calculation with the first coordinate information to obtain a first distance; Traversing 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; Using the mean of the first weighted water pressures as the first interpolation water pressure of the first to-be-interpolated point; The first interpolated water pressure is added to the construction structure water pressure prediction map, and the construction structure water pressure contour map is obtained through analysis.

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