Supporting structure stress monitoring method and device for deep foundation pit construction and medium

Abstract

The invention discloses a supporting structure stress monitoring method and device for deep foundation pit construction and a medium, and relates to the field of intelligent construction sites. The method comprises the steps that in the construction stage of a deep foundation pit, environment data of a supporting structure at different monitoring positions and supporting structure body data are collected; obtaining theoretical support structure body data of the support structure at different monitoring positions according to a pre-constructed correction regression model and the environment data; obtaining deviation values of the supporting structure at different monitoring positions according to the theoretical payment structure body data and the supporting structure body data; correcting the data of the supporting structure body according to the deviation value; and performing correlation analysis on the corrected supporting structure body data at different monitoring positions so as to perform stress monitoring on the supporting structure. By correcting the body data of the supporting structure, the actual state of the supporting structure can be accurately reflected, and deviation data which is not interfered by the environment can be accurately reflected.

Description

Technical Field

[0001] This application relates to the technical field of intelligent construction sites, and specifically relates to a method, device, and medium for monitoring the stress of a supporting structure during deep foundation pit construction. Background Art

[0002] With the acceleration of the social construction process, the scale of underground space development is expanding day by day, the number of deep foundation pit projects is increasing day by day, and the construction safety of deep foundation pit projects is directly related to the safety of surrounding buildings, underground pipelines and other facilities, as well as the smooth progress of the project itself.

[0003] The supporting structure is a retaining, reinforcement and protection measure for the side wall and surrounding environment in deep foundation pit engineering to ensure the safety of underground structure construction and the surrounding environment. By monitoring the stress state of the supporting structure, the bearing capacity of the structure is evaluated to ensure construction safety.

[0004] However, due to the complex construction site environment of deep foundation pit projects, factors such as temperature, humidity, and vibration will affect the measurement accuracy of sensors, making it difficult to provide accurate and reliable stress data, which affects the evaluation results of the bearing capacity of the structure. Summary of the Invention

[0005] To solve the above problems, this application proposes a method for monitoring the stress of a supporting structure during deep foundation pit construction, including:

[0006] During the construction stage of the deep foundation pit, collect the environmental data and the data of the supporting structure itself at different monitoring positions;

[0007] According to the pre-constructed correction regression model and the environmental data, obtain the theoretical data of the supporting structure itself at different monitoring positions;

[0008] According to the theoretical data of the supporting structure itself and the data of the supporting structure itself, obtain the deviation amount of the supporting structure at different monitoring positions;

[0009] According to the deviation amount, correct the data of the supporting structure itself;

[0010] Conduct a correlation analysis on the corrected data of the supporting structure itself at different monitoring positions to monitor the stress of the supporting structure.

[0011] On the other hand, this application also proposes a device for monitoring the stress of a supporting structure during deep foundation pit construction, including:

[0012] At least one processor; and,

[0013] A memory communicatively connected to the at least one processor; wherein,

[0014] The memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to execute a stress monitoring method for a support structure in deep foundation pit construction as described in the above example.

[0015] On the other hand, the present application also proposes a non-volatile computer storage medium storing computer-executable instructions, and the computer-executable instructions are set as: a stress monitoring method for a support structure in deep foundation pit construction as described in the above example.

[0016] By proposing a stress monitoring method for a support structure in deep foundation pit construction by the present application, the following

[0017] beneficial effects can be brought:

[0018] By setting different acquisition frequencies at different construction stages, the monitoring frequency is dynamically adjusted according to the progress of the construction stage. When the stress and deformation of the support structure change greatly, the monitoring frequency can be increased in real time, making the data acquisition more targeted and timely.

[0019] By correcting the data of the support structure body, the actual state of the support structure can be accurately reflected, rather than the deviation data affected by the environment, providing a more accurate judgment basis for the construction team, helping to identify potential problems and avoiding wrong decisions caused by errors.

[0020] By stressing the data of the support structure body, the stress condition and deformation trend of the support structure can be accurately judged. During the excavation process, the construction method can be adjusted according to the stress monitoring results at different stages, such as reasonably arranging the construction sequence of the support structure and strengthening the support system to ensure the construction safety and smooth progress. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] The drawings described herein are used to provide a further understanding of the present application and form a part of the present application. The schematic embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation to the present application. In the drawings:

[0022] Figure 1 is a schematic flow chart of a stress monitoring method for a support structure in deep foundation pit construction in an embodiment of the present application;

[0023] Figure 2 is a schematic diagram of a stress monitoring device for a support structure in deep foundation pit construction in an embodiment of the present application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0024] To make the objectives, technical solutions, and advantages of this application clearer, the technical solutions of this application will be clearly and completely described below in conjunction with specific embodiments of this application and the corresponding drawings. Obviously, the described embodiments are only a part of the embodiments of this application, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments in this application without creative efforts belong to the scope of protection of this application.

[0025] The following will detail the technical solutions provided by each embodiment of this application in conjunction with the drawings.

[0026] As Figure 1 shown, an embodiment of this application provides a method for monitoring the stress of a retaining structure in deep foundation pit construction, including:

[0027] S101: During the construction stage of the deep foundation pit, collect the environmental data and the data of the retaining structure itself at different monitoring positions.

[0028] Specifically, the excavation depth of the deep foundation pit is monitored in real time to obtain the current excavation depth of the deep foundation pit. The current excavation depth is compared one by one with the depth ranges of each stage in the construction schedule to determine the construction stage corresponding to the range to which the current excavation depth belongs, which is the current construction stage of the deep foundation pit.

[0029] Furthermore, according to the current construction stage of the deep foundation pit, determine the current key monitoring objectives and corresponding monitoring points of the retaining structure in the deep foundation pit.

[0030] Among them, before deploying sensor devices in the deep foundation pit, it is necessary to determine in advance all the key monitoring objectives and corresponding monitoring points in the retaining structure. Specifically, according to the construction drawings of the deep foundation pit and the design drawings of the retaining structure, geometric models of each part such as the foundation pit, soil, retaining structure, and surrounding environment are constructed, corresponding parameter values are set for the shape parameters, material parameters of the retaining structure, and the soil environment parameters of the deep foundation pit. Based on the set parameter values, a finite element model of the retaining structure is constructed. Based on different construction conditions of the deep foundation pit, the boundary conditions of the finite element model are set, and the construction conditions are simulated through the finite element model to obtain the stress distribution of the retaining structure under different construction conditions.

[0031] According to the stress distribution, determine the key monitoring objectives of the retaining structure under different construction conditions, including displacement, deformation, stress distribution, soil pressure, etc. Set the area that has the greatest impact on the above key monitoring objectives as the monitoring points of the key monitoring objectives, including the areas with stress concentration, obvious deformation, and large changes in soil pressure in the retaining structure. Deploy sensor devices in advance at the monitoring point locations.

[0032] It should be noted that deep foundation pit construction usually has multiple different stages, each stage has its corresponding key monitoring targets, and the construction stages of deep foundation pits include earthwork excavation stage, support installation stage, bottom plate construction stage and support removal stage. When the deep foundation pit is in the earthwork excavation stage, the key monitoring targets include the displacement of the support structure, the soil settlement of the deep foundation pit and the groundwater level of the deep foundation pit; when the deep foundation pit is in the support installation stage, the key monitoring targets include the support axial force, the stress distribution of the support piles / walls, etc.; when the deep foundation pit is in the bottom plate construction stage, the key monitoring targets include the bottom plate settlement, the overall stability of the support structure, etc.; when the deep foundation pit is in the bottom plate construction stage, the key monitoring targets include the stress concentration of the support piles / walls, the deformation after the support is removed, etc.

[0033] Furthermore, when the construction stage changes, the collection frequency of the sensor device is adjusted based on the collection frequency corresponding to the different construction stages. When the predetermined collection time point is reached, the sensor device starts to collect data, including the collection of the support structure body data and environmental data of the support structure. Figure 2 The figure shows the design of sensor layout in deep foundation pit.

[0034] Furthermore, the data allowable fluctuation range corresponding to the acquisition frequency is obtained, the data change rate of the support structure body data is calculated, and it is determined whether the data change rate conforms to the data allowable fluctuation range. If not, the acquisition frequency of the sensor device is adjusted according to the data change rate. When it is determined that the data change rate is higher than the high change rate threshold in the data allowable fluctuation range, the acquisition frequency of the sensor device is gradually increased based on the preset step size. When it is determined that the data change rate is lower than the low change rate threshold in the data allowable fluctuation range, the acquisition frequency of the sensor device is gradually reduced based on the preset step size.

[0035] For example, the displacement sensor measures the displacement change of the support pile relative to the initial position in real time through the internal sensing element, and converts this change into an electrical signal output, and converts it into an intuitive displacement value, such as recording it in millimeters. For the axial force sensor, it converts the axial force borne by the internal support into an electrical signal for collection based on the deformation of the elastic element when it is subjected to force.

[0036] It should be noted that before the construction of the deep foundation pit, various sensors have been precisely deployed at the corresponding monitoring points according to the key monitoring targets of different construction stages. For example, during the earth excavation stage, in order to monitor the horizontal displacement of the support piles, displacement sensors were installed at key positions such as the pile top, middle and bottom of the pile body; in order to monitor the axial force of the internal support, axial force sensors were installed at the mid-span and end nodes of the internal support.

[0037] In addition, temperature sensors, humidity sensors, vibration sensors, etc. are also installed near the monitoring points. The ambient temperature at the construction site is measured in real time by the temperature sensor, the air humidity is measured by the humidity sensor, and the vibration generated during the construction process is monitored by the vibration sensor. The environmental data and the data of the support structure body are collected simultaneously and have the same time stamp.

[0038] Specifically, for the sensors with wired connections, the data is transmitted to the data acquisition terminal through the laid data lines (such as RS485, USB data lines, etc.). The data acquisition terminal converts the original signals transmitted by the sensors into a data format recognizable by a computer. For the sensors with wireless connections, such as the sensors using wireless communication technologies such as Bluetooth, Wi-Fi, 4G / 5G, etc., the data is directly sent to the nearby wireless receiving module, and then the wireless receiving module transmits the data to the data acquisition terminal. The data acquisition terminal packs the sorted data of the support structure body and the environmental data into data packets in a specific format at set time intervals. For example, the JSON (JavaScript Object Notation) format is used, and the data packets are sent to the database server through a network protocol (such as the TCP / IP protocol). After receiving the data packets, the database server parses the data and stores the data into the corresponding support structure body data table and environmental data table respectively according to the pre-designed database table structure.

[0039] S102: Obtain the theoretical support structure body data of the support structure at different monitoring positions according to the pre-constructed correction regression model and the environmental data.

[0040] S103: Obtain the deviation amount of the support structure at different monitoring positions according to the theoretical support structure body data and the support structure body data.

[0041] S104: Correct the support structure body data according to the deviation amount.

[0042] Specifically, the environmental data is preprocessed, and the preprocessed environmental data is input into the deployed correction regression model. The correction amount of the support structure body data is calculated through the correction regression model, and the support structure body data is corrected according to the correction amount.

[0043] In the embodiments of the present application, before deploying the modified regression model, it further includes: respectively statistically analyzing the correlation between each environmental data and the data of the support structure body, calculating the regression coefficient corresponding to the environmental data according to the correlation, constructing a modified regression model according to the regression coefficient, inputting historical environmental data into the modified regression model to obtain the historical correction amount output by the modified regression model, obtaining the modified historical support structure body data according to the historical correction amount, calculating the error between the modified historical support structure body data and the actual historical support structure body data, evaluating the correction effect, and optimizing the parameters of the modified regression model according to the correction result.

[0044] Specifically, calculate the Pearson correlation coefficient between the environmental data (temperature, humidity, air pressure, groundwater level) and the data of the support structure body (stress, displacement), and screen out the significantly correlated (for example, p-value < 0.05) environmental variables. Taking the data of the support structure body as the dependent variable Y and the environmental data as the independent variable X 1 、X 2 ……X n , establish a regression equation: Y = β 0 +β 1 X 1 +β 2 X 2 +……+β n X n +∈, where β i is the regression coefficient, which is solved by the least squares method.

[0045] After inputting the environmental data into the model, the theoretical data of the support structure body Y 理论 is output, and the correction amount is ΔY = Y 实际 -Y 理论 .

[0046] Furthermore, perform time series analysis on the deviation amount ΔY to extract the low-frequency component and the high-frequency component, where the low-frequency component is the systematic deviation ΔY 系统性 , and the high-frequency component is the high-frequency noise ΔY 噪声 . Through the formula: Y 修正 =Y 实际 -α·ΔY 系统性 calculate the corrected data of the support structure body, where α is the correction coefficient, and its range is between 0 and 1, which is used to control the correction amplitude.

[0047] It should be noted that during the verification process of the modified regression model, if the verification error of the modified regression model < 5%, α can be close to 1 to greatly correct the systematic deviation. If the error of the modified regression model > 10% and is close to α can be close to 0 to retain the characteristics of the actual data.

[0048] S105: Analyze the correlation of the corrected support structure body data at different monitoring positions to perform stress monitoring on the support structure.

[0049] Specifically, based on the ratio between the bearing capacity of the support structure and the corrected support structure body data, calculate the safety factor of the support structure, and determine whether the safety factor is lower than the preset safety threshold. If so, it is determined that the support structure is abnormal. Based on the abnormal type of the support structure, trigger an alarm and notify the construction personnel.

[0050] Among them, the designed bearing capacity F of the support structure 设计 can be calculated according to the material strength (such as concrete compressive strength, steel yield strength) and structural geometric parameters. According to the safety factor calculation formula: where F 实际 is the corrected support structure body data (such as the actual stress value). In the embodiments of the present application, the preset safety threshold can be set to 1.5. When SF < 1.5, an alarm is triggered.

[0051] Furthermore, obtain the safety value difference between the safety factor and the preset safety threshold. When the safety value difference is higher than the preset abnormal threshold, it is determined that the support structure has structural deformation abnormality. When the safety value difference is not higher than the preset abnormal threshold, it is determined that the support structure has support force abnormality. Based on the corresponding abnormal types, generate corresponding support structure adjustment suggestions, trigger an abnormal alarm, and send the support structure adjustment suggestions to the construction personnel.

[0052] It should be noted that in addition to paying attention to whether the instantaneous value of the support structure body data is within the safe range, it is also necessary to analyze the change trend of the support structure body data. If the stress or displacement and other indicators of the support structure are within the safety threshold currently, but show a continuous and rapid growth trend, it also indicates that there may be potential safety risks for the support structure. For example, if the stress value of the support structure increases by more than the designed allowable growth rate per week during a certain period of time, even if the current stress value has not reached the upper limit of the safety threshold, it is necessary to pay close attention and take corresponding measures, such as increasing the monitoring frequency, strengthening the support structure, etc. By comprehensively considering the instantaneous value and change trend of the support structure body data, it is possible to more accurately judge whether the current state of the support structure is within the safe range, providing a strong basis for the safety decision-making of deep foundation pit construction.

[0053] In the embodiments of the present application, by setting different acquisition frequencies at different construction stages, the monitoring frequency is dynamically adjusted according to the progress of the construction stage. When the stress and deformation of the support structure change greatly, the monitoring frequency can be increased in real time, making the data acquisition more targeted and timely.

[0054] By correcting the data of the support structure body, the actual state of the support structure can be accurately reflected, rather than the deviation data affected by the environment, providing a more accurate judgment basis for the construction team, helping to identify potential problems and avoid wrong decisions caused by errors.

[0055] By stressing the data of the support structure body, the stress condition and deformation trend of the support structure can be accurately judged. During the excavation process, the construction method is adjusted according to the stress monitoring results at different stages, such as reasonably arranging the construction sequence of the support structure and strengthening the support system to ensure the safety and smooth progress of the construction.

[0056] As Figure 2 shown, the embodiment of the present application also proposes a stress monitoring device for the support structure in deep foundation pit construction, including:

[0057] At least one processor; and,

[0058] A memory communicatively connected to the at least one processor; wherein,

[0059] The memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute a stress monitoring method for the support structure in deep foundation pit construction as described in any one of the above embodiments.

[0060] The embodiment of the present application also provides a non-volatile computer storage medium storing computer-executable instructions, and the computer-executable instructions are set to: a stress monitoring method for the support structure in deep foundation pit construction as described in any one of the above embodiments.

[0061] The embodiments in the present application are all described in a progressive manner. The same or similar parts among the embodiments can be referred to each other, and the differences between each embodiment and other embodiments are emphasized. In particular, for the device and medium embodiments, since they are basically similar to the method embodiments, the description is relatively simple, and the relevant parts can refer to the partial description of the method embodiments.

[0062] The devices and media provided by the embodiments of the present application correspond one by one to the methods. Therefore, the devices and media also have beneficial technical effects similar to those of their corresponding methods. Since the beneficial technical effects of the methods have been described in detail above, the beneficial technical effects of the devices and media are not elaborated here.

[0063] Those skilled in the art should understand that the embodiments of the present invention can be provided as a method, a system, or a computer program product. Therefore, the present invention can take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present invention can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk memory, CD-ROM, optical memory, etc.) that contain computer-usable program code.

[0064] The present invention is described with reference to the flowcharts and / or block diagrams of methods, apparatuses (systems), and computer program products according to embodiments of the present invention. It should be understood that each flow and / or block in the flowcharts and / or block diagrams, and the combination of flows and / or blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, such that the instructions executed by the processor of the computer or other programmable data processing devices generate means for implementing the functions specified in Figure 1 one flow or multiple flows and / or blocks Figure 1 one block or multiple blocks.

[0065] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, such that the instructions stored in the computer-readable memory generate a manufactured article including instruction means that implement the functions specified in Figure 1 one flow or multiple flows and / or blocks Figure 1 one block or multiple blocks.

[0066] These computer program instructions can also be loaded onto a computer or other programmable data processing device, such that a series of operation steps are executed on the computer or other programmable device to generate a computer-implemented process, and thus the instructions executed on the computer or other programmable device provide steps for implementing the functions specified in Figure 1 one flow or multiple flows and / or blocks Figure 1 one block or multiple blocks.

[0067] In a typical configuration, a computing device includes one or more processors (CPUs), an input / output interface, a network interface, and memory.

[0068] The memory may include non-permanent memory in the form of computer-readable media, random access memory (RAM), and / or non-volatile memory such as read-only memory (ROM) or flash memory (flash RAM). The memory is an example of computer-readable media.

[0069] A computer-readable medium includes permanent and non-permanent, removable and non-removable media and can implement information storage by any method or technology. The information can be computer-readable instructions, data structures, program modules, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transitory media that can be used to store information accessible by a computing device. As defined herein, computer-readable media does not include transitory computer-readable media, such as modulated data signals and carrier waves.

[0070] It should also be noted that the term "comprising", "including" or any other variant thereof is intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an..." does not exclude the presence of additional identical elements in the process, method, article, or apparatus that comprises the element.

[0071] The above description is only for the embodiments of the present application and is not intended to limit the present application. For those skilled in the art, various changes and modifications can be made to the present application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included within the scope of the claims of the present application.

Claims

1. A method for monitoring stress of a support structure in deep foundation pit construction, characterized in that: include: During the construction phase of the deep foundation pit, the environmental data of the support structure and the data of the support structure itself at different monitoring locations are collected; According to the pre-constructed modified regression model and the environmental data, the theoretical support structure ontology data of the support structure at different monitoring positions are obtained; According to the theoretical payment structure body data and the support structure body data, the deviation amount of the support structure at different monitoring positions is obtained; According to the deviation, the support structure body data is corrected; Correlation analysis is performed on the modified support structure body data at different monitoring positions to perform stress monitoring on the support structure.

2. A method for monitoring stress of a supporting structure in deep foundation pit construction according to claim 1, characterized in that: In the construction stage of the deep foundation pit, before collecting the environmental data of the supporting structure at different monitoring positions and the supporting structure body data, the method further includes: Determine the current acquisition frequency corresponding to the current construction stage of the deep foundation pit; Obtain the data allowable fluctuation range corresponding to the current acquisition frequency.

3. A method for monitoring stress of a supporting structure in deep foundation pit construction according to claim 2, characterized in that: During the construction phase of the deep foundation pit, after collecting environmental data and body data of the supporting structure at different monitoring positions, the method further includes: Calculating the data change rate of the supporting structure body data, and determining whether the data change rate conforms to the data allowable fluctuation range; If not, the acquisition frequency of the monitoring position sensor device is adjusted based on a preset step size according to the data change rate.

4. The method for monitoring stress of a supporting structure in deep foundation pit construction according to claim 1, characterized in that: Before obtaining theoretical support structure ontology data of the support structure at different monitoring positions according to the pre-constructed modified regression model and the environmental data, the method further includes: Acquire historical environmental data and historical supporting structure body data of the supporting structure, and calculate the linear correlation between the historical environmental data and the historical supporting structure body data respectively; Based on the linear correlation, significantly correlated variables of the historical environmental data are screened to construct a multivariate linear regression model; The regression coefficients corresponding to the significantly correlated variables in the multivariate linear regression model are calculated by the least squares method, and the regression coefficients are optimized by an optimization method to obtain a modified regression model.

5. The method for monitoring stress of a supporting structure in deep foundation pit construction according to claim 1, characterized in that: The method of obtaining theoretical support structure ontology data of the support structure at different monitoring positions based on the pre-constructed modified regression model and the environmental data specifically includes: Preprocessing the environmental data at the different monitoring locations, and inputting the preprocessed environmental data into the modified regression model; The theoretical supporting structure ontology data of the supporting structure at different monitoring positions are obtained.

6. A method for monitoring stress of a supporting structure in deep foundation pit construction according to claim 5, characterized in that: The step of correcting the support structure body data according to the deviation specifically includes: Analyze the deviation based on the time series to extract the systematic deviation and high-frequency noise in the deviation; According to the systematic deviation, the support structure body data is corrected.

7. The method for monitoring stress of a supporting structure in deep foundation pit construction according to claim 1, characterized in that: The correlation analysis of the modified support structure body data at different monitoring positions to monitor the stress of the support structure specifically includes: Based on the relationship between the bearing capacity of different monitoring positions of the support structure and the modified support structure body data, the safety factors of the different monitoring positions are calculated to determine whether the safety factors are lower than a preset safety threshold; If so, it is determined that an abnormality exists at the corresponding monitoring location, and based on the type of abnormality at the corresponding monitoring location, an early warning is triggered and the construction personnel are notified.

8. A method for monitoring stress of a supporting structure in deep foundation pit construction according to claim 7, characterized in that: The triggering of an early warning and notifying construction personnel based on the abnormal type of the corresponding monitoring location specifically includes: Obtaining a safety value difference between the safety factor and the preset safety threshold; When the safety value difference is higher than a preset abnormality threshold, it is determined that there is a structural deformation abnormality at the corresponding monitoring position; When the safety value difference is not higher than the preset abnormality threshold, it is determined that there is a support force abnormality at the corresponding monitoring position; Based on the corresponding abnormality types, corresponding support structure adjustment suggestions are generated, abnormality warnings are triggered, and the support structure adjustment suggestions are sent to construction personnel.

9. A support structure stress monitoring device for deep foundation pit construction, characterized in that: include: at least one processor; as well as, a memory communicatively connected to the at least one processor; wherein, The memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute a method for monitoring stress of a support structure for deep foundation pit construction as described in any one of claims 1 to 8.

10. A non-volatile computer storage medium storing computer executable instructions, characterized in that: The computer executable instructions are set to: a method for monitoring stress of a support structure in deep foundation pit construction as described in any one of claims 1 to 8.

Images