Method and system for calculating stability of underground diaphragm wall of subway station

Abstract

The invention provides a stability calculation method and system for an underground diaphragm wall of a subway station. The stability calculation method comprises the following steps: S101, obtaining a construction plan of the underground diaphragm wall; s102, a construction acquisition device is used for measurement, and pouring depth data of a current construction groove section and liquid level data of a dewatering well corresponding to the current construction groove section are obtained in real time; s104, after pouring of the current construction groove section is completed, perpendicularity data of the side wall of the construction groove section is obtained through an ultrasonic detection device, and when the perpendicularity data is within the corresponding preset range, a change curve of the perpendicularity data and the pouring depth data and a change curve of the liquid level data are input into the stability scoring model; and the next construction groove section serves as the current construction groove section, and S102 is executed. The stability calculation in the construction process of the underground diaphragm wall is realized by comprehensively considering the change of the perpendicularity data and the pouring depth data and the liquid level data.

Description

Technical Field

[0001] The present application relates to the technical field of construction quality stability calculation, and in particular to a stability calculation method and system for an underground continuous wall of a subway station. Background Art

[0002] With the rapid development of the national rail transit industry, underground continuous walls have been widely used as an excellent structural engineering for the enclosure of subway stations. However, the structure of underground continuous walls will face many difficulties when constructed under some complex geological conditions. Take the case of a thick, water-rich, weak, fine sand layer as an example. Under this geological condition, the soil layer has high liquefaction and poor self-stability, which makes it easy for soil disturbance to occur. The underground continuous wall groove wall is prone to shrinkage, exposed reinforcement, landslides, and mud in the joints. It will also cause sand and water leakage at the excavation of the underground continuous wall joints, the steel cage cannot be lowered into place, and the wall surface bulges over a large area, which seriously affects the safe excavation of the foundation pit. Most of the related technologies are improved by controlling the quality of the mud. Although the possibility of these problems has been reduced to a certain extent, there is still uncertainty. The stability calculation of the underground continuous wall is particularly important under such geological conditions. The related technology also proposes technical means for monitoring the force of the continuous wall.

[0003] For example, application number CN202110965412.9 discloses that based on dynamic back-analysis calculation and fusion algorithm and intelligent monitoring system, the collected deep horizontal displacement monitoring data is fed back to the intelligent monitoring platform to form a real-time displacement change curve, and the deformation of underground continuous wall, internal force of underground continuous wall, horizontal displacement and vertical displacement of underground continuous wall top are monitored through a dynamic back-analysis calculation and fusion algorithm. In other words, it mainly focuses on the analysis and calculation of monitoring displacement and deformation data after the overall construction is completed. What it discloses is not a calculation method based on the data of underground continuous wall during the construction process of underground continuous wall, and is not suitable for timely adjustment of construction during the construction process.

[0004] For example, application number CN201910441572.6 discloses a device for automatic underwater multi-parameter detection of underground continuous walls, which can replace the original laborious and time-consuming manual random point selection inspection working method. However, since it is suitable for underground continuous walls that serve as water interception, anti-seepage, load-bearing, and water retaining structures of docks, the provided multi-parameter automatic detection device mainly transmits back and displays the underwater detection images and data of underwater execution equipment in a timely manner, and is not suitable for non-dock application scenarios and is not suitable for underground continuous wall construction in subway stations.

[0005] Based on this, the present application aims to provide a stability calculation method and system for underground continuous walls of subway stations to solve the above-mentioned problems. Summary of the invention

[0006] The purpose of the present application is to provide a method and system for calculating the stability of underground continuous walls of subway stations, which solves the problem of lack of means for calculating the stability of underground continuous walls of subway stations.

[0007] The purpose of this application is achieved by the following technical solutions:

[0008] The present application provides a stability calculation method for an underground continuous wall of a subway station, the stability calculation method comprising:

[0009] S101, obtaining a construction plan of the underground continuous wall;

[0010] S102, pouring concrete in the current construction slot section according to the construction plan, using a construction acquisition device to measure and obtain in real time the pouring depth data of the current construction slot section and the liquid level data of the precipitation well corresponding to the current construction slot section; the pouring depth data and the liquid level data are used to indicate changes in the pouring depth and the liquid level of the precipitation well, respectively;

[0011] S104, when the current construction slot section is poured, the verticality data of the side wall of the construction slot section is obtained by using an ultrasonic detection device. When the verticality data is within the corresponding preset range, the verticality data, the change curve of the pouring depth data and the change curve of the liquid level data are input into a stability scoring model to obtain the stability score of the current construction slot section and send it to the user device, and the next construction slot section is used as the current construction slot section and S102 is executed;

[0012] Wherein, the construction data collection device includes a pressure sensor arranged in a conduit of a construction trench section of the underground continuous wall and a liquid level sensor arranged in a dewatering well of the underground continuous wall.

[0013] Furthermore, the stability scoring model is obtained by training a deep learning model, and the training process of the stability scoring model includes the following steps:

[0014] Acquire a training set, the training set comprising a plurality of training data, each of the training data comprising verticality data, a pouring depth change curve and a liquid level change curve, and labeled data of stability scores corresponding to the verticality data, the pouring depth change curve and the liquid level change curve;

[0015] For each training data in the training set, perform the following processing:

[0016] Inputting the verticality data, the pouring depth change curve and the liquid level change curve in the training data into a preset deep learning model to obtain prediction data of the stability score corresponding to the verticality data, the pouring depth change curve and the liquid level change curve;

[0017] Based on the predicted data and the labeled data, updating the model parameters of the deep learning model;

[0018] Check whether the preset training end condition is met; if so, use the trained deep learning model as the stability scoring model; if not, continue to train the deep learning model using the next training data.

[0019] Furthermore, the stability calculation method further includes:

[0020] When the number of stability scores of the construction trench sections that have completed stability scoring meets the preset number, the stability calculation results of the underground continuous wall in the previous construction stage are obtained according to the stability score of each construction trench section that has completed stability scoring, the trench section key coefficient and the stability scoring standard, and the stability calculation results include normal and abnormal results;

[0021] When the stability calculation result is abnormal, abnormal prompt information is generated and sent to the user device.

[0022] Furthermore, the stability calculation method further includes:

[0023] S103, obtaining a water pump control signal according to the pouring depth data and the liquid level data, wherein the water pump control signal is used to control the water pump group of the dewatering well to pump water so that the water level of the dewatering well is lower than the current pouring height of the current construction trench section.

[0024] Furthermore, the method of obtaining the water pump control signal includes:

[0025] Obtaining target liquid level data corresponding to the pouring depth interval where the pouring depth data is located;

[0026] According to the target liquid level data and the liquid level data, a water pump control signal is generated in a PID manner to control the operation of the water pump group so that the actual liquid level meets the target liquid level requirement.

[0027] Further, the generating a water pump control signal in a PID manner according to the target liquid level data and the liquid level data includes:

[0028] Obtaining target liquid level data and predicted liquid level data corresponding to the pouring depth interval where the pouring depth data is located, wherein the predicted liquid level data is obtained according to a preset target liquid level curve;

[0029] When the difference between the target liquid level data and the predicted liquid level data is within the corresponding preset range, updating the target liquid level data according to the predicted liquid level data;

[0030] When the difference between the target liquid level data and the predicted liquid level data is not within the corresponding preset range, updating the target liquid level curve according to the target liquid level data;

[0031] The error is calculated based on the target liquid level data and the liquid level data, and the error is input into a preset PID control algorithm to obtain a water pump control signal.

[0032] Furthermore, a plurality of drainage wells are arranged in the foundation pit of the underground continuous wall, and each drainage well is used as a precipitation well for drainage before and during concrete pouring to lower the groundwater level, so that the moisture in the soil above the water level slope line seeps down, the fluidity of the soil is reduced, and the sandy soil layer is consolidated, thereby reducing the lateral pressure of the groundwater on the trench wall.

[0033] Furthermore, the construction plan of the underground continuous wall also includes: wrapping the soft soil layer on the steel cage of the underground continuous wall and within a range of 3m above and below with colored strips of cloth to isolate the contact between the soil and the steel bars on both sides of the construction trench section.

[0034] Furthermore, the conduit refers to the perfusion conduit of the current construction trench section.

[0035] In a second aspect, the present application further provides a stability calculation system for an underground continuous wall of a subway station, the stability calculation system comprising a controller, a construction collection device and an ultrasonic detection device connected to the controller, the construction collection device comprising a pressure sensor of a conduit arranged in a construction trench section of the underground continuous wall and a liquid level sensor arranged in a precipitation well of the underground continuous wall; the controller is configured as follows:

[0036] S101, obtaining a construction plan of the underground continuous wall;

[0037] S102, pouring concrete in the current construction slot section according to the construction plan, using a construction acquisition device to measure and obtain in real time the pouring depth data of the current construction slot section and the liquid level data of the precipitation well corresponding to the current construction slot section; the pouring depth data and the liquid level data are used to indicate changes in the pouring depth and the liquid level of the precipitation well, respectively;

[0038] S104, when the current construction slot section is cast, the verticality data of the side wall of the construction slot section is obtained by using an ultrasonic detection device. When the verticality data is within the corresponding preset range, the verticality data, the change curve of the casting depth data and the change curve of the liquid level data are input into a stability scoring model to obtain the stability score of the current construction slot section and send it to the user device to set the next construction slot section as the current construction slot section and execute S102.

[0039] Furthermore, the stability scoring model is obtained by training a deep learning model, and the training process of the stability scoring model includes the following steps:

[0040] Acquire a training set, the training set comprising a plurality of training data, each of the training data comprising verticality data, a pouring depth change curve and a liquid level change curve, and labeled data of stability scores corresponding to the verticality data, the pouring depth change curve and the liquid level change curve;

[0041] For each training data in the training set, perform the following processing:

[0042] Inputting the verticality data, the pouring depth change curve and the liquid level change curve in the training data into a preset deep learning model to obtain prediction data of the stability score corresponding to the verticality data, the pouring depth change curve and the liquid level change curve;

[0043] Based on the predicted data and the labeled data, updating the model parameters of the deep learning model;

[0044] Check whether the preset training end condition is met; if so, use the trained deep learning model as the stability scoring model; if not, continue to train the deep learning model using the next training data.

[0045] Furthermore, the controller is also configured to:

[0046] When the number of stability scores of the construction trench sections that have completed stability scoring meets the preset number, the stability calculation results of the underground continuous wall in the previous construction stage are obtained according to the stability score of each construction trench section that has completed stability scoring, the trench section key coefficient and the stability scoring standard, and the stability calculation results include normal and abnormal results;

[0047] When the stability calculation result is abnormal, abnormal prompt information is generated and sent to the user device.

[0048] Furthermore, the controller is also configured to:

[0049] S103, obtaining a water pump control signal according to the pouring depth data and the liquid level data, wherein the water pump control signal is used to control the water pump group of the dewatering well to pump water so that the water level of the dewatering well is lower than the current pouring height of the current construction trench section.

[0050] Furthermore, the controller obtains the water pump control signal in the following manner:

[0051] Obtaining target liquid level data corresponding to the pouring depth interval where the pouring depth data is located;

[0052] According to the target liquid level data and the liquid level data, a water pump control signal is generated in a PID manner to control the operation of the water pump group so that the actual liquid level meets the target liquid level requirement.

[0053] Furthermore, the controller generates a water pump control signal in a PID manner according to the target liquid level data and the liquid level data in the following manner:

[0054] Obtaining target liquid level data and predicted liquid level data corresponding to the pouring depth interval where the pouring depth data is located, wherein the predicted liquid level data is obtained according to a preset target liquid level curve;

[0055] When the difference between the target liquid level data and the predicted liquid level data is within the corresponding preset range, updating the target liquid level data according to the predicted liquid level data;

[0056] When the difference between the target liquid level data and the predicted liquid level data is not within the corresponding preset range, updating the target liquid level curve according to the target liquid level data;

[0057] The error is calculated based on the target liquid level data and the liquid level data, and the error is input into a preset PID control algorithm to obtain a water pump control signal.

[0058] Furthermore, a plurality of drainage wells are arranged in the foundation pit of the underground continuous wall, and each drainage well is used as a precipitation well for drainage before and during concrete pouring to lower the groundwater level, so that the moisture in the soil above the water level slope line seeps down, the fluidity of the soil is reduced, and the sandy soil layer is consolidated, thereby reducing the lateral pressure of the groundwater on the trench wall.

[0059] Furthermore, the construction plan of the underground continuous wall also includes: wrapping the soft soil layer on the steel cage of the underground continuous wall and within a range of 3m above and below with colored strips of cloth to isolate the contact between the soil and the steel bars on both sides of the construction trench section.

[0060] Furthermore, the conduit refers to the perfusion conduit of the current construction trench section.

[0061] The beneficial effects of the present application: through the collaborative calculation of multiple collected data, the construction safety and quality are ensured. Specifically, the concrete pouring of the current construction slot section is carried out according to the construction plan. The pouring depth data of the current construction slot section is obtained in real time by the pressure sensor arranged on the conduit, and the corresponding liquid level data is obtained in real time by the liquid level sensor arranged on the precipitation well. These data are used to indicate the changes in the pouring depth and the liquid level of the precipitation well. After the pouring of the current construction slot section is completed, the verticality data of the side wall of the construction slot section is obtained by an ultrasonic detection device. When the verticality data is within the preset range, the data and the change curve of the pouring depth data and the change curve of the liquid level data are input into the stability scoring model, and the stability score of the current construction slot section is generated and sent to the user device to realize the stability calculation of the underground continuous wall of the subway station.

[0062] The technical solution provided in this embodiment uses an ultrasonic detection device to obtain verticality data after each construction slot section is completed, and takes into account the changes in the pouring depth and the liquid level of the precipitation well during the pouring process, the impact on the stability of the underground continuous wall (the current construction slot section), combined with the pouring depth and liquid level data change curve, and a comprehensive evaluation is performed through a stability scoring model. The above calculation method provides a stability score that reflects the stability of the wall, and realizes the stability calculation of the underground continuous wall during the construction process. Once the stability obtained by monitoring is not ideal, the subsequent construction plan of the underground continuous wall can be adjusted in time. The pressure sensor, liquid level sensor and ultrasonic detection device are used in conjunction with the stability scoring model. The calculation results obtained make the monitoring and control process more intelligent and accurate. The construction acquisition device provided is more suitable for the stability calculation of the underground continuous wall of the subway station than the device for automatic underwater multi-parameter detection of the underground continuous wall mentioned in the background technology.

[0063] To sum up, this technical solution utilizes the changes in pouring depth and liquid level in the precipitation well reflected by the real-time acquired pouring depth data and liquid level data, and comprehensively considers the verticality data to participate in the stability calculation during the construction of the underground continuous wall, thereby effectively ensuring the stability and safety of the construction process. The stability calculation results provide a comprehensive stability monitoring and management method for the construction of the underground continuous wall, creating conditions for timely adjustment of the construction quality and construction plan, and ensuring the smooth progress of the project. BRIEF DESCRIPTION OF THE DRAWINGS

[0064] The present application is further described below in conjunction with the accompanying drawings and embodiments.

[0065] Figure 1 It is a flow chart of a stability calculation method provided in an embodiment of the present application.

[0066] Figure 2 It is a flow chart of obtaining a water pump control signal provided in an embodiment of the present application.

[0067] Figure 3 It is a flow chart of generating a water pump control signal provided in an embodiment of the present application.

[0068] Figure 4 It is a partial flow chart of a stability calculation method provided in an embodiment of the present application.

[0069] Figure 5 It is a flow chart of another stability calculation method provided in an embodiment of the present application. DETAILED DESCRIPTION

[0070] Below, in conjunction with the accompanying drawings and specific implementation methods, the present application is further described. It should be noted that, under the premise of no conflict, the various embodiments described below or the various technical features can be arbitrarily combined to form a new embodiment. The implementation procedures of the present application will be described below with reference to the accompanying drawings and preferred embodiments. Those skilled in the art can easily understand other advantages and effects of the present application from the contents disclosed in this specification. The present application can also be implemented or applied through other different specific implementation procedures, and the details in this specification can also be modified or changed in various ways based on different viewpoints and applications without departing from the spirit of the present application. It should be understood that the preferred embodiments are only for illustrating the present application, not for limiting the scope of protection of the present application.

[0071] Below, some terms in this application are explained to facilitate understanding by those skilled in the art.

[0072] The underground continuous wall is used to form the peripheral retaining structure of the underground structure. The underground continuous wall mentioned in this application refers to the underground continuous wall used to form the peripheral retaining structure of the subway station. It is used to withstand soil pressure and water pressure and transmit them to the deep stable soil layer to ensure the stability of the subway station structure.

[0073] Machine Learning (ML) is a multi-disciplinary subject involving probability theory, statistics, approximation theory, convex analysis, algorithm complexity theory, etc. By using statistical and algorithmic techniques, computers can learn from data and make decisions or predictions. The core concept is to use data to train models, and then use the trained models to score, predict or classify new data.

[0074] Deep learning is a special type of machine learning that achieves tremendous power and flexibility by learning to use nested hierarchies of concepts to represent, where each concept is defined in relation to simpler concepts, and more abstract representations are computed in less abstract ways. Machine learning and deep learning typically include artificial neural networks, belief networks, reinforcement learning, transfer learning, inductive learning, and teaching learning.

[0075] The main purpose of the stability calculation of the continuous wall is to ensure the safety and quality during the construction process, to prevent accidents such as wall instability and collapse caused by changes in groundwater, geological conditions or improper construction, so as to ensure the smooth progress of the project and the reliability of the final structure. The related technologies all consider the further calculation after the completion of the underground continuous wall construction, while the present application provides a stability calculation method and system for the underground continuous wall of the subway station. By reusing the pouring depth data and liquid level data obtained in real time, the pouring depth and the change of the liquid level of the precipitation well are reflected, and the stability calculation during the construction of the underground continuous wall is realized, which effectively ensures the stability and safety of the construction process. The stability calculation results provide a comprehensive stability monitoring and management means for the construction of the underground continuous wall, improve the construction quality and the conditions for timely adjustment of the construction plan, and ensure the smooth progress of the project. In specific applications, the stability calculation method provided by this application can be used to conduct preliminary and quick monitoring during the construction of the underground continuous wall, and then continue to monitor using the means provided by the relevant technology after the construction is completed. The following will first explain the method, and then explain the system, etc.

[0076] Method embodiment.

[0077] See also Figure 1 , Figure 1 It is a flow chart of a stability calculation method provided in an embodiment of the present application.

[0078] This embodiment provides a method for calculating the stability of an underground continuous wall of a subway station, including:

[0079] S101, obtaining a construction plan of the underground continuous wall;

[0080] S102, pouring concrete in the current construction slot section according to the construction plan, using a construction acquisition device to measure and obtain in real time the pouring depth data of the current construction slot section and the liquid level data of the precipitation well corresponding to the current construction slot section; the pouring depth data and the liquid level data are used to indicate changes in the pouring depth and the liquid level of the precipitation well, respectively;

[0081] S104, when the current construction slot section is cast, the verticality data of the side wall of the construction slot section is obtained by using an ultrasonic detection device. When the verticality data is within the corresponding preset range, the verticality data, the change curve of the casting depth data and the change curve of the liquid level data are input into a stability scoring model to obtain the stability score of the current construction slot section and send it to the user device; the next construction slot section is used as the current construction slot section and S102 is executed.

[0082] Wherein, the construction data collection device includes a pressure sensor arranged in a conduit of a construction trench section of the underground continuous wall and a liquid level sensor arranged in a dewatering well of the underground continuous wall.

[0083] The stability calculation method provided in this embodiment ensures construction safety and quality through the collaborative calculation of multiple collected data. Specifically, the concrete pouring of the current construction slot section is carried out according to the construction plan. The pouring depth data of the current construction slot section is obtained in real time by a pressure sensor arranged on the conduit, and the corresponding liquid level data is obtained in real time by a liquid level sensor arranged on the precipitation well. The obtained data is used to indicate the changes in the pouring depth and the liquid level of the precipitation well. After the pouring of the current construction slot section is completed, the verticality data of the side wall of the construction slot section is obtained by an ultrasonic detection device. When the verticality data is within a preset range, the data and the change curve of the pouring depth data and the change curve of the liquid level data are input into the stability scoring model, and the stability score of the current construction slot section is generated and sent to the user device to realize the stability calculation of the underground continuous wall of the subway station.

[0084] Among them, the pressure sensor can be installed on the inside or outside wall of the concrete pouring conduit of the underground continuous wall construction slot section, and the filling depth of the concrete can be inferred by monitoring the pressure change inside or outside the conduit. The conduit can be a perfusion conduit. As the pressure in the concrete perfusion conduit increases, the sensor converts the pressure into an electrical signal to reflect the pouring of the concrete in real time, and combines the depth of the perfusion conduit in the current construction slot section to monitor the pouring depth of the concrete in real time. The conduit can also be a conduit that is separately set in the construction slot section for the pressure sensor to monitor the filling depth of the concrete, so as to reflect the pouring of the concrete in real time. The liquid level sensor is installed in the precipitation well corresponding to the underground continuous wall, which is used to monitor the change of the groundwater level in the well in real time. The liquid level sensor mentioned in this application can be a resistive liquid level sensor, which detects the liquid level height by using the resistance change caused by the liquid level change. The ultrasonic detection device can measure the deviation of the concrete side wall from the vertical direction by emitting and receiving ultrasonic waves, and evaluate the verticality of the construction slot section after completion through the obtained verticality data. The verticality data can be expressed as an angle, that is, the angle at which the wall side wall of the construction slot section tilts to one side. In specific applications, the verticality data can be obtained by measuring the side wall on either side; or the verticality data of two adjacent construction trench sections can be obtained by measuring the side walls on different sides, for example, one construction trench section measures the inner side wall, and the other construction trench section measures the outer side wall. The advantage of this is that it avoids the need to perform the same calculation on the other side, thereby saving computing resources; a smaller amount of data can speed up data analysis, allowing users to make decisions faster. In this case, the verticality data also includes identification information of the measurement type to indicate how it is measured.

[0085] Compared with the related art, which only considers further calculation after the completion of the underground continuous wall construction, the technical solution provided in this embodiment uses an ultrasonic detection device to obtain verticality data after each construction slot section is completed, and takes into account the changes in the pouring depth and the liquid level of the precipitation well during the pouring process, and the impact on the stability of the underground continuous wall (the current construction slot section), combined with the pouring depth and liquid level data change curve, through the stability scoring model for comprehensive evaluation, and provides a stability score reflecting the stability of the wall through the above calculation method, so as to realize the stability calculation of the underground continuous wall during the construction process. Once the stability obtained by monitoring is not ideal, the subsequent construction plan of the underground continuous wall can be adjusted in time. The pressure sensor, liquid level sensor and ultrasonic detection device are used, and the calculation results obtained in conjunction with the stability scoring model make the monitoring and control process more intelligent and precise.

[0086] To sum up, this technical solution participates in the stability calculation during the construction of underground continuous walls by utilizing the changes in the pouring depth and liquid level in the precipitation wells reflected by the real-time acquired pouring depth data and liquid level data, thereby effectively ensuring the stability and safety of the construction process. The stability calculation results provide a comprehensive stability monitoring and management method for underground continuous wall construction, creating conditions for timely adjustment of construction quality and construction plans, and ensuring the smooth progress of the project.

[0087] At the same time, the construction collection device provided by the present technical solution is obviously more suitable for the stability calculation of the underground continuous wall of the subway station mentioned in this application than the device for automatic underwater multi-parameter detection of underground continuous walls mentioned in the background technology.

[0088] In an exemplary embodiment, the stability calculation method further includes:

[0089] S103, obtaining a water pump control signal according to the pouring depth data and the liquid level data, wherein the water pump control signal is used to control the water pump group of the dewatering well to pump water so that the water level of the dewatering well is lower than the current pouring height of the current construction trench section.

[0090] It can be understood that during the concrete pouring process, the pouring depth data and liquid level data acquired in real time are reused to generate a water pump control signal for controlling the water pump group of the dewatering well to pump water, ensuring that the water level of the dewatering well is always lower than the current pouring height of the current construction slot section, so as to reduce the lateral pressure of the groundwater on the slot wall and prevent the wall from collapsing. Among them, S103 can be executed after S102.

[0091] The advantage of this is that the calculation results can be used for real-time monitoring and the groundwater level can be controlled through the water pump control signal, which can reduce the pressure of groundwater on the trench wall, effectively prevent accidents such as trench wall collapse, and improve construction safety. By reusing the pouring depth data and liquid level data obtained in real time, the water pump control signal can be generated in time, the water pumping volume of the precipitation well can be dynamically adjusted, the appropriate groundwater level can be maintained, and the stability of the trench wall can be ensured. Reusing the pouring depth data and liquid level data for calculation can avoid repeated data collection and improve data utilization efficiency. By comprehensively utilizing the existing data, the water pump can be accurately controlled to ensure the construction stability of the underground continuous wall.

[0092] See also Figure 2 , Figure 2 It is a flow chart of obtaining a water pump control signal provided in an embodiment of the present application.

[0093] In an exemplary embodiment, the method of obtaining the water pump control signal includes:

[0094] S201, obtaining target liquid level data corresponding to the pouring depth interval where the pouring depth data is located;

[0095] S202, generating a water pump control signal in a PID manner according to the target liquid level data and the liquid level data, and controlling the operation of the water pump group so that the actual liquid level meets the target liquid level requirement.

[0096] First, determine the pouring depth interval according to the current pouring depth data, and each depth interval corresponds to a preset target liquid level data. It can be understood that multiple continuous pouring depth intervals are pre-set according to the engineering design and construction plan, and multiple continuous pouring depth intervals are, for example, greater than 33m and not less than 36m, greater than 36m and not less than 39m, etc., and then each pouring depth interval corresponds to a target liquid level data (for example, 30m, 33m, 45m). The pouring depth indicated by the pouring depth data is within which pouring depth interval, and the target liquid level data corresponding to the interval is used as the target liquid level data of the pouring depth data. It can be considered that the correspondence between the pouring depth interval and the target liquid level data is pre-set according to the engineering design and construction plan, reflecting the ideal state of the groundwater level or precipitation well water level expected in a specific depth interval.

[0097] The PID (proportional-integral-differential) control algorithm is used to generate a water pump control signal to regulate and control the operation of the water pump group. In specific operations, the target liquid level data and the (actual) liquid level data are first compared, and the error value is calculated as the deviation amount based on the difference between the actual liquid level and the target liquid level. The error amount indicates the distance between the current liquid level and the target liquid level, reflecting the degree of water pump regulation required. Among them, the PID control algorithm calculates the control outputs of the proportional term (P term), the integral term (I term) and the differential term (D term) according to the error amount. Specifically:

[0098] The proportional term (P term) refers to the generation of a control quantity proportional to the error based on the current error amount for immediate adjustment.

[0099] The integral term (I term) takes into account the cumulative history of errors and is used to eliminate long-term deviations.

[0100] The derivative term (D term) refers to the trend of the forecast error change and is used to suppress future overshoot.

[0101] The control quantity calculated by the PID algorithm is converted into the operating parameters of the water pump group, including start, stop, speed regulation and other instructions, to affect the pumping efficiency and water level regulation capacity of the water pump group.

[0102] The advantage of this is that by accurately matching the pouring depth interval with the target liquid level, the groundwater level or the water level of the precipitation well can be accurately controlled to meet the construction requirements at different depths. The target liquid level data can be obtained in intervals to maintain relatively stable control parameters within different pouring depth intervals. There is no need to respond to every tiny depth change, thus avoiding the need to frequently adjust the target liquid level data due to changes in the actual pouring depth, simplifying the complexity of real-time adjustment.

[0103] See also Figure 3 , Figure 3 It is a flow chart of generating a water pump control signal provided in an embodiment of the present application.

[0104] In an exemplary embodiment, the step of generating a water pump control signal in a PID manner according to the target liquid level data and the liquid level data includes:

[0105] S301, obtaining target liquid level data and predicted liquid level data corresponding to the pouring depth interval where the pouring depth data is located, wherein the predicted liquid level data is obtained according to a preset target liquid level curve;

[0106] S302, when the difference between the target liquid level data and the predicted liquid level data is within the corresponding preset range, updating the target liquid level data according to the predicted liquid level data;

[0107] S303, when the difference between the target liquid level data and the predicted liquid level data is not within the corresponding preset range, updating the target liquid level curve according to the target liquid level data;

[0108] S304, calculating an error based on the target liquid level data and the liquid level data, and inputting the error into a preset PID control algorithm to obtain a water pump control signal.

[0109] The target liquid level curve can be pre-set data in the construction plan, which is composed of a set of data points that describe the expected groundwater level height at different pouring depths. The data points in the target liquid level curve can be obtained through engineering design and simulation. In practical applications, the target liquid level curve can be discrete data points, or it can be obtained through interpolation or fitting to obtain a continuous curve form, so as to facilitate the acquisition of predicted liquid level data. In this case, the predicted liquid level data is a predicted value calculated based on the preset target liquid level curve and the current depth.

[0110] When the difference between the target liquid level data and the predicted liquid level data is within the preset range, the predicted liquid level data is directly used as the target liquid level data. This is because the target liquid level data in the specific application is obtained based on the interval of the pouring depth data, which is used to save the calculation process in the underground continuous wall construction process. The pouring depth data is a value obtained after processing the sensor signals obtained by multiple sensors to indicate the pouring depth situation, and the predicted liquid level data is calculated based on the system modeling when the construction plan is formulated. When the difference between the target liquid level data and the predicted liquid level data is within the preset range, it indicates that the prediction model is highly effective. The direct use of the predicted liquid level data can improve the prediction accuracy of the water pump group control process, and strengthen the decision-making process based on data, making the construction process more scientific and accurate. When the difference exceeds the preset range, the target liquid level curve will be adjusted and updated according to the target liquid level data obtained in the pouring depth interval, so that the target liquid level curve of the subsequent construction slot section can be used accurately.

[0111] The advantage of doing this is that the predicted liquid level data is calculated based on system modeling and historical data, reflecting the trend and law of groundwater level changes. Directly using the predicted liquid level data on the premise of accurate judgment of the target liquid level curve can improve the accuracy of predicting groundwater level changes during the control of the water pump group.

[0112] In an exemplary embodiment, when the difference between the target liquid level data and the predicted liquid level data is not within the corresponding preset range, updating the target liquid level curve according to the target liquid level data includes:

[0113] When the difference between the target liquid level data and the predicted liquid level data is not within the preset range, a new target liquid level curve is generated based on the target liquid level data using interpolation or fitting techniques. As an example, the SciPy library in Python is used for spline interpolation, the interp1d function in the SciPy library is used to create an interpolation function, and the interpolation function is used to generate an updated target liquid level curve.

[0114] In an exemplary embodiment, the stability scoring model is obtained by training a deep learning model, and the training process of the stability scoring model includes the following steps:

[0115] Acquire a training set, the training set comprising a plurality of training data, each of the training data comprising verticality data, a pouring depth change curve and a liquid level change curve, and labeled data of stability scores corresponding to the verticality data, the pouring depth change curve and the liquid level change curve;

[0116] For each training data in the training set, perform the following processing:

[0117] Inputting the verticality data, the pouring depth change curve and the liquid level change curve in the training data into a preset deep learning model to obtain prediction data of the stability score corresponding to the verticality data, the pouring depth change curve and the liquid level change curve;

[0118] Based on the predicted data and the labeled data, updating the model parameters of the deep learning model;

[0119] Check whether the preset training end condition is met; if so, use the trained deep learning model as the stability scoring model; if not, continue to train the deep learning model using the next training data.

[0120] The stability scoring model is used to predict the stability score of the construction slot section according to the changing trends of the pouring depth and the liquid level of the precipitation well obtained by the construction acquisition device and the verticality data after the pouring of the current construction slot section is completed. For example, during the training process, a large amount of sample data is used, including verticality data, pouring depth change curves and liquid level change curves, and corresponding stability scores. A preset deep learning model is trained with these data, and the parameters of the deep learning model are adjusted and updated using the back propagation algorithm based on the predicted data output by the deep learning model and the actual labeled stability score data, so that it can more accurately predict the impact of various variables on stability in the construction of underground continuous walls. Detect whether the preset training end conditions are met, such as reaching the maximum number of iterations or the model performance is stable within a certain threshold range. If the end conditions are met, the stability scoring model is obtained; if not, the model is continued to be trained using the next training data.

[0121] In a specific application, the pouring depth change curve can be represented as the first time series data of the pouring depth data, the liquid level change curve can be represented as the second time series data of the liquid level data, and the verticality data is represented as a single data point. The selected deep learning model is a fusion model, which combines a recurrent neural network (RNN), specifically using a long short-term memory network (LSTM) to process two time series data sets, and a convolutional neural network (CNN) to extract local features. The model includes a fully connected layer to process a single data point (verticality data). In the model architecture, the input layer receives two time series data sets (pouring depth change curve and liquid level change curve) and a verticality data point. In the feature extraction layer, for time series data, features are extracted using the LSTM layer and the CNN layer, and the verticality data point is directly fed to the fully connected layer. The fusion layer integrates different features to capture the relationship between them. The output layer finally outputs a stability score based on the fused features. In this way, complex nonlinear relationships can be captured and the accuracy and reliability of the score can be improved.

[0122] The advantage of this is that the use of deep learning models for training and predicting stability scores achieves a certain degree of automation. Deep learning models can learn and optimize based on a large amount of data, reducing the need for manual intervention and improving efficiency and consistency. By designing, establishing an appropriate number of neuron computing nodes and a multi-layer computing hierarchy, and selecting appropriate input and output layers, a preset deep learning model can be obtained. Through the learning and tuning of the deep learning model, a functional relationship from input to output is established. Although the functional relationship between input and output cannot be found 100%, it can be as close to the actual correlation as possible. The stability scoring model trained in this way can obtain the corresponding stability score based on the verticality data, pouring depth change curve and liquid level change curve of the same construction slot section, and the calculation results are accurate and reliable.

[0123] The embodiments of the present application can train to obtain a stability scoring model. In other optional embodiments, the present application can use a pre-trained stability scoring model. The preset deep learning model can be a convolutional neural network model or a recurrent neural network model. The present application does not limit the preset training end condition, which can be, for example, the number of training times reaches a preset number of times (the preset number of times is, for example, 1 time, 3 times, 10 times, 100 times, 1000 times, 10000 times, etc.), or the training data in the training set have completed one or more trainings, or the total loss value obtained in this training is not greater than the preset loss value.

[0124] The training data in the training set can be historical construction data and monitoring records, including verticality data, pouring depth change curves and liquid level change curves obtained from multiple sets of field data collection, as well as technicians' scores; it can be simulation data generated after modeling and simulation based on known physical models and assumptions to simulate the stability conditions under different combinations of verticality data, pouring depth change curves and liquid level change curves.

[0125] In specific applications, when the verticality data of two adjacent construction trench sections are obtained by measuring the sidewalls on different sides, the verticality data also includes the identification information of the measurement type to indicate the measurement method. In this case, the training of the stability scoring model clearly identifies whether each (verticality data) data point is the measurement result of the inner sidewall or the outer sidewall. The stability scoring model can learn the characteristics of the inner and outer sidewall data and take this into account when predicting, thereby improving the generalization ability of the model, avoiding the establishment and maintenance of a separate model for each sidewall type, and simplifying model management.

[0126] See also Figure 4 , Figure 4 It is a partial flow chart of a stability calculation method provided in an embodiment of the present application.

[0127] In an exemplary embodiment, the stability calculation method further includes:

[0128] S105, when the number of stability scores of the construction trench sections that have completed stability scoring meets a preset number, the stability calculation results of the underground continuous wall in the previous construction stage are obtained according to the stability score of each construction trench section that has completed stability scoring, the trench section key coefficient and the stability scoring standard, and the stability calculation results include normal and abnormal results;

[0129] S106: When the stability calculation result is abnormal, generate abnormal prompt information and send it to the user device.

[0130] In specific applications, the slot segment critical coefficient can indicate the importance of the location of the construction slot segment in the overall underground continuous wall, such as whether the slot segment is located at the corner, edge or key support position of the structure. If so, the coefficient is greater than 1 (for example, preset to 1.2), and if not, the coefficient is 1; if the slot segment critical coefficient is greater than 1, when the stability calculation result of the underground continuous wall in the previous construction stage is obtained according to the stability score, slot segment critical coefficient and stability scoring standard of each construction slot segment that has completed stability scoring, the stability score of the corresponding construction slot segment is copied as the stability score of the two construction slot segments for stability calculation result judgment. If the slot segment critical coefficient is 1, it is calculated normally.

[0131] Among them, the preset numbers are, for example, 5, 8, 12, etc., the stability scores obtained by the stability scoring model are, for example, 90, 75, A, C, etc., and the stability scoring standard is, for example, the mean of the stability scores of multiple construction trench sections is 85, 75, or the mode is B, C and above, the monitoring result is normal, where the higher the number, the better the stability, and the further forward the alphabetical order, the better the stability.

[0132] As an example, the stability scores are A, A, B, C, C, C, and the key coefficients of the slot sections are all 1. The stability scoring standard is that the mode of the stability scores is B and above, then the mode of the stability scores is considered to be C, and the monitoring results are abnormal, indicating that even if the verticality data is within its corresponding preset range, there are hidden dangers in the stability of the current underground continuous wall, and further inspection is required.

[0133] As another example, the stability scores are A, A, B, C, C, C, and the corresponding slot key coefficients are 1.2, 1.2, 1, 1, 1, and the stability scores corresponding to the slot key coefficients greater than 1 are copied respectively, and all the stability scores are: A, A, A, A, B, C, C, C. The stability scoring standard is that the mode of the stability score is B or above, then the mode of the stability score is considered to be A, and the monitoring result is normal, indicating that the verticality data is within its corresponding preset range, and there is no hidden danger in the stability of the current underground continuous wall.

[0134] This application does not limit the user device, such as a tablet computer, industrial computer, laptop computer, etc. The abnormal prompt information can be presented in the form of voice notification, SMS notification or APP pop-up window, etc.

[0135] After the scoring is completed, the stability calculation results of each construction slot section in the previous construction stage are obtained according to the stability score, key coefficient of the slot section and stability scoring standard. The stability calculation results include normal and abnormal states. The normal state means that the stability of the construction slot section is good and there are no obvious problems; the abnormal state generates an abnormal prompt message and sends it to the user equipment of the project supervisor or the person in charge on site so that necessary measures can be taken in time.

[0136] The benefit of doing this is that by real-time monitoring and evaluating the stability of multiple completed construction trench sections, possible risks can be discovered immediately, facilitating the provision of early warning and feedback mechanisms to reduce potential structural problems.

[0137] In an exemplary embodiment, a plurality of drainage wells are arranged in the foundation pit of the underground continuous wall, and each drainage well is used as a precipitation well for drainage before and during concrete pouring to lower the groundwater level, so that the moisture in the soil above the water level slope line seeps down, the fluidity of the soil is reduced, and the sandy soil layer is consolidated, thereby reducing the lateral pressure of the groundwater on the trench wall.

[0138] Several drainage wells are pre-arranged in the underground continuous wall foundation pit, and these drainage wells are used as precipitation wells to perform drainage operations before and during concrete pouring. Through the pumping function of the precipitation well, the groundwater level in the foundation pit is lowered, reducing the lateral pressure of groundwater on the trench wall. The precipitation activity causes the water in the soil above the water level slope line to penetrate downward, thereby reducing the moisture content in the soil. As the moisture content decreases, the sandy soil layer begins to consolidate, enhancing the overall stability of the soil. The consolidation of the soil and the reduction of moisture reduce the lateral pressure of groundwater on the trench wall and reduce the risk of trench wall collapse. Concrete pouring is carried out under the condition that the groundwater level is effectively controlled to ensure the pouring quality and the stability of the trench section.

[0139] In an exemplary embodiment, the construction plan of the underground continuous wall also includes: wrapping the soft soil layer position on the steel cage of the underground continuous wall and within a range of 3m above and below, so as to isolate the contact between the soil and the steel bars on both sides of the construction trench section, and to prevent the trench wall soil caused by the shrinkage of the construction trench section from invading the steel cage or leaning on the steel cage, causing mud inclusion and leakage of steel bars in the underground continuous wall.

[0140] In the construction of underground continuous walls, the steel cage is the main supporting structure of the wall. The position where the steel cage contacts the soft soil layer and the area 3 meters above and below it are covered with colored strips. The function of the colored strips is to separate the soil on both sides of the construction trench from the direct contact with the steel cage, forming a physical barrier. The isolation measures provided in this embodiment help to avoid mud inclusion caused by soil intrusion and the problem of underground continuous wall reinforcement leakage caused by poor contact between the soil and the steel bars.

[0141] See also Figure 5 , Figure 5 It is a flow chart of another stability calculation method provided in an embodiment of the present application.

[0142] In a specific application, a stability calculation method for an underground continuous wall of a subway station is provided, comprising:

[0143] First, obtain the construction plan. The construction plan includes the construction arrangement of each construction slot section and the identification information of the construction slot section, such as 1# construction slot section and 2# construction slot section; it also includes the target liquid level curve, which includes multiple data points to indicate the corresponding predicted liquid level data for different pouring depth intervals. Pour concrete and collect data for 1# construction slot section. While pouring concrete, use instruments (construction collection devices) to measure the depth of concrete and the corresponding precipitation well water level, and perform liquid level control at the same time. The liquid level control process includes:

[0144] According to the pouring depth data, the target liquid level data is obtained, the target liquid level curve is obtained, and the predicted liquid level data is obtained (from the target liquid level curve). It is determined that the difference between the two (target liquid level data and predicted liquid level data) is within the corresponding preset range. When it is within the preset range (according to the predicted liquid level data), the target liquid level data is updated. When it is not within the preset range (according to the target liquid level data), the target liquid level curve is updated; (according to the target liquid level data and liquid level data), the error is calculated and input into the preset PID control algorithm to obtain the water pump control signal, and the water pump group is controlled by PID to ensure that the water level remains at the appropriate position. When the 1# construction slot section is poured, its verticality is detected by ultrasound to determine whether there is any problem with the verticality. If not, the stability score of the 1# construction slot section is scored based on the changes in verticality, concrete depth and water level. If the verticality detection shows a problem, that is, the verticality data of the wall is not within the preset range, it means that there is a deviation or error in the construction process, and a prompt message is sent to the user's device. The project supervisor or the person in charge of the site will handle it. The project supervisor or the person in charge of the site will analyze the cause of the verticality deviation from aspects such as unstable formwork support, uneven foundation settlement, improper construction, etc., and take corresponding corrective measures according to the cause of the problem. After processing, re-judge the verticality.

[0145] Determine whether the number of stability scores is greater than 5. If yes, obtain the stability calculation results of the underground continuous wall in the previous construction stage according to each stability score, key coefficient of the stability slot section and stability scoring standard, and determine whether the results are normal. If the status is abnormal, generate an abnormal prompt message and send it to the project supervisor or the person in charge on site.

[0146] In another specific application, a construction plan for underground continuous wall is provided, and the construction plan includes the following construction steps: 1. Construction preparation; 2. Guide wall construction; 3. Pre-drainage of pipe well and mud preparation; 4. Grooving; 5. Cleaning sediment and replacing mud; 6. Brushing the wall of I-beam joints; 7. Making steel cages and setting anti-circulation iron sheets; 8. Hanging and placing steel cages; 9. Setting sand control layers; 10. Hanging and placing locking pipes; 11. Pouring concrete; 12. Pulling out locking pipes; 13. Grooving the next construction slot section and obtaining stability calculation results in the previous construction stage. The information of the construction plan also includes the construction arrangement of each construction slot section obtained in advance, the identification information of the construction slot section, and the target liquid level curve.

[0147] During the construction preparation stage, the continuous wall is divided into multiple construction trench sections, and the corresponding identification information (numbers) are 1# construction trench section, 2# construction trench section...N# construction trench section, and construction is carried out in the order of the numbering.

[0148] The shape of the cast-in-place guide wall is "┐┌" type. The guide wall construction shall meet the requirement that the bottom is more than 150mm deep into the bottom elevation of the crown beam. The pavement reinforcement and the guide wall reinforcement are connected and penetrated. During construction, focus on checking the centerline deviation, verticality and net width inside the guide wall.

[0149] The advance dewatering of pipe wells is temporary dewatering. The dewatering wells are only operated during the construction of the ground-connected wall. The operation time is short. The cost of arranging dewatering wells separately is too high, which is not conducive to project management from the perspective of reducing engineering costs. Therefore, the dewatering wells in the pit are constructed in advance, and the dewatering wells are used as dewatering wells after completion. If the dewatering wells cannot meet the dewatering requirements, appropriate dewatering wells are set outside the foundation pit. According to the construction location of the ground-connected wall, a certain number of dewatering wells at the corresponding locations nearby are selected for pumping. In order to prevent the impact on the surrounding area, the dewatering wells in other areas should stop pumping construction, and the hydraulic gradient outside the foundation pit should be reduced by dewatering in sections and zones.

[0150] During the trenching construction, ensure that the groundwater level is lower than the mud level. Use an automated remote control device to replenish the mud in time. The mud replenishment should be carried out when the grab is raised 2m above the ground; the speed of the trenching machine should be kept balanced when the bucket is lowered and lifted. When constructing trench sections of different depths, the shallower trench section should be constructed last, and the deeper trench section should be dug first. The excavation depth of the trench bottom in the same trench section should be kept consistent. Ultrasonic testing should be carried out after the trenching of the same trench section is completed. During construction, the concrete at the joints should be dense and free of mud. An extra-long vibrating rod should be used to vibrate the concrete, and the vibration ratio at the interface of the I-beam of the underground continuous wall should be increased. The underground continuous wall steel cage at the location of the silt and silt layer is covered with colored strips to 1m above and below it, and is tied and fixed every 2 to 3m with buckles or thin steel bars. The colored strips are used to separate the soil on both sides of the trench section from the steel bars in the trench to avoid the phenomenon of mud and exposed steel bars in the underground continuous wall caused by the shrinkage of the trench section. The time interval between the concrete pouring time and the installation of the steel cage should not be too long, and 4h is the standard. The above construction plan for underground continuous wall and its corresponding stability calculation method are suitable for the construction of underground continuous wall in deep water-rich soft silt sand strata and in areas with abundant groundwater, high water head, soft soil, poor self-stability, shallow silt sand layer and deep underground continuous wall.

[0151] In another specific application, a method for calculating the stability of an underground continuous wall of a subway station is provided, comprising:

[0152] S101, obtaining a construction plan of the underground continuous wall;

[0153] S102, pouring concrete in the current construction slot section according to the construction plan, using a construction acquisition device to measure and obtain in real time the pouring depth data of the current construction slot section and the liquid level data of the precipitation well corresponding to the current construction slot section; the pouring depth data and the liquid level data are used to indicate changes in the pouring depth and the liquid level of the precipitation well, respectively;

[0154] S103, obtaining the target liquid level data and the predicted liquid level data corresponding to the pouring depth interval where the pouring depth data is located, wherein the predicted liquid level data is obtained according to a preset target liquid level curve; when the difference between the target liquid level data and the predicted liquid level data is within the corresponding preset range, updating the target liquid level data according to the predicted liquid level data; when the difference between the target liquid level data and the predicted liquid level data is not within the corresponding preset range, updating the target liquid level curve according to the target liquid level data; calculating the error according to the target liquid level data and the liquid level data, inputting the error into a preset PID control algorithm to obtain a water pump control signal, and using the water pump control signal to control the operation of the water pump group so that the actual liquid level meets the target liquid level requirement (making the water level of the dewatering well lower than the current pouring height of the current construction slot section);

[0155] S104, when the current construction slot section is cast, the verticality data of the side wall of the construction slot section is obtained by using an ultrasonic detection device. When the verticality data is within its corresponding preset range, the verticality data, the change curve of the casting depth data and the change curve of the liquid level data are input into a stability scoring model to obtain the stability score of the current construction slot section and send it to the user device, and the next construction slot section is used as the current construction slot section and S102 is executed.

[0156] S105, when the number of stability scores of the construction trench sections that have completed stability scoring meets a preset number, the stability calculation results of the underground continuous wall in the previous construction stage are obtained according to the stability score of each construction trench section that has completed stability scoring, the trench section key coefficient and the stability scoring standard, and the stability calculation results include normal and abnormal results;

[0157] S106: When the stability calculation result is abnormal, generate abnormal prompt information and send it to the user device.

[0158] The training process of the stability scoring model includes the following steps:

[0159] Acquire a training set, the training set comprising a plurality of training data, each of the training data comprising verticality data, a pouring depth change curve and a liquid level change curve, and labeled data of stability scores corresponding to the verticality data, the pouring depth change curve and the liquid level change curve;

[0160] For each training data in the training set, perform the following processing:

[0161] Inputting the verticality data, the pouring depth change curve and the liquid level change curve in the training data into a preset deep learning model to obtain prediction data of the stability score corresponding to the verticality data, the pouring depth change curve and the liquid level change curve;

[0162] Based on the predicted data and the labeled data, updating the model parameters of the deep learning model;

[0163] Check whether the preset training end condition is met; if so, use the trained deep learning model as the stability scoring model; if not, continue to train the deep learning model using the next training data.

[0164] System Embodiments.

[0165] This embodiment provides a stability calculation system for an underground continuous wall of a subway station. The specific working process and beneficial effects of the stability calculation system can refer to the corresponding process and beneficial effects in the aforementioned method embodiment, and will not be repeated here.

[0166] The stability calculation system includes a controller, a construction collection device and an ultrasonic detection device connected to the controller, wherein the construction collection device includes a pressure sensor of a conduit provided in a construction trench section of the underground continuous wall and a liquid level sensor provided in a dewatering well of the underground continuous wall; the controller is configured as follows:

[0167] S101, obtaining a construction plan of the underground continuous wall;

[0168] S102, pouring concrete in the current construction slot section according to the construction plan, using a construction acquisition device to measure and obtain in real time the pouring depth data of the current construction slot section and the liquid level data of the precipitation well corresponding to the current construction slot section; the pouring depth data and the liquid level data are used to indicate changes in the pouring depth and the liquid level of the precipitation well, respectively;

[0169] S104, when the current construction slot section is cast, the verticality data of the side wall of the construction slot section is obtained by using an ultrasonic detection device. When the verticality data is within the corresponding preset range, the verticality data, the change curve of the casting depth data and the change curve of the liquid level data are input into a stability scoring model to obtain the stability score of the current construction slot section and send it to the user device to set the next construction slot section as the current construction slot section and execute S102.

[0170] In an exemplary embodiment, the controller is further configured to:

[0171] S103, obtaining a water pump control signal according to the pouring depth data and the liquid level data, wherein the water pump control signal is used to control the water pump group of the dewatering well to pump water so that the water level of the dewatering well is lower than the current pouring height of the current construction trench section.

[0172] In an exemplary embodiment, the controller obtains the water pump control signal in the following manner:

[0173] Obtaining target liquid level data corresponding to the pouring depth interval where the pouring depth data is located;

[0174] According to the target liquid level data and the liquid level data, a water pump control signal is generated in a PID manner to control the operation of the water pump group so that the actual liquid level meets the target liquid level requirement.

[0175] In an exemplary embodiment, the controller generates a water pump control signal in a PID manner according to the target liquid level data and the liquid level data in the following manner:

[0176] Obtaining target liquid level data and predicted liquid level data corresponding to the pouring depth interval where the pouring depth data is located, wherein the predicted liquid level data is obtained according to a preset target liquid level curve;

[0177] When the difference between the target liquid level data and the predicted liquid level data is within the corresponding preset range, updating the target liquid level data according to the predicted liquid level data;

[0178] When the difference between the target liquid level data and the predicted liquid level data is not within the corresponding preset range, updating the target liquid level curve according to the target liquid level data;

[0179] The error is calculated based on the target liquid level data and the liquid level data, and the error is input into a preset PID control algorithm to obtain a water pump control signal.

[0180] In an exemplary embodiment, the stability scoring model is obtained by training a deep learning model, and the training process of the stability scoring model includes the following steps:

[0181] Acquire a training set, the training set comprising a plurality of training data, each of the training data comprising verticality data, a pouring depth change curve and a liquid level change curve, and labeled data of stability scores corresponding to the verticality data, the pouring depth change curve and the liquid level change curve;

[0182] For each training data in the training set, perform the following processing:

[0183] Inputting the verticality data, the pouring depth change curve and the liquid level change curve in the training data into a preset deep learning model to obtain prediction data of the stability score corresponding to the verticality data, the pouring depth change curve and the liquid level change curve;

[0184] Based on the predicted data and the labeled data, updating the model parameters of the deep learning model;

[0185] Check whether the preset training end condition is met; if so, use the trained deep learning model as the stability scoring model; if not, continue to train the deep learning model using the next training data.

[0186] In an exemplary embodiment, the controller is further configured to:

[0187] When the number of stability scores of the construction trench sections that have completed stability scoring meets the preset number, the stability calculation results of the underground continuous wall in the previous construction stage are obtained according to the stability score of each construction trench section that has completed stability scoring, the trench section key coefficient and the stability scoring standard, and the stability calculation results include normal and abnormal results;

[0188] When the stability calculation result is abnormal, abnormal prompt information is generated and sent to the user device.

[0189] In an exemplary embodiment, a plurality of drainage wells are arranged in the foundation pit of the underground continuous wall, and each drainage well is used as a precipitation well for drainage before and during concrete pouring to lower the groundwater level, so that the moisture in the soil above the water level slope line seeps down, the fluidity of the soil is reduced, and the sandy soil layer is consolidated, thereby reducing the lateral pressure of the groundwater on the trench wall.

[0190] In an exemplary embodiment, the construction plan of the underground continuous wall also includes: wrapping the soft soil layer position on the steel cage of the underground continuous wall and within a range of 3m above and below, so as to isolate the contact between the soil and the steel bars on both sides of the construction trench section, and to prevent the trench wall soil caused by the shrinkage of the construction trench section from invading the steel cage or leaning on the steel cage, causing mud inclusion and leakage of steel bars in the underground continuous wall.

[0191] In an exemplary embodiment, the conduit refers to the perfusion conduit of the current construction slot section.

[0192] In the various implementation modes of the specification of the present application, the size of the serial number of each process does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the present application.

[0193] The terms "first", "second", "third", etc. (if any) in the specification and claims of the present application and the drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "corresponding to" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0194] This application is explained from the perspectives of purpose of use, effectiveness, progress and novelty, and has met the functional enhancement and usage requirements emphasized by the Patent Law. The above description and drawings of this application are only the preferred embodiments of this application, and are not intended to limit this application. Therefore, all structures, devices, features, etc. that are similar or identical to this application, that is, all equivalent replacements or modifications made in accordance with the scope of the patent application of this application, should fall within the scope of protection of the patent application of this application.

Claims

1. A method for calculating the stability of underground continuous walls of subway stations, characterized in that: The stability calculation method comprises: S101, obtaining a construction plan of the underground continuous wall; S102, pouring concrete in the current construction slot section according to the construction plan, using a construction acquisition device to measure and obtain in real time the pouring depth data of the current construction slot section and the liquid level data of the precipitation well corresponding to the current construction slot section; the pouring depth data and the liquid level data are used to indicate changes in the pouring depth and the liquid level of the precipitation well, respectively; S104, when the current construction slot section is poured, the verticality data of the side wall of the construction slot section is obtained by using an ultrasonic detection device. When the verticality data is within the corresponding preset range, the verticality data, the change curve of the pouring depth data and the change curve of the liquid level data are input into a stability scoring model to obtain the stability score of the current construction slot section and send it to the user device, and the next construction slot section is used as the current construction slot section and S102 is executed; Wherein, the construction data collection device includes a pressure sensor arranged in a conduit of a construction trench section of the underground continuous wall and a liquid level sensor arranged in a dewatering well of the underground continuous wall.

2. The method for calculating the stability of underground continuous walls of subway stations according to claim 1, characterized in that: The stability scoring model is obtained by training a deep learning model, and the training process of the stability scoring model includes the following steps: Acquire a training set, the training set comprising a plurality of training data, each of the training data comprising verticality data, a pouring depth change curve and a liquid level change curve, and labeled data of stability scores corresponding to the verticality data, the pouring depth change curve and the liquid level change curve; For each training data in the training set, perform the following processing: Inputting the verticality data, the pouring depth change curve and the liquid level change curve in the training data into a preset deep learning model to obtain prediction data of the stability score corresponding to the verticality data, the pouring depth change curve and the liquid level change curve; Based on the predicted data and the labeled data, updating the model parameters of the deep learning model; Check whether the preset training end condition is met; if so, use the trained deep learning model as the stability scoring model; if not, continue to train the deep learning model using the next training data.

3. The method for calculating the stability of underground continuous walls of subway stations according to claim 2, characterized in that: The stability calculation method further includes: When the number of stability scores of the construction trench sections that have completed stability scoring meets the preset number, the stability calculation results of the underground continuous wall in the previous construction stage are obtained according to the stability score of each construction trench section that has completed stability scoring, the trench section key coefficient and the stability scoring standard, and the stability calculation results include normal and abnormal results; When the stability calculation result is abnormal, abnormal prompt information is generated and sent to the user device.

4. The method for calculating the stability of underground continuous walls of a subway station according to claim 1, characterized in that: The stability calculation method further includes: S103, obtaining a water pump control signal according to the pouring depth data and the liquid level data, wherein the water pump control signal is used to control the water pump group of the dewatering well to pump water so that the water level of the dewatering well is lower than the current pouring height of the current construction trench section.

5. The method for calculating the stability of underground continuous walls of a subway station according to claim 4, characterized in that: Ways to obtain water pump control signals include: Obtaining target liquid level data corresponding to the pouring depth interval where the pouring depth data is located; According to the target liquid level data and the liquid level data, a water pump control signal is generated in a PID manner to control the operation of the water pump group so that the actual liquid level meets the target liquid level requirement.

6. The method for calculating the stability of underground continuous walls of a subway station according to claim 5, characterized in that: The step of generating a water pump control signal in a PID manner according to the target liquid level data and the liquid level data comprises: Obtaining target liquid level data and predicted liquid level data corresponding to the pouring depth interval where the pouring depth data is located, wherein the predicted liquid level data is obtained according to a preset target liquid level curve; When the difference between the target liquid level data and the predicted liquid level data is within the corresponding preset range, updating the target liquid level data according to the predicted liquid level data; When the difference between the target liquid level data and the predicted liquid level data is not within the corresponding preset range, updating the target liquid level curve according to the target liquid level data; The error is calculated based on the target liquid level data and the liquid level data, and the error is input into a preset PID control algorithm to obtain a water pump control signal.

7. The method for calculating the stability of underground continuous walls of a subway station according to claim 1, characterized in that: A plurality of drainage wells are arranged in the foundation pit of the underground continuous wall, and each drainage well is used as a precipitation well for drainage before and during concrete pouring to lower the groundwater level, so that the moisture in the soil above the water level slope line seeps down, the fluidity of the soil is reduced, and the sandy soil layer is consolidated, thereby reducing the lateral pressure of the groundwater on the trench wall.

8. The method for calculating the stability of underground continuous walls of a subway station according to claim 1, characterized in that: The construction plan of the underground continuous wall also includes: wrapping the soft soil layer on the steel cage of the underground continuous wall and within a range of 3m above and below, so as to isolate the contact between the soil and the steel bars on both sides of the construction trench section.

9. The method for calculating the stability of underground continuous walls of a subway station according to claim 1, characterized in that: The conduit refers to the perfusion conduit of the current construction slot section.

10. A stability calculation system for underground continuous walls of subway stations, characterized in that: The stability calculation system includes a controller, a construction collection device and an ultrasonic detection device connected to the controller, wherein the construction collection device includes a pressure sensor of a conduit provided in a construction trench section of the underground continuous wall and a liquid level sensor provided in a dewatering well of the underground continuous wall; the controller is configured as follows: S101, obtaining a construction plan of the underground continuous wall; S102, pouring concrete in the current construction slot section according to the construction plan, using a construction acquisition device to measure and obtain in real time the pouring depth data of the current construction slot section and the liquid level data of the precipitation well corresponding to the current construction slot section; the pouring depth data and the liquid level data are used to indicate changes in the pouring depth and the liquid level of the precipitation well, respectively; S104, when the current construction slot section is cast, the verticality data of the side wall of the construction slot section is obtained by using an ultrasonic detection device. When the verticality data is within the corresponding preset range, the verticality data, the change curve of the casting depth data and the change curve of the liquid level data are input into a stability scoring model to obtain the stability score of the current construction slot section and send it to the user device to set the next construction slot section as the current construction slot section and execute S102.

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