Intelligent monitoring method for deep foundation pit

Abstract

According to the intelligent monitoring method for the deep foundation pit, the efficiency and precision of measurement and control are greatly improved, errors caused by manual operation are reduced, and the actual condition of the foundation pit can be reflected more accurately. The real-time monitoring and early warning function enables constructors to find and process potential safety hazards in time, construction risks are effectively reduced, life safety of the constructors is guaranteed, whole-process operation of coordinate point obtaining, station setting, lofting or data monitoring by a single person is achieved, measurement and control precision and efficiency are improved, and construction safety is improved. The problem that the data accuracy and stability cannot be guaranteed when the foundation pit is measured manually in the past is solved.

Description

Technical Field

[0001] The present invention relates to the field of foundation pit monitoring, and particularly to an intelligent monitoring method for deep foundation pits. Background Art

[0002] In civil engineering, the lofting and monitoring of deep foundation pits are key links to ensure construction safety and quality. Traditional measurement and control methods often rely on manual operations, which are not only inefficient but also easily restricted by occlusion and the on-site environment. In complex construction sites, accurate data may not be obtained during manual measurement due to occlusion by surrounding buildings, construction equipment, etc.; in adverse weather conditions, due to the occlusion of the support system, surveyors need to set up stations repeatedly for measurement work. Lofting the four corner points of a deep foundation pit often requires repeated setting up twice or more to complete the lofting work, and the internal structures of the foundation pit need to be lofted according to the construction progress. The accuracy and efficiency of manual measurement will be greatly reduced, and even measurement work may not be possible. At the same time, there are also human errors in manual operations, making it difficult to ensure the accuracy and stability of data.

[0003] With the development of technology, high-precision sensors such as lidar, total stations, displacement sensors, etc. can be used to collect various data of the foundation pit in real time, including displacement, settlement, inclination, etc. With the help of the Internet of Things technology, automatic transmission and real-time sharing of data are realized, and the data is transmitted to the monitoring center. Then, through big data analysis and artificial intelligence algorithms, the collected data is deeply processed and analyzed, so as to realize real-time monitoring and accurate early warning of the foundation pit state and timely discover potential safety hazards. Summary of the Invention

[0004] The main purpose of the present invention is to provide an intelligent monitoring method for deep foundation pits, which solves the problem that the accuracy and stability of data cannot be guaranteed during the previous manual measurement of foundation pits.

[0005] To solve the above technical problems, the technical solution adopted by the present invention is: an intelligent monitoring method for deep foundation pits, the method comprising: S1. Construct the foundation pit and install a support frame in the foundation pit; S2. Install a collection component on the support frame, and arrange a first prism, a second prism and a third prism in the foundation pit; S3. Collect various parameters of the first prism, the second prism and the third prism through the collection component; S4. The collection component uploads the position data to the data processing module; S5. The data processing module extracts features from the various parameters, and designers establish a mechanical model according to the features; S6. Conduct a safety assessment according to the mechanical model, and give an early warning and an optimization plan; S7. Repeat steps S4 - S5 to conduct regular monitoring and optimization of the foundation pit until the construction of the foundation pit is completed.

[0006] In the preferred solution, in step S2, the acquisition component is installed at point A on the support frame, and the first prism, the second prism, and the third prism are sequentially installed at points B, C, and D.

[0007] In the preferred solution, in step S2, the acquisition component includes a cross beam, and a movable longitudinal beam is provided on one side of the cross beam, and the longitudinal beam is arranged perpendicular to the cross beam.

[0008] In the preferred solution, a rotatable second lead screw is provided inside the cross beam, and a movable cross - slide seat is provided on the second lead screw; A cross - slide chute is also provided on one side of the cross beam, one side of the cross - slide seat penetrates through the cross - slide chute, and a slot is provided on one side of the cross - slide seat for connecting the longitudinal beam.

[0009] In the preferred solution, a fourth bevel gear is provided at one end of the second lead screw, a third bevel gear is provided on one side of the fourth bevel gear, one end of the third bevel gear meshes with the fourth bevel gear, and the third bevel gear and the fourth bevel gear are arranged perpendicular to each other; A second interface is provided at the other end of the third bevel gear, the second interface penetrates through the cross beam, and the second interface is used to connect a servo motor.

[0010] In the preferred solution, a GPS receiver is provided on the top of the cross beam, a connecting plate is provided on one side of the cross beam close to the longitudinal beam, and a plug board is provided below the connecting plate for cooperating with the slot; A first support is provided inside the cross beam, a rotatable lifting lead screw is provided on the first support, a lifting plate is provided on the lifting lead screw, and an intelligent total station is provided on the lifting plate.

[0011] In the preferred solution, a second bevel gear is provided at one end of the lifting lead screw, a first bevel gear is provided on one side of the second bevel gear, one end of the first bevel gear meshes with the second bevel gear, and the first bevel gear and the second bevel gear are arranged perpendicular to each other; A first interface is provided at the other end of the first bevel gear, the first interface penetrates through the longitudinal beam, and the first interface is used to connect a servo motor.

[0012] In the preferred solution, in step S3, the parameters collected by the acquisition component from the first prism, the second prism, and the third prism include: angle parameters, distance parameters, and coordinate parameters; The angle parameters include horizontal angles and vertical angles , the horizontal angle is used to determine the position of the prism in the horizontal direction, and the vertical angle is used to determine the position of the prism in the vertical direction; The distance parameters include slope distances , by measuring the slope distance , the three-dimensional coordinates of the prism can be calculated by combining the horizontal angle and the vertical angle, and the calculation formula is as follows: , , , where is the coordinate of the total station, and the intelligent total station uploads the position data to the data processing module; In step S4, the data processing module includes: a data receiving module, a data storage module, and a feature extraction module; The data receiving module is used to receive the position data uploaded by the acquisition component and perform preliminary format checks and data verification; The data storage module is used to store the received data in the database for subsequent query and analysis; The feature extraction module is used to extract features related to the foundation pit deformation from the stored data; In step S5, the designer then establishes a mechanical model based on the features extracted by the feature extraction module, combined with the geological conditions of the foundation pit and the information of the support structure.

[0013] In the preferred solution, in step S5, the geological condition information of the foundation pit includes: the unit weight of the soil γ , cohesion c , internal friction angle φ , and the support structure information includes: the stiffness of the support frame k and the tension of the anchor T , to establish a mechanical model; in step S6, a safety assessment is carried out according to the established mechanical model, and the safety assessment steps include: S6.1 determining the assessment indicators as the maximum displacement, maximum settlement, and maximum internal force of the support structure of the foundation pit; S6.2 calculating the index values using the mechanical model; S6.3 comparing the calculated index values with the pre-set safety thresholds; S6.4 dividing the safety levels according to the comparison results, and the safety levels are divided into safe, warning, and dangerous; S6.5 automatically sending a warning signal when the safety level is warning, taking measures such as increasing the number of supports and increasing the support stiffness for displacements exceeding the safety threshold, and taking measures such as increasing the anchor tension and strengthening the support structure for internal forces of the support structure exceeding the safety threshold, to form a warning and optimization plan; S6.6 reconnecting the warning and optimization plan to the data processing module, and by setting a feedback mechanism, storing the warning information and optimization plan in the database, and adjusting and recalculating and evaluating the mechanical model according to the optimization plan in the model establishment module; S6.7 repeating steps such as data upload and feature extraction to regularly monitor and optimize the foundation pit until the foundation pit construction is completed.

[0014] In the preferred solution, in steps S6.1 - 6.5, the safety assessment algorithm is: setting a function where is the unit weight of the soil mass, is the cohesion, is the internal friction angle, is the stiffness of the support frame, is the tension of the anchor rod; Calculate the mean value of the performance function and the standard deviation ; Determine the reliability index ; By comparing the reliability index with the target reliability index evaluate the safety level of the foundation pit. When , it is determined that the foundation pit is in an unsafe state; The optimization algorithm for adjusting the support stiffness is: Set the objective function , where is the safety index, is the cost function, related to the support stiffness , and are the weight coefficients. Using the genetic algorithm operation, through continuous iteration, find the value of the support stiffness that optimizes the objective function to determine the optimization plan.

[0015] The present invention provides an intelligent monitoring method for deep foundation pits, which has the following beneficial effects: 1. The intelligent monitoring method of the present invention greatly improves the efficiency and accuracy of measurement and control, reduces the errors caused by manual operation, and can more accurately reflect the actual situation of the foundation pit. The real-time monitoring and early warning functions can enable construction personnel to promptly discover and handle potential safety hazards, effectively reducing construction risks and ensuring the safety of construction personnel.

[0016] 2. The large amount of data accumulated by the system can also provide valuable references for subsequent engineering design and construction, helping to optimize the construction plan, improve the project quality, and promote the development of the civil engineering industry towards intelligence and high efficiency.

[0017] 3. By moving the crossbeam left and right and moving the total station up and down to solve the problem of line-of-sight occlusion, and controlling the total station through a remote control device to automatically find the prism and feedback the measurement deviation, only one person is required to complete the whole process of obtaining coordinate points, setting up stations, staking out, or monitoring data, saving labor and realizing the whole process operation of a single person for coordinate point acquisition, station setting, staking out, or monitoring data, improving the measurement and control accuracy and efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] The present invention will be further described below in conjunction with the drawings and embodiments: Figure 1 is the layout schematic diagram of the acquisition component of the present invention; Figure 2 is the layout schematic diagram of the prism of the present invention; Figure 3 It is a layout schematic diagram of the acquisition component and the prism of the present invention; Figure 4 It is an axonometric view of the acquisition component of the present invention; Figure 5 It is an axonometric view of the acquisition component in another direction of the present invention; Figure 6 It is a cross-sectional view of the longitudinal beam of the present invention; Figure 7 It is a cross-sectional view of the cross beam of the present invention; Figure 8 It is a data acquisition flow chart of the acquisition component of the present invention.

[0019] In the figure: support frame 1; acquisition component 2; cross beam 201; longitudinal beam 202; first interface 203; transverse sliding groove 204; GPS receiver 205; lifting lead screw 206; lifting plate 207; intelligent total station 208; first support 209; second interface 210; connecting plate 211; fixing plate 212; first bevel gear 213; second bevel gear 214; first lead screw 215; insertion plate 216; insertion slot 217; third bevel gear 218; fourth bevel gear 219; second support 220; transverse moving seat 221; second lead screw 222; first prism 3; second prism 4; third prism 5. Specific implementation mode

[0020] Embodiment 1 As Figure 1-8 shown, a deep foundation pit intelligent monitoring method, the method includes: S1. Construct a foundation pit and install a support frame 1 in the foundation pit; S2. Install an acquisition component 2 on the support frame 1, and arrange a first prism 3, a second prism 4 and a third prism 5 in the foundation pit; S3. Collect various parameters of the first prism 3, the second prism 4 and the third prism 5 through the acquisition component 2; S4. The acquisition component 2 uploads the position data to the data processing module; S5. The data processing module extracts features from the various parameters, and the designer establishes a mechanical model according to the features; S6. Conduct a safety assessment according to the mechanical model, and give a warning and an optimization plan; S7. Repeat steps S4 - S5 to regularly monitor and optimize the foundation pit until the foundation pit construction is completed.

[0021] In the preferred solution, in step S2, the acquisition component 2 is installed at point A on the support frame 1, and the first prism 3, the second prism 4 and the third prism 5 are sequentially installed at points B, C and D.

[0022] In the preferred solution, in step S2, the acquisition component 2 includes a cross beam 201. One side of the cross beam 201 is provided with a movable longitudinal beam 202, and the longitudinal beam 202 is arranged perpendicular to the cross beam 201.

[0023] In the preferred solution, a rotatable second lead screw 222 is arranged inside the cross beam 201, and a movable cross slide 221 is arranged on the second lead screw 222; One side of the cross beam 201 is further provided with a cross slide chute 204. One side of the cross slide 221 penetrates through the cross slide chute 204, and one side of the cross slide 221 is provided with a slot 217, and the slot 217 is used for connecting the longitudinal beam 202.

[0024] In the preferred solution, one end of the second lead screw 222 is provided with a fourth bevel gear 219. One side of the fourth bevel gear 219 is provided with a third bevel gear 218. One end of the third bevel gear 218 meshes with the fourth bevel gear 219, and the third bevel gear 218 and the fourth bevel gear 219 are arranged perpendicular to each other; The other end of the third bevel gear 218 is provided with a second interface 210. The second interface 210 penetrates through the cross beam 201, and the second interface 210 is used for connecting a servo motor.

[0025] In the preferred solution, a GPS receiver 205 is arranged on the top of the cross beam 201. One side of the cross beam 201 close to the longitudinal beam 202 is provided with a connecting plate 211. Below the connecting plate 211 is provided with a plug board 216, and the plug board 216 is used for cooperating with the slot 217; Inside the cross beam 201 is provided with a first support 209. On the first support 209 is arranged a rotatable lifting lead screw 206. On the lifting lead screw 206 is arranged a lifting plate 207, and on the lifting plate 207 is arranged an intelligent total station 208.

[0026] In the preferred solution, one end of the lifting lead screw 206 is provided with a second bevel gear 214. One side of the second bevel gear 214 is provided with a first bevel gear 213. One end of the first bevel gear 213 meshes with the second bevel gear 214, and the first bevel gear 213 and the second bevel gear 214 are arranged perpendicular to each other; The other end of the first bevel gear 213 is provided with a first interface 210. The first interface 210 penetrates through the longitudinal beam 202, and the first interface 210 is used for connecting a servo motor.

[0027] In the preferred solution, in step S3, the parameters collected by the acquisition component 2 for the first prism 3, the second prism 4 and the third prism 5 include: angle parameters, distance parameters and coordinate parameters; The angle parameters include horizontal angles and vertical angles , the horizontal angles are used to determine the position of the prism in the horizontal direction, and the vertical angles are used to determine the position of the prism in the vertical direction; The distance parameters include inclined distances , by measuring the slant range , the three-dimensional coordinates of the prism can be calculated by combining the horizontal angle and the vertical angle. The calculation formula is as follows: , , , where is the coordinate of the total station, and the intelligent total station 208 uploads the position data to the data processing module; After the intelligent total station 208 completes data acquisition, it will upload these position data through the wireless communication module (the specific communication method can be selected according to the environment and requirements of the construction site) to the data processing module.

[0028] In step S4, the data processing module includes: a data receiving module, a data storage module, and a feature extraction module; The data receiving module is used to receive the position data uploaded by the acquisition component 2 and perform preliminary format checking and data verification; The data receiving module is responsible for receiving the position data uploaded by the acquisition component 2. During the receiving process, data verification is first performed to check the integrity and correctness of the data. By checking the length of the data, the data format, and whether it contains a specific check code, etc., it is judged whether data loss or error occurs during the transmission process.

[0029] If data errors are found, the data receiving module will send a retransmission request to the acquisition component 2 to ensure that the received data is accurate. After that, preliminary format conversion is performed on the data to make it meet the requirements of the data storage module and subsequent processing.

[0030] The data storage module is used to store the received data in the database for subsequent query and analysis; The data storage module stores the data processed by the data receiving module in the database. The database uses SQL, which is suitable for processing a large amount of unstructured or semi-structured data, collecting the original data collected by sensors, and managing it.

[0031] The stored data includes the angle parameters, distance parameters, and coordinate parameters of the first prism 3, the second prism 4, and the third prism 5 at different time points. At the same time, the time stamp of data acquisition will also be recorded to facilitate subsequent time series analysis.

[0032] The feature extraction module is used to extract features related to foundation pit deformation from the stored data; The feature extraction module extracts features related to the foundation pit deformation from the data stored in the database. For the displacement feature, the displacement amount is calculated by comparing the coordinate values of the same prism at different time points. At time t1, the coordinates of the prism are (X1, Y1, Z1), and at time t2, the coordinates are (X2, Y2, Z2). Then, the displacement amount in the X direction is ΔX = X2 - X1, the displacement amount in the Y direction is ΔY = Y2 - Y1, and the displacement amount in the Z direction is ΔZ = Z2 - Z1.

[0033] For the displacement rate, it is obtained by calculating the displacement change amount per unit time. For example, in the time period [t1, t2], the displacement rate Vx in the X direction is Vx = (X2 - X1) / (t2 - t1). Also, by performing fitting analysis on multiple groups of displacement data, features such as the change trend of displacement can be extracted.

[0034] In step S5, the designer establishes a mechanical model based on the features extracted by the feature extraction module, combined with the geological conditions of the foundation pit and the information of the support structure.

[0035] The geological condition information of the foundation pit includes the unit weight γ, cohesion c, and internal friction angle φ of the soil mass. The unit weight γ of the soil mass can be calculated by taking soil samples on-site, weighing and measuring the volume in the laboratory, and using the formula γ = G / V, where G is the weight of the soil sample and V is the volume of the soil sample.

[0036] The cohesion c and the internal friction angle φ are determined through indoor geotechnical tests, and can be determined by direct shear tests and triaxial compression tests. The support structure information includes the stiffness k of the support frame 1 and the tension T of the anchor rod. The stiffness k of the support frame 1 is calculated using the material mechanics formula k = 3EI / L³ according to the material properties, cross-sectional dimensions, and length L of the support frame. The tension T of the anchor rod can be measured in real-time by installing a dynamometer on the anchor rod.

[0037] When establishing the mechanical model, the finite element method is adopted. The foundation pit and the surrounding soil mass are discretized into a finite number of elements. According to the mechanical properties of the elements and the connection relationship of the nodes, the overall stiffness matrix is established. During the establishment of the stiffness matrix, the constitutive relationship of the soil, elastic constitutive relationship, elastoplastic constitutive relationship are considered, combined with the boundary conditions (, and parameters such as the unit weight γ, cohesion c, internal friction angle φ of the soil mass, as well as the stiffness k of the support frame and the tension T of the anchor rod are substituted into the model to form a set of equations describing the mechanical behavior of the foundation pit.

[0038] In the preferred solution, in step S5, the geological condition information of the foundation pit includes: the unit weight of the soil mass γ , cohesion c , internal friction angle φ , and the support structure information includes: the stiffness of the support frame 1 k and the tension of the anchor rod T, establish a mechanical model; in step S6, conduct a safety assessment based on the established mechanical model. The safety assessment steps include: S6.1 Determine the evaluation indicators as the maximum displacement, maximum settlement of the foundation pit, and the maximum internal force of the supporting structure. These indicators can directly reflect the stability and safety of the foundation pit.

[0039] In actual engineering, the monitoring of the maximum displacement and maximum settlement can be carried out by setting multiple monitoring points around the foundation pit, and real-time monitoring the displacement and settlement data of these points to find the maximum value. The maximum internal force of the supporting structure is obtained through the calculation and analysis of the mechanical model. S6.2 Calculate the index values using the mechanical model. For the calculation of the displacement and settlement of the foundation pit, use numerical calculation methods to solve the equations in the mechanical model. During the iteration process, according to the deformation coordination conditions and equilibrium conditions of the soil body, gradually update the displacement values of the nodes until the convergence conditions are met. After obtaining the node displacements, according to the corresponding relationship between the nodes and the monitoring points, obtain the displacement and settlement values of the monitoring points. For the calculation of the maximum internal force of the supporting structure, calculate the internal force of the element according to the stress-strain relationship of the element in the mechanical model, and then find the maximum value by comparing the internal force values of all elements. S6.3 Compare the calculated index values with the pre-set safety thresholds. The pre-set safety thresholds are determined based on engineering experience, relevant code standards, and the design requirements of the foundation pit.

[0040] For example, for a certain specific type of foundation pit, according to the code regulations, the safety threshold for the maximum displacement may be set at 50 mm, the safety threshold for the maximum settlement is set at 30 mm, and the safety threshold for the maximum internal force of the supporting structure is determined according to the material strength and design bearing capacity of the supporting structure. Compare the calculated index values with these safety thresholds to judge the safety status of the foundation pit. S6.4 Divide the safety level according to the comparison results. The safety levels are divided into safe, warning, and dangerous. When the maximum displacement, maximum settlement, and maximum internal force of the supporting structure of the foundation pit are all less than the safety threshold, it is determined that the foundation pit is in a safe state; when any one of the index values is close to the safety threshold, it is determined that the foundation pit is in a warning state; when an index value exceeds the safety threshold, it is determined that the foundation pit is in a dangerous state. S6.5 Automatically send a warning signal when the safety level is warning. For the displacement exceeding the safety threshold, increase the number of supports and increase the support stiffness. For the internal force of the supporting structure exceeding the safety threshold, increase the anchor tension and reinforce the supporting structure to form a warning and optimization plan; When the safety level is a warning, a warning signal is automatically issued. The warning signal can be issued in various ways such as through an audible and visual alarm system, SMS notification, and pop-up window on the monitoring platform to ensure that construction workers can obtain warning information in a timely manner. For displacements exceeding the safety threshold, measures such as increasing the number of supports and increasing the stiffness of the supports are taken. When increasing the number of supports, according to the force analysis and stability requirements of the foundation pit, the number of supports n to be increased is determined through calculation.

[0041] Assume that the original number of supports is n0. The calculation formula for increasing the number of supports can be expressed as n = n0 + Δn, where Δn is determined based on factors such as the displacement excess of the foundation pit, the bearing capacity of the supports, and the mechanical properties of the soil. When increasing the stiffness of the supports, considering the relationship between the support stiffness and factors such as materials and cross-sectional dimensions, it is achieved by replacing the support material (such as replacing ordinary steel with high-strength steel) or increasing the cross-sectional dimension of the support (such as increasing the diameter or cross-sectional area of the support).

[0042] For the internal force of the support structure exceeding the safety threshold, measures such as increasing the anchor rod tension and strengthening the support structure are taken. Increasing the anchor rod tension can be achieved by adjusting the prestressing device of the anchor rod, and the specific increased tension value is determined according to the internal force excess of the support structure and the bearing capacity of the anchor rod.

[0043] To strengthen the support structure, additional strengthening materials can be used on the original support structure, such as pasting carbon fiber cloth or adding steel plates. To change the form of the support structure, the number of support layers can be increased or the support arrangement method can be changed. S6.6 Reconnect the warning and optimization plan to the data processing module. By setting a feedback mechanism, store the warning information and optimization plan in the database, and adjust and recalculate and evaluate the mechanical model according to the optimization plan in the model establishment module; S6.7 Repeat steps such as data upload and feature extraction to regularly monitor and optimize the foundation pit until the foundation pit construction is completed.

[0044] In the preferred solution, in steps S6.1 - 6.5, the safety assessment algorithm is: set the performance function , where is the unit weight of the soil, is the cohesion, is the internal friction angle, is the stiffness of the support frame, is the tension of the anchor rod; Calculate the mean and standard deviation of the performance function; Determine the reliability index ; By comparing the reliability index with the target reliability index evaluate the safety level of the foundation pit. When , it is determined that the foundation pit is in an unsafe state; The optimization algorithm for adjusting the support stiffness is as follows: Set the objective function , where is the safety index, is the cost function, related to the support stiffness . and are the weight coefficients. Using the genetic algorithm operation, through continuous iteration, find the value of the support stiffness that optimizes the objective function , and determine the optimization scheme; Set the objective function , where S is the safety index, which is a function of parameters related to safety such as foundation pit displacement, settlement, and internal force. Assume , where is the maximum displacement, is the maximum settlement, is the maximum internal force of the support structure, , , are the weight coefficients, determined according to the importance attached to displacement, settlement, and internal force in the project; C(k) is the cost function, related to the support stiffness k. Assume the cost function is C(k) = ak² + bk + c, where a, b, and c are constants, determined according to factors such as the price of the support material and construction cost; α and (1 - α) are the weight coefficients, used to balance the importance of the safety index and the cost function, with a value range between 0 and 1, which can be adjusted according to the actual situation of the project; The genetic algorithm operations adopted include: S1. Assume the probability of each individual being selected , where is the objective function value of the i-th individual, is the number of individuals in the population. During the selection process, the higher the objective function value of an individual, the higher the probability of being selected, so as to ensure that excellent individuals have a greater chance of being inherited to the next generation.

[0045] S2. Assume a random crossover point is selected, and the genes of two parent individuals after the crossover point are exchanged. Assume there are two parent individuals A = [1, 2, 3, 4, 5] and B = [6, 7, 8, 9, 10]. Assume the randomly selected crossover point is 3. Then the offspring individuals generated after crossover are A' = [1, 2, 3, 9, 10], B' = [6, 7, 8, 4, 5]. Through the crossover operation, new individual combinations can be generated, increasing the diversity of the population.

[0046] S3. Randomly change the gene values. Assuming the mutation probability is Pm, take the gene value corresponding to the support stiffness k as an example. Suppose the gene value of k is binary encoded as

[0101] . Perform mutation operations on each gene bit with probability Pm. If the mutation probability is 0.01 and a certain gene bit is selected for mutation, the value of that gene bit is inverted, where 0 becomes 1 and 1 becomes 0. The mutation operation can prevent the genetic algorithm from falling into a local optimal solution and increase the probability of the algorithm finding the global optimal solution.

[0047] In step S6.6, in the model establishment module, adjust the mechanical model according to the optimization plan, recalculate and evaluate. Suppose after taking optimization measures such as increasing the number of supports or increasing the support stiffness, update the relevant parameters of the supports in the mechanical model, and perform finite element analysis again to calculate indicators such as the displacement, settlement of the foundation pit, and internal force of the support structure, and evaluate the optimized effect.

[0048] In step S6.7, during the construction process, due to factors such as the increase in the excavation depth of the foundation pit, the change of construction loads, and the time-dependent change of soil properties, the mechanical state of the foundation pit will constantly change. Therefore, it is necessary to regularly collect and analyze data, timely discover potential safety problems, and optimize and adjust the support measures of the foundation pit according to the monitoring results to ensure the safety and stability of the foundation pit during the entire construction process.

[0049] Embodiment 2, further described in combination with Embodiment 1. The acquisition component 2 is arranged on the top of the foundation pit support frame 1. When the foundation pit is excavated downward, the GPS receiver 205 cannot obtain satellite signals in the deep foundation pit; Secondly, when the intelligent total station 208 is conventionally set up, two control points are required for resection or coordinate orientation to calculate and obtain the coordinates of the measuring station for setting up the station. However, control points cannot be set in advance in the deep foundation pit, resulting in the inability of the intelligent total station 208 to set up the station in the foundation pit, and thus unable to complete the measurement work. If the intelligent total station 208 is set up at the upper opening of the foundation pit, there will be a problem that the safety of personnel and equipment cannot be guaranteed. Secondly, in the deep foundation pit, the multi-layer support frame 1 system has serious occlusion, and it is necessary to set up the station twice or even multiple times to avoid the occlusion problem, with low efficiency. Generally, 2 to 3 surveyors are required to operate the intelligent total station 208; Therefore, the GPS receiver 205 is arranged on the top of the longitudinal beam 202, outside the foundation pit. Due to the occlusion of the support system, surveyors need to repeatedly set up the station for measurement work. Lofting the four corner points of a deep foundation pit often requires repeated setting up twice or multiple times to complete the lofting work. Moreover, the structures in the foundation pit need to be lofted according to the construction progress. Therefore, the problem of line-of-sight occlusion can be solved by the lateral movement of the cross beam 201 and the up-and-down movement of the longitudinal beam of the intelligent total station 208. The servo motor disposed at the first interface 203 on the cross beam 201 is controlled by a remote control device to move horizontally, and the servo motor disposed at the second interface 210 on the longitudinal beam 202 is controlled to move up and down, so as to control the intelligent total station 208 to find the prism and feedback the measurement deviation. Only one person is needed to complete this, saving labor.

[0050] The above embodiments are only the preferred technical solutions of the present invention and should not be regarded as limitations to the present invention. The protection scope of the present invention should be the technical solutions recorded in the claims, including the equivalent replacement solutions of the technical features in the technical solutions recorded in the claims. That is, the equivalent replacement improvements within this scope are also within the protection scope of the present invention.

Claims

1. An intelligent monitoring method for deep foundation pits, characterized in that: The method includes: S1. Construct a construction foundation pit and install a support frame (1) inside the foundation pit; S2. Install a collection component (2) on the support frame (1), and arrange a first prism (3), a second prism (4), and a third prism (5) inside the foundation pit; S3. Collect various parameters of the first prism (3), the second prism (4), and the third prism (5) through the collection component (2); S4. The collection component (2) uploads the position data to the data processing module; S5. The data processing module extracts features from the various parameters, and the designer establishes a mechanical model based on the features; S6. Conduct a safety assessment according to the mechanical model, and give a warning and an optimization plan; S7. Repeat steps S4 - S5 to conduct regular monitoring and optimization of the foundation pit until the construction of the foundation pit is completed.

2. The intelligent monitoring method for deep foundation pit according to claim 1, wherein: In step S2, the collection component (2) is installed at point A on the support frame (1), and the first prism (3), the second prism (4), and the third prism (5) are successively installed at points B, C, and D.

3. The intelligent monitoring method for deep foundation pit according to claim 1, wherein: In step S2, the collection component (2) includes a cross beam (201). A movable longitudinal beam (202) is provided on one side of the cross beam (201), and the longitudinal beam (202) is arranged perpendicular to the cross beam (201).

4. The intelligent monitoring method for deep foundation pit according to claim 3, characterized in that: A rotatable second lead screw (222) is provided inside the cross beam (201), and a movable cross - moving seat (221) is provided on the second lead screw (222); A cross - moving sliding groove (204) is also provided on one side of the cross beam (201). One side of the cross - moving seat (221) penetrates through the cross - moving sliding groove (204), and a slot (217) is provided on one side of the cross - moving seat (221). The slot (217) is used to connect the longitudinal beam (202).

5. The intelligent monitoring method for deep foundation pits according to claim 3, characterized in that: One end of the second lead screw (222) is provided with a fourth bevel gear (219). A third bevel gear (218) is provided on one side of the fourth bevel gear (219). One end of the third bevel gear (218) meshes with the fourth bevel gear (219), and the third bevel gear (218) and the fourth bevel gear (219) are arranged perpendicular to each other; The other end of the third bevel gear (218) is provided with a second interface (210). The second interface (210) penetrates through the cross beam (201), and the second interface (210) is used to connect a servo motor.

6. The intelligent monitoring method for deep foundation pit according to claim 5, characterized in that: A GPS receiver (205) is provided on the top of the cross beam (201). A connecting plate (211) is provided on one side of the cross beam (201) close to the longitudinal beam (202). An inserting plate (216) is provided below the connecting plate (211), and the inserting plate (216) is used to cooperate with the slot (217); A first support (209) is provided inside the cross beam (201). A rotatable lifting lead screw (206) is provided on the first support (209). A lifting plate (207) is provided on the lifting lead screw (206), and an intelligent total station (208) is provided on the lifting plate (207).

7. The intelligent monitoring method for deep foundation pit according to claim 1, wherein: One end of the lifting lead screw (206) is provided with a second bevel gear (214). A first bevel gear (213) is provided on one side of the second bevel gear (214). One end of the first bevel gear (213) meshes with the second bevel gear (214), and the first bevel gear (213) and the second bevel gear (214) are arranged perpendicular to each other; At the other end of the first bevel gear (213), there is a first interface (210). The first interface (210) penetrates through the longitudinal beam (202), and the first interface (210) is used to connect the servo motor.

8. The intelligent monitoring method for deep foundation pit according to claim 1, characterized in that: In step S3, the parameters collected by the acquisition component (2) for the first prism (3), the second prism (4), and the third prism (5) include: angular parameters, distance parameters, and coordinate parameters; The angular parameters include the horizontal angle and the vertical angle , where the horizontal angle is used to determine the position of the prism in the horizontal direction, and the vertical angle is used to determine the position of the prism in the vertical direction; The distance parameter includes the slant range , by measuring the slant range , the three-dimensional coordinates of the prism can be calculated by combining the horizontal angle and the vertical angle. The calculation formula is as follows: ， ， ， Among them are the coordinates of the total station, and the intelligent total station (208) uploads the position data to the data processing module; In step S4, the data processing module includes: a data receiving module, a data storage module, and a feature extraction module; The data receiving module is used to receive the position data uploaded by the acquisition component (2), and perform preliminary format checks and data validations; The data storage module is used to store the received data in a database for subsequent query and analysis; The feature extraction module is used to extract features related to the foundation pit deformation from the stored data; In step S5, the designer then establishes a mechanical model based on the features extracted by the feature extraction module, combined with the geological conditions of the foundation pit and the support structure information.

9. The intelligent monitoring method for deep foundation pit according to claim 8, characterized in that: In step S5, the geological condition information of the foundation pit includes: the unit weight of the soil mass γ , cohesion c , and internal friction angle φ . The support structure information includes: the stiffness of the support frame (1) k and the tension of the anchor rod T . A mechanical model is established. In step S6, safety assessment is carried out according to the established mechanical model. The safety assessment steps include: S6.1 determining the assessment indicators as the maximum displacement, maximum settlement of the foundation pit, and the maximum internal force of the support structure; S6.2 calculating the index values using the mechanical model; S6.3 comparing the calculated index values with the preset safety thresholds; S6.4 dividing the safety levels according to the comparison results. The safety levels are divided into safe, warning, and dangerous; S6.5 automatically sending a warning signal when the safety level is warning. For the displacement exceeding the safety threshold, increase the number of supports and increase the support stiffness. For the internal force of the support structure exceeding the safety threshold, increase the anchor rod tension and reinforce the support structure to form a warning and optimization plan; S6.6 reconnect the warning and optimization plan to the data processing module. By setting a feedback mechanism, store the warning information and optimization plan in the database, and adjust the mechanical model according to the optimization plan in the model establishment module for recalculation and evaluation; S6.7 repeat steps such as data upload and feature extraction to regularly monitor and optimize the foundation pit until the foundation pit construction is completed.

10. The intelligent monitoring method for deep foundation pits according to claim 9, wherein: In steps S6.1 - S6.5, the safety assessment algorithm is: set the function , where is the unit weight of soil, is the cohesion, is the internal friction angle, is the stiffness of the support frame, is the tension of the anchor bolt; Calculate the mean value of the functional function and the standard deviation ; Determine the reliability index ; By comparing the reliability index with the target reliability index Evaluate the safety level of the foundation pit. When , it is determined that the foundation pit is in an unsafe state; The optimization algorithm for adjusting the support stiffness is as follows: Set the objective function , where is the safety index, is the cost function, which is related to the support stiffness . and are the weight coefficients. Using the genetic algorithm operation, through continuous iteration, find the value of the support stiffness that optimizes the objective function , and determine the optimization scheme.

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