Cloud-computing-based prefabricated retaining wall stability analysis system and method

Abstract

The application relates to the technical field of engineering management, and discloses an assembled retaining wall stability analysis system and method based on cloud computing, which comprises a multidimensional data module and an intelligent evaluation module. The assembled retaining wall stability analysis system and method based on cloud computing acquires construction data of all assembled retaining walls and environmental monitoring data at all time points through the multidimensional data module, classifies and forms data sets, the intelligent evaluation module analyzes the bearing coefficient of each assembled retaining wall, the deformation degree and the pressure state of each assembled retaining wall, generates a deformation coefficient and a side push coefficient, quantitatively evaluates whether the retaining wall has a lateral instability risk, comprehensively considers the influence of the long-term cumulative effect of environmental factors on the stability of the wall, generates an influence coefficient, has high multidimensional analysis precision, the intelligent evaluation module judges the bearing grade of the assembled retaining wall, the structural strength and the durability of the assembled retaining wall, outputs corresponding judgment results, evaluates the present situation and predicts future changes, and is high in safety.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of engineering management, in particular to an assembled retaining wall stability analysis system and method based on cloud computing. BACKGROUND

[0002] Assembled retaining walls are a type of retaining structure that is completed through factory prefabrication and on-site assembly. Their main functions include supporting soil, controlling landslides, maintaining slope stability, and preventing soil erosion. Assembled retaining walls are widely used in fields such as highways, railways, water conservancy, ports, and municipal engineering due to their rapid construction, controllable cost, and stable quality. Assembled retaining walls are assembled from prefabricated components, which include wall panels, foundation units, connecting pieces, and reinforced units. Common materials include reinforced concrete, prestressed concrete, and ecological materials, and some projects also use steel or plastic reinforcing materials to enhance performance. Components are manufactured through standardized processes in factories, ensuring dimensional accuracy and quality consistency, facilitating efficient on-site installation. At the same time, the shape and size of the components can be flexibly adjusted according to engineering needs to adapt to different terrain conditions and load requirements. Assembled retaining walls reduce the workload of on-site cast-in-place concrete through factory production of prefabricated components, shorten the construction period, and reduce dependence on environmental and climate conditions. Prefabricated components are designed with standardization, allowing for reuse or recycling, reducing resource waste. Assembled retaining walls need to withstand complex load conditions, including soil pressure, seismic force, wind force, and water pressure. If the stability is insufficient, it may cause wall sliding, overturning or damage, leading to soil instability and even landslides, collapse and other disasters, causing serious damage to the project and the surrounding environment. In particular, in high slopes, large-volume retaining walls, or important infrastructure, stability is crucial.

[0003] Currently, traditional assembled retaining wall stability analysis systems usually use real-time monitoring data to evaluate the current state of the retaining wall. When predicting the trend of retaining wall structure changes, long-term cumulative factors are often ignored, lacking precise early warning management capabilities, and unable to effectively predict potential safety risks. SUMMARY

[0004] (I) Technical problems solved

[0005] To address the shortcomings of the prior art, the present application provides an assembled retaining wall stability analysis system and method based on cloud computing, which has the advantages of high multi-dimensional analysis precision, intelligent early warning safety, etc., solving the problem that traditional assembled retaining wall stability analysis systems often ignore the comprehensive impact of long-term cumulative factors on wall structure, thus lacking precise early warning management capabilities.

[0006] (II) Technical solutions

[0007] In order to achieve the above object, the present application provides the following technical scheme: the prefabricated retaining wall stability analysis system based on cloud computing, comprising a multidimensional data module and an intelligent evaluation module;

[0008] The multidimensional data module is composed of a construction data unit and an environmental data unit, the construction data unit collects a construction data set through a network connection monitoring device, the construction data set includes construction data of all prefabricated retaining walls, and the environmental data unit collects an environmental data set through a network connection monitoring device, the environmental data set includes environmental monitoring data at all time points;

[0009] The intelligent evaluation module is composed of a quality analysis unit, a monitoring evaluation unit and a warning management unit, the quality analysis unit analyzes the bearing coefficient Czx of each group of prefabricated retaining walls according to the construction data set, the monitoring evaluation unit is provided with a fixed monitoring period zQ, and the deformation degree and the pressure state of each group of prefabricated retaining walls are analyzed in combination with the construction data set and the environmental data set, and the corresponding deformation coefficient Bxx and the lateral thrust coefficient Ctx are generated, the warning management unit analyzes the influence degree of various environmental factors on the prefabricated retaining wall according to the environmental data set, and generates the corresponding influence coefficient Yxx, the warning management unit is provided with a fixed range of bearing threshold Czy, deformation threshold Bxy, lateral thrust threshold Cty and influence threshold Yxy, and in combination with the bearing coefficient Czx, the deformation coefficient Bxx, the lateral thrust coefficient Ctx and the influence coefficient Yxx, the bearing grade of the prefabricated retaining wall, the structural strength and the durability of the prefabricated retaining wall are judged, and the corresponding judgment result is output.

[0010] Preferably, the expression of the construction data set is {Q1 d , Q2 d , Q3 d , …, Qn d}, Q1 d to Qn d are the construction data of the first group to the n-th group of prefabricated retaining walls, the construction data includes concrete compressive strength, reinforcement yield strength, grout bond strength, welding hardness, wall length, wall height and wall thickness, and d represents the construction time point of each group of prefabricated retaining walls.

[0011] Preferably, the expression of the environmental data set is {BX s , TY s , ZP s , ZF s , JL s}, BX s represents the deformation amount, TY s represents the soil pressure, ZP s represents the vibration frequency, ZF s represents the vibration amplitude, and JL srepresents the runoff, and s represents a specific time point at which the environmental monitoring data is obtained.

[0012] Preferably, the bearing coefficient Czx is calculated as follows:

[0013] Extract the construction data of the i-th group of fabricated retaining walls in the construction data set, and mark the compressive strength of the concrete of the i-th group of fabricated retaining walls as HK i Mark the yield strength of the steel reinforcement of the i-th group of fabricated retaining walls as GQ i Mark the bond strength of the grout of the i-th group of fabricated retaining walls as JN i Mark the welding hardness of the i-th group of fabricated retaining walls as HJ i Mark the wall height of the i-th group of fabricated retaining walls as GD i Mark the wall thickness of the i-th group of fabricated retaining walls as HD i ;

[0014]

[0015] In the formula, α1 represents the evaluation weight for the compressive strength of the concrete, α2 represents the evaluation weight for the yield strength of the steel reinforcement, α3 represents the evaluation weight for the bond strength of the grout, α4 represents the evaluation weight for the welding hardness, represents the ratio of the wall height to the wall thickness, and is used to measure the overturning resistance of the i-th group of fabricated retaining walls, α5 represents the evaluation weight for the ratio of the wall height to the wall thickness, and α1+α2+α3+α4+α5=1, represents the bearing coefficient Czx of the i-th group of fabricated retaining walls obtained according to α1, α2, α3, α4, and α5 i .

[0016] Preferably, the deformation coefficient Bxx is calculated as follows:

[0017] According to the construction data set, mark the construction time point of the i-th group of fabricated retaining walls as i d ;

[0018] According to the environmental data set, statistics the environmental monitoring data of the i-th group of fabricated retaining walls in the monitoring period zQ, and mark the deformation amount of the i-th group of fabricated retaining walls as {bx 1 , bx 2 , bx 3 , …, bx e}, bx 1 to bx e are the deformation amounts of the i-th group of fabricated retaining walls at the first to e-th monitoring times, respectively;

[0019]

[0020] In the formula, bx f represents the deformation amount of the i-th assembled retaining wall at the f-th monitoring time within the monitoring period ZQ, i s represents the specific time point of the environmental monitoring data of the i-th assembled retaining wall, i s d represents the time difference between the monitoring time point and the completion time point, that is, the completion duration of the i-th assembled retaining wall, represents the ratio of the deformation amount to the completion duration, that is, the deformation coefficient Bxx of the i-th assembled retaining wall i .

[0021] Preferably, the side pushing coefficient Ctx calculation process is as follows:

[0022] According to the construction data set, the wall length of the i-th assembled retaining wall is marked as CD i ;

[0023] According to the environmental data set, the environmental monitoring data of the i-th assembled retaining wall within the monitoring period ZQ is counted, and the earth pressure received by the i-th assembled retaining wall is marked as {ty 1 , ty 2 , ty 3 , …, ty u}, ty 1 to ty u are the earth pressures received by the i-th assembled retaining wall at the first to u-th monitoring times, respectively;

[0024]

[0025] In the formula, CD i × GD i represents the pressure area of the i-th assembled retaining wall, ty g represents the earth pressure received by the i-th assembled retaining wall at the g-th monitoring time within the monitoring period ZQ, represents the ratio of the earth pressure to the pressure area, that is, the side pushing coefficient Ctx of the i-th assembled retaining wall i .

[0026] Preferably, the influence coefficient Yxx calculation process is as follows:

[0027] According to the environmental data set, the environmental monitoring data of the i-th assembled retaining wall is extracted, and the vibration frequency of the environment where the i-th assembled retaining wall is located is marked as ZP i , the vibration amplitude of the environment where the i-th assembled retaining wall is located is marked as ZF i , and the runoff of the environment where the i-th assembled retaining wall is located is marked as JL i ;

[0028] Yxx i ​= β1 x ZP i + β2 x ZF i + β3 x JL i + β4 x (i s - i d )

[0029] In the formula, β1 represents an evaluation weight for the vibration frequency, β2 represents an evaluation weight for the vibration amplitude, β3 represents an evaluation weight for the runoff, β4 represents an evaluation weight for the built time, β1+β2+β3+β4=1, β1x ZP i + β2 x ZF i + β3 x JL i + β4 x (i s - i d ) represents an influence coefficient Yxx of the environment where the i-th assembled retaining wall is located according to the weights β1, β2, β3 and β4 i .

[0030] Preferably, when the bearing coefficient Czx is lower than the bearing threshold CZY, the assembled retaining wall is of a third bearing level, when the bearing coefficient Czx is included in the bearing threshold CZY, the assembled retaining wall is of a second bearing level, and when the bearing coefficient Czx is higher than the bearing threshold CZY, the assembled retaining wall is of a first bearing level, the stability of the assembled retaining wall of the first bearing level is higher than that of the second bearing level, and the stability of the assembled retaining wall of the second bearing level is higher than that of the third bearing level.

[0031] Preferably, when the deformation coefficient Bxx exceeds the deformation threshold BXY or the side push coefficient Ctx exceeds the side push threshold CTY within the monitoring period zQ, it indicates that the structural strength of the assembled retaining wall has been damaged, and when the influence coefficient Yxx exceeds the influence threshold YXY, it indicates that the durability of the assembled retaining wall has been damaged.

[0032] The assembled retaining wall stability analysis method based on cloud computing comprises the following steps:

[0033] Step one: connect the monitoring device through the network, obtain the construction data of all assembled retaining walls and the environmental monitoring data at all time points, and classify them into construction data set and environmental data set;

[0034] Step two: according to the construction data set and the environmental data set, analyze the bearing coefficient Cz x of each group of assembled retaining walls, and the deformation degree and pressure state of each group of assembled retaining walls, generate the corresponding deformation coefficient Bx x and side push coefficient Ct x ;

[0035] Step three: according to the environmental data set, analyze the influence degree of various environmental factors on the prefabricated retaining wall, and generate the corresponding influence coefficient Yx x ;

[0036] Step four: set the fixed range of bearing threshold CZY, deformation threshold BXY, side push threshold CTY and influence threshold YXY, and combine the bearing coefficient Cz x , the deformation coefficient Bx x , the side push coefficient Ct x and the influence coefficient Yx x , to judge the bearing grade of the prefabricated retaining wall, and the structural strength and durability of the prefabricated retaining wall, and output the corresponding judgment result.

[0037] Compared with the prior art, the present application provides a prefabricated retaining wall stability analysis system and method based on cloud computing, which has the following advantages:

[0038] 1、The present application obtains the construction data of all prefabricated retaining walls and the environmental monitoring data of all time points through the multi-dimensional data module network connection monitoring device, and classifies and forms the construction data set and the environmental data set, and the intelligent evaluation module analyzes the bearing coefficient Cz x of each group of prefabricated retaining walls according to the construction data set and the environmental data set, and the deformation degree and pressure state of each group of prefabricated retaining walls, generates the corresponding deformation coefficient Bx x and side push coefficient Ct x , carries out weighted analysis for each material in the wall structure, and combines with the cloud computing technology to accurately manage all prefabricated retaining walls, quantitatively evaluates whether the retaining wall exists lateral instability risk, analyzes the influence degree of various environmental factors on the prefabricated retaining wall, generates the corresponding influence coefficient Yx x , establishes a unified evaluation system to comprehensively consider the influence of environmental factors on the long-term cumulative effect of wall stability, and has high multi-dimensional analysis accuracy.

[0039] 2、The application sets fixed range bearing threshold CZY, deformation threshold BXY, side push threshold CTY and influence threshold YXY through the intelligent evaluation module, and then combines bearing coefficient Czx, deformation coefficient Bxx, side push coefficient Ctx and influence coefficient Yxx to judge the bearing grade of the assembled retaining wall and the structural strength and durability of the assembled retaining wall, the stability of the assembled retaining wall of the first bearing grade is higher than that of the second bearing grade, the stability of the assembled retaining wall of the second bearing grade is higher than that of the third bearing grade, and when the deformation coefficient Bxx exceeds the deformation threshold BXY or the side push coefficient Ctx exceeds the side push threshold CTY within the monitoring period ZQ, it indicates that the structural strength of the assembled retaining wall has been damaged, and when the influence coefficient Yxx exceeds the influence threshold YXY, it indicates that the durability of the assembled retaining wall has been damaged, which can not only evaluate the current situation of the retaining wall, but also predict the future stability change, issue an early warning, reduce the risk, and help to prolong the service life of the structure, and the intelligent early warning safety is high. BRIEF DESCRIPTION OF DRAWINGS

[0040] Figure 1 It is a system flowchart of the application;

[0041] Figure 2 It is a method step diagram of the application. DETAILED DESCRIPTION

[0042] The technical solutions in the embodiments of the application will be clearly and completely described below with reference to the drawings in the embodiments of the application. Obviously, the described embodiments are only part of the embodiments of the application, not all the embodiments. Based on the embodiments in the application, all other embodiments obtained by those skilled in the art without creative labor are within the scope of protection of the application.

[0043] Since the traditional assembled retaining wall stability analysis system usually uses real-time monitoring data to evaluate the current state of the retaining wall, when predicting the change trend of the retaining wall structure, the long-term cumulative factors on the wall structure are often ignored, and the precise early warning management ability is lacking, and potential safety risks cannot be effectively predicted, therefore, the assembled retaining wall stability analysis system and method based on cloud computing are provided, please refer to Figure 1 The assembled retaining wall stability analysis system based on cloud computing comprises a multi-dimensional data module and an intelligent evaluation module.

[0044] The multi-dimensional data module is composed of a construction data unit and an environment data unit, the construction data unit collects construction data sets through network connection monitoring devices, the construction data sets comprise construction data of all assembled retaining walls, and the expression of the construction data sets is {Q1 d , Q2 d , Q3 d , …, Qn d}, Q1d To Qn d These are the construction data for the first to nth groups of prefabricated retaining walls. The construction data includes concrete compressive strength, steel bar yield strength, grout bonding strength, welding hardness, wall length, wall height, and wall thickness. d represents the completion time of each group of prefabricated retaining walls. Accurate monitoring of the construction quality of each group of prefabricated retaining walls helps to quickly determine the load-bearing capacity of walls of different quality in the future.

[0045] The environmental data unit collects environmental datasets via a network connection to monitoring devices. The environmental datasets include environmental monitoring data at all time points, and the expression for the environmental dataset is {BX}. s TY s ZP s ZF s JL s}, BX s TY represents the amount of deformation. s ZP represents earth pressure. s ZF represents the vibration frequency. s Indicates the amplitude of vibration, JL s 's' represents the runoff volume, and 's' represents the specific time point at which the environmental monitoring data was acquired. Long-term monitoring of the potential impact of the external environment on the stability of the retaining wall provides multi-dimensional data support for subsequent assessments.

[0046] The intelligent assessment module consists of a quality analysis unit, a monitoring and assessment unit, and an early warning management unit. The quality analysis unit analyzes the bearing capacity coefficient Czx of each group of prefabricated retaining walls based on the construction dataset. The calculation process is as follows:

[0047] Extract the construction data of the i-th group of prefabricated retaining walls from the construction dataset, and label the concrete compressive strength of the i-th group of prefabricated retaining walls as HK. i Let GQ be the yield strength of the steel reinforcement in the i-th group of prefabricated retaining walls. i The mortar bonding strength of the i-th group of prefabricated retaining walls is marked as J『N i The welding hardness of the i-th group of prefabricated retaining walls is marked as HJ. i The height of the i-th group of prefabricated retaining walls is marked as GD. i The wall thickness of the i-th group of prefabricated retaining walls is marked as HD. i ;

[0048]

[0049] In the formula, α1 represents the evaluation weight for the compressive strength of concrete, α2 represents the evaluation weight for the yield strength of steel reinforcement, α3 represents the evaluation weight for the bond strength of grout, and α4 represents the evaluation weight for the weld hardness. represents the ratio of the wall height to the wall thickness, and is used to measure the overturning resistance of the i th group of fabricated retaining walls, a 5 represents the evaluation weight of the ratio of the wall height to the wall thickness, a 1 + a 2 + a 3 + a 4 + a 5 = 1, represents the bearing coefficient C zx of the i th group of fabricated retaining walls obtained according to a 1, a 2, a 3, a 4 and a 5 i , according to the weighted analysis of each material in the wall structure, and combined with cloud computing technology, the bearing coefficient C zx of all fabricated retaining walls is accurately managed, which can provide timely and accurate basis for decision-making of all parties;

[0050] The monitoring and evaluation unit is provided with a fixed monitoring period ZQ, and combined with the construction data set and the environmental data set, the deformation degree and the pressure state of each group of fabricated retaining walls are analyzed, and the corresponding deformation coefficient B xx and the lateral push coefficient C tx are generated;

[0051] The deformation coefficient B xx calculation process is as follows:

[0052] According to the construction data set, the construction time point of the i th group of fabricated retaining walls is marked as i d ;

[0053] According to the environmental data set, the environmental monitoring data of the i th group of fabricated retaining walls in the monitoring period ZQ is counted, and the deformation amount of the i th group of fabricated retaining walls is marked as {b x 1 , b x 2 , b x 3 , …, b x e}, b x 1 to b x e are the deformation amounts of the i th group of fabricated retaining walls at the first to e th monitoring times;

[0054]

[0055] In the formula, b x f represents the deformation amount of the i th group of fabricated retaining walls at the f th monitoring time in the monitoring period ZQ, i s represents the specific time point of the environmental monitoring data of the i th group of fabricated retaining walls, i s -i d represents the time difference between the monitoring time point and the construction time point, that is, the construction duration of the i th group of fabricated retaining walls, represents the ratio of the deformation amount to the construction duration, that is, the deformation coefficient B xx of the i th group of fabricated retaining walls i , specifically, the deformation amount includes but is not limited to the amount of subsidence, the inclination angle and the number of cracks, and the data source can be obtained by monitoring the appearance of the wall. According to each monitoring result, the deformation coefficient B xx is updated in real time, which is helpful to accurately judge the stability of the retaining wall;

[0056] The side push coefficient Ctx calculation process is as follows:

[0057] According to the construction data set, the wall length of the i th set of assembled retaining wall is marked as CD i ;

[0058] According to the environmental data set, the environmental monitoring data of the i th set of assembled retaining wall in the monitoring period zQ is counted, and the earth pressure received by the i th set of assembled retaining wall is marked as {ty 1 , ty 2 , ty 3 , …, ty u}, ty 1 to ty u are the earth pressures received by the i th set of assembled retaining wall in the first to u th monitoring, respectively;

[0059]

[0060] In the formula, CD i ×GD i represents the pressure area of the i th set of assembled retaining wall, ty g represents the earth pressure received by the i th set of assembled retaining wall in the g th monitoring in the monitoring period zQ, represents the ratio of earth pressure to pressure area, that is, the side push coefficient Ctx of the i th set of assembled retaining wall i , which quantitatively evaluates whether the retaining wall has lateral instability risk, and provides decision basis for later maintenance and reinforcement;

[0061] The early warning management unit analyzes the influence degree of various environmental factors on the assembled retaining wall according to the environmental data set, and generates the corresponding influence coefficient Yxx, and the calculation process is as follows:

[0062] According to the environmental data set, the environmental monitoring data of the i th set of assembled retaining wall is extracted, and the vibration frequency of the environment where the i th set of assembled retaining wall is located is marked as ZP i , the vibration amplitude of the environment where the i th set of assembled retaining wall is located is marked as ZF i , and the runoff of the environment where the i th set of assembled retaining wall is located is marked as JL i ;

[0063] Yxx i =β1×ZP i +β2×ZF i +β3×JL i +β4×(i s -i d )

[0064] In the formula, β1 represents the evaluation weight for the vibration frequency, β2 represents the evaluation weight for the vibration amplitude, β3 represents the evaluation weight for the runoff, β4 represents the evaluation weight for the construction time, β1+β2+β3+β4=1, β1×ZP i +β2×ZF i +β3×JL i +β4×(i s -i d ) represents the influence coefficient Yxxi of the environment where the ith assembled retaining wall is located according to the weights β1, β2, β3 and β4, a unified evaluation system is established to comprehensively consider the influence of environmental factors on the long-term cumulative effect of wall stability;

[0065] The early warning management unit is provided with fixed range bearing threshold CZY, deformation threshold BXY, side push threshold CTY and influence threshold YXY, and in combination with the bearing coefficient Czx, the deformation coefficient Bxx, the side push coefficient Ctx and the influence coefficient Yxx, the bearing grade of the assembled retaining wall and the structural strength and durability of the assembled retaining wall are judged. When the bearing coefficient Czx is lower than the bearing threshold CZY, the assembled retaining wall is of the third bearing grade, when the bearing coefficient Czx is included in the bearing threshold CZY, the assembled retaining wall is of the second bearing grade, and when the bearing coefficient Czx is higher than the bearing threshold CZY, the assembled retaining wall is of the first bearing grade. The stability of the assembled retaining wall of the first bearing grade is higher than that of the second bearing grade, and the stability of the assembled retaining wall of the second bearing grade is higher than that of the third bearing grade. Specifically, the inspection cycle of the assembled retaining wall of different bearing grades is also different. The inspection cycle of the third bearing grade retaining wall is shorter than that of the second bearing grade retaining wall. When the deformation coefficient Bxx exceeds the deformation threshold BXY or the side push coefficient Ctx x exceeds the side push threshold CTY, it indicates that the structural strength of the assembled retaining wall has been damaged, the influence coefficient Yx x exceeds the influence threshold YXY, it indicates that the durability of the assembled retaining wall has been damaged. Not only can the current situation of the retaining wall be evaluated, but also the future stability change can be predicted, early warning can be given, risk can be reduced, and the service life of the structure can be prolonged.

[0066] Please refer to Figure 2 , the assembled retaining wall stability analysis method based on cloud computing, comprising the following steps:

[0067] Step 1: Connect the monitoring device through the network to obtain the construction data of all assembled retaining walls and the environmental monitoring data at all time points, and classify them into construction data set and environmental data set;

[0068] Step 2: Based on the construction dataset and environmental dataset, analyze the bearing capacity coefficient Czx of each group of prefabricated retaining walls, as well as the deformation degree and compression state of each group of prefabricated retaining walls, and generate the corresponding deformation coefficient Bxx and lateral thrust coefficient Ctx.

[0069] Step 3: Based on the environmental dataset, analyze the impact of various environmental factors on prefabricated retaining walls and generate the corresponding impact coefficients Yxx. The multidimensional analysis has high accuracy.

[0070] Step 4: Set fixed ranges for the load-bearing threshold CZY, deformation threshold BXY, lateral thrust threshold CTY, and influence threshold YXY. Then, combine these with the load-bearing coefficient Czx, deformation coefficient Bxx, lateral thrust coefficient Ctx, and influence coefficient Yxx to determine the load-bearing capacity of the prefabricated retaining wall, as well as its structural strength and durability. Output the corresponding judgment results for intelligent early warning with high safety.

[0071] Example 1: In this experiment, a prefabricated retaining wall in a highway slope area was selected as the experimental object. The test results showed that the concrete compressive strength of the retaining wall was 30 MPa, the steel yield strength was 400 MPa, the grout bond strength was 2.5 MPa, the weld hardness was 1.8 MPa, the wall height was 5 m, and the wall thickness was 0.2 m. The bearing capacity coefficient Czx of this retaining wall is calculated using the following formula:

[0072]

[0073] In the formula, The ratio of wall height to wall thickness is used to measure the overturning resistance of the retaining wall. α1+α2+α3+α4+α5=1, α1, α2, α3, α4 and α5 are all 0.2, and the bearing capacity coefficient Czx of the retaining wall is 86.868.

[0074] Example 2: In this experiment, a prefabricated retaining wall in the railway track area was selected as the experimental object. After three quarters of testing, the deformation of the retaining wall in each quarter was 2mm, 3mm, and 4mm, respectively. The deformation coefficient Bxx of the retaining wall is calculated using the following formula:

[0075]

[0076] In the formula, i s -i d The time difference between the monitoring time point and the construction time point represents the construction time of the retaining wall. In the first quarter of monitoring, the construction time was 3 months; in the second quarter, it was 6 months; and in the third quarter, it was 9 months. After the three monitoring periods, the deformation coefficient of the retaining wall was 1.1.

[0077] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A cloud computing-based stability analysis system for prefabricated retaining walls, characterized in that: Includes a multi-dimensional data module and an intelligent evaluation module; The multidimensional data module consists of a construction data unit and an environmental data unit. The construction data unit collects construction datasets through a network-connected monitoring device. The construction datasets include construction data for all prefabricated retaining walls. The environmental data unit collects environmental datasets through a network-connected monitoring device. The environmental datasets include environmental monitoring data at all points in time. The intelligent assessment module consists of a quality analysis unit, a monitoring and assessment unit, and an early warning management unit. The quality analysis unit analyzes the bearing capacity coefficient Czx of each group of prefabricated retaining walls based on the construction dataset. The calculation process for the bearing capacity coefficient Czx is as follows: Extract the construction data of the i-th group of prefabricated retaining walls from the construction dataset, and label the concrete compressive strength of the i-th group of prefabricated retaining walls as HK. i Let GQ be the yield strength of the steel reinforcement in the i-th group of prefabricated retaining walls. i The mortar bonding strength of the i-th group of prefabricated retaining walls is denoted as JN. i The welding hardness of the i-th group of prefabricated retaining walls is marked as HJ. i The height of the i-th group of prefabricated retaining walls is marked as GD. i The wall thickness of the i-th group of prefabricated retaining walls is marked as HD. i ; In the formula, α1 represents the evaluation weight for the compressive strength of concrete, α2 represents the evaluation weight for the yield strength of steel reinforcement, α3 represents the evaluation weight for the bond strength of grout, and α4 represents the evaluation weight for the weld hardness. α1 represents the ratio of wall height to wall thickness, used to measure the overturning resistance of the i-th group of prefabricated retaining walls. α5 represents the evaluation weight for the ratio of wall height to wall thickness, and α1+α2+α3+α4+α5=1. This indicates that the bearing capacity Czx of the i-th group of prefabricated retaining walls is obtained according to α1, α2, α3, α4, and α5. i ; The monitoring and evaluation unit is set with a fixed monitoring period ZQ. Combined with the construction dataset and environmental dataset, it analyzes the deformation degree and compression state of each group of prefabricated retaining walls and generates the corresponding deformation coefficient Bxx and lateral thrust coefficient Ctx. The calculation process for the deformation coefficient Bxx is as follows: Based on the construction dataset, the completion time of the i-th group of prefabricated retaining walls is marked as i. d ; Based on the environmental dataset, the environmental monitoring data of the i-th group of prefabricated retaining walls within the monitoring period ZQ are statistically analyzed, and the deformation of the i-th group of prefabricated retaining walls is marked as {bx}. 1 bx 2 bx 3 ... bx e }, bx 1 To bx e These represent the deformation of the i-th group of prefabricated retaining walls during the first to the e-th monitoring sessions; In the formula, bx f This represents the deformation of the i-th prefabricated retaining wall during the f-th monitoring within the monitoring period ZQ. s This represents the specific time point of the environmental monitoring data for the i-th group of prefabricated retaining walls. s -i d The time difference between the monitoring time point and the construction time point represents the construction time of the i-th group of prefabricated retaining walls. The ratio of deformation to construction time is the deformation coefficient Bxx of the i-th group of prefabricated retaining walls. i ; The calculation process for the lateral thrust coefficient Ctx is as follows: Based on the construction dataset, the wall length of the i-th group of prefabricated retaining walls is marked as CD. i ; Based on the environmental dataset, the environmental monitoring data of the i-th group of prefabricated retaining walls within the monitoring period ZQ are statistically analyzed, and the earth pressure on the i-th group of prefabricated retaining walls is denoted as {ty}. 1 ty 2 ty 3 、...、ty u }, ty 1 to ty u These represent the earth pressures exerted on the i-th group of prefabricated retaining walls during the first to the u-th monitoring sessions; In the formula, CD i ×GD i ty represents the pressure-bearing area of ​​the i-th group of prefabricated retaining walls. g This represents the earth pressure exerted on the i-th prefabricated retaining wall during the g-th monitoring within the monitoring period ZQ. The ratio of earth pressure to the area under pressure is the lateral thrust coefficient Ctx of the i-th group of prefabricated retaining walls. i ; The early warning management unit analyzes the impact of various environmental factors on prefabricated retaining walls based on the environmental dataset and generates corresponding impact coefficients Yxx. The calculation process for the influence coefficient Yxx is as follows: Based on the environmental dataset, environmental monitoring data for the i-th group of prefabricated retaining walls are extracted, and the vibration frequency of the environment where the i-th group of prefabricated retaining walls is located is labeled as ZP. i The vibration amplitude of the environment where the i-th group of prefabricated retaining walls is located is denoted as ZF. i The runoff volume of the environment where the i-th group of prefabricated retaining walls is located is marked as JL. i ; Yxx i =β1×ZP i +β2×ZF i +β3×JL i +β4×(i s -i d ) In the formula, β1 represents the evaluation weight for vibration frequency, β2 represents the evaluation weight for vibration amplitude, β3 represents the evaluation weight for runoff, and β4 represents the evaluation weight for construction duration. β1 + β2 + β3 + β4 = 1, β1 × ZP i +β2×ZF i +β3×JL i +β4×(i s -i d The symbol Yxx represents the influence coefficient of the environment of the i-th group of prefabricated retaining walls, calculated according to the weights β1, β2, β3, and β4. i ; The early warning management unit is equipped with a fixed range of bearing threshold CZY, deformation threshold BXY, lateral thrust threshold CTY, and influence threshold YXY. Combined with the bearing coefficient Czx, deformation coefficient Bxx, lateral thrust coefficient Ctx, and influence coefficient Yxx, it determines the bearing capacity level of the prefabricated retaining wall, as well as the structural strength and durability of the prefabricated retaining wall, and outputs the corresponding judgment results.

2. The cloud computing-based prefabricated retaining wall stability analysis system according to claim 1, characterized in that: The expression for the construction dataset is {Q1} d Q2 d Q3 d ... Qn d }, Q1 d To Qn d These are the construction data for the first to nth groups of prefabricated retaining walls. The construction data includes concrete compressive strength, steel bar yield strength, grout bond strength, welding hardness, wall length, wall height, and wall thickness. d represents the completion time of each group of prefabricated retaining walls.

3. The cloud computing-based prefabricated retaining wall stability analysis system according to claim 2, characterized in that: The expression for the environmental dataset is {BX} s TY s ZP s ZF s JL s }, BX s TY represents the amount of deformation. s ZP represents earth pressure. s ZF represents the vibration frequency. s Indicates the amplitude of vibration, JL s 's' represents runoff volume, and 's' represents the specific time point at which environmental monitoring data was acquired.

4. The cloud computing-based prefabricated retaining wall stability analysis system according to claim 3, characterized in that: When the bearing capacity coefficient Czx is lower than the bearing capacity threshold CZY, the prefabricated retaining wall is of level three bearing capacity. When the bearing capacity coefficient Czx is included in the bearing capacity threshold CZY, the prefabricated retaining wall is of level two bearing capacity. When the bearing capacity coefficient Czx is higher than the bearing capacity threshold CZY, the prefabricated retaining wall is of level one bearing capacity. The stability of the prefabricated retaining wall of level one bearing capacity is higher than that of level two bearing capacity. The stability of the prefabricated retaining wall of level two bearing capacity is higher than that of level three bearing capacity.

5. The cloud computing-based prefabricated retaining wall stability analysis system according to claim 4, characterized in that: Within the monitoring period ZQ, if the deformation coefficient Bxx exceeds the deformation threshold BXY or the lateral thrust coefficient Ctx exceeds the lateral thrust threshold CTY, it indicates that the structural strength of the prefabricated retaining wall has been damaged. If the influence coefficient Yxx exceeds the influence threshold YXY, it indicates that the durability of the prefabricated retaining wall has been damaged.

6. A cloud computing-based method for analyzing the stability of prefabricated retaining walls, applied to the cloud computing-based prefabricated retaining wall stability analysis system described in any one of claims 1-5, characterized in that, Includes the following steps: Step 1: Connect the monitoring device via the network to acquire all construction data of the prefabricated retaining walls and environmental monitoring data at all time points, and classify them into construction datasets and environmental datasets; Step 2: Based on the construction dataset and environmental dataset, analyze the bearing capacity coefficient Vzx of each group of prefabricated retaining walls, as well as the deformation degree and compression state of each group of prefabricated retaining walls, and generate the corresponding deformation coefficient Bxx and lateral thrust coefficient Ctx. Step 3: Based on the environmental dataset, analyze the impact of various environmental factors on prefabricated retaining walls and generate the corresponding impact coefficients Yxx; Step 4: Set fixed ranges for the load-bearing threshold CZY, deformation threshold BXY, lateral thrust threshold CTY, and influence threshold YXY. Then, combine these with the load-bearing coefficient Czx, deformation coefficient Bxx, lateral thrust coefficient Ctx, and influence coefficient Yxx to determine the load-bearing capacity of the prefabricated retaining wall, as well as its structural strength and durability, and output the corresponding results.

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