A tunnel waterproofing construction method

Abstract

The present invention provides a tunnel waterproofing construction method, which identifies water-prone areas on an underground three-dimensional model by graying a deformation distribution cloud map into a grayscale cloud map; marks corresponding positions of the water-prone areas on a tunnel area to be constructed as installation positions of a waterproof protective layer to perform waterproofing layer construction at the installation positions; the waterproofing protective layer established by the waterproofing layer construction operation includes a self-waterproofing structural layer of a concrete structure connected to each other by a moisture-proof adhesive, an inner waterproofing layer of at least one layer of synthetic polymer waterproofing coiled material, and a reinforcing layer. The construction method can realize the identification of water-prone areas of a tunnel to be constructed in advance, and then waterproof protection of the tunnel is performed by a variety of effective waterproofing structures including synthetic polymer waterproofing coiled materials, thereby reducing the manpower and material resources for surveying, and has a good waterproofing effect, and can prevent possible water seepage in the future.

Description

Technical Field

[0001] The invention belongs to the technical field of model simulation calculation and waterproof construction, and specifically relates to a tunnel waterproof construction method. Background Art

[0002] Tunnel waterproofing projects often need to be constructed according to the specific water seepage conditions of the tunnel surface under the premise of meeting construction standards, and the construction method needs to consider factors such as the initial design of the tunnel, building quality and waterproof materials. At present, tunnel waterproofing projects are generally carried out manually after the internal conditions of the tunnel are surveyed on the spot. According to the survey results and manual evaluation results, the construction location is selected for the construction of the waterproof layer. This approach is too dependent on on-site surveys and manual evaluation levels, which consumes manpower and material resources, and the waterproofing effect is average. It cannot prevent possible water seepage in the future, so there are defects and it is urgent to improve. Summary of the invention

[0003] The purpose of the present invention is to propose a tunnel waterproofing construction method to solve one or more technical problems existing in the prior art and at least provide a beneficial option or create conditions.

[0004] In order to achieve the above object, according to one aspect of the present invention, a tunnel waterproofing construction method is provided, characterized in that the method comprises the following steps:

[0005] S100, obtaining an underground three-dimensional model of the area where the tunnel is to be constructed;

[0006] S200, importing the underground three-dimensional model into finite element analysis software to divide the finite element mesh to obtain a finite element model;

[0007] S300, performing nonlinear finite element analysis on the finite element model to obtain a deformation distribution cloud map of the underground three-dimensional model at a preset water level;

[0008] S400, graying the deformation distribution cloud map into a gray cloud map, performing edge detection to divide the deformation area;

[0009] S500, identifying a water-prone area on the underground three-dimensional model according to the deformation area;

[0010] S600, marking the corresponding position of the water-permeable area on the tunnel area to be constructed as the installation position of the waterproof protective layer;

[0011] S700, in the tunnel area to be constructed, waterproof layer construction work is carried out at the installation position; the waterproof protective layer established by the waterproof layer construction work includes a self-waterproof structural layer of a concrete structure connected to each other by a moisture-proof adhesive, an inner waterproof layer of at least one layer of synthetic polymer waterproof membrane, and a reinforcement layer.

[0012] Furthermore, in step S100, the method for obtaining the underground three-dimensional model of the area where the tunnel is to be constructed is:

[0013] A sensor group is arranged on multiple tunnel surfaces in the tunnel area to be constructed to collect underground space exploration data corresponding to the tunnel area to be constructed, including multiple types of sensor data; the sensor group includes a ground penetrating radar, a temperature and humidity sensor, an infrared ranging sensor and a sonar sensor; the ground penetrating radar is a BA series three-dimensional ground penetrating radar or a GeoScope three-dimensional ground penetrating radar;

[0014] Based on a preset hybrid model 3D modeling algorithm, 3D modeling is performed according to the underground space survey data to obtain an initial underground 3D model;

[0015] Initial stress data of tunnel components and tunnel soil are added to the initial underground three-dimensional model to perform initial working condition simulation to obtain the underground three-dimensional model of the tunnel area to be constructed.

[0016] Furthermore, in step S300, the specific method of performing nonlinear finite element analysis on the finite element model to obtain the deformation distribution cloud map of the underground three-dimensional model at a preset water level is:

[0017] Inputting the underground three-dimensional model into ABAQUS finite element software, and obtaining preset water pressure load simulation conditions including multiple water level levels;

[0018] According to the hydraulic load simulation conditions of the multiple water levels, a hydraulic load is applied to the underground three-dimensional model in the software, and the water pressure is directly applied to the water-facing surface of the underground three-dimensional model in the form of surface force, and a full-process simulation calculation of the underground three-dimensional model bearing the water pressure is performed to obtain multiple simulation results; the material parameters of the full-process simulation calculation are: regression statistical analysis is performed on the temperature and radial deformation monitoring data of the tunnel, and the water temperature boundary conditions, air temperature boundary conditions and mechanical parameters of the tunnel are obtained by inversion. Under the conditions of the preset linear expansion coefficient and elastic modulus of the concrete material parameters, the relationship between the deformation and the load change is obtained through positive analysis, and the material parameters are adjusted based on the regression analysis of the measured deformation data using the relationship, so as to determine the material parameters of the tunnel;

[0019] A deformation distribution cloud map of the underground three-dimensional model is determined according to the multiple simulation results.

[0020] Furthermore, each simulation result includes deformation parameters in different directions on different tunnel surfaces of the underground three-dimensional model; and determining the deformation distribution cloud map of the underground three-dimensional model according to the multiple simulation results includes:

[0021] All the simulation results are superimposed and combined to obtain a deformation distribution result corresponding to the underground three-dimensional model;

[0022] For each tunnel face position in the underground three-dimensional model, calculating a parameter set corresponding to all deformation parameters in the deformation distribution result corresponding to the tunnel face position;

[0023] The parameter set of the tunnel surface position is input into a trained CNN neural network model to obtain a deformation degree parameter corresponding to the tunnel surface; the CNN neural network model is trained by a training data set including a training parameter set and corresponding deformation degree annotations;

[0024] Based on the deformation degree parameter, all deformation parameters corresponding to the tunnel surface position are screened to obtain a target deformation parameter set corresponding to the tunnel surface position;

[0025] Calculating the average values ​​of all parameters in the target deformation parameter set to obtain the deformation parameter result corresponding to the tunnel face position;

[0026] A deformation distribution cloud map of the underground three-dimensional model is generated according to the deformation parameter results corresponding to all the tunnel surface positions.

[0027] Furthermore, based on the deformation degree parameter, all deformation parameters corresponding to the tunnel surface position are screened to obtain a target deformation parameter set corresponding to the tunnel surface position, including:

[0028] Calculating a screening weight proportional to the deformation degree parameter;

[0029] Calculating the product of a preset deformation parameter reference value and the screening weight to obtain a screening threshold;

[0030] Among all deformation parameters corresponding to the tunnel surface position, deformation parameters whose parameter values ​​are greater than the screening threshold are retained to obtain a target deformation parameter set corresponding to the tunnel surface position.

[0031] Further, in step S500, the method for identifying the water-permeable area on the underground three-dimensional model according to the deformation area is:

[0032] For each of the deformation regions, in the spatial coordinate system of the underground three-dimensional model, visual framing images corresponding to multiple angles of the deformation region are obtained at different viewpoint angles;

[0033] Inputting the visual images corresponding to the multiple angles into a trained RNN neural network to obtain the water seepage probability corresponding to the deformed area; the RNN neural network model is trained by a training data set including a training visual image set and corresponding water seepage probability annotations;

[0034] Acquire a plurality of historical simulation data of the area position corresponding to the deformation area in the historical database;

[0035] Calculating a position hazard parameter corresponding to the deformation area according to the plurality of historical simulation data;

[0036] Calculate the number of component edges of the tunnel surface corresponding to the deformation area;

[0037] Calculate the product of the water seepage probability, the position hazard parameter and the number of component edges to obtain the water seepage parameter corresponding to the deformation area;

[0038] According to the water seepage parameter, a water-prone area in the underground three-dimensional model where the water seepage parameter is greater than a preset water seepage threshold is identified from all the deformation areas.

[0039] Furthermore, according to the plurality of historical simulation data, a method for calculating the position hazard parameter corresponding to the deformation area is:

[0040] Calculate the ratio of the number of records with deformation at the regional position in each of the historical simulation data to the number of all records;

[0041] Calculate the weighted sum average of all the quantity ratios to obtain the position hazard parameter corresponding to the deformation area; wherein the calculation weight corresponding to each of the quantity ratios is inversely proportional to the nearby deformation ratio corresponding to the regional position in the corresponding historical simulation data; the nearby deformation ratio is the proportion of the number of deformed positions within a circular area with a preset radius as the center of the regional position in the historical simulation data.

[0042] Furthermore, the method for calculating the number of component edges of the tunnel surface corresponding to the deformation area is:

[0043] Traversing all component objects in the tunnel surface corresponding to the deformation area;

[0044] Acquiring the contact edge lines between any two of the component objects;

[0045] Screening out all the contact edge lines that intersect with the deformation area to obtain a line set;

[0046] The number of lines in the line set is calculated to obtain the number of component edges of the tunnel surface corresponding to the deformation area.

[0047] Furthermore, after step S600, the method further includes:

[0048] For each of the installation positions, obtaining the area of ​​the water-prone region, the water seepage probability, and the number of component edges corresponding to the installation position;

[0049] According to the preset mathematical correspondence between area and materials, the type of construction materials, the amount of materials and the construction operation corresponding to the area of ​​the region are calculated; the construction operation includes the number and sequence of construction of different waterproof layers;

[0050] Calculate the product of the water seepage probability and the number of edges of the component to obtain a construction difficulty parameter;

[0051] Calculating a first weight and a second weight that are proportional to the construction difficulty parameter;

[0052] Calculating the product of the material amount and the first weight to obtain a corrected material amount;

[0053] Calculate the product of the construction quantity and the second weight to obtain the corrected waterproof layer quantity;

[0054] The type of construction materials, the amount of revised materials and the construction operation including the number of revised waterproof layers are determined as the construction strategy plan corresponding to the installation location.

[0055] Furthermore, before step S700, the method further includes:

[0056] Inputting the construction strategy scheme corresponding to each installation position into the trained cost accounting neural network to obtain the construction cost corresponding to each installation position;

[0057] Calculate the sum of the construction costs corresponding to all the installation locations to obtain the project cost;

[0058] Calculate the sum of the parameters in all the construction strategy solutions to obtain the engineering solution;

[0059] The engineering plan and the engineering cost are sent to the corresponding construction party equipment terminal.

[0060] The present invention also provides a tunnel waterproof construction system, which includes: a processor, a memory, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps in the tunnel waterproof construction method are implemented. The tunnel waterproof construction system can be run in computing devices such as desktop computers, laptop computers, PDAs, and cloud data centers. The executable system may include, but is not limited to, a processor, a memory, and a server cluster. The processor executes the computer program and runs it in the following system units:

[0061] An underground model acquisition unit, used to acquire an underground three-dimensional model of the tunnel area to be constructed;

[0062] Finite element division unit, used to import the underground three-dimensional model into the finite element analysis software to divide the finite element mesh to obtain the finite element model;

[0063] A deformation simulation unit is used to perform nonlinear finite element analysis on the finite element model to obtain a deformation distribution cloud map of the underground three-dimensional model at a preset water level;

[0064] An edge detection unit is used to grayscale the deformation distribution cloud map into a grayscale cloud map, perform edge detection and divide the deformation area;

[0065] A water seepage identification unit, used to identify water-prone areas on the underground three-dimensional model based on the deformation area;

[0066] The protective layer positioning unit is used to mark the corresponding position of the water-permeable area on the tunnel area to be constructed as the installation position of the waterproof protective layer.

[0067] The beneficial effects of the present invention are as follows: the present invention provides a tunnel waterproofing construction method, which can use a finite element analysis algorithm to analyze the underground three-dimensional model of the tunnel to obtain the deformation area, and then accurately identify the water-prone area, and construct a corresponding waterproof protective layer containing a synthetic polymer waterproof membrane in the water-prone area, so as to realize the early identification of the water-prone area of ​​the tunnel to be constructed, and then waterproof the tunnel through a variety of effective waterproof structures including synthetic polymer waterproof membranes, thereby reducing the manpower and material resources for surveying, and having a good waterproofing effect, which can prevent possible water seepage in the future. BRIEF DESCRIPTION OF THE DRAWINGS

[0068] The above and other features of the present invention will become more obvious by describing in detail the embodiments shown in the accompanying drawings. The same reference numerals in the accompanying drawings of the present invention represent the same or similar elements. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other accompanying drawings can be obtained based on these accompanying drawings without creative work. In the accompanying drawings:

[0069] Figure 1 Shown is a flow chart of a tunnel waterproofing construction method;

[0070] Figure 2 Shown is the structural diagram of the tunnel waterproofing construction system. DETAILED DESCRIPTION

[0071] The following will be combined with the embodiments and drawings to clearly and completely describe the concept, specific structure and technical effects of the present invention, so as to fully understand the purpose, scheme and effect of the present invention. It should be noted that the embodiments and features in the embodiments of this application can be combined with each other without conflict.

[0072] like Figure 1 The figure shows a flow chart of a tunnel waterproofing construction method. Figure 1 A tunnel waterproofing construction method according to an embodiment of the present invention is described, and the method comprises the following steps:

[0073] S100, obtaining an underground three-dimensional model of the area where the tunnel is to be constructed;

[0074] S200, importing the underground three-dimensional model into finite element analysis software to divide the finite element mesh to obtain a finite element model;

[0075] S300, performing nonlinear finite element analysis on the finite element model to obtain a deformation distribution cloud map of the underground three-dimensional model at a preset water level;

[0076] S400, graying the deformation distribution cloud map into a gray cloud map, performing edge detection to divide the deformation area;

[0077] S500, identifying a water-prone area on the underground three-dimensional model according to the deformation area;

[0078] S600, marking the corresponding position of the water-permeable area on the tunnel area to be constructed as the installation position of the waterproof protective layer;

[0079] S700, in the tunnel area to be constructed, waterproof layer construction work is carried out at the installation position; the waterproof protective layer established by the waterproof layer construction work includes a self-waterproof structural layer of a concrete structure connected to each other by a moisture-proof adhesive, an inner waterproof layer of at least one layer of synthetic polymer waterproof membrane, and a reinforcement layer.

[0080] Through the above-mentioned embodiments, it is possible to identify the water-prone areas of the tunnel to be constructed in advance, and then waterproof the tunnel through a variety of effective waterproof structures including synthetic polymer waterproof membranes, thereby reducing the manpower and material resources for surveying, and achieving good waterproofing effects, which can prevent possible water seepage in the future.

[0081] In an optional embodiment, in step S100, the method for obtaining the underground three-dimensional model of the area where the tunnel is to be constructed is:

[0082] A sensor group is arranged on multiple tunnel faces in the tunnel area to be constructed to collect underground space exploration data corresponding to the tunnel area to be constructed, including various types of sensor data; the sensor group includes a ground penetrating radar, a temperature and humidity sensor, an infrared ranging sensor, and a sonar sensor; the ground penetrating radar is a BA series three-dimensional ground penetrating radar or a GeoScope three-dimensional ground penetrating radar;

[0083] Based on the preset hybrid model 3D modeling algorithm, 3D modeling is performed according to the underground space survey data to obtain an initial underground 3D model;

[0084] The initial stress data of tunnel components and tunnel soil are added to the initial underground three-dimensional model to perform initial working condition simulation to obtain an underground three-dimensional model of the tunnel area to be constructed.

[0085] Through the above-mentioned optional embodiments, an initial underground three-dimensional model can be obtained by three-dimensional modeling through underground space exploration data including various types of sensor data and a hybrid model three-dimensional modeling algorithm, so as to obtain a three-dimensional model that can more realistically reflect the physical conditions of the tunnel area. Subsequently, it can be realized to identify the water-prone areas of the tunnel to be constructed in advance, and then the tunnel can be waterproofed through a variety of effective waterproof structures including synthetic polymer waterproof membranes, thereby reducing the manpower and material resources for surveying, and having a good waterproofing effect, which can prevent possible water seepage in the future.

[0086] In an optional embodiment, in step S300, the specific method of performing nonlinear finite element analysis on the finite element model to obtain a deformation distribution cloud map of the underground three-dimensional model at a preset water level is:

[0087] Input the underground three-dimensional model into ABAQUS finite element software and obtain the preset water pressure load simulation conditions including multiple water level levels;

[0088] According to the hydraulic load simulation conditions of multiple water levels, a hydraulic load is applied to the underground three-dimensional model in the software, and the water pressure is directly applied to the water-facing surface of the underground three-dimensional model in the form of surface force, and the whole process simulation calculation of the underground three-dimensional model bearing the water pressure is performed to obtain multiple simulation results; the material parameters of the whole process simulation calculation are: regression statistical analysis is performed on the temperature and radial deformation monitoring data of the tunnel, and the water temperature boundary conditions, air temperature boundary conditions and mechanical parameters of the tunnel are obtained by inversion. Under the conditions of the preset linear expansion coefficient and elastic modulus of the concrete material parameters, the relationship between the deformation and the load change is obtained through positive analysis, and the material parameters are adjusted based on the regression analysis of the measured deformation data using the relationship, so as to determine the material parameters of the tunnel;

[0089] According to multiple simulation results, the deformation distribution cloud map of the underground three-dimensional model is determined.

[0090] Through the above-mentioned optional embodiments, it is possible to obtain multiple simulation results by performing full-process simulation calculations of the underground three-dimensional model withstanding water pressure through water pressure load simulation conditions including multiple water level levels, so as to obtain tunnel deformation simulation results under multiple water pressure conditions, and then determine the deformation distribution cloud map based on this, so that the deformation distribution cloud map can more realistically reflect the deformation of the tunnel area under multiple water pressure conditions, and subsequently it can be realized to identify the water-prone areas of the tunnel to be constructed in advance, and then use a variety of effective waterproof structures including synthetic polymer waterproof membranes to provide waterproof protection for the tunnel, thereby reducing the manpower and material resources for surveying, and having a good waterproof effect, which can prevent possible water seepage in the future.

[0091] In an optional embodiment, each simulation result includes deformation parameters in different directions on different tunnel surfaces of the underground three-dimensional model; and determining a deformation distribution cloud map of the underground three-dimensional model according to the multiple simulation results includes:

[0092] All simulation results are superimposed and combined to obtain the deformation distribution results corresponding to the underground three-dimensional model;

[0093] For each tunnel face position in the underground three-dimensional model, a parameter set corresponding to all deformation parameters in the deformation distribution result corresponding to the tunnel face position is calculated;

[0094] The parameter set of the tunnel surface position is input into the trained CNN neural network model to obtain the deformation degree parameter corresponding to the tunnel surface; the CNN neural network model is trained by a training data set including the training parameter set and the corresponding deformation degree annotation;

[0095] Based on the deformation degree parameter, all deformation parameters corresponding to the tunnel surface position are screened to obtain a target deformation parameter set corresponding to the tunnel surface position;

[0096] Calculate the average value of all parameters in the target deformation parameter set to obtain the deformation parameter result corresponding to the tunnel face position;

[0097] According to the deformation parameter results corresponding to all tunnel face positions, a deformation distribution cloud map of the underground three-dimensional model is generated.

[0098] Through the above optional embodiments, the deformation degree parameters can be predicted by the trained CNN neural network model, and then used to screen the parameter set of each tunnel surface position for average calculation to generate the deformation distribution cloud map of the underground three-dimensional model, so that the deformation distribution cloud map can more realistically reflect the deformation of the tunnel area under various water pressure conditions, and subsequently it can be realized to identify the water-prone areas of the tunnel to be constructed in advance, and then the tunnel can be waterproofed through a variety of effective waterproof structures including synthetic polymer waterproof membranes, thereby reducing the manpower and material resources for surveying, and the waterproof effect is good, which can prevent possible water seepage in the future.

[0099] In an optional embodiment, based on the deformation degree parameter, all deformation parameters corresponding to the tunnel surface position are screened to obtain a target deformation parameter set corresponding to the tunnel surface position, including:

[0100] Calculate the screening weight proportional to the deformation degree parameter;

[0101] Calculate the product of the preset deformation parameter reference value and the screening weight to obtain the screening threshold;

[0102] Among all deformation parameters corresponding to the tunnel surface position, deformation parameters whose parameter values ​​are greater than the screening threshold are retained to obtain a target deformation parameter set corresponding to the tunnel surface position.

[0103] Through the above optional embodiments, the screening threshold can be obtained by multiplying the preset deformation parameter reference value and the screening weight, and then used to screen out the parameter set corresponding to the number of parameters and the deformation degree of each tunnel surface position for average calculation to generate the deformation distribution cloud map of the underground three-dimensional model, so that the deformation distribution cloud map can more realistically reflect the deformation of the tunnel area under various water pressure conditions, and subsequently it can be realized to identify the water-prone areas of the tunnel to be constructed in advance, and then the tunnel can be waterproofed through a variety of effective waterproof structures including synthetic polymer waterproof membranes, thereby reducing the manpower and material resources for surveying, and the waterproof effect is good, which can prevent possible water seepage in the future.

[0104] In an optional embodiment, in step S500, the method for identifying the water-permeable area on the underground three-dimensional model according to the deformation area is:

[0105] For each deformation area, in the spatial coordinate system of the underground three-dimensional model, visual framing images corresponding to multiple angles of the deformation area are obtained at different viewpoints;

[0106] The visual images corresponding to multiple angles are input into the trained RNN neural network to obtain the water seepage probability corresponding to the deformed area; the RNN neural network model is trained by a training data set including a training visual image set and corresponding water seepage probability annotations;

[0107] Acquire a plurality of historical simulation data of the area position corresponding to the deformation area in the historical database;

[0108] Calculate the position hazard parameter corresponding to the deformation area according to a plurality of historical simulation data;

[0109] Calculate the number of component edges of the tunnel surface corresponding to the deformation area;

[0110] Calculate the product of water seepage probability, location hazard parameter and number of component edges to obtain the water seepage parameter corresponding to the deformation area;

[0111] According to the water seepage parameter, the water-prone areas in the underground three-dimensional model whose water seepage parameters are greater than a preset water seepage threshold are identified from all deformation areas.

[0112] Through the above optional embodiments, the water seepage probability corresponding to each deformation area can be calculated through the RNN neural network and multi-angle visual framing images, and then used to calculate the water seepage parameters to identify the water-prone areas in the underground three-dimensional model whose water seepage parameters are greater than the preset water seepage threshold from all deformation areas. It is possible to accurately identify the water-prone areas of the tunnel to be constructed in advance, and then use a variety of effective waterproof structures including synthetic polymer waterproof membranes to waterproof the tunnel, thereby reducing the manpower and material resources for surveying, and having a good waterproof effect, which can prevent possible water seepage in the future.

[0113] In an optional embodiment, a method for calculating the position hazard parameter corresponding to the deformation area according to a plurality of historical simulation data is:

[0114] Calculate the ratio of the number of records with deformation in the regional position in each historical simulation data to the number of all records;

[0115] Calculate the weighted sum average of all quantity ratios to obtain the position hazard parameter corresponding to the deformation area; wherein the calculation weight corresponding to each quantity ratio is inversely proportional to the nearby deformation ratio corresponding to the regional position in the corresponding historical simulation data; the nearby deformation ratio is the proportion of the number of deformed positions in the circular area with a preset radius as the center of the regional position in the historical simulation data.

[0116] Through the above-mentioned optional embodiments, the ratio of the number of records with deformation at the regional location to the number of all records can be calculated through historical simulation data, and then used to calculate the position hazard parameters corresponding to the deformed area, so that the seepage parameters calculated based on this can identify the water-prone areas in the underground three-dimensional model where the seepage parameters are greater than the preset seepage threshold from all deformed areas, thereby achieving accurate identification of the water-prone areas of the tunnel to be constructed in advance, and then waterproofing the tunnel through a variety of effective waterproof structures including synthetic polymer waterproof membranes, thereby reducing the manpower and material resources for surveying, and having a good waterproofing effect, which can prevent possible water seepage in the future.

[0117] In an optional embodiment, the method for calculating the number of component edges of the tunnel surface corresponding to the deformation area is:

[0118] Traversing all component objects in the tunnel surface corresponding to the deformation area;

[0119] Obtain the contact edge lines between any two component objects;

[0120] Filter out all contact edge lines that intersect with the deformation area to obtain a line set;

[0121] The number of lines in the line set is calculated to obtain the number of component edges of the tunnel surface corresponding to the deformation area.

[0122] Through the above-mentioned optional embodiments, the number of component edges of the tunnel surface corresponding to the deformation area can be determined through a traversal algorithm and intersection calculation, so that the seepage parameters calculated based on this can identify the water-prone areas in the underground three-dimensional model where the seepage parameters are greater than the preset seepage threshold from all deformation areas, thereby achieving accurate identification of the water-prone areas of the tunnel to be constructed in advance, and then waterproofing the tunnel through a variety of effective waterproof structures including synthetic polymer waterproof membranes, thereby reducing the manpower and material resources for surveying, and having a good waterproofing effect, which can prevent possible water seepage in the future.

[0123] In an optional embodiment, after step S600, the method further includes:

[0124] For each installation position, obtain the area, water seepage probability and number of component edges of the water-prone area corresponding to the installation position;

[0125] According to the preset mathematical correspondence between area and materials, the type, quantity and construction operation of construction materials corresponding to the area are calculated; the construction operation includes the number and sequence of construction of different waterproof layers;

[0126] Calculate the product of the water seepage probability and the number of component edges to obtain the construction difficulty parameter;

[0127] Calculate a first weight and a second weight that are proportional to the construction difficulty parameter;

[0128] Calculate the product of the material amount and the first weight to obtain the corrected material amount;

[0129] Calculate the product of the construction quantity and the second weight to obtain the corrected waterproof layer quantity;

[0130] The type of construction materials, the corrected material quantities and the construction operations including the corrected number of waterproof layers are determined as the construction strategy plan corresponding to the installation location.

[0131] Through the above optional embodiments, the construction strategy plan corresponding to the installation location can be calculated through the preset mathematical correspondence between the area and materials and the weight calculation rules, so that the construction party can accurately prepare for the construction based on the results of the above data simulation and improve construction efficiency.

[0132] In an optional embodiment, before step S700, the method further includes:

[0133] Input the construction strategy plan corresponding to each installation position into the trained cost accounting neural network to obtain the construction cost corresponding to each installation position;

[0134] Calculate the sum of the construction costs corresponding to all installation locations to obtain the project cost;

[0135] Calculate the sum of the parameters in all construction strategy solutions to obtain the engineering solution;

[0136] Send the project plan and project cost to the corresponding construction party's equipment terminal.

[0137] Through the above optional embodiments, the engineering plan and engineering cost corresponding to the construction plan can be determined through cost accounting neural network and parameter calculation, so that the construction party can accurately prepare for construction based on the results of the above data simulation and improve construction efficiency.

[0138] like Figure 2 The figure shows the structure diagram of the tunnel waterproof construction system of the present invention. The tunnel waterproof construction system of this embodiment includes: a processor, a memory, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps in the above-mentioned tunnel waterproof construction system embodiment are implemented.

[0139] The system comprises: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to run in the following units of the system:

[0140] An underground model acquisition unit, used to acquire an underground three-dimensional model of the tunnel area to be constructed;

[0141] Finite element division unit, used to import the underground three-dimensional model into the finite element analysis software to divide the finite element mesh to obtain the finite element model;

[0142] A deformation simulation unit is used to perform nonlinear finite element analysis on the finite element model to obtain a deformation distribution cloud map of the underground three-dimensional model at a preset water level;

[0143] An edge detection unit is used to grayscale the deformation distribution cloud map into a grayscale cloud map, perform edge detection and divide the deformation area;

[0144] A water seepage identification unit, used to identify water-prone areas on the underground three-dimensional model based on the deformation area;

[0145] The protective layer positioning unit is used to mark the corresponding position of the water-permeable area on the tunnel area to be constructed as the installation position of the waterproof protective layer.

[0146] The tunnel waterproof construction system can be run in computing devices such as desktop computers, laptops, PDAs, and cloud servers. The tunnel waterproof construction system can include, but is not limited to, a processor and a memory. Those skilled in the art will appreciate that the examples are merely examples of tunnel waterproof construction systems and do not constitute a limitation on the tunnel waterproof construction system. The system can include more or fewer components than the examples, or a combination of certain components, or different components. For example, the tunnel waterproof construction system can also include input and output devices, network access devices, buses, etc.

[0147] The above describes specific embodiments of the present specification, and other embodiments are within the scope of the appended claims. In some cases, the actions or steps recorded in the claims can be performed in an order different from that in the embodiments and still achieve the desired results. In addition, the processes depicted in the accompanying drawings do not necessarily have to be performed in the specific order or sequential order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0148] The systems, devices, modules or units described in the above embodiments may be implemented by computer chips or entities, or by products with certain functions. A typical implementation device is a computer. Specifically, the computer may be, for example, a personal computer, a laptop computer, a cellular phone, a camera phone, a smart phone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or a combination of any of these devices.

[0149] For the convenience of description, the above device is described in various units according to their functions. Of course, when implementing this specification, the functions of each unit can be implemented in the same or multiple software and / or hardware.

[0150] Those skilled in the art will appreciate that the embodiments of this specification may be provided as methods, systems, or computer program products. Therefore, the embodiments of this specification may be in the form of complete hardware embodiments, complete software embodiments, or embodiments in combination with software and hardware. Moreover, the embodiments of this specification may be in the form of a computer program product implemented in one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code.

[0151] This specification is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of this specification. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0152] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0153] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0154] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0155] The memory may include non-permanent storage in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. The memory is an example of a computer-readable medium.

[0156] Computer readable media include permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. Information can be computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include temporary computer readable media (transitory media), such as modulated data signals and carrier waves.

[0157] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0158] This specification may be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform specific tasks or implement specific abstract data types. This specification may also be practiced in distributed computing environments where tasks are performed by remote processing devices connected through a communication network. In a distributed computing environment, program modules may be located in local and remote computer storage media, including storage devices.

[0159] Each embodiment in this specification is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the system embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0160] Finally, it should be noted that the methods and systems disclosed in the embodiments of the present invention are only preferred embodiments of the present invention, and are only used to illustrate the technical solutions of the present invention, rather than to limit them. Although the present invention has been described in detail with reference to the aforementioned embodiments, it should be understood by those skilled in the art that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features therein may be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A tunnel waterproofing construction method, characterized in that: The method comprises the following steps: S100, obtaining an underground three-dimensional model of the area where the tunnel is to be constructed; S200, importing the underground three-dimensional model into finite element analysis software to divide the finite element mesh to obtain a finite element model; S300, performing nonlinear finite element analysis on the finite element model to obtain a deformation distribution cloud map of the underground three-dimensional model at a preset water level; S400, graying the deformation distribution cloud map into a gray cloud map, performing edge detection to divide the deformation area; S500, identifying the water-prone area on the underground three-dimensional model according to the deformation area; In step S500, the method for identifying the water-prone area on the underground three-dimensional model according to the deformation area is: For each of the deformation regions, in the spatial coordinate system of the underground three-dimensional model, visual framing images corresponding to multiple angles of the deformation region are obtained at different viewpoint angles; Inputting the visual images corresponding to the multiple angles into a trained RNN neural network to obtain the water seepage probability corresponding to the deformed area; the RNN neural network model is trained by a training data set including a training visual image set and corresponding water seepage probability annotations; Acquire a plurality of historical simulation data of the area position corresponding to the deformation area in the historical database; According to the plurality of historical simulation data, the position hazard parameter corresponding to the deformation area is calculated; according to the plurality of historical simulation data, the method for calculating the position hazard parameter corresponding to the deformation area is: Calculate the ratio of the number of records with deformation at the regional position in each of the historical simulation data to the number of all records; Calculate the weighted sum average of all the quantity ratios to obtain the position hazard parameter corresponding to the deformed area; wherein the calculation weight corresponding to each of the quantity ratios is inversely proportional to the nearby deformation ratio corresponding to the regional position in the corresponding historical simulation data; the nearby deformation ratio is the proportion of the number of deformed positions in a circular area with a preset radius as the center of the regional position in the historical simulation data; The number of component edges of the tunnel surface corresponding to the deformation area is calculated; the method for calculating the number of component edges of the tunnel surface corresponding to the deformation area is: Traversing all component objects in the tunnel surface corresponding to the deformation area; Acquiring the contact edge lines between any two of the component objects; Screening out all the contact edge lines that intersect with the deformation area to obtain a line set; Calculating the number of lines in the line set to obtain the number of component edges of the tunnel surface corresponding to the deformation area; Calculate the product of the water seepage probability, the position hazard parameter and the number of component edges to obtain the water seepage parameter corresponding to the deformation area; According to the water seepage parameter, identifying, from all the deformation areas, water-prone areas in the underground three-dimensional model where the water seepage parameter is greater than a preset water seepage threshold; S600, marking the corresponding position of the water-permeable area on the tunnel area to be constructed as the installation position of the waterproof protective layer; S700, in the tunnel area to be constructed, waterproof layer construction work is carried out at the installation position; the waterproof protective layer established by the waterproof layer construction work includes a self-waterproof structural layer of a concrete structure connected to each other by a moisture-proof adhesive, an inner waterproof layer of at least one layer of synthetic polymer waterproof membrane, and a reinforcement layer.

2. A tunnel waterproofing construction method according to claim 1, characterized in that: In step S100, the method for obtaining the underground three-dimensional model of the area where the tunnel is to be constructed is: A sensor group is arranged on multiple tunnel surfaces in the tunnel area to be constructed to collect underground space exploration data corresponding to the tunnel area to be constructed, including multiple types of sensor data; the sensor group includes a ground penetrating radar, a temperature and humidity sensor, an infrared ranging sensor and a sonar sensor; the ground penetrating radar is a BA series three-dimensional ground penetrating radar or a GeoScope three-dimensional ground penetrating radar; Based on a preset hybrid model 3D modeling algorithm, 3D modeling is performed according to the underground space survey data to obtain an initial underground 3D model; Initial stress data of tunnel components and tunnel soil are added to the initial underground three-dimensional model to perform initial working condition simulation to obtain the underground three-dimensional model of the tunnel area to be constructed.

3. A tunnel waterproofing construction method according to claim 1, characterized in that: In step S300, the specific method of performing nonlinear finite element analysis on the finite element model to obtain the deformation distribution cloud map of the underground three-dimensional model at a preset water level is: Inputting the underground three-dimensional model into ABAQUS finite element software, and obtaining preset water pressure load simulation conditions including multiple water level levels; According to the hydraulic load simulation conditions of the multiple water level levels, a hydraulic load is applied to the underground three-dimensional model in the software, the hydraulic pressure is directly applied to the water-facing surface of the underground three-dimensional model in the form of surface force, and a full-process simulation calculation of the underground three-dimensional model bearing the hydraulic pressure is performed to obtain multiple simulation results; The material parameters of the whole process simulation calculation are as follows: regression statistical analysis is performed on the temperature and radial deformation monitoring data of the tunnel, and the water temperature boundary conditions, air temperature boundary conditions and mechanical parameters of the tunnel are obtained by inversion. Under the conditions of the linear expansion coefficient and elastic modulus of the preset concrete material parameters, the relationship between the deformation and the load change is obtained by forward analysis, and the material parameters are adjusted based on the regression analysis of the measured deformation data by using the relationship, so as to determine the material parameters of the tunnel; A deformation distribution cloud map of the underground three-dimensional model is determined according to the multiple simulation results.

4. A tunnel waterproofing construction method according to claim 3, characterized in that: Each simulation result includes deformation parameters in different directions on different tunnel surfaces of the underground three-dimensional model; Determining the deformation distribution cloud map of the underground three-dimensional model according to the multiple simulation results includes: All the simulation results are superimposed and combined to obtain a deformation distribution result corresponding to the underground three-dimensional model; For each tunnel face position in the underground three-dimensional model, calculating a parameter set corresponding to all deformation parameters in the deformation distribution result corresponding to the tunnel face position; The parameter set of the tunnel surface position is input into a trained CNN neural network model to obtain a deformation degree parameter corresponding to the tunnel surface; the CNN neural network model is trained by a training data set including a training parameter set and corresponding deformation degree annotations; Based on the deformation degree parameter, all deformation parameters corresponding to the tunnel surface position are screened to obtain a target deformation parameter set corresponding to the tunnel surface position; Calculating the average values ​​of all parameters in the target deformation parameter set to obtain the deformation parameter result corresponding to the tunnel face position; A deformation distribution cloud map of the underground three-dimensional model is generated according to the deformation parameter results corresponding to all the tunnel surface positions.

5. A tunnel waterproofing construction method according to claim 4, characterized in that: Based on the deformation degree parameter, all deformation parameters corresponding to the tunnel surface position are screened to obtain a target deformation parameter set corresponding to the tunnel surface position, including: Calculating a screening weight proportional to the deformation degree parameter; Calculating the product of a preset deformation parameter reference value and the screening weight to obtain a screening threshold; Among all deformation parameters corresponding to the tunnel surface position, deformation parameters whose parameter values ​​are greater than the screening threshold are retained to obtain a target deformation parameter set corresponding to the tunnel surface position.

6. A tunnel waterproofing construction method according to claim 1, characterized in that: After step S600, the method further includes: For each of the installation positions, obtaining the area of ​​the water-prone region, the water seepage probability, and the number of component edges corresponding to the installation position; According to the preset mathematical correspondence between area and materials, the type of construction materials, the amount of materials and the construction operation corresponding to the area of ​​the region are calculated; the construction operation includes the number and sequence of construction of different waterproof layers; Calculate the product of the water seepage probability and the number of edges of the component to obtain a construction difficulty parameter; Calculating a first weight and a second weight that are proportional to the construction difficulty parameter; Calculating the product of the material amount and the first weight to obtain a corrected material amount; Calculate the product of the construction quantity and the second weight to obtain the corrected waterproof layer quantity; The type of construction materials, the amount of revised materials and the construction operation including the number of revised waterproof layers are determined as the construction strategy plan corresponding to the installation location.

7. A tunnel waterproofing construction method according to claim 1, characterized in that: Before step S700, the method further includes: Inputting the construction strategy scheme corresponding to each installation position into the trained cost accounting neural network to obtain the construction cost corresponding to each installation position; Calculate the sum of the construction costs corresponding to all the installation locations to obtain the project cost; Calculate the sum of the parameters in all the construction strategy solutions to obtain the engineering solution; The engineering plan and the engineering cost are sent to the corresponding construction party equipment terminal.

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