Prediction method of existing tunnel deformation caused by new construction projects based on big data analysis

Abstract

The present invention relates to the field of data analysis, and discloses a method for predicting deformation of existing tunnels caused by new construction projects based on big data analysis, which is used to solve the problem that when soil collapse occurs at a construction site, the existing tunnel will be affected. The method comprises the following steps: detecting the speed and direction of change of groundwater level, and calculating the influence coefficient of groundwater level change, obtaining collapse data and the vertical distance of the collapse center from the existing tunnel, calculating the collapse degree according to the collapse data, and calculating the collapse influence coefficient, obtaining the tunnel's own situation data, and calculating the tunnel aging coefficient according to the own situation data, comprehensively evaluating the groundwater level change influence coefficient, the collapse influence coefficient and the tunnel aging coefficient to obtain a tunnel deformation index, and issuing an early warning according to the tunnel deformation index, thereby effectively improving the accuracy of tunnel deformation prediction and the safety of the tunnel.

Description

Technical Field

[0001] The present invention relates to the field of data analysis, and more specifically to a method for predicting deformation of existing tunnels caused by new construction projects based on big data analysis. Background Art

[0002] Deformation of existing tunnels caused by new construction projects refers to the disturbance or change of the strata, soil structure and groundwater level around the tunnel caused by various construction activities around the tunnel. This disturbance may cause the soil around the tunnel to become unstable, resulting in a series of reactions such as settlement, lateral displacement, tilt, deformation, etc. of the tunnel structure, thus affecting the safety, durability and normal operation of the tunnel.

[0003] The prediction of deformation of existing tunnels caused by existing new construction projects is achieved by analyzing the geological conditions, tunnel structure and construction parameters during the construction process, conducting real-time data monitoring, and using numerical simulation, machine learning and other technologies to predict the trend and degree of settlement, displacement or other deformation that may be caused by the construction.

[0004] However, during construction, soil collapse may occur at the construction site, which may also affect the existing tunnel. If the above prediction method is still used, the deformation of the tunnel cannot be accurately predicted, which reduces the safety of the tunnel.

[0005] In view of the above problems, the present invention proposes a solution. Summary of the invention

[0006] In order to overcome the above-mentioned defects of the prior art, the present invention provides a method for predicting deformation of existing tunnels caused by new construction projects based on big data analysis to solve the problems existing in the above-mentioned background technology.

[0007] To achieve the above object, the present invention provides the following technical solutions:

[0008] The method for predicting deformation of existing tunnels caused by new construction projects based on big data analysis includes the following steps:

[0009] Step 1: Use the acoustic wave detection technology to detect the change speed and direction of the groundwater level, and calculate the groundwater level change influence coefficient based on the change speed and direction of the groundwater level;

[0010] Step 2: Use GPS measurement technology to obtain collapse data and the vertical distance between the collapse center and the existing tunnel. Calculate the collapse degree based on the collapse data. Calculate the collapse influence coefficient based on the collapse degree and the vertical distance between the collapse center and the existing tunnel. The calculation formula is: Where CP represents the collapse influence coefficient, DC represents the collapse degree, and DT represents the vertical distance from the collapse center to the existing tunnel;

[0011] Step 3: Obtaining tunnel condition data, including tunnel aging data and crack data, and calculating the tunnel aging coefficient based on the tunnel condition data;

[0012] Step 4: Comprehensively evaluate the influence coefficient of groundwater level change, the influence coefficient of collapse and the tunnel aging coefficient to obtain the tunnel deformation index, the calculation formula of which is TD=a1×GL+a2×CP+a3×TC, where TD represents the tunnel deformation index, GL represents the influence coefficient of groundwater level change, CP represents the influence coefficient of collapse, TC represents the tunnel aging coefficient, and a1, a2 and a3 represent the weight coefficients of the influence coefficient of groundwater level change, the influence coefficient of collapse and the tunnel aging coefficient;

[0013] Step 5: Issue early warning based on tunnel deformation index.

[0014] Preferably, the step of calculating the influence coefficient of groundwater level change is:

[0015] Place acoustic sensors in the groundwater layers around the construction area and existing tunnels to monitor the flow speed and direction of groundwater in real time;

[0016] Obtain the distance between the acoustic wave sensors installed in the construction area and the existing tunnel and the propagation time difference of the acoustic wave between the two sensors, and calculate the ratio to obtain the acoustic wave propagation speed v s ;

[0017] Obtain the angle between the sound wave propagation direction and the water flow direction, and calculate the actual groundwater flow rate based on the sound wave propagation speed. The calculation formula is v w =v s ·cos(θ), where v w is the actual velocity of groundwater, θ is the angle between the direction of sound wave propagation and the direction of water flow, v s Expressed as the speed of sound wave propagation;

[0018] Use multiple acoustic wave detectors, arranged in different directions, to detect the water flow velocity in different directions and the direction angle of groundwater flow, and calculate the change in the direction of the water flow velocity based on the actual groundwater flow velocity. The calculation formula is v x =v w ·cos(α),v y =v w sin(α), where v x With v y They represent the directional change of water velocity as groundwater flow velocity, and α represents the directional angle of groundwater flow;

[0019] The change of water flow velocity is continuously monitored by the acoustic wave detector during the detection period, and the change rate of groundwater level over time is calculated. The calculation formula is: Where V h It is expressed as the speed of change of groundwater level, dh is expressed as the height difference of groundwater level change, and dt is the detection time period;

[0020] According to the change in the direction of water flow velocity, the direction of water level change is calculated, and the calculation formula is: where θ w It is expressed as the direction angle of groundwater level change;

[0021] The influence coefficient of groundwater level change is calculated based on the change speed and direction of groundwater level. The calculation formula is GL = V h ·cos(θ w ), where GL is the influence coefficient of groundwater level change.

[0022] Preferably, the step of calculating the collapse degree according to the collapse data is:

[0023] Using data measured by GPS measurement technology, a plan view and a three-dimensional model of the collapsed area are drawn, and the boundaries of the collapsed area are marked;

[0024] The area of ​​the collapsed region is obtained by image processing technology;

[0025] The collapsed area is divided into n parts, recorded as collapsed sub-areas, and the vertical depth of collapse of each collapsed sub-area is measured by ground radar detection technology, and the vertical depth of collapse of each collapsed sub-area is averaged to obtain the average collapse depth;

[0026] The actual collapse volume is calculated by multiplying the area of ​​the collapsed region by the average collapse depth. The calculation formula is: Where Vt represents the actual collapsed volume, A represents the area of ​​the collapsed region, is the average collapse depth;

[0027] The theoretical maximum collapse volume is obtained based on design standards and geological conditions, and the collapse degree is calculated by calculating the ratio of the actual collapse volume to the theoretical maximum collapse volume.

[0028] Preferably, the step of obtaining the area of ​​the collapsed region by image processing technology is:

[0029] For the plan view of the collapsed area, denoising technology is used to reduce the noise in the image and enhance the image contrast and brightness;

[0030] Use edge detection algorithm to identify the boundary of the collapsed area, segment the image into different areas, and identify and extract the collapsed area;

[0031] The pixel area of ​​the collapsed region in the image is calculated and converted into the actual area, which is recorded as the area of ​​the collapsed region.

[0032] Preferably, the step of obtaining the theoretical maximum collapse volume according to the design standards and geological conditions is:

[0033] Obtain geological exploration reports for the construction area, understand the stratum structure, including the distribution and thickness of soil layers and rocks, and analyze the strength characteristics of different geological materials;

[0034] Determine the depth of the groundwater level and the existence of aquifers, assess the impact of groundwater on formation stability, and assess the additional pressure and softening effects of groundwater on collapse;

[0035] Determine the design load of the tunnel according to the load calculation formula in the design specification. The design load includes earth pressure, live load and seismic load. Combined with the safety factor of the project, determine the maximum load that the tunnel structure can withstand.

[0036] Based on the geological conditions and tunnel design, the limit equilibrium analysis method is used to evaluate the stability of the tunnel, determine the potential collapse range above and on the sides of the tunnel, analyze the location of the instability point, and determine the maximum potential collapse area;

[0037] According to the instability point analysis in the previous step, determine the geometric area with the maximum probability of collapse and construct a geometric model of the theoretical collapse area;

[0038] According to the established geometric model of the collapse area, the theoretical maximum collapse volume is calculated using the geometric volume formula.

[0039] Preferably, the step of calculating the tunnel aging coefficient according to the own situation data is:

[0040] Obtain the time from the completion of the tunnel to date, record it as the completion time, and obtain the tunnel maintenance record from the management data;

[0041] Obtain the total number of maintenance operations since the tunnel was built through the tunnel maintenance records;

[0042] The degree of tunnel aging is calculated based on the time of construction and the total number of maintenance times. The calculation formula is: Where Ad represents the degree of tunnel aging, T j Indicated as the completion time, NUM w It is expressed as the total number of maintenance operations;

[0043] A three-dimensional laser scanning device is deployed in the tunnel to accurately scan the inner surface of the tunnel to obtain the number of cracks in the tunnel. The tunnel aging coefficient is calculated based on the degree of tunnel aging and the number of cracks in the tunnel. The calculation formula is: Where TC is the tunnel aging coefficient, NUM L Expressed as the number of cracks in the tunnel.

[0044] Preferably, the step of providing early warning according to the tunnel deformation index is:

[0045] The tunnel deformation index is compared with the preset threshold. If the tunnel deformation index is less than the preset threshold, it is determined that the current tunnel deformation probability is small, and no warning is issued; if the tunnel deformation index is greater than the preset threshold, it is determined that the current tunnel deformation probability is large, and a warning is issued to remind relevant staff to take safety precautions in a timely manner.

[0046] Compared with the prior art, the technical effects and advantages of the present invention are as follows:

[0047] The present invention solves the problem of the influence of soil collapse at the construction site on the deformation of the existing tunnel, by detecting the change speed and direction of the groundwater level and calculating the groundwater level change influence coefficient, obtaining the collapse data and the vertical distance of the collapse center from the existing tunnel, calculating the collapse degree according to the collapse data, and calculating the collapse influence coefficient, obtaining the tunnel's own situation data, and calculating the tunnel aging coefficient according to the own situation data, comprehensively evaluating the groundwater level change influence coefficient, the collapse influence coefficient and the tunnel aging coefficient to obtain the tunnel deformation index, and issuing an early warning according to the tunnel deformation index, thereby effectively improving the accuracy of tunnel deformation prediction and the safety of the tunnel. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] Figure 1 It is the overall flow chart of the present invention. DETAILED DESCRIPTION

[0049] The technical solution of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the present invention. In addition, the forms of the various structures recorded in the following embodiments are only examples. The method for predicting deformation of existing tunnels caused by new construction projects based on big data analysis involved in the present invention is not limited to the various structures recorded in the following embodiments. All other embodiments obtained by ordinary technicians in this field without making creative work belong to the scope of protection of the present invention.

[0050] The present invention provides a method for predicting deformation of existing tunnels caused by new construction projects based on big data analysis, comprising the following steps:

[0051] Step 1: Use the acoustic wave detection technology to detect the change speed and direction of the groundwater level, and calculate the groundwater level change influence coefficient based on the change speed and direction of the groundwater level;

[0052] Construction subsidence can cause changes in the speed and direction of groundwater flow, mainly because the collapse causes a sudden change in the structure of the underground soil layer, destroying the original groundwater flow path. The soil density and permeability in the collapsed area change, which may form new infiltration channels or block the original water flow channels, thereby changing the speed and direction of groundwater flow. This change may cause the water level to drop, rise, or increase the flow rate, affecting the natural circulation of groundwater.

[0053] In this embodiment, it should be specifically explained that the calculation steps of the groundwater level change influence coefficient are:

[0054] Place acoustic sensors in the groundwater layers around the construction area and existing tunnels to monitor the flow speed and direction of groundwater in real time;

[0055] The acoustic wave sensor is a device that detects the flow of substances in liquids or gases by emitting and receiving sound waves. In groundwater monitoring, the acoustic wave sensor uses the relationship between the propagation speed of sound waves in water and the water flow speed, and calculates the flow speed and direction of groundwater by detecting the propagation time difference of sound waves. This sensor usually consists of a transmitter and a receiver, and is installed in the groundwater layer. By continuously monitoring the dynamic changes of water flow, it provides real-time data on groundwater level changes, helping to evaluate the impact of construction activities on the strata and existing tunnels.

[0056] The distance between the acoustic wave sensors installed in the construction area and the existing tunnel and the propagation time difference of the acoustic wave between the two sensors are obtained, and the ratio is calculated to obtain the acoustic wave propagation speed. The calculation formula is: where v s It is expressed as the speed of sound wave propagation, d is the distance of the sound wave sensor, and Δt is the propagation time difference;

[0057] Obtain the angle between the sound wave propagation direction and the water flow direction, and calculate the actual groundwater flow rate based on the sound wave propagation speed. The calculation formula is v w =v s ·cos(θ), where v w It is expressed as the actual flow velocity of groundwater, and θ is expressed as the angle between the propagation direction of sound waves and the direction of water flow, which reflects the relative angle between the propagation direction of sound waves in water and the direction of water flow;

[0058] Use multiple acoustic wave detectors, arranged in different directions, to detect the water flow velocity in different directions and the direction angle of groundwater flow, and calculate the change in the direction of the water flow velocity based on the actual groundwater flow velocity. The calculation formula is v x =v w ·cos(α),v y =v w sin(α), where v x With v yThey are respectively represented by the direction change of the water flow velocity of the groundwater flow velocity, and α is represented by the direction angle of the groundwater flow, which refers to the angle between the actual groundwater flow direction and a certain reference direction (such as the north direction or the horizontal line), which indicates the main direction of the groundwater flow;

[0059] The change of water flow velocity is continuously monitored by the acoustic wave detector during the detection period, and the change rate of groundwater level over time is calculated. The calculation formula is: Where V h It is expressed as the speed of change of groundwater level, dh is expressed as the height difference of groundwater level change, and dt is the detection time period;

[0060] According to the change in the direction of water flow velocity, the direction of water level change is calculated, and the calculation formula is: where θ w It is expressed as the direction angle of groundwater level change;

[0061] The influence coefficient of groundwater level change is calculated based on the change speed and direction of groundwater level. The calculation formula is GL = V h ·cos(θ w ), where GL is the influence coefficient of groundwater level change.

[0062] Groundwater usually flows from high water level areas to low water level areas. The direction of water flow is consistent with the gradient of the water level (i.e. the direction of change of the water level). In other words, water always flows from high water level areas to low water level areas. If the water level changes, this will change the water level gradient, thus affecting the direction of water flow. When the water level rises, the water will flow from the new high water level area to the relatively low water level area; when the water level drops, the direction of water flow may also be adjusted accordingly;

[0063] By measuring the velocity and direction of the water flow through an acoustic wave sensor, the components of the water flow in different directions can be obtained. These data reflect the actual direction of groundwater flow, and when the water level changes, the direction of the water flow will adjust accordingly. By monitoring the changes in the direction of the water flow velocity, the direction of the water level change can be inferred, because the direction of the water flow is a direct reflection of the change in the water level gradient; measuring the components of the water flow in different directions can determine the main direction of the water flow. Using the changes in these flow velocity components, the direction of the water level change can be calculated, because the change in the direction of the water flow caused by the water level change directly reflects the change in the water level gradient. By measuring the change in the direction of the flow velocity (that is, the change in the direction of the water flow), the direction of the water level change can be inferred. For example, if the direction of the water flow turns from one side to the other, it means that the water level has changed in the corresponding direction;

[0064] The change in the water flow direction angle can be used to deduce the direction of the water level change. For example, if the change angle of the water flow direction matches a certain reference angle (such as the initial water flow direction), it can be considered that the change direction of the water level is consistent with the change in the water flow direction.

[0065] Step 2: Use GPS measurement technology to obtain collapse data and the vertical distance between the collapse center and the existing tunnel. Calculate the collapse degree based on the collapse data. Calculate the collapse influence coefficient based on the collapse degree and the vertical distance between the collapse center and the existing tunnel. The calculation formula is: Where CP represents the collapse influence coefficient, DC represents the collapse degree, and DT represents the vertical distance from the collapse center to the existing tunnel;

[0066] In this embodiment, it should be specifically explained that the step of calculating the collapse degree according to the collapse data is:

[0067] Using data measured by GPS measurement technology, a plan view and a three-dimensional model of the collapsed area are drawn, and the boundaries of the collapsed area are marked;

[0068] The area of ​​the collapsed area is obtained through image processing technology, which is a technology that analyzes, processes and interprets image data through computer algorithms to extract useful information. It involves steps such as image acquisition, preprocessing, feature extraction and analysis to identify and measure objects or areas in the image. When determining the area of ​​the collapsed area, image processing technology uses high-resolution image data to accurately calculate the boundaries and areas of the collapsed area through methods such as edge detection, region segmentation and contour recognition. This technology is usually combined with computer vision and machine learning algorithms to improve processing accuracy and efficiency;

[0069] The collapsed area is divided into n parts, recorded as collapsed sub-areas, and the vertical depth of collapse of each collapsed sub-area is measured by ground radar detection technology, and the average vertical depth of collapse of each collapsed sub-area is calculated to obtain the average collapse depth;

[0070] The actual collapse volume is calculated by multiplying the area of ​​the collapsed region by the average collapse depth. The calculation formula is: Where Vt represents the actual collapsed volume, A represents the area of ​​the collapsed region, is the average collapse depth;

[0071] The theoretical maximum collapse volume is obtained based on design standards and geological conditions, which is used as a criterion for judging the impact on surrounding buildings (such as tunnels). This threshold can help engineers assess the potential risk of collapse to the surrounding environment and determine whether additional protective measures are needed. The collapse degree is calculated based on the theoretical maximum collapse volume and the actual collapse volume. The calculation steps are as follows: Where DC represents the degree of collapse, Vt represents the actual collapse volume, and Vt max represents the theoretical maximum collapse volume.

[0072] In this embodiment, it should be specifically explained that the step of obtaining the area of ​​the collapsed region by image processing technology is:

[0073] For the plan view of the collapsed area, denoising technology is used to reduce the noise in the image to improve processing accuracy, enhance image contrast and brightness, and make the boundary of the collapsed area clearer;

[0074] Use edge detection algorithms (such as Canny edge detection and Sobel operator) to identify the boundaries of the collapsed area, segment the image into different areas, and identify and extract the collapsed area;

[0075] The edge detection algorithm is an image processing technology used to identify the position information of the edge of an object in an image. It analyzes the grayscale changes of the image to find the part with the most significant intensity change in the image, that is, the edge. Common edge detection algorithms include Canny edge detection and Sobel operator. Canny edge detection is a multi-stage algorithm that first removes noise through Gaussian filtering, then calculates the gradient of the image and applies non-maximum suppression and double threshold processing to determine the edge. The Sobel operator uses convolution operations to calculate the gradient of the image and detect edges in the horizontal and vertical directions. The edge detection algorithm can clearly extract the contours of objects in the image and help analyze and measure the boundaries of collapsed areas.

[0076] Calculate the pixel area of ​​the collapsed region in the image and convert it into the actual area. The calculation formula is A=P×ns, where A represents the area of ​​the collapsed region, P is the number of pixels in the collapsed region in the image, and ns represents the actual area represented by each pixel.

[0077] In this embodiment, it should be specifically explained that the steps of obtaining the theoretical maximum collapse volume according to factors such as design standards and geological conditions are as follows:

[0078] Obtain geological exploration reports for the construction area, understand the stratum structure, including the distribution and thickness of soil and rock layers, and analyze the strength characteristics of different geological materials, such as the compressive strength of rocks, the shear strength of soil layers, and cohesion;

[0079] Determine the depth of the groundwater table and the existence of aquifers, assess the impact of groundwater on formation stability, and assess the additional pressure or softening effect that groundwater may cause on collapse;

[0080] According to the load calculation formula in the design specification, determine the design load of the tunnel, including earth pressure, live load, seismic load, etc., and combine the safety factor of the project to determine the maximum load that the tunnel structure can withstand;

[0081] Based on the geological conditions and tunnel design, the tunnel stability is evaluated using limit equilibrium analysis methods (such as the Mohr-Coulomb failure criterion), the potential collapse range above or on the side of the tunnel is determined, the location of the instability point is analyzed, and the maximum potential collapse area is determined;

[0082] Based on the instability point analysis in the previous step, determine the geometric area that may collapse. The collapse shape can usually be approximated by several geometric shapes, such as wedges, trapezoids or hemispheres. According to the inclination, thickness, groundwater level and other factors of the geological layer, a geometric model of the theoretical collapse area is constructed;

[0083] According to the established geometric model of the collapse area, the theoretical maximum collapse volume is calculated using the geometric volume formula.

[0084] Step 3: Obtain the tunnel's own condition data, and calculate the tunnel aging coefficient based on the own condition data;

[0085] In this embodiment, it should be specifically explained that the step of calculating the tunnel aging coefficient according to the own situation data is:

[0086] Obtain the time from the completion of the tunnel to date, record it as the completion time, and obtain the tunnel maintenance record from the management data;

[0087] Obtain the total number of maintenance operations since the tunnel was built through the tunnel maintenance records;

[0088] The degree of tunnel aging is calculated based on the time of construction and the total number of maintenance times. The calculation formula is: Where Ad represents the degree of tunnel aging, T j Indicated as the completion time, NUM w It is expressed as the total number of maintenance operations;

[0089] A three-dimensional laser scanning device is deployed in the tunnel to accurately scan the inner surface of the tunnel to obtain the number of cracks in the tunnel. The tunnel aging coefficient is calculated based on the degree of tunnel aging and the number of cracks in the tunnel. The calculation formula is: Where TC is the tunnel aging coefficient, NUM L Expressed as the number of cracks in the tunnel.

[0090] Step 4: Comprehensively evaluate the influence coefficient of groundwater level change, the influence coefficient of collapse and the aging coefficient of the tunnel to obtain the tunnel deformation index, which is calculated as TD = a1 × GL + a2 × CP + a3 × TC, where TD represents the tunnel deformation index, GL represents the influence coefficient of groundwater level change, and the influence coefficient of groundwater level change is an indicator used to quantify the potential impact of groundwater level change on tunnel deformation, which is usually determined by measuring the speed and direction of groundwater level change. When the influence coefficient of groundwater level change increases, it means that the fluctuation or flow of groundwater level has a more significant effect on the stability and deformation of the tunnel, resulting in an increase in the tunnel deformation index. This relationship shows that the change of groundwater level is an important factor in the deformation of tunnel structure. Special attention should be paid to the dynamic change of groundwater level in engineering so as to take reinforcement measures in time to prevent excessive deformation or structural damage of the tunnel. CP represents the collapse influence coefficient, which is an indicator used to quantify the impact of collapse on tunnel deformation. It reflects the influence of collapse scale, depth and other related factors on tunnel stability. When the collapse influence coefficient increases, it means that the volume or depth of the collapse area increases, and the pressure and deformation caused to the tunnel will also increase accordingly, resulting in an increase in the tunnel deformation index. This proportional relationship shows that the stratum changes caused by collapse directly affect the safety and stability of the tunnel. Therefore, during the engineering design and construction process, it is necessary to closely monitor the collapse and take effective control measures to prevent excessive deformation or structural damage to the tunnel. TC is represented by the tunnel aging coefficient. As the service life of the tunnel increases or the degree of material aging increases, the degree of deformation of the tunnel will also increase accordingly. The tunnel aging coefficient is an indicator used to quantify the degree of structural degradation of the tunnel due to factors such as time, environmental influences, and material aging. As the tunnel ages, the strength, stiffness, and durability of the tunnel material may decrease, making the tunnel less able to withstand external loads and geological changes, resulting in an increase in the deformation index. This proportional relationship shows that the aging process of the tunnel will significantly affect its structural performance and increase the risk of deformation. Therefore, in the operation and maintenance management of the tunnel, it is necessary to regularly inspect and evaluate the aging condition of the tunnel, and take reinforcement and maintenance measures in time to ensure the safety and stability of the tunnel. a1, a2, and a3 are expressed as the weight coefficients of the groundwater level change influence coefficient, the collapse influence coefficient, and the tunnel aging coefficient, and a1+a2+a3=1. The specific values ​​of a1, a2, and a3 are determined by professionals according to the actual situation. For example, a1, a2, and a3 can be 0.4, 0.4, and 0.2.

[0091] Step 5: Issue early warning based on the tunnel deformation index to remind relevant staff to take safety precautions in a timely manner;

[0092] In this embodiment, it should be specifically explained that the steps of performing early warning according to the tunnel deformation index are:

[0093] The tunnel deformation index is compared with the preset threshold. If the tunnel deformation index is less than the preset threshold, it is determined that the current tunnel deformation probability is small, and no warning is issued; if the tunnel deformation index is greater than the preset threshold, it is determined that the current tunnel deformation probability is large, and a warning is issued to remind relevant staff to take safety precautions in a timely manner.

[0094] Finally: The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

[0095] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A method for predicting deformation of existing tunnels caused by new construction projects based on big data analysis, characterized in that: The following steps are involved: Step 1: Use the acoustic wave detection technology to detect the change speed and direction of the groundwater level, and calculate the groundwater level change influence coefficient based on the change speed and direction of the groundwater level; Step 2: Use GPS measurement technology to obtain collapse data and the vertical distance between the collapse center and the existing tunnel. Calculate the collapse degree based on the collapse data. Calculate the collapse influence coefficient based on the collapse degree and the vertical distance between the collapse center and the existing tunnel. The calculation formula is: Where CP represents the collapse influence coefficient, DC represents the collapse degree, and DT represents the vertical distance from the collapse center to the existing tunnel; Step 3: Obtaining tunnel condition data, including tunnel aging data and crack data, and calculating the tunnel aging coefficient based on the tunnel condition data; Step 4: Comprehensively evaluate the influence coefficient of groundwater level change, the influence coefficient of collapse and the tunnel aging coefficient to obtain the tunnel deformation index, the calculation formula of which is TD=a1×GL+a2×CP+a3×TC, where TD represents the tunnel deformation index, GL represents the influence coefficient of groundwater level change, CP represents the influence coefficient of collapse, TC represents the tunnel aging coefficient, and a1, a2 and a3 represent the weight coefficients of the influence coefficient of groundwater level change, the influence coefficient of collapse and the tunnel aging coefficient; Step 5: Issue early warning based on tunnel deformation index.

2. The method for predicting deformation of existing tunnels caused by new construction projects based on big data analysis according to claim 1 is characterized by: The calculation steps of the influence coefficient of groundwater level change are as follows: Place acoustic sensors in the groundwater layers around the construction area and existing tunnels to monitor the flow speed and direction of groundwater in real time; Obtain the distance between the acoustic wave sensors installed in the construction area and the existing tunnel and the propagation time difference of the acoustic wave between the two sensors, and calculate the ratio to obtain the acoustic wave propagation speed v s ; Obtain the angle between the sound wave propagation direction and the water flow direction, and calculate the actual groundwater flow rate based on the sound wave propagation speed. The calculation formula is v w =v s cos(θ), where v w is the actual velocity of groundwater, θ is the angle between the direction of sound wave propagation and the direction of water flow, v s Expressed as the speed of sound wave propagation; Use multiple acoustic wave detectors, arranged in different directions, to detect the water flow velocity in different directions and the direction angle of groundwater flow, and calculate the change in the direction of the water flow velocity based on the actual groundwater flow velocity. The calculation formula is v x =v w ·cos(α),v y =v w sin(α), where v x With v y They represent the directional change of water velocity as groundwater flow velocity, and α represents the directional angle of groundwater flow; The change of water flow velocity is continuously monitored by the acoustic wave detector during the detection period, and the change rate of groundwater level over time is calculated. The calculation formula is: Where V h It is expressed as the speed of change of groundwater level, dh is expressed as the height difference of groundwater level change, and dt is the detection time period; According to the change in the direction of water flow velocity, the direction of water level change is calculated, and the calculation formula is: where θ w It is expressed as the direction angle of groundwater level change; The influence coefficient of groundwater level change is calculated based on the change speed and direction of groundwater level. The calculation formula is GL = V h ·cos(θ w ), where GL is the influence coefficient of groundwater level change.

3. The method for predicting deformation of existing tunnels caused by new construction projects based on big data analysis according to claim 1 is characterized by: The step of calculating the collapse degree according to the collapse data is: Using data measured by GPS measurement technology, a plan view and a three-dimensional model of the collapsed area are drawn, and the boundaries of the collapsed area are marked; The area of ​​the collapsed region is obtained by image processing technology; The collapsed area is divided into n parts, recorded as collapsed sub-areas, and the vertical depth of collapse of each collapsed sub-area is measured by ground radar detection technology, and the average vertical depth of collapse of each collapsed sub-area is calculated to obtain the average collapse depth; The actual collapse volume is calculated by multiplying the area of ​​the collapsed region by the average collapse depth. The calculation formula is: Where Vt represents the actual collapsed volume, A represents the area of ​​the collapsed region, is the average collapse depth; The theoretical maximum collapse volume is obtained based on design standards and geological conditions, and the collapse degree is calculated by calculating the ratio of the actual collapse volume to the theoretical maximum collapse volume.

4. The method for predicting deformation of existing tunnels caused by new construction projects based on big data analysis according to claim 3 is characterized by: The step of obtaining the area of ​​the collapsed region by image processing technology is: For the plan view of the collapsed area, denoising technology is used to reduce the noise in the image and enhance the image contrast and brightness; Use edge detection algorithm to identify the boundary of the collapsed area, segment the image into different areas, and identify and extract the collapsed area; The pixel area of ​​the collapsed region in the image is calculated and converted into the actual area, which is recorded as the area of ​​the collapsed region.

5. The method for predicting deformation of existing tunnels caused by new construction projects based on big data analysis according to claim 3 is characterized by: The steps for obtaining the theoretical maximum collapse volume according to the design standards and geological conditions are as follows: Obtain geological exploration reports for the construction area, understand the stratum structure, including the distribution and thickness of soil layers and rocks, and analyze the strength characteristics of different geological materials; Determine the depth of the groundwater level and the existence of aquifers, assess the impact of groundwater on formation stability, and assess the additional pressure and softening effects of groundwater on collapse; Determine the design load of the tunnel according to the load calculation formula in the design specification. The design load includes earth pressure, live load and seismic load. Combined with the safety factor of the project, determine the maximum load that the tunnel structure can withstand. Based on the geological conditions and tunnel design, the limit equilibrium analysis method is used to evaluate the stability of the tunnel, determine the potential collapse range above and on the sides of the tunnel, analyze the location of the instability point, and determine the maximum potential collapse area; According to the instability point analysis in the previous step, determine the geometric area with the maximum probability of collapse and construct a geometric model of the theoretical collapse area; According to the established geometric model of the collapse area, the theoretical maximum collapse volume is calculated using the geometric volume formula.

6. The method for predicting deformation of existing tunnels caused by new construction projects based on big data analysis according to claim 1 is characterized by: The steps of calculating the tunnel aging coefficient according to the data of the own situation are as follows: Obtain the time from the completion of the tunnel to date, record it as the completion time, and obtain the tunnel maintenance record from the management data; Obtain the total number of maintenance operations since the tunnel was built through the tunnel maintenance records; The degree of tunnel aging is calculated based on the time of construction and the total number of maintenance times. The calculation formula is: Where Ad represents the tunnel aging degree, T j Indicated as the completion time, NUM w It is expressed as the total number of maintenance operations; A three-dimensional laser scanning device is deployed in the tunnel to accurately scan the inner surface of the tunnel to obtain the number of cracks in the tunnel. The tunnel aging coefficient is calculated based on the degree of tunnel aging and the number of cracks in the tunnel. The calculation formula is: Where TC is the tunnel aging coefficient, NUM L Expressed as the number of cracks in the tunnel.

7. The method for predicting deformation of existing tunnels caused by new construction projects based on big data analysis according to claim 1 is characterized by: The steps of early warning according to the tunnel deformation index are as follows: The tunnel deformation index is compared with the preset threshold. If the tunnel deformation index is less than the preset threshold, it is determined that the current tunnel deformation probability is small, and no warning is issued; If the tunnel deformation index is greater than the preset threshold, it is determined that the current tunnel deformation probability is high, and an early warning prompt is issued to remind relevant staff to take safety precautions in a timely manner.

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