Reservoir dam deformation monitoring method and system based on sensor network

Abstract

The invention relates to the technical field of deformation monitoring, in particular to a reservoir dam deformation monitoring method and system based on a sensor network, and the method comprises the steps: carrying out the calibration analysis of the failure degree of a corresponding position based on the basic engineering parameters of each position of a reservoir dam and a failure degree prediction result; and performing failure analysis on each position according to the predicted future water flow impact condition and the failure degree calibration analysis result of each position of the dam, and performing maintenance analysis resource allocation on the corresponding position based on the failure analysis result of each position. Failure analysis and maintenance resource allocation are carried out based on water flow conditions, deformation conditions, basic engineering parameters and failure degree prediction and calibration analysis of all positions of a reservoir dam, potential risks are found in time by collecting water flow and deformation data in real time, the maintenance priority of all areas is determined, it is ensured that high-risk areas are processed in time, and the maintenance efficiency is improved. And according to the real-time monitoring and prediction result, the maintenance plan is dynamically adjusted, and the flexibility and adaptability of resource allocation are improved.

Description

Technical Field

[0001] This application relates to the technical field of deformation monitoring, and particularly to a method and system for monitoring the deformation of a reservoir dam based on a sensor network. Background Art

[0002] As an important water conservancy infrastructure, the safety and stability of a reservoir dam are directly related to the life and property safety of downstream residents, the ecological environment, and the development of the social economy. With the rapid advancement of water conservancy project construction in China, the number and scale of dams are increasing continuously, and the requirements for dam safety monitoring and operation and maintenance management are also rising. However, there are many deficiencies in traditional dam monitoring and operation and maintenance methods, making it difficult to meet the requirements of modern water conservancy projects for high efficiency, precision, and intelligence. Traditional dam monitoring methods mainly rely on manual inspections and local monitoring with single sensors, and there are the following problems:

[0003] 1. Lack of real-time performance: The data collection frequency of manual inspections and single sensors is low, and real-time monitoring cannot be achieved, making it difficult to detect potential risks in a timely manner;

[0004] 2. Incomplete data coverage: Traditional monitoring methods usually only focus on local areas of the dam, making it difficult to comprehensively reflect the overall state of the dam and resulting in monitoring blind spots;

[0005] This leads to: Low accuracy of failure prediction: Lack of comprehensive analysis of water flow, deformation, and foundation engineering parameters, with limited accuracy of failure prediction results, making it difficult to support precise operation and maintenance decisions; Unreasonable resource allocation: The allocation of maintenance resources is usually based on experience or simple rules, lacking scientific basis, resulting in failure to promptly handle high-risk areas and possible resource waste in low-risk areas; Weak dynamic adjustment ability: Traditional methods are difficult to dynamically adjust the maintenance plan according to real-time monitoring data and prediction results, with insufficient flexibility and adaptability in resource allocation.

[0006] In response to the above problems, this application proposes a monitoring and operation and maintenance management solution for reservoir dams based on a sensor network and intelligent technology. Summary of the Invention

[0007] To overcome the defects and deficiencies of the existing technologies, the present application provides a deformation monitoring system and method for a reservoir dam based on a sensor network, which collects the water flow conditions and deformation conditions at various positions of the reservoir dam to predict the failure degree of the corresponding positions, calibrates and analyzes the failure degree of the corresponding positions based on the basic engineering parameters of various positions of the reservoir dam and the failure degree prediction results, conducts failure analysis for each position through the predicted future water flow impact conditions and the calibrated analysis results of the failure degree of each position of the dam, allocates maintenance analysis resources for the corresponding positions based on the failure analysis results of each position, and conducts failure analysis and maintenance resource allocation based on the water flow conditions, deformation conditions, basic engineering parameters, and failure degree prediction and calibration analysis of various positions of the reservoir dam. By collecting water flow and deformation data in real time, potential risks can be discovered in a timely manner, the maintenance priorities of each area can be clarified, and high-risk areas can be ensured to be processed in a timely manner. According to the real-time monitoring and prediction results, the maintenance plan can be dynamically adjusted to improve the flexibility and adaptability of resource allocation.

[0008] To achieve the above object, the present application adopts the following technical solutions:

[0009] In the first aspect, the present application provides a deformation monitoring method for a reservoir dam based on a sensor network, including the following steps:

[0010] S1: Establish a three-dimensional space model of the reservoir dam, and associate the three-dimensional space model, position coordinates with the basic engineering parameters of the corresponding positions;

[0011] S2: Collect the water flow conditions and deformation conditions at various positions of the reservoir dam to predict the failure degree of the corresponding positions;

[0012] S3: Calibrate and analyze the failure degree of the corresponding positions based on the basic engineering parameters of various positions of the reservoir dam and the failure degree prediction results;

[0013] S4: Conduct failure analysis for each position through the predicted future water flow impact conditions and the calibrated analysis results of the failure degree of each position of the dam;

[0014] S5. Allocate maintenance analysis resources for the corresponding positions based on the failure analysis results of each position.

[0015] In an implementation manner of the present application, step S1 includes the following specific steps:

[0016] S11. Obtain the corresponding position data of each position of the reservoir dam during construction, construct a three-dimensional space model of the reservoir dam, obtain the real-time three-dimensional space position coordinates of the corresponding positions based on a GPS or Beidou positioning module, and at the same time obtain the basic engineering parameter data of the corresponding positions. Here, the basic engineering parameter data includes the basic concrete strength, elasticity, and concrete thickness data of the corresponding positions to perform the association between the position coordinates of the corresponding positions in the three-dimensional space model and the basic engineering parameters of the corresponding positions.

[0017] S12. Obtain the internal humidity data of each corresponding position and the regional defect data of the corresponding position in real time. Among them, the defect data includes data reflecting the degree of regional defects such as the defect length, quantity, width, and depth of the corresponding position, and store the corresponding data in the corresponding storage module.

[0018] In an implementation manner of the present application, in step S2, the water flow condition and deformation condition of each position of the reservoir dam are collected to predict the failure degree of the corresponding position, including the following specific steps:

[0019] S21. Collect the deformation magnitude and deformation direction data of each corresponding monitoring point, as well as the internal humidity data of each corresponding position of each monitoring point and the regional defect data of the corresponding position.

[0020] S22. Collect the deformation magnitude and deformation direction data of each corresponding monitoring point, and perform deformation anomaly analysis based on the deviation abnormality between the deformation magnitude, deformation direction, and water flow impact direction. Among them, the deformation anomaly analysis formula for the i-th monitoring point is: Where, xci is the deformation magnitude under the water flow impact of the i-th monitoring point, xm is the safety value of the deformation magnitude, θsi-x is the included angle between the water flow impact direction and the displacement direction of the i-th monitoring point, and sin() is the sine of the angle;

[0021] S23. Collect the deformation magnitude, deformation direction data of each corresponding monitoring point and the deformation magnitude, deformation direction data of the nearby monitoring points to perform deformation deviation analysis of the monitoring points. Among them, exemplarily, the nearby monitoring points can be the monitoring points located in a circle around the corresponding monitoring point. The deformation deviation analysis is to analyze the deviation of the deformation of the corresponding monitoring point from the surrounding deformation under the water flow impact, so as to analyze the deformation anomaly of the corresponding monitoring point. Among them, the deformation deviation analysis formula for the i-th monitoring point: Where, xmi is the average deformation of the nearby monitoring points of the i-th monitoring point, and θsi-m is the angle difference between the displacement direction of the i-th monitoring point and the average displacement direction of the surrounding deformation;

[0022] S24. Obtain the deformation anomaly analysis and deformation deviation analysis results of the calculated monitoring points, and perform weighted summation to obtain the deformation degree of the corresponding monitoring points.

[0023] In an implementation manner of the present application, in step S2, when collecting the water flow conditions and deformation conditions at various positions of the reservoir dam for predicting the failure degree of the corresponding positions, the following specific steps are further included:

[0024] S25. Obtain the internal humidity data under the water flow impact at the corresponding monitoring points and the regional defect data at the corresponding positions, and analyze the abnormal water penetration at the monitoring points based on the change degrees of the internal humidity data under the water flow impact at the monitoring points and the regional defect data at the corresponding positions. Among them, the analysis formula for abnormal water penetration at the i-th monitoring point is: where bi is the internal environmental humidity data at the monitoring position of the i-th monitoring point under the water flow impact, bm is the average humidity in the environment, Vi is the regional defect volume of the i-th monitoring point under the water flow impact, Vm is the safety value of the regional defect volume, and the average humidity in the environment is the average value of the humidity in the environment where the dam is located;

[0025] S26. Obtain the analysis result of abnormal water penetration at the monitoring points under the water flow impact divided by the time length to obtain the analysis change speed of abnormal water penetration at the monitoring points under the corresponding water flow impact. At the same time, obtain the weighted sum of the analysis change speed of abnormal water penetration at the monitoring points and the standardized analysis result of abnormal water penetration at the monitoring points to obtain the water penetration risk value of the corresponding monitoring points;

[0026] S27. Obtain the water penetration risk value and the deformation degree of the corresponding monitoring points, and at the same time obtain the average value of the water flow impact force at the corresponding monitoring points. Divide the weighted sum value of the water penetration risk value and the deformation degree of the corresponding monitoring points by the standardized average value of the water flow impact force to obtain the prediction result of the failure degree of the corresponding position.

[0027] In an implementation manner of the present application, in step S3, based on the basic engineering parameters and the failure degree prediction results at various positions of the reservoir dam, a calibration analysis of the dam failure degree is carried out, including the following specific contents:

[0028] S31. Obtain the basic engineering parameters of the corresponding monitoring positions, and conduct a basic erosion resistance analysis based on the basic engineering parameters of the corresponding monitoring positions. Among them, the basic erosion resistance analysis formula for the i-th monitoring point is: Nci = (a1Qi + a2Wi)Di, where a1 is the weight of the basic concrete strength ratio, Qi is the standardized basic concrete strength of the i-th monitoring point, a2 is the weight of the basic concrete elasticity ratio, Wi is the standardized basic concrete elasticity of the i-th monitoring point, and Di is the standardized basic concrete thickness of the i-th monitoring point;

[0029] S32. Obtain the failure degree prediction result of the corresponding position and the basic erosion resistance analysis result of the corresponding position, and divide the failure degree prediction result of the corresponding position by the basic erosion resistance analysis result of the corresponding position to obtain the failure degree calibration analysis result.

[0030] In an implementation manner of the present application, in step S4, the failure analysis of each position is calibrated and analyzed through the predicted future water flow impact situation and the failure degree of each position of the dam, including the following specific contents:

[0031] S41. Obtain the water flow situation upstream, and predict the flow rate and water velocity data reaching the dam in the future based on the future water flow prediction model;

[0032] S42. Obtain the flow rate and water velocity data reaching the dam in the future, and at the same time obtain the failure degree calibration analysis results of the corresponding positions. The failure prediction of each position is carried out through the flow rate and water velocity data reaching the dam in the future and the failure degree calibration analysis results of the corresponding positions. Among them, the failure prediction formula for the i-th monitoring point position is: where Kmi is the failure degree calibration analysis result of the i-th monitoring point position, exp() is the exponential power of e, Ts is the future impact duration, g is the acceleration due to gravity, Qct is the water flow rate at future time t, Vct is the water velocity at future time t, L is the length of the dam, hi is the height of the i-th monitoring point position from the bottom of the water, dt is the time integral, and fm is the safety value of the pressure borne by the corresponding position; in this formula, What is calculated is the abnormal pressure of the water flow depth at the i-th monitoring point position at future time t on the dam, which is mainly determined by the water depth; is the abnormal pressure on the dam during the water flow movement, so as to analyze the overall damage of the water flow to the i-th monitoring point position of the dam.

[0033] In an implementation manner of the present application, the allocation of maintenance analysis resources for the corresponding positions based on the failure analysis results of each position includes the following specific steps:

[0034] Set a failure threshold. If the failure prediction result of the monitoring point position is greater than or equal to the failure threshold, set the corresponding monitoring point as a first-level abnormal point, indicating that the monitoring point position will fail during the next monitoring period, and remind the maintenance personnel to repair the corresponding monitoring point positions in order according to the sorting result of the failure prediction results of the monitoring points;

[0035] If the failure prediction result of the monitoring point position is less than the failure threshold and greater than half of the failure threshold, set the corresponding monitoring point as a second-level abnormal point, and set the proportion of the overall patrol time according to the proportion of the failure prediction result of the monitoring point position to the sum of the failure prediction results of all second-level abnormal points;

[0036] If the failure prediction result of the monitoring point position is less than or equal to half of the failure threshold, the corresponding monitoring point is set as a safety monitoring point. The advantage of this step is that, according to the failure analysis result, human, material and financial resources can be reasonably allocated to avoid resource waste, the maintenance priorities of each area can be clarified, and it is ensured that high-risk areas are dealt with in a timely manner. According to the real-time monitoring and prediction results, the maintenance plan is dynamically adjusted to improve the flexibility and adaptability of resource allocation.

[0037] In a second aspect, the present application further provides a reservoir dam deformation monitoring system based on a sensor network, including:

[0038] A model construction module for establishing a three-dimensional space model of the reservoir dam and associating the three-dimensional space model, position coordinates with the basic engineering parameters of the corresponding position;

[0039] A failure degree prediction module for collecting the water flow conditions and deformation conditions of each position of the reservoir dam to predict the failure degree of the corresponding position;

[0040] A calibration analysis module for calibrating and analyzing the failure degree of the corresponding position based on the basic engineering parameters of each position of the reservoir dam and the failure degree prediction result;

[0041] A position failure analysis module for performing failure analysis on each position through the predicted future water flow impact conditions and the calibration analysis results of the failure degree of each position of the dam;

[0042] A maintenance analysis module for allocating maintenance analysis resources for the corresponding position based on the failure analysis results of each position.

[0043] In a third aspect, an electronic device provided by the present application includes: a processor and a memory. Among them, a computer program that can be called by the processor is stored in the memory, and the processor executes a reservoir dam deformation monitoring method based on a sensor network by calling the computer program stored in the memory.

[0044] In a fourth aspect, a computer-readable storage medium provided by the present application stores instructions, and when the instructions run on a computer, the computer is made to execute a reservoir dam deformation monitoring method based on a sensor network.

[0045] Compared with the prior art, the present application has the following advantages and beneficial effects:

[0046] This application collects the water flow conditions and deformation conditions at various positions of the reservoir dam to predict the failure degree of the corresponding positions. Based on the basic engineering parameters and the failure degree prediction results at various positions of the reservoir dam, calibration analysis is carried out on the failure degree of the corresponding positions. Through the predicted future water flow impact conditions and the calibration analysis results of the failure degree at various positions of the dam, failure analysis is carried out for each position. Based on the failure analysis results of each position, resource allocation for maintenance analysis of the corresponding positions is carried out. Based on the water flow conditions, deformation conditions, basic engineering parameters, and failure degree prediction and calibration analysis at various positions of the reservoir dam, failure analysis and maintenance resource allocation are carried out. By collecting water flow and deformation data in real time, potential risks can be discovered in a timely manner, the maintenance priorities of each area can be clarified, and high-risk areas can be ensured to be processed in a timely manner. According to the real-time monitoring and prediction results, the maintenance plan is dynamically adjusted to improve the flexibility and adaptability of resource allocation. Description of the Drawings

[0047] By reading the detailed description of the non-limiting embodiments with reference to the following drawings, other features, objects, and advantages of this application will become more apparent:

[0048] Figure 1 It is a schematic diagram of the overall process of the method of this application;

[0049] Figure 2 It is a working flowchart of S2 in the method of this application;

[0050] Figure 3 It is a working flowchart of S4 in the method of this application;

[0051] Figure 4 It is a schematic diagram of the structure of the system of this application;

[0052] Figure 5 It is a schematic diagram of the installation of sensors at the dam monitoring positions of this application. Detailed Embodiments

[0053] The technical solution of this application will be described in detail below through the drawings and specific embodiments. It should be understood that the embodiments of this application and the specific features in the embodiments are detailed descriptions of the technical solution of this application, rather than limitations on the technical solution of this application. Without conflict, the technical features in the embodiments of this application and the embodiments can be combined with each other.

[0054] Embodiment 1

[0055] As Figures 1 to 3 shown, this embodiment provides a method for monitoring the deformation of a reservoir dam based on a sensor network, which specifically includes the following steps:

[0056] S1: Establish a three-dimensional space model of the reservoir dam, and associate the three-dimensional space model, position coordinates with the basic engineering parameters of the corresponding positions;

[0057] In a specific embodiment, step S1 includes the following specific steps:

[0058] S11. Obtain the corresponding position data at the time of construction of each position of the reservoir dam, construct a three-dimensional space model of the reservoir dam, obtain the real-time three-dimensional space position coordinates of the corresponding positions based on a GPS or Beidou positioning module, and at the same time obtain the basic engineering parameter data of the corresponding positions. The basic engineering parameter data here includes the basic concrete strength, elasticity, and concrete thickness data of the corresponding positions to perform the association between the position coordinates of the corresponding positions in the three-dimensional space model and the basic engineering parameters of the corresponding positions;

[0059] Exemplarily, construct a three-dimensional space model of the reservoir dam through BIM three-dimensional construction software, and perform data association on the three-dimensional space model of the corresponding reservoir dam. For example, Figure 5 , the sensor components are evenly installed at the corresponding monitoring positions of the dam. The monitoring position is an installation band perpendicular to the dam, and the sensor can be installed at any position on the installation band to avoid the insecurity of the installation position caused by a single installation point;

[0060] S12. Real-time obtain the internal humidity data of each corresponding position and the regional defect data of the corresponding position. Among them, the defect data includes data such as the defect length, quantity, width, and depth of the corresponding position, which reflect the degree of regional defects, and store the corresponding data in the corresponding storage module;

[0061] Exemplarily, obtain the humidity data of the corresponding position through humidity sensors installed at the corresponding positions of the reservoir dam. In order to facilitate the separate retrieval and analysis of various data types, perform separate storage of data types. For example, store the defect data in the defect data storage module;

[0062] S2: Collect the water flow conditions and deformation conditions of each position of the reservoir dam to predict the failure degree of the corresponding position;

[0063] In a specific embodiment, in step S2, collecting the water flow conditions and deformation conditions of each position of the reservoir dam to predict the failure degree of the corresponding position includes the following specific steps:

[0064] S21. Collect the deformation magnitude and deformation direction data of each corresponding monitoring point, as well as the internal humidity data of each corresponding position of each monitoring point and the regional defect data of the corresponding position;

[0065] S22. Collect the deformation magnitude and deformation direction data of each corresponding monitoring point, and perform deformation anomaly analysis based on the deviation abnormality between the deformation magnitude, deformation direction and the water flow impact direction. Among them, the deformation anomaly analysis formula for the i-th monitoring point is: Among them, xc i is the deformation magnitude under the water flow impact at the i-th monitoring point, xm is the safety value of the deformation magnitude, θsi-x is the included angle between the water flow impact direction and the displacement direction of the i-th monitoring point, and sin() is the sine of the angle;

[0066] Exemplarily, for example, the deformation magnitude of the corresponding monitoring point is 4 mm, the safety value of the deformation magnitude is 6 mm, and the included angle between the water flow impact direction and the displacement direction of the monitoring point is 30 degrees. In this way, the analysis result of the deformation anomaly of the monitoring point calculated is 1;

[0067] S23. Collect the deformation magnitude, deformation direction data of each corresponding monitoring point and the deformation magnitude, deformation direction data of the nearby monitoring points for the deformation deviation analysis of the monitoring points. Among them, exemplarily, the nearby monitoring points can be the monitoring points located in a circle around the corresponding monitoring point. The deformation deviation analysis is to analyze the deviation of the deformation of the corresponding monitoring point from the surrounding deformation under the water flow impact, so as to analyze the deformation anomaly of the corresponding monitoring point. Among them, the deformation deviation analysis formula for the i-th monitoring point is: Among them, xmi is the average deformation of the nearby monitoring points of the i-th monitoring point, and θsi-m is the angle difference between the displacement direction of the i-th monitoring point and the average displacement direction of the surrounding deformation;

[0068] Exemplarily, the deformation magnitude of the corresponding monitoring point is 4 mm, the average deformation of the nearby monitoring points is 2 mm, and the angle difference between the displacement direction of the i-th monitoring point and the average displacement direction of the surrounding deformation is 15 degrees. The calculated deformation deviation of the i-th monitoring point is 0.63;

[0069] S24. Obtain the analysis results of the deformation anomaly and deformation deviation of the calculated monitoring points, and perform weighted summation to obtain the deformation degree of the corresponding monitoring points;

[0070] Exemplarily, the weighted weights of the two parameters are obtained through experiments, and preferably the weight of the deformation anomaly analysis is 0.65, and the weight of the deformation deviation analysis result is 0.35.

[0071] In a specific embodiment, in step S2, when collecting the water flow conditions and deformation conditions at each position of the reservoir dam for predicting the failure degree of the corresponding position, the following specific steps are further included:

[0072] S25. Obtain the internal humidity data under the water flow impact at the corresponding monitoring points and the regional defect data at the corresponding positions, and analyze the water penetration anomaly of the monitoring points based on the change degree of the internal humidity data under the water flow impact at the monitoring points and the regional defect data at the corresponding positions. Among them, the water penetration anomaly analysis formula for the i-th monitoring point is: Among them, bi is the internal environmental humidity data at the i-th monitoring point under the impact of water flow, bm is the average humidity in the environment, Vi is the volume of regional defects at the i-th monitoring point under the impact of water flow, and Vm is the safety value of the volume of regional defects. Among them, the average humidity in the environment is the average humidity in the environment where the dam is located;

[0073] S26. Obtain the analysis result of water penetration anomaly at the monitoring point under the impact of water flow, divide it by the time length to obtain the change speed of the analysis of water penetration anomaly at the corresponding monitoring point under the impact of water flow. At the same time, obtain the change speed of the analysis of water penetration anomaly at the monitoring point and the standardized analysis result of water penetration anomaly at the monitoring point, and perform weighted summation to obtain the water penetration danger value of the corresponding monitoring point;

[0074] Exemplarily, the purpose of obtaining the weighted summation of the change speed of the analysis of water penetration anomaly at the monitoring point and the analysis result of water penetration anomaly at the monitoring point here is that since the damage of the monitoring point will increase with the increase of the change speed and also with the increase of the analysis result of water penetration anomaly at the monitoring point, because the increase of the defect of the monitoring point will further reduce the strength of the dam. In this step, the weights of the change speed of the analysis of water penetration anomaly at the monitoring point and the analysis result of water penetration anomaly at the monitoring point are preferably 0.67 and 0.33;

[0075] S27. Obtain the water penetration danger value and the degree of deformation of the corresponding monitoring point, and at the same time obtain the average value of the water flow impact force at the corresponding monitoring point. Divide the weighted summation value of the water penetration danger value and the degree of deformation of the corresponding monitoring point by the standardized average value of the water flow impact force to obtain the prediction result of the failure degree at the corresponding position;

[0076] Exemplarily, the standardization process in this step is to divide by the standard value of the corresponding parameter, and the weighted weights of the water penetration danger value and the degree of deformation in this step are obtained through experiments. Among them, the weighted weights of the water penetration danger value and the degree of deformation are preferably 0.266 and 0.734;

[0077] S3: Calibrate and analyze the failure degree of the corresponding position based on the basic engineering parameters and the prediction result of the failure degree of each position of the reservoir dam;

[0078] In a specific embodiment, it includes the following specific contents:

[0079] S31. Obtain the basic engineering parameters of the corresponding monitoring position, and perform basic erosion resistance analysis based on the basic engineering parameters of the corresponding monitoring position. Among them, the basic erosion resistance analysis formula for the i-th monitoring point is: Nci = (a1Qi + a2Wi)Di, where a1 is the weight of the basic concrete strength ratio, Qi is the standardized basic concrete strength of the i-th monitoring point, a2 is the weight of the basic concrete elasticity ratio, Wi is the standardized basic concrete elasticity of the i-th monitoring point, and Di is the standardized basic concrete thickness of the i-th monitoring point;

[0080] Exemplarily, the impact resistance of the corresponding monitoring position is obtained through the basic engineering parameters of the corresponding monitoring position. The weight ratio of the basic concrete strength and the weight ratio of the basic concrete elasticity here are preferably 0.55 and 0.45;

[0081] S32. Obtain the failure degree prediction result of the corresponding position and the basic impact resistance analysis result of the corresponding position, and divide the failure degree prediction result of the corresponding position by the basic impact resistance analysis result of the corresponding position to obtain the failure degree calibration analysis result;

[0082] Exemplarily, the failure degree calibration analysis result is obtained here by removing the influence of the basic impact resistance analysis result of the corresponding position from the failure degree prediction result of the corresponding position;

[0083] S4: Perform failure analysis on each position through the predicted future water flow impact situation and the failure degree calibration analysis results of each position of the dam;

[0084] In a specific embodiment, it includes the following specific content:

[0085] S41. Obtain the water flow situation upstream, and predict the future flow rate and water velocity data reaching the dam based on the future water flow prediction model. Here, it should be noted that the future water flow prediction model has been generally mentioned in the prior art. For example, the prior art uses neural networks and the flow rate data of historical river basins to predict the water flow situation of future river basins. This is a conventional technical means in the prior art and is not the main inventive point of this application, so it will not be elaborated in detail here;

[0086] S42. Obtain the future flow rate and water velocity data reaching the dam, and at the same time obtain the failure degree calibration analysis results of the corresponding positions. Perform failure prediction on each position through the future flow rate and water velocity data reaching the dam and the failure degree calibration analysis results of the corresponding positions. Among them, the failure prediction formula for the i-th monitoring point position is: where Kmi is the failure degree calibration analysis result of the i-th monitoring point position, exp() is the exponential power of e, Ts is the future impact duration, g is the acceleration due to gravity, Qct is the water flow rate at future time t, Vct is the water velocity at future time t, L is the length of the dam, hi is the height of the i-th monitoring point position from the bottom of the water, dt is the time integral, and fm is the safety value of the pressure borne by the corresponding position; in this formula, What is calculated is the abnormal pressure of the water flow depth at the i-th monitoring point position on the dam at future time t, which is mainly determined by the water depth; It is the abnormal pressure on the dam during the water flow movement, so as to analyze the overall damage of the water flow to the i-th monitoring point position of the dam;

[0087] S5. Perform maintenance analysis resource allocation for corresponding positions based on the failure analysis results of each position;

[0088] In a specific embodiment, it includes the following specific steps:

[0089] Set a failure threshold. If the failure prediction result of the monitoring point position is greater than or equal to the failure threshold, set the corresponding monitoring point as a first-level abnormal point, indicating that the monitoring period at the monitoring point position will fail, and remind the maintenance personnel to repair the corresponding monitoring point positions in order according to the sorting result of the failure prediction results of the monitoring points;

[0090] If the failure prediction result of the monitoring point position is less than the failure threshold and greater than half of the failure threshold, set the corresponding monitoring point as a second-level abnormal point, and set the proportion of the overall inspection time according to the proportion of the failure prediction result of the monitoring point position in the sum of the failure prediction results of all second-level abnormal points;

[0091] Exemplarily, for example, the failure prediction result of a certain monitoring point position is 4.23, and the sum of the failure prediction results of all second-level abnormal points is 205, and the total daily inspection time corresponding to it is 10h, then the inspection resource (duration) for inspecting this monitoring point position is 0.206h;

[0092] If the failure prediction result of the monitoring point position is less than or equal to half of the failure threshold, set the corresponding monitoring point as a safety monitoring point. The advantage of this step is that, based on the failure analysis results, manpower, material resources, and financial resources are reasonably allocated, resource waste is avoided, the maintenance priorities of each area are clarified, and high-risk areas are ensured to be processed in a timely manner. According to the real-time monitoring and prediction results, the maintenance plan is dynamically adjusted to improve the flexibility and adaptability of resource allocation.

[0093] It should be noted in this embodiment that the acquisition method of the set parameters (such as the weighted weights of each parameter and the set failure threshold, etc.) in this embodiment is obtained by experiments of engineers in the field through historical data. The specific experimental method is: obtain the water flow conditions, deformation conditions, and basic engineering parameters of each position of the historical reservoir dam, substitute them into each step of this embodiment for the analysis of the failure prediction results of the monitoring point positions in the next cycle, and at the same time obtain the failure judgment results of the monitoring point positions in the next cycle, and import them into the fitting software to output the set parameter values that meet the maximum failure judgment result accuracy rate.

[0094] It should be noted that in this embodiment, the following advantages exist. The water flow conditions and deformation conditions at various positions of the reservoir dam are collected for predicting the failure degree at the corresponding positions. Based on the basic engineering parameters at various positions of the reservoir dam and the prediction results of the failure degree, the failure degree at the corresponding positions is calibrated and analyzed. Through the predicted future water flow impact conditions and the calibrated analysis results of the failure degree at various positions of the dam, the failure analysis at each position is carried out. Based on the failure analysis results at each position, the resource allocation for the maintenance analysis at the corresponding positions is carried out. Based on the water flow conditions, deformation conditions, basic engineering parameters, and the prediction and calibration analysis of the failure degree at various positions of the reservoir dam, the failure analysis and the resource allocation for maintenance are carried out. By collecting water flow and deformation data in real time, potential risks can be discovered in a timely manner, the maintenance priorities of each area can be clarified, and it is ensured that high-risk areas are processed in a timely manner. According to the real-time monitoring and prediction results, the maintenance plan is dynamically adjusted to improve the flexibility and adaptability of resource allocation.

[0095] Embodiment 2

[0096] As Figure 4 shown, this embodiment provides a deformation monitoring system for a reservoir dam based on a sensor network, including:

[0097] A model construction module, which is used to establish a three-dimensional space model of the reservoir dam and associate the three-dimensional space model, position coordinates with the basic engineering parameters at the corresponding positions;

[0098] A failure degree prediction module, which collects the water flow conditions and deformation conditions at various positions of the reservoir dam for predicting the failure degree at the corresponding positions;

[0099] A calibration analysis module, which calibrates and analyzes the failure degree at the corresponding positions based on the basic engineering parameters at various positions of the reservoir dam and the prediction results of the failure degree;

[0100] A position failure analysis module, which conducts failure analysis at each position through the predicted future water flow impact conditions and the calibrated analysis results of the failure degree at various positions of the dam;

[0101] A maintenance analysis module, which allocates resources for the maintenance analysis at the corresponding positions based on the failure analysis results at each position;

[0102] It also includes modules that exist in existing systems such as a display module and an information push module. For example, the display module is used for displaying the three-dimensional model and the maintenance schedule, and the information push module is used for pushing the maintenance situation to the management personnel;

[0103] Regarding the steps and corresponding functions of each parameter and each unit module in the deformation monitoring system for the reservoir dam based on the sensor network of this application, reference can be made to the parameters and steps in the embodiment of the deformation monitoring method for the reservoir dam based on the sensor network in the method embodiment, which will not be elaborated here.

[0104] Example 3

[0105] An electronic device according to an embodiment of the present application includes: a processor and a memory. Among them, a computer program that can be called by the processor is stored in the memory. The processor executes a method for monitoring the deformation of a reservoir dam based on a sensor network by calling the computer program stored in the memory. It should be noted that: all computer programs of the method for monitoring the deformation of a reservoir dam based on a sensor network are implemented using the C language.

[0106] Example 4

[0107] This embodiment provides a computer-readable storage medium, on which a rewritable computer program is stored;

[0108] When the computer program runs on a computer device, the computer device is caused to execute the above-mentioned method for monitoring the deformation of a reservoir dam based on a sensor network.

[0109] The various embodiments in the present application are described in a progressive manner. For the same or similar parts between the various embodiments, reference can be made to each other. The key point of each embodiment is to illustrate the differences from other embodiments. In particular, for the embodiments of the Internet of Things devices and media, since they are basically similar to the method embodiments, the description is relatively simple, and reference can be made to the partial description of the method embodiments for the relevant parts.

[0110] The systems and media provided by the embodiments of the present application correspond one-to-one with the methods. Therefore, the systems and media also have beneficial technical effects similar to those of the corresponding methods. Since the beneficial technical effects of the methods have been described in detail above, the beneficial technical effects of the systems and media will not be elaborated here.

[0111] Those skilled in the art should understand that the embodiments of the present application can be provided as a method, a system, or a computer program product. Therefore, the present application can take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk memories, CD-ROMs, optical memories, etc.) containing computer-usable program codes.

[0112] This application is described with reference to the flowcharts and / or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the present application. It should be understood that each flow and / or block in the flowchart and / or block diagram, and the combination of flows and / or blocks in the flowchart and / or block diagram, can be realized by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate means for realizing the functions specified in one flow Figure 1 one flow or more flows and / or blocks Figure 1 or means for realizing the functions specified in one block or more blocks.

[0113] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer-readable memory generate a manufacture including instruction means, and the instruction means realizes the functions specified in one flow Figure 1 one flow or more flows and / or blocks Figure 1 or means for realizing the functions specified in one block or more blocks.

[0114] In a typical configuration, a computing device includes one or more processors (CPUs), an input / output interface, a network interface, and a memory.

[0115] The memory may include non-permanent memory in the computer-readable medium, in the form of random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash memory (flash RAM). The memory is an example of a computer-readable medium.

[0116] Computer-readable media includes permanent and non-permanent, removable and non-removable media that can store information by any method or technology. The 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 technologies, compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassette tapes, magnetic disk storage or other magnetic storage devices, or any other non-transmission media that can be used to store information accessible by a computing device. As defined herein, computer-readable media does not include transitory media, such as modulated data signals and carrier waves.

[0117] It should also be noted that the term "comprising", "including" or any other variant thereof is intended to cover non-exclusive inclusion, such that a process, method, commodity or device comprising a series of elements not only includes those elements but also includes other elements not expressly listed, or further includes elements inherent to such process, method, commodity or device. Without further limitation, an element defined by the statement "comprising an..." does not exclude the presence of additional identical elements in the process, method, commodity or device comprising the element.

[0118] The above are only embodiments of the present application and are not used to limit the present application. For those skilled in the art, various changes and modifications can be made to the present application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included within the scope of the claims of the present application.

Claims

1. A method for monitoring the deformation of a reservoir dam based on a sensor network, characterized in that, Including the following steps: S1: Establish a three-dimensional spatial model of the reservoir dam, and associate the three-dimensional spatial model, position coordinates with the basic engineering parameters at the corresponding positions; S2: Collect the water flow conditions and deformation conditions at each position of the reservoir dam to predict the failure degree at the corresponding positions; S3: Conduct calibration analysis on the failure degree at the corresponding positions based on the basic engineering parameters at each position of the reservoir dam and the failure degree prediction results; S4: Conduct failure analysis at each position through the predicted future water flow impact conditions and the calibration analysis results of the failure degree at each position of the dam; S5. Allocate maintenance analysis resources at the corresponding positions based on the failure analysis results at each position.

2. The method for monitoring the deformation of a reservoir dam based on a sensor network according to claim 1, wherein, The step of collecting the water flow conditions and deformation conditions at each position of the reservoir dam to predict the failure degree at the corresponding positions includes the following specific steps: Collect the deformation magnitude and deformation direction data of each corresponding monitoring point, as well as the internal humidity data at each corresponding position of each monitoring point and the regional defect data at the corresponding positions; Collect the deformation magnitude and deformation direction data corresponding to each monitoring point, and conduct deformation anomaly analysis based on the deviation anomalies between the deformation magnitude, deformation direction and the water flow impact direction. Among them, the deformation anomaly analysis formula for the i-th monitoring point is: where xci is the deformation magnitude under the water flow impact at the i-th monitoring point, xm is the safety value of the deformation magnitude, θsi-x is the angle formed by the water flow impact direction and the displacement direction of the i-th monitoring point, and sin() is the sine of the angle; Collect the deformation magnitude and deformation direction data corresponding to each monitoring point, as well as the deformation magnitude and deformation direction data of the nearby monitoring points, and conduct deformation deviation analysis of the monitoring points. Among them, the deformation deviation analysis formula for the i-th monitoring point is: Among them, xmi is the average deformation of the nearby monitoring points of the i-th monitoring point, and θsi-m is the angle difference between the displacement direction of the i-th monitoring point and the average displacement direction of the surrounding deformations; Obtain the deformation anomaly analysis and deformation deviation analysis results calculated for the monitoring points, and perform weighted summation to obtain the deformation degree of the corresponding monitoring points.

3. The method for monitoring the deformation of a reservoir dam based on a sensor network according to claim 2, wherein, The step of collecting the water flow conditions and deformation conditions at each position of the reservoir dam to predict the failure degree at the corresponding positions further includes the following specific steps: Obtain the internal humidity data under water flow impact at the corresponding monitoring points and the regional defect data at the corresponding positions, and analyze the abnormal water penetration at the monitoring points based on the change degree of the internal humidity data under water flow impact at the monitoring points and the regional defect data at the corresponding positions; Obtain the analysis result of the abnormal water penetration at the monitoring points under water flow impact and divide it by the time duration to obtain the change speed of the analysis of the abnormal water penetration at the corresponding monitoring points under water flow impact. At the same time, obtain the weighted summation of the change speed of the analysis of the abnormal water penetration at the monitoring points and the standardized analysis result of the abnormal water penetration at the monitoring points to obtain the water penetration risk value of the corresponding monitoring points; Obtain the water penetration risk value and deformation degree of the corresponding monitoring points, and at the same time obtain the mean value of the water flow impact force at the corresponding monitoring points. Divide the weighted summation value of the water penetration risk value and deformation degree of the corresponding monitoring points by the standardized mean value of the water flow impact force to obtain the failure degree prediction result at the corresponding positions.

4. The method for monitoring the deformation of a reservoir dam based on a sensor network according to claim 3, wherein, Conduct calibration analysis on the dam failure degree based on the basic engineering parameters at each position of the reservoir dam and the failure degree prediction results, including the following specific contents: S31: Obtain the basic engineering parameters at the corresponding monitoring positions, and conduct basic erosion resistance analysis based on the basic engineering parameters at the corresponding monitoring positions. Among them, the basic erosion resistance analysis formula for the i-th monitoring point is: Nci = (a1Qi + a2Wi)Di, where a1 is the weight of the basic concrete strength ratio, Qi is the standardized basic concrete strength of the i-th monitoring point, a2 is the weight of the basic concrete elasticity ratio, Wi is the standardized basic concrete elasticity of the i-th monitoring point, and Di is the standardized basic concrete thickness of the i-th monitoring point; S32: Obtain the failure degree prediction result at the corresponding position and the basic erosion resistance analysis result at the corresponding position, and divide the failure degree prediction result at the corresponding position by the basic erosion resistance analysis result at the corresponding position to obtain the failure degree calibration analysis result.

5. The method for monitoring the deformation of a reservoir dam based on a sensor network according to claim 4, wherein In S4, failure analysis of each position is carried out by calibrating the analysis results based on the predicted future water flow impact situation and the failure degree of each position of the dam, including the following specific contents: S41. Obtain the water flow situation upstream, and predict the flow rate and water velocity data reaching the dam in the future based on the future water flow prediction model; S42. Obtain the flow rate and water velocity data reaching the dam in the future, and at the same time obtain the calibration analysis results of the failure degree of the corresponding position. Carry out failure prediction of each position through the flow rate and water velocity data reaching the dam in the future and the calibration analysis results of the failure degree of the corresponding position.

6. The method for monitoring the deformation of a reservoir dam based on a sensor network according to claim 5, characterized in that, The specific steps for allocating maintenance analysis resources for the corresponding position based on the failure analysis results of each position are as follows: Set a failure threshold. If the failure prediction result of the monitoring point position is greater than or equal to the failure threshold, set the corresponding monitoring point as a first-level abnormal point, indicating that the monitoring point position will fail during the monitoring period, and remind the maintenance personnel to repair the corresponding monitoring point position in order according to the sorting result of the failure prediction results of the monitoring points; If the failure prediction result of the monitoring point position is less than the failure threshold and greater than half of the failure threshold, set the corresponding monitoring point as a second-level abnormal point, and set the proportion of the overall inspection time according to the proportion of the failure prediction result of the monitoring point position to the sum of the failure prediction results of all second-level abnormal points; If the failure prediction result of the monitoring point position is less than or equal to half of the failure threshold, set the corresponding monitoring point as a safety monitoring point.

7. The method for monitoring the deformation of a reservoir dam based on a sensor network according to claim 6, characterized in that, The specific steps for establishing a three-dimensional space model of the reservoir dam and associating the three-dimensional space model, position coordinates with the basic engineering parameters of the corresponding position are as follows: Obtain the corresponding position data during the construction of each position of the reservoir dam, construct a three-dimensional space model of the reservoir dam, obtain the real-time three-dimensional space position coordinates of the corresponding position based on the GPS or Beidou positioning module, and at the same time obtain the basic engineering parameter data of the corresponding position to associate the position coordinates of the corresponding position in the three-dimensional space model with the basic engineering parameters of the corresponding position; S12. Real-time obtain the internal humidity data of each corresponding position and the regional defect data of the corresponding position, and store the corresponding data in the corresponding storage module.

8. The method for monitoring the deformation of a reservoir dam based on a sensor network according to claim 5, characterized in that, The failure prediction formula for the position of the i-th monitoring point is as follows: Where, Kmi is the failure degree calibration analysis result at the position of the i-th monitoring point, exp() is the exponential power of e, Ts is the future impact duration, g is the acceleration due to gravity, Qct is the water flow rate at the future time t, Vct is the water velocity at the future time t, L is the dam length, hi is the height of the i-th monitoring point from the bottom of the water, dt is the time integral, and fm is the safety value of the pressure borne at the corresponding position.

9. A reservoir dam deformation monitoring system based on a sensor network, which is implemented based on the reservoir dam deformation monitoring method based on a sensor network according to any one of claims 1-8, characterized in that, The system includes: A model construction module for establishing a three-dimensional space model of the reservoir dam and associating the three-dimensional space model, position coordinates with the basic engineering parameters of the corresponding position; A failure degree prediction module for collecting the water flow situation and deformation situation of each position of the reservoir dam to predict the failure degree of the corresponding position; A calibration analysis module for calibrating and analyzing the failure degree of the corresponding position based on the basic engineering parameters of each position of the reservoir dam and the failure degree prediction results; A position failure analysis module for carrying out failure analysis of each position through the predicted future water flow impact situation and the calibration analysis results of the failure degree of each position of the dam; A maintenance analysis module for allocating maintenance analysis resources for the corresponding position based on the failure analysis results of each position.

10. An electronic device, comprising: A processor and a memory, wherein the memory stores a computer program that can be called by the processor; characterized in that the processor executes the method for monitoring the deformation of the reservoir dam based on the sensor network according to any one of claims 1-8 by calling the computer program stored in the memory.

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