Intelligent monitoring system for stress and seepage of water gate structure

Abstract

The invention discloses a sluice structure stress and seepage intelligent monitoring system, and belongs to the technical field of hydraulic engineering, and the system comprises a stress monitoring module which is used for monitoring the stress change of a sluice and monitoring the stress change of key parts, and the key parts comprise a sluice pier, a sluice gate and a breast wall; the seepage collection module is used for collecting seepage pressure and seepage quantity of the water gate; and the data processing and analyzing module is used for processing the stress change, the seepage pressure and the seepage flow, and the processing comprises cleaning and correction. Stress change monitoring can be carried out on key parts of a water gate, seepage pressure and seepage flow are collected, more comprehensive and accurate monitoring data can be obtained, fusion processing is carried out on the data, the limitation that the data are relatively independent in traditional monitoring is broken through, mutual verification and complementation of the data are achieved, and the monitoring accuracy is improved. The safety state of the water gate is comprehensively evaluated from multiple dimensions, and the monitoring accuracy and reliability are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of water conservancy engineering, in particular to a sluice structure stress and seepage intelligent monitoring system. Background Art

[0002] Sluice gates play a key control and regulation role in water conservancy projects, making their safe operation crucial. However, over the long term, sluice gates are subject to a variety of factors, including water flow impacts, gate opening and closing, and upstream and downstream water level fluctuations. These factors can cause structural stress changes and potentially lead to seepage problems. If these issues are not detected and addressed promptly, they can lead to damage or even collapse of the sluice gates, resulting in serious safety incidents and economic losses.

[0003] Regarding this research, application number CN202411549596.0 proposes an intelligent monitoring system for seepage in water conservancy projects. This technical solution includes a multi-sensor perception module, a data acquisition module, a data fusion and processing module, a machine learning prediction module, an intelligent decision-making module, an adaptive monitoring and scheduling module, an automatic inspection and response module, a digital twin and simulation analysis module, and a communication module. The multi-sensor perception module is responsible for collecting multi-dimensional data related to seepage in real time. By learning from historical and real-time data, this technical solution can automatically identify complex seepage patterns and predict future risks in advance, enabling proactive management of seepage risks in water conservancy projects and significantly improving the system's prediction accuracy and response speed.

[0004] Another application, CN202410037466.2, provides a sluice seepage monitoring method based on IoT technology. This technical solution includes collecting sluice seepage monitoring data, determining the likelihood that the left and right data points of each data point are its neighborhood data based on the amplitude difference between the data point and its left and right data points in the monitoring data, and then determining the neighborhood data interval for each data point; determining the similarity of the neighborhood data intervals of different data points based on the data differences between the neighborhood data intervals of different data points; and constructing a similarity matrix based on the similarities of the neighborhood data intervals of different data points. This technical solution monitors sluice seepage by adaptively counting the number of neighbors, resulting in more accurate monitoring results.

[0005] However, the above technical solutions lack effective collaborative analysis of important safety indicators such as structural stress and seepage. For example, there is a lack of effective correlation analysis between deformation monitoring data and seepage monitoring data, and it is impossible to timely discover implicit information and potential safety hazards in the data, which makes it difficult to conduct a comprehensive assessment of the safety status of the sluice from multiple dimensions, affecting the assessment of the overall safety status of the sluice. Summary of the Invention

[0006] In view of the above problems existing in the technical field of existing water conservancy engineering, the present invention is proposed.

[0007] Therefore, one of the purposes of the present invention is to provide an intelligent monitoring system for sluice structure stress and seepage, which can monitor stress changes in key parts of the sluice, and collect seepage pressure and seepage volume, so as to obtain more comprehensive and accurate monitoring data, and fuse the data, breaking the limitation of the relative independence of each data in traditional monitoring, realizing mutual verification and supplementation between data, comprehensively evaluating the safety status of the sluice from multiple dimensions, and improving the accuracy and reliability of monitoring.

[0008] In order to solve the above technical problems, the present invention provides the following technical solutions: The present invention provides a sluice structure stress and seepage intelligent monitoring system, comprising: A stress monitoring module is used to monitor stress changes in the sluice gate, including monitoring stress changes in key parts, such as the piers, gates, and breast walls; Seepage collection module, used to collect the seepage pressure and seepage volume of the sluice; A data processing and analysis module is used to process the stress change, seepage pressure and seepage volume, wherein the processing includes cleaning and correction; and to perform correlation analysis on the processed stress change, seepage pressure and seepage volume; A data fusion processing module is used to fuse the stress and seepage of the sluice gate according to the results of the correlation analysis; the data fusion processing module includes a differentiation unit, a calculation unit and an evaluation and early warning unit; The differentiation unit is used to differentiate the stress of the sluice gate according to the result of the correlation analysis, including differentiating the stress according to the area of ​​the sluice gate and dividing the stress into upper stress and lower stress; the upper stress and lower stress correspond to the upper half and lower half of the sluice gate respectively; The calculation unit is responsive to the differentiation unit and is used to calculate the stress of the sluice gate based on the dividing line between the upper half and the lower half of the sluice gate, including calculating the regular change from the stress of the dividing line to the lower stress; The evaluation and early warning unit responds to the calculation unit and is used to preset a risk threshold for the stress; if the change from the stress of the dividing line to the lower stress exceeds the risk threshold, the system determines that there is a safety hazard in the sluice and issues an early warning; otherwise, no determination is made; A seepage pressure acquisition module responds to the assessment and early warning unit and is used to collect the seepage pressure of the sluice when the system determines that the sluice has a safety hazard, including collecting the seepage pressure of related stress points; and presetting a critical value for the seepage pressure.

[0009] As a preferred solution of the present invention, wherein: in the seepage pressure acquisition module, the relevant stress points include stress points divided by the lower stress, and the division method includes dividing the largest 3 to 5 stress points in the lower stress, and collecting the seepage pressure closest to the largest 3 to 5 stress points, and the seepage pressure is the seepage pressure within 10 cm from the largest 3 to 5 stress points; if the seepage pressure exceeds the critical value, the system determines that the sluice is at risk of seepage and issues an early warning; otherwise, no determination is made.

[0010] As a preferred solution of the present invention, in the data processing and analysis module, the processing further includes extracting features of the stress change, seepage pressure, and seepage volume; wherein the feature extraction of the stress change includes extracting the stress peak value, the stress average value, and the stress fluctuation frequency; Feature extraction of seepage pressure and seepage volume, including extraction of pressure change rate and seepage velocity.

[0011] As a preferred embodiment of the present invention, the stress fluctuation frequency is extracted by calculating the standard deviation of the stress within a certain period of time, wherein the standard deviation is the standard deviation at intervals of 5 to 10 minutes; the calculation is performed according to the following formula: ;in, represents the standard deviation of stress; Where, Indicates the stress, It represents the average value of stress, which is the concentration trend of stress. The calculation formula is: ; Indicates the total number of stresses, which is the sum of the number of stresses collected within 5 to 10 minutes; represents the square of the difference between each stress and the average value. As a preferred embodiment of the present invention, wherein: extracting the seepage velocity includes extracting it by calculating the derivative of the seepage rate, and calculating it according to the following formula: ;in, represents the seepage velocity; Where, represents the seepage rate, Indicates time, used to obtain the change of seepage rate over time; Indicates seepage rate About time The derivative of , that is, the rate of change of seepage flow with time.

[0012] As a preferred solution of the present invention, in the calculation unit, the regular change from the stress of the dividing line to the lower stress is calculated according to the following formula: ;in, Indicates that the depth in the lower half of the sluice is stress at Where, represents the maximum stress in the lower part of the sluice gate, Indicates the total height of the lower half of the sluice gate. Represents the stress distribution index.

[0013] As a preferred solution of the present invention, the stress fluctuation frequency when the change from the stress of the boundary line to the lower stress exceeds the risk threshold, and the seepage velocity when the seepage pressure exceeds the critical value are collected based on the calculated stress fluctuation frequency and seepage velocity, and the stress fluctuation frequency corresponding to the change from the stress of the boundary line to the lower stress exceeds the risk threshold is marked as a reference stress fluctuation frequency, and the seepage velocity corresponding to the seepage pressure exceeding the critical value is marked as a reference seepage velocity, and at the same time, the water level corresponding to the reference stress fluctuation frequency and the reference seepage velocity is obtained, and the water level is marked as a reference water level. Based on the reference water level height, the stress fluctuation frequency and seepage velocity when the water level is at half of the reference water level height are obtained; based on the stress fluctuation frequency and seepage velocity, the stress fluctuation frequency and seepage velocity when the water level height increases by 10 cm are analyzed; the stress fluctuation frequency and seepage velocity are marked as regular stress fluctuation frequency and regular seepage velocity; when the stress fluctuation frequency and seepage velocity of the sluice are obtained in the future time period, when the water level height is only half of the height of the sluice, if the stress fluctuation frequency and seepage velocity are lower than the regular stress fluctuation frequency and regular seepage velocity, the system determines that there is no safety hazard in the sluice; otherwise, it is determined that there is a safety hazard and an early warning is issued.

[0014] As a preferred solution of the present invention, when the system determines that there is no safety hazard in the sluice gate, the difference in stress fluctuation frequency and the difference in seepage velocity between the middle and bottom of the sluice gate are obtained at the water level height, wherein the stress fluctuation frequency and seepage velocity at the bottom are the stress fluctuation frequency and seepage velocity of the same horizontal line, and at least 5 stress fluctuation frequencies and seepage velocities are obtained at the bottom, and the average value of the 5 stress fluctuation frequencies and seepage velocities is calculated. If the average value is greater than the stress fluctuation frequency and seepage velocity in the middle, the system determines that there is a safety hazard in the sluice gate and issues an early warning.

[0015] As a preferred solution of the present invention, when the average value is greater than the stress fluctuation frequency and seepage velocity in the middle part, 2 to 3 largest stress fluctuation frequencies and seepage velocities are collected from the 5 stress fluctuation frequencies and seepage velocities, and the stress fluctuation frequencies and seepage velocities are sorted in ascending order, and the dangerous parts of the sluice are divided according to the sorting results.

[0016] Beneficial effects: By monitoring stress changes at key locations of the sluice gate and collecting seepage pressure and flow rates, more comprehensive and accurate monitoring data can be obtained. Simultaneously, feature extraction of the data, such as stress fluctuation frequency and seepage velocity, helps provide a more detailed understanding of the sluice gate's stress and seepage conditions, further improving monitoring accuracy. The system can integrate the stress and seepage of the sluice gate based on the results of correlation analysis, breaking the limitation of relatively independent data in traditional monitoring, realizing mutual verification and supplementation between data, comprehensively evaluating the safety status of the sluice gate from multiple dimensions, and improving the accuracy and reliability of monitoring; The system can conduct real-time assessment of the stress changes of the sluice gate based on the preset risk threshold. When the change from the boundary stress to the lower stress exceeds the threshold, or the seepage pressure exceeds the critical value, it will issue a timely warning to remind relevant personnel to take measures to effectively prevent the occurrence of sluice gate accidents and reduce losses. The present invention also proposes a method for dividing dangerous areas of a sluice gate. When the average value is greater than the stress fluctuation frequency and seepage velocity in the middle, the larger stress fluctuation frequency and seepage velocity are collected and sorted. The dangerous areas of the sluice gate are then divided according to the sorting results. This method helps to quickly and accurately locate potential safety hazards in the sluice gate, provides clear guidance for subsequent maintenance and repair work, facilitates the rational allocation of resources, and improves maintenance efficiency. The present invention can also adapt to the monitoring needs under different water level changes. On the basis of obtaining the reference water level height, it analyzes the stress fluctuation frequency and seepage velocity when the water level is half of the reference water level, and then infers the law when the water level rises. This adaptive analysis of different water level conditions enables the system to better play its role when facing the frequent changes in water level during the actual operation of the sluice, and has strong flexibility and practicality. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. Those skilled in the art can also derive other drawings based on these drawings without inventive effort. Among them: Figure 1 This is a schematic diagram of the modular structure of the intelligent monitoring system for sluice structure stress and seepage according to an embodiment of the present invention; Figure 2 This is a schematic diagram of the process structure of an embodiment of the present invention; Numbers in the figure: 110 - stress monitoring module; 120 - seepage acquisition module; 130 - data processing and analysis module; 140 - data fusion processing module; 1401 - differentiation unit; 1402 - calculation unit; 1403 - assessment and early warning unit; 150 - seepage pressure acquisition module. DETAILED DESCRIPTION

[0018] To make the objectives, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions of the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the described embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field are within the scope of protection of the present invention.

[0019] Since existing technologies lack effective collaborative analysis of important safety indicators such as structural stress and seepage, it is difficult to conduct a comprehensive assessment of the safety status of the sluice from multiple dimensions, which affects the assessment of the overall safety status of the sluice.

[0020] Based on this, the present invention proposes an intelligent monitoring system for sluice structure stress and seepage, which can monitor stress changes in key parts of the sluice, and collect seepage pressure and seepage volume, so as to obtain more comprehensive and accurate monitoring data, and fuse the data, breaking the limitation of the relative independence of each data in traditional monitoring, realizing mutual verification and supplementation between data, comprehensively evaluating the safety status of the sluice from multiple dimensions, and improving the accuracy and reliability of monitoring.

[0021] The present invention will be further described in detail below through embodiments and in conjunction with the accompanying drawings.

[0022] Reference Figures 1 to 2 , is an embodiment of the present invention, which provides a sluice structure stress and seepage intelligent monitoring system, including: Stress monitoring module 110, used to monitor stress changes of the sluice gate, including monitoring stress changes of key parts, such as piers, gates and breast walls; In this embodiment, in a feasible implementation scheme, stress sensors are arranged at key parts of the sluice (such as piers, gates, breast walls, etc.) to monitor the stress changes of the sluice structure in real time. These sensors can be micro-resistance strain gauges or fiber Bragg grating sensors, which have the characteristics of high precision, high sensitivity, and strong anti-interference ability, and can accurately reflect the stress state of the sluice under different working conditions. Seepage collection module 120, used to collect seepage pressure and seepage volume of the sluice; In this embodiment, in a feasible implementation scheme, seepage monitoring points are set up upstream and downstream of the sluice gate and around the sluice gate foundation, and monitoring equipment such as piezometers and flow meters are installed to collect data such as seepage pressure and seepage volume in real time to understand the distribution, flow direction and intensity of seepage, and to judge the anti-seepage performance of the sluice gate and whether there are any leakage risks; The data processing and analysis module 130 is used to process stress changes, seepage pressure, and seepage volume, including cleaning and correction; and to perform correlation analysis on the processed stress changes, seepage pressure, and seepage volume; The data fusion processing module 140 is used to perform fusion processing on the stress and seepage of the sluice gate according to the results of the correlation analysis; the data fusion processing module 140 includes a differentiation unit 1401, a calculation unit 1402 and an evaluation and early warning unit 1403; The differentiation unit 1401 is used to differentiate the stress of the water gate according to the result of the correlation analysis, including differentiating the stress according to the area of ​​the water gate and differentiating the stress into upper stress and lower stress; the upper stress and lower stress correspond to the upper half and lower half of the water gate respectively; The calculation unit 1402 is responsive to the differentiation unit and is used to calculate the stress of the sluice gate based on the dividing line between the upper and lower parts of the sluice gate, including calculating the regular change from the stress at the dividing line to the lower stress; In this embodiment, from the perspective of fluid mechanics, the pressure exerted by stationary water on the surface of an object increases linearly with increasing depth. For a sluice gate, the water upstream of the sluice gate exerts pressure on the sluice gate under the action of gravity. This pressure gradually increases vertically with increasing depth. Specifically, the water pressure in the upper half of the sluice gate is relatively small; while in the lower half of the sluice gate, due to the greater water depth, the water pressure is relatively large. Therefore, the water pressure on the sluice gate generally exhibits a distribution characteristic of being smaller at the top and larger at the bottom. This embodiment calculates the stress of the sluice gate based on the dividing line, which has practical significance; The evaluation and warning unit 1403 responds to the calculation unit and is used to preset a risk threshold for stress. If the change from the stress at the dividing line to the lower stress exceeds the risk threshold, the system determines that there is a safety hazard in the sluice and issues a warning. Otherwise, no determination is made. Seepage pressure acquisition module 150, which responds to the evaluation and early warning unit and is used to collect the seepage pressure of the sluice when the system determines that there is a safety hazard in the sluice, including collecting the seepage pressure of relevant stress points; and presetting a critical value for the seepage pressure; In summary, the present invention establishes a comprehensive monitoring system, which monitors the stress changes of key parts of the sluice (piers, gates, and breast walls) through the stress monitoring module, collects seepage pressure and seepage volume data using the seepage collection module, and the data processing and analysis module is responsible for cleaning and correcting these data and conducting correlation analysis. The data fusion processing module fuses the sluice stress and seepage according to the correlation analysis results. The differentiation unit, calculation unit, and evaluation and early warning unit under it are respectively used for stress differentiation, stress calculation based on the dividing line, and safety assessment and early warning based on the preset risk threshold. When the stress change exceeds the threshold, it is determined that there is a safety hazard and an early warning is issued. At the same time, the seepage pressure collection module responds to the evaluation and early warning unit. When it is determined that there is a hidden danger, the seepage pressure of the relevant stress point is collected and it is determined whether it exceeds the critical value. This enables comprehensive monitoring of the sluice gate's stress and seepage conditions. Combining stress monitoring with seepage monitoring, data fusion processing enables a more comprehensive assessment of the sluice gate's safety status, timely identification of potential safety hazards and issuance of early warnings, effectively improving the safety and reliability of sluice gate operations. In the seepage pressure acquisition module, the relevant stress points include stress points divided by the lower stress. The division method includes dividing the 3 to 5 largest stress points in the lower stress and collecting the seepage pressure closest to the 3 to 5 largest stress points. The seepage pressure is the seepage pressure within 10 cm of the 3 to 5 largest stress points. If the seepage pressure exceeds the critical value, the system determines that there is a risk of seepage in the sluice and issues an early warning; otherwise, no determination is made. In this embodiment, the monitoring of seepage pressure focusing on the vicinity of key stress points can more accurately capture seepage risks and effectively monitor seepage conditions, helping to take timely measures to prevent sluice accidents caused by seepage, further enhancing the safety monitoring capability of the sluice. In the data processing and analysis module, the processing also includes feature extraction of stress changes, seepage pressure and seepage volume; the feature extraction of stress changes includes extracting stress peak value, stress average value and stress fluctuation frequency; Extraction of seepage pressure and seepage volume characteristics, including extraction of pressure change rate and seepage velocity; In this embodiment, feature extraction is performed in the data processing and analysis module. Features such as stress peak value, average value, and fluctuation frequency are extracted for stress changes, and features such as pressure change rate and seepage velocity are extracted for seepage pressure and seepage volume, thereby further analyzing the key characteristics of stress and seepage data. Feature extraction can more accurately grasp the core characteristics of stress and seepage, providing more valuable information for subsequent analysis and evaluation. This helps to detect abnormal signs earlier, improve the accuracy and sensitivity of monitoring, and more effectively ensure the safety of sluice gates. Extracting the stress fluctuation frequency involves calculating the standard deviation of stress over a certain period of time. The standard deviation is the standard deviation of stress at intervals of 5 to 10 minutes. This is calculated using the following formula: ;in, represents the standard deviation of stress; Where, Indicates the stress, represents the average value of stress; The standard deviation is an important indicator to measure the degree of stress dispersion. The larger the standard deviation, the stronger the stress fluctuation; the smaller the standard deviation, the more concentrated the stress. For example, each value of multiple stresses collected within a certain period of time; The mean value is the central tendency of stress and is calculated as: ; Indicates the total number of stresses, which is the total number of stresses collected within 5 to 10 minutes; represents the square of the difference between each stress and the mean value; It should be noted that this step is to eliminate the influence of negative values, make all differences positive, and amplify the difference in discreteness by squaring; The standard deviation is used to quantify the degree of stress dispersion, thereby reflecting the intensity of stress fluctuations. This makes the quantitative assessment of stress fluctuations more operational and accurate, which can provide a more detailed understanding of stress changes and provide strong support for judging the dynamic stress state of the sluice. Extract the seepage velocity, including extracting it by calculating the derivative of the seepage rate, according to the following formula: ;in, represents the seepage velocity; Where, represents the seepage rate, Indicates time, used to obtain the change of seepage rate over time; Indicates seepage rate About time The derivative of , that is, the rate of change of seepage flow with time; It should be noted that seepage velocity is an important physical quantity that reflects the strength of seepage. Its unit is usually meters per second (m / s) or other length units divided by time units (such as cm / s). The greater the seepage velocity, the longer the distance the fluid travels along the seepage path per unit time, and the more obvious the seepage phenomenon. Seepage rate refers to the volume of fluid passing through a certain cross-sectional area per unit time. Its units are usually cubic meters per second (m³ / s), liters per second (L / s) or cubic meters per day (m³ / d). The magnitude of seepage rate reflects the total amount of fluid flowing in porous media or seepage channels. Time, in units of seconds, minutes, hours, or days, is the independent variable in this formula and is used to describe the change of seepage volume over time. The seepage velocity is determined by taking its derivative. It reflects the changing trend and speed of seepage at a certain moment. The positive or negative value also indicates whether the seepage is increasing or decreasing. The seepage velocity calculated by this derivative is , which can intuitively reflect the velocity and direction of the seepage at that moment; By taking the derivative of the seepage rate, the change rate of the seepage rate over time is calculated, thereby obtaining the seepage velocity, a key seepage characteristic index; It can facilitate a more intuitive understanding of the strength and changing trend of seepage, further improve the monitoring methods of seepage conditions, and enhance the ability to control seepage risks; In the calculation unit, the regular change from the stress at the boundary line to the lower stress is calculated according to the following formula: ;in, The depth of the lower part of the sluice gate is stress at Where, represents the maximum stress in the lower part of the sluice gate, Indicates the total height of the lower half of the sluice gate. Represents the distribution index of stress; In this embodiment, the stress distribution index is related to the structure of the sluice and the load distribution, and usually needs to be determined according to the actual situation. For example, for a uniformly distributed load, You can take about 2; A specific formula is used in the calculation unit to calculate the regular change of stress from the dividing line to the lower stress. The formula takes into account factors such as the maximum stress, total height and stress distribution index in the lower half of the sluice gate to quantify the stress distribution along the depth. This provides a quantitative calculation basis for the stress distribution in the lower half of the sluice gate, helping to more accurately grasp the stress change trend, thereby more scientifically evaluating the stress state of the lower half of the sluice gate and improving the accuracy of safety assessment. Based on the calculated stress fluctuation frequency and seepage velocity, the stress fluctuation frequency when the change from the stress of the dividing line to the lower stress exceeds the risk threshold, and the seepage velocity when the seepage pressure exceeds the critical value are collected, and the stress fluctuation frequency corresponding to the change from the stress of the dividing line to the lower stress exceeds the risk threshold is marked as a reference stress fluctuation frequency, and the seepage velocity corresponding to the seepage pressure exceeds the critical value is marked as a reference seepage velocity. At the same time, the water level corresponding to the reference stress fluctuation frequency and the reference seepage velocity is obtained, and the water level is marked as a reference water level. Based on the reference water level, the stress fluctuation frequency and seepage velocity are obtained when the water level is at half the reference water level. Based on the stress fluctuation frequency and seepage velocity, the stress fluctuation frequency and seepage velocity are analyzed every time the water level increases by 10 cm. The stress fluctuation frequency and seepage velocity are marked as regular stress fluctuation frequency and regular seepage velocity. When the stress fluctuation frequency and seepage velocity of the sluice gate are obtained in the future, when the water level is only half the height of the sluice gate, if the stress fluctuation frequency and seepage velocity are lower than the regular stress fluctuation frequency and regular seepage velocity, the system determines that there is no safety hazard in the sluice gate; otherwise, it determines that there is a safety hazard and issues an early warning. In this embodiment, based on the stress fluctuation frequency and seepage velocity, data corresponding to when the stress at the boundary line exceeds the risk threshold and when the seepage pressure exceeds the critical value is collected and marked as a reference value. At the same time, the corresponding water level height is obtained as a reference. Then, based on the reference water level height, the stress fluctuation frequency and seepage velocity variation patterns at different water levels are analyzed. This is used to compare and evaluate future stress and seepage conditions. If the stress is lower than the regular value, it is determined that there is no hidden danger. Otherwise, an early warning is issued. This embodiment uses reference values ​​and regularity analysis to more dynamically assess the safety status of the sluice gate in combination with water level changes, thereby enhancing the adaptive monitoring and prejudgment capabilities of the sluice gate under different water level conditions, making the early warning more scientific and reasonable. When the system determines that there are no safety hazards in the sluice gate, it obtains the difference in stress fluctuation frequency and seepage velocity between the middle and bottom of the sluice gate under the condition of water level height. The stress fluctuation frequency and seepage velocity at the bottom are the stress fluctuation frequency and seepage velocity of the same horizontal line. At least five stress fluctuation frequencies and seepage velocities are obtained at the bottom, and the average value of the five stress fluctuation frequencies and seepage velocities is calculated. If the average value is greater than the stress fluctuation frequency and seepage velocity in the middle, the system determines that there is a safety hazard in the sluice gate and issues an early warning. In this embodiment, when the system determines that there are no safety hazards in the sluice gate, it further obtains the difference in stress fluctuation frequency and seepage velocity between the middle and bottom of the sluice gate. At least five stress fluctuation frequencies and seepage velocities are obtained at the bottom and the average value is calculated. If the average value is greater than the corresponding value in the middle, it is determined that there is a safety hazard and an early warning is issued. By analyzing the stress fluctuation frequency and seepage velocity differences at different locations of the sluice gate and calculating the average value of the bottom data, we can gain a more comprehensive understanding of the stress and seepage distribution inside the sluice gate, preventing local hidden dangers from being overlooked and further improving the accuracy of safety hazard assessments. When the average value is greater than the stress fluctuation frequency and seepage velocity in the middle, collect 2 to 3 largest stress fluctuation frequencies and seepage velocities from the 5 stress fluctuation frequencies and seepage velocities, and sort the stress fluctuation frequencies and seepage velocities in ascending order. The dangerous parts of the sluice are divided according to the sorting results. In this embodiment, during operation, the sluice gate is affected by a variety of factors, such as the impact of water flow, changes in water level, and temperature, which cause its stress state to constantly change. The stress fluctuation frequency, that is, the number of stress changes per unit time, reflects the dynamic response of the sluice gate structure under the action of these factors. When the stress fluctuation frequency exceeds a certain value, it indicates that the part is under high stress cycle and is prone to the risk of fatigue damage or structural destruction. Therefore, it is of practical significance to sort the stress fluctuation frequency and seepage velocity in ascending order and divide the dangerous parts of the sluice gate according to the sorting results.

[0023] To sum up, this application can monitor stress changes in key parts of the sluice, as well as collect seepage pressure and seepage volume, to obtain more comprehensive and accurate monitoring data, and fuse the data, breaking the limitations of the relative independence of each data in traditional monitoring, realizing mutual verification and supplementation between data, and comprehensively evaluating the safety status of the sluice from multiple dimensions, thereby improving the accuracy and reliability of monitoring.

[0024] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. The intelligent monitoring system for sluice structure stress and seepage is characterized by: include: A stress monitoring module is used to monitor stress changes in the sluice gate, including monitoring stress changes in key parts, such as the piers, gates, and breast walls; Seepage collection module, used to collect the seepage pressure and seepage volume of the sluice; A data processing and analysis module is used to process the stress change, seepage pressure and seepage volume, wherein the processing includes cleaning and correction; and to perform correlation analysis on the processed stress change, seepage pressure and seepage volume; A data fusion processing module is used to fuse the stress and seepage of the sluice gate according to the results of the correlation analysis; the data fusion processing module includes a differentiation unit, a calculation unit and an evaluation and early warning unit; The differentiation unit is used to differentiate the stress of the sluice gate according to the result of the correlation analysis, including differentiating the stress according to the area of ​​the sluice gate and differentiating the stress into upper stress and lower stress; The upper stress and the lower stress correspond to the upper half and the lower half of the sluice gate respectively; The calculation unit is responsive to the differentiation unit and is used to calculate the stress of the sluice gate based on the dividing line between the upper half and the lower half of the sluice gate, including calculating the regular change from the stress of the dividing line to the lower stress; The assessment and early warning unit responds to the calculation unit and is used to preset a risk threshold value regarding the stress; If the change from the stress of the dividing line to the lower stress exceeds the risk threshold, the system determines that there is a safety hazard in the sluice and issues an early warning; Otherwise, no judgment is made; A seepage pressure acquisition module, responsive to the evaluation and early warning unit, for acquiring the seepage pressure of the sluice when the system determines that the sluice has a potential safety hazard, including acquiring the seepage pressure of relevant stress points; And preset the critical value of seepage pressure.

2. The intelligent monitoring system for sluice structure stress and seepage according to claim 1, characterized in that: In the seepage pressure collection module, the relevant stress points include stress points divided by the lower stress, and the division method includes dividing the 3 to 5 largest stress points in the lower stress, and collecting the seepage pressure closest to the 3 to 5 largest stress points. The seepage pressure is the seepage pressure within 10 cm from the 3 to 5 largest stress points. If the seepage pressure exceeds the critical value, the system determines that there is a risk of seepage in the sluice and issues an early warning. Otherwise, no judgment is made.

3. The intelligent monitoring system for sluice structure stress and seepage according to claim 1, characterized in that: In the data processing and analysis module, the processing further includes extracting features of the stress change, seepage pressure, and seepage volume; wherein the feature extraction of the stress change includes extracting the stress peak value, the stress average value, and the stress fluctuation frequency; Feature extraction of seepage pressure and seepage volume, including extraction of pressure change rate and seepage velocity.

4. The intelligent monitoring system for sluice structure stress and seepage according to claim 3, characterized in that: Extracting the stress fluctuation frequency includes calculating the standard deviation of stress at intervals of 5 to 10 minutes, and calculating the frequency according to the following formula: ;in, represents the standard deviation of stress; Where, Indicates the stress, It represents the average value of stress, which is the concentration trend of stress. The calculation formula is: ; Indicates the total number of stresses, which is the sum of the number of stresses collected within 5 to 10 minutes; Represents the square of the difference between each stress and the mean.

5. The intelligent monitoring system for sluice structure stress and seepage according to claim 3, characterized in that: Extracting the seepage velocity includes extracting by calculating the derivative of the seepage rate, which is calculated according to the following formula: ;in, represents the seepage velocity; Where, represents the seepage rate, Indicates time, used to obtain the change of seepage rate over time; Indicates seepage rate About time The derivative of , that is, the rate of change of seepage flow with time.

6. The intelligent monitoring system for sluice structure stress and seepage according to claim 1, characterized in that: In the calculation unit, the regular change from the stress at the boundary line to the lower stress is calculated according to the following formula: ;in, Indicates that the depth in the lower half of the sluice is The stress at ; where, represents the maximum stress in the lower part of the sluice gate, Indicates the total height of the lower part of the sluice gate. Represents the stress distribution index.

7. The intelligent monitoring system for sluice structure stress and seepage according to claim 5, characterized in that: Based on the calculated stress fluctuation frequency and seepage velocity, the stress fluctuation frequency when the change from the stress of the boundary line to the lower stress exceeds the risk threshold, and the seepage velocity when the seepage pressure exceeds the critical value are collected, and the stress fluctuation frequency corresponding to the change from the stress of the boundary line to the lower stress exceeds the risk threshold is marked as a reference stress fluctuation frequency, and the seepage velocity corresponding to the seepage pressure exceeds the critical value is marked as a reference seepage velocity, and at the same time, a water level corresponding to the reference stress fluctuation frequency and the reference seepage velocity is obtained, and the water level is marked as a reference water level; Based on the reference water level, the stress fluctuation frequency and seepage velocity are obtained when the water level is at half the reference water level. Based on the stress fluctuation frequency and seepage velocity, the stress fluctuation frequency and seepage velocity are analyzed every time the water level increases by 10 cm. The stress fluctuation frequency and seepage velocity are marked as regular stress fluctuation frequency and regular seepage velocity. When the stress fluctuation frequency and seepage velocity of the sluice are obtained in the future, if the stress fluctuation frequency and seepage velocity are lower than the regular stress fluctuation frequency and regular seepage velocity when the water level is only half the height of the sluice, the system determines that there is no safety hazard in the sluice. Otherwise, it is determined that there is a safety hazard and an early warning is issued.

8. The intelligent monitoring system for sluice structure stress and seepage according to claim 7, characterized in that: When the system determines that there is no safety hazard in the sluice gate, the difference in stress fluctuation frequency and the difference in seepage velocity between the middle and bottom of the sluice gate are obtained at the water level height, wherein the stress fluctuation frequency and seepage velocity at the bottom are the stress fluctuation frequency and seepage velocity of the same horizontal line, and at least 5 stress fluctuation frequencies and seepage velocities are obtained at the bottom, and the average value of the 5 stress fluctuation frequencies and seepage velocities is calculated. If the average value is greater than the stress fluctuation frequency and seepage velocity in the middle, the system determines that there is a safety hazard in the sluice gate and issues an early warning.

9. The intelligent monitoring system for sluice structure stress and seepage according to claim 8, characterized in that: When the average value is greater than the stress fluctuation frequency and seepage velocity in the middle part, 2 to 3 largest stress fluctuation frequencies and seepage velocities are collected from the 5 stress fluctuation frequencies and seepage velocities, and the stress fluctuation frequencies and seepage velocities are sorted in ascending order, and the dangerous parts of the sluice are divided according to the sorting results.

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