A method and system for early warning of dam safety risks
By analyzing dam monitoring and historical data, and combining them with meteorological forecasts, a damage rate change model was established. This solved the problem of the single indicator deficiency in traditional dam safety risk early warning methods, and enabled dynamic and accurate early warning of dam safety risks.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- ZHONGSHUI ZHIYU (TIANJIN) INFORMATION TECHNOLOGY DEVELOPMENT CO LTD
- Filing Date
- 2026-02-06
- Publication Date
- 2026-05-26
AI Technical Summary
Traditional methods for early warning of dam safety risks rely on a single or few monitoring indicators, which makes it difficult to comprehensively and accurately reflect the actual safety status of the dam.
By analyzing dam monitoring data and historical monitoring data, a correlation model between impact data and damage rate changes is established. Combined with meteorological forecast data, the degree of damage and risk level of local areas of the dam are dynamically predicted. A multi-index comprehensive evaluation method is adopted, including the calculation of damage rate change curves and mixed impact factors.
It enables a more comprehensive and accurate identification of potential risk areas and risk levels of dams, and achieves localized and precise early warning of dam safety.
Smart Images
Figure CN122087532A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of dam safety risk early warning technology, specifically a dam safety risk early warning method and system. Background Technology
[0002] As an important water conservancy project, the safe and stable operation of dams is directly related to the safety of people's lives and property and the stability of the ecological environment downstream. However, dams are affected by a variety of factors during operation, such as natural disasters like floods, earthquakes, and landslides, as well as human factors such as design defects, construction quality, and improper operation and management. All of these factors may pose a threat to the safety of dams.
[0003] However, traditional dam safety risk early warning methods often rely on single or a few monitoring indicators, making it difficult to comprehensively and accurately reflect the actual safety status of the dam. Therefore, in view of the above situation, there is an urgent need to provide a dam safety risk early warning method and system to overcome the shortcomings in current practical applications. Summary of the Invention
[0004] The purpose of this invention is to provide a method and system for early warning of dam safety risks, effectively solving the problems mentioned in the background art.
[0005] This invention is implemented as follows: a method for early warning of dam safety risks, comprising: Acquire dam monitoring data and historical monitoring data; The historical monitoring data is analyzed, and historical impact data that are not within the preset safety range are marked as first impact data; The historical monitoring data is classified according to the data attributes of the first impact data to determine multiple groups of first historical monitoring data; each group of first historical monitoring data is analyzed in turn to determine the first damage rate change curve of the first impact data and the first mixed impact factor k1 of the first impact data with mixed impact, and to determine the comprehensive damage rate change curve of the first impact data. Based on the analysis of the dam monitoring data and historical monitoring data, several areas of interest were identified. Based on preset rules in time interval t n Select multiple time points T n ; The time point T is determined based on the dam monitoring data and meteorological forecast data. n The second impact data for the area of concern is used to determine the damage change value of each second impact data item based on the comprehensive damage rate change curve of the first impact data and the first mixed impact factor k1. The damage change value of the area of concern at time node T is then calculated. n The first damage degree change value Q n ; Based on the change value Q of the first degree of damage n Plot the curve of the change in the first degree of damage and calculate the time interval t. n At the end of the study, focus on the predicted damage rate of the area; The risk level of the area of interest is determined based on the predicted damage rate, and dam safety risk warning is issued based on the risk level of each area of interest.
[0006] As a further aspect of the present invention, the specific steps for classifying the historical monitoring data are as follows: Historical monitoring data are classified based on the type and quantity of first impact data, and historical monitoring data with the same first impact data are grouped into the same group of first historical monitoring data. The steps for determining the first damage rate change curve of the first impact data and the first mixed impact factor k1 of the first impact data with mixed effects are as follows: Analyze the first historical monitoring data that has a single first impact data to determine the first damage rate change curve of the first impact data; Analyze the first historical monitoring data with multiple primary impact data to determine the comprehensive damage rate change curve of multiple primary impact data; The comprehensive damage rate change curve is summed with the first damage rate change curve corresponding to the first impact data to determine the cumulative damage rate change curve. Calculate the curve similarity between the overall damage rate change curve and the cumulative damage rate change curve; When the curve similarity is greater than the preset similarity threshold, there is no mixed influence among multiple first-influence data. Conversely, if there is a mixed influence among multiple primary influence data, the first mixed influence factor k1 can be determined by analyzing the comprehensive damage rate change curve and the cumulative damage rate change curve.
[0007] As a further aspect of the present invention, the specific steps for determining the first mixed influence factor k1 are as follows: Based on the analysis of the overall damage rate change curve, multiple monitoring periods were determined; Multiple sets of corresponding comprehensive damage rates and cumulative damage rates were determined from the comprehensive damage rate change curve and the cumulative damage rate change curve based on multiple monitoring time periods; Calculate the ratio of the overall damage rate to the cumulative damage rate for each group in turn, and determine the average of the ratios as the first mixed influence factor k1.
[0008] As a further aspect of the present invention, the specific steps for determining multiple regions of interest are as follows: By analyzing historical monitoring data, areas where the damage frequency exceeds a preset frequency threshold are identified as the first area. By analyzing dam monitoring data, areas with a damage rate greater than a preset damage rate threshold were identified as the second area. The first and second regions are identified as areas of interest.
[0009] As a further aspect of the present invention: calculating the region of interest at time node T n The first damage degree change value Q n The specific steps are as follows: Based on the analysis of meteorological forecast data, the forecast time interval t n Meteorological data change curves for the area of concern; Based on meteorological forecast data, predict changes in water conditions and plot the time interval t. n Hydrological data change curves for the area of concern; Based on time node T n Multiple secondary impact data were obtained from the change curves of meteorological data and hydrological data; The damage change value of each second impact data item is determined based on the overall damage rate change curve of the first impact data; The damage changes of all the second-impact data are summed to determine the time node T. n The first damage change value Q in the area of concern n ; The first damage degree change value Q n The calculation formula is: ; Among them, Q n For the region of interest at time node T n The first change in the degree of damage, Q a For the damage change value of the second impact data 'a' where there is no mixed effect, Q b and Q c Here, k1 represents the damage change values of the second impact data b and c, which have mixed effects, and k2 represents the damage change value Q. b and Q c The second mixed influence factor.
[0010] As a further aspect of the present invention, it also includes: According to Q b and Q c Analyze historical monitoring data and identify those with the same impact data and the same damage change value as the second historical monitoring data; The first mixing factor k1 is determined as the damage change value Q. b and Q c The second mixed influence factor k2; When no second historical monitoring data exists, the second mixed influence factor k2 is calculated based on the damage change rate corresponding to the first influence data; the formula for calculating the second mixed influence factor k2 is as follows: ; Where k2 is the second mixed influence factor, P b and P c To influence the predicted data for data b and c, and To influence the maximum value of data b and c within a preset safety range, k b and k c These are the factors that influence the predicted data, b and c, respectively.
[0011] As a further aspect of the present invention: calculating the time interval t n The specific steps for determining the predicted damage rate of the area at the end of the survey are as follows: The coordinate axis is set with the establishment time on the horizontal axis and the change in damage level on the vertical axis; According to time node T n The first coordinate data is determined by the corresponding change value Q of the first degree of damage; The first coordinate data is input into the coordinate axes, and curve fitting is performed based on the first coordinate data to determine the region of interest within the time interval t. n The curve showing the change in the first degree of damage within the interior; Calculate the area of the region formed by the curve of the change in the first degree of damage and the coordinate axis, and determine the time interval t. n At the end, focus on the predicted damage rate of the area.
[0012] As a further aspect of the present invention, it also includes: When the time interval t n After completion, the actual damage rate of each area of interest will be obtained through dam monitoring data; The damage rate ratio is obtained by comparing the actual damage rate with the corresponding predicted damage rate. When the damage rate ratio is greater than the preset ratio threshold, the comprehensive damage rate change curve and the first mixed influence factor k1 of the first influence data are updated based on the actual damage rate.
[0013] The present invention also provides a dam safety risk early warning system for implementing the dam safety risk early warning method described above, comprising: The data acquisition module is used to acquire dam monitoring data and historical monitoring data; The first analysis module is used to analyze the historical monitoring data, mark historical impact data that are not within the preset safety range as first impact data; classify the historical monitoring data according to the data attributes of the first impact data, and determine multiple groups of first historical monitoring data; analyze each group of first historical monitoring data in sequence, determine the first damage rate change curve of the first impact data and the first mixed impact factor k1 of the first impact data with mixed impact, and determine the comprehensive damage rate change curve of the first impact data. The area of interest module is used to analyze the dam monitoring data and historical monitoring data to determine multiple areas of interest. The regional damage rate prediction module is used to predict the damage rate within a time interval t based on preset rules. n Select multiple time points T n The time point T is determined based on the dam monitoring data and meteorological forecast data. n The damage change value of each second impact data item is determined based on the comprehensive damage rate change curve of the first impact data and the first mixed impact factor k1 of the first impact data where mixed effects exist, for the second impact data of the area of concern. The damage change value of each second impact data item is then calculated for the area of concern at time node T. n The first damage degree change value Q n According to the region of interest at time node T n The first damage degree change value Q n Plot the curve of the change in the first degree of damage and calculate the time interval t. n At the end of the study, focus on the predicted damage rate of the area; The risk warning module is used to determine the risk level of the area of concern based on the predicted damage rate, and to provide dam safety risk warnings based on the risk level of each area of concern.
[0014] The present invention also provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the dam safety risk early warning method described above.
[0015] Compared with the prior art, the beneficial effects of the present invention are as follows: By analyzing historical monitoring data to establish correlation models between various impact data and damage rate changes (such as damage rate change curves and mixed impact factors), and combining real-time monitoring data with meteorological forecast data, this method dynamically predicts and assesses the degree of damage to local areas (areas of concern) of the dam within a specific future time interval. This method can more comprehensively and accurately identify potential risk areas of the dam and their risk levels, achieving precise local early warning for dam safety. Attached Figure Description
[0016] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.
[0017] Figure 1 A flowchart of a dam safety risk early warning method provided by the present invention; Figure 2 The first damage degree change value Q provided by the present invention n A flowchart of the calculation method; Figure 3 A flowchart illustrating the calculation method for the second mixed influence factor k2 provided by the present invention; Figure 4 A block diagram of a dam safety risk early warning system provided by the present invention. Detailed Implementation
[0018] The technical solution of the present invention will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.
[0019] The present invention will be further explained below with reference to specific embodiments.
[0020] like Figure 1 As shown, this invention discloses a method for early warning of dam safety risks, comprising: S102, acquire dam monitoring data and historical monitoring data; S104, Analyze historical monitoring data and mark historical impact data that are not within the preset safety range as first impact data; S106, classify historical monitoring data according to the data attributes of the first impact data, and determine multiple groups of first historical monitoring data; analyze each group of first historical monitoring data in turn, determine the first damage rate change curve of the first impact data and the first mixed impact factor k1 of the first impact data with mixed impact, and determine the comprehensive damage rate change curve of the first impact data. S108, based on the analysis of dam monitoring data and historical monitoring data, identified multiple areas of concern; S110, based on preset rules in time interval t n Select multiple time points T n ; S112, determine the time node T based on dam monitoring data and meteorological forecast data. n The damage change value of each second impact data item is determined based on the comprehensive damage rate change curve of the first impact data and the first mixed impact factor k1 of the first impact data where mixed effects exist, for the second impact data of the area of concern. The damage change value of each second impact data item is then calculated for the area of concern at time node T. n The first damage degree change value Q n ; S114, based on the region of interest at time node T n The first damage degree change value Q n Plot the curve of the change in the first degree of damage and calculate the time interval t. n At the end of the study, focus on the predicted damage rate of the area; S116. Determine the risk level of the area of concern based on the predicted damage rate, and conduct dam safety risk warning based on the risk level of each area of concern.
[0021] In embodiments of the present invention, dam monitoring data is acquired through monitoring equipment and sensors installed around the dam and reservoir. The dam monitoring data includes the damage rate of each area of the dam and the impact data affecting the change of the dam damage rate. The impact data includes meteorological data (such as temperature, humidity, sunshine, precipitation, etc.) and hydrological data (such as water level, water flow velocity, etc.). Historical monitoring data consists of dam monitoring data obtained during historical monitoring processes and the damage rate of each area of the dam at the corresponding data acquisition time.
[0022] Each data point has a corresponding preset safety range. When the data point falls within the preset safety range, its impact on dam damage is ignored and considered to have no effect. When the data point exceeds the maximum value of the preset safety range, it accelerates the rate of dam damage. The preset safety range is set by those skilled in the art based on actual needs.
[0023] By analyzing historical monitoring data, and by comparing the actual data when each influencing data exceeds the preset safety range with the corresponding damage rate changes over the time period used to represent the degree of dam damage, the extent of damage rate change of each influencing data under different values is determined, and the first damage rate change curve of the first influencing data is plotted. When multiple primary impact data exist within the historical monitoring data, the cumulative damage rate change curve is obtained by comparing the overall damage rate change curve and the cumulative damage rate change curve obtained by summing the primary damage rate change curves of each primary impact data. This determines whether there is a mixed impact among the multiple primary impact data, such as accelerating dam damage. If mutual influence exists, the primary mixed impact factor k1 of the multiple primary impact data in that group is calculated. The primary damage rate change curve of each primary impact data and the primary damage rate change curve of each primary impact data in each group are recorded and saved in the database.
[0024] By using historical monitoring data and dam monitoring data, areas with high dam damage frequency and high damage rate at the current time were identified and designated as areas of concern. Impact data (including meteorological and hydrological data) of the areas of concern were predicted using meteorological data, and each impact data point was plotted over the time interval t. n Impact data change curves (including meteorological data change curves and hydrological data change curves), based on the system's preset time interval from time interval t n Select multiple time points T n , for each time point T n Impact data that is not within the preset safety range is marked as second impact data. The mixed impact relationship between the second impact data is determined based on the mixed impact relationship between the first impact data in the database and the first damage rate change curve of each first impact data point. The time node T for each second impact data point is also considered. n The damage change value is calculated at time point T using a system preset formula. n The first damage degree change value Q n Based on the time interval t n All time nodes T n and the corresponding change value Q of the first degree of damage n Plot the curve of the change in the first degree of damage, with the time interval t n The area formed by the curves of change in the start time, end time, and first degree of damage, along with the coordinate axes, is used to determine the predicted damage rate of the region of interest.
[0025] Based on the dam damage rate, the areas of concern can be divided into four risk levels. Each risk level corresponds to a different range of dam damage rates; the higher the risk level, the higher the corresponding dam damage rate. By providing regional early warnings for dams based on the risk level of each area of concern, management personnel can better manage dam maintenance and risk control.
[0026] In an embodiment of the present invention, historical monitoring data is classified according to the data attributes of the first impact data to determine multiple sets of first historical monitoring data; each set of first historical monitoring data is analyzed sequentially to determine the first damage rate change curve of the first impact data and the first mixed impact factor k1 of the first impact data with mixed impact, including: Historical monitoring data are classified based on the type and quantity of first impact data, and historical monitoring data with the same first impact data are grouped into the same group of first historical monitoring data. Analyze the first historical monitoring data that has a single first impact data to determine the first damage rate change curve of the first impact data; Analyze the first historical monitoring data with multiple primary impact data to determine the comprehensive damage rate change curve of multiple primary impact data; The overall damage rate change curve is summed with the first damage rate change curve corresponding to the first impact data to determine the cumulative damage rate change curve. Calculate the similarity between the overall damage rate change curve and the cumulative damage rate change curve; When the curve similarity is greater than the preset similarity threshold, there is no mixed influence among multiple first-influence data; otherwise, there is a mixed influence among multiple first-influence data. The first mixed influence factor k1 is determined by analyzing the comprehensive damage rate change curve and the cumulative damage rate change curve.
[0027] It should be noted that the data attributes of the first impact data include the data type and quantity of the first impact data. By analyzing historical monitoring data, historical monitoring data with the same type and quantity of first impact data are identified as the same group of first historical monitoring data. Priority is given to analyzing the first historical monitoring data containing only a single first impact data to determine the correspondence between the specific value of the first impact data and the change in the damage rate of the corresponding dam damage (such as deformation, landslide, subsidence, cracks, etc.) during the duration of the first impact data, and to plot the first damage rate change curve of the first impact data. The remaining first historical monitoring data are analyzed in ascending order of the first impact data to determine the comprehensive damage rate change curve of multiple first impact data. By summing the first damage rate change curves corresponding to each first impact data, curve similarity calculation is performed on the cumulative damage rate change curve to determine whether there is a mixed impact among the multiple first impact data in this group. The first mixed impact factor k1 is determined by the relationship between the comprehensive damage rate change curve and the cumulative damage rate change curve.
[0028] The preset similarity threshold is set by those skilled in the art according to actual needs.
[0029] In an embodiment of the present invention, the first mixed influence factor k1 is determined by analyzing the combined damage rate change curve and the cumulative damage rate change curve, including: Based on the analysis of the overall damage rate change curve, multiple monitoring periods were determined; Multiple sets of corresponding comprehensive damage rates and cumulative damage rates were determined from the comprehensive damage rate change curve and the cumulative damage rate change curve based on multiple monitoring time periods; Calculate the ratio of the overall damage rate to the cumulative damage rate for each group in turn, and determine the average of the ratios as the first mixed influence factor k1.
[0030] It should be noted that the monitoring time can be selected based on the system's preset time interval, or the time corresponding to the peak and trough of the overall damage rate change curve can be determined as the monitoring time. After extracting the overall damage rate and cumulative damage rate, the overall damage rate and cumulative damage rate are paired according to the monitoring time, and the ratio of the overall damage rate and cumulative damage rate for each group is calculated. The average value of the ratio is determined by calculating the arithmetic mean or weighted arithmetic mean, thereby determining the first mixed influence factor k1 of the multiple first influence data in that group.
[0031] In embodiments of the present invention, multiple areas of interest are identified through analysis of dam monitoring data and historical monitoring data, including: By analyzing historical monitoring data, areas where the damage frequency exceeds a preset frequency threshold are identified as the first area. By analyzing dam monitoring data, areas with a damage rate greater than a preset damage rate threshold were identified as the second area. The first and second regions are identified as areas of interest.
[0032] It should be noted that by analyzing historical monitoring data, the frequency of damage to various locations and areas of the dam within a unit of time (e.g., per year) is determined, and areas with higher damage frequencies are designated as the first zone. Further analysis of dam monitoring data identifies areas showing partial damage or damage trends (e.g., deformation amplitude, crack size, or settlement amplitude not meeting the damage assessment criteria) as the second zone. The first and second zones are then designated as areas of concern, and the dam's safety risk level is determined by predicting the damage rate in these areas.
[0033] The preset frequency threshold and preset damage rate threshold are set by those skilled in the art according to actual needs.
[0034] like Figure 2 As shown, in an embodiment of the present invention, time node T is determined based on dam monitoring data combined with meteorological forecast data. nThe damage change value of each second impact data item is determined based on the comprehensive damage rate change curve of the first impact data and the first mixed impact factor k1 of the first impact data where mixed effects exist, for the second impact data of the area of concern. The damage change value of each second impact data item is then calculated for the area of concern at time node T. n The first damage degree change value Q n ,include: S202, based on meteorological forecast data analysis, the forecast time interval t n Meteorological data change curves for the area of concern; S204, Based on meteorological forecast data, predict changes in water conditions and plot the time interval t. n Hydrological data change curves for the area of concern; S206, based on time node T n Multiple secondary impact data were obtained from the change curves of meteorological data and hydrological data; S208, Determine the damage change value of each second impact data based on the comprehensive damage rate change curve of the first impact data; S210, sum up the damage changes of all the second impact data to determine the time node T. n The first damage change value Q in the area of concern n ; The calculation method for the change in the first degree of damage is expressed by the formula: ; Among them, Q n For the region of interest at time node T n The first change in the degree of damage, Q a For the damage change value of the second impact data 'a' where there is no mixed effect, Q b and Q c Here, k1 represents the damage change values of the second impact data b and c, which have mixed effects, and k2 represents the damage change value Q. b and Q c The second mixed influence factor.
[0035] It should be noted that meteorological forecast data for the reservoir area was obtained through the internet and other means, and was processed according to the time interval t. n The system plots meteorological data change curves for each meteorological data item (such as temperature, humidity, precipitation, etc.) based on the domestic meteorological forecast data. By default, the hydrological data change curves for each area of interest are the same.
[0036] Hydrological change data includes changes in reservoir water levels and water levels upstream of the reservoir. The time interval t is determined using meteorological forecast data. nBased on the changing data of the reservoir's internal and upstream water conditions, hydrological data change curves for various reservoir parameters (such as water level and flow velocity) are determined. Furthermore, based on the location of each area of interest and the reservoir's overall hydrological data, a hydrological data change curve for each area of interest is determined. This is based on time node T. n Meteorological data w is determined from meteorological data change curves and hydrological data change curves. n and water situation data w m Meteorological data that is not within the preset safe range will be included. n and water situation data w m This is identified as the second influencing data. The second influencing data is then input into the overall damage rate change curve of the first influencing data, which shares the same data attributes, to determine the damage change value of the second influencing data.
[0037] During the process of accumulating the damage change values of the second impact data, the second impact data with mixed effects are determined as a whole for calculation, and the second mixed impact factor k2 is determined based on the data attributes of the second impact data with mixed effects.
[0038] The formula uses the example of second-influence data a, b, and c, where second-influence data b and c have a mixed influence. Q a It can represent the sum of damage changes of multiple second-effect data that do not have mixed effects. For example, when there are three second-effect data x, y, and z that do not have mixed effects, Q in the formula can be used to represent the sum of damage changes. a Replace with Q x +Q y +Q z Similarly, the second impact data with mixed effects is not limited to two types, b and c. b and c are modified and replaced according to the number of multiple first impact data in each group. It is also not limited to the existence of only one group of second impact data with mixed effects; each group of second impact data has a corresponding second mixed impact factor.
[0039] like Figure 3 As shown, in an embodiment of the present invention, it further includes: S302, based on the damage change value Q of the second impact data b and c. b and Q c Analyze historical monitoring data and identify those with the same impact data and the same damage change value as the second historical monitoring data; S304. The first mixing factor k1 of the second historical monitoring data is determined as the damage change value Q. b and Q c The second mixed influence factor k2; S306, When there is no second historical monitoring data, calculate the second mixed influence factor k2 based on the damage change rate of the corresponding first influence data; ; Where k2 is the second mixed influence factor, P b and P c To influence the predicted data for data b and c, and To influence the maximum value of data b and c within a preset safety range, k b and k c These are the factors that influence the predicted data, b and c, respectively.
[0040] It should be noted that there can be two or more second impact data. Taking b and c as examples of second impact data, the second historical monitoring data consists of only two impact data, b and c, that are not within the preset safety range, and the damage change values of impact data b and c are Q respectively. b and Q c Historical monitoring data. When second historical monitoring data exists, the first mixed influence factor k1 of the second historical monitoring data can be determined as the damage change value Q. b and Q c The second mixed influence factor k2 is determined by multiplying the ratio of each second influence data point to the maximum data point within the corresponding preset safety range with the influence factor of the corresponding predicted data. The results are then summed to determine the second mixed influence factor k2. The larger the predicted data point of the second influence data, the larger its corresponding influence factor. The influence factor ranges from 0 to 1.
[0041] In an embodiment of the present invention, based on the region of interest at time node T n The first damage degree change value Q n Plot the curve of the change in the first degree of damage and calculate the time interval t. n At the end, focus on the predicted damage rate of the area, including: The coordinate axis is set with the establishment time on the horizontal axis and the change in damage level on the vertical axis; According to time node T n The first coordinate data is determined by the corresponding change value Q of the first degree of damage; Input the first coordinate data into the coordinate axis, and perform curve fitting based on the first coordinate data to determine the region of interest within the time interval t. n The curve showing the change in the first degree of damage within the interior; Calculate the area of the region formed by the curve of the change in the first degree of damage and the coordinate axis, and combine it with the time interval t. nThe initial damage rate of the area of interest is monitored at the start time, and the time interval t is determined. n End time focuses on the predicted damage rate of the area.
[0042] It should be noted that the x-axis of the first coordinate data is the time node T. n The vertical axis represents the corresponding change in the first degree of damage, Q. After inputting all the first coordinate data into the coordinate axis, curve fitting is performed on the first coordinate data using methods such as least squares to obtain a smooth curve representing the data points corresponding to the first coordinate data, i.e., the curve of the change in the first degree of damage. This is achieved by calculating the time interval t. n The area of interest is determined by the curves showing the changes in start time, end time, and the first degree of damage, along with the area formed by the coordinate axes. n The change in damage rate, and its relationship with the time interval t n The initial damage rates of the areas of interest at the start time are summed to determine the time interval t. n End time focuses on the predicted damage rate of the area.
[0043] In embodiments of the present invention, it further includes: When the time interval t n After completion, the actual damage rate of each area of interest will be obtained through dam monitoring data; The damage rate ratio is obtained by comparing the actual damage rate with the corresponding predicted damage rate. When the damage rate ratio is greater than the preset ratio threshold, the comprehensive damage rate change curve and the first mixed influence factor k1 of the first influence data are updated based on the actual damage rate.
[0044] It should be noted that when the time interval t n After completion, the prediction results are verified by comparing the actual damage rate with the corresponding predicted damage rate. If the damage rate ratio exceeds a preset threshold, an error is determined between the prediction result and the actual data. This error is then determined based on the actual damage rate of the area of interest and the time interval t. n The monitoring data of various dams, combined with historical monitoring data over a certain period of time, are used to update the comprehensive damage rate change curve and the first mixed influence factor k1 of each primary impact data in the current area of concern.
[0045] The preset ratio threshold is set by those skilled in the art according to actual needs.
[0046] like Figure 4 As shown, a second aspect of the present invention provides a dam safety risk early warning system, comprising: The data acquisition module is used to acquire dam monitoring data and historical monitoring data; The first analysis module is used to analyze historical monitoring data, mark historical impact data that are not within the preset safety range as first impact data; classify historical monitoring data according to the data attributes of the first impact data to determine multiple groups of first historical monitoring data; analyze each group of first historical monitoring data in turn to determine the first damage rate change curve of the first impact data and the first mixed impact factor k1 of the first impact data with mixed impact. The area of interest module is used to analyze dam monitoring data and historical monitoring data to identify multiple areas of interest. The regional damage rate prediction module is used to predict the damage rate within a time interval t based on preset rules. n Select multiple time points T n The time point T is determined based on dam monitoring data and meteorological forecast data. n The damage change value of each second impact data item is determined based on the comprehensive damage rate change curve of the first impact data and the first mixed impact factor k1 of the first impact data where mixed effects exist, for the second impact data of the area of concern. The damage change value of each second impact data item is then calculated for the area of concern at time node T. n The first damage degree change value Q n Based on the region of interest at time node T n The first damage degree change value Q n Plot the curve of the change in the first degree of damage and calculate the time interval t. n At the end of the study, focus on the predicted damage rate of the area; The risk warning module is used to determine the risk level of the area of concern based on the predicted damage rate, and to provide dam safety risk warnings based on the risk level of each area of concern.
[0047] A third aspect of the present invention provides a computer-readable storage medium including a dam safety risk early warning method program, wherein when the dam safety risk early warning method program is executed by a processor, it implements the steps of the dam safety risk early warning method as described above.
[0048] All information (including but not limited to user equipment information, user personal information, etc.), data (including but not limited to data used for analysis, stored data, displayed data, etc.), and signals (including but not limited to signals transmitted between user terminals and other devices) involved in this application have been authorized by the user or fully authorized by all parties, and the collection, use, and processing of related data must comply with the relevant laws, regulations, and standards of the relevant countries and regions. For example, the "dam monitoring data" and "historical monitoring data" involved in this disclosure were obtained under full authorization.
[0049] This invention discloses a method and system for early warning of dam safety risks. The method includes: acquiring dam monitoring data and historical monitoring data; determining multiple sets of first historical monitoring data based on first impact data in the historical monitoring data, determining the first damage rate change curve of the first impact data and the first mixed impact factor of the first impact data with mixed impact; and determining the time node T based on the dam monitoring data and meteorological forecast data. n The second impact data for the area of interest is used to calculate the damage change value of the second impact data, and to determine the first damage degree change value Q for the area of interest. n This invention plots a curve showing the change in the first degree of damage, calculates the predicted damage rate for the area of interest, determines the risk level of the area of interest, and provides early warning of dam safety risks. Based on meteorological and water source data, this invention predicts the degree of damage to various areas of the dam, conducts local risk assessments of the dam, and achieves precise early warning.
[0050] In the several embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are merely illustrative. For example, the division of units is only a logical functional division, and in actual implementation, there may be other division methods, such as: multiple units or components can be combined, or integrated into another system, or some features can be ignored or not executed. In addition, the coupling, direct coupling, or communication connection between the various components shown or discussed can be through some interfaces, and the indirect coupling or communication connection between devices or units can be electrical, mechanical, or other forms.
[0051] The units described above as separate components may or may not be physically separate. The components shown as units may or may not be physical units. They may be located in one place or distributed across multiple network units. Some or all of the units may be selected to achieve the purpose of this embodiment according to actual needs.
[0052] In addition, in the various embodiments of the present invention, each functional unit can be integrated into one processing unit, or each unit can be a separate unit, or two or more units can be integrated into one unit; the integrated unit can be implemented in hardware or in the form of hardware plus software functional units.
[0053] Those skilled in the art will understand that all or part of the steps of the above method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When the program is executed, it performs the steps of the above method embodiments. The aforementioned storage medium includes various media capable of storing program code, such as mobile storage devices, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.
[0054] Alternatively, if the integrated units of this invention are implemented as software functional modules and sold or used as independent products, they can also be stored in a computer-readable storage medium. Based on this understanding, the technical solutions of the embodiments of this invention, or the parts that contribute to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the methods described in the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as mobile storage devices, ROM, RAM, magnetic disks, or optical disks.
Claims
1. A method for early warning of dam safety risks, characterized in that, include: Acquire dam monitoring data and historical monitoring data; The historical monitoring data is analyzed, and historical impact data that are not within the preset safety range are marked as first impact data; The historical monitoring data is classified according to the data attributes of the first impact data to determine multiple groups of first historical monitoring data; each group of first historical monitoring data is analyzed in turn to determine the first damage rate change curve of the first impact data and the first mixed impact factor k1 of the first impact data with mixed impact, and to determine the comprehensive damage rate change curve of the first impact data. Based on the analysis of the dam monitoring data and historical monitoring data, several areas of interest were identified. Based on preset rules in time interval t n Select multiple time points T n ; The time point T is determined based on the dam monitoring data and meteorological forecast data. n The second impact data for the area of concern is used to determine the damage change value of each second impact data item based on the comprehensive damage rate change curve of the first impact data and the first mixed impact factor k1. The damage change value of the area of concern at time node T is then calculated. n The first damage degree change value Q n ; Based on the change value Q of the first degree of damage n Plot the curve of the change in the first degree of damage and calculate the time interval t. n At the end of the study, focus on the predicted damage rate of the area; The risk level of the area of interest is determined based on the predicted damage rate, and dam safety risk warning is issued based on the risk level of each area of interest.
2. The dam safety risk early warning method according to claim 1, characterized in that, The specific steps for classifying the historical monitoring data are as follows: Historical monitoring data are classified based on the type and quantity of first impact data, and historical monitoring data with the same first impact data are grouped into the same group of first historical monitoring data. The steps for determining the first damage rate change curve of the first impact data and the first mixed impact factor k1 of the first impact data with mixed effects are as follows: Analyze the first historical monitoring data that has a single first impact data to determine the first damage rate change curve of the first impact data; Analyze the first historical monitoring data with multiple primary impact data to determine the comprehensive damage rate change curve of multiple primary impact data; The comprehensive damage rate change curve is summed with the first damage rate change curve corresponding to the first impact data to determine the cumulative damage rate change curve. Calculate the curve similarity between the overall damage rate change curve and the cumulative damage rate change curve; When the curve similarity is greater than the preset similarity threshold, there is no mixed influence among multiple first-influence data. Conversely, if there is a mixed influence among multiple primary influence data, the first mixed influence factor k1 can be determined by analyzing the comprehensive damage rate change curve and the cumulative damage rate change curve.
3. The dam safety risk early warning method according to claim 2, characterized in that, The specific steps to determine the first mixed influence factor k1 are as follows: Based on the analysis of the overall damage rate change curve, multiple monitoring periods were determined; Multiple sets of corresponding comprehensive damage rates and cumulative damage rates were determined from the comprehensive damage rate change curve and the cumulative damage rate change curve based on multiple monitoring time periods; Calculate the ratio of the overall damage rate to the cumulative damage rate for each group in turn, and determine the average of the ratios as the first mixed influence factor k1.
4. The dam safety risk early warning method according to claim 1, characterized in that, The specific steps for identifying multiple regions of interest are as follows: By analyzing historical monitoring data, areas where the damage frequency exceeds a preset frequency threshold are identified as the first area. By analyzing dam monitoring data, areas with a damage rate greater than a preset damage rate threshold were identified as the second area. The first and second regions are identified as areas of interest.
5. The dam safety risk early warning method according to claim 1, characterized in that, Calculate the region of interest at time node T n The first damage degree change value Q n The specific steps are as follows: Based on the analysis of meteorological forecast data, the forecast time interval t n Meteorological data change curves for the area of concern; Based on meteorological forecast data, predict changes in water conditions and plot the time interval t. n Hydrological data change curves for the area of concern; Based on time node T n Multiple secondary impact data were obtained from the change curves of meteorological data and hydrological data; The damage change value of each second impact data item is determined based on the overall damage rate change curve of the first impact data; The damage changes of all the second-impact data are summed to determine the time node T. n The first damage change value Q in the area of concern n ; The first damage degree change value Q n The calculation formula is: ； Among them, Q n For the region of interest at time node T n The first change in the degree of damage, Q a For the damage change value of the second impact data 'a' where there is no mixed effect, Q b and Q c Here, k1 represents the damage change values of the second impact data b and c, which have mixed effects, and k2 represents the damage change value Q. b and Q c The second mixed influence factor.
6. The dam safety risk early warning method according to claim 5, characterized in that, Also includes: According to Q b and Q c Analyze historical monitoring data and identify those with the same impact data and the same damage change value as the second historical monitoring data; The first mixing factor k1 is determined as the damage change value Q. b and Q c The second mixed influence factor k2; When no second historical monitoring data exists, the second mixed influence factor k2 is calculated based on the damage change rate corresponding to the first influence data; the formula for calculating the second mixed influence factor k2 is as follows: ； Where k2 is the second mixed influence factor, P b and P c To influence the predicted data for data b and c, and To influence the maximum value of data b and c within a preset safety range, k b and k c These are the factors that influence the predicted data, b and c, respectively.
7. The dam safety risk early warning method according to claim 1, characterized in that, Calculate the time interval t n The specific steps for determining the predicted damage rate of the area at the end of the survey are as follows: The coordinate axis is set with the establishment time on the horizontal axis and the change in damage level on the vertical axis; According to time node T n The first coordinate data is determined by the corresponding change value Q of the first degree of damage; The first coordinate data is input into the coordinate axes, and curve fitting is performed based on the first coordinate data to determine the region of interest within the time interval t. n The curve showing the change in the first degree of damage within the interior; Calculate the area of the region formed by the curve of the change in the first degree of damage and the coordinate axis, and determine the time interval t. n At the end, focus on the predicted damage rate of the area.
8. The dam safety risk early warning method according to claim 1, characterized in that, Also includes: When the time interval t n After completion, the actual damage rate of each area of interest will be obtained through dam monitoring data; The damage rate ratio is obtained by comparing the actual damage rate with the corresponding predicted damage rate. When the damage rate ratio is greater than the preset ratio threshold, the comprehensive damage rate change curve and the first mixed influence factor k1 of the first influence data are updated based on the actual damage rate.
9. A dam safety risk early warning system, used to implement the dam safety risk early warning method as described in any one of claims 1-8, characterized in that, include: The data acquisition module is used to acquire dam monitoring data and historical monitoring data; The first analysis module is used to analyze the historical monitoring data, mark historical impact data that are not within the preset safety range as first impact data; classify the historical monitoring data according to the data attributes of the first impact data, and determine multiple groups of first historical monitoring data; analyze each group of first historical monitoring data in sequence, determine the first damage rate change curve of the first impact data and the first mixed impact factor k1 of the first impact data with mixed impact, and determine the comprehensive damage rate change curve of the first impact data. The area of interest module is used to analyze the dam monitoring data and historical monitoring data to determine multiple areas of interest. The regional damage rate prediction module is used to predict the damage rate within a time interval t based on preset rules. n Select multiple time points T n The time point T is determined based on the dam monitoring data and meteorological forecast data. n The damage change value of each second impact data item is determined based on the comprehensive damage rate change curve of the first impact data and the first mixed impact factor k1 of the first impact data where mixed effects exist, for the second impact data of the area of concern. The damage change value of each second impact data item is then calculated for the area of concern at time node T. n The first damage degree change value Q n According to the region of interest at time node T n The first damage degree change value Q n Plot the curve of the change in the first degree of damage and calculate the time interval t. n At the end of the study, focus on the predicted damage rate of the area; The risk warning module is used to determine the risk level of the area of concern based on the predicted damage rate, and to provide dam safety risk warnings based on the risk level of each area of concern.
10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements the dam safety risk early warning method as described in any one of claims 1 to 8.