Dam monitoring and early warning method based on Beidou remote sensing data

Abstract

The present invention discloses a dam monitoring and early warning method based on Beidou remote sensing data. The present invention realizes comprehensive monitoring of dam deformation and hydrological data through Beidou remote sensing data, further comprehensively analyzes multi-source data of dam displacement, cracks and water level changes, constructs a comprehensive risk assessment model, and intelligently triggers early warnings based on the risk assessment model, thereby improving the accuracy and response speed of early warnings. The present invention solves the problems in the prior art of relying on manual inspections, mostly focusing on single deformation data analysis, lacking comprehensive assessment of cracks and hydrological multi-source data, and causing one-sided monitoring and low early warning accuracy.

Description

Technical Field

[0001] The present invention relates to the technical field of dam safety monitoring, and in particular to a dam monitoring and early warning method based on Beidou remote sensing data. Background Art

[0002] As a key water conservancy engineering facility, the dam undertakes important functions such as flood control, power generation, irrigation and water resource allocation; its safety is directly related to the ecological balance and economic development of the region; therefore, the construction of a dam safety monitoring and early warning system is particularly important.

[0003] However, the dam monitoring and early warning methods in the prior art still have the following shortcomings:

[0004] Relying on manual inspections, and mostly focusing on single deformation data analysis, lacking comprehensive evaluation of fracture and hydrological multi-source data, the monitoring is one-sided and leads to low early warning accuracy;

[0005] At the same time, the warning cannot be updated and optimized in real time, and the degree of intelligence is low.

[0006] To this end, a dam monitoring and early warning method based on Beidou remote sensing data was introduced. Summary of the invention

[0007] In view of this, the present invention provides a dam monitoring and early warning method based on Beidou remote sensing data to solve the problems raised by the above background technology.

[0008] The purpose of the present invention can be achieved by the following technical solution: A dam monitoring and early warning method based on Beidou remote sensing data, comprising:

[0009] Data collection: Set the data collection time interval for dam monitoring. After the set data collection time interval is reached, collect the remote sensing data of the dam at the current time point;

[0010] Data processing: pre-processing the remote sensing data of the dam at the current time point;

[0011] Feature extraction: Extract deformation data and hydrological data from preprocessed remote sensing data;

[0012] Risk assessment: Analyze the extracted deformation data and hydrological data to construct a risk assessment model for the dam at the current time point;

[0013] Trigger warning: Based on the risk assessment model constructed for the dam at the current time point, the safety status of the dam at the current time point is assessed. If the assessment result generates a warning, the pre-installed warning device is triggered to issue a warning;

[0014] Information release: When issuing a warning, the warning information will be released to the management department and the public through the preset channels in a timely manner;

[0015] Early warning optimization: Establish a feedback mechanism to update and optimize the early warning triggers of the dam.

[0016] In some embodiments, the extracted deformation data is analyzed, specifically:

[0017] Extract the horizontal and vertical displacement data of each monitoring point pre-deployed on the dam surface from the deformation data of the dam, compare the monitoring data at the current time point with the monitoring data at the previous time point, and calculate the horizontal and vertical displacement of each monitoring point;

[0018] The displacement rate of the horizontal displacement of each monitoring point is recorded as the horizontal rate, which is calculated by dividing the horizontal displacement of the corresponding monitoring point by the time interval between two time points; similarly, the displacement rate of the vertical displacement of each monitoring point is recorded as the vertical rate;

[0019] Preset the rate value ranges of each group corresponding to the horizontal rate and the vertical rate respectively, and set the rate value range corresponding to each group of the horizontal rate and the vertical rate to correspond to a horizontal hidden danger value and a vertical hidden danger value respectively;

[0020] The horizontal rate and vertical rate of each monitoring point are matched with the corresponding preset rate value ranges of each group, so as to obtain the horizontal hidden danger value and vertical hidden danger value corresponding to each monitoring point;

[0021] The horizontal hidden danger value and the vertical hidden danger value of the corresponding monitoring point are accumulated, and the accumulated result is used as the displacement hidden danger value of the corresponding monitoring point.

[0022] In some embodiments, analyzing the extracted deformation data further includes:

[0023] Set the maximum allowable value of the displacement hidden danger value; compare the displacement hidden danger value of each monitoring point with the set maximum allowable value one by one. If the displacement hidden danger value of a group of monitoring points is greater than the set maximum allowable value, mark the displacement hidden danger value of the group of monitoring points as an abnormal displacement point;

[0024] Count the number of abnormal displacement points of the dam at the current time point, recorded as the number of abnormal points , calculate the mean of the displacement hidden danger values ​​corresponding to each group of abnormal displacement points, and record it as the abnormal mean ;

[0025] According to the formula , the number of abnormal points of the dam at the current time point and abnormal mean Perform weighted calculation to obtain the displacement assessment index of the dam at the current time point ;in The number of abnormal points The corresponding preset maximum allowed points, Indicates the preset maximum allowable value corresponding to the displacement hidden danger value; and The number of abnormal points and abnormal mean The weight factor of influence.

[0026] In some embodiments, analyzing the extracted deformation data further includes:

[0027] Extract crack data from the deformation data of the dam; count the number of cracks in the dam at the current time point, and obtain the length and width of each group of cracks, respectively preset the numerical value ranges of each group of crack length and crack width, and set the numerical value ranges corresponding to each group of crack length and crack width to correspond to a length hidden danger value and a width hidden danger value respectively;

[0028] The length and width of the corresponding crack are matched with the corresponding preset value ranges of each group of values, so as to obtain the length hidden danger value and width hidden danger value of the corresponding crack;

[0029] The length hazard value and width hazard value of the corresponding crack are accumulated, and the accumulated result is used as the risk assessment value of the corresponding crack; the dam is divided into regions; after the risk assessment value of each group of cracks is obtained, the regions of each group of cracks are matched according to the location of each group of cracks in the dam; and a weight coefficient is set for each region;

[0030] The risk assessment value of each group of cracks is multiplied by the corresponding set weight coefficient, and then the sum is obtained to obtain the crack assessment index of the dam at the current time point. .

[0031] In some embodiments, the extracted hydrological data is analyzed, specifically:

[0032] Extract water level data from the hydrological data of the dam, take the dam water level data at the current time point as the reference value, obtain the water level change data of the dam within a set time period before the current time point, and extract the water level data of the dam at different time points within the set time period as the trend value;

[0033] Construct a line graph of the water level change of the dam at the current time point with the reference value and multiple groups of trend values, draw the numerical points corresponding to the reference value and multiple groups of trend values ​​in the line graph, and connect the adjacent numerical points to obtain the water level line; calculate the slope of each group of water level lines and the angle with the horizontal line. If the angle between one group of water level lines and the horizontal line is an obtuse angle, mark the slope of the group of water level lines as an upward slope; if the angle between one group of water level lines and the horizontal line is an acute angle, mark the slope of the group of water level lines as a downward slope;

[0034] Sum up all the rising slopes and falling slopes respectively to obtain the rising estimate and the falling estimate; calculate the ratio between the rising estimate and the falling estimate as the water level change value of the dam at the current time point;

[0035] The reference water level data of the dam water level at the current time point is preset, and the threshold line corresponding to the reference water level data is drawn in the line graph, and the numerical points above the threshold line are marked as the abnormal water level points of the dam at the current time point; and each group of abnormal water level points is used as the starting point, and the vertical lines between each group of starting points and the threshold line are constructed, and the lengths of each group of vertical lines are calculated and accumulated to obtain the over-threshold value of the dam at the current time point; the highest numerical point in the line graph is marked as the peak water level of the dam at the current time point.

[0036] In some embodiments, analyzing the extracted hydrological data further includes:

[0037] The water level change value, the exceeding threshold value and the water level peak value are marked as , as well as ; and substitute into the formula Perform weighted calculation to obtain the water level assessment index of the dam at the current time point ;in and The water level changes are and super threshold The corresponding preset maximum allowed value, Indicates the preset reference water level data of the dam water level at the current time point; , as well as The water level changes are , super threshold and peak water level The impact weight factor of

[0038] Taking the current time point as the starting time point, obtain the rainfall forecast data within the set time period after the starting time point;

[0039] Determine the rainfall intensity and duration within a set time period from the acquired rainfall forecast data; integrate the determined rainfall intensity and duration into a rainfall data packet at the current time point, and substitute it into the database for matching with each group of preset reference data packets, the reference data packet includes a rainfall intensity range and a duration range, and each group of reference data packets is set to correspond to a hidden danger additional value; match the rainfall data packet integrated at the current time point with each group of preset reference data packets, thereby obtaining the hidden danger additional value of the dam at the current time point;

[0040] The water level assessment index of the dam at the current time Multiply it by the additional value of hidden dangers, and the result of the multiplication is used as the additional index of the dam water level at the current time point .

[0041] In some embodiments, a risk assessment model for the dam corresponding to the current time point is constructed, specifically:

[0042] Extract the displacement assessment index of the dam at the current time point , Crack Assessment Index And water level additional index ;

[0043] Preset displacement evaluation index , Crack Assessment Index And water level additional index The reference threshold index and displacement evaluation index are calculated respectively. , Crack Assessment Index And water level additional index The ratios between the corresponding reference threshold indices are recorded as displacement ratio, crack ratio and water level ratio respectively;

[0044] The displacement ratio and crack ratio of the dam corresponding to the current time point are taken as the length and width of the pyramid base respectively, and the water level ratio is taken as the height of the pyramid. The pyramid figure of the dam at the current time point is constructed, and the constructed pyramid figure is used as the risk assessment model of the dam at the current time point.

[0045] In some embodiments, the safety status of the dam at the current time point is evaluated, specifically:

[0046] Extract each group of early warning models stored in the database; input the surface area for constructing the risk assessment model, and if it is shown that the surface area of ​​the risk assessment model is greater than the surface area of ​​one of the groups of early warning models, generate an early warning.

[0047] In some embodiments, a feedback mechanism is established to update and optimize the early warning trigger of the dam, specifically:

[0048] If the dam triggers an alarm at a certain time point, the time point when the alarm is triggered is taken as the starting time point, and the deformation data and hydrological data of the dam at the set data collection time interval before the starting time point are extracted for analysis. The risk assessment model constructed by the analysis results is used as an early warning model and transmitted to the database for updating and storage.

[0049] Compared with the prior art, the present invention has the following beneficial effects:

[0050] The present invention realizes comprehensive monitoring of dam deformation and hydrological data through Beidou remote sensing data, and further comprehensively analyzes multi-source data of dam displacement, cracks and water level changes, constructs a comprehensive risk assessment model, and intelligently triggers early warning based on the risk assessment model, thereby improving the accuracy and response speed of early warning, and solving the problem that the existing technology relies on manual inspections, mostly focuses on single deformation data analysis, lacks comprehensive evaluation of cracks and hydrological multi-source data, and has one-sided monitoring, resulting in low early warning accuracy.

[0051] When the dam triggers an alarm at a certain time point, the present invention takes the time point of triggering the alarm as the starting time point, extracts the deformation data and hydrological data of the dam during the data collection time interval set before the starting time point for analysis, uses the risk assessment model constructed by the analysis result as an early warning model and transmits it to the database for updating and storage, thereby realizing the updating and optimization of the early warning method. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] Further details, features and advantages of the present application are disclosed in the following description of exemplary embodiments in conjunction with the accompanying drawings, in which:

[0053] Figure 1 It is a principle block diagram of the present invention;

[0054] Figure 2 It is a schematic diagram of the water level change line graph in the present invention. DETAILED DESCRIPTION

[0055] Several embodiments of the present application will be described in more detail below with reference to the accompanying drawings so that those skilled in the art can implement the present application. The present application can be embodied in many different forms and purposes and should not be limited to the embodiments described herein. These embodiments are provided to make the present application comprehensive and complete, and to fully convey the scope of the present application to those skilled in the art. The embodiments do not limit the present application.

[0056] Unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by those of ordinary skill in the art to which this application belongs. It will be further understood that terms such as those defined in commonly used dictionaries should be interpreted as having a meaning consistent with their meaning in the relevant art and / or the context of this specification, and will not be interpreted in an idealized or overly formal sense unless explicitly defined as such herein.

[0057] See also Figure 1-Figure 2 As shown in the figure, the dam monitoring and early warning method based on Beidou remote sensing data includes:

[0058] Data collection: Set the data collection time interval for dam monitoring, and use the Beidou satellite system to collect remote sensing data of the dam at the current time point after the set data collection time interval is reached;

[0059] Deploy Beidou ground receiving stations to receive various remote sensing data transmitted by Beidou satellites;

[0060] Data processing: pre-process the remote sensing data of the dam at the current time point; pre-processing includes data cleaning, format conversion, spatial correction, etc.;

[0061] Use data processing software and algorithms to perform data cleaning (remove invalid or erroneous data), format conversion (unify data formats for easy processing), and spatial correction (ensure the spatial location of data is accurate);

[0062] Feature extraction: Extract deformation data and hydrological data from preprocessed remote sensing data;

[0063] Risk assessment: Analyze the extracted deformation data and hydrological data to construct a risk assessment model for the dam at the current time point;

[0064] The extracted deformation data is analyzed as follows:

[0065] Extract the horizontal and vertical displacement data of each monitoring point pre-deployed on the dam surface from the deformation data of the dam, compare the monitoring data at the current time point with the monitoring data at the previous time point, and calculate the horizontal and vertical displacement of each monitoring point;

[0066] Ensure that the displacement data at the current time point is in the same reference coordinate system as the data at the previous time point to facilitate direct comparison;

[0067] The displacement rate of the horizontal displacement of each monitoring point is recorded as the horizontal rate, which is calculated by dividing the horizontal displacement of the corresponding monitoring point by the time interval between two time points; similarly, the displacement rate of the vertical displacement of each monitoring point is recorded as the vertical rate;

[0068] Preset the rate value ranges of each group corresponding to the horizontal rate and the vertical rate respectively, and set the rate value ranges corresponding to each group of the horizontal rate and the vertical rate to correspond to a horizontal hidden danger value and a vertical hidden danger value respectively; the horizontal hidden danger value and the vertical hidden danger value range are set in 1-5, and the higher the horizontal rate and the vertical rate, the higher the hidden danger value obtained by the corresponding matching;

[0069] The horizontal rate and vertical rate of each monitoring point are matched with the corresponding preset rate value ranges of each group, so as to obtain the horizontal hidden danger value and vertical hidden danger value corresponding to each monitoring point;

[0070] The horizontal hidden danger value and the vertical hidden danger value of the corresponding monitoring point are accumulated, and the accumulated result is used as the displacement hidden danger value of the corresponding monitoring point;

[0071] Set the maximum permissible value of displacement hazard value; it is set by technical personnel based on factors such as the service life of the dam and material aging, and can be dynamically adjusted based on actual conditions later;

[0072] The displacement potential value of each monitoring point is compared with the set maximum allowable value one by one. If the displacement potential value of a group of monitoring points is greater than the set maximum allowable value, the displacement potential value of the group of monitoring points is marked as an abnormal displacement point;

[0073] Monitoring points with faster displacement rates indicate potential structural problems in the dam;

[0074] Count the number of abnormal displacement points of the dam at the current time point, recorded as the number of abnormal points , calculate the mean of the displacement hidden danger values ​​corresponding to each group of abnormal displacement points, and record it as the abnormal mean ;

[0075] According to the formula , the number of abnormal points of the dam at the current time point and abnormal mean Perform weighted calculation to obtain the displacement assessment index of the dam at the current time point ;in The number of abnormal points The corresponding preset maximum allowed points, Indicates the preset maximum allowable value corresponding to the displacement hidden danger value; and The number of abnormal points and abnormal mean The impact weight factor of

[0076] Extract crack data from the deformation data of the dam; use high-resolution remote sensing images and image processing to extract the crack data of the dam at the current time point;

[0077] Count the number of cracks in the dam at the current time point, and obtain the length and width of each group of cracks, preset the numerical value ranges of each group of crack length and crack width, and set the numerical value ranges corresponding to each group of crack length and crack width to correspond to a length hidden danger value and a width hidden danger value respectively; the value range of the length hidden danger value and the width hidden danger value is set to 1-10, and the higher the crack length and width, the higher the corresponding length hidden danger value and width hidden danger value;

[0078] The length and width of the corresponding crack are matched with the corresponding preset value ranges of each group of values, so as to obtain the length hidden danger value and width hidden danger value of the corresponding crack;

[0079] The length potential hazard value and the width potential hazard value of the corresponding crack are accumulated, and the accumulated result is used as the risk assessment value of the corresponding crack;

[0080] The dam is divided into regions including upstream, downstream, dam top and dam foundation. After the risk assessment value of each group of cracks is obtained, the regions of each group of cracks are matched according to their locations in the dam. A weight coefficient is set for each region.

[0081] The risk assessment value of each group of cracks is multiplied by the corresponding set weight coefficient, and then the sum is obtained to obtain the crack assessment index of the dam at the current time point. ;

[0082] It should be noted that, in summary, by analyzing the displacement data and crack data of the dam at the current time point, we can have a more comprehensive and in-depth understanding of the deformation condition of the dam.

[0083] The extracted hydrological data are analyzed as follows:

[0084] Extract water level data from the hydrological data of the dam, take the dam water level data at the current time point as the reference value, obtain the water level change data of the dam within a set time period before the current time point, and extract the water level data of the dam at different time points within the set time period as the trend value;

[0085] Construct a line graph of the water level change of the dam at the current time point with the reference value and multiple groups of trend values, draw the numerical points corresponding to the reference value and multiple groups of trend values ​​in the line graph, and connect adjacent numerical points to obtain the water level line;

[0086] Calculate the slope of each group of water level lines and the angle between them and the horizontal line. If the angle between one group of water level lines and the horizontal line is an obtuse angle, mark the slope of this group of water level lines as an ascending slope. If the angle between one group of water level lines and the horizontal line is an acute angle, mark the slope of this group of water level lines as a descending slope.

[0087] Sum all the rising slopes and falling slopes respectively to obtain the rising estimate and the falling estimate;

[0088] Calculate the ratio between the rising estimate and the falling estimate as the water level change value of the dam at the current time point; if the falling estimate is 0, take the integer 1 for calculation;

[0089] Preset the reference water level data of the dam water level at the current time point, draw the threshold line corresponding to the reference water level data in the line graph, and mark the numerical points above the threshold line as the abnormal water level point of the dam at the current time point;

[0090] Taking each group of abnormal water level points as the starting point, construct the vertical line between each group of starting points and the threshold line, calculate the length of each group of vertical lines and add them up to get the over-threshold value of the dam at the current time point;

[0091] Mark the highest value point in the line graph as the peak water level of the dam at the current time point;

[0092] The water level change value, the exceeding threshold value and the water level peak value are marked as , as well as ; and substitute into the formula Perform weighted calculation to obtain the water level assessment index of the dam at the current time point ;in and The water level changes are and super threshold The corresponding preset maximum allowed value, Indicates the preset reference water level data of the dam water level at the current time point; , as well as The water level changes are , super threshold and peak water level The impact weight factor of

[0093] It should be noted that, in summary, dynamic monitoring of dam water level changes over time is achieved, providing an intuitive display of water level changes.

[0094] Taking the current time point as the starting time point, obtain the rainfall forecast data within the set time period after the starting time point; obtain it by accessing the relevant meteorological service platform where the dam is located;

[0095] Determine the rainfall intensity and duration within the set time period from the acquired rainfall forecast data; integrate the determined rainfall intensity and duration into a rainfall data packet at the current time point, and substitute it into the database for matching with each group of preset reference data packets. The reference data packet includes a rainfall intensity range and a duration range, and each group of reference data packets is set to correspond to a hidden danger additional value; the hidden danger additional value range is set at 0.86-1.59, which can be dynamically adjusted according to actual application conditions; match the rainfall data packet integrated at the current time point with each group of preset reference data packets, thereby obtaining the hidden danger additional value of the dam at the current time point;

[0096] The water level assessment index of the dam at the current time Multiply it by the additional value of hidden dangers, and the result of the multiplication is used as the additional index of the dam water level at the current time point ;

[0097] Construct a risk assessment model for the dam at the current time point, specifically:

[0098] Extract the displacement assessment index of the dam at the current time point , Crack Assessment Index And water level additional index ;

[0099] Preset displacement evaluation index , Crack Assessment Index And water level additional index The reference threshold index and displacement evaluation index are calculated respectively. , Crack Assessment Index And water level additional index The ratios between the corresponding reference threshold indices are recorded as displacement ratio, crack ratio and water level ratio respectively;

[0100] The displacement ratio and crack ratio of the dam at the current time point are used as the length and width of the pyramid base, and the water level ratio is used as the height of the pyramid, thereby constructing a pyramid figure of the dam at the current time point, and the constructed pyramid figure is used as the risk assessment model of the dam at the current time point;

[0101] Use pyramid graphics to visualize risk quantification results and directly display the safety status and risk level of the dam;

[0102] Trigger warning: Based on the risk assessment model constructed for the dam at the current time point, the safety status of the dam at the current time point is assessed. If the assessment result generates a warning, the pre-installed warning device is triggered to issue a warning;

[0103] Specifically:

[0104] Extract each set of early warning models stored in the database; the early warning models are set by technical personnel and can also be updated through the feedback mechanism;

[0105] Input the surface area of ​​the risk assessment model, and if it is shown that the surface area of ​​the risk assessment model is greater than the surface area of ​​one of the warning models, generate a warning;

[0106] Information release: When issuing a warning, the warning information will be released to the management department and the public through preset channels in a timely manner. The preset channels include but are not limited to SMS, email, APP push, etc.;

[0107] Early warning optimization: Establish a feedback mechanism to update and optimize the early warning triggers of the dam;

[0108] If the dam triggers an alarm at a certain time point, the time point when the alarm is triggered is taken as the starting time point, and the deformation data and hydrological data of the dam at the set data collection time interval before the starting time point are extracted for analysis, and the risk assessment model constructed by the analysis results is used as an early warning model and transmitted to the database for updating and storage;

[0109] The above formulas are obtained by collecting a large amount of data and performing software simulation, and a formula close to the actual value is selected. The influencing weight factor and specific coefficient value in the formula are set by technical personnel in this field according to actual conditions, and can be adjusted and modified later.

[0110] The preferred embodiments of the present invention disclosed above are only used to help explain the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to only specific implementation methods. Obviously, many modifications and changes can be made according to the content of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the present invention, so that those skilled in the art can understand and use the present invention well. The present invention is limited only by the claims and their full scope and equivalents.

Claims

1. A dam monitoring and early warning method based on Beidou remote sensing data, characterized in that: include: Data collection: Set the data collection time interval for dam monitoring. After the set data collection time interval is reached, collect the remote sensing data of the dam at the current time point; Data processing: pre-processing the remote sensing data of the dam at the current time point; Feature extraction: Extract deformation data and hydrological data from preprocessed remote sensing data; Risk assessment: Analyze the extracted deformation data and hydrological data to construct a risk assessment model for the dam at the current time point; The extracted deformation data is analyzed as follows: Extract the horizontal and vertical displacement data of each monitoring point pre-deployed on the dam surface from the deformation data of the dam, compare the monitoring data at the current time point with the monitoring data at the previous time point, and calculate the horizontal and vertical displacement of each monitoring point; The displacement rate of the horizontal displacement of each monitoring point is recorded as the horizontal rate, which is calculated by dividing the horizontal displacement of the corresponding monitoring point by the time interval between two time points; similarly, the displacement rate of the vertical displacement of each monitoring point is recorded as the vertical rate; Preset the rate value ranges of each group corresponding to the horizontal rate and the vertical rate respectively, and set the rate value range corresponding to each group of the horizontal rate and the vertical rate to correspond to a horizontal hidden danger value and a vertical hidden danger value respectively; The horizontal rate and vertical rate of each monitoring point are matched with the corresponding preset rate value ranges, so as to obtain the horizontal hidden danger value and vertical hidden danger value corresponding to each monitoring point; the horizontal hidden danger value and vertical hidden danger value of the corresponding monitoring point are accumulated, and the accumulated result is used as the displacement hidden danger value of the corresponding monitoring point; Set the maximum permissible value of displacement hazard value; The displacement potential value of each monitoring point is compared with the set maximum allowable value one by one. If the displacement potential value of a group of monitoring points is greater than the set maximum allowable value, the displacement potential value of the group of monitoring points is marked as an abnormal displacement point; Count the number of abnormal displacement points of the dam at the current time point, recorded as the number of abnormal points , calculate the mean of the displacement hidden danger values ​​corresponding to each group of abnormal displacement points, and record it as the abnormal mean ; According to the formula , the number of abnormal points of the dam at the current time point and abnormal mean Perform weighted calculation to obtain the displacement assessment index of the dam at the current time point ;in The number of abnormal points The corresponding preset maximum allowed points, Indicates the preset maximum allowable value corresponding to the displacement hidden danger value; and The number of abnormal points and abnormal mean The impact weight factor of Extract crack data from the deformation data of the dam; count the number of cracks in the dam at the current time point, and obtain the length and width of each group of cracks, respectively preset the numerical value ranges of each group of crack length and crack width, and set the numerical value ranges corresponding to each group of crack length and crack width to correspond to a length hidden danger value and a width hidden danger value respectively; The length and width of the corresponding crack are matched with the corresponding preset value ranges of each group of values, so as to obtain the length hidden danger value and width hidden danger value of the corresponding crack; The length hazard value and width hazard value of the corresponding crack are accumulated, and the accumulated result is used as the risk assessment value of the corresponding crack; the dam is divided into regions; after the risk assessment value of each group of cracks is obtained, the regions of each group of cracks are matched according to the location of each group of cracks in the dam; and a weight coefficient is set for each region; The risk assessment value of each group of cracks is multiplied by the corresponding set weight coefficient, and then the sum is obtained to obtain the crack assessment index of the dam at the current time point. ; The extracted hydrological data are analyzed as follows: Extract water level data from the hydrological data of the dam, take the dam water level data at the current time point as the reference value, obtain the water level change data of the dam within a set time period before the current time point, and extract the water level data of the dam at different time points within the set time period as the trend value; Construct a line graph of the water level change of the dam at the current time point with the reference value and multiple groups of trend values, draw the numerical points corresponding to the reference value and multiple groups of trend values ​​in the line graph, and connect the adjacent numerical points to obtain the water level line; calculate the slope of each group of water level lines and the angle with the horizontal line. If the angle between one group of water level lines and the horizontal line is an obtuse angle, mark the slope of the group of water level lines as an upward slope; if the angle between one group of water level lines and the horizontal line is an acute angle, mark the slope of the group of water level lines as a downward slope; Sum up all the rising slopes and falling slopes respectively to obtain the rising estimate and the falling estimate; calculate the ratio between the rising estimate and the falling estimate as the water level change value of the dam at the current time point; The reference water level data of the dam water level at the current time point is preset, and the threshold line corresponding to the reference water level data is drawn in the line graph, and the numerical points above the threshold line are marked as the abnormal water level points of the dam at the current time point; and each group of abnormal water level points is used as the starting point, and the vertical lines between each group of starting points and the threshold line are constructed, and the lengths of each group of vertical lines are calculated and accumulated to obtain the super-threshold value of the dam at the current time point; the highest numerical point in the line graph is marked as the peak water level of the dam at the current time point; The water level change value, the exceeding threshold value and the water level peak value are marked as , as well as ; and substitute into the formula Perform weighted calculation to obtain the water level assessment index of the dam at the current time point ;in and The water level changes are and super threshold The corresponding preset maximum allowed value, Indicates the preset reference water level data of the dam water level at the current time point; , as well as The water level changes are , super threshold and peak water level The impact weight factor of Taking the current time point as the starting time point, obtain the rainfall forecast data within the set time period after the starting time point; Determine the rainfall intensity and duration within a set time period from the acquired rainfall forecast data; The determined rainfall intensity and duration are integrated into a rainfall data packet at the current time point, and substituted into the database for matching with each group of preset reference data packets. The reference data packet includes a rainfall intensity range and a duration range, and each group of reference data packets is set to correspond to a hidden danger additional value; the rainfall data packet integrated at the current time point is matched with each group of preset reference data packets, thereby obtaining the hidden danger additional value of the dam at the current time point; The water level assessment index of the dam at the current time Multiply it by the additional value of hidden dangers, and the result of the multiplication is used as the additional index of the dam water level at the current time point ; Construct a risk assessment model for the dam at the current time point, specifically: Extract the displacement assessment index of the dam at the current time point , Crack Assessment Index And water level additional index ; Preset displacement evaluation index , Crack Assessment Index And water level additional index The reference threshold index and displacement evaluation index are calculated respectively. , Crack Assessment Index And water level additional index The ratios between the corresponding reference threshold indices are recorded as displacement ratio, crack ratio and water level ratio respectively; The displacement ratio and crack ratio of the dam at the current time point are used as the length and width of the pyramid base, and the water level ratio is used as the height of the pyramid, thereby constructing a pyramid figure of the dam at the current time point, and the constructed pyramid figure is used as the risk assessment model of the dam at the current time point; Trigger warning: Based on the risk assessment model constructed for the dam at the current time point, the safety status of the dam at the current time point is assessed. If the assessment result generates a warning, the pre-installed warning device is triggered to issue a warning; Information release: When issuing a warning, the warning information will be released to the management department and the public through the preset channels in a timely manner; Early warning optimization: Establish a feedback mechanism to update and optimize the early warning triggers of the dam; Establish a feedback mechanism to update and optimize the dam’s early warning triggers, specifically: If the dam triggers an alarm at a certain time point, the time point when the alarm is triggered is taken as the starting time point, and the deformation data and hydrological data of the dam at the set data collection time interval before the starting time point are extracted for analysis. The risk assessment model constructed by the analysis results is used as an early warning model and transmitted to the database for updating and storage.

2. The dam monitoring and early warning method based on Beidou remote sensing data according to claim 1 is characterized in that: Assess the safety status of the dam at the current time, specifically: Extract each group of early warning models stored in the database; input the surface area for constructing the risk assessment model, and if it is shown that the surface area of ​​the risk assessment model is greater than the surface area of ​​one of the groups of early warning models, generate an early warning.

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