Slope deformation monitoring method and system based on millimeter wave radar

Abstract

The application provides a kind of based on millimeter wave radar's side slope deformation monitoring method and system, belong to the technical field of side slope deformation monitoring, for solving the problem that fixed monitoring interval length of related technology timing monitoring cannot obviously adapt to the monitoring frequency requirement of side slope change, in the method and system, the monitoring interval of side slope deformation can be intelligently determined by comprehensively considering past side slope deformation and rainfall, temperature, humidity and other conditions, so that the monitoring interval will not be too long to miss the key target deformation monitoring data, and will not be too short to cause energy waste caused by frequent start of millimeter wave radar, that is, the monitoring interval length intelligently adapts to the change of side slope, and the monitoring strategy of side slope can be intelligently and reasonably determined.

Description

Technical Field

[0001] This application relates to the technical field of slope deformation monitoring, and in particular to a slope deformation monitoring method and system based on millimeter-wave radar. Background Technology

[0002] Slope deformation can lead to geological disasters such as slope instability, landslides, and debris flows. In order to provide early warning of geological disasters such as slope instability, landslides, and debris flows, and to protect the lives and property of the people, it is necessary to monitor slope deformation.

[0003] Existing slope deformation monitoring technologies generally involve timed monitoring, which means that the positions of several monitoring target points on the slope are collected at regular intervals, and the collected positions are compared with the initial positions of the target points or the positions collected in the previous time to determine the displacement of the monitoring target points. When the displacement of the monitoring target points exceeds the displacement threshold, a pre-alarm is issued.

[0004] However, as the actual conditions of the slope change, the required frequency of slope deformation monitoring will also change. Timed monitoring based on fixed monitoring intervals is clearly unable to meet the monitoring frequency requirements of slope changes. Summary of the Invention

[0005] This application provides a slope deformation monitoring method and system based on millimeter-wave radar, which intelligently determines the monitoring interval of slope deformation monitoring, so that the monitoring interval can adapt to the changes in monitoring frequency requirements caused by slope changes.

[0006] Firstly, this application provides a slope deformation monitoring method based on millimeter-wave radar. The method includes:

[0007] In response to a monitoring trigger signal, target location data for each monitoring target point on the target slope is collected. The target location data is then recorded and stored as a target location record after being assigned a timestamp of the collection time and a target identifier of the corresponding monitoring target point. The monitoring interval between the next monitoring trigger signal and the current monitoring trigger signal is determined. The target location data is obtained based on millimeter-wave radar and corner reflectors configured at the monitoring target points.

[0008] Starting from the moment the current monitoring trigger signal occurs, the monitoring interval duration is consumed based on the clock signal and the equivalent consumption time determined by analyzing the rainfall monitoring data, temperature monitoring data, and humidity monitoring data of the target slope's geographical location. When the consumption is completed, the next monitoring trigger signal is generated. The equivalent consumption time is positively correlated with the rainfall detection data and humidity monitoring data, and also positively correlated with the degree of change in the temperature monitoring data.

[0009] The determination of the monitoring interval between the next monitoring trigger signal and the current monitoring trigger signal includes:

[0010] Retrieve target location records within a preset time period, with the occurrence time of the current monitoring trigger signal as the last time. Collect rainfall monitoring data, temperature monitoring data, and humidity monitoring data within a preset time period, with the occurrence time of the current monitoring trigger signal as the last time, of the geographical location of the target slope.

[0011] The target location records within a preset time period are analyzed to determine the interval time base value. The interval time base value is negatively correlated with the cumulative deformation of the target slope represented by the target location records and the unit time. ;

[0012] Analyze rainfall monitoring data, temperature monitoring data, and humidity monitoring data within a preset time period to determine a time period adjustment coefficient. The time period adjustment coefficient is negatively correlated with the rainfall monitoring data and humidity monitoring data, and negatively correlated with the degree of change in temperature monitoring data.

[0013] The monitoring interval duration is determined based on the interval duration base value and the duration adjustment coefficient. The monitoring interval duration is within the preset interval duration range and is positively correlated with the interval duration base value and the duration adjustment coefficient.

[0014] By adopting the above technical solution, the monitoring interval for slope deformation can be intelligently determined by comprehensively considering past slope deformation data as well as rainfall, temperature, humidity, and other factors. This ensures that the monitoring interval is neither too long, which would cause missing key target deformation monitoring data, nor too short, which would lead to frequent activation of the millimeter-wave radar and waste of energy. In other words, the monitoring interval length intelligently adapts to slope changes, enabling intelligent and reasonable determination of slope monitoring strategies.

[0015] Furthermore, the process of consuming the monitoring interval time based on a clock signal and an equivalent consumption time determined by analyzing the collected rainfall, temperature, and humidity monitoring data at the geographical location of the target slope, starting from the time the current monitoring trigger signal occurs, and generating the next monitoring trigger signal upon completion of the consumption, includes:

[0016] Analyze the rainfall monitoring data from the current moment to the moment the current monitoring trigger signal occurred to determine the cumulative rainfall, the peak rainfall, and the duration of high cumulative rainfall exceeding the first rainfall threshold.

[0017] Analyze the humidity monitoring data from the current moment to the moment the current trigger signal was generated to determine the cumulative humidity value, the peak humidity value, and the duration of high humidity exceeding the first humidity threshold;

[0018] Analyze the temperature monitoring data from the current moment to the moment the current monitoring trigger signal occurs to determine the temperature change data, analyze the temperature change data to determine the temperature change peak, the duration of a drastic temperature change when the temperature change data is higher than a first temperature change threshold, and the special duration of a drastic temperature change when the temperature change data is higher than the first temperature change threshold and the duration of a single occurrence exceeds the first temperature change preset duration.

[0019] Let the cumulative rainfall value be... The peak rainfall occurred at The cumulative duration of high rainfall was The cumulative humidity value is The peak humidity was The duration of high humidity is The peak temperature change is The duration of the drastic temperature change was The duration of drastic temperature changes is particularly long. The equivalent time consumed for the temperature change is The equivalent consumption time is ,but

[0020]

[0021]

[0022]

[0023]

[0024] In the formula, , , , , , , All are preset calculation coefficients that are greater than zero. To preset the rainfall amount, To preset the humidity value, To preset the temperature change value, To preset the occurrence duration, The preset unit duration.

[0025] Furthermore, the baseline value for determining the interval duration of target point location recording within the preset analysis time period includes:

[0026] Assume that the target slope is equipped with Each monitoring target point has a preset time interval before the current monitoring trigger signal occurs. The target location records are as follows: The j-th target location record for the i-th monitored target is... Let the first target location record correspond to the current monitoring trigger signal, and the second target location record... The target location record is the one furthest from the time of the current monitoring trigger signal. Article and Section The time interval between the occurrence times of the corresponding detection trigger signals for each target location is represented as follows: , and The base value of the interval duration is ,but

[0027]

[0028]

[0029]

[0030]

[0031]

[0032]

[0033]

[0034] In the formula, , , , , All are preset calculation coefficients that are greater than zero. As a preset time base value, As a preset distance base value, The first calculation threshold is... The function value is for the i-th monitoring target point at Within the range Sort by size from largest to smallest and then sum the first preset number of each.

[0035] Furthermore, the determination of the duration adjustment coefficient for analyzing rainfall monitoring data, temperature monitoring data, and humidity monitoring data within a preset duration includes:

[0036] Let the cumulative historical rainfall value within the preset time period be... The historical peak rainfall was The cumulative historical duration of high rainfall is Historical cumulative humidity value The historical peak humidity was The duration of the high humidity history is The historical peak of temperature change was The duration of the drastic temperature change was The history of drastic temperature changes is particularly long. The equivalent duration of historical temperature changes is The duration adjustment factor is ,but

[0037]

[0038]

[0039]

[0040]

[0041] In the formula, , , , , , , All are preset calculation coefficients that are greater than zero. To preset historical rainfall, For preset calculation adjustment coefficients and , To preset historical humidity values, To preset historical temperature change values, Preset historical duration.

[0042] Furthermore, determining the monitoring interval duration based on the interval duration base value and the duration adjustment coefficient includes:

[0043] Let the base value of the interval duration be... The duration adjustment factor is , , These are the upper and lower limits of the preset interval duration range, respectively. To monitor the interval duration, then

[0044]

[0045] In the formula, , and .

[0046] Furthermore, determining the monitoring interval duration based on the interval duration base value and the duration adjustment coefficient includes:

[0047] Let the base value of the interval duration be... The duration adjustment factor is , , These are the upper and lower limits of the preset interval duration range, respectively. To monitor the interval duration, then

[0048]

[0049] In the formula, and All are positive integers and .

[0050] Secondly, this application provides a slope deformation monitoring system based on millimeter-wave radar. The system includes a millimeter-wave radar, a server, and multiple corner reflectors. The corner reflectors are individually installed at monitoring target points on the target slope. The millimeter-wave radar covers all the corner reflectors. The millimeter-wave radar and corner reflectors work together to collect target point location data.

[0051] The server is connected to the millimeter-wave radar and is used to collect target location data of each monitoring target point on the target slope in response to the monitoring trigger signal. The target location data is assigned a timestamp of the collection time and a target point identifier of the corresponding monitoring target point and stored as a target location record. The server also determines the monitoring interval between the next monitoring trigger signal and the current monitoring trigger signal. The target location data is obtained based on the millimeter-wave radar and corner reflectors configured at the monitoring target points.

[0052] The server is also used to consume the monitoring interval time from the time the current monitoring trigger signal occurs, based on the clock signal and the equivalent consumption time determined by analyzing the collected rainfall monitoring data, temperature monitoring data and humidity monitoring data of the geographical location of the target slope. When the consumption is completed, the next monitoring trigger signal is generated. The equivalent consumption time is positively correlated with the rainfall detection data and humidity monitoring data, and positively correlated with the degree of change of the temperature monitoring data.

[0053] The server is further configured such that determining the monitoring interval between the next monitoring trigger signal and the current monitoring trigger signal includes:

[0054] Retrieve target location records within a preset time period, with the occurrence time of the current monitoring trigger signal as the last time. Collect rainfall monitoring data, temperature monitoring data, and humidity monitoring data within a preset time period, with the occurrence time of the current monitoring trigger signal as the last time, of the geographical location of the target slope.

[0055] The target location records within a preset time period are analyzed to determine the interval time base value. The interval time base value is negatively correlated with the cumulative deformation of the target slope represented by the target location records and the unit time. ;

[0056] Analyze rainfall monitoring data, temperature monitoring data, and humidity monitoring data within a preset time period to determine a time period adjustment coefficient. The time period adjustment coefficient is negatively correlated with the rainfall monitoring data and humidity monitoring data, and negatively correlated with the degree of change in temperature monitoring data.

[0057] The monitoring interval duration is determined based on the interval duration base value and the duration adjustment coefficient. The monitoring interval duration is within the preset interval duration range and is positively correlated with the interval duration base value and the duration adjustment coefficient.

[0058] Furthermore, the server is further configured such that, starting from the occurrence time of the current monitoring trigger signal, the monitoring interval duration is consumed based on a clock signal and an equivalent consumption time determined by analyzing the collected rainfall monitoring data, temperature monitoring data, and humidity monitoring data of the target slope's geographical location. Upon completion of this consumption, the next monitoring trigger signal is generated, including:

[0059] Analyze the rainfall monitoring data from the current moment to the moment the current monitoring trigger signal occurred to determine the cumulative rainfall, the peak rainfall, and the duration of high cumulative rainfall exceeding the first rainfall threshold.

[0060] Analyze the humidity monitoring data from the current moment to the moment the current trigger signal was generated to determine the cumulative humidity value, the peak humidity value, and the duration of high humidity exceeding the first humidity threshold;

[0061] Analyze the temperature monitoring data from the current moment to the moment the current monitoring trigger signal occurs to determine the temperature change data, analyze the temperature change data to determine the temperature change peak, the duration of a drastic temperature change when the temperature change data is higher than a first temperature change threshold, and the special duration of a drastic temperature change when the temperature change data is higher than the first temperature change threshold and the duration of a single occurrence exceeds the first temperature change preset duration.

[0062] Let the cumulative rainfall value be... The peak rainfall occurred at The cumulative duration of high rainfall was The cumulative humidity value is The peak humidity was The duration of high humidity is The peak temperature change is The duration of the drastic temperature change was The duration of drastic temperature changes is particularly long. The equivalent time consumed for the temperature change is The equivalent consumption time is ,but

[0063]

[0064]

[0065]

[0066]

[0067] In the formula, , , , , , , All are preset calculation coefficients that are greater than zero. To preset the rainfall amount, To preset the humidity value, To preset the temperature change value, To preset the occurrence duration, The preset unit duration.

[0068] Furthermore, the server is further configured such that the base value for determining the interval duration of the target location record within the preset analysis period includes:

[0069] Assume that the target slope is equipped with Each monitoring target point has a preset time interval before the current monitoring trigger signal occurs. The target location records are as follows: The j-th target location record for the i-th monitored target is... Let the first target location record correspond to the current monitoring trigger signal, and the second target location record... The target location record is the one furthest from the time of the current monitoring trigger signal. Article and Section The time interval between the occurrence times of the corresponding detection trigger signals for each target location is represented as follows: , and The base value of the interval duration is ,but

[0070]

[0071]

[0072]

[0073]

[0074]

[0075]

[0076]

[0077] In the formula, , , , , All are preset calculation coefficients that are greater than zero. As a preset time base value, As a preset distance base value, The first calculation threshold is... The function value is for the i-th monitoring target point at Within the range Sort by size from largest to smallest and then sum the first preset number of results;

[0078] And / or the server is further configured such that the determination of the duration adjustment factor for analyzing rainfall monitoring data, temperature monitoring data, and humidity monitoring data within a preset duration includes:

[0079] Let the cumulative historical rainfall value within the preset time period be... The historical peak rainfall was The cumulative historical duration of high rainfall is Historical cumulative humidity value The historical peak humidity was The duration of the high humidity history is The historical peak of temperature change was The duration of the drastic temperature change was The history of drastic temperature changes is particularly long. The equivalent duration of historical temperature changes is The duration adjustment factor is ,but

[0080]

[0081]

[0082]

[0083]

[0084] In the formula, , , , , , , All are preset calculation coefficients that are greater than zero. To preset historical rainfall, For preset calculation adjustment coefficients and , To preset historical humidity values, To preset historical temperature change values, Preset historical duration.

[0085] Furthermore, the server is further configured such that determining the monitoring interval duration based on the interval duration base value and the duration adjustment coefficient includes:

[0086] Let the base value of the interval duration be... The duration adjustment factor is , , These are the upper and lower limits of the preset interval duration range, respectively. To monitor the interval duration, then

[0087]

[0088] In the formula, , and ;

[0089] And / or the server is further configured such that determining the monitoring interval duration based on the interval duration base value and the duration adjustment coefficient includes:

[0090] Let the base value of the interval duration be... The duration adjustment factor is , , These are the upper and lower limits of the preset interval duration range, respectively. To monitor the interval duration, then

[0091]

[0092] In the formula, and All are positive integers and .

[0093] In summary, this application has at least the following beneficial effects:

[0094] 1. A method and system for monitoring slope deformation based on millimeter-wave radar is provided, which can intelligently determine the monitoring strategy by combining the specific deformation of the slope and key meteorological factors, and ensure that the monitoring interval is intelligently adapted to the specific conditions of the target slope.

[0095] 2. The specifically designed algorithm model for intelligently determining monitoring intervals is conducive to determining monitoring intervals more accurately and reasonably.

[0096] It should be understood that the description in the Summary Section is not intended to limit the key or essential features of the embodiments of this application, nor is it intended to restrict the scope of this application. Other features of this application will become readily apparent from the following description. Attached Figure Description

[0097] The above and other features, advantages, and aspects of the embodiments of this application will become more apparent from the accompanying drawings and the following detailed description. In the drawings, the same or similar reference numerals denote the same or similar elements, wherein:

[0098] Figure 1 A block diagram of a slope deformation monitoring system based on millimeter-wave radar is shown in an embodiment of this application;

[0099] Figure 2 A flowchart of a slope deformation monitoring method based on millimeter-wave radar is shown in an embodiment of this application. Detailed Implementation

[0100] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0101] Furthermore, the term "and / or" in this article is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. Additionally, the character " / " in this article generally indicates that the preceding and following related objects have an "or" relationship.

[0102] This application provides a slope deformation monitoring method and system based on millimeter-wave radar, which can intelligently determine the monitoring interval of the slope, so that the slope monitoring strategy can be adapted to the specific deformation and key meteorological conditions.

[0103] In one aspect, embodiments of this application disclose a slope deformation monitoring system based on millimeter-wave radar.

[0104] Figure 1 A block diagram of a slope deformation monitoring system based on millimeter-wave radar 120 is shown in an embodiment of this application.

[0105] Reference Figure 1The system specifically includes a millimeter-wave radar 120, a server 110, and multiple corner reflectors 130 (only one is shown in the figure). The corner reflectors 130 are set at the monitoring target points on the target slope, and the millimeter-wave radar 120 covers all the corner reflectors 130. The millimeter-wave radar 120 and the corner reflectors 130 work together to collect the target point location data of the monitoring target points.

[0106] The millimeter-wave radar 120 is fixedly installed at a stable location on the ground near the target slope, such as at the foot of the target slope where it is not easily affected by slope deformation. There are multiple corner reflectors 130, which are fixedly installed on the target slope to monitor the target point. By changing the position of the corner reflectors 130, the position change of the monitoring target point on the target slope can be determined, that is, the deformation of the target slope can be determined.

[0107] The specific installation location of the corner reflector 130 can be considered as a key part of the target slope, a place with complex geological conditions, or near a potential sliding surface. The specific installation method can be determined according to the specific monitoring target point, such as using anchor bolts for fixing. The installation angle and direction of the corner reflector 130 and the millimeter-wave radar 120 can be considered to be perpendicular to the millimeter-wave radar 120, and the installation angle and direction of the corner reflector 130 relative to the millimeter-wave radar 120 should be kept consistent as much as possible throughout the entire target slope. The specific installation and selection strategies of the corner reflector 130 are not part of the improvement of this application, and are conventional skills of those skilled in the art, and will not be elaborated here. It is only necessary to be able to monitor the target point position on the target slope.

[0108] The millimeter-wave radar 120 can transmit millimeter-wave signals over a wide range and cover all corner reflectors 130 on the target slope. The millimeter-wave radar 120 determines the distance between the corner reflector 130 and the millimeter-wave radar 120 based on the echo signals reflected by the received corner reflectors 130, and determines the position of the corner reflector 130 based on the built-in coordinate system and the direction information of the radar beam (such as azimuth and elevation angles), thus realizing the acquisition of target position data for monitoring the target point.

[0109] Server 110 communicates with millimeter-wave radar 120 to acquire target location data for each monitored target point. Server 110 can combine the target location data to analyze the deformation of the target slope and issue necessary early warnings. The analysis of deformation can be done using simple methods such as whether the maximum cumulative displacement of the monitored target point exceeds the maximum cumulative displacement threshold or whether the maximum time-varying displacement exceeds the maximum time-varying displacement threshold. More complex analysis methods can also be used, such as analyzing the local deformation or overall cumulative deformation of the target slope using the target location data. Other deformation analysis strategies can also be considered, or a self-designed deformation analysis algorithm model can be used. The methods for analyzing the deformation of the target slope and issuing early warnings are not within the scope of this application and will not be specifically disclosed here.

[0110] In addition, server 110 is connected to an external meteorological monitoring system. This system can consist of rainfall sensors, temperature sensors, and humidity sensors configured on the target slope. It collects rainfall, temperature, and humidity data for the target slope's geographical location. The rainfall data is a quantified value reflecting the amount of rainfall per unit time and includes a timestamp. Similarly, the temperature and humidity data also include timestamps, reflecting the temperature and humidity of the target slope. Alternatively, the meteorological monitoring system could be a meteorological service center, requiring only the ability to collect rainfall, temperature, and humidity data for the target slope's geographical location.

[0111] Considering that the millimeter-wave signal emitted by the millimeter-wave radar 120 needs to cover all corner reflectors 130 on the target slope, the server 110 is also used to control the activation and deactivation of the millimeter-wave radar 120. The millimeter-wave radar 120 can collect target position data for each monitoring target point within a unit of activation time; that is, each set of target position data (the collection of target position data for all monitoring target points during a single activation) carries a timestamp of the acquisition time. Each activation of the millimeter-wave radar 120 requires high energy consumption. Increasing the monitoring interval of the millimeter-wave radar 120 activation can undoubtedly save energy in long-term slope deformation monitoring work. However, if the monitoring interval is too long, it is easy to miss key information reflecting slope deformation, leading to delayed detection of slope deformation. Therefore, the server 110 intelligently and dynamically determines the monitoring interval based on the specific conditions of the target slope to achieve better monitoring results with lower energy consumption.

[0112] The algorithm model for monitoring the target slope executed in server 110 is specifically described in accordance with the disclosure of the second aspect of this application.

[0113] Secondly, this application provides a slope deformation monitoring method based on millimeter-wave radar 120. This method can be... Figure 1 The server 110 in the middle is executing.

[0114] Reference Figure 2 The method specifically includes the following steps:

[0115] S210: In response to the monitoring trigger signal, collect the target position data of each monitoring target point on the target slope, assign the target position data with a timestamp of the collection time and the target point identifier of the corresponding monitoring target point, and store it as a target position record, and determine the monitoring interval between the next monitoring trigger signal and the current monitoring trigger signal. The target position data is obtained based on the millimeter-wave radar 120 and the corner reflector 130 configured at the monitoring target point.

[0116] When the server 110 generates a monitoring trigger signal, the server 110 controls the millimeter-wave radar 120 to start for a unit of time, and performs the following actions: transmitting millimeter-wave signals to each corner transmitter of the target slope, receiving the echo signals reflected by each corner reflector 130, analyzing the echo signals to determine the target location data of each monitoring target point, and causing the server 110 to collect a set of target location data with timestamps.

[0117] Server 110 receives and stores a set of target location data with timestamps to form a target location record, which is historical target location data.

[0118] When generating a monitoring trigger signal, the server 110 will also analyze the target location record to determine the monitoring interval between the next monitoring trigger signal and the current monitoring trigger signal. The monitoring interval is used as the basis for the occurrence of the next monitoring trigger signal. Based on the built-in clock of the server 110 and subsequent method steps, the specific time when the next monitoring trigger signal occurs is determined. In this way, the monitoring interval can be determined intelligently, reasonably and dynamically.

[0119] The specific method for determining the monitoring interval is described below. Determining the monitoring interval between the next monitoring trigger signal and the current monitoring trigger signal includes: retrieving target location records within a preset time period ending at the occurrence time of the current monitoring trigger signal; collecting rainfall, temperature, and humidity monitoring data within a preset time period ending at the occurrence time of the current monitoring trigger signal at the geographical location of the target slope; analyzing the target location records within the preset time period to determine the interval base value, which is negatively correlated with the cumulative deformation of the target slope represented by the target location records and the unit time. The monitoring data of rainfall, temperature, and humidity within a preset time period are analyzed to determine a time period adjustment coefficient. The time period adjustment coefficient is negatively correlated with the rainfall and humidity monitoring data and negatively correlated with the degree of change in temperature monitoring data. The monitoring interval is determined based on the interval duration base value and the time period adjustment coefficient. The monitoring interval is within the preset interval duration range and positively correlated with the interval duration base value and the time period adjustment coefficient.

[0120] In this step, the determination of the target location record interval base value within the preset analysis time period includes:

[0121] Assume that the target slope is equipped with Each monitoring target point has a preset time interval before the current monitoring trigger signal occurs. The target location records are as follows: The j-th target location record for the i-th monitored target is... Let the first target location record correspond to the current monitoring trigger signal, and the second target location record... The target position record is the one furthest from the occurrence time of the current monitoring trigger signal, and any two target position records are defined as the first two. Article and Section Article, No. Article and Section The time interval between the occurrence times of the corresponding detection trigger signals for each target location is represented as follows: , and The base value of the interval duration is ,but

[0122]

[0123]

[0124]

[0125]

[0126]

[0127]

[0128]

[0129] In the formula, , , , , All are preset calculation coefficients that are greater than zero. As a preset time base value, As a preset distance base value, The first calculation threshold is... The function value is for the i-th monitoring target point at Within the range Sort by size from largest to smallest and sum the first predetermined number of terms, where e is a natural constant. In the example above, such as... , , "Equal to" represents the distance value calculated based on the position data of two target points, for example... This represents the coordinate distance calculated between the coordinates of the first and mth target position records for the i-th monitoring target. In this example, m=2. The interval duration base value shown in this example is specifically related to the displacement changes of the most recent two monitoring target points, the cumulative displacement changes of the monitoring target points within a preset duration, the cumulative value of the displacement change rate within a preset duration, the cumulative value of the displacement change rate exceeding a threshold, and a specific function. The extracted deformation features may be associated with only one or a few factors in other examples, or may be extended to consider other factors that characterize the cumulative deformation and deformation rate per unit time of the target slope. These will not be listed here.

[0130] In this step, determining the duration adjustment coefficient by analyzing rainfall monitoring data, temperature monitoring data, and humidity monitoring data within a preset duration includes:

[0131] Let the cumulative historical rainfall value within the preset time period be... This represents the cumulative historical rainfall over a preset time period, with the historical peak rainfall being [value missing]. This represents the highest historical rainfall value within a preset time period, and the cumulative historical duration of high rainfall is... This represents the cumulative duration during which historical rainfall exceeds a preset rainfall amount within a preset timeframe, with the cumulative historical humidity value being [value missing]. This represents the cumulative historical humidity value within a preset time period, with the historical peak humidity value being [value missing]. This represents the highest historical humidity value within a preset time period, where the historical high humidity period is... This represents the cumulative duration for which historical humidity values ​​are higher than a preset humidity value within a preset time period, with the historical peak temperature change being [value missing]. This represents the highest historical temperature change per unit time within a preset time period, and the duration of the drastic temperature change history is... This characterizes the cumulative duration during which the historical temperature change per unit time exceeds a preset temperature change threshold within a preset time period. A particularly long duration of drastic temperature changes is defined as... The historical duration of drastic temperature changes is the cumulative value of all individual special durations within a preset duration. The duration of a single special duration represents the duration of a single instance where the historical temperature change per unit time within the preset duration exceeds a preset temperature change threshold and the duration of the single instance exceeds the preset temperature change duration. The equivalent duration of historical temperature changes represents the integral value of the historical temperature change per unit time over a preset period of time, with a duration adjustment coefficient of [missing value]. ,but

[0132]

[0133]

[0134]

[0135]

[0136] In the formula, , , , , , , All are preset calculation coefficients that are greater than zero. To preset historical rainfall, For preset calculation adjustment coefficients and , To preset historical humidity values, To preset historical temperature change values, The preset historical duration is defined as follows, where e is a natural constant. The methods in this step consider factors including historical cumulative rainfall, historical peak rainfall, historical cumulative duration of high rainfall, historical cumulative humidity, historical peak humidity, historical duration of high humidity, historical peak temperature change, historical duration of severe temperature changes, historical exceptional duration of severe temperature changes, and equivalent duration of historical temperature changes. The duration adjustment coefficient can also be related to only one or a limited number of factors, or it can be extended to consider other rainfall characteristics, humidity characteristics, or temperature change characteristics. These will not be listed here.

[0137] In this step, determining the monitoring interval duration based on the interval duration base value and the duration adjustment coefficient includes: setting the interval duration base value as follows: The duration adjustment factor is , , These are the upper and lower limits of the preset interval duration range, respectively. To monitor the interval duration, then

[0138]

[0139] In the formula, , and .

[0140] In another example, determining the monitoring interval duration based on the interval duration base value and the duration adjustment coefficient includes: setting the interval duration base value as follows: The duration adjustment factor is , , These are the upper and lower limits of the preset interval duration range, respectively. To monitor the interval duration, then

[0141]

[0142] In the formula, and All are positive integers and .

[0143] Based on the above method, the calculated detection interval duration can fall within the preset interval duration range. The specific calculation weights can be configured according to actual needs. In addition to the structure described above, other structures can also be considered for the model structure, as long as they can be associated with the interval duration base value and the duration adjustment coefficient.

[0144] S220: Starting from the moment the current monitoring trigger signal occurs, the monitoring interval duration is consumed based on the clock signal and the equivalent consumption time determined by analyzing the rainfall monitoring data, temperature monitoring data and humidity monitoring data of the target slope's geographical location. When the consumption is completed, the next monitoring trigger signal is generated. The equivalent consumption time is positively correlated with the rainfall detection data and humidity monitoring data, and positively correlated with the degree of change in the temperature monitoring data.

[0145] The specific methods in this step include: analyzing the rainfall monitoring data from the current moment to the moment the current monitoring trigger signal occurred to determine the cumulative rainfall, the peak rainfall, and the duration of high cumulative rainfall events for rainfall monitoring data that exceed the first rainfall threshold;

[0146] Analyze the humidity monitoring data from the current moment to the moment the current trigger signal was generated to determine the cumulative humidity value, the peak humidity value, and the duration of high humidity exceeding the first humidity threshold;

[0147] Analyze the temperature monitoring data from the current moment to the moment the current monitoring trigger signal occurs to determine the temperature change data, analyze the temperature change data to determine the temperature change peak, the duration of a drastic temperature change when the temperature change data is higher than a first temperature change threshold, and the special duration of a drastic temperature change when the temperature change data is higher than the first temperature change threshold and the duration of a single occurrence exceeds the first temperature change preset duration.

[0148] Let the cumulative rainfall value be... This represents the cumulative rainfall from the current moment to the moment the current monitoring trigger signal occurred, with the peak rainfall being... This represents the highest rainfall value between the current moment and the moment the current monitoring trigger signal occurred, with the cumulative duration of high rainfall being [missing information]. The cumulative duration of rainfall exceeding the preset rainfall amount between the current moment and the moment the current monitoring trigger signal occurs is represented by the cumulative humidity value. This represents the cumulative humidity value between the current moment and the moment the current monitoring trigger signal was generated, with the peak humidity value being... This represents the highest humidity value between the current moment and the moment the current monitoring trigger signal was generated, with the high humidity occurrence duration being [duration missing]. This represents the cumulative duration for which the humidity value is higher than the preset humidity value between the current moment and the moment the current monitoring trigger signal occurs, with the peak value of the temperature change being... This represents the highest temperature change per unit time between the current moment and the moment the current monitoring trigger signal occurred, and the duration of the drastic temperature change is... This characterizes the cumulative duration during which the temperature change per unit time exceeds a preset temperature change threshold between the current moment and the moment the current monitoring trigger signal occurs. A particularly long duration is defined as follows: This represents the cumulative value of all single special durations between the current time and the time of occurrence of the current monitoring trigger signal. A single special duration represents the duration of a single instance where the temperature change per unit time exceeds a preset temperature change threshold and the duration of that single instance exceeds a preset temperature change duration. The equivalent time consumed for the temperature change is... This represents the integral of the temperature change per unit time over a unit time from the current moment to the moment the current monitoring trigger signal occurred, with the equivalent time consumption being... The detection interval acceleration consumption factor characterizes the environmental influence.

[0149]

[0150]

[0151]

[0152]

[0153] In the formula, , , , , , , All are preset calculation coefficients that are greater than zero. To preset the rainfall amount, To preset the humidity value, To preset the temperature change value, To preset the occurrence duration, This is a preset unit duration. Similarly, the equivalent duration is related to factors such as cumulative rainfall, peak rainfall, cumulative duration of high rainfall, cumulative humidity, peak humidity, duration of high humidity, peak temperature change, duration of severe temperature change, and special duration of severe temperature change. It can also be related to only one or a limited number of factors, or it can be extended to consider other factors that characterize rainfall, humidity, or temperature change. These will not be listed here.

[0154] After the monitoring interval duration is determined, the monitoring interval duration is consumed in real time as the built-in clock of server 110 keeps ticking. The equivalent consumption time also gradually increases from the moment the current monitoring trigger signal occurs. Once the sum of the equivalent consumption time and the actual ticking time equals the monitoring interval duration, server 110 generates the next monitoring trigger signal. During actual monitoring, the built-in clock of server 110 consumes the monitoring interval duration at a fixed rate. The monitoring interval will be dynamically increased based on real-time environmental data (rainfall, humidity, temperature changes), and the combined effect of these two factors will consume the monitoring interval time. For example, when the target slope experiences continuous heavy rainfall (high cumulative rainfall value, high rainfall peak value), The increased monitoring interval allows for faster consumption of data, thus shortening the actual time interval between two monitoring sessions and enabling timely detection of slope deformation that may be caused by rainwater infiltration. When environmental conditions are stable (no rainfall, low humidity, and gradual temperature changes), With a value close to 0, the monitoring interval is mainly consumed by the normal clock rate, avoiding unnecessary high-frequency monitoring that would lead to energy waste.

[0155] It should be understood that in the methods disclosed in the embodiments of this application, such as , , , , , , Calculation coefficients and , , The preset values ​​can be set based on data experience or expert experience. The boundary limitations of these preset coefficients and preset values ​​have been pointed out in this application. The specific values ​​can be obtained after a limited number of training or simulations according to the actual application requirements, and no specific limitations are made here.

[0156] The method disclosed in this application can intelligently, reasonably, and dynamically determine the monitoring interval between two monitoring sessions of the target slope by comprehensively considering the key meteorological factors and slope deformation of the target slope. This enables dynamic and adaptive determination of the monitoring strategy for the target slope, which is beneficial for achieving good monitoring of the target slope deformation with low energy consumption.

[0157] It should be noted that, for the sake of simplicity, the foregoing method embodiments are all described as a series of actions. However, those skilled in the art should understand that this application is not limited to the described order of actions, because according to the embodiments of this application, some steps can be performed in other orders or simultaneously. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are all optional embodiments, and the actions and modules involved are not necessarily essential to this application.

[0158] In summary, this application has at least the following beneficial effects:

[0159] 1. A slope deformation monitoring method and system based on millimeter-wave radar 120 is provided, which can intelligently determine the monitoring strategy by combining the specific deformation of the slope and key meteorological factors, and ensure that the monitoring interval is intelligently adapted to the specific conditions of the target slope.

[0160] 2. The specifically designed algorithm model for intelligently determining monitoring intervals is conducive to determining monitoring intervals more accurately and reasonably.

[0161] The above description is merely a preferred embodiment of this application and an explanation of the technical principles employed. Those skilled in the art should understand that the scope of disclosure in this application is not limited to technical solutions formed by specific combinations of the above-described technical features, but should also cover other technical solutions formed by arbitrary combinations of the above-described technical features or their equivalents without departing from the foregoing disclosed concept. For example, technical solutions formed by substituting the above features with (but not limited to) technical features with similar functions disclosed in this application.

Claims

1. A slope deformation monitoring method based on millimeter-wave radar (120), characterized in that, include: In response to the monitoring trigger signal, target location data of each monitoring target point on the target slope is collected. The target location data is assigned a timestamp of the collection time and the target identification of the corresponding monitoring target point and stored as a target location record. The monitoring interval between the next monitoring trigger signal and the current monitoring trigger signal is determined. The target location data is obtained based on millimeter-wave radar (120) and corner reflectors (130) configured at the monitoring target points. Starting from the moment the current monitoring trigger signal occurs, the monitoring interval duration is consumed based on the clock signal and the equivalent consumption time determined by analyzing the rainfall monitoring data, temperature monitoring data, and humidity monitoring data of the target slope's geographical location. When the consumption is completed, the next monitoring trigger signal is generated. The equivalent consumption time is positively correlated with the rainfall monitoring data and humidity monitoring data, and is also positively correlated with the degree of change in the temperature monitoring data. The determination of the monitoring interval between the next monitoring trigger signal and the current monitoring trigger signal includes: Retrieve target location records within a preset time period, with the occurrence time of the current monitoring trigger signal as the last time. Collect rainfall monitoring data, temperature monitoring data, and humidity monitoring data within a preset time period, with the occurrence time of the current monitoring trigger signal as the last time, of the geographical location of the target slope. The target location records within a preset time period are analyzed to determine the interval time base value. The interval time base value is negatively correlated with the cumulative deformation of the target slope represented by the target location records and the unit time. ; Analyze rainfall monitoring data, temperature monitoring data, and humidity monitoring data within a preset time period to determine a time period adjustment coefficient. The time period adjustment coefficient is negatively correlated with the rainfall monitoring data and humidity monitoring data, and negatively correlated with the degree of change in temperature monitoring data. The monitoring interval duration is determined based on the interval duration base value and the duration adjustment coefficient. The monitoring interval duration is within the preset interval duration range and is positively correlated with the interval duration base value and the duration adjustment coefficient.

2. The method according to claim 1, characterized in that, The process of consuming the monitoring interval time, starting from the time the current monitoring trigger signal occurs, based on a clock signal and an equivalent consumption time determined by analyzing the collected rainfall, temperature, and humidity monitoring data from the geographical location of the target slope, and generating the next monitoring trigger signal upon completion of the consumption, includes: Analyze the rainfall monitoring data from the current moment to the moment the current monitoring trigger signal occurred to determine the cumulative rainfall, the peak rainfall, and the duration of high cumulative rainfall exceeding the first rainfall threshold. Analyze the humidity monitoring data from the current moment to the moment the current trigger signal was generated to determine the cumulative humidity value, the peak humidity value, and the duration of high humidity exceeding the first humidity threshold; Analyze the temperature monitoring data from the current moment to the moment the current monitoring trigger signal occurs to determine the temperature change data, analyze the temperature change data to determine the temperature change peak, the duration of a drastic temperature change when the temperature change data is higher than a first temperature change threshold, and the special duration of a drastic temperature change when the temperature change data is higher than the first temperature change threshold and the duration of a single occurrence exceeds the first temperature change preset duration. Let the cumulative rainfall value be... The peak rainfall occurred at The cumulative duration of high rainfall was The cumulative humidity value is The peak humidity was The duration of high humidity is The peak temperature change is The duration of the drastic temperature change was The duration of drastic temperature changes is particularly long. The equivalent time consumed for the temperature change is The equivalent consumption time is ,but ; ; ; ; In the formula, , , , , , , All are preset calculation coefficients that are greater than zero. To preset the rainfall amount, To preset the humidity value, To preset the temperature change value, To preset the occurrence duration, The preset unit duration.

3. The method according to claim 1, characterized in that, The baseline value for determining the interval length of the target point location record within the preset analysis time period includes: Assume that the target slope is equipped with Each monitoring target point has a preset time interval before the current monitoring trigger signal occurs. The target location records are as follows: The j-th target location record for the i-th monitored target is... Let the first target location record correspond to the current monitoring trigger signal, and the second target location record... The target location record is the one furthest from the time of the current monitoring trigger signal. Article and Section The time interval between the occurrence times of the corresponding detection trigger signals for each target location is represented as follows: , and The base value of the interval duration is ,but ; ; ; ; ; ; ; In the formula, , , , , All are preset calculation coefficients that are greater than zero. As a preset time base value, As a preset distance base value, The first calculation threshold is... The function value is for the i-th monitoring target point at Within the range Sort by size from largest to smallest and then sum the first preset number of each.

4. The method according to claim 1, characterized in that, The analysis of rainfall monitoring data, temperature monitoring data, and humidity monitoring data within a preset time period determines the time adjustment coefficient, which includes: Let the cumulative historical rainfall value within the preset time period be... The historical peak rainfall was The cumulative historical duration of high rainfall is Historical cumulative humidity value The historical peak humidity was The duration of the high humidity history is The historical peak of temperature change was The duration of the drastic temperature change was The history of drastic temperature changes is particularly long. The equivalent duration of historical temperature changes is The duration adjustment factor is ,but ; ; ; ; In the formula, , , , , , , All are preset calculation coefficients that are greater than zero. To preset historical rainfall, For preset calculation adjustment coefficients and , To preset historical humidity values, To preset historical temperature change values, Preset historical duration.

5. The method according to claim 1, characterized in that, The determination of the monitoring interval duration based on the interval duration base value and the duration adjustment coefficient includes: Let the base value of the interval duration be... The duration adjustment factor is , , These are the upper and lower limits of the preset interval duration range, respectively. To monitor the interval duration, then ; In the formula, , and .

6. The method according to claim 1, characterized in that, The determination of the monitoring interval duration based on the interval duration base value and the duration adjustment coefficient includes: Let the base value of the interval duration be... The duration adjustment factor is , , These are the upper and lower limits of the preset interval duration range, respectively. To monitor the interval duration, then ; In the formula, and All are positive integers and .

7. A slope deformation monitoring system based on millimeter-wave radar (120), characterized in that, The system includes a millimeter-wave radar (120), a server (110), and multiple corner reflectors (130). Each corner reflector (130) is positioned at a monitoring target point on the target slope. The millimeter-wave radar (120) covers all the corner reflectors (130). The millimeter-wave radar (120) and the corner reflectors (130) work together to collect target point location data of the monitoring target points. The server (110) is connected to the millimeter-wave radar (120) and is used to collect target location data of each monitoring target point on the target slope in response to the monitoring trigger signal. The target location data is assigned a timestamp of the collection time and the target point identifier of the corresponding monitoring target point and stored as a target location record. The monitoring interval between the next monitoring trigger signal and the current monitoring trigger signal is determined. The target location data is obtained based on the millimeter-wave radar (120) and the corner reflector (130) configured at the monitoring target point. The server (110) is also used to consume the monitoring interval time based on the clock signal and the equivalent consumption time determined by analyzing the collected rainfall monitoring data, temperature monitoring data and humidity monitoring data of the geographical location of the target slope, starting from the time of occurrence of the current monitoring trigger signal. When the consumption is completed, the next monitoring trigger signal is generated. The equivalent consumption time is positively correlated with the rainfall detection data and humidity monitoring data, and positively correlated with the degree of change of the temperature monitoring data. The server (110) is further configured such that determining the monitoring interval between the next monitoring trigger signal and the current monitoring trigger signal includes: Retrieve target location records within a preset time period, with the occurrence time of the current monitoring trigger signal as the last time. Collect rainfall monitoring data, temperature monitoring data, and humidity monitoring data within a preset time period, with the occurrence time of the current monitoring trigger signal as the last time, of the geographical location of the target slope. The target location records within a preset time period are analyzed to determine the interval time base value. The interval time base value is negatively correlated with the cumulative deformation of the target slope represented by the target location records and the unit time. ; Analyze rainfall monitoring data, temperature monitoring data, and humidity monitoring data within a preset time period to determine a time period adjustment coefficient. The time period adjustment coefficient is negatively correlated with the rainfall monitoring data and humidity monitoring data, and negatively correlated with the degree of change in temperature monitoring data. The monitoring interval duration is determined based on the interval duration base value and the duration adjustment coefficient. The monitoring interval duration is within the preset interval duration range and is positively correlated with the interval duration base value and the duration adjustment coefficient.

8. The system according to claim 7, characterized in that, The server (110) is further configured such that, starting from the occurrence time of the current monitoring trigger signal, the monitoring interval duration is consumed based on a clock signal and an equivalent consumption time determined by analyzing the collected rainfall monitoring data, temperature monitoring data, and humidity monitoring data of the target slope's geographical location, and the generation of the next monitoring trigger signal upon completion of the consumption includes: Analyze the rainfall monitoring data from the current moment to the moment the current monitoring trigger signal occurred to determine the cumulative rainfall, the peak rainfall, and the duration of high cumulative rainfall exceeding the first rainfall threshold. Analyze the humidity monitoring data from the current moment to the moment the current trigger signal was generated to determine the cumulative humidity value, the peak humidity value, and the duration of high humidity exceeding the first humidity threshold; Analyze the temperature monitoring data from the current moment to the moment the current monitoring trigger signal occurs to determine the temperature change data, analyze the temperature change data to determine the temperature change peak, the duration of a drastic temperature change when the temperature change data is higher than a first temperature change threshold, and the special duration of a drastic temperature change when the temperature change data is higher than the first temperature change threshold and the duration of a single occurrence exceeds the first temperature change preset duration. Let the cumulative rainfall value be... The peak rainfall occurred at The cumulative duration of high rainfall was The cumulative humidity value is The peak humidity was The duration of high humidity is The peak temperature change is The duration of the drastic temperature change was The duration of drastic temperature changes is particularly long. The equivalent time consumed for the temperature change is The equivalent consumption time is ,but ; ; ; ; In the formula, , , , , , , All are preset calculation coefficients that are greater than zero. To preset the rainfall amount, To preset the humidity value, To preset the temperature change value, To preset the occurrence duration, The preset unit duration.

9. The system according to claim 7, characterized in that, The server (110) is further configured such that the target location record determination interval base value within the preset analysis time period includes: Assume that the target slope is equipped with Each monitoring target point has a preset time interval before the current monitoring trigger signal occurs. The target location records are as follows: The j-th target location record for the i-th monitored target is... Let the first target location record correspond to the current monitoring trigger signal, and the second target location record... The target location record is the one furthest from the time of the current monitoring trigger signal. Article and Section The time interval between the occurrence times of the corresponding detection trigger signals for each target location is represented as follows: , and The base value of the interval duration is ,but ; ; ; ; ; ; ; In the formula, , , , , All are preset calculation coefficients that are greater than zero. As a preset time base value, As a preset distance base value, The first calculation threshold is... The function value is for the i-th monitoring target point at Within the range Sort by size from largest to smallest and then sum the first preset number of results; And / or the server (110) is further configured such that the determination of the duration adjustment coefficient for analyzing rainfall monitoring data, temperature monitoring data, and humidity monitoring data within a preset duration includes: Let the cumulative historical rainfall value within the preset time period be... The historical peak rainfall was The cumulative historical duration of high rainfall is Historical cumulative humidity value The historical peak humidity was The duration of the high humidity history is The historical peak of temperature change was The duration of the drastic temperature change was The history of drastic temperature changes is particularly long. The equivalent duration of historical temperature changes is The duration adjustment factor is ,but ; ; ; ; In the formula, , , , , , , All are preset calculation coefficients that are greater than zero. To preset historical rainfall, For preset calculation adjustment coefficients and , To preset historical humidity values, To preset historical temperature change values, Preset historical duration.

10. The system according to claim 8, characterized in that, The server (110) is further configured such that determining the monitoring interval duration based on the interval duration base value and the duration adjustment coefficient includes: Let the base value of the interval duration be... The duration adjustment factor is , , These are the upper and lower limits of the preset interval duration range, respectively. To monitor the interval duration, then ; In the formula, , and ; Alternatively, the server (110) may be further configured such that determining the monitoring interval duration based on the interval duration base value and the duration adjustment coefficient includes: Let the base value of the interval duration be... The duration adjustment factor is , , These are the upper and lower limits of the preset interval duration range, respectively. To monitor the interval duration, then ; In the formula, and All are positive integers and .

Images