An intelligent monitoring method and system for slope landslide displacement based on Beidou positioning

Abstract

The present invention relates to the field of slope monitoring technology, and discloses a method and system for intelligent monitoring of slope landslide displacement based on Beidou positioning. The method sets auxiliary marking points in the slope monitoring area and establishes a coordinate system, and at the same time, performs preliminary positioning of the set auxiliary marking points through Beidou satellites, and sets two groups of positioning modes, offline positioning and online positioning; after preliminary positioning, each auxiliary marking point in the slope monitoring area is positioned based on the set offline positioning mode, and the offline positioning information is saved in real time; at the same time, after preliminary positioning, each auxiliary marking point in the slope monitoring area is positioned based on the set online positioning mode, and the online positioning information is saved in real time; finally, the displacement in the slope monitoring area is monitored based on the combination of the saved offline positioning information and the online positioning information, thereby improving the accuracy of intelligent monitoring of slope landslide displacement.

Description

Technical Field

[0001] The present invention relates to the technical field of slope monitoring, and in particular to a method and system for intelligently monitoring the displacement of slopes and landslides based on Beidou positioning. Background Art

[0002] With the accelerated development of water conservancy projects, the protection and monitoring of the environment around water resources has become a focus of attention. However, due to the complex geological conditions of the surrounding environment of water resources, the stability of the project slope is insufficient, the real-time monitoring results are poor, and timely updates and controls cannot be achieved.

[0003] The existing open patent application CN118794363A, the method obtains three-dimensional point cloud data of the slope; determines multiple characteristic monitoring points of the slope by processing the three-dimensional point cloud data; obtains the positioning data of each characteristic monitoring point at the same time; monitors the slope by combining and comparing the three-dimensional point cloud data and the positioning data of each characteristic monitoring point; but because it only focuses on the analysis of a single data source and lacks the fusion and comprehensive utilization of multi-source data, it is difficult to fully and accurately reflect the deformation characteristics and evolution laws of the slope. Summary of the invention

[0004] 1. Technical issues to be resolved

[0005] In view of the shortcomings of the existing technology, the present invention provides a method and system for intelligent monitoring of slope landslide displacement based on Beidou positioning, which has the advantages of real-time, stable and accurate, and solves the problems of insufficient stability of engineering slopes, poor real-time monitoring results, and inability to achieve timely updating and control.

[0006] (II) Technical solution

[0007] In order to solve the technical problems of insufficient stability of the above-mentioned engineering slope, poor real-time monitoring results, and inability to update and control in a timely manner, the present invention provides the following technical solutions:

[0008] The present invention discloses a method for intelligently monitoring the displacement of a slope and landslide based on Beidou positioning, which specifically comprises the following steps:

[0009] S1. Set q auxiliary marking points in the slope monitoring area, and establish a coordinate system based on the set q auxiliary marking points;

[0010] S2. Preliminary positioning of the set q auxiliary marker points is performed through Beidou satellites, and two positioning modes, offline positioning and online positioning, are set;

[0011] S3. After preliminary positioning, each auxiliary marking point in the slope monitoring area is positioned based on the set offline positioning mode, and the offline positioning information is saved in real time;

[0012] S4. After the preliminary positioning, each auxiliary marking point in the slope monitoring area is positioned based on the set online positioning mode, and the online positioning information is saved in real time;

[0013] S5. Based on the stored offline positioning information and the online positioning information, the displacement situation in the slope monitoring area is monitored.

[0014] The present invention sets auxiliary marking points in a slope monitoring area and establishes a coordinate system, and at the same time, preliminarily locates the set auxiliary marking points through Beidou satellites, and sets two groups of positioning modes, namely, offline positioning and online positioning. After the preliminary positioning, each auxiliary marking point in the slope monitoring area is positioned based on the set offline positioning mode, and the offline positioning information is saved in real time. At the same time, after the preliminary positioning, each auxiliary marking point in the slope monitoring area is positioned based on the set online positioning mode, and the online positioning information is saved in real time. Finally, the displacement situation in the slope monitoring area is monitored based on the combination of the saved offline positioning information and the online positioning information, thereby improving the accuracy of intelligent monitoring of slope landslide displacement.

[0015] Preferably, the step of setting q auxiliary marking points in the slope monitoring area and establishing a coordinate system based on the set q auxiliary marking points comprises the following steps:

[0016] S11, based on the set auxiliary marking points, number the q auxiliary marking points q1, q2...q q ;

[0017] S12, taking the auxiliary marking point q1 as the coordinate origin, establishing a coordinate system according to the coordinates of q1, and determining the coordinates of other auxiliary marking points based on the auxiliary marking point q1;

[0018] S13. Save the coordinates of each auxiliary marking point in the system database.

[0019] The present invention completes the preliminary arrangement of the numbering and corresponding positions of the auxiliary marking points by setting the auxiliary marking points in the slope monitoring area and establishing a coordinate system, thereby ensuring the rationality of the setting of the auxiliary marking points.

[0020] Preferably, performing preliminary positioning of the set q auxiliary marking points by using Beidou satellites, and setting two groups of positioning modes of offline positioning and online positioning comprises the following steps:

[0021] S21, regularly collecting measurement values ​​of multiple groups of Beidou satellites for each auxiliary beacon in the slope monitoring area;

[0022] Set the multiple measurement values ​​of the nth auxiliary beacon to ;

[0023] in, represents the first set of measurements of the nth auxiliary beacon, represents the e-th set of measurements of the n-th auxiliary beacon;

[0024] S22. Process the collected measurement values ​​to determine the standard position of each auxiliary beacon in the slope monitoring area.

[0025] Preferably, the processing of the collected measurement values ​​to determine the standard position of each auxiliary beacon in the slope monitoring area comprises the following steps:

[0026] The standard position calculation formula for each auxiliary beacon is as follows:

[0027] ;

[0028] in, represents the Euclidean distance between the nth auxiliary beacon and the jth auxiliary beacon, represents the horizontal coordinate of the nth auxiliary beacon, represents the abscissa of the jth auxiliary beacon, represents the ordinate of the nth auxiliary beacon, represents the ordinate of the jth auxiliary beacon;

[0029] The Euclidean distance between each auxiliary beacon is calculated to determine the standard position of each auxiliary beacon in the slope monitoring area.

[0030] The present invention regularly collects measurement values ​​of various auxiliary beacons in a slope monitoring area from multiple groups of Beidou satellites, and processes the collected measurement values ​​to determine the standard position of each auxiliary beacon in the slope monitoring area, thereby improving the reliability of the standard position of each auxiliary beacon in the slope monitoring area.

[0031] Preferably, after the preliminary positioning, positioning each auxiliary marking point in the slope monitoring area based on the set offline positioning mode and saving the offline positioning information in real time includes the following steps:

[0032] S31, collecting and saving fingerprint information;

[0033] Install a sensor in all auxiliary marking points;

[0034] Randomly select r auxiliary marking points from all auxiliary marking points as reference points, collect sensor signals that can be received at each reference point through the laser radar, and determine the collection range of the laser radar based on the collected sensor signals that can be received;

[0035] After receiving the sensor signal, the laser radar stores a set of data including the position coordinates of the auxiliary marker point, the sensor signal and the auxiliary marker point number into the database;

[0036] A set of data is set as a location fingerprint;

[0037] S32: Positioning based on the stored fingerprint information.

[0038] Preferably, the positioning based on the stored fingerprint information comprises the following steps:

[0039] Set each auxiliary marker fingerprint to be , the position coordinates of each auxiliary marker point are expressed as ;

[0040] in, represents the mth sensor signal received in the ith fingerprint;

[0041] Set the sensor signal received at the point to be positioned to ;

[0042] Then the distance between each auxiliary marking point and the point to be measured is:

[0043] ;

[0044] in, represents the hth sensor signal received in the i-th fingerprint, Indicates the rated value of the sensor signal; when t=1, Represents Manhattan distance, when t=2, represents the Euclidean distance;

[0045] Select The minimum coordinate of the point to be measured is taken as the positioning result of the point to be measured.

[0046] The present invention sets an offline positioning mode, collects sensor information in all auxiliary marking points and sets fingerprint storage, calculates the distance between each auxiliary marking point and the point to be measured based on the stored fingerprint information, and performs offline positioning by calculating the distance, thereby improving the accuracy of offline positioning.

[0047] Preferably, after the preliminary positioning, positioning each auxiliary marking point in the slope monitoring area based on the set online positioning mode and saving the online positioning information in real time includes the following steps:

[0048] S41, collecting image data of the environment in the slope monitoring area in real time based on the laser cameras installed at each auxiliary marking point;

[0049] S42, processing the image data of the environment in the slope monitoring area collected in real time to obtain processed image data;

[0050] Perform noise reduction processing on the image data of the environment in the slope monitoring area collected in real time;

[0051] The noisy image is shown in the formula:

[0052] ;

[0053] in, is the gray value of the noisy image, is the image after denoising, is the noise on the image;

[0054] Set the number of continuous automatic exposure image frames to U, and the image after multi-frame average noise reduction is as shown in the formula:

[0055] ;

[0056] in, Indicates the coordinate position of the pixel point, is the grayscale mean value output at this point, For the l The gray value of the frame image at this position, For the l The gray value of the noise in the frame image at this position, Represents the image after averaging and denoising multiple frames;

[0057] Set the image after multi-frame average noise reduction as the processed image data;

[0058] S43: Estimate the position of each auxiliary marking point based on the processed image data, and perform online positioning.

[0059] Preferably, the estimating the position of each auxiliary marking point based on the processed image data and performing online positioning comprises the following steps:

[0060] Assume that the longitude and latitude of two points in the slope monitoring area are A (lat1, lng1) and B (lat2, lng2), the radius of the earth is R, and the distance between the two points is ;

[0061] ;

[0062] Assume that the longitude and latitude coordinates of the two corresponding points in the processed image data are E(lat3, lng3) and F(lat4, lng4). According to the distance formula between the two points, the distance between EF can be calculated as ;

[0063] Assume the image size is h×w, and the corresponding distance between EF on the image is , the actual size of each pixel on the image , the actual size is obtained according to the ratio of the size on the image to the actual corresponding distance;

[0064] ;

[0065] The actual size of the distance between the auxiliary marking points in the processed image data is calculated as follows:

[0066] ;

[0067] Among them, sum represents the number of pixels between auxiliary marking points, Indicates the actual size of each pixel. The distance between auxiliary marking points;

[0068] Upload the distance between auxiliary markers calculated in real time to BeiDou satellite and save it;

[0069] Based on the distance between the auxiliary marking points calculated in real time, the preliminary positioning coordinates of each auxiliary marking point saved by the Beidou satellite are corrected;

[0070] ;

[0071] in, represents the corrected positioning coordinates, Indicates the horizontal axis correction of the initial positioning coordinates, Indicates the longitudinal axis correction value of the initial positioning coordinates, Indicates the distance change between auxiliary markers calculated in real time.

[0072] The present invention collects image data of the surrounding environment of each auxiliary marking point in the slope monitoring area, processes the real-time collected image data, and estimates the position of each auxiliary marking point based on the processed image data, completes the online positioning of each auxiliary marking point and uploads it, thereby improving the real-time performance of the online positioning.

[0073] Preferably, the monitoring of the displacement in the slope monitoring area based on the combination of the stored offline positioning information and the online positioning information comprises the following steps:

[0074] S51. When the satellite signal is good, the monitoring personnel download the online positioning information of each auxiliary marking point from the Beidou satellite, and verify the online positioning information of each auxiliary marking point through the offline positioning mode based on the downloaded online positioning information of each auxiliary marking point, and set the verification error threshold. When the verification error threshold is exceeded, the average value of the offline positioning information and the online positioning information is calculated, and the calculated average value is set as the standard positioning information, and the slope displacement is calculated based on the standard positioning information;

[0075] S52. When the satellite signal fluctuates, the monitoring personnel randomly download the online positioning information of an auxiliary marker point from the Beidou satellite, and perform offline positioning based on the downloaded auxiliary marker point, and compare the offline positioning result with the previous offline positioning result to calculate the slope displacement.

[0076] The present invention also discloses a slope landslide displacement intelligent monitoring system based on Beidou positioning, which is used to implement a slope landslide displacement intelligent monitoring method based on Beidou positioning. The system includes: a database, a data acquisition module, a preliminary positioning module, an offline positioning module, an online positioning module and a slope displacement monitoring module;

[0077] The database is used to store the position information of each auxiliary marking point;

[0078] The data acquisition module is used to collect the position information of each auxiliary marking point;

[0079] The preliminary positioning module is used to perform preliminary positioning based on the position information of each auxiliary marking point collected;

[0080] The offline positioning module is used to perform offline positioning according to sensor signals, laser radar and preliminary positioning results;

[0081] The online positioning module is used to collect image data of the environment in the slope monitoring area in real time through a laser camera for online positioning, and upload it regularly;

[0082] The slope displacement monitoring module is used to determine the slope displacement situation according to the combination of the offline positioning module and the online positioning module.

[0083] (III) Beneficial effects

[0084] Compared with the prior art, the present invention provides a method and system for intelligent monitoring of slope landslide displacement based on Beidou positioning, which has the following beneficial effects:

[0085] 1. The invention sets auxiliary marking points in the slope monitoring area and establishes a coordinate system, and at the same time, preliminarily locates the set auxiliary marking points through Beidou satellites, and sets two positioning modes: offline positioning and online positioning. After the preliminary positioning, each auxiliary marking point in the slope monitoring area is located based on the set offline positioning mode, and the offline positioning information is saved in real time. At the same time, after the preliminary positioning, each auxiliary marking point in the slope monitoring area is located based on the set online positioning mode, and the online positioning information is saved in real time. Finally, the displacement in the slope monitoring area is monitored based on the combination of the saved offline positioning information and the online positioning information, thereby improving the accuracy of intelligent monitoring of slope landslide displacement.

[0086] 2. The invention completes the preliminary arrangement of the numbering and corresponding positions of the auxiliary marking points by setting up auxiliary marking points and establishing a coordinate system in the slope monitoring area, thereby ensuring the rationality of the setting of the auxiliary marking points.

[0087] 3. The invention regularly collects measurement values ​​of each auxiliary beacon in the slope monitoring area from multiple groups of Beidou satellites, and processes the collected measurement values ​​to determine the standard position of each auxiliary beacon in the slope monitoring area, thereby improving the reliability of the standard position of each auxiliary beacon in the slope monitoring area.

[0088] 4. The invention sets an offline positioning mode, collects sensor information from all auxiliary marking points and sets fingerprint storage, and calculates the distance between each auxiliary marking point and the point to be measured based on the stored fingerprint information, and performs offline positioning by calculating the distance, thereby improving the accuracy of offline positioning.

[0089] 5. The invention collects image data of the surrounding environment of each auxiliary marking point in the slope monitoring area, processes the real-time collected image data, and estimates the position of each auxiliary marking point based on the processed image data, completes the online positioning of each auxiliary marking point and uploads it, thereby improving the real-time performance of online positioning. BRIEF DESCRIPTION OF THE DRAWINGS

[0090] Figure 1 It is a schematic diagram of the structure of the intelligent monitoring process of slope landslide displacement of the present invention. DETAILED DESCRIPTION

[0091] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0092] Example 1

[0093] See also Figure 1 This embodiment discloses a method for intelligent monitoring of slope landslide displacement based on Beidou positioning, which specifically includes the following steps:

[0094] S1. Set q auxiliary marking points in the slope monitoring area, and establish a coordinate system based on the set q auxiliary marking points;

[0095] S2. Preliminary positioning of the set q auxiliary marker points is performed through Beidou satellites, and two positioning modes, offline positioning and online positioning, are set;

[0096] S3. After preliminary positioning, each auxiliary marking point in the slope monitoring area is positioned based on the set offline positioning mode, and the offline positioning information is saved in real time;

[0097] S4. After the preliminary positioning, each auxiliary marking point in the slope monitoring area is positioned based on the set online positioning mode, and the online positioning information is saved in real time;

[0098] S5. Monitoring the displacement of the slope monitoring area based on the stored offline positioning information and the online positioning information;

[0099] For further information, see Figure 1 , setting q auxiliary marking points in the slope monitoring area, and establishing a coordinate system based on the set q auxiliary marking points includes the following steps:

[0100] S11, based on the set auxiliary marking points, number the q auxiliary marking points q1, q2...q q ;

[0101] S12, taking the auxiliary marking point q1 as the coordinate origin, establishing a coordinate system according to the coordinates of q1, and determining the coordinates of other auxiliary marking points based on the auxiliary marking point q1;

[0102] S13, saving the coordinates of each auxiliary marking point in the database of the system;

[0103] For further information, see Figure 1 , using Beidou satellites to preliminarily locate the q auxiliary markers set, and setting two sets of positioning modes, offline positioning and online positioning, includes the following steps:

[0104] S21, regularly collecting measurement values ​​of multiple groups of Beidou satellites for each auxiliary beacon in the slope monitoring area;

[0105] Set the multiple measurement values ​​of the nth auxiliary beacon to ;

[0106] in, represents the first set of measurements of the nth auxiliary beacon, represents the e-th set of measurements of the n-th auxiliary beacon;

[0107] S22, processing the collected measurement values ​​to determine the standard position of each auxiliary beacon in the slope monitoring area;

[0108] The standard position calculation formula for each auxiliary beacon is as follows:

[0109] ;

[0110] in, represents the Euclidean distance between the nth auxiliary beacon and the jth auxiliary beacon, represents the horizontal coordinate of the nth auxiliary beacon, represents the abscissa of the jth auxiliary beacon, represents the ordinate of the nth auxiliary beacon, represents the ordinate of the jth auxiliary beacon;

[0111] Calculate the Euclidean distance between each auxiliary beacon and determine the standard position of each auxiliary beacon in the slope monitoring area;

[0112] For further information, see Figure 1 After the initial positioning, each auxiliary mark point in the slope monitoring area is positioned based on the set offline positioning mode, and the offline positioning information is saved in real time, including the following steps:

[0113] S31, collecting and saving fingerprint information;

[0114] Install a sensor in all auxiliary marking points;

[0115] Randomly select r auxiliary marking points from all auxiliary marking points as reference points, collect sensor signals that can be received at each reference point through the laser radar, and determine the collection range of the laser radar based on the collected sensor signals that can be received;

[0116] Furthermore, after receiving the sensor signal, the laser radar stores a set of data including the position coordinates of the auxiliary marking point, the sensor signal and the auxiliary marking point number into a database;

[0117] A set of data is set as a location fingerprint;

[0118] S32, positioning based on the stored fingerprint information;

[0119] Set each auxiliary marker fingerprint to be , the position coordinates of each auxiliary marker point are expressed as ;

[0120] in, represents the mth sensor signal received in the ith fingerprint;

[0121] Set the sensor signal received at the point to be positioned to ;

[0122] Then the distance between each auxiliary marking point and the point to be measured is:

[0123] ;

[0124] in, represents the hth sensor signal received in the i-th fingerprint, Indicates the rated value of the sensor signal; when t=1, Represents Manhattan distance, when t=2, represents the Euclidean distance;

[0125] Furthermore, select The minimum coordinate of the point to be measured is taken as the positioning result of the point to be measured;

[0126] For further information, see Figure 1 After the initial positioning, each auxiliary mark point in the slope monitoring area is positioned based on the set online positioning mode, and the online positioning information is saved in real time, including the following steps:

[0127] S41, collecting image data of the environment in the slope monitoring area in real time based on the laser cameras installed at each auxiliary marking point;

[0128] S42, processing the image data of the environment in the slope monitoring area collected in real time to obtain processed image data;

[0129] Perform noise reduction processing on the image data of the environment in the slope monitoring area collected in real time;

[0130] The noisy image is shown in the formula:

[0131] ;

[0132] in, is the gray value of the noisy image, is the image after denoising, is the noise on the image;

[0133] Set the number of continuous automatic exposure image frames to U, and the image after multi-frame average noise reduction is as shown in the formula:

[0134] ;

[0135] in, Indicates the coordinate position of the pixel point, is the grayscale mean value output at this point, For the l The gray value of the frame image at this position, For the l The gray value of the noise in the frame image at this position, Represents the image after averaging and denoising multiple frames;

[0136] Further, the image after the average noise reduction of multiple frames is set as the processed image data;

[0137] S43, estimating the position of each auxiliary marking point based on the processed image data, and performing online positioning;

[0138] Assume that the longitude and latitude of two points in the slope monitoring area are A (lat1, lng1) and B (lat2, lng2), the radius of the earth is R, and the distance between the two points is ;

[0139] ;

[0140] Assume that the longitude and latitude coordinates of the two corresponding points in the processed image data are E(lat3, lng3) and F(lat4, lng4). According to the distance formula between the two points, the distance between EF can be calculated as ;

[0141] Assume the image size is h×w, and the corresponding distance between EF on the image is , the actual size of each pixel on the image , the actual size is obtained according to the ratio of the size on the image to the actual corresponding distance;

[0142] ;

[0143] Furthermore, the actual size of the distance between the auxiliary marking points in the processed image data is calculated as follows:

[0144] ;

[0145] Among them, sum represents the number of pixels between auxiliary marking points, Indicates the actual size of each pixel. The distance between auxiliary marking points;

[0146] Furthermore, the distances between the auxiliary marking points calculated in real time are uploaded to the BeiDou satellite and saved;

[0147] Further, the preliminary positioning coordinates of each auxiliary marking point stored by the Beidou satellite are corrected based on the distances between the auxiliary marking points calculated in real time;

[0148] ;

[0149] in, represents the corrected positioning coordinates, Indicates the horizontal axis correction of the initial positioning coordinates, Indicates the longitudinal axis correction value of the initial positioning coordinates, Indicates the distance change between auxiliary marking points calculated in real time;

[0150] For further information, see Figure 1 , based on the stored offline positioning information and the online positioning information, the displacement situation in the slope monitoring area is monitored, including the following steps:

[0151] S51. When the satellite signal is good, the monitoring personnel download the online positioning information of each auxiliary marking point from the Beidou satellite, and verify the online positioning information of each auxiliary marking point through the offline positioning mode based on the downloaded online positioning information of each auxiliary marking point, and set the verification error threshold. When the verification error threshold is exceeded, the average value of the offline positioning information and the online positioning information is calculated, and the calculated average value is set as the standard positioning information, and the slope displacement is calculated based on the standard positioning information;

[0152] S52. When the satellite signal fluctuates, the monitoring personnel randomly downloads online positioning information of an auxiliary marker point from the Beidou satellite, and performs offline positioning based on the downloaded auxiliary marker point, and compares the offline positioning result with the previous offline positioning result to calculate the slope displacement;

[0153] Example 2

[0154] See also Figure 1 , this embodiment also discloses a slope landslide displacement intelligent monitoring system based on Beidou positioning, which is used to implement a slope landslide displacement intelligent monitoring method based on Beidou positioning. The system includes: a database, a data acquisition module, a preliminary positioning module, an offline positioning module, an online positioning module and a slope displacement monitoring module;

[0155] The database is used to store the position information of each auxiliary marking point;

[0156] The data acquisition module is used to collect the position information of each auxiliary marking point;

[0157] The preliminary positioning module is used to perform preliminary positioning based on the position information of each auxiliary marking point collected;

[0158] The offline positioning module is used to perform offline positioning according to sensor signals, laser radar and preliminary positioning results;

[0159] The online positioning module is used to collect image data of the environment in the slope monitoring area in real time through a laser camera for online positioning, and upload it regularly;

[0160] The slope displacement monitoring module is used to determine the slope displacement situation according to the combination of the offline positioning module and the online positioning module.

[0161] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A method for intelligent monitoring of slope landslide displacement based on Beidou positioning, characterized in that: The following steps are involved: S1. Set q auxiliary marking points in the slope monitoring area, and establish a coordinate system based on the set q auxiliary marking points; S2. Preliminary positioning of the set q auxiliary marker points is performed through Beidou satellites, and two positioning modes, offline positioning and online positioning, are set; S3. After preliminary positioning, each auxiliary marking point in the slope monitoring area is positioned based on the set offline positioning mode, and the offline positioning information is saved in real time; The S3 comprises the following steps: S31, collecting and saving fingerprint information; Install a sensor in all auxiliary marking points; Randomly select r auxiliary marking points from all auxiliary marking points as reference points, collect sensor signals that can be received at each reference point through the laser radar, and determine the collection range of the laser radar based on the collected sensor signals that can be received; After receiving the sensor signal, the laser radar stores a set of data including the position coordinates of the auxiliary marker point, the sensor signal and the auxiliary marker point number into the database; A set of data is set as a location fingerprint; S32, positioning based on the stored fingerprint information; S4. After the preliminary positioning, each auxiliary marking point in the slope monitoring area is positioned based on the set online positioning mode, and the online positioning information is saved in real time; The S4 comprises the following steps: S41, collecting image data of the environment in the slope monitoring area in real time based on the laser cameras installed at each auxiliary marking point; S42, processing the image data of the environment in the slope monitoring area collected in real time to obtain processed image data; Perform noise reduction processing on the image data of the environment in the slope monitoring area collected in real time; The noisy image is shown in the formula: g(α,β)=f(α,β)+a(α,β); Among them, g(α,β) is the gray value of the noisy image, f(α,β) is the denoised image, and a(α,β) is the noise on the image; Set the number of continuous automatic exposure image frames to U, and the image after multi-frame average noise reduction is as shown in the formula: Among them, (α, β) represents the coordinate position of the pixel point, is the grayscale mean value output at this point, g l (α, β) is the gray value of the l-th frame image at this position, a l (α, β) is the gray value of the noise in the l-th frame image at this position, Represents the image after averaging and denoising multiple frames; Set the image after multi-frame average noise reduction as the processed image data; S43, estimating the position of each auxiliary marking point based on the processed image data, and performing online positioning; S5. Based on the stored offline positioning information and the online positioning information, the displacement situation in the slope monitoring area is monitored.

2. The method for intelligent monitoring of slope landslide displacement based on Beidou positioning according to claim 1 is characterized in that: The method of setting q auxiliary marking points in the slope monitoring area and establishing a coordinate system based on the set q auxiliary marking points includes the following steps: S11, based on the set auxiliary marking points, number the q auxiliary marking points q1, q2...q q ; S12, taking the auxiliary marking point q1 as the coordinate origin, establishing a coordinate system according to the coordinates of q1, and determining the coordinates of other auxiliary marking points based on the auxiliary marking point q1; S13. Save the coordinates of each auxiliary marking point in the system database.

3. The method for intelligent monitoring of slope landslide displacement based on Beidou positioning according to claim 1 is characterized in that: The method of performing preliminary positioning of the set q auxiliary marking points by using Beidou satellites and setting two sets of positioning modes, namely, offline positioning and online positioning, comprises the following steps: S21, regularly collecting measurement values ​​of multiple groups of Beidou satellites for each auxiliary beacon in the slope monitoring area; Set the multiple measurement values ​​of the nth auxiliary beacon to [C n1 ,C n2 ,...,C ne ]; Among them, C n1 represents the first set of measurements of the nth auxiliary beacon, C ne represents the e-th set of measurements of the n-th auxiliary beacon; S22. Process the collected measurement values ​​to determine the standard position of each auxiliary beacon in the slope monitoring area.

4. The method for intelligent monitoring of slope landslide displacement based on Beidou positioning according to claim 3 is characterized in that: The processing of the collected measurement values ​​to determine the standard position of each auxiliary beacon in the slope monitoring area includes the following steps: The standard position calculation formula for each auxiliary beacon is as follows: Among them, D nj represents the Euclidean distance between the nth auxiliary beacon and the jth auxiliary beacon, x n Indicates the horizontal coordinate of the nth auxiliary beacon, x j represents the horizontal coordinate of the jth auxiliary beacon, y n Indicates the ordinate of the nth auxiliary beacon, y j represents the ordinate of the jth auxiliary beacon; The Euclidean distance between each auxiliary beacon is calculated to determine the standard position of each auxiliary beacon in the slope monitoring area.

5. The method for intelligent monitoring of slope landslide displacement based on Beidou positioning according to claim 1 is characterized in that: The positioning based on the stored fingerprint information includes the following steps: Set each auxiliary marker fingerprint to be F{RS1 i ,RS2 i ,...,RS i m }, the position coordinates of each auxiliary marker point are expressed as L z (x z ,y z ); Among them, RS i m represents the mth sensor signal received in the ith fingerprint; Assume that the sensor signal received at the point to be located is M{RS1,RS2,...,RS m }; Then the distance between each auxiliary marking point and the point to be measured is: in, represents the hth sensor signal received in the i-th fingerprint, RS represents the rated value of the sensor signal; when t = 1, D i represents the Manhattan distance. When t = 2, D i represents the Euclidean distance; Select D i The minimum coordinate of the point to be measured is taken as the positioning result of the point to be measured.

6. The method for intelligent monitoring of slope landslide displacement based on Beidou positioning according to claim 1 is characterized in that: The process of estimating the position of each auxiliary marking point based on the processed image data and performing online positioning comprises the following steps: Assume that the longitude and latitude of two points in the slope monitoring area are A (lat1, lng1) and B (lat2, lng2), the radius of the earth is R, and the distance between the two points is DL1; The longitude and latitude coordinates of the two corresponding points in the processed image data are set to E(lat3, lng3) and F(lat4, lng4). According to the distance formula between the two points, the distance between EF can be calculated to be DL2; Set the image size to h×w, the distance between EF on the image to DL3, and the actual size of each pixel on the image to V. The actual size is obtained based on the ratio of the size on the image to the actual corresponding distance. The actual size of the distance between the auxiliary marking points in the processed image data is calculated as follows: DL = V × sum; Among them, sum represents the number of pixels between auxiliary marking points, V represents the actual size corresponding to each pixel, and the distance between DL auxiliary marking points; Upload the distance between auxiliary markers calculated in real time to BeiDou satellite and save it; Based on the distance between the auxiliary marking points calculated in real time, the preliminary positioning coordinates of each auxiliary marking point saved by the Beidou satellite are corrected; Δ(X,Y)=(X+ΔDL,Y+ΔDL); Among them, Δ(X,Y) represents the corrected positioning coordinates, X+ΔDL represents the horizontal axis correction amount of the preliminary positioning coordinates, Y+ΔDL represents the vertical axis correction amount of the preliminary positioning coordinates, and ΔDL represents the distance change between the auxiliary marking points calculated in real time.

7. The method for intelligent monitoring of slope landslide displacement based on Beidou positioning according to claim 1 is characterized in that: The combined monitoring of the displacement in the slope monitoring area based on the stored offline positioning information and the online positioning information comprises the following steps: S51. When the satellite signal is good, the monitoring personnel download the online positioning information of each auxiliary marking point from the Beidou satellite, and verify the online positioning information of each auxiliary marking point through the offline positioning mode based on the downloaded online positioning information of each auxiliary marking point, and set the verification error threshold. When the verification error threshold is exceeded, the average value of the offline positioning information and the online positioning information is calculated, and the calculated average value is set as the standard positioning information, and the slope displacement is calculated based on the standard positioning information; S52. When the satellite signal fluctuates, the monitoring personnel randomly download the online positioning information of an auxiliary marker point from the Beidou satellite, and perform offline positioning based on the downloaded auxiliary marker point, and compare the offline positioning result with the previous offline positioning result to calculate the slope displacement.

8. A system for implementing the intelligent monitoring method for slope landslide displacement based on Beidou positioning as described in any one of claims 1 to 7, characterized in that: It includes database, data acquisition module, preliminary positioning module, offline positioning module, online positioning module and slope displacement monitoring module; The database is used to store the position information of each auxiliary marking point; The data acquisition module is used to collect the position information of each auxiliary marking point; The preliminary positioning module is used to perform preliminary positioning based on the position information of each auxiliary marking point collected; The offline positioning module is used to perform offline positioning according to sensor signals, laser radar and preliminary positioning results; The online positioning module is used to collect image data of the environment in the slope monitoring area in real time through a laser camera for online positioning, and upload it regularly; The slope displacement monitoring module is used to determine the slope displacement situation according to the combination of the offline positioning module and the online positioning module.

Images