CN115077394A - Power station dam slope displacement detection method and device and electronic equipment - Google Patents
Power station dam slope displacement detection method and device and electronic equipment Download PDFInfo
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Abstract
The invention provides a method and a device for detecting the displacement of a side slope of a dam of a power station and electronic equipment, wherein the method comprises the following steps: acquiring a first view image by using an unmanned aerial vehicle in a close-up photography mode; performing aerial triangulation to determine first three-dimensional coordinate data; establishing a digital surface model corresponding to a pixel point in a first view image; setting a flight path and shooting parameters of the unmanned aerial vehicle; the unmanned aerial vehicle acquires a second view image; calculating second three-dimensional coordinate data; establishing a three-dimensional point cloud model; determining three-dimensional point cloud data; and analyzing the difference between the three-dimensional point cloud data at different times to determine the displacement offset of the power station dam slope. According to the invention, data are acquired by an unmanned aerial vehicle close to photography, so that high-precision data automatic acquisition is realized; the difference between three-dimensional point cloud data at different time is calculated by analyzing the distance from the point cloud to the three-dimensional grid plane, the displacement offset of the power station dam side slope is determined, and large-range, high-precision and high-accuracy side slope displacement detection is realized.
Description
Technical Field
The invention relates to the technical field of side slope displacement detection, in particular to a method and a device for detecting the side slope displacement of a power station dam and electronic equipment.
Background
The hydropower station dam side slope is one of major risk sources of hydropower engineering, rapid and high-precision patrol and inspection investigation is carried out on the hydropower station dam side slope, the change of the landform and the landform of the side slope can be timely acquired, and meanwhile early warning and monitoring can be carried out on natural disasters. Due to the limitation of the topographic position of the high side slope close to the dam, the traditional manual investigation method has the problems of low efficiency, poor precision, high danger coefficient, high monitoring difficulty and the like.
In the traditional method for monitoring the automatic deformation of the side slope of the dam of the hydropower station, only local displacement change monitoring can be carried out on the side slope by adopting an inclinometer method; the method adopting the ground radar is influenced by factors such as weather, flood discharge and the like, and is not suitable for hydropower station environments with various environments; although the method adopting three-dimensional laser scanning has high precision, scanning dead angles are easy to generate, and point cloud data needs to be spliced, so that the precision of a point cloud model is reduced. The conventional monitoring method is difficult to realize quick, comprehensive and accurate inspection of the side slope of the dam of the hydropower station, is not beneficial to providing effective and reliable monitoring data for dam region managers, is not beneficial to judging the stability of the side slope and influences the safe and stable operation of the hydropower station.
Disclosure of Invention
In order to solve the problems, the invention provides a method and a device for detecting the displacement of a side slope of a power station dam and electronic equipment.
The embodiment of the invention is realized by the following technical scheme:
in a first aspect, the present disclosure provides a method for detecting displacement of a side slope of a power station dam, comprising the following steps:
collecting a first view image of a power station dam slope by using an unmanned aerial vehicle close-up photography mode, and acquiring geographic position information of pixel points of the first view image;
performing aerial triangulation on the pixel points of the first view image according to the geographic position information, and determining first three-dimensional coordinate data corresponding to the pixel points in the first view image;
establishing a digital surface model corresponding to a pixel point in the first view image according to the first three-dimensional coordinate data;
setting a flight path of the unmanned aerial vehicle by using the digital surface model, and setting shooting parameters;
acquiring positioning data of the unmanned aerial vehicle, wherein the unmanned aerial vehicle acquires a second view image according to the flight path and shooting parameters of the unmanned aerial vehicle;
extracting feature points of the second view image, and calculating second three-dimensional coordinate data of the feature points;
establishing a three-dimensional point cloud model according to the shooting parameters, the positioning data and the second three-dimensional coordinate data;
determining three-dimensional point cloud data according to the three-dimensional point cloud model;
and acquiring the three-dimensional point cloud data at different times, analyzing the difference between the three-dimensional point cloud data at different times, and determining the displacement offset of the power station dam slope.
In a second aspect, the present disclosure provides a power station dam slope displacement detection device, including: the device comprises a collecting unit, a measuring unit, a first model establishing unit, a setting unit, an obtaining unit, a processing unit, a second model establishing unit, a determining unit and an analyzing unit;
the acquisition unit is used for acquiring a first view image of a power station dam slope by using an unmanned aerial vehicle close-up photography mode and acquiring geographic position information of pixel points of the first view image;
the measuring unit is used for carrying out aerial triangulation on the pixel points of the first view image according to the geographic position information and determining first three-dimensional coordinate data corresponding to the pixel points in the first view image;
the first model establishing unit is used for establishing a digital surface model corresponding to a pixel point in the first view image according to the first three-dimensional coordinate data;
the setting unit is used for setting a flight path of the unmanned aerial vehicle by using the digital surface model and setting shooting parameters;
the acquisition unit is used for acquiring positioning data of the unmanned aerial vehicle, and the unmanned aerial vehicle acquires a second view image according to the flight path and shooting parameters of the unmanned aerial vehicle;
the processing unit is used for extracting the characteristic points of the second view image and calculating second three-dimensional coordinate data of the characteristic points;
the second model establishing unit is used for establishing a three-dimensional point cloud model according to the shooting parameters, the positioning data and the second three-dimensional coordinate data;
the determining unit is used for determining three-dimensional point cloud data according to the three-dimensional point cloud model;
the analysis unit is used for acquiring the three-dimensional point cloud data at different times, analyzing the difference between the three-dimensional point cloud data at different times and determining the displacement offset of the power station dam slope.
In a third aspect, the present disclosure provides an electronic device, comprising:
a processor and a memory;
the memory is used for storing computer operation instructions;
and the processor is used for executing the power station dam slope displacement detection method by calling the computer operation instruction.
The invention has the beneficial effects that: according to the invention, data are acquired by an unmanned aerial vehicle close to photography, so that high-precision data automatic acquisition is realized; constructing a three-dimensional live-action scene by using a digital surface model to realize the flight path planning of the unmanned aerial vehicle, so that the unmanned aerial vehicle automatically navigates according to the set shooting parameters and the set air route; the three-dimensional point cloud model is utilized to generate three-dimensional point cloud data, so that a high-precision and high-accuracy measurement result can be obtained; and calculating the difference between three-dimensional point cloud data at different times according to the distance from the point cloud to the three-dimensional grid plane, determining the displacement offset of the side slope of the power station dam, and realizing large-range, high-precision and high-accuracy side slope displacement detection.
On the basis of the technical scheme, the invention can be improved as follows.
Further, the step of obtaining the three-dimensional point cloud data at different times, analyzing the difference between the three-dimensional point cloud data at different times, and determining the displacement of the power station dam slope comprises the following steps:
acquiring the three-dimensional point cloud data at initial time as reference data, and acquiring the three-dimensional point cloud data after set time as comparison data;
clipping the reference data and the comparison data according to the same range;
fitting the discrete point clouds in the reference data into a three-dimensional grid plane;
and calculating the distance from the point cloud in the comparison data to the adjacent three-dimensional grid plane to obtain the displacement offset of the point cloud of the power station dam slope after the initial time and the set time.
The method has the advantages that the three-dimensional point cloud data at the initial time is compared with the three-dimensional point cloud data after the set time is obtained, the data are cut according to the same range, the slope displacement analysis is guaranteed to be compared in the same range, and the consistency of the comparison range is guaranteed; the point cloud scattered in the reference data is fitted into the three-dimensional grid plane, and the distance from the point cloud in the comparison data to the adjacent three-dimensional grid plane is calculated, so that the displacement of two time points of the slope can be calculated more stably and accurately.
Further, the determining the displacement offset of the power station dam slope further comprises: and obtaining a distance distribution map of the point cloud according to the displacement offset of the point cloud.
The beneficial effect of adopting above-mentioned further scheme is that, can be visual with the displacement offset of point cloud through the distance distribution map, be favorable to managers to carry out quick judgement to the stability of side slope.
Further, the method for acquiring the positioning data of the unmanned aerial vehicle is a real-time dynamic carrier phase difference method.
The beneficial effect who adopts above-mentioned further scheme is that, adopts real-time dynamic carrier phase difference method can carry out high accuracy location to unmanned aerial vehicle.
Further, the method for extracting the feature points of the second view image comprises: and extracting the feature points of the second view image by using an accelerated robust feature algorithm.
The beneficial effect of adopting the further scheme is that the characteristic points of the view image can be effectively extracted by accelerating the robust characteristic algorithm.
Further, the determining three-dimensional point cloud data according to the three-dimensional point cloud model includes:
and performing dense reconstruction on the three-dimensional point cloud model by using an MVS algorithm, performing pixel-by-pixel matching on each second view image of the collected multi-view, and regenerating the three-dimensional coordinates of each pixel point to obtain three-dimensional point cloud data.
The method has the advantages that dense reconstruction is carried out on the three-dimensional point cloud model through the MVS algorithm, pixel-by-pixel matching is carried out on the collected second view images with multiple visual angles, three-dimensional coordinates of each pixel are generated through reconstruction, and three-dimensional point cloud data are obtained.
Further, the shooting parameters comprise shooting angles, shooting effective pixels, shooting apertures, shooting focal lengths and pixel sizes.
The beneficial effect of adopting the further scheme is that the quality of the view image is favorably improved by setting the shooting parameters.
Drawings
Fig. 1 is a flowchart of a method for detecting displacement of a side slope of a power station dam according to embodiment 1 of the present invention;
FIG. 2 (a) is a schematic diagram illustrating the calculation of the distance between a point cloud and an adjacent three-dimensional mesh plane in embodiment 1 of the present invention;
FIG. 2 (b) is a schematic diagram illustrating the calculation of the distance from a point cloud to an adjacent point cloud in a conventional manner;
fig. 3 is a schematic diagram of a power station dam slope displacement detection device according to embodiment 2 of the present invention;
fig. 4 is a schematic diagram of an electronic device according to embodiment 3 of the present invention;
FIG. 5 is a schematic diagram of the distribution of the reference point clouds obtained before the displacement of two test blocks in the verification experiment;
FIG. 6 is a schematic diagram of the distribution of the reference point cloud after horizontal displacement and vertical displacement in the verification experiment;
FIG. 7 is a schematic diagram of a comparison point cloud region after a test block is horizontally displaced in a verification experiment;
FIG. 8 is a schematic diagram of a comparison point cloud region after a test block is vertically displaced in a verification experiment;
FIG. 9 is a statistical graph of the distribution of displacement offsets of point clouds before and after horizontal displacement of a proof test block;
FIG. 10 is a statistical graph of the distribution of displacement offsets of point clouds of test blocks before and after vertical displacement in a verification experiment;
fig. 11 (c) is a side slope three-dimensional model diagram collected for the first time in the verification experiment;
FIG. 11 (d) is a diagram of a slope point cloud model acquired for the first time in a verification experiment;
fig. 11 (e) is a diagram of a slope three-dimensional model collected for the second time in the verification experiment;
fig. 11 (f) is a diagram of a slope point cloud model acquired for the second time in the verification experiment;
FIG. 11 (g) is a schematic diagram of point cloud space superposition in a verification experiment;
fig. 12 is a statistical diagram of point cloud displacement offset in a verification experiment.
Icon: 40-an electronic device; 410-a processor; 420-a bus; 430-a memory; 440-a transceiver.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. The components of embodiments of the present invention generally described and illustrated in the figures herein may be arranged and designed in a wide variety of different configurations.
Example 1
As an embodiment, as shown in fig. 1, to solve the above technical problem, the present embodiment provides a method for detecting displacement of a side slope of a power station dam, including the following steps:
collecting a first view image of a power station dam slope by using an unmanned aerial vehicle close-up photography mode, and acquiring geographic position information of pixel points of the first view image;
performing aerial triangulation on the pixel points of the first view image according to the geographic position information, and determining first three-dimensional coordinate data corresponding to the pixel points in the first view image;
establishing a Digital Surface Model (Digital Surface Model-DSM) corresponding to the pixel points in the first view image according to the first three-dimensional coordinate data; carrying out fine unmanned aerial vehicle track planning close to photography on a DSM model, and generating track points with set shooting parameters;
setting a flight path of the unmanned aerial vehicle by using the digital surface model, and setting shooting parameters;
acquiring positioning data of the unmanned aerial vehicle, wherein the unmanned aerial vehicle acquires a second view image according to the flight path and shooting parameters of the unmanned aerial vehicle; the unmanned aerial vehicle flies according to the set flight path in an automatic flying mode to obtain a second view image with higher quality;
extracting feature points of the second view image, and calculating second three-dimensional coordinate data of the feature points;
establishing a three-dimensional point cloud model according to the shooting parameters, the positioning data and the second three-dimensional coordinate data;
determining three-dimensional point cloud data according to the three-dimensional point cloud model;
and acquiring the three-dimensional point cloud data at different times, analyzing the difference between the three-dimensional point cloud data at different times, and determining the displacement offset of the power station dam slope.
According to the invention, data are acquired by an unmanned aerial vehicle close to photography, so that high-precision data automatic acquisition is realized; constructing a three-dimensional live-action scene by using a digital surface model to realize the flight path planning of the unmanned aerial vehicle, so that the unmanned aerial vehicle automatically navigates according to the set shooting parameters and the set air route; the three-dimensional point cloud model is utilized to generate three-dimensional point cloud data, so that a high-precision and high-accuracy measurement result can be obtained; and calculating the difference between three-dimensional point cloud data at different times according to the distance from the point cloud to the three-dimensional grid plane, determining the displacement offset of the side slope of the power station dam, and realizing large-range, high-precision and high-accuracy side slope displacement detection.
Optionally, the obtaining the three-dimensional point cloud data at different times, analyzing the difference between the three-dimensional point cloud data at different times, and determining the displacement of the power station dam slope includes:
acquiring the three-dimensional point cloud data at initial time as reference data, and acquiring the three-dimensional point cloud data after set time as comparison data;
clipping the reference data and the comparison data according to the same range;
fitting the discrete point clouds in the reference data into a three-dimensional grid plane;
and calculating the distance from the point cloud in the comparison data to the adjacent three-dimensional grid plane to obtain the displacement offset of the point cloud of the power station dam slope after the initial time and the set time.
In the practical application process, because the point cloud data has the characteristics of disorder and sparsity, and the traditional method for calculating the distance from the point cloud to the point cloud has low accuracy, the invention provides a method for calculating the distance from the point cloud in the three-dimensional point cloud data to the adjacent three-dimensional grid plane after the set time, and as shown in a schematic diagram of the principle shown in fig. 2 (a), the distance calculation formula is as follows:
in the formula (I), the compound is shown in the specification,
representing the distance of the point cloud to the adjacent three-dimensional mesh plane,
representing a point cloud
The coordinates of the direction are shown in the figure,
representing a point cloud
The coordinates of the direction are shown in the figure,
representing a point cloud
The directional coordinates, Ax + By + Cz + D =0, represent a plane in three dimensions of space, A, B, C, D being a constant coefficient of the three-dimensional mesh plane in the reference data. Fig. 2 (b) is a schematic diagram illustrating the calculation of the distance from the point cloud P1 to the neighboring point cloud in the conventional manner. L1 denotes the measured distance, L2 denotes the actual distance, and E1, E2 denote the deviation of the actual distance from the measured distance.
The three-dimensional point cloud data at the initial time is compared with the three-dimensional point cloud data after the set time is obtained, and the data are cut according to the same range, so that the slope displacement analysis is ensured to be compared in the same range, and the consistency of the comparison range is ensured; the point cloud scattered in the reference data is fitted into the three-dimensional grid plane, and the distance from the point cloud in the comparison data to the adjacent three-dimensional grid plane is calculated, so that the displacement of two time points of the slope can be calculated more stably and accurately.
Optionally, the determining the displacement offset of the power station dam slope further includes: and obtaining a distance distribution map of the point cloud according to the displacement offset of the point cloud.
In the practical application process, the displacement offset of the point cloud can be visualized through the distance distribution map, and the rapid judgment of the slope stability by managers is facilitated.
Optionally, the method for acquiring the positioning data of the unmanned aerial vehicle is a real-time dynamic carrier phase difference method.
In the practical application process, the real-time dynamic carrier phase difference method is adopted to carry out high-precision positioning on the unmanned aerial vehicle.
Optionally, the method for extracting the feature points of the second view image includes: and extracting the feature points of the second view image by using an accelerated robust feature algorithm.
In the practical application process, the characteristic points of the view image can be effectively extracted by accelerating the robust characteristic algorithm.
Optionally, the determining three-dimensional point cloud data according to the three-dimensional point cloud model includes:
and performing dense reconstruction on the three-dimensional point cloud model by using an MVS algorithm, performing pixel-by-pixel matching on each second view image of the collected multi-view, and regenerating the three-dimensional coordinates of each pixel to obtain three-dimensional point cloud data.
In the practical application process, dense reconstruction is carried out on the three-dimensional point cloud model through an MVS algorithm, pixel-by-pixel matching is carried out on the collected multi-view second view image, the three-dimensional coordinates of each pixel are generated through reconstruction, and three-dimensional point cloud data are obtained.
Optionally, the shooting parameters include a shooting angle, a shooting effective pixel, a shooting aperture, a shooting focal length, and a pixel size.
In the practical application process, the quality of the view image is favorably improved by setting the shooting parameters.
Example 2
As an embodiment, as shown in fig. 3, to solve the above technical problem, the present embodiment provides a power station dam slope displacement detecting device, including: the device comprises a collecting unit, a measuring unit, a first model establishing unit, a setting unit, an obtaining unit, a processing unit, a second model establishing unit, a determining unit and an analyzing unit;
the acquisition unit is used for acquiring a first view image of the power station dam slope by using an unmanned aerial vehicle close-up photography mode and acquiring geographic position information of pixel points of the first view image;
the measuring unit is used for carrying out aerial triangulation on the pixel points of the first view image according to the geographic position information and determining first three-dimensional coordinate data corresponding to the pixel points in the first view image;
the first model establishing unit is used for establishing a digital surface model corresponding to a pixel point in the first view image according to the first three-dimensional coordinate data;
the setting unit is used for carrying out track setting on the unmanned aerial vehicle by utilizing the digital surface model and setting shooting parameters; optionally, the shooting parameters include a shooting angle, a shooting effective pixel, a shooting aperture, a shooting focal length, and a pixel size.
The acquisition unit is used for acquiring positioning data of the unmanned aerial vehicle, and the unmanned aerial vehicle acquires a second view image according to the flight path and shooting parameters of the unmanned aerial vehicle; optionally, the method for acquiring the positioning data of the unmanned aerial vehicle is a real-time dynamic carrier phase difference method.
The processing unit is used for extracting the characteristic points of the second view image and calculating second three-dimensional coordinate data of the characteristic points; optionally, the method for extracting the feature points of the second view image includes: and extracting the feature points of the second view image by using an accelerated robust feature algorithm.
The second model establishing unit is used for establishing a three-dimensional point cloud model according to the shooting parameters, the positioning data and the second three-dimensional coordinate data;
the determining unit is used for determining three-dimensional point cloud data according to the three-dimensional point cloud model;
and the analysis unit is used for acquiring the three-dimensional point cloud data at different times, analyzing the difference between the three-dimensional point cloud data at different times and determining the displacement offset of the side slope of the power station dam.
Optionally, the analysis unit includes a second obtaining unit, a third obtaining unit, a data clipping unit, a fitting unit, and a calculation processing unit:
the second acquisition unit is used for acquiring three-dimensional point cloud data of initial time as reference data;
the third acquisition unit is used for acquiring the three-dimensional point cloud data after the set time as comparison data;
the data clipping unit is used for clipping the reference data and the comparison data according to the same range;
the fitting unit is used for fitting the scattered point cloud in the reference data into a three-dimensional grid plane;
and the calculation processing unit is used for calculating the distance from the point cloud in the comparison data to the adjacent three-dimensional grid plane to obtain the displacement offset of the point cloud of the dam slope of the power station after the initial time and the set time.
Optionally, the calculation processing unit further includes a visualized content processing unit, configured to obtain a distance distribution map of the point cloud according to the displacement offset of the point cloud.
Optionally, the determining unit includes:
the reconstruction unit is used for performing dense reconstruction on the three-dimensional point cloud model by utilizing an MVS algorithm;
and the matching unit is used for matching the collected second view images with multiple visual angles pixel by pixel, and regenerating the three-dimensional coordinates of each pixel to obtain three-dimensional point cloud data.
Example 3
Based on the same principle as the method shown in the embodiment of the present invention, an embodiment of the present invention further provides an electronic device, as shown in fig. 4, which may include but is not limited to: a processor and a memory; a memory for storing a computer program; a processor for executing the method according to any of the embodiments of the present invention by calling a computer program.
In an alternative embodiment, an electronic device is provided, the electronic device 40 shown in fig. 4 comprising: a processor 410 and a memory 430. Wherein processor 410 is coupled to memory 430, such as via bus 420.
Optionally, the electronic device 40 may further include a transceiver 440, and the transceiver 440 may be used for data interaction between the electronic device and other electronic devices, such as transmission of data and/or reception of data. It should be noted that the transceiver 440 is not limited to one in practical applications, and the structure of the electronic device 40 is not limited to the embodiment of the present invention.
The Processor 410 may be a CPU (Central Processing Unit), a general-purpose Processor, a DSP (Digital Signal Processor), an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array) or other Programmable logic device, a transistor logic device, a hardware component, or any combination thereof. Which may implement or perform the various illustrative logical blocks, modules, and circuits described in connection with the disclosure. The processor 410 may also be a combination of computing functions, e.g., comprising one or more microprocessors, a combination of a DSP and a microprocessor, or the like.
The Memory 430 may be a ROM (Read Only Memory) or other type of static storage device that can store static information and instructions, a RAM (Random Access Memory) or other type of dynamic storage device that can store information and instructions, an EEPROM (Electrically Erasable Programmable Read Only Memory), a CD-ROM (Compact Disc Read Only Memory) or other optical Disc storage, optical Disc storage (including Compact Disc, laser Disc, optical Disc, digital versatile Disc, blu-ray Disc, etc.), a magnetic Disc storage medium or other magnetic storage device, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a computer, but is not limited to these.
The memory 430 is used for storing application program codes (computer programs) for performing aspects of the present invention and is controlled to be executed by the processor 410. The processor 410 is configured to execute application program code stored in the memory 430 to implement the aspects illustrated in the foregoing method embodiments.
The effectiveness of the method of the invention is verified by a specific verification experiment:
the invention selects a 300RTK unmanned aerial vehicle for the longitude and latitude of the great Xinjiang, and carries a zensi P1 full-frame camera with 4500 ten thousand pixels and a controllable pitch angle pan-tilt. The total weight of the unmanned aerial vehicle is 6300g, the maximum flying speed is 23m/s, the wheelbase is 895mm, the maximum inclinable angle is 30 degrees, and the maximum operation time is 55 min; camera parameters: 4500w effective pixel, 8192 × 5460 resolution, f2.8-f15 aperture, 35mm focal length, 4.4 μm pixel size.
Data are collected by adopting the approach photography mode, the flying height of the unmanned aerial vehicle is set to be 200m, the flying speed is set to be 12m/s, the heading image overlapping rate is set to be 60%, and the side image overlapping rate is set to be 50%, so that the integrity of DSM data in a survey area is ensured.
Shooting resolution ratio sets for 1mm, and the image resolution ratio that obtains promptly is 1mm, and it shoots apart from the side slope distance for fixed 8m to obtain unmanned aerial vehicle through calculating, and the track point is automatic to follow the undulation of side slope. The unmanned aerial vehicle has a course overlapping rate of 80 percent, a side overlapping rate of 70 percent and a camera pitch angle set to-12 degrees. And obtaining image data of different time periods through multiple aerial surveys.
In order to further verify the precision of the displacement detection method, a cement test block with a fixed size is selected to be placed at the side slope, the position of the test block is manually moved to simulate the displacement of the side slope in the horizontal and vertical directions, and the displacement precision is verified. Two test blocks are selected, and the specification of the first test block is as follows: the length is 19.9cm, the width is 8.8cm, the height is 4.6cm, and the specification of a second test block is as follows: the length of the test block is 19.9cm, the width of the test block is 10.0cm, the height of the test block is 3.0cm, the two test blocks are respectively subjected to horizontal displacement and padding height operation to simulate horizontal displacement and vertical direction displacement, two groups of data are acquired in an aerial survey mode, the first group is used as a reference group, the second group is used as a comparison group, the second group is used for performing artificial displacement in the horizontal direction and the vertical direction for 1cm on the basis of the first group, a three-dimensional point cloud model is established by utilizing the acquired data, and the three-dimensional point cloud data are cut according to the same range after being obtained.
As shown in fig. 5, two reference point clouds obtained before the test block displacement; as shown in fig. 6, the left test block is the point cloud after horizontal displacement, and the right test block is the point cloud after vertical displacement. As shown in fig. 7, the reference point cloud area before the horizontal displacement of the test block is S1, the comparison point cloud area after the horizontal displacement is S2, and for the horizontal displacement, only the point clouds in the front horizontal plane are compared; as shown in fig. 8, the point cloud areas S3 are compared before the test block is vertically displaced, and the point cloud areas S4 are compared after the test block is vertically displaced, and only the point clouds on the upper plane are compared for the vertical displacement.
And calculating displacement offset of the reference point cloud area and the point cloud area before and after horizontal displacement and before and after vertical displacement of the test block to obtain a distribution statistical diagram of the displacement offset of the point cloud. As shown in fig. 9, for the horizontal displacement of the test block, the average displacement of the point cloud in the horizontal direction is 0.9691cm, and the error between the calculated distance in the horizontal direction and the actual distance is 0.0309 cm. As shown in fig. 10, the statistical graph of the distribution of the displacement offsets of the point clouds before and after the vertical displacement of the test block, for the vertical displacement of the test block, the average displacement of the point clouds in the vertical direction is 1.0257cm, and the error between the calculation result in the vertical direction and the actual displacement is 0.0257 cm. And calculating according to the statistical distribution map of the displacement offset of the point cloud, wherein the calculated fluctuation of the displacement deviation is +/-5 mm of the average displacement for the test block with horizontal displacement, and the calculated fluctuation of the displacement deviation is +/-6 mm of the average displacement for the test block with vertical displacement.
In addition, the experiment carries out data acquisition in two time periods, the time interval of the two acquisition is three months, the same track point is used for the two data acquisition, and the same resolution ratio of the two acquired data is ensured. Three-dimensional reconstruction is carried out on the data to obtain a three-dimensional point cloud model and three-dimensional point cloud data acquired twice in the survey area, the point cloud model is cut to ensure the consistency of a comparison range, the three-dimensional point cloud data generated by acquiring the data for the first time is used as reference data, the three-dimensional point cloud data generated for the second time is used as comparison data, and the three-dimensional point cloud data before and after cutting are shown in figure 11. In fig. 11, (c) is a first time of collecting a side slope three-dimensional model diagram; (d) collecting a slope point cloud model diagram for the first time; (e) collecting a slope three-dimensional model diagram for the second time; (f) acquiring a slope point cloud model map for the second time; (g) is a schematic diagram of the superposition of the point cloud space.
Performing migration data statistics on the obtained point cloud distance to obtain two time slope point cloud displacement migration offset statistical graphs, as shown in fig. 12, where the horizontal axis is displacement offset, and the unit is: cm, the vertical axis represents the number of power supplies in units: as can be seen from the figure, the displacement distances of the 99.85% point clouds were all 0.166cm or less, and the displacement amount of the entire slope was small.
The above is only a preferred embodiment of the present invention, and is not intended to limit the present invention, and various modifications and changes will occur to those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (9)
1. The method for detecting the displacement of the side slope of the power station dam is characterized by comprising the following steps:
collecting a first view image of a power station dam slope by using an unmanned aerial vehicle close-up photography mode, and acquiring geographic position information of pixel points of the first view image;
performing aerial triangulation on the pixel points of the first view image according to the geographic position information, and determining first three-dimensional coordinate data corresponding to the pixel points in the first view image;
establishing a digital surface model corresponding to a pixel point in the first view image according to the first three-dimensional coordinate data;
setting a flight path of the unmanned aerial vehicle by using the digital surface model, and setting shooting parameters;
acquiring positioning data of the unmanned aerial vehicle, wherein the unmanned aerial vehicle acquires a second view image according to the flight path and shooting parameters of the unmanned aerial vehicle;
extracting characteristic points of the second view image, and calculating second three-dimensional coordinate data of the characteristic points;
establishing a three-dimensional point cloud model according to the shooting parameters, the positioning data and the second three-dimensional coordinate data;
determining three-dimensional point cloud data according to the three-dimensional point cloud model;
and acquiring the three-dimensional point cloud data at different times, analyzing the difference between the three-dimensional point cloud data at different times, and determining the displacement offset of the power station dam slope.
2. The method for detecting the displacement of the side slope of the power station dam according to claim 1, wherein the steps of obtaining the three-dimensional point cloud data at different times, analyzing the difference between the three-dimensional point cloud data at different times and determining the displacement of the side slope of the power station dam comprise the following steps:
acquiring the three-dimensional point cloud data at initial time as reference data, and acquiring the three-dimensional point cloud data after set time as comparison data;
clipping the reference data and the comparison data according to the same range;
fitting the discrete point clouds in the reference data into a three-dimensional grid plane;
and calculating the distance from the point cloud in the comparison data to the adjacent three-dimensional grid plane to obtain the displacement offset of the point cloud of the power station dam slope after the initial time and the set time.
3. The method of claim 1, wherein the determining the displacement offset of the dam side slope further comprises: and obtaining a distance distribution map of the point cloud according to the displacement offset of the point cloud.
4. The power station dam slope displacement detection method according to claim 1, wherein the method for obtaining the positioning data of the unmanned aerial vehicle is a real-time dynamic carrier phase differential method.
5. The method for detecting the slope displacement of the power station dam as claimed in claim 1, wherein the method for extracting the feature points of the second view image comprises the following steps: and extracting the feature points of the second view image by using an accelerated robust feature algorithm.
6. The method for detecting the slope displacement of the power station dam as claimed in claim 1, wherein the determining three-dimensional point cloud data according to the three-dimensional point cloud model comprises:
and performing dense reconstruction on the three-dimensional point cloud model by using an MVS algorithm, performing pixel-by-pixel matching on each second view image of the collected multi-view, and regenerating the three-dimensional coordinates of each pixel to obtain three-dimensional point cloud data.
7. The power station dam slope displacement detection method according to claim 1, characterized in that the shooting parameters include shooting angle, shooting effective pixels, shooting aperture, shooting focal length and pixel size.
8. Power station dam side slope displacement detection device, its characterized in that includes: the device comprises a collecting unit, a measuring unit, a first model establishing unit, a setting unit, an obtaining unit, a processing unit, a second model establishing unit, a determining unit and an analyzing unit;
the acquisition unit is used for acquiring a first view image of a power station dam slope by using an unmanned aerial vehicle close-up photography mode and acquiring geographic position information of pixel points of the first view image;
the measuring unit is used for carrying out aerial triangulation on the pixel points of the first view image according to the geographic position information and determining first three-dimensional coordinate data corresponding to the pixel points in the first view image;
the first model establishing unit is used for establishing a digital surface model corresponding to a pixel point in the first view image according to the first three-dimensional coordinate data;
the setting unit is used for setting a flight path of the unmanned aerial vehicle by using the digital surface model and setting shooting parameters;
the acquisition unit is used for acquiring positioning data of the unmanned aerial vehicle, and the unmanned aerial vehicle acquires a second view image according to the flight path and shooting parameters of the unmanned aerial vehicle;
the processing unit is used for extracting the characteristic points of the second view image and calculating second three-dimensional coordinate data of the characteristic points;
the second model establishing unit is used for establishing a three-dimensional point cloud model according to the shooting parameters, the positioning data and the second three-dimensional coordinate data;
the determining unit is used for determining three-dimensional point cloud data according to the three-dimensional point cloud model;
the analysis unit is used for acquiring the three-dimensional point cloud data at different times, analyzing the difference between the three-dimensional point cloud data at different times and determining the displacement offset of the power station dam slope.
9. An electronic device, comprising:
a processor and a memory;
the memory is used for storing computer operation instructions;
the processor is used for executing the method of any one of claims 1 to 7 by calling the computer operation instruction.
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