CN113916136A - High-rise structure dynamic displacement measurement method based on unmanned aerial vehicle aerial photography - Google Patents
High-rise structure dynamic displacement measurement method based on unmanned aerial vehicle aerial photography Download PDFInfo
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Abstract
The invention provides a method for measuring dynamic displacement of a towering structure based on aerial photography of an unmanned aerial vehicle, which comprises the following steps: acquiring a dynamic displacement video of the top end of the towering structure shot by the unmanned aerial vehicle; capturing a plurality of points to be measured of the first frame of dynamic displacement image at the top end of the towering structure as measuring points; capturing a plurality of dynamic displacement points of the multi-dynamic displacement image by using a pyramid algorithm to obtain a plurality of optical flows; calculating optical flow vectors of a plurality of optical flows by using an optical flow method to obtain an optical flow field; carrying out threshold segmentation on the optical flow field to divide the multi-frame dynamic displacement image into a background and a moving target; extracting pixel coordinates of a moving target in each frame of dynamic displacement image, taking a measuring point of the first frame of dynamic displacement image as a zero coordinate, and calculating displacement coordinates of the measuring point to obtain initial data of top dynamic displacement of the towering structure; and correcting the initial data of the top dynamic displacement of the high-rise structure by using unmanned aerial vehicle suspension displacement compensation. The invention can solve the problem that the camera is far away from the moving part of the measured high-rise structure, which causes larger error of the measuring result.
Description
Technical Field
The invention relates to the technical field of structure dynamic displacement measurement, in particular to a method for measuring the dynamic displacement of a towering structure based on unmanned aerial vehicle aerial photography.
Background
For dynamic displacement of a structure, the most common method for measuring the dynamic displacement is to arrange a displacement sensor, and the method needs a fixed point and a moving point. Specifically, for the fixed point, the displacement sensor can be fixed on the bracket before measurement, the displacement sensor is kept in a static state during measurement to serve as the fixed point, and then the movable end of the displacement sensor is connected to the test piece. For a short structure, the problem of a sensor fixing point can be well solved by erecting a support, but for a high-rise structure exceeding 10 meters, the safety risk exists by erecting the support, the cost is particularly high, most importantly, the support cannot be erected in many occasions, so that the sensor cannot be arranged, and the test data of the dynamic displacement cannot be acquired.
In order to overcome the defects, the prior art provides another method for measuring the structural dynamic displacement, which adopts a video method; the method is characterized in that one or more cameras are erected on the ground, the structure is shot from different angles, and a dynamic displacement curve of the structure is calculated through an algorithm. However, for the high-rise structure, the accuracy of the dynamic displacement measurement result of the high-rise structure is low and the error is large because the camera is far away from the moving part of the measured high-rise structure.
Disclosure of Invention
Aiming at the defects in the prior art, the invention provides a method for measuring the dynamic displacement of a towering structure based on unmanned aerial vehicle aerial photography, which aims to solve the technical problem that the dynamic displacement measurement result of the towering structure has larger error due to the fact that a camera is far away from the moving part of the measured towering structure in the prior art.
The technical scheme adopted by the invention is as follows:
in a first aspect, a method for measuring the dynamic displacement of a towering structure based on unmanned aerial vehicle aerial photography is provided,
in a first implementation, the method includes:
acquiring a dynamic displacement video of the top end of the towering structure shot by the unmanned aerial vehicle to obtain a plurality of frames of dynamic displacement images;
capturing a plurality of points to be measured of the first frame of dynamic displacement image at the top end of the towering structure as measuring points;
capturing a plurality of dynamic displacement images by using a pyramid algorithm to obtain a plurality of optical flows;
calculating optical flow vectors of a plurality of optical flows by using an optical flow method to obtain an optical flow field;
carrying out threshold segmentation on the optical flow field, and dividing a plurality of dynamic displacement images into a background part and a moving target part;
extracting pixel coordinates of a moving target in each frame of dynamic displacement image, taking a measuring point of the first frame of dynamic displacement image as a zero coordinate, and calculating displacement coordinates of the measuring point according to the pixel coordinates and the zero coordinate to obtain initial data of the top dynamic displacement of the towering structure;
and correcting the initial data of the top dynamic displacement of the towering structure by using unmanned aerial vehicle suspension displacement compensation to obtain the measurement data of the top dynamic displacement of the towering structure.
According to the technical scheme of the first implementation mode, the beneficial technical effects of the invention are as follows: the method comprises the steps of shooting a close-range video of a measured structure by using an unmanned aerial vehicle in a hovering state, fusing the unmanned aerial vehicle technology and the video method technology, analyzing and calculating acquired image information by using a pyramid algorithm and a two-frame differential optical flow estimation algorithm, obtaining a motion trajectory time-course curve of the measured high-rise structure, realizing high-precision measurement of the dynamic displacement of the high-rise structure, and overcoming the defect of insufficient precision of a common video method.
In combination with the first implementation mode, in the second implementation mode, when the unmanned aerial vehicle shoots the top end of the high-rise structure, the hovering space coordinate of the unmanned aerial vehicle is calculated according to the shooting principle of the short distance and the size of the high-rise structure model.
According to the technical scheme of the second implementation mode, the beneficial technical effects of the invention are as follows: the unmanned aerial vehicle can hover at almost any spatial position, can carry out close-range shooting near the structure to be measured, can also assist with optics or digital zoom technique, not only has changeable measurement accuracy, has still overcome the limitation that need set up the fixed point in measuring the structure movement displacement, has improved the feasibility of testing, has advantages such as convenient to use, flexible operation, with low costs.
With reference to the first implementation manner, in a third implementation manner, the pyramid algorithm includes:
establishing a Gaussian pyramid for each frame of dynamic displacement image, and enabling the lowest resolution image to be on the topmost layer and the original image to be on the bottom layer;
calculating the optical flow of each point in the top layer image;
feeding back the light stream calculation result of the top layer to an adjacent layer of the top layer as an estimated value of the initial light stream of the adjacent layer;
feeding back down the pyramid until the bottom layer of the pyramid is reached.
With reference to the third implementable manner, in a fourth implementable manner, calculating an optical flow for each point in the image includes: the optical flow of each point in the image is obtained by minimizing the sum of the matching errors in the neighborhood of each point.
In a fifth implementable manner, in combination with the first implementable manner, when calculating an optical flow vector of a plurality of optical flows using the optical flow method, the optical flow vector is calculated by performing weighted sum-of-squares minimization on the optical flow basic constraint equation.
With reference to the fifth implementable manner, in a sixth implementable manner, the optical flow method is an optical flow estimation algorithm of two-frame difference.
In combination with the first implementable manner, in a seventh implementable manner, when performing threshold segmentation on the optical flow field, the threshold is selected by using a maximum inter-class variance method.
In combination with the first implementable manner, in an eighth implementable manner, before performing moving point capture on a plurality of frames of moving displacement video by using a pyramid algorithm, performing image graying and binarization preprocessing on the plurality of frames of moving displacement video.
In combination with the first implementation manner, in a ninth implementation manner, before the unmanned aerial vehicle shoots a dynamic displacement video of the top end of the towering structure, calculating to obtain a hovering space coordinate of the unmanned aerial vehicle according to the area of the top end of the towering structure, the position of a stationary point and the shooting angle of a camera of the unmanned aerial vehicle;
according to the hovering space coordinate of the unmanned aerial vehicle, the hovering space position and the shooting angle of the unmanned aerial vehicle are controlled, and videos of the top end measuring point of the high-rise structure and the peripheral static points are completely collected.
According to the technical scheme of the ninth implementation mode, the beneficial technical effects of the invention are as follows: can revise because of the structure area of towering when too big, the measuring point of the structure top of towering is outside unmanned aerial vehicle's camera lens, to the influence that the measurement of the structure that towering moved and displace brought, further promote the measurement accuracy to the structure that towering moves and displace.
In a second aspect, there is provided an electronic device, in a tenth implementable form, comprising:
one or more processors;
storage means for storing one or more programs;
when the one or more programs are executed by the one or more processors, the one or more processors implement any one of the first to ninth realizable manners of measuring the dynamic displacement of the towering structure based on the aerial photography of the unmanned aerial vehicle.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below. Throughout the drawings, like elements or portions are generally identified by like reference numerals. In the drawings, elements or portions are not necessarily drawn to scale.
Fig. 1 is a flowchart of a method for measuring dynamic displacement of a towering structure according to embodiment 1 of the present invention.
Detailed Description
Embodiments of the present invention will be described in detail below with reference to the accompanying drawings. The following examples are only for illustrating the technical solutions of the present invention more clearly, and therefore are only examples, and the protection scope of the present invention is not limited thereby.
It is to be noted that, unless otherwise specified, technical or scientific terms used herein shall have the ordinary meaning as understood by those skilled in the art to which the invention pertains.
Example 1
The embodiment provides a method for measuring dynamic displacement of a towering structure based on unmanned aerial vehicle aerial photography, as shown in fig. 1, the method comprises the following steps:
s1, obtaining the dynamic displacement video of the top end of the towering structure shot by the unmanned aerial vehicle, and obtaining a plurality of dynamic displacement images
In a specific implementation mode, an unmanned aerial vehicle is used as an operating platform, and the unmanned aerial vehicle is used for carrying out close-range video shooting on a measured high-rise structure (such as an iron tower) in a hovering state. The unmanned aerial vehicle adopts the mode of hovering, and the hovering space coordinate of the unmanned aerial vehicle is calculated through the shooting principle of big and small distance and the size of the high-rise structural model, so that the measuring points are all in the shooting range in the shooting process. According to the actual situation of the site, the unmanned aerial vehicle can hover at a place which is very close to the high-rise structure and shoot at a position (such as 10-90 cm) from a short distance to tens of cm, so that a clear top dynamic displacement video of the high-rise structure is obtained. And multiple dynamic displacement images can be analyzed according to the dynamic displacement video.
And S2, capturing a plurality of points to be measured of the first frame of dynamic displacement image at the top end of the towering structure as measuring points.
In a specific embodiment, a plurality of points to be measured at the top of the towering structure in the first frame of dynamic displacement image can be captured as measuring points manually according to the time sequence of video shooting.
S3, performing displacement moving point capture on multiple dynamic displacement images by using a pyramid algorithm to obtain a plurality of optical flow pyramid algorithms as follows:
1. establishing a Gaussian pyramid for each frame of dynamic displacement image, wherein the lowest resolution image is at the topmost layer, and the original image is at the bottom layer;
2. computing optical flow for each point in top-level image
Starting from the top layer, obtaining the optical flow of each point in the top layer image by minimizing the sum of matching errors in the neighborhood range of each point, wherein the calculation method specifically comprises the following steps:
assuming that the size of the image is zoomed to half of the original size each time, and the L layers are zoomed together, the 0 th layer is the original image. Assuming that the displacement of the known original is d, the displacement of each layer is:
3. the optical flow calculation result (i.e. displacement situation) of the top layer is fed back to the L-1 th layer adjacent to the top layer as the estimated value g of the initial optical flow value of the layer, and then:
gL-1＝2(gL+dL) (3)
4. feeding back down the pyramid, repeating the estimation until the bottom layer of the pyramid (i.e. the layer where the original image is) is reached, then:
d＝g0+d0 (4)
the pyramid algorithm can be used for processing larger pixel motion by using a relatively smaller field window, and iteration is performed in sequence to obtain the position of a point to be measured in a subsequent image sequence, so that the capture of a larger-displacement moving point is realized.
And performing displacement moving point capture on the moving displacement video through a pyramid algorithm to obtain the optical flow. The number of optical flows is plural. In a specific embodiment, preferably, before performing moving point capture on a multi-frame moving displacement video by using a pyramid algorithm, preprocessing of image graying and binarization can be further performed on the multi-frame moving displacement video.
S4, calculating optical flow vectors of a plurality of optical flows by using an optical flow method to obtain an optical flow field
Using the optical flow method, an optical flow vector is calculated by minimizing a weighted sum of squares of the basic constraint equations for the optical flow, the optical flow vector including the velocity and direction of the optical flow.
In a specific embodiment, a two-frame differential optical flow estimation algorithm may be selected, which adds a "spatially consistent" assumption based on two basic assumptions of the original optical flow method, that is, all neighboring pixels have similar actions, that is, each pixel has the same optical flow vector in an m × m area around the target pixel. The optical flow estimation algorithm of the two-frame difference is specifically as follows:
the optical flow formula is set as: i isx·u+Iy·v+It＝0 (5)
The basic constraint equation of optical flow is: sigma(x,y)∈Ωw2(x)(Ix·u+Iy·v+It)2 (6)
Performing weighted square sum minimization on the optical flow basic constraint equation can obtain:
V＝(ATW2A)-1ATW2b (7)
and (4) using a two-frame differential optical flow estimation algorithm, and combining the moving point capture obtained in the step S2 to finally solve to obtain the optimal solution of each optical flow vector to obtain the optical flow field.
S5, carrying out threshold segmentation on the optical flow field, and dividing the multi-dynamic displacement image into a background part and a moving object part
The optical flow field of the whole picture can be divided into two parts by using threshold segmentation, namely, a background and a foreground are distinguished, so that the motion points of each image sequence can be extracted conveniently.
In a specific embodiment, the selection of the threshold value during the threshold segmentation may be determined by using a maximum inter-class variance method, which divides the image into two parts, namely a background and a moving object according to the gray characteristics of the image. The moving object is the moving point of each image sequence.
S6, extracting the pixel coordinates of the moving target in each frame of dynamic displacement image, taking the measuring point of the first frame of dynamic displacement image as a zero coordinate, and calculating the displacement coordinates of the measuring point according to the pixel coordinates and the zero coordinate to obtain the initial data of the top dynamic displacement of the towering structure
The step uses the change of the pixel in the image sequence in the time domain and the correlation between two adjacent frames to find the corresponding relation between the frames. And according to the displacement coordinate of the measuring point, the offset of the pixel coordinate relative to the zero point coordinate is obtained. Due to the multiple dynamic displacement images, the displacement coordinates of the plurality of measurement points are calculated, and the displacement coordinates of the plurality of measurement points have correlation in time sequence. Through the displacement coordinates of the plurality of measuring points, the motion trail time-course curve of the measured high-rise structure can be obtained, and initial data of the top dynamic displacement of the high-rise structure is obtained.
S7, correcting the initial data of the top dynamic displacement of the towering structure by using unmanned aerial vehicle suspension displacement compensation to obtain the measurement data of the top dynamic displacement of the towering structure
In the hovering shooting process of the unmanned aerial vehicle, drift is inevitably generated, so that the shot video is superimposed with the position drift value of the unmanned aerial vehicle in addition to the structural dynamic displacement; therefore, the initial data of the top dynamic displacement of the high-rise structure calculated according to the video image shot by the unmanned aerial vehicle is not accurate data of the top dynamic displacement of the high-rise structure, and the drift displacement of the unmanned aerial vehicle needs to be corrected.
When the drift displacement correction of the unmanned aerial vehicle is carried out, the drift displacement correction can be carried out in any mode which can be realized in the prior art.
According to the technical scheme, the unmanned aerial vehicle is used for shooting the close-range video of the structure to be measured in the hovering state, the unmanned aerial vehicle technology and the video method technology are combined, the collected image information is analyzed and calculated through the pyramid algorithm and the two-frame differential optical flow estimation algorithm, the motion track time-course curve of the structure to be measured is obtained, high-precision measurement of the dynamic displacement of the structure to be measured is achieved, and the defect of insufficient precision of a common video method is overcome.
The unmanned aerial vehicle can hover at almost any spatial position, can carry out close-range shooting near the structure to be measured, can also assist with optics or digital zoom technique, not only has changeable measurement accuracy, has still overcome the limitation that need set up the fixed point in measuring the structure movement displacement, has improved the feasibility of testing, has advantages such as convenient to use, flexible operation, with low costs.
Example 2
When actual measurement, if unmanned aerial vehicle is close apart from the structure distance that stands tall and erects that awaits measuring, or the structure top area that stands tall and erects is too big, can lead to unmanned aerial vehicle photography range can not completely cover whole structure that stands tall and erects, and partial structure top measuring point and the peripheral dead center that stands tall and erects are outside unmanned aerial vehicle's camera lens, and pixel motion trail can't be drawed.
In order to solve the above technical problem, on the basis of embodiment 1, the following technical solutions are adopted:
before the unmanned aerial vehicle shoots a dynamic displacement video of the top end of the towering structure, calculating to obtain a hovering space coordinate of the unmanned aerial vehicle according to the area of a vibrating table, the area of the top end of the towering structure, the position of a static point and the shooting angle of a camera of the unmanned aerial vehicle;
controlling the hovering space position and the shooting angle of the unmanned aerial vehicle according to the hovering space coordinate of the unmanned aerial vehicle, and completely acquiring videos of a top measuring point and peripheral static points of the high-rise structure;
steps S1-S7 in example 1 were then performed.
In a particular embodiment, the oscillating table is used in the case of laboratory experiments, the purpose of which is to give a certain amplitude to the top of the towering structure in order to facilitate the modelling. The vibration table can be selected from a model of 6 multiplied by 6 meters and bearing 40 tons; the area of the vibration table is the length multiplied by the width of the vibration table surface.
The area of the top end of the high-rise structure can be obtained through field measurement or building design files.
The static point is a plurality of mark points of the first frame of video image on the static ground are selected as compensation points of the hovering drift of the unmanned aerial vehicle; the marker point is a pixel point position where the marker is located, and the selection of the marker can be determined according to the actual situation.
The technical scheme of this embodiment can revise because of the structure area that towns is too big, and the measuring point of the structure top that towns is outside unmanned aerial vehicle's camera lens, and the measurement that brings the structure that towns moves the displacement that towns further promotes the measurement accuracy to the structure that towns moves the displacement.
Example 3
Provided is an electronic device including:
one or more processors;
storage means for storing one or more programs;
when the one or more programs are executed by the one or more processors, the one or more processors implement the method for measuring the dynamic displacement of the towering structure based on the aerial photography of the unmanned aerial vehicle provided in embodiment 1 or embodiment 2.
Finally, it should be noted that: the above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; while the invention has been described in detail and with reference to the foregoing embodiments, it will be understood by those skilled in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; such modifications and substitutions do not depart from the spirit and scope of the present invention, and they should be construed as being included in the following claims and description.
Claims (10)
1. The utility model provides a high-rise structure dynamic displacement measurement method based on unmanned aerial vehicle takes photo by plane which characterized in that includes:
acquiring a dynamic displacement video of the top end of the towering structure shot by the unmanned aerial vehicle to obtain a plurality of frames of dynamic displacement images;
capturing a plurality of points to be measured of the first frame of dynamic displacement image at the top end of the towering structure as measuring points;
capturing a plurality of dynamic displacement images by using a pyramid algorithm to obtain a plurality of optical flows;
calculating optical flow vectors of a plurality of optical flows by using an optical flow method to obtain an optical flow field;
carrying out threshold segmentation on the optical flow field, and dividing a plurality of dynamic displacement images into a background part and a moving target part;
extracting pixel coordinates of a moving target in each frame of dynamic displacement image, taking a measuring point of the first frame of dynamic displacement image as a zero coordinate, and calculating displacement coordinates of the measuring point according to the pixel coordinates and the zero coordinate to obtain initial data of the top dynamic displacement of the towering structure;
and correcting the initial data of the top dynamic displacement of the towering structure by using unmanned aerial vehicle suspension displacement compensation to obtain the measurement data of the top dynamic displacement of the towering structure.
2. The method for measuring the dynamic displacement of the towering structure based on the aerial photography of the unmanned aerial vehicle as claimed in claim 1, wherein when the unmanned aerial vehicle photographs the top end of the towering structure, the hovering space coordinate of the unmanned aerial vehicle is calculated according to the short-distance and short-distance photography principle and the size of the towering structure model.
3. The method for measuring the dynamic displacement of the towering structure based on unmanned aerial vehicle aerial photography according to claim 1, wherein the pyramid algorithm comprises:
establishing a Gaussian pyramid for each frame of dynamic displacement image, and enabling the lowest resolution image to be on the topmost layer and the original image to be on the bottom layer;
calculating the optical flow of each point in the top layer image;
feeding back the optical flow calculation result of the top layer to an adjacent layer of the top layer as an estimated value of the initial optical flow of the adjacent layer;
feeding back down the pyramid until the bottom layer of the pyramid is reached.
4. The method for measuring the dynamic displacement of the towering structure based on the unmanned aerial vehicle aerial photography of claim 3, wherein the step of calculating the optical flow of each point in the image comprises the following steps: the optical flow of each point in the image is obtained by minimizing the sum of the matching errors in the neighborhood of each point.
5. The method for measuring the dynamic displacement of the towering structure based on the unmanned aerial vehicle aerial photography according to claim 1, wherein when the optical flow vectors of a plurality of optical flows are calculated by using an optical flow method, the optical flow vectors are calculated by performing weighted square sum minimization on an optical flow basic constraint equation.
6. The method for measuring the dynamic displacement of the towering structure based on unmanned aerial vehicle aerial photography according to claim 5, wherein the optical flow method is a two-frame differential optical flow estimation algorithm.
7. The method for measuring the dynamic displacement of the towering structure based on the unmanned aerial vehicle aerial photography of claim 1, wherein the threshold is selected by using a maximum inter-class variance method when the optical flow field is subjected to threshold segmentation.
8. The method for measuring the dynamic displacement of the towering structure based on the unmanned aerial vehicle aerial photography of claim 1, wherein the preprocessing of image graying and binarization is carried out on the multi-frame dynamic displacement video before the pyramid algorithm is used for carrying out the displacement dynamic point capture on the multi-frame dynamic displacement video.
9. The method for measuring the dynamic displacement of the towering structure based on the aerial photography of the unmanned aerial vehicle as claimed in claim 1, wherein before the dynamic displacement video of the top end of the towering structure is shot by the unmanned aerial vehicle, the hovering space coordinate of the unmanned aerial vehicle is obtained through calculation according to the area of the top end of the towering structure, the position of a stationary point and the shooting angle of a camera of the unmanned aerial vehicle;
according to the hovering space coordinate of the unmanned aerial vehicle, the hovering space position and the shooting angle of the unmanned aerial vehicle are controlled, and videos of the top end measuring point of the high-rise structure and the peripheral static points are completely collected.
10. An electronic device, comprising:
one or more processors;
storage means for storing one or more programs;
when executed by the one or more processors, cause the one or more processors to implement the method for measuring dynamic displacement of towering structure based on drone photography of any of claims 1-7.
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