CN110425999A - A kind of lifting equipment measuring for verticality method and system based on unmanned plane image - Google Patents

Abstract

The invention discloses a method and system for detecting verticality of lifting equipment based on images of unmanned aerial vehicles. The verticality obtains the image of the bottom of the tower crane bracket with configuration information and obtains the image of the equipment bracket with configuration information; 2 1. Obtain the top image of the tower crane bracket with configuration information; 3. Choose one image from the bottom image obtained in step 1) and the top image obtained in step 2), complete image calibration, and obtain the spatial resolution of the image 4. Select reference points L ₁ and L ₂ on the left bracket of the bottom image obtained in step 1) and the top image obtained in step 2) respectively; 5. Calculate the L ₂ point in the L ₁ coordinate system Abscissa; 6. Calculate the ordinate of point L ₂ in the L ₁ coordinate system; 7. Calculate the verticality of the lifting device.

Description

A method and system for verticality detection of lifting equipment based on UAV images

technical field

The invention relates to the field of verticality detection of lifting equipment, in particular to a method and system for detecting verticality of lifting equipment based on images of unmanned aerial vehicles.

Background technique

In the past two decades, China's construction industry has developed rapidly, and tower cranes (tower cranes) have become the most widely used lifting machinery on construction sites. According to official statistics, there were at least 207 construction crane safety accidents across the country in 2016, causing direct losses of hundreds of millions of yuan. In order to protect the life safety of tower crane operators, it is particularly important to periodically inspect the tower crane to ensure the safe operation of the equipment and the smooth completion of the entire construction project.

The verticality of the lifting equipment is used to characterize the inclination of the lifting equipment support, and it is one of the important measurement indicators for the detection of lifting equipment defects. Take Figure 1 as an example, after the tower crane is installed, the increase is in a balanced state, verticality ΔL=x/h (x is the lateral offset between the top and bottom of the lifting equipment support, h is the height of the lifting equipment support). According to 5.2.3i) of GB/T5031-2008 "Tower Cranes", the tolerance of verticality is 4/1000. The difficulty in detecting the verticality of lifting equipment lies in: most of the lifting equipment is located on the construction site, and the working condition is poor; the height of the lifting equipment is high (50-500m), and it is difficult to climb; up to mm level.

At present, the verticality detection of lifting equipment mainly adopts the laser plummet measurement method. Referring to Figure 2, the tested equipment is parked according to the detection requirements, and the laser plummet is placed near the bottom edge of the tested equipment (generally in the main section of the standard section). At the support rod), adjust the level according to the instruction manual, so that the laser beam is in a vertical upward state. At 100-200m directly above the laser beam, fix the digital display light target, move the vernier digital display ruler, make the reference point align with the laser beam spot, reset the digital display ruler, this position is the original reference point, keep the plummet Move the digital display light target to the same position on the top of the device under test, and then move the vernier digital display ruler again so that the reference point is aligned with the laser beam spot. At this time, the reading on the digital display ruler is the verticality. The disadvantages of this method are as follows: it is necessary to manually fix the light target on the top of the equipment, and there is a great potential safety hazard; and the range of the laser plummet is about 200m. As the measurement height increases, the error will increase sharply, which is not conducive to 500m ultra-high tower crane verticality detection.

So far, there is no verticality detection method and system for lifting equipment that can simultaneously satisfy high measurement accuracy, large measurement height range, and low safety risk in the prior art.

Contents of the invention

Aiming at the deficiencies of the prior art, the technical problem to be solved by the present invention is to provide a method and system for detecting verticality of lifting equipment based on UAV images.

For this reason, the present invention proposes a kind of lifting equipment verticality detection method based on drone image, comprises the following steps:

1) Use the flight control module to control the UAV to fly to a certain distance from the lifting equipment, move the aircraft up and down, left and right, so that it hovers at the bottom of the special equipment, adjust the focal length of the camera, so that the equipment rack fills the screen as much as possible, and take a vertical shot. Detect the bottom image at a high degree, and record the position information (X _w1 , Y _w1 ) and camera rotation angle θ ₁ of the drone at this time;

2) Control the aircraft to rise vertically through the flight control module until the top of the equipment rack can be observed on the camera screen, keep the focal length of the camera unchanged, take a picture of the top of the verticality detection, and record the position information of the drone at this time (X _w2 , Y _w2 ) and camera rotation angle θ ₂ ;

3) Choose one image from the bottom image obtained in step 1) and the top image obtained in step 2), complete the image calibration, and obtain the spatial resolution k _x , _ky of the image, and the k _x , k _y is the real distance represented by each pixel distance horizontally and vertically;

4) Select reference points L ₁ (X ₁ , Y ₁ ), L ₂ (X ₂ , Y ₂ ) on the left bracket of the bottom image obtained in step 1) and the top image obtained in step 2), respectively;

5) According to L ₂ (X ₂ , Y ₂ ), rotation angle θ ₁ , rotation angle θ ₂ , and image pixel width w, calculate the abscissa X′ _{2_θ1} of point L ₂ in the θ ₁ coordinate system. For different imaging positions, rotation directions, and rotation angles, there are

a) When the L ₂ imaging point is on the left side of the image, the relative rotation angle is leftward and θ>α:

b) When the L ₂ imaging point is on the left side of the image, the relative rotation angle is to the left and θ<α:

c) When the L ₁ imaging point is on the left side of the image and the relative rotation angle is to the right:

d) When the L ₂ imaging point is on the right side of the image, the relative rotation angle is to the right and θ>α:

e) When the L ₂ imaging point is on the right side of the image, the relative rotation angle is to the right and θ<α:

f) When the L ₂ imaging point is on the right side of the image and the relative rotation angle is to the left:

Calculate the ordinate Y ₂ ' of point L ₂ in the θ ₁ coordinate system, there is:

Y′ _{2_θ1} = Y′ ₂ (4-7)

Where: θ is the relative rotation angle and θ=θ ₂ -θ ₁ , w is the image pixel width, and f is the focal length of the camera;

6) Calculate the coordinates (X ₂ ', Y ₂ ') of point L ₂ in the L ₁ coordinate system according to the position offset during imaging, and the calculation formulas are shown in the following formulas (5-1)~(5-2):

7) The verticality of the crane can be calculated according to formula (3):

The present invention also provides a verticality detection system for lifting equipment based on images of unmanned aerial vehicles, including an unmanned aerial vehicle, a flight control module and an image processing module.

The unmanned aerial vehicle is used to shoot the video of the lifting equipment and the task image set with configuration information, and transmit the data to the flight control module in real time; the configuration information is when the unmanned aerial vehicle takes images The high-precision position information and the rotation angle of the camera; the task image set includes the bottom image of the lifting equipment support and the top image of the lifting equipment support;

The flight control module is used to control the flight of the unmanned aerial vehicle, receive the video stream transmitted back by the unmanned aerial vehicle in real time, and store the task image set with configuration information taken by the unmanned aerial vehicle;

The image processing module integrates the above-mentioned verticality calculation method, and is used to process and analyze the task image set with configuration information stored in the flight control module, and calculate and obtain the verticality of the lifting device;

Furthermore, when the UAV acquires the task image set, it is necessary to ensure that the distance between the UAV and the section of the lifting equipment support remains unchanged.

Furthermore, the UAV adopts dual RTK positioning, which can obtain high-precision positioning under strong electric and magnetic interference.

The beneficial effect of the present invention is: aiming at how to detect the verticality of the lifting equipment, a method and system for detecting the verticality of the lifting equipment based on the image of the unmanned aerial vehicle are proposed. The characteristics of high precision.

Description of drawings

Figure 1 is a schematic diagram of the verticality of the lifting equipment, where x is the horizontal offset between the top of the lifting equipment bracket and the bottom of the bracket, and h is the height of the equipment bracket.

Figure 2 is a measurement diagram of the verticality laser plummet.

Figure 3 is a schematic diagram of the horizontal coordinate image formation of the reference point, where L _2-w is the selected reference point, O is the image source, f is the focal length of the camera, α is the angle between the imaging point and the optical axis, and L ₂ is L _2-w The imaging point on the image plane, L ₂ ' is the imaging point of L _2-w on the image plane after the camera is rotated by θ.

Figure 4 is a schematic diagram of the structure of the UAV system, in which ① is the dual RTK onboard the platform, ② is the real-time image transmission, ③ is the mission computer on board, ④ is the dual gimbal camera, ⑤ is the rotating shaft of the dual gimbal camera, and ⑥ is mm Wave radar, ⑦ is the remote control, ⑧ is the ground station, and ⑨ is the VR glasses.

Fig. 5 is the imaging diagram of the bottom in specific embodiment 1.

FIG. 6 is a top imaging diagram in Embodiment 1.

Fig. 7 is the bottom image in specific embodiment 2.

Fig. 8 is the top imaging diagram in specific embodiment 2.

Detailed ways

The present invention will be further described below in conjunction with the accompanying drawings and specific embodiments.

Example 1:

1) Use the flight control module to control the UAV to fly to a certain distance from the lifting equipment, move the aircraft up and down, left and right, so that it hovers at the bottom of the special equipment, adjust the focal length of the camera, so that the equipment rack fills the screen as much as possible, and take a vertical shot. The bottom image of the degree detection is shown in Figure 5. Record the position information (X _w1 , Y _w1 )=(0, 1231) and the camera rotation angle θ ₁ =90° obtained by the drone according to the dual RTK positioning at this time;

2) Control the aircraft to rise vertically through the flight control module until the top of the equipment rack can be observed on the camera screen, keep the focal length of the camera unchanged, take a picture of the top of the verticality detection as shown in Figure 6, and record the drone at this time Position information (X _w2 , Y _w2 ) = (533, 60163) and camera rotation angle θ ₂ = 82° obtained according to dual RTK positioning;

3) import the bottom image obtained in step 1) and the top image obtained in step 2) into the image processing module;

4) Select the bottom image image imported in step 3), and through human-computer interaction, the operator uses the mouse to draw horizontal lines and vertical lines on the image, and input the real distance represented by them to complete the image calibration and obtain the space of the image Resolution k _x =0.8321, k _y =0.8733;

5) Through human-computer interaction, the operator draws a horizontal line with the mouse on the left support bar of the bottom image and top image imported in step 3), and the program automatically calculates the midpoint of the horizontal line, which is the reference point L ₁ (X ₁ , Y ₁ )=(621, 1400), L ₂ (X ₂ , Y ₂ )=(400, 1350);

6) According to L ₂ (X ₂ , Y ₂ ), rotation angle θ ₁ , rotation angle θ ₂ , and image pixel width w, calculate the coordinates (X′ _{2_θ1} , Y′ _{2_θ1} ) of point L ₂ in the θ ₁ coordinate system: The situation of this embodiment is as described in accompanying drawing 3 (b), according to formula (4-2), (4-7) calculation can get (X' _{2_θ1} , Y' _{2_θ1} )=(648, 1350):

Y′ _{2_θ1} = Y′ ₂ (4-7)

Where: θ is the relative rotation angle and θ=θ ₂ -θ ₁ , w is the image pixel width, and f is the focal length of the camera;

7) According to the position offset during imaging, calculate the coordinates (X ₂ ', Y ₂ ')=(1289, 68832) of point L ₂ in the L ₁ coordinate system, and the calculation formula is as follows: (5-1)～( 5-2) as shown:

8) The verticality of the crane can be calculated according to formula (3), and ΔL=0.009439 can be obtained:

Example 2:

1) Use the flight control module to control the UAV to fly to a certain distance from the lifting equipment, move the aircraft up and down, left and right, so that it hovers at the bottom of the special equipment, adjust the focal length of the camera, so that the equipment rack fills the screen as much as possible, and take a vertical shot. The bottom image of the degree detection is shown in Figure 7. Record the position information (X _w1 , Y _w1 )=(0, 3536) and the camera rotation angle θ ₁ =100° obtained by the UAV according to the dual RTK positioning at this time;

2) Control the aircraft to rise vertically through the flight control module until the top of the equipment rack can be observed on the camera screen, keep the focal length of the camera unchanged, take a picture of the top of the verticality detection as shown in Figure 8, and record the drone at this time Position information (X _w2 , Y _w2 )=(253, 15971) and camera rotation angle θ ₂ =104° obtained according to dual RTK positioning;

3) import the bottom image obtained in step 1) and the top image obtained in step 2) into the image processing module;

4) Select the bottom image image imported in step 3), and through human-computer interaction, the operator uses the mouse to draw horizontal lines and vertical lines on the image, and input the real distance represented by them to complete the image calibration and obtain the space of the image Resolution k _x =0.8433, k _y =0.8231;

5) Through human-computer interaction, the operator draws a horizontal line with the mouse on the left support bar of the bottom image and top image imported in step 3), and the program automatically calculates the midpoint of the horizontal line, which is the reference point L ₁ (X ₁ , Y ₁ )=(1203, 1380), L ₂ (X ₂ , Y ₂ )=(1306, 1350);

6) According to L ₂ (X ₂ , Y ₂ ), rotation angle θ ₁ , rotation angle θ ₂ , and image pixel width w, calculate the coordinates of point L ₂ in the θ ₁ imaging coordinate system (X′ _{2_θ1} , Y′ _{2_θ1} ) : present embodiment situation is as described in accompanying drawing 3 (e), can get (X ' _{2_θ1} , Y' _{2_θ1} )=(1045,1350) by formula (4-5), (4-7):

Y′ _{2_θ1} = Y′ ₂ (4-7)

Where: θ is the relative rotation angle and θ=θ ₂ -θ ₁ , w is the image pixel width, and f is the focal length of the camera;

7) According to the position offset during imaging, calculate the coordinates (X ₂ ', Y ₂ ')=(1345, 16457) of point L ₂ in the L ₁ coordinate system, and the calculation formula is as follows: (5-1)～( 5-2) as shown:

8) The verticality of the crane can be calculated according to formula (3), and ΔL=0.009630 can be obtained:

Claims (5)

1. a kind of lifting equipment measuring for verticality method based on unmanned plane image, it is characterised in that, include the following steps:

1) the bottom image of the tower crane bracket with configuration information, the configuration information high-precision position letter when being shooting are obtained Cease (X_w1, Y_w1) and rotation angle of camera θ₁；

2) top image of the tower crane bracket with configuration information, the configuration information high-precision position letter when being shooting are obtained Cease (X_w2, Y_w2) and rotation angle of camera θ₂；

3) optional piece image in the top image obtained in the bottom image and step 2) obtained in step 1), completes image Calibration, obtains the spatial resolution k of image_x、k_y, the k_x、k_yRespectively laterally, each longitudinal pixel distance represents Actual distance；

4) reference is selected in the left side brackets of the bottom image, the middle top image obtained of step 2) that obtain in step 1) respectively Point L₁(X₁, Y₁)、L₂(X₂, Y₂)；

5) according to L₂(X₂, Y₂), rotation angle, θ₁, rotation angle, θ₂, imaging when position (X_w1, Y_w1)、(X_w2, Y_w2), image pixel Width w calculates L₂Point is in L₁Abscissa X under coordinate system₂'.For different imaging positions, direction of rotation, rotation angle, have:

A) work as L₂Imaging point is on the left of the top image, and relative rotation angle is to the left and when θ > α:

B) work as L₂Imaging point is on the left of the top image, and relative rotation angle is to the left and when θ < α:

C) work as L₁Imaging point on the left of the top image, relative rotation angle to the right when:

D) work as L₂Imaging point is on the right side of the top image, and relative rotation angle is to the right and when θ > α:

E) work as L₂Imaging point is on the right side of the top image, and relative rotation angle is to the right and when θ < α:

F) work as L₂Imaging point on the right side of the top image, relative rotation angle to the left when:

Wherein: θ is relative rotation angle and θ=θ₂-θ₁, w is image pixel width, and f is camera focus；

6) L is calculated₂Point is in L₁Ordinate Y under coordinate system₂', specific formula for calculation such as following formula (2):

7) verticality of lifting equipment is calculated, specific formula for calculation such as following formula (3):

2. a kind of lifting equipment measuring for verticality method based on unmanned plane image according to claim 1, feature exist In: the step 1), 2) in high precision position information using double RTK (Real-Time Kinematic, in real time dynamic) to nothing It is man-machine to carry out positioning acquisition.

3. a kind of lifting equipment measuring for verticality method based on unmanned plane image according to claim 1, feature exist In: image calibration in the step 3) uses human-computer interaction, and being struck in the picture by people horizontal line, vertical line and inputs its correspondence Actual range.

4. a kind of lifting equipment measuring for verticality method based on unmanned plane image according to claim 1, feature exist In: the mark of the reference point in the step 4) uses human-computer interaction, and horizontal line of being struck in the picture by people marks branch on the left of bracket Strut, it is as a reference point that program calculates horizontal line midpoint automatically.

5. a kind of lifting equipment system for detecting verticality based on unmanned plane image, it is characterised in that: the measuring for verticality System includes unmanned plane, flies control module and image processing module, in which:

The unmanned plane is used to shoot the video of lifting equipment and the task image image set with configuration information, and data are real-time Be transferred to fly control module in；

The configuration information is high precision position information, the rotation angle of camera of unmanned plane when unmanned plane shoots image；

The task image image set includes lifting equipment frame bottom image and lifting equipment cradle top image；

The winged control module is used to control the flight of unmanned plane, and real-time reception unmanned plane is transmitted back to the video flowing come, Yi Jicun Store up the task image image set with configuration information of unmanned plane shooting；

The image processing module is integrated with 1 step 3) of claim to lifting equipment verticality calculating side described in step 7) Method flies the task image image set with configuration information stored in control module for handling analysis, calculates and obtain hanging down for lifting equipment Straight degree.