LU503475B1 - An Unmanned Airborne Binocular and Infrared Joint Diagnosis System and Method for Dam Patrol Inspection - Google Patents
An Unmanned Airborne Binocular and Infrared Joint Diagnosis System and Method for Dam Patrol Inspection Download PDFInfo
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Abstract
The invention discloses an unmanned aerial vehicle (UAV) for linear engineering disease detection and a detection method, wherein the UAV comprises an UAV body and a tripod head connected below the UAV; The tripod head comprises a shell, wherein a load mechanism is arranged in the shell and used for embedding the camera device; The camera device comprises a binocular camera, an infrared thermal imager and hyperspectral imaging equipment, and the orientations of the camera devices are consistent. The invention integrates binocular, infrared and hyperspectral imaging devices, and can realize the accurate identification of linear engineering diseases.
Description
An Unmanned Airborne Binocular and Infrared Joint Diagnosis 0503475
System and Method for Dam Patrol Inspection
The invention belongs to the field of linear engineering disease detection, in particular to an unmanned aerial vehicle (UAV) and a detection method for linear engineering disease detection.
The statements in this part only provide background information related to this disclosure, and do not necessarily constitute prior art..
Most of the important structures of the dam are made of concrete. In the long-term use process, it is damaged by external factors such as water power, corrosion and temperature stress, and influenced by many factors such as material performance degradation, which leads to great hidden dangers in dam safety. If there is an abnormality and it is not found in time, the consequences will be unimaginable. In order to ensure the safety of dam operation, it is necessary to detect the dam in time.
For the inspection of dam safety, the commonly used method is manual inspection.
Through traditional methods, such as visual observation and tapping, manual measurement and recording are carried out in the designated area to be measured, so as to judge whether the dam is abnormal or not. The number of daily inspections is normally once a week. In the annual flood season, torrential rain, earthquake and other special circumstances, daily inspections will be conducted continuously. Manual inspection is time-consuming and labor- intensive, and largely depends on empirical judgment, which leads to inaccurate inspection, low efficiency and low safety.
With the continuous maturity and development of UAV technology, UAVs can be used to inspect dams. Because the diseases around the dam usually appear in small positions in the pictures taken by unmanned aerial vehicles, and some diseases are not obvious, it is difficult to find them.
In order to overcome the shortcomings of the prior art, the invention provides an unmanned aerial vehicle (UAV) and a detection method for linear engineering disease 1 detection, which integrates binocular, infrared and hyperspectral imaging devices to realize LUS03475 accurate identification of linear engineering diseases.
To achieve the above object, one or more embodiments of the present invention provide the following technical solutions:
An unmanned aerial vehicle (UAV) for linear engineering disease detection and a detection method thereof. The UAV comprises an UAV body and a tripod head connected below the UAV;
The tripod head comprises a shell, wherein a load mechanism is arranged in the shell and used for embedding the camera device; The camera device comprises a binocular camera, an infrared thermal imager and hyperspectral imaging equipment, and the orientations of the camera devices are consistent.
One or more embodiments provide an unmanned aerial vehicle (UAV) and a detection method for linear engineering disease detection, including the following steps:
Initializing an area to be inspected and an inspection route of the unmanned aerial vehicle;
Receiving the pose information of the unmanned aerial vehicle, and controlling the shooting angle and zoom adjustment of the camera device according to the pose;
Receiving the image data of the shooting device, sending it to the mobile client and storing it;
The mobile client receives the image data, fuses and visualizes the images taken by different camera devices.
A variety of imaging devices, including binocular, infrared and hyperspectral imaging devices, are integrated through the pan/tilt, and all kinds of imaging devices can adjust the direction and focal length based on the pose of the unmanned aerial vehicle, so that they can be accurately aligned with the linear engineering to be detected, which provides a guarantee for the accurate identification of the diseases of the linear engineering,
The drawings in the specification which form a part of the present invention are used to provide a further understanding of the present invention. The illustrative embodiments of the present invention and their descriptions are used to explain the present invention, and do not constitute undue limitations on the present invention. 2
Fig. 2 is a schematic diagram of a four-eye tripod head used for linear engineering LY503475 disease detection and a detection method in the embodiment of the invention.
Fig. 3 is a side view of a four-eye tripod head used for linear engineering disease detection and a detection method in the embodiment of the invention.
Fig. 4 is a flow chart of an unmanned aerial vehicle (UAV) for linear engineering disease detection and the working method of the detection method in the embodiment of the present invention.
Fig. 5 is a flow chart of a zoom binocular operation of an unmanned aerial vehicle (UAV) and a detection method for linear engineering diseases in the embodiment of the present invention.
Embodiment I
This embodiment provides an unmanned aerial vehicle (UAV) and a detection method for linear engineering diseases. The UAV comprises an UAV body 1, an expansion board 2 fixed at the lower end of the UAV body, and a tripod head 3 installed below the expansion board.
The UAV body 1 comprises a plurality of moment arms arranged around the UAV body, a rotor arranged at the tail end of the moment arms, and a control device for controlling the flight of the UAV body 1. In this embodiment, the unmanned aerial vehicle adopts a six-rotor wing; Furthermore, the UAV body 1 is provided with a gyroscope to measure the posture and tilt angle of the UAV.
The expansion plate 2 is fixed at the lower end of the belly of the unmanned aerial vehicle. The upper part of the expansion board 2 also includes a voltage adapter 11, and the connector of the voltage adapter is fixed at the converted voltage to supply power to the pan/tilt, the sensor device, the camera device, etc. Specifically, the power supply is provided by the UAV power supply.
A tripod head base is arranged below the expansion plate 2, and is connected with the tripod head through a rotating shaft and a supporting assembly. The upper part of the rotating shaft 10 is connected with the base, and the rotating shaft can rotate horizontally relative to the base 7; The lower part of the rotating shaft 10 is connected with the supporting assembly 8, and the supporting assembly 8 can rotate vertically relative to the rotating shaft. The supporting assembly 8 comprises a plurality of mechanical arms and a tripod head support 3 frame, which are connected with the base 7 through a rotating shaft 10. In this embodiment, LYS05475 the multi-mechanical arms are two mechanical arms. The other end of that multi-section support arm is connected with a cradle head support frame.
The tripod head comprises a shell, and a load mechanism and a control unit are also arranged in the shell. Wherein the load mechanism is used for fixing the control unit and the imaging device. The camera device includes a binocular camera 4, an infrared thermal imager and a hyperspectral imaging device 6. Image data captured by the binocular camera 4, the infrared thermal imager 5 and the hyperspectral equipment 6 are all transmitted to the control unit. The shell is a hemispherical shell, which is surrounded in a cradle head support frame and is rotationally connected with the cradle head support frame, and the other end of the cradle head support frame is connected with a plurality of support arms. There are four holes on the shell surface corresponding to the cross section of the hemispherical shell, which are respectively used to accommodate the two lenses of the binocular camera 4, the infrared thermal imager 5 and the lens of the hyperspectral equipment 6. The load mechanism is provided with a rotating shaft and a corresponding driving module for each lens. The hemispherical setting of the tripod head and the multi-degree-of-freedom rotating shaft ensure the flexibility of the tripod head and facilitate the comprehensive monitoring of all positions of the linear project.
Specifically, the camera device includes a binocular camera 4, an infrared thermal imager 5 and a hyperspectral device 6, which are connected with a control unit through an image transmission unit. Among them, the axis of the binocular camera 4 is fixed, and the binocular camera is connected with the control unit of the pan/tilt through a signal line, and the left and right cameras can zoom at the same time. The collected images are processed by feature extraction and feature tracking, so that the distance and location of the target can be obtained, and the size of the disease can be quantitatively measured in the processed images.
The infrared detector of the infrared thermal imager 5 selects a detector capable of receiving long-wave infrared rays, and by utilizing the strong penetrating power of long-wave infrared rays, it can shoot the leakage object covered by interference factors such as weeds in a long distance; The imaging spectrometer of the hyperspectral equipment 6 can obtain multi-band image data with narrow band width, which can supplement the image data shot by binocular camera and infrared thermal imager to enhance the identification of diseases.
The control unit receives the measurement result sent by the gyroscope, and adjusts the torque and rotation angle of the motor of the driving module to adjust the shooting angle of the camera, so as to ensure that the camera can accurately shoot the target. The control unit 4 and the driving module are connected with the camera device; The driving module comprises LUYS03475 a plurality of motors and transmission components, and the motors are connected with the transmission components.
Furthermore, a shock absorber is arranged at the joint of the cradle head and the expansion board to reduce the vibration of the cradle head when the unmanned aerial vehicle shakes and lands.
The mobile client receives the information transmitted by the image transmission unit, processes the data, and sends out a control signal.
The image transmission unit is an unmanned aerial vehicle mobile transmission device adopting COFDM technology, which is internally provided with a memory card slot. The image transmission unit is electrically connected with the control unit and the camera device of the tripod head. The image transmission unit is installed at the rear of the load device of the quadruped tripod head. The image transmission unit has the characteristics of anti-multipath interference ability of COFDM modulation technology, and has certain diffraction ability and mobility at a lower frequency, which can realize long-distance stable transmission of a large number of high-quality data images and store them in the memory card.
After the image information transmitted by the image transmission unit is analyzed by the mobile client processor, the images shot by the camera device are fused and output to the display screen, the images shot by binocular are used as the base map, and the images shot by the infrared thermal imager and hyperspectral equipment are suspended on the base map for joint imaging, which can be displayed in contrast or switched, so that the situation of the shot images can be observed in real time, and the ambiguous diseases and abnormalities can be compared and determined by combining multiple images. The processor also combines the application of image processing in the field of deep learning, and through relevant program algorithms, it can be used in image processing.
Specifically, the stereo image shot by binocular camera is used as the base map, and at least one of infrared image and hyperspectral image floats on the base map. Among them, because the hyperspectral image includes many bands of images, and the images with different bands have different degrees of recognition for the target, in this embodiment, the optimal combination mode is also selected for the hyperspectral image, so as to obtain the disease of hyperspectral image recognition.
The expansion board, the tripod head and the camera device are all made of carbon fiber, which can greatly reduce the weight of the device and improve the endurance time and mobility of the unmanned aerial vehicle.
A shock absorber 12 is arranged at the joint with the extension plate of the platform, and LU503475 the shock absorber can also use a simple shock-absorbing ball to reduce the vibration of the platform when the drone shakes and lands, thus playing a role in protecting the platform.
Embodiment II
The purpose of this embodiment is to provide an unmanned aerial vehicle detection method for linear engineering disease detection, which includes the following steps:
S1, setting the inspection route of the unmanned aerial vehicle or manually controlling the unmanned aerial vehicle to fly in the area to be inspected;
S2, the tripod head senses the pose and tilt angle of the unmanned aerial vehicle to judge, controls the shooting angle of the camera and adjusts the zoom;
S3, the camera takes pictures of linear projects such as dams and the like, and sends the pictures to the image transmission unit, which sends the data image information to the mobile client and saves the shot videos and pictures;
S4, the inspector can see the real-time picture shot by the camera device from the display screen of the mobile client on the ground, and control the UAV and the PTZ according to the observed situation; Then, the target features are automatically extracted and measured. It can be displayed in contrast or switched pictures, and can observe the situation of the shot pictures in real time. For ambiguous diseases and abnormalities, it can be compared and determined by combining multiple pictures.
At the same time, S5, the mobile client performs data processing on the received video picture to obtain the position and size of the disease.
In the developed software, the program will automatically extract and measure the features of the received video images in the background, at least they are parallel; After processing, the disease information can be effectively marked on the display screen in real time.
The image data processing method of the binocular camera comprises the following steps:
Firstly, set the initial position and calibrate Zhang Zhengyou's plane; After changing the lens parameters, the internal and external parameters are estimated according to the matching points of the front and back images, and the binocular parameters are further obtained. 1) Zhang Zhengyou's plane calibration method is adopted, and the camera's internal and external parameters are obtained by shooting images with binocular cameras. The points of the binocular camera's optical axis passing through the imaging plane are taken as the origin 6
(u0, v0) of the image coordinate system as the camera's internal reference, and the focal LUS03475 lengths of the binocular cameras are f1 and f2, respectively; Calibrate the coordinates of the target point P on the image coordinate system on the coordinate system "checkerboard", and record them as (ul, v1) on the left coordinate system and (u2, v2) on the right; 2) The world coordinate system is established by the optical centers of binocular cameras, with the optical center of left camera being Ol, the optical center of right camera being Or, and the optical center spacing being B. The two world coordinate systems are Ol-x1y1z1 and
Or-x2y272, and the coordinates of point P in the two world coordinate systems are (x1, y1, z1) and (x2, y2, z2) respectively; According to the spatial relationship between the two coordinate systems, the coordinates of point P in Or-x2y2z2 can also be expressed as (x1-b, y1, z1);
The left camera is a fixed-focus camera, and the right camera is a zoom camera. Repeat the above steps, establish a coordinate system, and show the P-point image coordinates according to the damage target identification. 3) Through the image coordinates of point P, it can be obtained from similar triangles and projection relation: ul=yl-y0=f ha zl visyl-vO=fl 7,
Zi uësu2-u0 ppt? ; v2svè-v eros si
From the above formula, the coordinate relation of point P can be obtained: xl — PME , wlf2-u2f1 ï ulf2-u2fi pie A uif2-u2f1 4) Use the above method to calculate the three-dimensional coordinates (x1, y1, z1) and (x1'y1",z1") of the two points to be measured, and then conveniently calculate the distance between the two points to be measured, that is, the size of the disease is: dod (x1—x1)2 + (y1l—y1)* + (21-21)? 7
After the inspection, the inspector can recheck the video and image information stored in LUS08475 the memory card to ensure the detection accuracy of the detected object. 8
Claims (9)
1. An unmanned aerial vehicle (UAV) and a detection method for linear engineering disease 1705475 detection, characterized by comprising: an UAV body and a tripod head connected below the UAV; The tripod head comprises a shell, wherein a load mechanism is arranged in the shell and used for embedding the camera device; The camera device comprises a binocular camera, an infrared thermal imager and hyperspectral imaging equipment, and the orientations of the camera devices are consistent.
2. The unmanned aerial vehicle (UAV) and detection method for linear engineering diseases according to claim 1, characterized in that a control unit is embedded in the load mechanism and connected with the camera device.
3. The unmanned aerial vehicle (UAV) and the detection method for linear engineering disease detection according to claim 1, characterized in that a cradle base is arranged below the UAV body, and the cradle base is connected with the cradle through a rotating shaft and a supporting assembly; Wherein, the upper part of the rotating shaft is connected with the platform base and can rotate horizontally relative to the platform base; The lower part of the rotating shaft is connected with the supporting component, so that the supporting component can rotate in the vertical direction relative to the rotating shaft; The support assembly is connected with the cradle head.
4. The unmanned aerial vehicle (UAV) and detection method for linear engineering disease detection according to claim 3, characterized in that the support assembly comprises a multi- section mechanical arm and a tripod head support frame, and one end of the multi-section support arm is connected with a rotating shaft and the other end is connected with the tripod head support frame.
5. The unmanned aerial vehicle (UAV) and the detection method for linear engineering diseases as claimed in claim 4, characterized in that the shell is a hemispherical shell, which is surrounded in a tripod head support frame and rotatably connected with the tripod head support frame, and the other end of the tripod head support frame is connected with a plurality of support arms.
6. The unmanned aerial vehicle (UAV) and the detection method for linear engineering diseases as claimed in claim 5, characterized in that the shell surface corresponding to the cross section of the hemispherical shell is provided with four holes, which are respectively used for accommodating two lenses of a binocular camera, an infrared thermal imager and a lens of a hyperspectral device. 9
7. The unmanned aerial vehicle (UAV) and the detection method for linear engineering LU503475 diseases according to claim 1, characterized in that the load mechanism includes the rotating shaft of each lens and the corresponding driving module.
8. The unmanned aerial vehicle (UAV) and the detection method for linear engineering diseases according to claim 1, characterized in that an expansion plate is further arranged between the UAV body and the platform, and a shock absorber is arranged at the joint between the platform and the expansion plate.
9. The unmanned aerial vehicle (UAV) and detection method for linear engineering disease detection according to claim 8, characterized in that the expansion board is provided with a voltage adapter for providing power to the pan/tilt.
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| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| LU503475A LU503475B1 (en) | 2023-02-13 | 2023-02-13 | An Unmanned Airborne Binocular and Infrared Joint Diagnosis System and Method for Dam Patrol Inspection |
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| Application Number | Priority Date | Filing Date | Title |
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| LU503475A LU503475B1 (en) | 2023-02-13 | 2023-02-13 | An Unmanned Airborne Binocular and Infrared Joint Diagnosis System and Method for Dam Patrol Inspection |
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