Pole tower real-time positioning method and system for power grid inspection

Abstract

The invention discloses a tower real-time positioning method and system for power grid inspection, and relates to the technical field of power grid inspection, and the technical scheme is characterized in that an airborne end sets identification information for airborne data collected in the flight process of the airborne end; the airborne end carries out data preprocessing on the airborne data provided with the identification information and uploads the data to a cloud end, three-dimensional positioning is carried out according to the preprocessed airborne data, and height data of a tower is obtained through calculation; the airborne end uploads real-time data collected in the flying process of the airborne end to the cloud end, and the position coordinates of the tower are calculated by combining the height data of the tower. According to the method, a stand-alone virtual cross positioning method is adopted, in the flight process, the nacelle locks the spire, meanwhile, carrier poses and nacelle attitude angles of a plurality of collection points are taken out according to specific intervals, cross points of a plurality of nacelle sight lines are solved, and position coordinates of a tower are obtained through calculation.

Description

Technical Field

[0001] The invention relates to the field of power grid inspection technology, and more specifically, to a real-time positioning method and system for pole towers used for power grid inspection. Background Art

[0002] Automatic inspection by drones is widely used in the field of power grid inspection. It has the advantages of low technical requirements, easy operation and low labor costs. The optoelectronic payloads carried by drones can provide real-time detection, pole tower tracking, real-time pole tower positioning and other services. Therefore, the target positioning accuracy of the airborne optoelectronic system is an important indicator. Affected by the terrain, the main difficulty in pole tower positioning is that the height of the pole tower is not fixed, so it is necessary to accurately obtain the tower height during positioning.

[0003] The visual positioning method is mainly divided into direction finding positioning and distance finding positioning. The present invention uses the direction finding positioning method. Direction finding positioning means that a ray is extended according to the direction in which the optoelectronic pod is looking, and the intersection of the ray and the target height is calculated, which is the target position. The airborne sensor can measure the azimuth and pitch angle. Combined with the tower height, the tower can be positioned in real time.

[0004] In the prior art, a Chinese patent (CN110487266B) proposes an airborne optoelectronic high-precision passive positioning method suitable for sea surface targets. In this method, the height of the sea level is known, and during the positioning calculation, the earth is regarded as an ellipsoid, and the parameters of the ground target are substituted into the ellipsoid equation for solution. In fact, the height of the tower is unknown, and the tower is on the ground. The ground target is not suitable for the ellipsoid equation, so it is necessary to propose a method that can accurately locate the height and position of the ground tower.

[0005] In the prior art, a Chinese patent (CN112985398A) also proposes a passive target positioning method, which can support the positioning of any target point on the pixel plane in the geographic coordinate system. In this method, the take-off position of the drone is taken as the origin, and the due east and due north are used as the X and Y axes respectively to construct an inertial coordinate system. The center of mass of the carrier is taken as the origin, and the due north and due east are used as the X and Y axes respectively to construct the aircraft geographic coordinate system. The position coordinates of the aircraft in the inertial coordinate system are used as the conversion matrix to form a conversion from the inertial coordinate system to the aircraft geographic coordinate system. Then, the aircraft geographic coordinate system is gradually converted from the aircraft geographic coordinate system to the aircraft geographic coordinate system. The coordinate system is converted to the camera coordinate system. In the subsequent calculation, the position coordinates of the camera optical center in the camera coordinate system are transformed into the inertial coordinate system. The conversion matrix from the inertial coordinate system to the aircraft geographic coordinate system is directly used. By default, in the inertial coordinate system, the aircraft position and the camera position are the same, but there is a position difference between the two. At the same time, the assumption put forward in this passive target positioning method is that the ground is flat, that is, the ground elevation at the aircraft's flight position and the ground elevation of the target point must be consistent, while the change of the ground elevation during the actual flight is uncertain, which has limitations in actual use.

[0006] Therefore, the present invention aims to provide a real-time positioning method and system of a tower for power grid inspection to solve the above problems. Summary of the invention

[0007] The purpose of the present invention is to provide a real-time positioning method and system for pole towers for power grid inspection. The present invention adopts a single-machine virtual cross positioning method. During the flight, the pod locks the tower top, and at the same time, the carrier posture and pod attitude angle of multiple collection points are taken out at specific intervals, the intersection of multiple pod sight lines are solved, and the position coordinates of the pole tower are calculated.

[0008] The present invention is implemented as follows: a real-time positioning method for a tower used for power grid inspection, the method comprising:

[0009] The airborne end sets identification information on the collected airborne data to obtain the airborne data with the identification information set;

[0010] The airborne end performs data preprocessing on the airborne data provided with the identification information to obtain the preprocessed airborne data;

[0011] The airborne end uploads the pre-processed airborne data to the cloud, performs three-dimensional positioning according to the pre-processed airborne data, and calculates the height data of the tower;

[0012] The airborne terminal uploads the collected real-time data to the cloud, and calculates the position coordinates of the tower in combination with the height data of the tower.

[0013] Further, the airborne end performs data preprocessing on the airborne data provided with the identification information, including:

[0014] The airborne end performs error calibration on the airborne data provided with the identification information to obtain the error-calibrated airborne data after error calibration;

[0015] The airborne end synchronizes the calibrated airborne data to the cloud, completes the operation of preprocessing the airborne data provided with the identification information, and obtains the preprocessed airborne data.

[0016] Furthermore, the airborne end synchronizes the calibrated airborne data to the cloud, including:

[0017] The airborne end performs time alignment processing using identification information of the airborne data;

[0018] The airborne end calculates the information of the pod attitude at the time of the identification information of the carrier attitude based on the time of the carrier attitude, and obtains the data closest to the time of the latest carrier attitude identification information;

[0019] The airborne end determines whether the time difference is within a preset time range based on the data closest to the latest carrier posture identification information, and obtains the identification information of the carrier posture.

[0020] Furthermore, the method further comprises:

[0021] The cloud receives the airborne data preprocessed by the airborne end;

[0022] The cloud end calculates the intersection of the airborne data based on the airborne data preprocessed by the airborne end;

[0023] The cloud end converts the intersection points of the airborne data into three-dimensional coordinates of the tower, thereby obtaining the height data of the tower.

[0024] Furthermore, the method further comprises:

[0025] The cloud receives the real-time data collected by the airborne terminal;

[0026] The cloud terminal combines the real-time data collected by the airborne terminal with the height data of the pole tower, and calculates the intersection information of the real-time data and the height of the pole tower by using the spatial relationship;

[0027] The cloud performs coordinate conversion according to the intersection information of the real-time data and the tower height, and calculates the position coordinates of the tower.

[0028] Further, the airborne end determines whether the time difference is within a preset time range according to the data closest to the latest carrier posture identification information, including:

[0029] The airborne terminal stores 20 aircraft postures and pod postures collected during the flight, finds the data closest to the latest aircraft posture identification information from the pod posture identification information, and obtains the identification information of the aircraft posture;

[0030] When the airborne end determines that the time difference is less than 10 ms according to the identification information of the carrier posture, the airborne end does not need to perform interpolation alignment; otherwise, the airborne end needs to perform interpolation alignment.

[0031] The present invention also provides a real-time positioning system for a pole tower used for power grid inspection, the real-time positioning system for a pole tower comprising:

[0032] A setting module, used to set identification information on the collected airborne data, and obtain the airborne data set with the identification information;

[0033] A preprocessing module, used for performing data preprocessing on the airborne data provided with the identification information to obtain the preprocessed airborne data;

[0034] A transmission module is used to upload the pre-processed airborne data to the cloud, and perform three-dimensional positioning according to the pre-processed airborne data to calculate the height data of the tower;

[0035] The positioning module is used to upload the collected real-time data to the cloud, and calculate the position coordinates of the tower in combination with the height data of the tower.

[0036] Furthermore, the tower real-time positioning system also includes an airborne terminal, which includes a device body, and the airborne terminal also includes

[0037] A memory storing executable program code;

[0038] a processor coupled to the memory;

[0039] The processor calls the executable program code stored in the memory to execute the steps performed by the airborne end in a method for real-time positioning of a tower for power grid inspection.

[0040] Furthermore, the tower real-time positioning system also includes a cloud, which includes:

[0041] A memory storing executable program code;

[0042] a processor coupled to the memory;

[0043] The processor calls the executable program code stored in the memory to execute the steps performed by the cloud in a method for real-time positioning of a tower for power grid inspection.

[0044] Furthermore, the real-time positioning system for pole towers also includes a computer storage medium, wherein the computer storage medium stores computer instructions, and when the computer instructions are called, a real-time positioning method for pole towers used for power grid inspection is executed.

[0045] Compared with the prior art, the present invention has the following beneficial effects:

[0046] 1. The present invention combines a single-machine virtual cross positioning method with a single-machine real-time direction finding positioning method to accurately obtain the height and position of the power grid tower, significantly improving the accuracy of tower positioning during power grid inspection, especially when the tower height is not fixed and the terrain is complex. At the same time, the present invention can give the current tower position within 50ms, meeting the requirements for real-time positioning during short-distance inspections, so that the UAV can quickly respond to changes in the tower position during flight, thereby improving inspection efficiency;

[0047] 2. The method of the present invention can also reduce the demand for manual inspections, reduce labor costs, and improve the safety of inspection work, avoiding the dangers that may occur in manual inspections. In addition, the real-time positioning method of the tower of the present invention is applicable to various terrains and is not affected by changes in ground elevation, so that drones can perform power grid inspections under different terrain conditions, thereby improving the efficiency and coverage of inspection work;

[0048] 3. The present invention fully considers the applicability of various terrains, so that the real-time positioning system of the pole tower has better adaptability, can work stably under various environmental conditions, and improves the reliability of the system. At the same time, the present invention can effectively process and correct data errors through data preprocessing steps, including pixel deviation calibration and data synchronization processing, and improves the accuracy and stability of data processing;

[0049] 4. The positioning method of the present invention is not only applicable to power grid inspection, but can also be extended to other fields that require precise positioning, such as building monitoring, environmental monitoring, etc. It has broad application prospects, and can help reduce the impact on the environment by reducing the use of manual inspections and ground equipment. It is an environmentally friendly technical solution;

[0050] 5. The present invention adopts advanced UAV technology and optoelectronic payload, combined with modern computer vision and spatial positioning technology, which reflects the advancement and innovation of technology. At the same time, by improving inspection efficiency and reducing labor costs, it can bring significant economic benefits to power grid operators and reduce the risk of power grid failure caused by untimely inspection, which has great practical significance. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] Figure 1 It is a flow chart of a method for real-time positioning of a tower for power grid inspection provided by an embodiment of the present invention;

[0052] Figure 2 is a schematic diagram of time calibration using polynomial interpolation provided by an embodiment of the present invention;

[0053] Figure 3 is a schematic diagram of a positioning accuracy evaluation test provided by an embodiment of the present invention;

[0054] Figure 4 It is a structural schematic diagram of a real-time positioning system for a tower used for power grid inspection provided by an embodiment of the present invention;

[0055] Figure 5 It is a data flow diagram of a real-time positioning system for a tower used for power grid inspection provided by an embodiment of the present invention;

[0056] Figure 6 is a structural schematic diagram of an airborne terminal provided by an embodiment of the present invention;

[0057] Figure 7 It is a schematic diagram of a cloud structure provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0058] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0059] The implementation of the present invention is described in detail below in conjunction with specific embodiments.

[0060] The same or similar numbers in the drawings of this embodiment correspond to the same or similar parts; in the description of the present invention, it should be understood that if the terms "upper", "lower", "left", "right" and the like indicate directions or positional relationships based on the directions or positional relationships shown in the drawings, it is only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific direction, be constructed and operated in a specific direction. Therefore, the terms describing the positional relationship in the drawings are only used for illustrative purposes and cannot be understood as limitations on this patent. For ordinary technicians in this field, the specific meanings of the above terms can be understood according to specific circumstances.

[0061] Reference Figure 1-7 The figure shows a preferred embodiment of the present invention.

[0062] Embodiment 1: A real-time positioning method for power towers used for power grid inspection

[0063] 1) The airborne end sets identification information for the collected airborne data to obtain the airborne data with the identification information set.

[0064] In this embodiment, a single-machine virtual cross-positioning method is used to calculate the tower height. During the flight, the tower top is locked by the pod, and the carrier posture and pod attitude angle of multiple collection points are taken out at specific intervals (different intervals are used for different offline heights). The intersection of multiple pod lines of sight is solved, which is the three-dimensional coordinate of the tower. Conceptually, this method virtualizes multiple collection points during the flight of a drone into multiple drones for use, so it is called single-machine virtual cross-positioning.

[0065] 2) The airborne end performs data preprocessing on the airborne data provided with the identification information to obtain preprocessed airborne data.

[0066] In the data preprocessing of this embodiment, the airborne data is first denoised. Since the drone may be subject to various interferences during flight, the collected data may contain noise. This embodiment uses denoising algorithms such as median filtering and mean filtering to effectively reduce the impact of noise on subsequent positioning accuracy. After the airborne end receives the airborne data such as the carrier posture and pod posture published by the vision, the pole tower real-time positioning system performs pixel deviation calibration and data synchronization operations on the airborne data; during the pixel deviation calibration, the image captured by the airborne end is always locked to the pole tower. When the airborne end continuously captures and tracks during the flight, the airborne end determines that if the pole tower is not in the center of the image, the pole tower position is not the position pointed to by the pod light source. At this time, the airborne end should make corrections based on the pixel deviation of the pole tower. The formula for pixel deviation calibration is as follows:

[0067] dθ2=atan2(dpixcelY,focus)

[0068] dψ2=atan2(dpixcelX,focus)

[0069] g_θ=g_θ1-dθ2

[0070] g_ψ=g_ψ1+dψ2

[0071] Among them, dpixcelX and dpixcelY represent the pixel deviation in the x direction and the pixel deviation in the y direction from the center of the image to the top of the tower, respectively; focus represents the physical focal length; dθ2 and dψ2 represent the frame angle deviation of the tower from the center of the image, respectively; g_θ1 and g_ψ1 represent the pitch angle and yaw angle of the pod frame, respectively; g_θ and g_ψ represent the pitch angle and yaw angle of the pod frame after the tower is corrected to the center of the image, respectively.

[0072] During the flight of the drone, the positioning algorithm corrects the pod frame angle by receiving pixel deviations in real time.

[0073] 3) The airborne end uploads the preprocessed airborne data to the cloud, performs three-dimensional positioning based on the preprocessed airborne data, and calculates the height data of the tower.

[0074] In the data synchronization operation of this embodiment, after the visual system receives the image message, it sends the carrier posture with timestamp and the gimbal frame angle with timestamp to the positioning algorithm. Due to the link transmission delay, the time when the visual posture information is received and the time when the pod posture is received may be inconsistent, so the pod information needs to be time-aligned.

[0075] In this embodiment, a polynomial interpolation method is used for time calibration, such as Figure 2 As shown, the time of the carrier posture is taken as the standard, and the information of the pod posture at the timestamp of the carrier posture is calculated. In this embodiment, 20 carrier postures and pod postures are stored. From the timestamp of the pod posture, find the data closest to the timestamp of the latest carrier posture. If the time difference is less than 10ms, it is considered that no interpolation alignment is required, otherwise interpolation alignment is required, as follows:

[0076] If the function y=f(x) is known at points x0,x1,...,x n The values ​​on are y0,y1,...,y n , define an n-order interpolation polynomial L n (x), so that L n (x) is approximately equal to the function y = f(x), L n The expression of (x) is as follows:

[0077] L n (x) = a0 + a1x + a2x 2 +...+a n x n

[0078] Substitute the above n+1 points to solve the n+1 order linear equations:

[0079]

[0080] Right now:

[0081]

[0082] The solution is that at any point x i Department:

[0083]

[0084] Taking the three-dimensional case as an example, at the kth sampling moment, the pod Euler yaw angle and the pod Euler pitch angle of the ith observation point can be expressed as t observation stations can obtain t groups of measurement values. Due to the existence of time drift, each observation station does not provide measurements strictly according to a fixed sampling period. In this embodiment, an interpolation polynomial is constructed using 4 difference nodes, and the aligned pod Euler yaw angle and pod Euler pitch angle at k (k≥5) sampling moments can be obtained as follows:

[0085]

[0086] where is the kth sampling moment of the ith observation station, are the azimuth angle and pitch angle of the ith observation station after drift calibration, respectively.

[0087] In actual use, the interpolation method is adopted, and the coefficient moments are 1, 2, 3, 4. The value to be fitted is inserted between 3 and 4, and the aligned pod Euler yaw angle and pod Euler pitch angle at the moment s (3<s<4) can be obtained as follows:

[0088]

[0089] where t s represents the position of the difference between the moment of the pod attitude and the moment of the nearest carrier position attitude among the four coefficient moments. For example, if the carrier position attitude refresh frequency is 20Hz and the unit interval is 50ms, the moment of the pod attitude is 20984082, and the moment of the nearest carrier position attitude to the pod is 20984052, and the difference between the two is 30ms, then t s =3 + 30 / 50 = 3.6.

[0090] During the flight, the positioning algorithm will obtain the moment of the carrier position attitude and the pod attitude in real time for time alignment processing. The aligned pod attitude is the pod attitude at the moment of the carrier position attitude.

[0091] In the multi-point direction finding cross positioning method, this embodiment calculates the tower height by adopting the idea of ​​single-machine virtual cross positioning. In this link, in addition to taking out the carrier posture and pod attitude angle of multiple collection points at specific intervals, it can also combine the point cloud data obtained by the airborne laser radar to further improve the solution accuracy of the three-dimensional coordinates of the tower. By preprocessing the point cloud data, the key feature points of the tower are extracted, and then merged with the results of the single-machine virtual cross positioning, the position of the tower can be determined more accurately. Single-machine virtual cross positioning is to virtualize multiple collection points during the flight of a drone into multiple drones for use. The positioning method used is multi-point direction finding cross positioning. The multi-point direction finding cross positioning method is to use two or more drones carrying high-precision sensors to measure the direction of the target. Since the airborne sensor can measure the azimuth and pitch angle, the target can be positioned in three dimensions by two drones.

[0092] At the same time, this embodiment also includes an improvement on the multi-point direction finding cross positioning method. In practical applications, in addition to using two or three drones for cross positioning, more drones are considered to be introduced to participate in positioning to form a multi-machine collaborative positioning system. By optimizing the flight path and direction finding angle of the drones, and adopting more advanced data fusion algorithms, such as Kalman filtering, the accuracy and reliability of tower positioning are further improved.

[0093] When positioning the target with two set drones, the coordinate system OXYZ is the northeast sky coordinate system, and the three-dimensional coordinates of the target radiation source C are expressed as (x, y, z) T , the three-dimensional coordinates of each drone (x i ,y i ,z i ) T , i = 1, 2, the azimuth and pitch angles of each UAV measured by the airborne sensor in the ground northeast sky coordinate system are (α i ,β i ) T ,i=1,2, the positioning equation can be expressed as:

[0094]

[0095] The Euler angle of the pod when drone A locks the target is (α1, β1), and the Euler angle of the pod when drone B locks the target is (α2, β2). According to the trigonometric formula of azimuth angle α1 It turns out that:

[0096] -xtanα1+y=y1-x1tanα1

[0097] From the trigonometric formula of the pitch angle β1 It turns out that:

[0098] ytanβ1+zsinα1=y1tanβ1+z1sinα1

[0099] From the trigonometric formula of the azimuth angle α2, we get

[0100] -xtanα2+y=y2-x2tanα2

[0101] From the trigonometric formula of the pitch angle β2 It turns out that:

[0102] ytanβ2+zsinα2=y2tanβ2+z2sinα2

[0103] The system of equations can be expressed in matrix form as:

[0104]

[0105] The above formula is simplified to: AX = b, and its least square root is X = (A T -A) -1 A T b, X is the solved three-axis coordinates.

[0106] In this embodiment, in order to more accurately obtain the tower height, a three-drone cross positioning algorithm is used. The expression of the three drone cross positioning is as follows:

[0107]

[0108] The solution (x,y,z) T It is the three-dimensional coordinate of the tower. However, due to the low frequency of positioning calculation by the virtual cross positioning algorithm, it cannot meet the real-time positioning requirements of the tower during short-distance inspections by drones. Therefore, the present invention only uses the z coordinate in the positioning result as the tower height.

[0109] In the single-machine real-time direction finding and positioning, the spatial relationship is used to calculate the coordinates of the intersection of the optoelectronic pod line of sight and the tower height. The calculation method is as follows:

[0110] The coordinate transformation formula from the earth to the body is as follows:

[0111]

[0112] Among them, θ, Φ, and ψ represent the pitch angle, roll angle, and yaw angle of the carrier aircraft, respectively, and c and s in the formula represent cos and sin, respectively.

[0113] The coordinate conversion formula from the fuselage to the pod is as follows:

[0114]

[0115] Among them, g_θ and g_ψ represent the pitch angle and yaw angle of the pod frame respectively.

[0116] The coordinate conversion from the earth to the pod pointing is as follows:

[0117] Rvg=Rbg×Rvb

[0118] Rvg[1][3]=Rbg[1][1]·Rvb[1][3]+Rbg[1][2]·Rvb[2][3]+Rbg[1][3]·Rvb[3][3]

[0119] Rvg[1][2]=Rbg[1][1]·Rvb[1][2]+Rbg[1][2]·Rvb[2][2]+Rbg[1][3]·Rvb[3][2]

[0120] Rvg[1][1]=Rbg[1][1]·Rvb[1][1]+Rbg[1][2]·Rvb[2][1]+Rbg[1][3]·Rvb[3][1]

[0121] The Euler angle of the pod is calculated as follows:

[0122] GimEularTheta=-asin(Rvg[1][3])

[0123] GimEularPsi=atan2(Rvg[1][2],Rvg[1][1])

[0124] Among them, GimEularTheta represents the Euler yaw angle of the pod, and GimEularPsi represents the Euler pitch angle of the pod.

[0125] The target positioning calculation for known ground height is as follows:

[0126] X target =X plane +(H plane -H target )×cos(GimEularPsi) / tan(GimEularTheta)

[0127] Y target =Y plane +(H plane -H target )×sin(GimEularPsi) / tan(GimEularTheta)

[0128] In the above formula, X plane , Y plane , H planeThey represent the coordinates of the aircraft in the northeast sky coordinate system, H target Indicates the tower height.

[0129] 4) The airborne terminal uploads the collected real-time data to the cloud, and calculates the location coordinates of the tower in combination with the tower height data.

[0130] In the present embodiment, during the flight, the positioning algorithm will obtain the coordinates of the carrier aircraft, the three-axis angles of the carrier aircraft, and the frame angle of the pod in real time to calculate the X and Y coordinates of the tower.

[0131] The method in this embodiment is applicable to power grid inspection technology in various terrains, making the industry application more extensive. The positioning of the pole tower can also be adjusted in real time during the flight of the drone. Moreover, when switching the pole tower, the method can give the current tower position within 50ms, meeting the requirements of real-time positioning and rapid response during short-distance inspections.

[0132] Specifically, in this embodiment, a positioning accuracy evaluation test is also set, such as Figure 3 As shown, adjust the pod to one-fold field of view, adjust the pod pitch angle to -10 degrees, -25 degrees, and -45 degrees respectively. After the pod pitch angle reaches the specified angle, adjust the drone height to 5 meters, 13 meters, and 26 meters offline respectively. The drone is about 30 meters away from the tower, maintain the visual detection state, and the tower tip is in the center of the image. Make the drone hover to check the system's positioning accuracy to the tower at different pitch angles. In the figure below, the horizontal axis is the x-axis of the northeast sky coordinate system, and the vertical axis is the y-axis of the northeast sky coordinate system. The blue mark represents the drone coordinates and the tower positioning coordinates when the pod pitch angle is -10 degrees, and the positioning accuracy is 5 to 8 meters. The green mark represents the drone coordinates and the tower positioning coordinates when the pod pitch angle is -25 degrees, and the positioning accuracy is 3 to 4 meters. The black mark represents the drone coordinates and the tower positioning coordinates when the pod pitch angle is -45 degrees, and the positioning accuracy is 2 to 3 meters.

[0133] During the inspection process, a white circle is used to represent the actual position of the tower, and a blue circle represents the tower position given by the positioning algorithm. When the pod locking effect is good, the tower positioning is refreshed in real time, and the final tower positioning deviation along the line is within five meters. The final recorded tower positioning and flight trajectory have a lateral deviation of less than 1 meter.

[0134] Embodiment 2: A real-time positioning system for a pole tower used for power grid inspection, the pole tower inspection real-time positioning system includes an airborne terminal, and the airborne terminal includes:

[0135] A setting module, used for setting identification information on the airborne data collected during the flight, and obtaining the airborne data with the identification information set;

[0136] A preprocessing module, used for preprocessing the airborne data provided with identification information to obtain preprocessed airborne data;

[0137] The transmission module is used to upload the pre-processed airborne data to the cloud, and perform three-dimensional positioning according to the pre-processed airborne data to calculate the height data of the tower;

[0138] The positioning module is used to upload the real-time data collected during its flight to the cloud, and calculate the location coordinates of the tower in combination with the tower's height data.

[0139] The pole tower real-time positioning system in this embodiment is used to implement a pole tower real-time positioning method for power grid inspection in this embodiment 1, the method comprising: the airborne end sets identification information for the airborne data collected during its flight to obtain the airborne data set with the identification information; the airborne end performs data preprocessing on the airborne data set with the identification information to obtain the preprocessed airborne data; the airborne end uploads the preprocessed airborne data to the cloud, and performs three-dimensional positioning based on the preprocessed airborne data to calculate the height data of the pole tower; the airborne end uploads the real-time data collected during its flight to the cloud, and calculates the position coordinates of the pole tower in combination with the height data of the pole tower.

[0140] The airborne end performs error calibration on the airborne data with identification information to obtain error-calibrated airborne data after error calibration; the airborne end performs data synchronization on the error-calibrated airborne data after calibration to complete the operation of data preprocessing on the airborne data with identification information to obtain preprocessed airborne data.

[0141] The airborne end uses the identification information of the airborne data to perform time alignment processing; the airborne end uses the time of the carrier posture as the basis, calculates the information of the pod posture at the time of the identification information of the carrier posture, and obtains the data closest to the latest identification information of the carrier posture; the airborne end determines whether the time difference is within the preset time range based on the data closest to the latest identification information of the carrier posture, and obtains the identification information of the carrier posture.

[0142] The airborne end in this embodiment further adds a fault diagnosis module, through which the operating status of the airborne equipment, such as the accuracy of the sensor, the stability of the communication link, etc., can be monitored in real time. When an abnormal situation is detected, an alarm is issued in time and corresponding measures are taken, such as automatically switching to backup equipment or adjusting flight parameters, to ensure the smooth progress of the tower inspection task.

[0143] The cloud receives the airborne data preprocessed by the airborne end; the cloud calculates the intersection of the airborne data based on the airborne data preprocessed by the airborne end; the cloud converts the intersection of the airborne data into the three-dimensional coordinates of the tower, thereby obtaining the height data of the tower.

[0144] The cloud receives the real-time data collected by the airborne terminal during its flight; the cloud calculates the intersection information of the real-time data and the tower height based on the real-time data collected by the airborne terminal during its flight and the height data of the tower using the spatial relationship; the cloud performs coordinate conversion based on the intersection information of the real-time data and the tower height to calculate the position coordinates of the tower.

[0145] This embodiment also includes optimization of cloud data processing. When the cloud receives data uploaded by the airborne end, in addition to three-dimensional positioning and coordinate conversion, it can also analyze and mine historical data. By establishing a big data model for tower inspections and using machine learning algorithms to predict the health status and fault trends of towers, decision support is provided for the maintenance and management of the power grid.

[0146] The airborne end stores 20 pieces of aircraft posture and pod posture collected during its flight, finds out the piece of data closest to the latest identification information of the aircraft posture from the identification information of the pod posture, and obtains the identification information of the aircraft posture; when the airborne end judges that the time difference is less than 10ms according to the identification information of the aircraft posture, the airborne end does not need to perform interpolation alignment, otherwise the airborne end needs to perform interpolation alignment.

[0147] Embodiment 3: An airborne terminal includes a device body, and the airborne terminal further includes:

[0148] A memory storing executable program code;

[0149] a processor coupled to the memory;

[0150] The processor calls the executable program code stored in the memory to execute the steps executed by the airborne end in a real-time positioning method for a pole tower for power grid inspection in Example 1 of the present invention. The real-time positioning method for a pole tower includes: the airborne end sets identification information for the airborne data collected during its flight to obtain the airborne data with the identification information; the airborne end performs data preprocessing on the airborne data with the identification information to obtain the preprocessed airborne data; the airborne end uploads the preprocessed airborne data to the cloud, and performs three-dimensional positioning based on the preprocessed airborne data to calculate the height data of the pole tower; the airborne end uploads the real-time data collected during its flight to the cloud, and calculates the position coordinates of the pole tower in combination with the height data of the pole tower.

[0151] The airborne end performs error calibration on the airborne data with identification information to obtain error-calibrated airborne data after error calibration; the airborne end performs data synchronization on the error-calibrated airborne data after calibration to complete the operation of data preprocessing on the airborne data with identification information to obtain preprocessed airborne data.

[0152] The airborne end uses the identification information of the airborne data to perform time alignment processing; the airborne end uses the time of the carrier posture as the basis, calculates the information of the pod posture at the time of the identification information of the carrier posture, and obtains the data closest to the latest identification information of the carrier posture; the airborne end determines whether the time difference is within the preset time range based on the data closest to the latest identification information of the carrier posture, and obtains the identification information of the carrier posture.

[0153] The cloud receives the airborne data preprocessed by the airborne end; the cloud calculates the intersection of the airborne data based on the airborne data preprocessed by the airborne end; the cloud converts the intersection of the airborne data into the three-dimensional coordinates of the tower, thereby obtaining the height data of the tower.

[0154] The cloud receives the real-time data collected by the airborne terminal during its flight; the cloud calculates the intersection information of the real-time data and the tower height based on the real-time data collected by the airborne terminal during its flight and the height data of the tower using the spatial relationship; the cloud performs coordinate conversion based on the intersection information of the real-time data and the tower height to calculate the position coordinates of the tower.

[0155] The airborne end stores 20 pieces of aircraft posture and pod posture collected during its flight, finds out the piece of data closest to the latest identification information of the aircraft posture from the identification information of the pod posture, and obtains the identification information of the aircraft posture; when the airborne end judges that the time difference is less than 10ms according to the identification information of the aircraft posture, the airborne end does not need to perform interpolation alignment, otherwise the airborne end needs to perform interpolation alignment.

[0156] In order to better implement the real-time positioning method of the pole tower, the device body of the airborne end of this embodiment adopts a high-performance processor and a larger capacity memory, and optimizes the program code, improves the operation efficiency of the algorithm, and reduces the time delay of data processing to meet the requirements of real-time positioning and rapid response during short-distance inspections. In practical applications, this embodiment also combines with satellite remote sensing technology to enable the airborne end to cooperate with satellite remote sensing technology, calibrate the pole tower coordinates using satellite images, and compare the pole tower positioning data obtained by the drone with the pole tower position in the satellite image to correct the positioning deviation caused by factors such as drone flight deviation and sensor error, thereby improving the absolute accuracy of pole tower positioning.

[0157] Embodiment 4: A cloud comprising:

[0158] A memory storing executable program code;

[0159] a processor coupled to the memory;

[0160] The processor calls the executable program code stored in the memory to execute the steps executed by the cloud in a real-time positioning method for a pole tower for power grid inspection in Example 1 of the present invention. The real-time positioning method for a pole tower includes: the airborne end sets identification information for the airborne data collected during its flight to obtain the airborne data with the identification information; the airborne end performs data preprocessing on the airborne data with the identification information to obtain the preprocessed airborne data; the airborne end uploads the preprocessed airborne data to the cloud, and performs three-dimensional positioning based on the preprocessed airborne data to calculate the height data of the pole tower; the airborne end uploads the real-time data collected during its flight to the cloud, and calculates the position coordinates of the pole tower in combination with the height data of the pole tower.

[0161] The airborne end performs error calibration on the airborne data with identification information to obtain error-calibrated airborne data after error calibration; the airborne end performs data synchronization on the error-calibrated airborne data after calibration to complete the operation of data preprocessing on the airborne data with identification information to obtain preprocessed airborne data.

[0162] The airborne end uses the identification information of the airborne data to perform time alignment processing; the airborne end uses the time of the carrier posture as the basis, calculates the information of the pod posture at the time of the identification information of the carrier posture, and obtains the data closest to the latest identification information of the carrier posture; the airborne end determines whether the time difference is within the preset time range based on the data closest to the latest identification information of the carrier posture, and obtains the identification information of the carrier posture.

[0163] The cloud receives the airborne data preprocessed by the airborne end; the cloud calculates the intersection of the airborne data based on the airborne data preprocessed by the airborne end; the cloud converts the intersection of the airborne data into the three-dimensional coordinates of the tower, thereby obtaining the height data of the tower.

[0164] The cloud receives the real-time data collected by the airborne terminal during its flight; the cloud calculates the intersection information of the real-time data and the tower height based on the real-time data collected by the airborne terminal during its flight and the height data of the tower using the spatial relationship; the cloud performs coordinate conversion based on the intersection information of the real-time data and the tower height to calculate the position coordinates of the tower.

[0165] The airborne end stores 20 pieces of aircraft posture and pod posture collected during its flight, finds out the piece of data closest to the latest identification information of the aircraft posture from the identification information of the pod posture, and obtains the identification information of the aircraft posture; when the airborne end judges that the time difference is less than 10ms according to the identification information of the aircraft posture, the airborne end does not need to perform interpolation alignment, otherwise the airborne end needs to perform interpolation alignment.

[0166] In this embodiment, a visualization platform is also provided to display the positioning results, inspection tracks, fault information, etc. of the pole tower to the user in an intuitive manner. The user can view the inspection status of the pole tower in real time through the platform, and quickly respond to and handle abnormal situations. At the same time, through integration with other systems, the cloud can be integrated with other management systems of the power grid, such as production management systems, dispatching systems, etc., to share the pole tower positioning data and inspection results with relevant departments in real time, realize information interconnection, and improve the overall operation and maintenance efficiency and management level of the power grid.

[0167] Embodiment 5: A computer storage medium stores computer instructions. When the computer instructions are called, a real-time positioning method for pole towers for power grid inspection in Embodiment 1 of the present invention is executed. The real-time positioning method for pole towers includes: an airborne end sets identification information for airborne data collected during its flight to obtain airborne data with identification information; the airborne end performs data preprocessing on the airborne data with identification information to obtain preprocessed airborne data; the airborne end uploads the preprocessed airborne data to the cloud, and performs three-dimensional positioning based on the preprocessed airborne data to calculate the height data of the pole tower; the airborne end uploads the real-time data collected during its flight to the cloud, and calculates the position coordinates of the pole tower in combination with the height data of the pole tower.

[0168] The airborne end performs error calibration on the airborne data with identification information to obtain error-calibrated airborne data after error calibration; the airborne end performs data synchronization on the error-calibrated airborne data after calibration to complete the operation of data preprocessing on the airborne data with identification information to obtain preprocessed airborne data.

[0169] The airborne end uses the identification information of the airborne data to perform time alignment processing; the airborne end uses the time of the carrier posture as the basis, calculates the information of the pod posture at the time of the identification information of the carrier posture, and obtains the data closest to the latest identification information of the carrier posture; the airborne end determines whether the time difference is within the preset time range based on the data closest to the latest identification information of the carrier posture, and obtains the identification information of the carrier posture.

[0170] The cloud receives the airborne data preprocessed by the airborne end; the cloud calculates the intersection of the airborne data based on the airborne data preprocessed by the airborne end; the cloud converts the intersection of the airborne data into the three-dimensional coordinates of the tower, thereby obtaining the height data of the tower.

[0171] The cloud receives the real-time data collected by the airborne terminal during its flight; the cloud calculates the intersection information of the real-time data and the tower height based on the real-time data collected by the airborne terminal during its flight and the height data of the tower using the spatial relationship; the cloud performs coordinate conversion based on the intersection information of the real-time data and the tower height to calculate the position coordinates of the tower.

[0172] The airborne end stores 20 pieces of aircraft posture and pod posture collected during its flight, finds out the piece of data closest to the latest identification information of the aircraft posture from the identification information of the pod posture, and obtains the identification information of the aircraft posture; when the airborne end judges that the time difference is less than 10ms according to the identification information of the aircraft posture, the airborne end does not need to perform interpolation alignment, otherwise the airborne end needs to perform interpolation alignment.

[0173] The computer storage medium optimization in this embodiment adopts more advanced storage technology, including solid-state hard disks, etc., to improve the data reading and writing speed and storage reliability. At the same time, the data encryption function is added to ensure the security and confidentiality of the tower inspection data. In this link, Tongshi also integrates with artificial intelligence technology so that the computer instructions stored in the computer storage medium can integrate more artificial intelligence algorithms, such as deep learning algorithms, for tower image recognition, fault diagnosis, positioning accuracy improvement, etc., and improve the intelligence level of the tower inspection system through continuous learning and optimization.

[0174] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A real-time positioning method for a tower used for power grid inspection, characterized in that: The method comprises: The airborne end sets identification information on the collected airborne data to obtain the airborne data with the identification information set; The airborne end performs data preprocessing on the airborne data provided with the identification information to obtain the preprocessed airborne data; The airborne end uploads the pre-processed airborne data to the cloud, performs three-dimensional positioning according to the pre-processed airborne data, and calculates the height data of the tower; The airborne terminal uploads the collected real-time data to the cloud, and calculates the position coordinates of the tower in combination with the height data of the tower.

2. A real-time positioning method for a tower for power grid inspection according to claim 1, characterized in that: The airborne end performs data preprocessing on the airborne data provided with the identification information, including: The airborne end performs error calibration on the airborne data provided with the identification information to obtain the error-calibrated airborne data after error calibration; The airborne end synchronizes the calibrated airborne data to the cloud, completes the operation of preprocessing the airborne data provided with the identification information, and obtains the preprocessed airborne data.

3. A real-time positioning method for a tower for power grid inspection according to claim 2, characterized in that: The airborne end synchronizes the calibrated airborne data to the cloud, including: The airborne end performs time alignment processing using identification information of the airborne data; The airborne end calculates the information of the pod attitude at the time of the identification information of the carrier attitude based on the time of the carrier attitude, and obtains the data closest to the time of the latest carrier attitude identification information; The airborne end determines whether the time difference is within a preset time range based on the data closest to the latest carrier posture identification information, and obtains the identification information of the carrier posture.

4. A real-time tower positioning method for power grid inspection according to any one of claims 1 to 3, characterized in that: The method further comprises: The cloud receives the airborne data preprocessed by the airborne end; The cloud end calculates the intersection of the airborne data based on the airborne data preprocessed by the airborne end; The cloud end converts the intersection points of the airborne data into three-dimensional coordinates of the tower, thereby obtaining the height data of the tower.

5. A real-time tower positioning method for power grid inspection according to claim 4, characterized in that: The method further comprises: The cloud receives the real-time data collected by the airborne terminal; The cloud terminal combines the real-time data collected by the airborne terminal with the height data of the pole tower, and calculates the intersection information of the real-time data and the height of the pole tower by using the spatial relationship; The cloud performs coordinate conversion according to the intersection information of the real-time data and the tower height, and calculates the position coordinates of the tower.

6. A real-time tower positioning method for power grid inspection according to claim 3, characterized in that: The airborne end determines whether the time difference is within a preset time range based on the data closest to the latest carrier posture identification information, including: The airborne terminal stores 20 aircraft postures and pod postures collected during the flight, finds the data closest to the latest aircraft posture identification information from the pod posture identification information, and obtains the identification information of the aircraft posture; When the airborne end determines that the time difference is less than 10 ms according to the identification information of the carrier posture, the airborne end does not need to perform interpolation alignment; otherwise, the airborne end needs to perform interpolation alignment.

7. A real-time positioning system for power towers used for power grid inspection, characterized in that: The tower real-time positioning system comprises: A setting module, used to set identification information on the collected airborne data, and obtain the airborne data set with the identification information; A preprocessing module, used for performing data preprocessing on the airborne data provided with the identification information to obtain the preprocessed airborne data; A transmission module is used to upload the pre-processed airborne data to the cloud, and perform three-dimensional positioning according to the pre-processed airborne data to calculate the height data of the tower; The positioning module is used to upload the collected real-time data to the cloud, and calculate the position coordinates of the tower in combination with the height data of the tower.

8. A real-time tower positioning system for power grid inspection according to claim 7, characterized in that: The tower real-time positioning system also includes an airborne end, the airborne end includes a device body, and the airborne end also includes: A memory storing executable program code; a processor coupled to the memory; The processor calls the executable program code stored in the memory to execute the steps performed by the airborne end in the real-time positioning method of a tower for power grid inspection as described in any one of claims 1 to 6.

9. A real-time tower positioning system for power grid inspection according to claim 7, characterized in that: The system further includes a cloud, wherein the cloud includes: A memory storing executable program code; a processor coupled to the memory; The processor calls the executable program code stored in the memory to execute the steps performed by the cloud in the real-time positioning method of a tower for power grid inspection as described in any one of claims 1 to 6.

10. A real-time tower positioning system for power grid inspection according to claim 7, characterized in that: The system also includes a computer storage medium, which stores computer instructions. When the computer instructions are called, the method for real-time positioning of towers for power grid inspection according to any one of claims 1 to 6 is executed.

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