Distribution network equipment inspection method based on unmanned aerial vehicle

Abstract

The invention discloses a distribution network equipment inspection method based on an unmanned aerial vehicle and relates to the technical field of power grid inspection. The invention aims to solve the problem of high difficulty in routing inspection of distribution network lines in mountainous areas. The distribution network equipment inspection method based on the unmanned aerial vehicle comprises the following steps: acquiring coordinates and topographic information of a to-be-inspected area, and establishing an inspection area model; the flight height of the unmanned aerial vehicle is controlled to be within a preset inspection height range, the unmanned aerial vehicle performs inspection according to the inspection area model, and a thermodynamic image with topographic information of the to-be-inspected area is obtained; uniformly distributing mark points on the thermodynamic image, and collecting the temperature value of each mark point at each moment; and calculating the temperature and temperature rise variation of each mark point at each moment in real time, and when the temperature or temperature rise variation exceeds a standard threshold value, determining that a fault exists at the mark point.

Description

Technical Field

[0001] The invention belongs to the technical field of power grid inspection. Background Art

[0002] With the high-quality economic development of society, the pace of power development is getting faster and faster, and the demand for electricity is also getting higher and higher. However, the distribution network lines started later than the transmission network lines, and there are problems such as a messy grid framework and difficult line operation and maintenance, which requires more manpower and time to operate and maintain the distribution network. UAV intelligent inspection can improve the work efficiency of operation and maintenance personnel and improve the accuracy of defect identification, but because the lines in mountainous areas are more complex, operation and maintenance in mountainous areas is more difficult. Especially in the northern mountainous areas, the dry and windy autumn is very easy to cause fires. Once a disaster occurs, it will not only bring great natural disasters, but also cause large-scale power paralysis. Summary of the invention

[0003] The invention aims to solve the problem of difficulty in inspecting distribution network lines in mountainous areas, and proposes a distribution network equipment inspection method based on unmanned aerial vehicles.

[0004] A distribution network equipment inspection method based on a drone, comprising:

[0005] Obtain the coordinates and terrain information of the area to be inspected and establish an inspection area model;

[0006] The drone is controlled to fly within the preset inspection altitude range. The drone conducts inspections according to the inspection area model and obtains a thermal image with terrain information of the area to be inspected.

[0007] Evenly distribute the marking points on the thermal image, and collect the temperature value at each marking point at each time;

[0008] The temperature and temperature rise variation of each marked point at each moment are calculated in real time. When the temperature or temperature rise variation exceeds the standard threshold, it is determined that there is a fault at the marked point.

[0009] Furthermore, the above real-time calculation of the temperature change of each marked point at each moment includes:

[0010] Q it =T it / T is ,

[0011] Among them, Q it is the temperature change at point i at time t, T it is the temperature at point i at time t, T is It is the maximum temperature at point i during normal operation.

[0012] Furthermore, the above-mentioned real-time calculation of the temperature rise variation of each marked point at each moment includes:

[0013]

[0014] Among them, ΔQ it is the temperature rise change at point i at time t, w is the temperature rise change weight, ΔT is is the maximum temperature rise at point i during normal operation, T ht is the ambient temperature at point i at time t.

[0015] Furthermore, the above-mentioned drone is controlled to fly at a height within a preset inspection height range, and the drone performs inspections according to the inspection area model to obtain a thermal image with terrain information of the area to be inspected, including:

[0016] S1: Obtain the coordinates of the area to be inspected, establish a model of the area to be inspected according to the coordinates, and obtain the horizontal length and vertical length of the area to be inspected;

[0017] S2: according to the established model of the area to be inspected, the inspection height is set, and the inspection direction is horizontal. The area to be inspected is divided into multiple horizontal inspection areas according to the width of the picture obtained by the inspection device at the set inspection height and the longitudinal length of the area to be inspected. The horizontal inspection maps of the multiple horizontal inspection areas are respectively obtained by the inspection device, and the multiple horizontal inspection maps are spliced ​​to obtain the horizontal inspection map of the area to be inspected;

[0018] S3: According to the set inspection height, with the longitudinal direction as the inspection direction, and based on the horizontal length of the area to be inspected, the area to be inspected is divided into multiple longitudinal inspection areas according to the width of the picture obtained by the inspection device at the set inspection height, and longitudinal inspection partition maps are respectively obtained for the multiple longitudinal inspection areas through the inspection device;

[0019] S4: Divide the obtained transverse inspection map of the area to be inspected into a plurality of longitudinal partition maps of the transverse inspection map according to the longitudinal inspection direction, wherein the longitudinal partition maps of the plurality of transverse inspection maps are respectively divided into the longitudinal inspection partition maps. Figure 1 One to one correspondence;

[0020] S5: Connect the longitudinal partition diagram of the transverse inspection diagram to the corresponding longitudinal inspection partition diagram Figure 1 1. Perform image comparison, wherein the image comparison includes obtaining image similarity. If the image similarity between the longitudinal partition diagram of the transverse inspection diagram and the corresponding longitudinal inspection partition diagram is not less than the set image similarity, the image data acquisition is qualified; otherwise, execute S6;

[0021] S6: Extract the longitudinal partition map of the transverse inspection map whose image similarity is less than the set image similarity, perform overlap rate detection on each transverse partition in the longitudinal partition map of the transverse inspection map and the corresponding area in the corresponding longitudinal inspection map, screen out the transverse partitions whose overlap rate is lower than the set image similarity, re-collect the image data of the area, and perform similarity detection on the re-collected image data. If qualified, replace the image data of the area in the transverse inspection map to obtain a thermal image with terrain information of the area to be inspected.

[0022] A computer-readable storage medium stores a computer program, and when the computer program is executed, the above-mentioned distribution network equipment inspection method based on a drone is implemented.

[0023] An electronic device includes a storage medium, a processor, and a computer program stored in the storage medium and executable on the processor, wherein the processor executes the computer program to implement a distribution network equipment inspection method based on a drone as described above.

[0024] The beneficial effects of the present invention are:

[0025] The distribution network equipment inspection method based on unmanned aerial vehicle described in the present invention can realize the power distribution network inspection in the inspection area, especially in the area where manual inspection is inconvenient, and can conveniently realize the automatic inspection of the power distribution network. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 The figure is a flow chart of a distribution network equipment inspection method based on drones. DETAILED DESCRIPTION

[0027] The following will be combined with the accompanying drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work belong to the scope of protection of the present invention. It should be noted that the embodiments of the present invention and the features in the embodiments can be combined with each other without conflict.

[0028] Specific implementation method 1: refer to Figure 1 Specifically describing this embodiment, a distribution network equipment inspection method based on a drone described in this embodiment includes:

[0029] Obtain the coordinates and terrain information of the area to be inspected and establish an inspection area model;

[0030] The drone is controlled to fly within the preset inspection altitude range. The drone conducts inspections according to the inspection area model and obtains a thermal image with terrain information of the area to be inspected.

[0031] Evenly distribute the marking points on the thermal image, and collect the temperature value at each marking point at each time;

[0032] The temperature and temperature rise variation of each marked point at each moment are calculated in real time. When the temperature or temperature rise variation exceeds the standard threshold, it is determined that there is a fault at the marked point.

[0033] Preferably, the real-time calculation of the temperature change of each marked point at each moment includes:

[0034] Q it =T it / T is ,

[0035] Among them, Q it is the temperature change at point i at time t, T it is the temperature at point i at time t, T is It is the maximum temperature at point i during normal operation.

[0036] Preferably, the real-time calculation of the temperature rise variation of each marking point at each moment includes:

[0037]

[0038] Among them, ΔQ it is the temperature rise change at point i at time t, w is the temperature rise change weight, ΔT is is the maximum temperature rise at point i during normal operation, T ht is the ambient temperature at point i at time t.

[0039] Preferably, the UAV is controlled to fly at a preset inspection altitude, and the UAV performs inspections according to the inspection area model to obtain a thermal image with terrain information of the area to be inspected, including:

[0040] S1: Obtain the coordinates of the area to be inspected, establish a model of the area to be inspected according to the coordinates, and obtain the horizontal length and vertical length of the area to be inspected;

[0041] S2: according to the established model of the area to be inspected, the inspection height is set, and the inspection direction is horizontal. The area to be inspected is divided into multiple horizontal inspection areas according to the width of the picture obtained by the inspection device at the set inspection height and the longitudinal length of the area to be inspected. The horizontal inspection maps of the multiple horizontal inspection areas are respectively obtained by the inspection device, and the multiple horizontal inspection maps are spliced ​​to obtain the horizontal inspection map of the area to be inspected;

[0042] S3: According to the set inspection height, with the longitudinal direction as the inspection direction, and based on the horizontal length of the area to be inspected, the area to be inspected is divided into multiple longitudinal inspection areas according to the width of the picture obtained by the inspection device at the set inspection height, and longitudinal inspection partition maps are respectively obtained for the multiple longitudinal inspection areas through the inspection device;

[0043] S4: Divide the obtained transverse inspection map of the area to be inspected into a plurality of longitudinal partition maps of the transverse inspection map according to the longitudinal inspection direction, wherein the longitudinal partition maps of the plurality of transverse inspection maps are respectively divided into the longitudinal inspection partition maps. Figure 1 One to one correspondence;

[0044] S5: Connect the longitudinal partition diagram of the transverse inspection diagram to the corresponding longitudinal inspection partition diagram Figure 1 1. Perform image comparison, wherein the image comparison includes obtaining image similarity. If the image similarity between the longitudinal partition diagram of the transverse inspection diagram and the corresponding longitudinal inspection partition diagram is not less than the set image similarity, the image data acquisition is qualified; otherwise, execute S6;

[0045] S6: Extract the longitudinal partition map of the transverse inspection map whose image similarity is less than the set image similarity, perform overlap rate detection on each transverse partition in the longitudinal partition map of the transverse inspection map and the corresponding area in the corresponding longitudinal inspection map, screen out the transverse partitions whose overlap rate is lower than the set image similarity, re-collect the image data of the area, and perform similarity detection on the re-collected image data. If qualified, replace the image data of the area in the transverse inspection map to obtain a thermal image with terrain information of the area to be inspected.

[0046] Specific implementation method 2: A computer-readable storage medium, wherein the storage medium stores a computer program, and when the computer program is executed, the method described in specific implementation method 1 is implemented.

[0047] Specific implementation method three: An electronic device includes a storage medium, a processor, and a computer program stored in the storage medium and executable on the processor, wherein the processor executes the computer program to implement the method described in specific implementation method one.

[0048] Although the present invention is described herein with reference to specific embodiments, it should be understood that these embodiments are merely examples of the principles and applications of the present invention. It should therefore be understood that many modifications may be made to the exemplary embodiments and that other arrangements may be devised without departing from the spirit and scope of the present invention as defined by the appended claims. It should be understood that the various dependent claims and features described herein may be combined in a manner different from that described in the original claims. It should also be understood that the features described in conjunction with a single embodiment may be used in other described embodiments.

Claims

1. A distribution network equipment inspection method based on drones, characterized in that: include: Obtain the coordinates and terrain information of the area to be inspected and establish an inspection area model; The drone is controlled to fly within the preset inspection altitude range. The drone conducts inspections according to the inspection area model and obtains a thermal image with terrain information of the area to be inspected. Evenly distribute the marking points on the thermal image, and collect the temperature value at each marking point at each time; The temperature and temperature rise variation of each marked point at each moment are calculated in real time. When the temperature or temperature rise variation exceeds the standard threshold, it is determined that there is a fault at the marked point.

2. A distribution network equipment inspection method based on drone according to claim 1, characterized in that: The real-time calculation of the temperature change of each marked point at each moment includes: Q it =T it / T is , Among them, Q it is the temperature change at point i at time t, T it is the temperature at point i at time t, T is It is the maximum temperature at point i during normal operation.

3. A distribution network equipment inspection method based on drone according to claim 2, characterized in that: The real-time calculation of the temperature rise variation of each marked point at each moment includes: Among them, ΔQ it is the temperature rise change at point i at time t, w is the temperature rise change weight, ΔT is is the maximum temperature rise at point i during normal operation, T ht is the ambient temperature at point i at time t.

4. A distribution network equipment inspection method based on a drone according to claim 1, 2 or 3, characterized in that: The control of the drone's flight altitude within a preset inspection altitude range, the drone performs inspections according to the inspection area model, and obtains a thermal image with terrain information of the area to be inspected, including: S1: Obtain the coordinates of the area to be inspected, establish a model of the area to be inspected according to the coordinates, and obtain the horizontal length and vertical length of the area to be inspected; S2: according to the established model of the area to be inspected, the inspection height is set, and the inspection direction is horizontal. The area to be inspected is divided into multiple horizontal inspection areas according to the width of the picture obtained by the inspection device at the set inspection height and the longitudinal length of the area to be inspected. The horizontal inspection maps of the multiple horizontal inspection areas are respectively obtained by the inspection device, and the multiple horizontal inspection maps are spliced ​​to obtain the horizontal inspection map of the area to be inspected; S3: According to the set inspection height, with the longitudinal direction as the inspection direction, and based on the horizontal length of the area to be inspected, the area to be inspected is divided into multiple longitudinal inspection areas according to the width of the picture obtained by the inspection device at the set inspection height, and longitudinal inspection partition maps are respectively obtained for the multiple longitudinal inspection areas through the inspection device; S4: dividing the obtained transverse inspection map of the area to be inspected into a plurality of longitudinal partition maps of the transverse inspection map according to the longitudinal inspection direction, wherein the longitudinal partition maps of the plurality of transverse inspection maps correspond one to one to the longitudinal inspection partition maps respectively obtained; S5: performing image comparison on the longitudinal partition map of the transverse inspection map and the corresponding longitudinal inspection partition map one by one, wherein the image comparison includes obtaining image similarity. If the image similarity between the longitudinal partition map of the transverse inspection map and the corresponding longitudinal inspection partition map is not less than the set image similarity, the image data acquisition is qualified; otherwise, executing S6; S6: Extract the longitudinal partition map of the transverse inspection map whose image similarity is less than the set image similarity, perform overlap rate detection on each transverse partition in the longitudinal partition map of the transverse inspection map and the corresponding area in the corresponding longitudinal inspection map, screen out the transverse partitions whose overlap rate is lower than the set image similarity, re-collect the image data of the area, and perform similarity detection on the re-collected image data. If qualified, replace the image data of the area in the transverse inspection map to obtain a thermal image with terrain information of the area to be inspected.

5. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed, the method according to any one of claims 1 to 4 is implemented.

6. An electronic device comprising a storage medium, a processor, and a computer program stored in the storage medium and executable on the processor, characterized in that: The processor executes the computer program to implement the method according to any one of claims 1 to 4.

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