CN115774166A - Line fault diagnosis positioning system and method based on distributed fault and unmanned aerial vehicle - Google Patents
Line fault diagnosis positioning system and method based on distributed fault and unmanned aerial vehicle Download PDFInfo
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- CN115774166A CN115774166A CN202211447989.1A CN202211447989A CN115774166A CN 115774166 A CN115774166 A CN 115774166A CN 202211447989 A CN202211447989 A CN 202211447989A CN 115774166 A CN115774166 A CN 115774166A
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Abstract
The invention provides a line fault diagnosis and positioning system and method based on distributed faults and an unmanned aerial vehicle, wherein the system comprises the following steps: the distributed fault diagnosis device is used for collecting the current to be measured of the line in real time, and the current to be measured of the line is arranged in a target area; carrying out abnormity detection on waveform data of the current to be detected of the line to obtain abnormal waveform data; marking the abnormal waveform data, compressing the marked abnormal waveform data to obtain a compressed data packet, and uploading the compressed data packet to a background processing subsystem; the background processing subsystem is used for identifying fault types and calculating fault point location information according to the compressed data packets, and linking the unmanned aerial vehicle to fly to the fault point location according to the fault point location information, so that the unmanned aerial vehicle shoots real-time images and video data, and the shot real-time images and video data are transmitted back to the background processing subsystem. The invention solves the problems that the fault point position can not be accurately positioned and the field fault condition can not be visually presented.
Description
Technical Field
The invention relates to the technical field of communication line diagnosis, in particular to a line fault diagnosis positioning system and method based on distributed faults and an unmanned aerial vehicle.
Background
The conditions of line tripping and power failure caused by external force damage, tree growth, mountain fire and ground short circuit faults of an overhead transmission line channel corridor are more and more. How to reduce the loss caused by the transmission line fault, ensure the stable and safe operation of the transmission line, need to give alarm information in time, and accurately position the fault point position so as to eliminate the fault and hidden trouble in time. At present, only one fault monitoring device is singly adopted for fault location of a power transmission line, and the fault monitoring device is installed in a mode of 20-30 kilometers, so that the field fault condition cannot be presented timely and intuitively, and an effective fault elimination scheme can be formulated.
Disclosure of Invention
In order to overcome the defects of the prior art, the invention aims to provide a line fault diagnosis and positioning system and method based on distributed faults and an unmanned aerial vehicle, and the system and method provided by the invention solve the problems that fault point positions cannot be accurately positioned and field fault conditions cannot be visually presented.
In order to achieve the purpose, the invention provides the following scheme:
a line fault diagnosis positioning system based on distributed fault and unmanned aerial vehicle comprises:
the system comprises a background processing subsystem, a distributed fault diagnosis device, an unmanned aerial vehicle nest, a CORS reference station and a Beidou satellite, wherein the unmanned aerial vehicle nest, the CORS reference station and the Beidou satellite are wirelessly connected with one another; the unmanned aerial vehicle is respectively connected with the unmanned aerial vehicle nest and the Beidou satellite; the background processing subsystem is respectively connected with the distributed fault diagnosis device and the unmanned aerial vehicle nest; the distributed fault diagnosis device is arranged on a monitoring point position of the power transmission line; the distance between each monitoring point and each monitoring point is 20-30 kilometers; the unmanned aerial vehicle nest is arranged on the power transmission iron tower; the unmanned aerial vehicle is arranged in the unmanned aerial vehicle nest;
the distributed fault diagnosis device is used for collecting the current to be measured of the line in real time, and the current to be measured of the line is arranged in a target area; carrying out abnormity detection on the waveform data of the current to be detected of the line to obtain abnormal waveform data; marking the abnormal waveform data, compressing the marked abnormal waveform data to obtain a compressed data packet, and uploading the compressed data packet to the background processing subsystem; the unmanned aerial vehicle nest is used for placing the unmanned aerial vehicle and charging the unmanned aerial vehicle; the unmanned aerial vehicle is used for shooting a target area and uploading shooting data to the unmanned aerial vehicle nest; the target area is arranged on the power transmission iron tower; the CORS reference station is used for receiving Beidou satellite positioning data in real time, outputting RTK differential correction quantity and correcting the position information of the unmanned aerial vehicle; the background processing subsystem is used for identifying fault types and calculating fault point location information according to the compressed data packets and linking the unmanned aerial vehicle to fly to a fault point according to the fault point location information so that the unmanned aerial vehicle shoots real-time images and video data and transmits the shot real-time images and video data back to the background processing subsystem.
Preferably, the distributed fault diagnosis apparatus includes:
the system comprises an MCU processing unit, a communication unit, a power taking unit, a high-precision sampling unit, a fault studying and judging unit and a Beidou time service unit; the MCU processing unit is respectively connected with the communication unit, the power taking unit, the high-precision sampling unit, the fault studying and judging unit and the Beidou time service unit; the communication unit is wirelessly connected with the background processing subsystem;
the power taking unit is used for acquiring current to be measured on the power transmission line; the high-precision sampling unit is used for acquiring waveform data of the current to be measured; the fault studying and judging unit is used for judging whether the waveform of the current to be detected is abnormal or not; the Beidou time service unit is used for marking a high-precision timestamp on the abnormal waveform; the MCU processing unit is used for compressing and packaging the abnormal waveform to obtain a compressed data packet; the communication unit is used for uploading the compressed data packet to the background processing subsystem.
Preferably, the communication unit is any one of a 2G/4G communication unit and a first Beidou No. 3 short message communication unit.
Preferably, the first beidou No. 3 short message communication unit is configured to perform data transmission on the compressed data packet when the 2G/4G communication unit cannot transmit data.
Preferably, the unmanned aerial vehicle is provided with:
the AI edge calculation unit and the second communication unit are connected through a wired network; the second communication unit is connected with the unmanned aerial vehicle nest;
the AI edge calculation unit is used for analyzing whether hidden dangers occur or not according to the images and video data shot by the unmanned aerial vehicle to obtain alarm information; the second communication unit is used for uploading the alarm information to the unmanned aerial vehicle nest.
Preferably, the drone nest has built in:
a third communication unit; the third communication unit is connected with the background processing subsystem;
and the third communication unit is used for uploading the alarm information to the background processing subsystem.
Preferably, the third communication unit is one of a 4G/5G and second beidou No. 3 short message communication unit.
A line fault diagnosis positioning method based on distributed faults and unmanned aerial vehicles comprises the following steps:
acquiring current waveform data to be detected of a line in real time by using a distributed fault diagnosis device, carrying out abnormity detection on the waveform data of the current to be detected of the line to obtain an abnormal data waveform, marking the abnormal waveform data, compressing the marked abnormal waveform data to obtain a compressed data packet, and uploading the compressed data packet to the background processing subsystem;
placing the unmanned aerial vehicle by using the unmanned aerial vehicle nest and charging the unmanned aerial vehicle;
shooting a target area by using an unmanned aerial vehicle, and uploading shooting data to an unmanned aerial vehicle nest;
receiving Beidou satellite positioning data in real time by using a CORS reference station, outputting RTK differential correction, and correcting the position information of the unmanned aerial vehicle;
and identifying a fault type and calculating fault point location information according to the compressed data packet by using a background processing subsystem, linking the unmanned aerial vehicle to fly to a fault point according to the fault point location information so that the unmanned aerial vehicle shoots real-time images and video data, and transmitting the shot real-time images and video data back to the background processing subsystem.
According to the specific embodiment provided by the invention, the invention discloses the following technical effects:
the invention provides a line fault diagnosis positioning system and method based on distributed faults and an unmanned aerial vehicle.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained according to these drawings without creative efforts.
Fig. 1 is a structural diagram of a line fault diagnosis positioning system based on distributed faults and an unmanned aerial vehicle according to an embodiment of the present invention;
fig. 2 is a flowchart of a line fault diagnosis positioning method based on distributed faults and an unmanned aerial vehicle according to an embodiment of the present invention;
FIG. 3 is a flow chart of a fire suppression scheme provided by an embodiment of the present invention;
fig. 4 is a schematic diagram of a fault diagnosis principle provided by an embodiment of the present invention.
Description of reference numerals:
1-distributed fault diagnosis device, 2-unmanned aerial vehicle, 3-Beidou satellite, 4-unmanned aerial vehicle nest and 5-CORS reference station.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Reference herein to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of the application. The appearances of the phrase in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. It is explicitly and implicitly understood by one skilled in the art that the embodiments described herein can be combined with other embodiments.
The terms "first," "second," "third," and "fourth," etc. in the description and claims of this application and in the accompanying drawings are used for distinguishing between different elements and not for describing a particular sequential order. Furthermore, the terms "include" and "have," as well as any variations thereof, are intended to cover a non-exclusive inclusion. For example, the inclusion of a list of steps, processes, methods, etc. is not limited to only those steps recited, but may alternatively include additional steps not recited, or may alternatively include additional steps inherent to such processes, methods, articles, or devices.
The invention aims to provide a line fault diagnosis and positioning system and method based on distributed faults and an unmanned aerial vehicle, and solves the problems that fault point positions cannot be accurately positioned and field fault conditions cannot be visually presented.
In order to make the aforementioned objects, features and advantages of the present invention comprehensible, embodiments accompanied with figures are described in further detail below.
As shown in fig. 1, the present invention provides a line fault diagnosis and positioning system based on distributed fault and unmanned aerial vehicle 2, including:
the system comprises a background processing subsystem, a distributed fault diagnosis device 1, an unmanned aerial vehicle 2, an unmanned aerial vehicle nest 4, a CORS reference station 5 and a Beidou satellite 3 which are wirelessly connected with one another; the unmanned aerial vehicle 2 is respectively connected with the unmanned aerial vehicle nest 4 and the Beidou satellite 3; the background processing subsystem is respectively connected with the distributed fault diagnosis device 1 and the unmanned aerial vehicle airframe 4; the distributed fault diagnosis device 1 is arranged on a monitoring point position of the power transmission line; each phase of an ABC phase conductor is provided with 1 set of device, the distance between each monitoring point and each monitoring point is 20-30 kilometers, the full coverage of a line is realized, and the distributed fault diagnosis device 1 is powered by induction electricity; the unmanned aerial vehicle nest 4 is arranged on the power transmission iron tower; the unmanned aerial vehicle 2 is arranged in the unmanned aerial vehicle nest 4, and the nest takes electricity through a solar panel;
the distributed fault diagnosis device 1 is used for collecting the current to be measured of the line in real time, and the current to be measured of the line is arranged in a target area; carrying out abnormity detection on the waveform data of the current to be detected of the line to obtain abnormal waveform data; labeling the abnormal waveform data, compressing the labeled abnormal waveform data to obtain a compressed data packet, and uploading the compressed data packet to the background processing subsystem; the unmanned aerial vehicle 2 nest is used for placing the unmanned aerial vehicle 2 and charging the unmanned aerial vehicle 2; the unmanned aerial vehicle 2 is used for shooting a target area and uploading shooting data to the unmanned aerial vehicle nest 4; the target area is arranged on the power transmission iron tower; the CORS reference station 5 is used for receiving Beidou satellite 3 positioning data in real time, outputting RTK differential correction, and correcting the position information of the unmanned aerial vehicle 2; the background processing subsystem is used for identifying fault types and calculating fault point location information according to the compressed data packet and linking the unmanned aerial vehicle 2 to fly to a fault point according to the fault point location information, so that the unmanned aerial vehicle 2 shoots real-time images and video data, analyzes whether fire, external force damage and tree growth hidden danger occur or not, and transmits the shot real-time images and video data back to the background processing subsystem. And identifying the type of the fault through fault waveform characteristic analysis.
According to the threshold triggering principle, the high-frequency transient traveling wave current data and the power frequency current data of the line are collected in real time, when the waveform data are larger than the threshold, the abnormal data are considered, when abnormal waveforms occur, a wave recording unit is started, one section of fault high-frequency transient waveform and one section of fault power frequency waveform are recorded, a high-precision timestamp is marked, and the high-precision timestamp is used for calculating high-precision fault position information.
Based on the high-precision RTK differential positioning technology, a Beidou CORS reference station 5 is deployed around the power transmission pole, beidou satellite 3 positioning data is received in real time, and RTK differential correction is output. The built-in processing unit of unmanned aerial vehicle nest 4 receives and acquires 5RTK differential correction data of big dipper CORS reference station through the data radio station, corrects the positioning data that self acquireed to provide RTK differential correction data for unmanned aerial vehicle 2 through radio frequency communication, correct 2 positional information of unmanned aerial vehicle, realize the high accuracy positioning machine navigation that unmanned aerial vehicle nest 4 and unmanned aerial vehicle 2 patrolled and examined.
Further, the distributed fault diagnosis apparatus 1 includes:
the system comprises an MCU processing unit, a communication unit, a power taking unit, a high-precision sampling unit, a fault studying and judging unit and a Beidou time service unit; the MCU processing unit is respectively connected with the communication unit, the power taking unit, the high-precision sampling unit, the fault studying and judging unit and the Beidou time service unit; the communication unit is wirelessly connected with the background processing subsystem;
the power taking unit is used for acquiring current to be detected on the power transmission line; the high-precision sampling unit is used for acquiring waveform data of the current to be measured; the fault studying and judging unit is used for judging whether the waveform of the current to be detected is abnormal or not; the Beidou time service unit is used for marking a high-precision timestamp on the abnormal waveform; the MCU processing unit is used for compressing and packaging the abnormal waveform to obtain a compressed data packet; the communication unit is used for uploading the compressed data packet to the background processing subsystem.
Further, the communication unit is any one of a 2G/4G communication unit and a first Beidou No. 3 short message communication unit. The distributed fault diagnosis device 1 has the functions of 2G/4G communication, beidou No. 3 short message communication unit link self-diagnosis, automatic switching and recovery and communication channel backup.
The unmanned aerial vehicle nest 4 has the functions of 2G/4G communication and Beidou No. 3 short message communication unit link self-diagnosis, automatic switching and recovery and communication channel backup.
The embodiment discloses the principle of calculating fault point location information and identifying waveform types as follows:
the background processing subsystem combines the waveform data of the distributed fault diagnosis device 1 with the same phase line based on different monitoring points of the same line with the line information recorded into the background subsystem and the station account information of the monitoring points of the distributed fault diagnosis device 1, accurately calculates the fault point information based on a double-end positioning principle, and identifies the fault category according to the fault waveform characteristics. The fault diagnosis principle is based on a double-end positioning traveling wave distance measurement principle, waveform data of a plurality of fault diagnosis devices are combined, fault point location information is obtained through calculation according to the propagation speed of electromagnetic waves on a wire and a labeled high-precision timestamp, and the specific formula is as follows:
wherein, as shown in FIG. 4, L is the distance, L M Distance from fault point to point M, L N Is the distance from the fault point to the N point, v is the waveform propagation velocity, t M For the time of propagation of the fault waveform from the point of fault to the point M, t N The time for the fault waveform to propagate from the point of the fault to the point N.
Further, the first beidou No. 3 short message communication unit is configured to perform data transmission on the compressed data packet when the 2G/4G communication unit cannot transmit data. If no mobile operator signal or weak signal exists on the site and transmission failure is caused, the Beidou No. 3 short message communication unit is started, data are sent to the background Beidou No. 3 short message receiver through the Beidou No. 3 satellite, and the data are transmitted to the background processing subsystem after being decompressed by the Beidou receiver.
Further, unmanned aerial vehicle 2 embeds there is:
an AI edge calculation unit and a second communication unit connected by a wired network; the second communication unit is connected with the unmanned aerial vehicle nest 4;
the AI edge calculation unit is used for analyzing whether hidden dangers occur or not according to the images and video data shot by the unmanned aerial vehicle 2 to obtain alarm information; and the second communication unit is used for uploading the alarm information to the unmanned aerial vehicle airframe 4.
Further, unmanned aerial vehicle machine nest 4 embeds there is:
a third communication unit; the third communication unit is connected with the background processing subsystem;
and the third communication unit is used for uploading the alarm information to the background processing subsystem.
Furthermore, the third communication unit is one of a 4G/5G and second Beidou No. 3 short message communication unit, and only transmits the high compression ratio alarm image and does not transmit the video due to bandwidth limitation when the Beidou No. 3 short message communication is carried out. And the background processing subsystem maintainers make decisions of fault elimination and fire extinguishing on site by combining the alarm information, the fault point positions and the fault category information.
As shown in fig. 2, this embodiment further provides a line fault diagnosis and positioning method based on the distributed fault and the unmanned aerial vehicle 2, including:
step 100: collecting current waveform data to be detected of a line in real time by using a distributed fault diagnosis device 1;
step 200: carrying out abnormity detection on waveform data of the current to be measured of the line to obtain abnormal data waveforms, labeling the abnormal waveform data, compressing the labeled abnormal waveform data to obtain compressed data packets, and uploading the compressed data packets to the background processing subsystem;
step 300: placing the unmanned aerial vehicle 2 in the unmanned aerial vehicle 2 nest and charging the unmanned aerial vehicle 2;
step 400: shooting a target area by using the unmanned aerial vehicle 2, and uploading shooting data to an unmanned aerial vehicle nest 4;
step 500: receiving Beidou satellite 3 positioning data in real time by using a CORS reference station 5, outputting RTK differential correction, and correcting the position information of the unmanned aerial vehicle 2;
step 600: and identifying the fault type and calculating fault point location information according to the compressed data packet by using a background processing subsystem, linking the unmanned aerial vehicle 2 to fly to the fault point location according to the fault point location information, so that the unmanned aerial vehicle 2 shoots real-time images and video data, and transmitting the shot real-time images and video data back to the background processing subsystem.
As shown in fig. 3, the present embodiment also provides a specific fire prevention scheme flow:
the distributed fault diagnosis device 1 samples in real time; triggering a threshold value by waveform data, starting recording and uploading to a background analysis system; the background analysis system is combined with the multi-point fault diagnosis device to carry out fault location and fault type identification; the unmanned aerial vehicle 2 is linked to perform routing inspection operation, field routing inspection and image video AI analysis; transmitting the on-site alarm pictures and data back to background system operation and maintenance personnel through a cell communication unit to formulate a fault elimination and hidden danger troubleshooting scheme strategy; eliminating faults and hidden troubles.
The invention has the following beneficial effects:
according to the invention, the fault type is judged by detecting the abnormal waveform data of the current to be detected of the line, the fault point location information is calculated according to the abnormal waveform data, and the unmanned aerial vehicle is linked to shoot the image and video data of the fault point in real time, so that the accuracy and real-time performance of line fault detection are improved, and a fire prevention and extinguishing scheme is conveniently formulated by a manager of a background system.
The embodiments in the present description are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments are referred to each other. The method disclosed by the embodiment corresponds to the system disclosed by the embodiment, so that the description is simple, and the relevant points can be referred to the description of the method part.
The principle and the embodiment of the present invention are explained by applying specific examples, and the above description of the embodiments is only used to help understanding the method and the core idea of the present invention; meanwhile, for a person skilled in the art, according to the idea of the present invention, the specific embodiments and the application range may be changed. In view of the above, the present disclosure should not be construed as limiting the invention.
Claims (8)
1. The utility model provides a line fault diagnosis positioning system based on distributed fault and unmanned aerial vehicle which characterized in that includes:
the system comprises a background processing subsystem, a distributed fault diagnosis device, an unmanned aerial vehicle nest, a CORS reference station and a Beidou satellite, wherein the unmanned aerial vehicle nest, the CORS reference station and the Beidou satellite are wirelessly connected with one another; the unmanned aerial vehicle is respectively connected with the unmanned aerial vehicle nest and the Beidou satellite; the background processing subsystem is respectively connected with the distributed fault diagnosis device and the unmanned aerial vehicle nest; the distributed fault diagnosis device is arranged on a monitoring point position of the power transmission line; the distance between each monitoring point and each monitoring point is 20-30 kilometers; the unmanned aerial vehicle nest is arranged on the power transmission iron tower; the unmanned aerial vehicle is arranged in the unmanned aerial vehicle nest;
the distributed fault diagnosis device is used for collecting the current to be measured of the line in real time, and the current to be measured of the line is arranged in a target area; carrying out abnormity detection on the waveform data of the current to be detected of the line to obtain abnormal waveform data; marking the abnormal waveform data, compressing the marked abnormal waveform data to obtain a compressed data packet, and uploading the compressed data packet to the background processing subsystem; the unmanned aerial vehicle nest is used for placing the unmanned aerial vehicle and charging the unmanned aerial vehicle; the unmanned aerial vehicle is used for shooting a target area and uploading shooting data to the unmanned aerial vehicle nest; the target area is arranged on the power transmission iron tower; the CORS reference station is used for receiving Beidou satellite positioning data in real time, outputting RTK differential correction quantity and correcting the position information of the unmanned aerial vehicle; the background processing subsystem is used for identifying fault types and calculating fault point location information according to the compressed data packets and linking the unmanned aerial vehicle to fly to a fault point according to the fault point location information so that the unmanned aerial vehicle shoots real-time images and video data and transmits the shot real-time images and video data back to the background processing subsystem.
2. The line fault diagnosis positioning system based on distributed fault and unmanned aerial vehicle of claim 1, characterized in that, the distributed fault diagnosis device comprises:
the system comprises an MCU processing unit, a communication unit, a power taking unit, a high-precision sampling unit, a fault studying and judging unit and a Beidou time service unit; the MCU processing unit is respectively connected with the communication unit, the power taking unit, the high-precision sampling unit, the fault studying and judging unit and the Beidou time service unit; the communication unit is wirelessly connected with the background processing subsystem;
the power taking unit is used for acquiring current to be detected on the power transmission line; the high-precision sampling unit is used for acquiring waveform data of the current to be measured; the fault studying and judging unit is used for judging whether the waveform of the current to be detected is abnormal or not; the Beidou time service unit is used for marking a high-precision timestamp on the abnormal waveform; the MCU processing unit is used for compressing and packaging the abnormal waveform to obtain a compressed data packet; the communication unit is used for uploading the compressed data packet to the background processing subsystem.
3. The line fault diagnosis positioning system based on the distributed fault and unmanned aerial vehicle of claim 2, wherein the communication unit is any one of a 2G/4G communication unit and a first Beidou No. 3 short message communication unit.
4. The line fault diagnosis and positioning system based on the distributed faults and the unmanned aerial vehicle as claimed in claim 3, wherein the first beidou No. 3 short message communication unit is configured to perform data transmission on the compressed data packet when the 2G/4G communication unit cannot transmit data.
5. The line fault diagnosis positioning system based on distributed fault and unmanned aerial vehicle of claim 1, wherein the unmanned aerial vehicle is provided with:
an AI edge calculation unit and a second communication unit connected by a wired network; the second communication unit is connected with the unmanned aerial vehicle nest;
the AI edge calculation unit is used for analyzing whether hidden dangers occur or not according to the images and video data shot by the unmanned aerial vehicle to obtain alarm information; the second communication unit is used for uploading the alarm information to the unmanned aerial vehicle nest.
6. The distributed fault and drone based line fault diagnosis and location system of claim 5, wherein the drone nest has built in:
a third communication unit; the third communication unit is connected with the background processing subsystem;
and the third communication unit is used for uploading the alarm information to the background processing subsystem.
7. The line fault diagnosis positioning system based on the distributed fault and unmanned aerial vehicle of claim 6, wherein the third communication unit is one of a 4G/5G and a second Beidou No. 3 short message communication unit.
8. A line fault diagnosis and positioning method based on distributed faults and unmanned aerial vehicles is characterized by comprising the following steps:
acquiring current waveform data to be detected of a line in real time by using a distributed fault diagnosis device, carrying out abnormity detection on the waveform data of the current to be detected of the line to obtain an abnormal data waveform, marking the abnormal waveform data, compressing the marked abnormal waveform data to obtain a compressed data packet, and uploading the compressed data packet to the background processing subsystem;
placing the unmanned aerial vehicle by using the unmanned aerial vehicle nest and charging the unmanned aerial vehicle;
shooting a target area by using an unmanned aerial vehicle, and uploading shooting data to an unmanned aerial vehicle nest;
receiving Beidou satellite positioning data in real time by using a CORS reference station, outputting RTK differential correction, and correcting the position information of the unmanned aerial vehicle;
and identifying the fault type and calculating fault point location information according to the compressed data packet by using a background processing subsystem, linking the unmanned aerial vehicle to fly to the fault point location according to the fault point location information so that the unmanned aerial vehicle shoots real-time images and video data, and transmitting the shot real-time images and video data back to the background processing subsystem.
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