CN117761455A

CN117761455A - Line fault studying and judging method and system based on fault ranging

Info

Publication number: CN117761455A
Application number: CN202311625997.5A
Authority: CN
Inventors: 才绪东; 周怡; 张鹏; 李强; 尹朋; 李晓良; 刘成明; 朱小滕
Original assignee: Shandong Luruan Digital Technology Co Ltd
Current assignee: Shandong Luruan Digital Technology Co Ltd
Priority date: 2023-11-30
Filing date: 2023-11-30
Publication date: 2024-03-26

Abstract

The invention relates to the technical field of power grid maintenance, in particular to a line fault studying and judging method and system based on fault location, comprising the following steps: acquiring wave-recording distance-measuring data of fault distance measurement, and analyzing a fault section based on the wave-recording distance-measuring data; generating a cruising route for the fault section, and issuing the cruising route to the unmanned aerial vehicle; acquiring patrol data acquired by an unmanned aerial vehicle, and acquiring a fault position and a fault scene based on the patrol data; and analyzing the fault reasons based on the fault monitoring data and the fault scene at the power grid side, and outputting the fault positions and the fault reasons as a research and judgment result. The invention can improve the positioning accuracy of the line fault and analyze the fault reason.

Description

Line fault studying and judging method and system based on fault ranging

Technical Field

The invention belongs to the technical field of power grid maintenance, and particularly relates to a line fault studying and judging method and system based on fault ranging.

Background

In the fault operation of a power transmission line, traveling wave ranging is one of the current mainstream methods for judging the fault point of the line, and the purpose of the traveling wave ranging is to accurately judge the position of the fault point of the line by using the propagation time of the fault traveling wave on the line to measure the fault distance. The traveling wave ranging is divided into single-end ranging and double-end ranging, the single-end ranging technology is simple to realize, the input cost is low, and the current application scene is wider. The method comprises the steps of judging a traveling wave ranging fault point, namely, a traveling wave acquisition device, acquiring the fault distance from a fault signal to a bus, secondly, a fault handling system, judging the approximate position of the fault point according to fault ranging and equipment account, thirdly, pushing line fault information to a mobile phone of a line inspection worker by means of a short message platform and the like, and fourthly, carrying out fault information confirmation and handling by the line inspection worker according to the fault information to the fault point. Because the transmission line passes by the terrain, climate, surrounding environment and other factors relatively complex, the single traveling wave ranging method is limited by the accuracy of equipment standing account information maintenance, and line inspection personnel often need to perform secondary positioning of the fault point after reaching the fault point, so that the rapid treatment and repair of the line fault cannot be effectively realized.

Disclosure of Invention

Aiming at the defects in the prior art, the invention provides a line fault studying and judging method and system based on fault ranging so as to solve the technical problems.

In a first aspect, the present invention provides a line fault diagnosis method based on fault location, including:

acquiring wave-recording distance-measuring data of fault distance measurement, and analyzing a fault section based on the wave-recording distance-measuring data;

generating a cruising route for the fault section, and issuing the cruising route to the unmanned aerial vehicle;

acquiring patrol data acquired by an unmanned aerial vehicle, and acquiring a fault position and a fault scene based on the patrol data;

and analyzing the fault reasons based on the fault monitoring data and the fault scene at the power grid side, and outputting the fault positions and the fault reasons as a research and judgment result.

In an alternative embodiment, acquiring the wave-recording ranging data of the fault ranging, and analyzing the fault section based on the wave-recording ranging data, including:

acquiring original fault information pushed by a dispatching automation system through a kafka subscription message and an Internet of things management platform; analyzing the fault wave recording file to obtain fault location, fault power station, fault phase and reclosing condition information of the line fault point research and judgment reference factor; if fault information of the same line and the same transformer substation exists in the appointed period, the fault information is combined into the same fault information; if the fault information of different substations of the same line exists within the appointed time limit, judging the fault information as different fault information;

Acquiring the minimum distance and the maximum distance within 2.5km around according to the wave recording distance measurement, and defaulting to 0 if the distance measurement is calculated as a negative number; firstly, calculating a distance through a fault power station coordinate and a tower coordinate, and if the distance is in a range of a maximum distance and a minimum distance, recording the tower information into a fault tower section set; calculating the distance between the next tower and the previous tower according to the topological connection sequence through the newly calculated tower coordinates, and if the distance is in the range of the maximum distance and the minimum distance, recording the tower information into a fault tower section set, and calculating the length of the fault section; if the distance exceeds the range of the maximum distance and the minimum distance, completing the calculation of the fault section, and recording the number of the initial tower and the number of the final tower according to the topological connection sequence of the towers.

In an alternative embodiment, generating a cruising route for the faulty section and issuing the cruising route to the unmanned aerial vehicle comprises:

and generating a cruising route based on the starting point position, the terminal position, the middle characteristic point position and the position of the unmanned aerial vehicle nest of the fault section, and issuing the cruising route to the unmanned aerial vehicle.

In an optional embodiment, acquiring patrol data acquired by the unmanned aerial vehicle, and acquiring a fault location and a fault scene based on the patrol data, includes:

Identifying an image frame containing a fault scene from the patrol data by utilizing an image identification technology;

and obtaining the fault position based on the image frame shooting time and the position coordinates of the unmanned aerial vehicle at the image frame shooting time.

In an optional embodiment, analyzing the fault cause based on the fault monitoring data and the fault scenario at the grid side, and outputting the fault location and the fault cause as the research result, including:

the mountain fire fault judging method comprises the following steps: a. the fault phase is single-phase, and reclosing is unsuccessful; b. inquiring hidden danger information in a forest area according to the fault line and the fault section tower id and the position name; c. if the information is obtained, inquiring the information of the terrain area to which the line belongs and locating in the forest area, and judging that the line is a fault mountain fire hidden danger; d. if not, inquiring whether the air temperature exceeds 30 ℃ according to the fault time and the city of the fault section, and if so, judging that the fault-air temperature exceeds 30 ℃;

the lightning stroke fault judging method comprises the following steps: a. the phase is single-phase and reclosing is successful; b. inquiring hidden danger information in mountain areas according to the tower ids and the position names of the fault lines and the fault sections, if the hidden danger information is obtained, inquiring the information of the terrain areas to which the lines belong at the same time, and judging that the faults are in the mountain areas if the hidden danger information is in the mountain areas; c. according to the fault time, inquiring lightning positioning information within 5 minutes before and after the fault, cruising and calculating a lightning stroke distance according to the tower coordinates and the lightning point coordinates, judging that the fault is lightning stroke when the distance is within 5km, and recording the number of the lightning stroke tower, the lightning occurrence time, the lightning stroke distance and the lightning current when the distance is within 1 km; d. if the two conditions are not met, inquiring whether the thunderstorm weather is the thunderstorm weather or not according to the fault time and the fault section, and if the thunderstorm weather is obtained, judging that the thunderstorm weather is the fault thunderstorm weather;

The wind deflection fault judging method comprises the following steps: a. the fault phase is single-phase; b. inquiring weather information of the wind power exceeding 5 levels according to the fault time and the fault section, and judging that the fault-wind power exceeds 5 levels if the weather information is obtained; c. if the line id, the tower id of the fault section and the query defect part are defects of the bow line type, if the line id, the tower id of the fault section and the query defect part are not satisfied, judging that the fault exists, and if the line id, the tower id of the fault section and the query defect part are defects of the bow line type, judging that the fault exists; d. if the C is not satisfied, according to the line id, the tower id of the fault section and the query defect part, judging that the fault exists and the ground potential distance is insufficient if the defect is obtained;

the method for judging the foreign matter short-circuit fault comprises the following steps: a. the fault phase is single-phase; b. according to the line id, the tower id of the fault section and the potential query hazards are mainly the potential hazards of the fishing type, if the potential hazards are obtained, the fault-the potential fishing hazards are judged; c. if the wind power is not satisfied with the wind power b, inquiring weather information of the wind power exceeding 5 levels according to the fault time, the fault section, and judging that the fault-wind power exceeds 5 levels if the weather information is obtained; d. if the potential hazards do not meet the requirement c, the potential hazards are classified as floating object potential hazards according to the line id, the fault section tower id and the query potential hazards, and if the potential hazards are obtained, the fault-existence of the floating object potential hazards is judged; e. if the step d is not satisfied, inquiring hidden danger in the greenhouse according to the line id, the tower id of the fault section and the position name, and judging that the fault is in the greenhouse area if the hidden danger is obtained; f. if the phases are multiphase, the potential hazards are classified as floating object hidden hazards according to the line id, the tower id of the fault section and the query hidden hazards, and if the potential hazards are acquired, the fault is judged to be the floating object hidden hazards;

The judging method of the body fault comprises the following steps: a. inquiring defects of the types of wires, ground wires, insulators and hardware fittings according to the tower ids of the fault lines and the fault sections; b. if the main body defects are obtained, judging that the main body defects of the lead, the ground wire, the insulator and the hardware are present; c. if the fault phase is three-phase, and the wind power exceeds five stages according to the fault time and the fault section query, judging that the fault-body fault exists;

the method for judging the construction external breaking fault comprises the following steps: a. the fault phase is single-phase; b. inquiring hidden danger information which is mainly of construction external breaking type according to the tower ids of the fault line and the fault section; c. if the construction failure is obtained, judging that the construction failure exists;

the method for judging the tree discharge faults comprises the following steps: a. the fault phase is single-phase, reclosing is successful, and hidden danger information of tree types is inquired according to the fault line and the fault section tower id; b. if the tree hidden danger is acquired, judging that the tree hidden danger exists as a fault; c. if the weather information of the air temperature exceeding 30 ℃ is not obtained, whether the occurrence time is at 10-14 points is calculated according to the fault time, and if the weather information of the air temperature exceeding 30 ℃ is inquired according to the fault time and the fault section in the time period, the fault is judged as: 10-14 points, and the temperature exceeds 30 ℃; d. and e, if the fault is multiple phases, acquiring the information of the terrain area to which the line belongs at the same time, and judging that the fault is located in the nursery area.

In a second aspect, the present invention provides a line fault diagnosis system based on fault location, including:

the data acquisition module is used for acquiring wave-recording distance-measuring data of fault distance measurement and analyzing a fault section based on the wave-recording distance-measuring data;

the cruise control module is used for generating a cruise route for the fault section and issuing the cruise route to the unmanned aerial vehicle;

the patrol analysis module is used for acquiring patrol data acquired by the unmanned aerial vehicle and acquiring a fault position and a fault scene based on the patrol data;

and the reason research and judgment module is used for analyzing the fault reason based on the fault monitoring data and the fault scene at the power grid side and outputting the fault position and the fault reason as a research and judgment result.

In an alternative embodiment, the data acquisition module includes:

the information acquisition unit is used for acquiring original fault information pushed by the dispatching automation system through the kafka subscription message and the Internet of things management platform; analyzing the fault wave recording file to obtain fault location, fault power station, fault phase and reclosing condition information of the line fault point research and judgment reference factor; if fault information of the same line and the same transformer substation exists in the appointed period, the fault information is combined into the same fault information; if the fault information of different substations of the same line exists within the appointed time limit, judging the fault information as different fault information;

The information analysis unit is used for acquiring the minimum distance and the maximum distance within 2.5km around according to the wave recording distance measurement, and defaulting to 0 if the distance measurement is calculated as a negative number; firstly, calculating a distance through a fault power station coordinate and a tower coordinate, and if the distance is in a range of a maximum distance and a minimum distance, recording the tower information into a fault tower section set; calculating the distance between the next tower and the previous tower according to the topological connection sequence through the newly calculated tower coordinates, and if the distance is in the range of the maximum distance and the minimum distance, recording the tower information into a fault tower section set, and calculating the length of the fault section; if the distance exceeds the range of the maximum distance and the minimum distance, completing the calculation of the fault section, and recording the number of the initial tower and the number of the final tower according to the topological connection sequence of the towers.

In an alternative embodiment, the cruise control module includes:

and the route generation unit is used for generating a cruising route based on the starting point position, the terminal point position, the middle characteristic point position and the position of the unmanned aerial vehicle nest of the fault section and issuing the cruising route to the unmanned aerial vehicle.

In an alternative embodiment, the patrol analysis module includes:

An image recognition unit for recognizing an image frame containing a fault scene from the patrol data by using an image recognition technology;

and the accurate positioning unit is used for obtaining the fault position based on the image frame shooting time and the position coordinates of the unmanned aerial vehicle at the image frame shooting time.

In an alternative embodiment, the reason grinding module includes:

The line fault research and judgment method and system based on the fault distance measurement have the advantages that the line fault research and judgment method and system based on the fault distance measurement are based on the fault distance measurement technology, the equipment account information is combined, the reference parameter quantity of fault point research and judgment is constructed, the distance measurement is carried out by adopting the tower space coordinate information according to the condition that the tower span maintenance is missing, the influence of the tower span missing on the line fault point judgment is filled, and the accuracy of fault point judgment is improved. The preprocessing of deadline data such as lightning and disaster early warning is realized by utilizing a data cleaning technology, and aiming at the condition that lightning stroke, strong wind and other weather exist in the range of 5 km near a fault point, the detection of deadline information such as lightning and disaster early warning is added to the research and judgment of line faults, so that the accuracy of the research and judgment of fault reasons is improved. By utilizing the data analysis technology, the real-time inspection result of line visual inspection and unmanned aerial vehicle inspection intelligent equipment is comprehensively utilized and used as the parameter quantity for fault point research and judgment, so that the method provided by the patent can realize the fine judgment of fault information, and the efficiency of fault treatment is promoted by utilizing the digital technology.

In addition, the invention has reliable design principle, simple structure and very wide application prospect.

Drawings

In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings that are required to be used in the description of the embodiments or the prior art will be briefly described below, and it will be obvious to those skilled in the art that other drawings can be obtained from these drawings without inventive effort.

FIG. 1 is a schematic flow chart of a method of one embodiment of the invention.

Fig. 2 is a flowchart of fault diagnosis based on the fault location and data analysis technology in an embodiment of the present invention.

FIG. 3 is a flow chart of determining a fault section according to fault location and ledger in an embodiment of the present invention.

FIG. 4 is a flow chart of a visual inspection in an embodiment of the present invention.

Fig. 5 is a flowchart of unmanned aerial vehicle inspection in an embodiment of the invention.

Fig. 6 is a flowchart of mountain fire fault determination in an embodiment of the present invention.

FIG. 7 is a flow chart of lightning strike fault determination in an embodiment of the invention.

FIG. 8 is a flowchart of a wind deflection fault determination in accordance with an embodiment of the present invention.

Fig. 9 is a flowchart of a foreign matter short-circuit fault determination according to an embodiment of the present invention.

FIG. 10 is a schematic block diagram of a system of one embodiment of the present invention.

Detailed Description

In order to make the technical solution of the present invention better understood by those skilled in the art, the technical solution of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, and it is apparent that the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the present invention without making any inventive effort, shall fall within the scope of the present invention.

Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. The terminology used herein in the description of the invention is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention.

The line fault studying and judging method based on the fault location provided by the embodiment of the invention is executed by the computer equipment, and correspondingly, the line fault studying and judging system based on the fault location runs in the computer equipment.

FIG. 1 is a schematic flow chart of a method of one embodiment of the invention. The execution subject of fig. 1 may be a line fault determination system based on fault location. The order of the steps in the flow chart may be changed and some may be omitted according to different needs.

As shown in fig. 1, the method includes:

step 110, acquiring wave-recording distance-measuring data of fault distance measurement, and analyzing a fault section based on the wave-recording distance-measuring data;

step 120, generating a cruising route for the fault section, and issuing the cruising route to the unmanned aerial vehicle;

130, acquiring patrol data acquired by an unmanned aerial vehicle, and acquiring a fault position and a fault scene based on the patrol data;

and 140, analyzing the fault reasons based on the fault monitoring data and the fault scene at the power grid side, and outputting the fault positions and the fault reasons as a research and judgment result.

In order to facilitate understanding of the present invention, the principle of the line fault determination method based on fault location according to the present invention is used to further describe the line fault determination method based on fault location according to the present invention in combination with the process of determining a line fault based on fault location in the embodiment.

Aiming at the defect that line inspection personnel need to secondarily locate the fault point when arriving at the fault site caused by inaccurate line fault point research and judgment in the existing method, the invention provides a novel power transmission line fault research and judgment method based on fault location and data analysis technology, and refer to fig. 2. The invention collects fault data based on the existing fault wave recording device, and extracts fault distance measurement and a fault power station as reference factors; rough research and judgment are carried out by utilizing space topology information of line equipment, and a fault section is determined; starting a full line monitoring command of a fault line by using a visual monitoring device, issuing a fault point inspection task by using an unmanned aerial vehicle nest, and comprehensively utilizing real-time monitoring results returned by visual monitoring and intelligent equipment of the unmanned aerial vehicle nest to accurately determine fault point information and fault site conditions; preprocessing information such as lightning location, real-time deadlines, mountain fires, bird damage, disaster early warning and the like by using the Dataworks, extracting information such as lightning points, real-time deadlines, mountain fires, bird damage, disaster early warning and the like near a fault section, and finely judging line fault points and fault reasons.

Specifically, the line fault studying and judging method based on fault location comprises the following steps:

s1, acquiring wave-recording distance measurement data of fault distance measurement, and analyzing a fault section based on the wave-recording distance measurement data.

Collecting fault study reference factors: and through the kafka subscription message, the original fault information pushed by the dispatching automation system is accessed by means of the Internet of things management platform, the fault record file is analyzed, and the acquisition of information such as fault location, fault power station, fault phase, reclosing condition and the like of the line fault point research and judgment reference factors is realized. The analyzed fault data needs to judge whether faults sent by different substations of the same line exist within 5 minutes, and if faults of the same substation of the same line exist within 5 minutes, the faults are the same faults; if the transformer stations are different substations of the same line, the transformer stations are different faults.

And (3) judging a fault section: acquiring the minimum distance and the maximum distance within 2.5km around according to the recorded distance measurement, and defaulting to 0 if the distance measurement is calculated as a negative number, refer to fig. 3; a. firstly, calculating a distance through a fault power station coordinate and a tower coordinate, and if the distance is in a range of a maximum distance and a minimum distance, recording the tower information into a fault tower section set; b. calculating the distance between the next tower and the previous tower according to the topological connection sequence through the newly calculated tower coordinates, if the distance is within the range of the maximum distance and the minimum distance, recording the tower information into a fault tower section set, calculating the length of the fault section, and repeating the action of b; c. if the distance exceeds the range of the maximum distance and the minimum distance, completing the calculation of the fault section, and recording the number of the initial tower and the number of the final tower according to the topological connection sequence of the towers.

The expression for calculating the faulty section is:

max=x+2500 (1)

min= (x-2500) <00:x-2500 (formula 2)

dis=f ((x 1, y 1), (x 2, y 2), wgs) (formula 3)

z= (min < dis < max) (4)

Wherein x is the fault distance measurement acquired by the fault wave recording device; max is the maximum distance in the range of 2.5km calculated by fault ranging; min is the minimum distance in the range of 2.5km calculated by fault ranging; f (x, y, z) is a distance calculation function between two coordinate points, x is a starting point longitude and latitude coordinate, y is a target point longitude and latitude coordinate, z is a reference coordinate system, wgs is adopted as the coordinate system in the method, x1 is a starting point longitude, y1 is a starting point latitude, y1 is a target point longitude, and y2 is a target point latitude; z is a formula for judging the fault section point, and the derivation process of the formula shows that the equipment within the range of 2.5km of fault location belongs to the fault section.

S2, generating a cruising route for the fault section, and issuing the cruising route to the unmanned aerial vehicle.

Specifically, based on the fault section, the algorithm service layer automatically generates an instruction task of full-line visual monitoring, and sends the instruction task to the visual monitoring system by means of a communication link, please refer to fig. 4, the visual monitoring system immediately starts full-line monitoring after receiving the monitoring task, and returns the monitoring result to the fault judging algorithm. The algorithm test compares the fault section with the uploaded monitoring result information by means of a data analysis technology, and further determines fault point information; based on the fault section, the algorithm service layer can automatically generate a patrol task of the unmanned aerial vehicle nest, and the patrol task is issued to the unmanned aerial vehicle patrol system by means of a communication link, please refer to fig. 5, after the unmanned aerial vehicle patrol system receives the patrol task, the unmanned aerial vehicle patrol is started immediately, and patrol records and defect records found in the patrol process are returned to the fault studying and judging algorithm for measurement. The algorithm test compares the fault section with the sent patrol record and defect record information by means of a data analysis technology, and finely determines fault point information and fault site conditions.

S3, acquiring patrol data acquired by the unmanned aerial vehicle, and acquiring a fault position and a fault scene based on the patrol data.

Identifying an image frame containing a fault scene from the patrol data by utilizing an image identification technology; and obtaining the fault position based on the image frame shooting time and the position coordinates of the unmanned aerial vehicle at the image frame shooting time.

The image recognition technology is used for recognizing image frames containing fault scenes, for example, common fault scene images are used as recognition objects, and the fault scenes are recognized from the inspection video by using the YOLO-3 algorithm.

And S4, analyzing the fault reasons based on the fault monitoring data and the fault scene at the power grid side, and outputting the fault positions and the fault reasons as a research and judgment result.

Data preprocessing: the method has the advantages that the information such as lightning stroke and disaster early warning is greatly influenced by weather factors, the characteristics of large instantaneous data quantity and the like are often existed, the traditional data processing and processing means are long in time consumption, the requirement on timeliness of fault judgment cannot be met, the data is processed and preprocessed by using a Dataworks tool, the lightning point and disaster early warning information near a fault section which are based on initial judgment are output to a specific target library, and the data comparison efficiency is improved.

And (3) fault cause research and judgment: and acquiring information such as fault sections, fault phases, reclosing conditions and the like in the fault information.

Mountain fire failure: a. the fault phase is single-phase, and reclosing is unsuccessful; b. inquiring hidden danger information in a forest area according to the fault line and the fault section tower id and the position name; c. if the information is obtained, inquiring the information of the terrain area to which the line belongs and locating in the forest area, and judging that the line is a fault-forest fire hidden danger; d. if not, inquiring whether the air temperature exceeds 30 ℃ according to the fault time and the city of the fault section, and if so, judging that the fault-air temperature exceeds 30 ℃, referring to fig. 6.

Lightning strike fault: a. the phase is single-phase and reclosing is successful; b. inquiring hidden danger information in mountain areas according to the tower ids and the position names of the fault lines and the fault sections, if the hidden danger information is obtained, inquiring the information of the terrain areas to which the lines belong at the same time, and judging that the fault is located in the mountain areas; c. according to the fault time, inquiring lightning positioning information within 5 minutes before and after the fault, cruising and calculating a lightning stroke distance according to the tower coordinates and the lightning point coordinates, judging that the fault is lightning stroke when the distance is within 5km, and recording the number of the lightning stroke tower, the lightning occurrence time, the lightning stroke distance and the lightning current when the distance is within 1 km; d. if the two conditions are not met, inquiring whether the weather is thunderstorm or not according to the fault time and the fault section, and if the weather is obtained, judging that the weather is the thunderstorm, and referring to fig. 7.

Wind deflection fault: a. the fault phase is single-phase; b. inquiring weather information of the wind power exceeding 5 levels according to the fault time and the fault section, and judging that the fault-wind power exceeds 5 levels if the weather information is obtained; c. if the line id, the tower id of the fault section and the query defect part are defects of the bow line type, if the line id, the tower id of the fault section and the query defect part are not satisfied, judging that the fault exists, and if the line id, the tower id of the fault section and the query defect part are defects of the bow line type, judging that the fault exists; d. if c is not satisfied, a defect of insufficient distance to the ground potential is determined to be a fault-defect of insufficient distance to the ground potential if obtained according to the line id, the fault section tower id and the query defect part, and refer to fig. 8.

Foreign matter short circuit fault: a. the fault phase is single-phase; b. according to the line id, the tower id of the fault section and the potential query hazards are mainly the potential hazards of the fishing type, if the potential hazards are obtained, the fault-the potential fishing hazards are judged; c. if the wind power is not satisfied with the wind power b, inquiring weather information of the wind power exceeding 5 levels according to the fault time, the fault section, and judging that the fault-wind power exceeds 5 levels if the weather information is obtained; d. if the potential hazards do not meet the requirement c, the potential hazards are classified as floating object potential hazards according to the line id, the fault section tower id and the query potential hazards, and if the potential hazards are obtained, the fault-existence of the floating object potential hazards is judged; e. if the step d is not satisfied, inquiring hidden danger in the greenhouse according to the line id, the tower id of the fault section and the position name, and judging that the fault is in the greenhouse area if the hidden danger is obtained; f. if the phases are multi-phase, the potential hazards are classified as floating object potential hazards according to the line id, the tower id of the fault section and the query potential hazard, and if the potential hazards are acquired, the fault is judged to be the floating object potential hazard, and please refer to fig. 9.

Body failure: a. inquiring defects of the types of wires, ground wires, insulators and hardware fittings according to the tower ids of the fault lines and the fault sections; b. if the main body defects are obtained, judging that the main body defects of the lead, the ground wire, the insulator and the hardware are present; c. if the fault phase is three-phase, and the wind power exceeds five stages according to the fault time and the fault section query, the fault-body fault (inverted tower) is determined.

Construction external breaking fault: a. the fault phase is single-phase; b. inquiring hidden danger information which is mainly of construction external breaking type according to the tower ids of the fault line and the fault section; c. if the failure is obtained, the failure is judged to be the hidden trouble of construction external damage.

Tree discharge failure: a. the fault phase is single-phase, reclosing is successful, and hidden danger information of tree types is inquired according to the fault line and the fault section tower id; b. if the tree hidden danger is acquired, judging that the tree hidden danger exists as a fault; c. if the weather information of the air temperature exceeding 30 ℃ is not obtained, whether the occurrence time is at 10-14 points is calculated according to the fault time, and if the weather information of the air temperature exceeding 30 ℃ is inquired according to the fault time and the fault section in the time period, the fault is judged as: 10-14 points, and the temperature exceeds 30 ℃; d. and e, if the fault is multiple phases, acquiring the information of the terrain area to which the line belongs at the same time, and judging that the fault is located in the nursery area.

The expression used to calculate the tree fault is:

y1= (10 < x < 14) (formula 5)

y2= (30 ℃ < y) (6)

Wherein x is the number of hours corresponding to the failure time; y is the time limit temperature information according to the fault time and the city query of the fault section.

In some embodiments, the line fault finding based line fault finding system may include a plurality of functional modules comprised of computer program segments. The computer program of each program segment in the line fault finding based line fault finding system may be stored in a memory of a computer device and executed by at least one processor to perform (see fig. 1 for details) the function of line fault finding based line fault finding.

In this embodiment, the line fault diagnosis system based on the fault location may be divided into a plurality of functional modules according to the functions performed by the line fault diagnosis system, as shown in fig. 10. The functional modules of system 1000 may include: the system comprises a data acquisition module 1010, a cruise control module 1020, a patrol analysis module 1030, and a cause grinding module 1040. The module referred to in the present invention refers to a series of computer program segments capable of being executed by at least one processor and of performing a fixed function, stored in a memory. In the present embodiment, the functions of the respective modules will be described in detail in the following embodiments.

Optionally, as an embodiment of the present invention, the data obtaining module includes:

Optionally, as an embodiment of the present invention, the cruise control module includes:

Optionally, as an embodiment of the present invention, the patrol analysis module includes:

Optionally, as an embodiment of the present invention, the reason grinding module includes:

Although the present invention has been described in detail by way of preferred embodiments with reference to the accompanying drawings, the present invention is not limited thereto. Various equivalent modifications and substitutions may be made in the embodiments of the present invention by those skilled in the art without departing from the spirit and scope of the present invention, and it is intended that all such modifications and substitutions be within the scope of the present invention/be within the scope of the present invention as defined by the appended claims. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.

Claims

1. The line fault studying and judging method based on fault ranging is characterized by comprising the following steps of:

2. The method of claim 1, wherein obtaining recorded ranging data for the fault range and resolving the fault section based on the recorded ranging data comprises:

3. The method of claim 1, wherein generating a cruising route for the faulty section and issuing the cruising route to a drone, comprises:

4. The method of claim 1, wherein acquiring the drone collected tour data, acquiring a fault location and a fault scenario based on the tour data, comprises:

5. The method according to claim 1, wherein analyzing the fault cause based on the fault monitoring data and the fault scenario on the grid side and outputting the fault location and the fault cause as the determination result, comprises:

6. A line fault studying and judging system based on fault ranging is characterized by comprising:

7. The system of claim 6, wherein the data acquisition module comprises:

8. The system of claim 6, wherein the cruise control module comprises:

9. The system of claim 6, wherein the tour resolution module comprises:

10. The system of claim 6, wherein the cause grinding module comprises: