CN114696467B - Method and system for analyzing and processing fault tripping event of high-voltage transmission long line - Google Patents

Method and system for analyzing and processing fault tripping event of high-voltage transmission long line Download PDF

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CN114696467B
CN114696467B CN202210603431.1A CN202210603431A CN114696467B CN 114696467 B CN114696467 B CN 114696467B CN 202210603431 A CN202210603431 A CN 202210603431A CN 114696467 B CN114696467 B CN 114696467B
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CN114696467A (en
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雷剧璋
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Foshan Power Supply Bureau of Guangdong Power Grid Corp
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    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J13/00—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network
    • H02J13/00002—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network characterised by monitoring
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
    • G01R31/08—Locating faults in cables, transmission lines, or networks
    • G01R31/081—Locating faults in cables, transmission lines, or networks according to type of conductors
    • G01R31/085—Locating faults in cables, transmission lines, or networks according to type of conductors in power transmission or distribution lines, e.g. overhead
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
    • G01R31/08—Locating faults in cables, transmission lines, or networks
    • G01R31/088—Aspects of digital computing
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02H—EMERGENCY PROTECTIVE CIRCUIT ARRANGEMENTS
    • H02H7/00—Emergency protective circuit arrangements specially adapted for specific types of electric machines or apparatus or for sectionalised protection of cable or line systems, and effecting automatic switching in the event of an undesired change from normal working conditions
    • H02H7/26—Sectionalised protection of cable or line systems, e.g. for disconnecting a section on which a short-circuit, earth fault, or arc discharge has occured
    • H02H7/261—Sectionalised protection of cable or line systems, e.g. for disconnecting a section on which a short-circuit, earth fault, or arc discharge has occured involving signal transmission between at least two stations
    • H02H7/263—Sectionalised protection of cable or line systems, e.g. for disconnecting a section on which a short-circuit, earth fault, or arc discharge has occured involving signal transmission between at least two stations involving transmissions of measured values
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J13/00—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network
    • H02J13/00001—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network characterised by the display of information or by user interaction, e.g. supervisory control and data acquisition systems [SCADA] or graphical user interfaces [GUI]
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J13/00—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network
    • H02J13/00032—Systems characterised by the controlled or operated power network elements or equipment, the power network elements or equipment not otherwise provided for
    • H02J13/00034—Systems characterised by the controlled or operated power network elements or equipment, the power network elements or equipment not otherwise provided for the elements or equipment being or involving an electric power substation
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J13/00—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network
    • H02J13/00032—Systems characterised by the controlled or operated power network elements or equipment, the power network elements or equipment not otherwise provided for
    • H02J13/00036—Systems characterised by the controlled or operated power network elements or equipment, the power network elements or equipment not otherwise provided for the elements or equipment being or involving switches, relays or circuit breakers
    • H02J13/0004—Systems characterised by the controlled or operated power network elements or equipment, the power network elements or equipment not otherwise provided for the elements or equipment being or involving switches, relays or circuit breakers involved in a protection system
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
    • Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
    • Y04S10/00—Systems supporting electrical power generation, transmission or distribution
    • Y04S10/16—Electric power substations

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  • Engineering & Computer Science (AREA)
  • Power Engineering (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Human Computer Interaction (AREA)
  • Mathematical Physics (AREA)
  • Theoretical Computer Science (AREA)
  • Supply And Distribution Of Alternating Current (AREA)
  • Remote Monitoring And Control Of Power-Distribution Networks (AREA)
  • Locating Faults (AREA)

Abstract

The invention provides a method and a system for analyzing and processing a fault tripping event of a high-voltage transmission long line, wherein the method comprises the steps of judging and processing faults according to action information and time scale information of each monitoring device on the line, and continuing the subsequent steps if each monitoring device on the line has no fault; acquiring environmental parameters of the line, and calculating the correlation between the line fault and external influence factors by using a correlation calculation method; determining influence factors of the line fault based on the correlation, and extracting historical data to further determine and process the influence factors of the line fault; and fault judgment and processing are carried out on the line equipment, the line control loop and the background signal based on the health degree of the first line equipment and the second line equipment. According to the invention, the fault conditions of the power transmission line and the related devices are effectively analyzed and judged by integrating the monitoring data of all aspects, so that help can be provided for workers to quickly and comprehensively analyze the line problems, the analysis time is reduced, and the working efficiency is improved.

Description

Method and system for analyzing and processing fault tripping event of high-voltage transmission long line
Technical Field
The invention belongs to the technical field of power grid dispatching automation, and particularly relates to a method and a system for analyzing and processing a fault tripping event of a high-voltage transmission long line.
Background
With the continuous advance of the unmanned substation, workers are required to go to the site for inspection in time after a substation event occurs, but most of the substation positions are in remote areas, so that the time for the workers to arrive at the station is long. In addition, the field inspection work of workers is also hindered by the problem of severe weather and the like.
At present, after a line is tripped in a line fault station, an operator in charge of equipment monitoring can not check equipment in a substation on site, but the existing monitoring system is fully utilized to obtain information and analyze the information, and a duty dispatcher reports whether the equipment abnormality influencing the forced transmission of the line is found or not within 12 minutes. After the line is tripped and under normal conditions, after the outside of the switch and the line protection action condition need to be checked on site, the switch is confirmed to be abnormal, the protection action condition is judged to be abnormal, and the line operation and maintenance unit is confirmed to not find the abnormal condition which influences forced transmission, so that the line can be forcibly transmitted once. If the first forced delivery is unsuccessful, the on-duty dispatcher can carry out second forced delivery according to the fault condition and the system requirement; if the two times of forced delivery are not successful, the on-duty dispatcher can forcibly deliver the materials for many times after asking the unit to manage the production leaders to agree.
However, the existing line fault station flow is only isolated and compared to find the situation of an analysis event on one side, on one hand, a large amount of time is consumed for finding, and on the other hand, the line is forced to be sent under the condition that the analysis situation is not clear, so that the line is impacted for many times.
Disclosure of Invention
In view of this, the present invention aims to solve the problem that the line is impacted many times due to the fact that the existing line fault intra-station flow is isolated and one-sided to search for the analysis event, which requires a lot of time to search and may have an ambiguous analysis condition.
In order to solve the technical problems, the invention provides the following technical scheme:
in a first aspect, the invention provides a method for analyzing and processing a high-voltage transmission long-line fault tripping event, which comprises the following steps:
judging and processing faults according to the action information and the time mark information of each monitoring device on the line, and continuing the subsequent steps if each monitoring device on the line has no fault;
acquiring environmental parameters of the line, and calculating the correlation between the line fault and external influence factors by using a correlation calculation method;
comparing the calculated correlation with a preset external influence threshold and an internal influence threshold, determining influence factors causing the line fault according to the comparison result, wherein the influence factors comprise external influence factors and internal influence factors, and extracting historical data to further determine and process the influence factors of the line fault;
and fault judgment and processing are carried out on the line equipment, the line control loop and the background signal based on the health degree of the first line equipment and the second line equipment.
Further, the fault judgment and processing is performed according to the action information and the time scale information of each monitoring device on the line, and the method specifically comprises the following steps:
acquiring action information and corresponding time scale information of each monitoring device on a line;
time conversion is carried out according to the time mark information of each device, action information of each device is judged after being unified on the same time axis, if the monitoring device breaks down, the maintenance operation is carried out, and the time conversion is carried out according to the following formula:
fy（t）=f（0）+f0（t）+f（yz）
where fy (t) is the remapped time axis, f (0) is the actual time to start recording, f0 (t) is the relative time of each monitoring device, and f (yz) is the correction parameter of each monitoring device.
Further, the environmental parameters specifically include:
the image data of the fault point when the line has a fault, the historical image data of the fault point and the lightning stroke data of the fault point.
Further, the method for calculating the correlation between the line fault and the external influence factor by using the correlation calculation method specifically comprises the following steps:
constructing a correlation calculation formula considering barrier factors and atmospheric factors, wherein the correlation calculation formula specifically comprises the following steps:
Figure 380657DEST_PATH_IMAGE001
in the formula,
Figure 428247DEST_PATH_IMAGE002
indicating a correlation, x0 is an influencing factor, x0=0 indicates an obstacle factor, x0=1 indicates an atmospheric factor,
Figure 800323DEST_PATH_IMAGE003
、
Figure 933364DEST_PATH_IMAGE004
、
Figure 49087DEST_PATH_IMAGE005
、
Figure 888867DEST_PATH_IMAGE006
respectively a position factor, a time factor, a frequency factor,The size factor is a factor of the size,
Figure 431844DEST_PATH_IMAGE007
、
Figure 786602DEST_PATH_IMAGE008
、
Figure 643700DEST_PATH_IMAGE009
、
Figure 400303DEST_PATH_IMAGE010
respectively area, time, number of landings, size of landings,
Figure 114181DEST_PATH_IMAGE011
for the correlation of the fault ranging with the location factor,
Figure 221814DEST_PATH_IMAGE012
for the correlation of the fault ranging with the time factor,
Figure 617024DEST_PATH_IMAGE013
is composed of
Figure 228134DEST_PATH_IMAGE007
The correlation of the number of occurrences over the area,
Figure 378492DEST_PATH_IMAGE014
is composed of
Figure 645526DEST_PATH_IMAGE007
The correlation of the size of the landmine within the area,
Figure 641163DEST_PATH_IMAGE015
represents a correction coefficient;
determining whether the fault point has an obstacle or not by using image data of the fault point when the line has a fault and historical image data of the fault point, if so, determining the correlation under the current condition according to a correlation calculation formula when x0=0, and otherwise, continuing the subsequent steps;
and calculating the correlation in the current situation by using a correlation calculation formula at x0=1 based on the lightning stroke data of the fault point.
In a second aspect, the present invention provides a system for analyzing and processing a high voltage transmission long line fault trip event, including: a forced delivery judging module;
the forced transmission judging module comprises a logic judging unit, a fault influence judging unit and an equipment judging unit;
the logic judgment unit is used for judging and processing faults according to the action information and the time mark information of each monitoring device on the line, and if each monitoring device on the line has no fault, the subsequent steps are continued;
the fault influence judging unit is used for acquiring the environmental parameters of the line and calculating the correlation between the line fault and the external influence factors by using a correlation calculation method; the system is also used for comparing the calculated correlation with a preset external influence threshold and an internal influence threshold, determining influence factors causing the line fault according to the comparison result, wherein the influence factors comprise external influence factors and internal influence factors, and extracting historical data to further determine and process the influence factors of the line fault;
the equipment judgment unit is used for judging and processing faults of the line equipment, the line control loop and the background signal based on the health degree of the line I and the secondary equipment.
Further, the logic determining unit is specifically configured to:
acquiring action information and corresponding time mark information of each monitoring device on a line;
time conversion is carried out according to the time mark information of each device, the action information of each device is judged after being unified on the same time axis, if the monitoring device breaks down, the maintenance operation is carried out, and the time conversion is carried out according to the following formula:
fy（t）=f（0）+f0（t）+f（yz）
where fy (t) is the remapped time axis, f (0) is the actual time to start recording, f0 (t) is the relative time of each monitoring device, and f (yz) is the correction parameter of each monitoring device.
Further, the environmental parameters specifically include:
the image data of the fault point when the line has a fault, the historical image data of the fault point and the lightning stroke data of the fault point.
Further, the fault influence judging unit includes an external influence judging unit, and the external influence judging unit is specifically configured to:
constructing a correlation calculation formula considering barrier factors and atmospheric factors, wherein the correlation calculation formula specifically comprises the following steps:
Figure 372359DEST_PATH_IMAGE001
in the formula,
Figure 631302DEST_PATH_IMAGE002
indicating a correlation, x0 is an influencing factor, x0=0 indicates an obstacle factor, x0=1 indicates an atmospheric factor,
Figure 182369DEST_PATH_IMAGE003
、
Figure 253136DEST_PATH_IMAGE004
、
Figure 776522DEST_PATH_IMAGE005
、
Figure 3104DEST_PATH_IMAGE006
respectively a position factor, a time factor, a frequency factor and a size factor,
Figure 307046DEST_PATH_IMAGE007
、
Figure 910066DEST_PATH_IMAGE008
、
Figure 350274DEST_PATH_IMAGE009
、
Figure 951020DEST_PATH_IMAGE010
respectively area, time, number of landfall and size of landfall,
Figure 476679DEST_PATH_IMAGE011
for the correlation of the fault ranging with the location factor,
Figure 883390DEST_PATH_IMAGE012
for the correlation of the fault ranging with the time factor,
Figure 443684DEST_PATH_IMAGE013
is composed of
Figure 949752DEST_PATH_IMAGE007
The correlation of the number of occurrences over the area,
Figure 228286DEST_PATH_IMAGE014
is composed of
Figure 173109DEST_PATH_IMAGE007
The correlation of the size of the lightning strike within the area,
Figure 587909DEST_PATH_IMAGE015
represents a correction coefficient;
determining whether the fault point has an obstacle or not by using image data of the fault point when the line has a fault and historical image data of the fault point, if so, determining the correlation under the current condition according to a correlation calculation formula when x0=0, and otherwise, continuing the subsequent steps;
calculating the correlation under the current condition by using a correlation calculation formula when x0=1 based on the lightning stroke data of the fault point;
the correlation is used to determine whether a line fault is affected by an external factor.
In conclusion, the invention provides a method and a system for analyzing and processing a fault tripping event of a high-voltage transmission long line, wherein the method comprises the steps of judging and processing faults according to the action information and the time scale information of each monitoring device on the line, and continuing the subsequent steps if each monitoring device on the line has no fault; acquiring environmental parameters of the line, and calculating the correlation between the line fault and external influence factors by using a correlation calculation method; determining influence factors of the line fault based on the correlation, and extracting historical data to further determine and process the influence factors of the line fault; and fault judgment and processing are carried out on the line equipment, the line control loop and the background signal based on the health degree of the primary line equipment and the secondary line equipment. According to the invention, the fault conditions of the power transmission line and the related devices are effectively analyzed and judged by integrating the monitoring data of all aspects, so that help can be provided for workers to quickly and comprehensively analyze the line problems, the analysis time is reduced, and the working efficiency is improved.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art 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 for those skilled in the art, other drawings can be obtained according to these drawings without inventive exercise.
Fig. 1 is a schematic flowchart of a method for analyzing and processing a fault trip event of a high-voltage transmission long line according to an embodiment of the present invention;
FIG. 2 is a schematic flow chart of fault differentiation provided by an embodiment of the present invention;
fig. 3 is a schematic flow chart of a first stage of forced transmission determination according to an embodiment of the present invention;
fig. 4 is a schematic flow chart of a second stage of forced sending determination according to an embodiment of the present invention;
fig. 5 is a schematic flow chart of a third stage of forced sending determination according to an embodiment of the present invention;
fig. 6 is a schematic diagram of waveform data of a line recorder according to an embodiment of the present invention;
fig. 7 is a block diagram of a system for analyzing and processing a high-voltage transmission long line fault trip event according to an embodiment of the present invention.
Detailed Description
In order to make the objects, features and advantages of the present invention more obvious and understandable, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. 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.
With the continuous advance of the unmanned substation, workers are required to go to the site for inspection in time after a substation event occurs, but most of the substation positions are in remote areas, so that the time for the workers to arrive at the station is long. In addition, the field inspection work of workers is also hindered by the problem of severe weather and the like.
At present, after a line is tripped, an operator in charge of equipment monitoring can not check equipment in a transformer substation on site, but can fully utilize the existing monitoring system to acquire information and analyze the information, and report whether the abnormal equipment influencing the forced transmission of the line is found to an on-duty dispatcher within 12 minutes. After the circuit is tripped and under normal conditions, the outside of the switch and the circuit protection action condition need to be checked on site, the switch is confirmed to be abnormal, the protection action condition is judged to be abnormal, the circuit operation and maintenance unit is confirmed to not find the abnormal condition which influences forced transmission, and the circuit can be forcibly transmitted once. If the first forced delivery is unsuccessful, the on-duty dispatcher can carry out second forced delivery according to the fault condition and the system requirement; if the two times of forced delivery are not successful, the on-duty dispatcher can forcibly deliver the materials for many times after asking the unit to manage the production leaders to agree.
However, the existing line fault station flow is only isolated and compared to find the situation of an analysis event on one side, on one hand, a large amount of time is consumed for finding, and on the other hand, the line is forced to be sent under the condition that the analysis situation is not clear, so that the line is impacted for many times.
Based on the method, the invention provides a method and a system for analyzing and processing the high-voltage transmission long-line fault tripping event.
The following describes an embodiment of a method for analyzing and processing a high-voltage transmission long-line fault tripping event according to the present invention in detail.
Referring to fig. 1, the present embodiment provides a method for analyzing and processing a high voltage transmission long line fault trip event, including:
s100: and judging and processing faults according to the action information and the time mark information of each monitoring device on the line, and continuing the subsequent steps if each monitoring device on the line has no fault.
As shown in fig. 1, this step is the first stage of forced delivery determination. The monitoring devices on the circuit comprise relay protection devices and wave recording devices, such as relay protection devices, safety automatic devices and wave recording devices.
By acquiring action information and related time marks, a time axis is established, whether the action condition is correct is judged through a primary equipment wiring diagram and action logic, for example, line action recording is as shown in fig. 6, time mark data is extracted, time conversion is carried out, the time mark data is remapped to a new time axis, and comparative analysis is carried out.
The time change rule is as follows: fy (t) = f (0) + f0 (t) + f (yz), where fy (t) is the remapped time axis, f (0) is the actual time to start recording, f0 (t) is the relative time recorded by the recording or relay device, and f (yz) is the correction parameter for each device. As shown in fig. 3, the time scale information of the relevant device (including the time of the relay protection operation of the line, the safety automatic device, the wave recording device, and the traveling wave device) is used to determine whether the relay protection device, the safety automatic device, the wave recording device, and the traveling wave device are operating correctly. And (3) putting the action waveforms of all the monitoring devices on the same time axis to carry out logic and peak value judgment, and if the action is wrong, judging that the equipment is in misoperation or refused to operate, and immediately reporting to carry out equipment maintenance. This completes the analysis of the first stage of forced delivery judgment in this embodiment.
In addition, before step S100 of the present embodiment, it is also necessary to perform fault differentiation on the line. The fault distinguishing is to judge whether the fault of the line is caused by manual operation or actual fault. As shown in fig. 2, the judgment method is to obtain the work task and the operation task, and further confirm whether the action condition is normal or abnormal, and if the action condition is normal, the judgment is directly finished, and if the action condition is abnormal, the line state is confirmed through the energy management system, and if the line is in a closing state, the reclosing is successful after the line fault is judged, and then part of information is extracted to be collected and reported, including the fault type, the reclosing action condition and other conventional information. If the line state is the brake separating position, judging that the reclosing is unsuccessful, and entering a forced delivery judging process.
S200: and acquiring environmental parameters of the line, and calculating the correlation between the line fault and the external influence factors by using a correlation calculation method.
It should be noted that the second stage of the forced transmission determination is to determine whether the line fault is caused by an external influence or an internal influence. If each monitoring device is operating correctly, an external influence is determined, which is determined first because, for the line, the external influence accounts for a large part of all accident events.
As shown in fig. 4, in this step, corresponding environmental parameters, such as lightning system, inspection result of the unmanned aerial vehicle, historical data, etc., need to be acquired. By acquiring the information and the corresponding actual time scale, whether the influence is caused by external reasons or not is further judged, whether the external influence is thunder or external hanging objects or not is judged, whether the fault disappears or not is judged, and the like. Determining whether external factors such as lightning strike and obstacles exist near a fault point, and acquiring lightning strike data such as a certain lightning system query result in a lightning monitoring system with an XX station as a center and a radius of x 1 XX is divided into a time starting point front-back interval x when XX is carried out on km and XX days 2 min, finding out the occurrence of lightning x in the area 3 Sub (thunderstorm frequency) and XX in XX day XX has a lightning current of x in 220kVXX station 4 kA thunderbolt (thunderbolt size).
The unmanned aerial vehicle system judges the system fault caused by the barrier through image recognition and other methods by acquiring images near the fault point for multiple times. For example, the stored normal image is compared with the recorded image when the fault occurs, whether an abnormal object exists is analyzed, and then the stored normal image is compared with the recorded image after the fault, so that whether the abnormal object still exists is judged. And feeds back the result. The external factors of thunder and lightning are transient faults, and internal factors such as hanging objects and the like can exist for a long time, so that judgment is needed to provide guiding opinions for forced delivery.
The image recognition method is based on unmanned aerial vehicle position information, shooting angle information and shooting parameter information to comprehensively perform image recognition. Under the condition that the shooting parameter information is the same, the six-degree-of-freedom system comprises the following steps:
Figure 264878DEST_PATH_IMAGE016
and comparing the shot picture with historical data, and analyzing and identifying the fault object.
In this step, the influence of the external factors on the line fault is judged by using the correlation.
The correlation calculation and judgment method is used for comprehensively judging the lightning strike time, the lightning strike frequency and the maximum lightning current data. The following correlation calculation formula is established with respect to external factors (including obstacle factors and atmospheric factors):
Figure 765130DEST_PATH_IMAGE017
wherein,
Figure 513643DEST_PATH_IMAGE018
indicating an obstruction factor, and in the presence of an obstruction,
Figure 720633DEST_PATH_IMAGE019
that is, in the case of an obstacle existing in the line, the correlation between the line fault and the obstacle factor is 1 (the correlation value may be adjusted according to the actual situation, and is set to be 1 only for convenient comparison in the subsequent steps);
Figure 896400DEST_PATH_IMAGE020
indicating atmospheric factors, mainly mines near points of obstructionThe hit situation is relevant.
The correlation calculation considering the atmospheric factors needs to comprehensively consider various factors, and the following calculation formula is obtained:
Figure 883947DEST_PATH_IMAGE021
wherein
Figure 108255DEST_PATH_IMAGE003
、
Figure 497648DEST_PATH_IMAGE004
、
Figure 838457DEST_PATH_IMAGE005
、
Figure 47721DEST_PATH_IMAGE006
、
Figure 138037DEST_PATH_IMAGE015
Respectively a position factor, a time factor, a frequency factor, a size factor and a correction factor,
Figure 319620DEST_PATH_IMAGE007
、
Figure 837189DEST_PATH_IMAGE008
、
Figure 799328DEST_PATH_IMAGE009
、
Figure 427756DEST_PATH_IMAGE010
the area size, the time interval, the lightning falling frequency and the lightning falling size are respectively. Wherein
Figure 463845DEST_PATH_IMAGE022
The specific data can be set according to historical data, wherein
Figure 152315DEST_PATH_IMAGE003
、
Figure 336172DEST_PATH_IMAGE004
Fixed, both set to 0.25.
Figure 705973DEST_PATH_IMAGE005
、
Figure 924465DEST_PATH_IMAGE006
、
Figure 783837DEST_PATH_IMAGE015
Along with the dynamic change of historical data, for example, the historical lightning falling frequency and the lightning falling magnitude of the area are low, when a high value appears, the specific mode of increasing the coefficient can be obtained through comparison as follows:
taking 50 historical data, wherein the average value of the lightning falling frequency and the size of 50 lightning falling frequency is
Figure 392673DEST_PATH_IMAGE023
Coefficient mean of
Figure 362903DEST_PATH_IMAGE024
The adjustment is as follows:
Figure 435901DEST_PATH_IMAGE025
Figure 466174DEST_PATH_IMAGE026
Figure 562306DEST_PATH_IMAGE027
wherein
Figure 336227DEST_PATH_IMAGE028
The results were ranked 50 times.
Figure 529311DEST_PATH_IMAGE011
For the correlation of the fault ranging with the location factor,
Figure 668168DEST_PATH_IMAGE012
for the correlation of the fault ranging with the time factor,
Figure 48334DEST_PATH_IMAGE013
is composed of
Figure 631805DEST_PATH_IMAGE007
The correlation of the number of occurrences over the area,
Figure 679395DEST_PATH_IMAGE014
is composed of
Figure 989154DEST_PATH_IMAGE007
Correlation of the size of landfall within the area.
Figure 856616DEST_PATH_IMAGE029
L represents the result of the recording ranging,
Figure 972339DEST_PATH_IMAGE030
for the total number of landings within the difference range,
Figure 874436DEST_PATH_IMAGE031
is the total lightning current within the difference of the two.
And calculating a corresponding correlation value according to the image data and the lightning stroke data near the obstacle point and the rule.
S300: and comparing the calculated correlation with a preset external influence threshold and an internal influence threshold, determining influence factors causing the line fault according to the comparison result, wherein the influence factors comprise external influence factors and internal influence factors, and extracting historical data to further determine and process the influence factors of the line fault.
It should be noted that, in the following description,after the correlation value is calculated according to the above steps, it is necessary to set a corresponding external influence threshold and internal influence threshold, and when the correlation is greater than the external influence threshold, it is determined that the line fault occurs as an external influence, whereas when the correlation is less than the internal influence threshold, it is determined that the line fault occurs as an internal influence. As shown in FIG. 4, in practical implementation, if the correlation between the motion distance measurement and the external factors is determined
Figure 355096DEST_PATH_IMAGE002
When the current reaches 80% or more, the process directly enters the next stage, for example, the radius is 3km by taking a 110kVXX line as a center, the distance between the front and the back is 3 minutes, 122 times of lightning falling in the area is found, and a lightning falling with the lightning current of 93.4kA occurs at 2.2km of an off-line road. Consistent with a 10kVXX line tripping at the same time in the system,
Figure 975433DEST_PATH_IMAGE002
＞80%。
if there is a correlation between the motion range and the external factors
Figure 629269DEST_PATH_IMAGE002
And if the internal influence is less than 50%, judging that the internal influence is small, but the data has large fluctuation and exceeds the qualified range, directly reporting abnormal information and stopping power for maintenance. If there is a correlation between the motion range and the external factors
Figure 651451DEST_PATH_IMAGE002
And (4) between 50% and 80%, carrying out optimization judgment by combining local historical processing result data. And if all the data are qualified, entering the subsequent step.
S400: and fault judgment and processing are carried out on the line equipment, the line control loop and the background signal based on the health degree of the first line equipment and the second line equipment.
Note that this step is the third stage of forced delivery determination. The fault analysis of the line equipment is carried out based on the state degree of the primary and secondary equipment, and is carried out according to each equipmentDegree of health of
Figure 303012DEST_PATH_IMAGE032
And degree of importance
Figure 145067DEST_PATH_IMAGE033
The classification is carried out into four levels I, II, III and IV.
Firstly, the numerical value is normalized, and then the classification rule is obtained as follows:
Figure 602593DEST_PATH_IMAGE034
as shown in fig. 5, based on the classification rule, the fault condition of the primary and secondary devices of the line is checked. If the equipment has a fault, the line equipment is changed to be maintained and the health degree of the line equipment is increased 1/4 on the original basis, so that the status degree of the equipment is improved, and the higher the grade is, the more attention needs to be paid.
In addition, the forced transmission judgment also comprises line stability judgment, whether a background abnormal signal exists, whether a history left signal exists and the like. Specifically, the primary condition simulates whether the dynamic stability and the thermal stability of the line meet the requirements under the fault condition, the short circuit resistance of the line is calculated, the air pressure of a line switch is normal and the like, the secondary circuit condition simulates no abnormal signal or historical left signal, and the operating mechanism condition simulates normal hydraulic pressure, normal energy storage and the like. For the equipment or the control loop with the fault, corresponding operation and maintenance work needs to be carried out according to the state degree rating and the operation and maintenance strategy and the implementation rule of the substation equipment.
The embodiment provides a method for analyzing and processing a fault tripping event of a high-voltage transmission long line, which comprises the steps of judging and processing faults according to action information and time scale information of each monitoring device on the line, and continuing the subsequent steps if each monitoring device on the line has no fault; acquiring environmental parameters of the line, and calculating the correlation between the line fault and external influence factors by using a correlation calculation method; determining influence factors of the line fault based on the correlation, and extracting historical data to further determine and process the influence factors of the line fault; and fault judgment and processing are carried out on the line equipment, the line control loop and the background signal based on the health degree of the first line equipment and the second line equipment. According to the invention, the fault conditions of the power transmission line and the related devices are effectively analyzed and judged by integrating the monitoring data of all aspects, so that help can be provided for workers to quickly and comprehensively analyze the line problems, the analysis time is reduced, and the working efficiency is improved.
The above is a detailed description of an embodiment of the method for analyzing and processing a high-voltage transmission long-line fault tripping event according to the present invention, and the following is a detailed description of an embodiment of the system for analyzing and processing a high-voltage transmission long-line fault tripping event according to the present invention.
The embodiment provides a high-voltage transmission long-line fault tripping event analysis and processing system which is formed by a power grid dispatching primary system (EMS energy management system), a production management system, intelligent online monitoring data, lightning system data, unmanned aerial vehicle inspection data and the like in a comprehensive mode.
As shown in fig. 7, the analysis processing system of the present embodiment includes: the system comprises a fault starting module, a fault distinguishing module, a forced transmission judging module and a fault reporting module.
The fault starting module is used for starting the system through remote signaling and telemetry data acquired by a primary power grid dispatching system (EMS energy management system) after a line switching action occurs.
The fault distinguishing module firstly judges whether the fault distinguishing module is manual operation work or actual fault, the judging mode is that the working task and the operating task are obtained, whether the action condition is normal or abnormal is further confirmed, the judgment is direct finished if the action condition is normal, the judgment is abnormal, the state of a line is confirmed through an energy management system, if the line is in a closing state, the reclosing is successful after the line fault is judged, partial information is extracted, and the information enters the fault reporting module and comprises fault type, reclosing action condition and other conventional information. If the line state is the brake separating position, judging that the reclosing is unsuccessful, and entering a forced delivery judging module.
The forced delivery judging module comprises a logic judging unit, an external influence judging unit, an internal influence judging unit and an equipment judging unit. The concrete description is as follows:
the forced transmission judging unit is mainly used for judging whether a relay protection device, a safety automatic device and a wave recording device operate correctly or not under the condition of a fault, establishing a time axis by acquiring action information and relevant time marks, judging whether the action condition is correct or not through a primary equipment wiring diagram and action logic, for example, as shown in a line action wave recording diagram 1, extracting time mark data, performing time conversion, remapping the time mark data onto a new time axis, and performing comparative analysis.
The time change rule is as follows: fy (t) = f (0) + f0 (t) + f (yz), where fy (t) is the remapping time axis, f (0) is the actual time to start recording, f0 (t) is the relative time recorded by the recording or relay device, and f (yz) is the correction parameter for each device.
And the action waveforms of all the monitoring devices are placed on the same time axis to carry out logic and peak value judgment, if the action is wrong, the equipment is judged to be in misoperation or refused to operate, and the equipment is immediately reported to a reporting module to carry out equipment maintenance. If the action is correct, the external influence is entered into an external influence judging unit, and the external influence is judged firstly because the external influence accounts for most of all accident events for the line.
Corresponding environmental parameters such as lightning systems, unmanned aerial vehicle patrol results and the like need to be obtained, and whether the influence of external reasons is caused or not is further judged by obtaining the information and corresponding actual time scales. And whether the external influence is thunder or external hanging objects, whether the fault disappears and the like are judged. For example, whether there are external factors such as lightning loss and obstacles near the fault point, for example, the query result of a certain lightning system is centered on the XX station in the lightning monitoring system, and the radius is x 1 XX in Km, XX day XX is divided into a central front-back interval x 2 min, finding out the occurrence of lightning x in the area 3 Sub (thunderstorm frequency) and XX in XX day XX has a lightning current of x in 220kVXX station 4 kA lightning strike (lightning strike size).
The unmanned aerial vehicle system judges the system fault caused by the barrier through image recognition and other methods by acquiring images near the fault point for multiple times. For example, the stored normal image is compared with the recorded image when the fault occurs, whether an abnormal object exists is analyzed, and then the stored normal image is compared with the recorded image after the fault, so that whether the abnormal object still exists is judged. And feeds back the results to the fault reporting module. The external factors of thunder and lightning are transient faults, and internal factors such as hanging objects and the like can exist for a long time, so that judgment is needed to provide guiding opinions for forced delivery.
The image recognition method is based on unmanned aerial vehicle position information, shooting angle information and shooting parameter information to comprehensively perform image recognition. Under the condition that the shooting parameter information is the same, the six-degree-of-freedom system comprises the following components:
Figure 479282DEST_PATH_IMAGE035
and comparing the shot picture with historical data, and analyzing and identifying the fault object.
The correlation calculation and judgment method is to consider the lightning strike time, frequency and maximum lightning current data to carry out comprehensive judgment:
wherein,
Figure 301744DEST_PATH_IMAGE018
indicating an obstruction factor, and in the presence of an obstruction,
Figure 631095DEST_PATH_IMAGE019
that is, in the case of an obstacle existing in the line, the correlation between the line fault and the obstacle factor is 1 (the correlation value can be adjusted according to the actual situation, and is only set to be 1 for convenient comparison in the subsequent steps);
Figure 892312DEST_PATH_IMAGE020
indicating atmospheric factors, mainly related to lightning strike conditions near the points of obstruction.
The correlation calculation formula considering the atmospheric factors is specifically as follows:
Figure 561190DEST_PATH_IMAGE021
wherein
Figure 616871DEST_PATH_IMAGE003
、
Figure 433517DEST_PATH_IMAGE004
、
Figure 498425DEST_PATH_IMAGE005
、
Figure 21810DEST_PATH_IMAGE006
、
Figure 265971DEST_PATH_IMAGE015
Respectively a position factor, a time factor, a frequency factor, a size factor and a correction factor,
Figure 569913DEST_PATH_IMAGE007
、
Figure 110616DEST_PATH_IMAGE008
、
Figure 550824DEST_PATH_IMAGE009
、
Figure 213887DEST_PATH_IMAGE010
the area size, the time interval, the lightning falling frequency and the lightning falling size are respectively. Wherein
Figure 739546DEST_PATH_IMAGE022
The specific data can be set according to historical data, wherein
Figure 83940DEST_PATH_IMAGE003
、
Figure 378655DEST_PATH_IMAGE004
Fixed, both set to 0.25.
Figure 212619DEST_PATH_IMAGE005
、
Figure 163257DEST_PATH_IMAGE006
、
Figure 108079DEST_PATH_IMAGE015
When a high value appears, the specific way of increasing the coefficient can be obtained by comparison as follows:
taking 50 historical data, wherein the average value of the lightning falling frequency and the size of 50 lightning falling frequency is
Figure 522880DEST_PATH_IMAGE023
Coefficient mean of
Figure 527745DEST_PATH_IMAGE024
The adjustment is as follows:
Figure 965680DEST_PATH_IMAGE036
Figure 714193DEST_PATH_IMAGE037
Figure 983500DEST_PATH_IMAGE027
in which
Figure 96950DEST_PATH_IMAGE028
The results were ranked 50 times.
Figure 84498DEST_PATH_IMAGE011
For the correlation of the fault ranging with the location factor,
Figure 371122DEST_PATH_IMAGE012
for locating faultsThe correlation with the time factor is such that,
Figure 760515DEST_PATH_IMAGE013
is composed of
Figure 779287DEST_PATH_IMAGE007
The correlation of the number of occurrences over the area,
Figure 254131DEST_PATH_IMAGE014
is composed of
Figure 350306DEST_PATH_IMAGE007
Correlation of the size of landfall within the area.
Figure 531888DEST_PATH_IMAGE038
L represents the result of the recording ranging,
Figure 49457DEST_PATH_IMAGE030
for the total number of landings within the difference range,
Figure 746018DEST_PATH_IMAGE031
is the total lightning current within the difference range of the lightning current and the lightning current.
If there is a correlation between the motion range and the external factors
Figure 312129DEST_PATH_IMAGE002
When the current reaches 80% or more, the next stage is directly entered, for example, the distance between the front and rear ends is 3 minutes with the radius of 3km around the 110kVXX line as the center, 122 times of lightning falling in the area is found, and a lightning falling with the lightning current of 93.4kA occurs at 2.2km off-line. Consistent with a 10kVXX line tripping at the same time in the system,
Figure 676114DEST_PATH_IMAGE002
＞80%。
if there is a correlation between the motion range and the external factors
Figure 364584DEST_PATH_IMAGE002
And if the internal influence is within the qualified range, judging that the internal influence is small, but the data has large fluctuation and exceeds the qualified range, and directly reporting the data to a report module to judge the power failure maintenance. If there is a correlation between the motion range and the external factors
Figure 548441DEST_PATH_IMAGE002
And (4) between 50% and 80%, carrying out optimization judgment by combining local historical processing result data. And if the data is qualified, entering the next stage.
The third stage of forced delivery judgment is performed based on the state degree of one or two of the devices, and is performed according to the health degree of each device
Figure 918242DEST_PATH_IMAGE032
And degree of importance
Figure 136734DEST_PATH_IMAGE033
The classification is carried out into four levels I, II, III and IV.
Firstly, the numerical value is normalized, and then the classification rule is obtained as follows:
Figure 996106DEST_PATH_IMAGE039
and starting to check the fault conditions of the primary equipment and the secondary equipment of the line based on the grading rule. If the equipment has a fault condition, the health degree of the equipment is increased 1/4 on the original basis, so that the status degree of the equipment is improved, and the higher the grade is, the more important attention is needed.
In addition, the forced transmission judgment also comprises line stability judgment, whether a background abnormal signal exists, whether a history left signal exists and the like. Specifically, as shown in fig. 5, a primary condition, for example, simulates whether the dynamic stability and thermal stability of the line meet the requirements in the fault condition, the short-circuit resistance of the line can be calculated, the air pressure of the line switch is normal, etc., a secondary circuit condition, for example, there is no abnormal signal, no historical remaining signal, and an operating mechanism condition, for example, the hydraulic pressure is normal, the stored energy is normal, etc. For the equipment or the control loop with the fault, corresponding operation and maintenance work needs to be carried out according to the state degree rating and the operation and maintenance strategy and the implementation rule of the substation equipment. And after the judgment of the equipment judgment module is finished, the equipment judgment module finally reports the judgment result to the reporting module.
The report module is mainly used for immediately overhauling the abnormal condition report, providing specific reasons for the normal condition and providing strong power transmission suggestions.
It should be noted that the analysis processing system of this embodiment is mainly used for implementing the analysis processing method provided in the foregoing embodiment, and the specific settings of each module are subject to complete implementation of the method, which is not described herein again.
The above examples are only intended to illustrate the technical solution of the present invention, and not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.

Claims (6)

1. A method for analyzing and processing a fault tripping event of a high-voltage transmission long line is characterized by comprising the following steps:
the method for judging and processing the faults according to the action information and the time mark information of each monitoring device on the line specifically comprises the following steps:
acquiring action information and corresponding time mark information of each monitoring device on a line;
performing time conversion according to the time mark information of each device, judging the action information of each device after unifying the time mark information to the same time axis, and switching to maintenance operation if the monitoring device fails, wherein the time conversion is performed according to the following formula:
fy（t）=f（0）+f 0 （t）+f（yz）
wherein fy (t) is remappingTime axis of radiation, f (0) is the actual time at which recording is initiated, f 0 (t) is the relative time of each monitoring device, and f (yz) is the correction parameter of each monitoring device;
if all the monitoring devices on the line have no faults, continuing the subsequent steps;
acquiring environmental parameters of the line, and calculating the correlation between the line fault and external influence factors by using a correlation calculation method;
comparing the calculated correlation with a preset external influence threshold and an internal influence threshold, determining influence factors causing the line fault according to a comparison result, wherein the influence factors comprise the external influence factors and the internal influence factors, and extracting historical data to further determine and process the influence factors of the line fault;
and fault judgment and processing are carried out on the line equipment, the line control loop and the background signal based on the health degree of the first line equipment and the second line equipment.
2. The method according to claim 1, wherein the environmental parameters specifically include:
the image data of the fault point when the line has a fault, the historical image data of the fault point and the lightning stroke data of the fault point.
3. The method for analyzing and processing the tripping event of the high-voltage transmission long line fault according to claim 2, wherein the correlation between the line fault and the external influence factor is calculated by using a correlation calculation method, which specifically comprises the following steps:
constructing a correlation calculation formula considering barrier factors and atmospheric factors, wherein the correlation calculation formula specifically comprises the following steps:
Figure DEST_PATH_IMAGE001
in the formula,
Figure 457339DEST_PATH_IMAGE002
indicating a correlation, x0 is an influencing factor, x0=0 indicates an obstacle factor, x0=1 indicates an atmospheric factor,
Figure 598470DEST_PATH_IMAGE003
、
Figure 909497DEST_PATH_IMAGE004
、
Figure 681144DEST_PATH_IMAGE005
、
Figure 694099DEST_PATH_IMAGE006
respectively a position factor, a time factor, a frequency factor and a size factor,
Figure 389654DEST_PATH_IMAGE007
、
Figure 804455DEST_PATH_IMAGE008
、
Figure 560052DEST_PATH_IMAGE009
、
Figure 60304DEST_PATH_IMAGE010
respectively area, time, number of landfall and size of landfall,
Figure 480921DEST_PATH_IMAGE011
for the correlation of the fault ranging with the location factor,
Figure 763610DEST_PATH_IMAGE012
for the correlation of the fault ranging with the time factor,
Figure 939376DEST_PATH_IMAGE013
is composed of
Figure 677656DEST_PATH_IMAGE007
The correlation of the number of occurrences over the area,
Figure 901964DEST_PATH_IMAGE014
is composed of
Figure 25778DEST_PATH_IMAGE007
The correlation of the size of the landmine within the area,
Figure 123178DEST_PATH_IMAGE015
represents a correction coefficient;
determining whether the fault point has an obstacle or not by using the image data of the fault point when the line has a fault and the historical image data of the fault point, and if so, determining according to the image data of the fault point
Figure 598022DEST_PATH_IMAGE016
The temporal correlation calculation formula determines the correlation under the current situation, otherwise, the subsequent steps are continued;
lightning strike data utilization based on the fault point
Figure DEST_PATH_IMAGE017
The temporal correlation calculation formula calculates the correlation in the current case.
4. A system for analyzing and processing a high voltage transmission long line fault trip event, comprising: a forced delivery judging module;
the forced transmission judging module comprises a logic judging unit, a fault influence judging unit and an equipment judging unit;
the logic judgment unit is used for performing fault judgment and processing according to the action information and the time scale information of each monitoring device on the line, and is specifically used for:
acquiring action information and corresponding time mark information of each monitoring device on a line;
performing time conversion according to the time mark information of each device, judging the action information of each device after unifying the time mark information to the same time axis, and switching to maintenance operation if the monitoring device fails, wherein the time conversion is performed according to the following formula:
fy（t）=f（0）+f 0 （t）+f（yz）
where fy (t) is the remapped time axis, f (0) is the actual time to start recording, f (0) is the time to start recording 0 (t) is the relative time of each monitoring device, and f (yz) is the correction parameter of each monitoring device;
if all the monitoring devices on the line have no faults, continuing the subsequent steps;
the fault influence judging unit is used for acquiring environmental parameters of the line and calculating the correlation between the line fault and external influence factors by using a correlation calculation method; the correlation calculation module is also used for comparing the calculated correlation with a preset external influence threshold and an internal influence threshold, determining influence factors causing the line fault according to a comparison result, wherein the influence factors comprise the external influence factors and the internal influence factors, and extracting historical data to further determine and process the influence factors of the line fault;
the equipment judgment unit is used for carrying out fault judgment and processing on the line equipment, the line control loop and the background signal based on the health degree of the line I and the secondary equipment.
5. The system according to claim 4, wherein the environmental parameters specifically include:
the image data of the fault point when the line has a fault, the historical image data of the fault point and the lightning stroke data of the fault point.
6. The system according to claim 5, wherein the fault impact determination unit comprises an external impact determination unit, and the external impact determination unit is specifically configured to:
constructing a correlation calculation formula considering barrier factors and atmospheric factors, wherein the correlation calculation formula specifically comprises the following steps:
Figure 501387DEST_PATH_IMAGE018
in the formula,
Figure 682970DEST_PATH_IMAGE002
indicating a correlation, x0 is an influencing factor, x0=0 indicates an obstacle factor, x0=1 indicates an atmospheric factor,
Figure 682762DEST_PATH_IMAGE003
、
Figure 644902DEST_PATH_IMAGE004
、
Figure 211012DEST_PATH_IMAGE005
、
Figure 325730DEST_PATH_IMAGE006
respectively a position factor, a time factor, a frequency factor and a size factor,
Figure 748621DEST_PATH_IMAGE007
、
Figure 948789DEST_PATH_IMAGE008
、
Figure 380908DEST_PATH_IMAGE009
、
Figure 271503DEST_PATH_IMAGE010
respectively area, time, number of landings, size of landings,
Figure 881607DEST_PATH_IMAGE011
for the correlation of the fault ranging with the location factor,
Figure 552760DEST_PATH_IMAGE012
for the correlation of the fault ranging with the time factor,
Figure 559810DEST_PATH_IMAGE013
is composed of
Figure 570491DEST_PATH_IMAGE007
The correlation of the number of occurrences over the area,
Figure 600764DEST_PATH_IMAGE014
is composed of
Figure 509945DEST_PATH_IMAGE007
The correlation of the size of the landmine within the area,
Figure 283866DEST_PATH_IMAGE015
represents a correction coefficient;
determining whether the fault point has an obstacle or not by using the image data of the fault point when the line has a fault and the historical image data of the fault point, and if so, determining according to the image data of the fault point when the line has a fault and the historical image data of the fault point
Figure 149054DEST_PATH_IMAGE016
The temporal correlation calculation formula determines the correlation under the current condition, otherwise, the subsequent steps are continued;
lightning strike data utilization based on the fault point
Figure 100961DEST_PATH_IMAGE017
Calculating the correlation under the current condition by using a temporal correlation calculation formula;
and determining whether the line fault is caused by the external influence factor by using the correlation.
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