CN-122017384-A - Method and device for detecting running state of drop-out arrester on line

CN122017384ACN 122017384 ACN122017384 ACN 122017384ACN-122017384-A

Abstract

The invention discloses a method and a device for detecting the running state of a drop-out arrester on line, and relates to the detection technology of power distribution network equipment; the device comprises a composite insulating shell, a multi-dimensional sensor group, a data processing module, a Beidou positioning module, a non-explosive disengaging module, a communication alarm module and a solar-lithium battery power supply module, and realizes full-insulation packaging through a vacuum injection molding process. According to the method, the sensor group is used for collecting the operation electric parameters, the insulation state parameters, the environment parameters and the equipment attitude parameters in real time, and the insulation attenuation comprehensive index and the equipment action reliability index are calculated after the sensor drift, the time attenuation and the dynamic calibration of the environment temperature are fused, so that the insulation failure, the action mechanism fault and the short circuit fault are accurately judged. And during faults, through Beidou positioning and attitude parameter correction positions, risk grades are evaluated, a non-explosive separation threshold value is determined by fusing multiple factors, and explosion-free breaking and multi-level alarming are triggered. Real-time monitoring, accurate diagnosis, safe handling and high-efficiency operation and maintenance are realized.

Inventors

WEI LEI
HUANG WENHUA
YIN HUIYANG
LIU HONG
FENG CHUANHAO
CHENG LIANG
YU CHONGGUANG
JIANG QIHAO

Assignees

国网江西省电力有限公司都昌县供电分公司

Dates

Publication Date: 20260512
Application Date: 20251219

Claims (10)

1. The method for detecting the running state of the drop-out arrester on line is characterized by comprising the following steps of: S1, arranging a multi-dimensional sensor group of a fully insulated package, wherein the multi-dimensional sensor group comprises a current sensor, an insulation resistance sensor, a temperature and humidity sensor and an attitude sensor, and collecting operation electric parameters, insulation state parameters, environment influence parameters and equipment attitude parameter data of a lightning arrester in real time; s2, calibrating the data collected in the step S1, and performing data calibration based on a dynamic calibration formula integrating sensor drift, time attenuation and environmental temperature influence to obtain calibrated data; S3, calculating an insulation attenuation comprehensive index and an equipment action reliability index according to the calibrated data, and judging insulation failure and action reliability deficiency states according to preset thresholds respectively; S4, judging the fault type based on an insulation and action reliability evaluation result and a leakage current threshold value, starting a positioning module to acquire original coordinates, combining equipment attitude parameters to complete positioning correction, and evaluating a fault risk level through a fault spreading risk coefficient; And S5, calculating a non-explosive disengagement triggering threshold value by fusing rated short-circuit current, an insulation state and a fault risk level, triggering the action of the hot-melt type disengaging device when the short-circuit current reaches the threshold value, and dividing the multistage warning parallel animal networking platform according to the fault risk coefficient to push related information.
2. The method for detecting the operation state of the drop-out arrester in the on-line detection according to claim 1, wherein the step S2 performs data calibration based on a dynamic calibration formula integrating sensor drift, time attenuation and environmental temperature influence, and the calibration formula is as follows: In the formula, Is the calibrated data value; the method comprises the steps of (1) acquiring a value for the original of a sensor; Correcting a coefficient for sensor drift; The value of the time attenuation factor is positively correlated with the accumulated use duration of the sensor; accumulating the operation time length of the sensor, wherein the unit is a day; The value range is 0.005-0.02 for the environmental temperature correction coefficient; Is the real-time ambient temperature; the temperature is calibrated for a standard, and the fixed value is 25 ℃; To withstand the extreme temperatures of the equipment, the fixed value is 85 ℃.
3. The method for detecting the operation state of the drop-out arrester in an on-line detection manner according to claim 1, wherein the insulation attenuation integrated index in step S3 is as follows The calculation formula is as follows: In the formula, Is an insulation attenuation comprehensive index; is an insulation resistance value; An initial insulation resistance for the lightning arrester; To allow maximum leakage current; the value range of the environmental erosion factor is 0.01-0.05; Is the surface pollution degree; Is the ambient humidity; the value range is 1.2-2.5 for the current influence coefficient; Is the leakage current peak; the life loss coefficient is in a value range of 0.8-1.0; The service life of the lightning arrester is designed, and the unit is day; The operating time is accumulated for the arrester.
4. The method for detecting the operation state of a drop-out arrester in an on-line manner according to claim 1, wherein the equipment operation reliability index in step S3 is as follows The calculation formula is as follows: In the formula, The index value is equal to or more than 0.7, and is reliable, and if the index value is less than 0.7, the index value is judged to be insufficient in reliability; The value range is 0.01-0.03 for the attitude influence coefficient; The value range is 0.1-0.3 for the temperature sensitivity coefficient; The value range is 3-5 for the temperature decay index; Is the equipment tilt angle; Is the real-time ambient temperature; the temperature is calibrated for a standard, and the fixed value is 25 ℃; To withstand the extreme temperatures of the equipment, the fixed value is 85 ℃.
5. The method according to claim 1, wherein the step S4 of determining the fault type based on the insulation and operational reliability evaluation result and the leakage current threshold value specifically includes passing through a fault characteristic function Determining a fault type, the fault signature function The following are provided: In the formula, Is an insulation attenuation comprehensive index; For the insulation reliability threshold, the value is fixed to be 0.35, when When the insulation failure is judged; the index value is equal to or more than 0.7, and is reliable, and if the index value is less than 0.7, the index value is judged to be insufficient in reliability; Is the leakage current peak; To allow maximum leakage current.
6. The method for detecting the running state of the drop-out arrester in the on-line detection mode according to claim 5, wherein when the drop-out arrester is judged to be a non-0 type fault, a positioning module is started to collect original coordinates, combine with equipment attitude parameters to complete positioning correction, and calculate a fault spreading risk coefficient, and the positioning correction formula is as follows: In the formula, The corrected accurate longitude coordinates; the corrected precise latitude coordinate is obtained; positioning an original longitude coordinate for the Beidou; positioning an original latitude coordinate for the Beidou; for positioning error correction coefficient, the value range is taken ; The azimuth angle of the equipment is acquired by an attitude sensor; Is the equipment tilt angle; The fault spreading risk coefficient calculation formula is as follows: In the formula, A failure spreading risk coefficient of >1.2 is a high risk, 0.8< 1.2 is a medium risk, and < 0.8 is a low risk; The value range of the line association coefficient is 1.0-1.8; the value range is 0.02-0.05 for the humidity amplification factor; Is the leakage current peak; To allow maximum leakage current; Is the ambient humidity.
7. The method for detecting the operation state of the drop-out arrester in the on-line detection mode according to claim 1, wherein the step S5 is to calculate a non-explosive disengagement triggering threshold by fusing rated short-circuit current, insulation state and failure risk level, and the calculation formula is as follows: In the formula, A non-explosive disengagement triggering threshold value, and triggering disengagement action when the short-circuit current is more than or equal to the value; Rated short-circuit current for the lightning arrester; the value range is 0.5-1.0 for the insulating state influence weight; The value range is 0.8-1.5 for the risk grade weight; Is an insulation attenuation comprehensive index; Is a fault spreading risk factor.
8. The method for detecting the operation state of a drop-out arrester on line according to claim 7, wherein when the short-circuit current reaches The time-contact hot-melting type disconnector acts to safely disconnect the lightning arrester from the power grid, and meanwhile, the multistage warning parallel animal networking platform is divided according to the fault risk coefficient to push related information, and the method specifically comprises the following steps: triggering a primary alarm, namely, a platform real-time popup window, a short message and a telephone to inform operation and maintenance personnel to generate an optimal rush-repair path; triggering a secondary alarm, namely a platform popup window and a short message notice, and completing rush repair within 6 hours; and triggering three-level alarm, namely recording alarm information by the platform, and finishing inspection and verification within 24 hours.
9. An on-line detection drop-out arrester running state detection device, which is characterized by comprising: The composite insulating shell is internally provided with a sensor group, and comprises a current sensor, an insulating resistance sensor, a temperature and humidity sensor and an attitude sensor, and is used for executing parameter acquisition; The data processing module is integrated with the Internet of things card and the storage unit, is internally provided with an embedded chip and is used for executing dynamic calibration, insulation reliability evaluation and fault diagnosis calculation; The Beidou positioning module is buried in the lightning arrester and used for acquiring original positioning coordinates and executing positioning correction by matching with the data processing module; the non-explosive separation module comprises a low-temperature alloy fuse piece and a magnetic fluid optimizing fuse cavity, and is used for receiving a trigger signal of the data processing module to realize non-explosive breaking; The communication alarm module supports encrypted data transmission, establishes real-time connection with the platform of the Internet of things and executes multistage alarm linkage of the steps; and the power supply module is used for supplying power by adopting a solar panel and a lithium battery pack.
10. The device for detecting the running state of the drop-out arrester in the on-line detection mode according to claim 9, wherein the composite insulating shell is encapsulated in an all-insulating manner, and particularly, the conductive component is encapsulated through a vacuum injection molding process.

Description

Method and device for detecting running state of drop-out arrester on line Technical Field The invention relates to a power distribution network equipment detection technology, in particular to a method and a device for detecting the running state of a drop-out arrester on line. Background The drop-out arrester is used as key protection equipment in a power distribution network system, is widely applied to 10kV-35kV lines, and has the core functions of avoiding damage of the lines and rear-end power equipment due to overvoltage impact by discharging lightning overvoltage and operating overvoltage energy, so that continuous and stable operation of a power grid is ensured. With the expansion of the coverage range of the distribution network and the complicating of the running environment, the lightning arrester is in outdoor severe conditions for a long time, faults such as insulation aging, abnormal leakage current, jamming of an action mechanism and the like are easy to occur, and if the faults are not detected and treated in time, line tripping, equipment burning and even large-area power failure accidents can be caused, so that serious threat is formed to the safe operation and maintenance of the power system. Currently, the operation state detection of the lightning arrester is mainly divided into two types, namely off-line detection and on-line detection. The traditional offline detection relies on manual regular inspection, and parameters such as insulation resistance, leakage current and the like are measured through a portable instrument, so that the labor intensity is high, the detection efficiency is low, the problem of 'inspection clearance fault missed judgment' exists, sudden faults of equipment cannot be captured in real time, meanwhile, the manual detection is greatly influenced by environmental conditions and operation level, the data consistency is poor, and the long-term running state of the equipment is difficult to accurately reflect. The existing online detection technology still has the technical defects that firstly, a data calibration mechanism is imperfect, most schemes only consider single factors of environmental temperature, neglect influence of sensor drift and long-term running time attenuation on collected data, cause larger error of original data and influence accuracy of subsequent state evaluation, secondly, fault diagnosis dimension is single, the existing online detection technology is mainly used for monitoring dominant faults such as short-circuit faults and the like, effective discrimination of hidden faults such as insulation attenuation and reliability of an action mechanism is lacked, misjudgment or misjudgment of faults is easy to occur, thirdly, fault positioning precision is insufficient, original coordinate output of a positioning module is only relied, posture parameters of equipment are not combined for correction, fault positions are difficult to be accurately locked, operation and maintenance investigation difficulty is increased, fourthly, a separation and alarm mechanism is unreasonable, a traditional explosion type detacher has explosion risk, secondary potential safety hazards are easy to be caused, an alarm mode is single prompt, response priority is not divided according to fault risk grades, operation and maintenance resource allocation is unreasonable, fault efficiency is low, and power supply mode suitability is poor, part of online detection devices is powered by a power grid, and long-term running stability is not influenced under a long-term condition. In conclusion, the existing detection technology has the defects in the aspects of data accuracy, fault diagnosis comprehensiveness, positioning reliability, safety separation, operation and maintenance response efficiency and the like, and cannot meet the core requirements of a power distribution network on 'real-time monitoring, accurate diagnosis, safety treatment and high-efficiency operation and maintenance' of a lightning arrester. Therefore, research and development of a multidimensional sensing, accurate calibration, comprehensive diagnosis, safety and reliability on-line detection drop-out arrester running state detection system becomes a technical problem to be solved in the field of electric power operation and maintenance. Disclosure of Invention The invention aims to provide a method and a device for detecting the running state of a drop-out arrester on line, which are used for acquiring relevant parameters in real time through a multi-dimensional sensor group of a fully-insulated package, calculating an insulation attenuation comprehensive index and an equipment action reliability index after dynamic calibration to judge the fault type, synchronously finishing fault position correction by means of a Beidou positioning module and evaluating the fault spreading risk level, finally fusing multiple factors to calculate a non-explosive separation triggering threshold value, triggering a hot