CN103323771A - High-voltage breaker mechanical characteristic fault probability monitoring method and system based on on-line monitoring - Google Patents

High-voltage breaker mechanical characteristic fault probability monitoring method and system based on on-line monitoring Download PDF

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CN103323771A
CN103323771A CN2013102261285A CN201310226128A CN103323771A CN 103323771 A CN103323771 A CN 103323771A CN 2013102261285 A CN2013102261285 A CN 2013102261285A CN 201310226128 A CN201310226128 A CN 201310226128A CN 103323771 A CN103323771 A CN 103323771A
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probability
failure
phase
line monitoring
energy storage
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CN103323771B (en
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王成友
张勇
程新功
刘灿东
郭兆静
任宏伟
宗西举
郝朝阳
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SHANDONG TAIKAI ELECTRIC AUTOMATION CO Ltd
University of Jinan
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SHANDONG TAIKAI ELECTRIC AUTOMATION CO Ltd
University of Jinan
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Abstract

The invention discloses a high-voltage breaker mechanical characteristic fault probability monitoring method and system based on on-line monitoring. The method comprises the steps that (1) the mechanical characteristic curve of the breaker is read by an on-line monitoring system under the normal circumstance of the breaker; (2) when the breaker is put into operation in the field, the mechanical characteristic curve of the breaker is read by the on-line monitoring system under the operation circumstance of the breaker; (3) fault probabilities, of energy storage motor fault probability, tripping fault probability and closing fault probability, showed by all characteristic values are respectively calculated by the on-line monitoring system; (4) the total on-line monitoring fault probability, namely, the sum of the fault probabilities worked out according to the third step: F=FM+FF+FH, of the breaker is calculated; (5) whether alarming should be conducted or not is judged by the on-line monitoring system according to the fault probabilities, and a fault alarming signal is generated by the on-line monitoring system when the fault probability is equal to or larger than an threaded alarming value and is not generated by the on-line monitoring system when the fault probability is smaller than the threaded alarming value.

Description

Mechanical characteristic of high-voltage circuit breaker probability of failure monitoring method and system based on on-line monitoring
Technical field
The present invention is specifically related to a kind of mechanical characteristic of high-voltage circuit breaker probability of failure monitoring method and system based on on-line monitoring.
Background technology
Isolating switch plays vital effect in electrical network, it is the key equipment that electric system is control effectively, along with society and expanding economy, security, reliability to electric system are had higher requirement, but in confession, distribution system, because the unplanned power outage that circuit breaker failure causes accounts for more than 60% of electric system power outage total amount, be one of principal element that affects power system security, reliability.The mechanical characteristic of high-voltage circuit breaker fault sums up can be divided three classes (not comprising the insulation system fault):
1) accumulator system fault comprises stored energy mechanism fault and energy storage motor fault.
2) the combined floodgate system failure comprises that mistake is closed, refused to close or clamping stagnation (switching-on mechanism fault, combined floodgate secondary circuit failure), contact abrasion are excessive, closing time or velocity sag, three-phase same period etc. not.
3) brake-dividing system fault comprises mistake minute, refuses minute or clamping stagnation (brake separating mechanism fault, separating brake secondary circuit failure), opening time or velocity sag, three-phase same period etc. not.
The reliability that improves isolating switch manufactures and designs the link except strengthening, the Forecasting Methodology of studying mechanical characteristic failures also is very necessary, yet in traditional transformer station field, owing to there not being enough breaker mechanic property Monitoring Data, therefore can't carry out effective failure prediction, it is the main counter-measures of Utilities Electric Co.s at different levels that isolating switch is carried out scheduled overhaul.In recent years, construction along with intelligent grid, transformer station has realized intellectuality, the primary equipment on-line monitoring system is widely applied in intelligent substation, wherein the breaker mechanic property on-Line Monitor Device can gather the data such as energy storage motor current curve, divide-shut brake coil current curve, divide-shut brake stroke curve, and this also provides possibility for the breaker mechanic property failure prediction.Application along with on-line monitoring system, people have carried out various algorithm researches to the mechanical property data that obtain, comprise the D-S evidence theory analysis of the EMD of isolating switch vibrations sound wave and SVM Algorithm Analysis, mechanical property data etc., these methods mainly are that the mechanical property data after fault is occured are studied, and do not give be out of order early stage judgement and early warning.
Summary of the invention
The shortcoming that exists in order to solve prior art the invention provides a kind of mechanical characteristic of high-voltage circuit breaker probability of failure monitoring method and system based on on-line monitoring.
For achieving the above object, the present invention has adopted following technical scheme:
Mechanical characteristic of high-voltage circuit breaker probability of failure monitoring method based on on-line monitoring may further comprise the steps:
1) during the isolating switch factory inspection, on-line monitoring system reads isolating switch mechanical characteristic under normal circumstances, and calculating normal eigenvalues, comprise that energy storage motor starts time-delay, energy storage motor current peak, mean value, energy storage time, divide-shut brake coil current mean value, divide-shut brake coil current duration, divide-shut brake stroke, three-phase separate combined floodgate stroke startup maximum time difference, divide-shut brake speed, normal eigenvalues is stored in real-time data base and the file system.
When 2) put into operation in the isolating switch scene, on-line monitoring system reads the mechanical characteristic in the isolating switch action situation in real time, each eigenwert of on-line monitoring when calculating the isolating switch action comprises that energy storage motor starts time-delay, energy storage motor current peak, mean value, energy storage time, divide-shut brake coil current mean value, divide-shut brake coil current peak value number, divide-shut brake coil current duration, divide-shut brake stroke, three-phase separate combined floodgate stroke startup maximum time difference, divide-shut brake speed.
3) on-line monitoring system calculates respectively the probability of failure that each eigenwert characterizes, and comprises energy storage motor probability of failure, separating brake probability of failure, Closing fault probability.
4) calculate isolating switch on-line monitoring total failare probability, isolating switch on-line monitoring total failare probability is the probability of failure sum that step (3) calculates:
F=F M+F F+F H
Wherein: F is isolating switch on-line monitoring total failare probability, F M, F F, F HBe respectively the probability of failure of energy storage motor, separating brake, combined floodgate.
5) on-line monitoring system is according to step 4) probability of failure that obtains size, judge whether to report to the police; When probability of failure 〉=alarm threshold value, then on-line monitoring system produces failure alarm signal, and when probability of failure<alarm threshold value, then on-line monitoring system does not produce failure alarm signal.
The described energy storage motor probability of failure of step (3) comprises A phase, B phase, C phase energy storage motor probability of failure, the wherein monitoring method of single-phase energy storage motor probability of failure:
F MX = { { ( T MS - T MSD - 2 ) × 0.3 } + 1 + { ( | T MA - T MAD | ) × 0.1 } + 1
+ { ( | I MA - I MAD | - I MAD / 4 ) } + 1 } + 1
Wherein: the desirable A of X, B, C, represent respectively the energy storage motor probability of failure of A phase, B phase, C phase, get energy storage motor resultant fault probability and be:
F M=MAX{F MA,F MB,F MC}
Wherein: F MBe energy storage motor resultant fault probability, F MA, F MB, F MCBe respectively the energy storage motor probability of failure of A, B, C three-phase;
The described separating brake probability of failure of step (3) comprises A phase, B phase, C phase separating brake probability of failure, the wherein monitoring method of single-phase separating brake probability of failure:
F FX = { { | N FP - 2 | } + 1 + { ( | I FA - I FAD | - I FAD / 3 ) } + 1 + { ( T FT - 1.3 T FTD ) × 0.1 } + 1
+ { ( T FS - 1.3 T FSD ) × 0.1 } + 1 + { ( S FAD - 1.2 S FA ) × 0.5 } + 1 } + 1
Wherein: the desirable A of X, B, C, represent respectively the separating brake probability of failure of A phase, B phase, C phase, get separating brake resultant fault probability and be:
F F = MAX { F FA , F FB , F FC } + { ( Δ T F max - 6 ) × 0.2 } + 1
Wherein: F FBe separating brake resultant fault probability, F FA, F FB, F FCBe respectively the separating brake probability of failure of A, B, C three-phase.
The described Closing fault probability of step (3) comprises A phase, B phase, C close a floodgate mutually probability of failure, the wherein monitoring method of single phase closing probability of failure:
The single phase closing probability of failure is:
T HX = { { | N HP - 2 | } + 1 + { ( | I HA - I HAD | - I HAD / 3 ) } + 1 + { ( T HT - 1.3 T HTD ) × 0.1 } + 1
( T HS - 1.3 T HSD ) × } + 1 + { ( S HAD - 1.2 S HA ) × } + 1 } + 1
Wherein: the desirable A of X, B, C, represent respectively the Closing fault probability of A phase, B phase, C phase, get combined floodgate resultant fault probability and be:
F H = MAX { F HA , F HB , F HC } + { ( Δ T H max - 6 ) × 0.2 } + 1
Wherein: F HBe combined floodgate resultant fault probability, F HA, F HB, F HCBe respectively the Closing fault probability of A, B, C three-phase.
Monitoring system based on the mechanical characteristic of high-voltage circuit breaker probability of failure of on-line monitoring, comprise the energy storage motor sensor, combined floodgate sensor, separating brake sensor, the stroke sensor that gather the primary cut-out signal, and described energy storage motor sensor, combined floodgate sensor, separating brake sensor and stroke sensor all link to each other with mechanical feature detection device, and described mechanical feature detection device links to each other with computer supervisory control system.
What described energy storage motor sensor, combined floodgate sensor, separating brake sensor all adopted is current sensor, and model is HEC15-LX (V5, ± 12).
Described stroke sensor is angular displacement sensor, model: KSJ-1-360-V-05.
The beneficial effect that the present invention produces is: by the Eigenvalues analysis to the mechanical characteristic of high-voltage circuit breaker online monitoring data, provide the probability of failure (between the span 0~1) of mechanical characteristic of high-voltage circuit breaker, thereby can grasp in real time the isolating switch operating mode, the possible breakdown of prediction isolating switch, formulate rational turnaround plan, for the safe and reliable operation of electric system provides a kind of new technological means, thereby has important using value.The present invention does not relate to complicated theoretical formula, has obtained the scale application.
Description of drawings
Fig. 1 is the experimental system block diagram;
Fig. 2 is the normal energy storage motor current curve of isolating switch (A phase);
Fig. 3 is the normal switching winding current curve of isolating switch (A phase);
Fig. 4 is the normal separating brake stroke curve of isolating switch (A phase);
Fig. 5 is the normal closing coil current curve of isolating switch (A phase);
Fig. 6 is the isolating switch stroke curve (A phase) that closes a floodgate normally;
Fig. 7 is fault simulation experiment breaker energy storage current of electric curve (A phase);
Fig. 8 is fault simulation experiment breaker open operation coil current curve (A phase);
Fig. 9 is fault simulation experiment breaker open operation stroke curve (A phase);
Figure 10 is fault simulation experiment breaker closing coil current curve (A phase);
Figure 11 is fault simulation experiment breaker closing stroke curve (A phase).
Embodiment
The present invention is described in detail below in conjunction with accompanying drawing:
Fig. 1 is the experimental system block diagram, and wherein: (Thailand opens electric, model: ZF16-252) rated voltage is that 252KV, specified KA Rms are 50KA to the hydraulic high-pressure isolating switch; Fuser sensor is the three-phase independent input; (Thailand opens electric embedded mechanical property monitoring device, model: IEM-610) have the functions such as data acquisition, demonstration, wave file storage (COMTRADE form), communication (DL/T860 standard), alarm.
Based on the mechanical characteristic of high-voltage circuit breaker probability of failure monitoring method of on-line monitoring, method for expressing: establish for expression formula given f (x 1x 2...) time value be F, and:
Figure BDA00003320690500041
, then remember f (x 1x 2...) be
Figure BDA00003320690500042
Below explanation includes A phase, B phase, C phase.
1) read under normal circumstances on-line monitoring curve of isolating switch (see Fig. 2~Fig. 6), calculate breaker mechanic property on-line monitoring normal eigenvalues such as following table 3:
Figure BDA00003320690500043
Figure BDA00003320690500051
Table 3: experiment breaker mechanic property on-line monitoring normal eigenvalues
2) under the operation monitoring state (this example is under the fault simulation state: simulate leakage of oil by adjusting oil-pressure shut-off switch and safety valve), the mechanical property on-line monitoring curve when reading in real time the isolating switch action (is seen Fig. 7~Figure 11).
The on-line monitoring eigenwert sees Table 4 when 3) calculating the isolating switch action.
Figure BDA00003320690500052
Figure BDA00003320690500061
Table 4: experiment breaker mechanic property on-line monitoring eigenwert under the fault simulation state
4) mechanical property on-line monitoring probability of failure calculates.
A): energy storage motor on-line monitoring probability of failure calculates.Energy storage motor on-line monitoring eigenwert has: electric motor starting time-delay T MS(take the divide-shut brake coil current as reference point), motor average current I MA, motor energy storage time T MAFor specific energy storage motor, I MAShould be within rational scope, the too small reflection motor of numerical value electric loop fault, numerical value is excessive to have infringement or scaling loss to motor coil, same because T MS, T MABe subjected to the stored energy mechanism switch to control T MS, T MANumerical value transfinites, and has reflected accumulator system/operating mechanism fault.
Single-phase energy storage motor probability of failure is:
F MX = { { ( T MS - T MSD - 2 ) × 0.3 } + 1 + { ( | T MA - T MAD | ) × 0.1 } + 1
+ { ( | I MA - I MAD | - I MAD / 4 ) } + 1 } + 1
Wherein: the desirable A of X, B, C, represent respectively the energy storage motor probability of failure of A phase, B phase, C phase, get energy storage motor resultant fault probability and be:
F M=MAX{F MA,F MB,F MC}
Wherein: F MBe energy storage motor resultant fault probability, F MA, F MB, F MCBe respectively the energy storage motor probability of failure of A, B, C three-phase.
B) separating brake on-line monitoring probability of failure calculates.Separating brake on-line monitoring eigenwert has: separating brake current peak quantity N FP, separating brake current average I FA, separating brake current duration T FA, separating brake stroke starting time-delay T FS(to detect the switching winding electric current as starting point), separating brake average velocity S FA(or opening time).N under normal circumstances FP=2, if N FP≠ 2 have reflected the magnetic bobbin core fault; I FAThe too small reflection separating brake of numerical value electric loop fault, numerical value is excessive to have infringement or scaling loss to switching winding; T FAThe excessive reflection separating brake of numerical value numerical value auxiliary contact fault or refuse to jump; T FSNumerical value is excessive have been reflected accumulator system/operating mechanism clamping stagnation or has refused jumping, S FAToo small accumulator system/operating mechanism the clamping stagnation that reflected of numerical value.
Single-phase separating brake probability of failure is (curvilinear characteristic when formula has been considered to break large electric current):
F FX = { { | N FP - 2 | } + 1 + { ( | I FA - I FAD | - I FAD / 3 ) } + 1 + { ( T FT - 1.3 T FTD ) × 0.1 } + 1
+ { ( T FS - 1.3 T FSD ) × 0.1 } + 1 + { ( S FAD - 1.2 S FA ) × 0.5 } + 1 } + 1
Wherein: the desirable A of X, B, C, represent respectively the separating brake probability of failure of A phase, B phase, C phase, get the separating brake resultant fault several
Rate is:
F F = MAX { F FA , F FB , F FC } + { ( Δ T F max - 6 ) × 0.2 } + 1
Wherein: F FBe separating brake resultant fault probability, F FA, F FB, F FCBe respectively the separating brake probability of failure of A, B, C three-phase.
C) combined floodgate on-line monitoring probability of failure calculates.Combined floodgate on-line monitoring eigenwert has: switching current number of peaks N HP, switching current mean value I HA, the switching current duration T HA, combined floodgate stroke starting time-delay T HS(to detect the closing coil electric current as starting point), combined floodgate average velocity S HA(or closing time).N under normal circumstances HP=2, if N HP≠ 2 have reflected the magnetic bobbin core fault; I HAThe too small reflection combined floodgate of numerical value electric loop fault, numerical value is excessive to have infringement or scaling loss to closing coil; T HAThe excessive reflection combined floodgate of numerical value numerical value auxiliary contact fault or refuse to close; T HSNumerical value is excessive have been reflected accumulator system/operating mechanism clamping stagnation or has refused to close S HAToo small accumulator system/operating mechanism the clamping stagnation that reflected of numerical value.
The single phase closing probability of failure is:
F HX = { { | N HP - 2 | } + 1 + { ( | I HA - I HAD | - I HAD / 3 ) } + 1 + { ( T HT - 1.3 T HTD ) × 0.1 } + 1
( T HS - 1.3 T HSD ) × } + 1 + { ( S HAD - 1.2 S HA ) × } + 1 } + 1
Wherein: the desirable A of X, B, C, represent respectively the Closing fault probability of A phase, B phase, C phase, get combined floodgate resultant fault probability and be:
F H = MAX { F HA , F HB , F HC } + { ( Δ T H max - 6 ) × 0.2 } + 1
Wherein: F HBe combined floodgate resultant fault probability, F HA, F HB, F HCBe respectively the Closing fault probability of A, B, C three-phase.
D) isolating switch on-line monitoring total failare probability calculates.Isolating switch on-line monitoring total failare probability is above-mentioned 1), 2), 3) the probability of failure sum that calculates of step:
F=F M+F F+F H
Wherein: F is isolating switch on-line monitoring total failare probability, F M, F F, F HBe respectively the probability of failure of energy storage motor, separating brake, combined floodgate.
The monitoring method of bringing into after the concrete data is as follows:
A): energy storage motor on-line monitoring probability of failure calculates:
F MA = { { ( 0.5 - 0.5 - 2 ) × 0.3 } + 1 + { ( | 27.2 - 24.6 | ) × 0.1 } + 1
+ { ( | 1.15 - 1.18 | - 1.18 / 4 ) } + 1 } + 1
= 0.26
F MB = { { ( 0.5 - 0.5 - 2 ) × 0.3 } + 1 + { ( | 27.8 - 25 | ) × 0.1 } + 1
+ { ( | 1.16 - 1.19 | - 1.19 / 4 ) } + 1 } + 1
= 0.28
F MC = { { ( 0.5 - 0.5 - 2 ) × 0.3 } + 1 + { ( | 27.5 - 24.1 | ) × 0.1 } + 1
+ { ( | 1.2 - 1.22 | - 1.18 / 4 ) } + 1 } + 1
= 0.34
F M=MAX{0.26,0.28,0.34}=0.34
B) separating brake on-line monitoring probability of failure calculates:
F FA = { { | 2 - 2 | } + 1 + { ( | 0.7 - 0.75 | - 0.75 / 3 ) } + 1 + { ( 20 - 1.3 × 19 ) × 0.1 } + 1
+ { ( 10 - 1.3 × 10 ) × 0.1 } + 1 + { ( 9.2 - 1.2 × 8.6 ) × 0.5 } + 1 } + 1
+ { ( 10 - 1.3 × 11 ) × 0.1 } + 1 + { ( 9 . 1 - 1.2 × 8 . 5 ) × 0.5 } + 1 } + 1
= 0
F FC = { { | 2 - 2 | } + 1 + { ( | 0 . 69 - 0.79 | - 0.79 / 3 ) } + 1 + { ( 20 - 1.3 × 20 ) × 0.1 } + 1
+ { ( 11 - 1.3 × 11 ) × 0.1 } + 1 + { ( 9 . 0 - 1.2 × 8 . 3 ) × 0.5 } + 1 } + 1
= 0
T F = MAX { 0,0,0 } + { ( 3 - 6 ) × 0.2 } + 1 = 0
C) combined floodgate on-line monitoring probability of failure calculates:
F HA = { { | 2 - 2 | } + 1 + { ( | 0 . 85 - 0 . 88 | - 0 . 88 / 3 ) } + 1 + { ( 4 4 - 1.3 × 40 ) × 0.1 } + 1
+ { ( 8 - 1.3 × 7 ) × 0.1 } + 1 + { ( 4 . 2 - 1.2 × 3 . 3 ) × 0.5 } + 1 } + 1
= 0.12
F HA = { { | 2 - 2 | } + 1 + { ( | 0 . 89 - 0 . 91 | - 0 . 91 / 3 ) } + 1 + { ( 4 4 - 1.3 × 41 ) × 0.1 } + 1
+ { ( 9 - 1.3 × 8 ) × 0.1 } + 1 + { ( 4 4 . 1 - 1.2 × 3 . 2 ) × 0.5 } + 1 } + 1
= 0.13
F HA = { { | 2 - 2 | } + 1 + { ( | 0 . 87 - 0 . 89 | - 0 . 89 / 3 ) } + 1 + { ( 4 4 - 1.3 × 41 ) × 0.1 } + 1
+ { ( 9 - 1.3 × 8 ) × 0.1 } + 1 + { ( 4 . 0 - 1.2 × 3 . 0 ) × 0.5 } + 1 } + 1
= 0.20
F H = MAX { 0.12,0.13,0.2 } + { ( 4 - 6 ) × 0.2 } + 1 = 0.2
D) isolating switch on-line monitoring total failare probability calculates:
F=0.34+0+0.2=0.54
5) alarm threshold value is 0.3, probability of failure〉threshold value, the IEM-610 on-Line Monitor Device has produced alerting signal.

Claims (7)

1. based on the mechanical characteristic of high-voltage circuit breaker probability of failure monitoring method of on-line monitoring, may further comprise the steps, it is characterized in that:
1) during the isolating switch factory inspection, on-line monitoring system reads isolating switch mechanical characteristic under normal circumstances, and calculating normal eigenvalues, comprise that energy storage motor starts time-delay, energy storage motor current peak, mean value, energy storage time, divide-shut brake coil current mean value, divide-shut brake coil current duration, divide-shut brake stroke, three-phase separate combined floodgate stroke startup maximum time difference, divide-shut brake speed, normal eigenvalues is stored in real-time data base and the file system;
When 2) put into operation in the isolating switch scene, on-line monitoring system reads the mechanical characteristic in the isolating switch action situation in real time, each eigenwert of on-line monitoring when calculating the isolating switch action comprises that energy storage motor starts time-delay, energy storage motor current peak, mean value, energy storage time, divide-shut brake coil current mean value, divide-shut brake coil current peak value number, divide-shut brake coil current duration, divide-shut brake stroke, three-phase separate combined floodgate stroke startup maximum time difference, divide-shut brake speed;
3) on-line monitoring system calculates respectively the probability of failure that each eigenwert characterizes, and comprises energy storage motor probability of failure, separating brake probability of failure, Closing fault probability;
4) calculate isolating switch on-line monitoring total failare probability, isolating switch on-line monitoring total failare probability is the probability of failure sum that step (3) calculates:
F=F M+F F+F H
Wherein: F is isolating switch on-line monitoring total failare probability, F M, F F, F HBe respectively the probability of failure of energy storage motor, separating brake, combined floodgate;
5) on-line monitoring system is according to step 4) probability of failure that obtains size, judge whether to report to the police; When probability of failure 〉=alarm threshold value, then on-line monitoring system produces failure alarm signal, and when probability of failure<alarm threshold value, then on-line monitoring system does not produce failure alarm signal.
2. the mechanical characteristic of high-voltage circuit breaker probability of failure monitoring method based on on-line monitoring as claimed in claim 1, it is characterized in that: the described energy storage motor probability of failure of step (3) comprises A phase, B phase, C phase energy storage motor probability of failure, the wherein monitoring method of single-phase energy storage motor probability of failure:
Figure FDA00003320690400011
Figure FDA00003320690400012
Wherein: the desirable A of X, B, C, represent respectively the energy storage motor probability of failure of A phase, B phase, C phase, get energy storage motor resultant fault probability and be:
F M=MAX{F MA,F MB,F Mc}
Wherein: F MBe energy storage motor resultant fault probability, F MA, F MB, F MCBe respectively the energy storage motor probability of failure of A, B, C three-phase.
3. the mechanical characteristic of high-voltage circuit breaker probability of failure monitoring method based on on-line monitoring as claimed in claim 1, it is characterized in that: the described separating brake probability of failure of step (3) comprises A phase, B phase, C phase separating brake probability of failure, the wherein monitoring method of single-phase separating brake probability of failure:
Figure FDA00003320690400021
Figure FDA00003320690400022
Wherein: the desirable A of X, B, C, represent respectively the separating brake probability of failure of A phase, B phase, C phase, get separating brake resultant fault probability and be:
Wherein: F FBe separating brake resultant fault probability, F FA, F FB, F FCBe respectively the separating brake probability of failure of A, B, C three-phase.
4. the mechanical characteristic of high-voltage circuit breaker probability of failure monitoring method based on on-line monitoring as claimed in claim 1, it is characterized in that: the described Closing fault probability of step (3) comprises A phase, B phase, C close a floodgate mutually probability of failure, the wherein monitoring method of single phase closing probability of failure:
The single phase closing probability of failure is:
Figure FDA00003320690400024
Figure FDA00003320690400025
Wherein: the desirable A of X, B, C, represent respectively the Closing fault probability of A phase, B phase, C phase, get combined floodgate resultant fault probability and be:
Figure FDA00003320690400026
Wherein: F HBe combined floodgate resultant fault probability, F HA, F HB, F HCBe respectively the Closing fault probability of A, B, C three-phase.
5. based on the monitoring system of the mechanical characteristic of high-voltage circuit breaker probability of failure of on-line monitoring, it is characterized in that: comprise the energy storage motor sensor, combined floodgate sensor, separating brake sensor, the stroke sensor that gather the primary cut-out signal, and described energy storage motor sensor, combined floodgate sensor, separating brake sensor and stroke sensor all link to each other with mechanical feature detection device, and described mechanical feature detection device links to each other with computer supervisory control system.
6. the monitoring system of the mechanical characteristic of high-voltage circuit breaker probability of failure based on on-line monitoring as claimed in claim 5, it is characterized in that: what described energy storage motor sensor, combined floodgate sensor, separating brake sensor all adopted is current sensor.
7. the monitoring system of the mechanical characteristic of high-voltage circuit breaker probability of failure based on on-line monitoring as claimed in claim 5, it is characterized in that: described stroke sensor is angular displacement sensor.
CN201310226128.5A 2013-06-07 2013-06-07 High-voltage breaker mechanical characteristic fault probability monitoring method and system based on on-line monitoring Expired - Fee Related CN103323771B (en)

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CN110426624A (en) * 2019-07-29 2019-11-08 西安西拓电气股份有限公司 The appraisal procedure and device of circuit-breaker status
CN110568838A (en) * 2019-08-27 2019-12-13 浙江吉利汽车研究院有限公司 vehicle quiescent current acquisition method and system, electronic device and storage medium
CN110988665A (en) * 2019-12-01 2020-04-10 国网辽宁省电力有限公司锦州供电公司 Abnormal alarm method for closing function of spring type circuit breaker
CN112485664A (en) * 2020-11-27 2021-03-12 国网宁夏电力有限公司电力科学研究院 High-voltage circuit breaker diagnosis system and method, electronic terminal and storage medium
CN113552479A (en) * 2021-08-12 2021-10-26 北京慧智神光科技有限公司 Fault analysis capability evaluation method and system of circuit breaker monitoring device
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CN116679200A (en) * 2023-08-03 2023-09-01 国网山东省电力公司淄博供电公司 Method for detecting action characteristics of high-voltage circuit breaker and terminal

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CN103760489A (en) * 2014-01-22 2014-04-30 国家电网公司 Intelligent detection device for high-voltage circuit breaker
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CN104765001A (en) * 2015-04-27 2015-07-08 句容华源电器设备有限公司 Spring energy storage type circuit breaker closing iron core non-action fault detection method
CN104808137A (en) * 2015-05-19 2015-07-29 新疆特变电工自控设备有限公司 Method for on-line judgment of breaker failure
CN104808137B (en) * 2015-05-19 2017-11-14 新疆特变电工自控设备有限公司 A kind of online method for judging circuit breaker failure
CN110192115A (en) * 2017-06-19 2019-08-30 Abb瑞士股份有限公司 Method and apparatus for monitoring breaker and the Internet of Things using this method and device
EP3896805A4 (en) * 2018-12-12 2021-12-01 Mitsubishi Electric Corporation Diagnostic device
CN110261077A (en) * 2019-05-29 2019-09-20 西安西电电气研究院有限责任公司 Breaker mechanical stability determines method and apparatus
CN110398350A (en) * 2019-07-23 2019-11-01 赵怡宸 Breaker mechanic property monitoring method, device, electronic equipment and storage medium
CN110426624A (en) * 2019-07-29 2019-11-08 西安西拓电气股份有限公司 The appraisal procedure and device of circuit-breaker status
CN110568838A (en) * 2019-08-27 2019-12-13 浙江吉利汽车研究院有限公司 vehicle quiescent current acquisition method and system, electronic device and storage medium
CN110988665A (en) * 2019-12-01 2020-04-10 国网辽宁省电力有限公司锦州供电公司 Abnormal alarm method for closing function of spring type circuit breaker
CN112485664A (en) * 2020-11-27 2021-03-12 国网宁夏电力有限公司电力科学研究院 High-voltage circuit breaker diagnosis system and method, electronic terminal and storage medium
CN113552479A (en) * 2021-08-12 2021-10-26 北京慧智神光科技有限公司 Fault analysis capability evaluation method and system of circuit breaker monitoring device
CN113552479B (en) * 2021-08-12 2023-10-31 北京慧智神光科技有限公司 Fault analysis capability evaluation method and system of breaker monitoring device
CN116679200A (en) * 2023-08-03 2023-09-01 国网山东省电力公司淄博供电公司 Method for detecting action characteristics of high-voltage circuit breaker and terminal
CN116679200B (en) * 2023-08-03 2023-11-14 国网山东省电力公司淄博供电公司 Method for detecting action characteristics of high-voltage circuit breaker and terminal

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