CN102495318A - Fault diagnosis method of capacitive equipment - Google Patents

Fault diagnosis method of capacitive equipment Download PDF

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Publication number
CN102495318A
CN102495318A CN201110426803XA CN201110426803A CN102495318A CN 102495318 A CN102495318 A CN 102495318A CN 201110426803X A CN201110426803X A CN 201110426803XA CN 201110426803 A CN201110426803 A CN 201110426803A CN 102495318 A CN102495318 A CN 102495318A
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matter
element model
fault
capacitance type
type equipment
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Chinese (zh)
Inventor
王永强
律方成
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North China Electric Power University
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North China Electric Power University
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Abstract

The invention provides a fault diagnosis method of capacitive equipment. The fault diagnosis method comprises the following steps of: utilizing a grey correlation analysis method to obtain a grey correlation degree between a dielectric loss factor tandelta of the capacitive equipment and an environmental factor and taking the obtained grey correlation degree as characteristic quantity to establish a matter-element model of the capacitive equipment to be diagnosed; and then, gaining the grey correlation degree between the matter-element model of the capacitive equipment to be diagnosed and each pre-established typical fault matter-element model by applying an extension theory; and finally, comparing the grey correlation degrees to judge that the equipment has the type of fault if the grey correlation degree between the matter-element model of the capacitive equipment to be diagnosed and the type of fault matter-element model is the highest. According to the invention, influences on diagnosed results by the environmental factor are effectively eliminated, not only various probable faults can be accurately diagnosed, but also the condition that a plurality of the faults simultaneously happen can be diagnosed. The method provided by the invention has the advantages of definite physical meaning and easiness of realizing programming.

Description

A kind of capacitance type equipment method for diagnosing faults
Technical field
The present invention relates to a kind of method that can accurately diagnose the capacitance type equipment insulation fault, belong to technical field of measurement and test.
Background technology
Capacitance type equipment is important power transmission and transforming equipment; Mainly comprise current transformer (TA), sleeve pipe, coupling condenser, capacitance type potential transformer (CVT) etc., quantity accounts for 40%～50% of substation equipment total amount, in transformer station, occupies critical role; Its insulation fault not only influences the safe operation of whole transformer station; Also jeopardize the safety of the miscellaneous equipment and the person simultaneously, therefore, capacitance type equipment carried out fault diagnosis is significant accurately.
At present; More existing research institutions have developed capacitance type equipment insulation on-line monitoring system; But the research about the capacitance type equipment fault diagnosis is less relatively; The main size that adopts dielectric loss angle tangent (
Figure 192741DEST_PATH_IMAGE001
) qualitatively judges insulation and whether has fault, perhaps through current measured value vertical than (referring to that mainly history compares), horizontally come the judgment device state than (mainly referring to alternate same category of device).
When adopting the size qualitative judgement insulation fault of dielectric loss angle tangent (
Figure 57929DEST_PATH_IMAGE001
); Because the on-line monitoring of
Figure 727944DEST_PATH_IMAGE001
and the influence that the off-line test data can receive environmental factor (temperature, humidity etc.); Thereby certainly will also can receive Effect of Environmental to the judged result of equipment failure; Cause the erroneous judgement or fail to judge; And this method can not be distinguished the kind of fault; Can't instruct maintenance, diagnosis effect is relatively poor relatively.
Do not consider the influence of environmental factor through the vertical ratio of current measured value, the horizontal method of judgment device insulation status recently to monitoring result; Diverse location, different data monitored constantly do not have comparability; Therefore the needs of radiodiagnosis x can't be useful in, also the differentiation of failure mode can't be carried out.
Summary of the invention
The objective of the invention is to overcome prior art deficiency, a kind of capacitance type equipment method for diagnosing faults is provided, whether have fault and failure judgement type with accurate diagnostic device.
Problem according to the invention realizes with following technical proposals:
A kind of capacitance type equipment method for diagnosing faults; It adopts grey relation analysis method; Obtain the grey degree of association of capacitance type equipment dielectric dissipation factor and environmental factor; And the grey degree of association that will obtain is set up the matter-element model of the disconnected capacitance type equipment of follow-up as characteristic quantity; Use then and can open up the grey degree of association that the scientific principle opinion is asked for the disconnected capacitance type equipment matter-element model of follow-up and set up each good typical fault matter-element model in advance; At last these grey degrees of association are compared, the grey degree of association height of the disconnected capacitance type equipment matter-element model of follow-up and which kind of typical fault matter-element model can think there is the fault of which kind of type in this equipment.
Above-mentioned capacitance type equipment method for diagnosing faults is considered environment temperature, these two environmental factors of humidity, and then the concrete steps of fault diagnosis are following:
(1) the grey degree of association with capacitance type equipment dielectric dissipation factor and environment temperature, humidity is a characteristic quantity, sets up capacitance type equipment fault diagnosis matter-element model:
Figure 857946DEST_PATH_IMAGE002
，
Where:
Figure 698863DEST_PATH_IMAGE003
,
Figure 300746DEST_PATH_IMAGE004
denote
Figure 885311DEST_PATH_IMAGE001
and the ambient temperature, ambient humidity gray correlation degree;
Figure 725091DEST_PATH_IMAGE005
,
Figure 487642DEST_PATH_IMAGE006
denote
Figure 311241DEST_PATH_IMAGE003
and
Figure 168339DEST_PATH_IMAGE004
value, ,
Figure 576503DEST_PATH_IMAGE006
is calculated by the following formula:
Figure 402246DEST_PATH_IMAGE007
，
In the following formula;
Figure 328614DEST_PATH_IMAGE008
is correlation coefficient, confirmed by following formula:
Figure 877407DEST_PATH_IMAGE009
，
In the formula; X0 is
Figure 496607DEST_PATH_IMAGE001
monitor value after the normalization; Xj representes the environment parameter value after the normalization; Here j=1,2, ρ is a resolution ratio; ζ j (k) is at the correlation coefficient of the xj of a k place sequence to the x0 sequence, 1≤k≤n;
The normalization reduction formula of capacitance type equipment dielectric dissipation factor
Figure 294798DEST_PATH_IMAGE001
monitor value and environment parameter value is following:
；
Figure 178889DEST_PATH_IMAGE011
，
Wherein:
Figure 968990DEST_PATH_IMAGE012
representes the maximal value in
Figure 254478DEST_PATH_IMAGE001
monitor value and the environment parameter value respectively, and representes the minimum value in
Figure 46034DEST_PATH_IMAGE001
monitor value and the environment parameter value respectively;
(2) adopt the method identical that the exemplary apparatus of known fault is carried out environmental impact and test, set up the typical matter-element model Rm of various fault types with step (1);
(3) according to the correlation degree
Figure 256304DEST_PATH_IMAGE014
of computes follow-up capacitance type equipment and each typical fault type:
Figure 763509DEST_PATH_IMAGE015
；
In the formula,
Figure 304212DEST_PATH_IMAGE016
is weight coefficient;
Figure 478841DEST_PATH_IMAGE017
is the correlation function value, and its value is confirmed by following formula:
Figure 345166DEST_PATH_IMAGE018
，
When denominator in the formula is 0, get:
When denominator in the formula is 0, get:
Figure 74087DEST_PATH_IMAGE019
;
Figure 434793DEST_PATH_IMAGE020
is the siding-to-siding block length of
In the formula;
Figure 501155DEST_PATH_IMAGE022
is the distance of point
Figure 717372DEST_PATH_IMAGE023
and interval
Figure 131036DEST_PATH_IMAGE021
, and is interval;
(4) the grey degree of association with the disconnected capacitance type equipment matter-element model of follow-up and each typical fault matter-element model compares; The grey degree of association of the disconnected capacitance type equipment matter-element model of follow-up and any typical fault matter-element model is the highest, can think there is the fault of which kind of type in this equipment.
The present invention is that characteristic quantity is set up capacitance type equipment fault diagnosis matter-element model with the grey degree of association of dielectric dissipation factor and environmental factor; And diagnose the capacitance type equipment fault according to the disconnected capacitance type equipment matter-element model of follow-up and the grey degree of association of typical fault matter-element model, effectively discharged the influence of environmental factor to diagnostic result.This method explicit physical meaning, programming realizes easily, not only can accurately diagnose various contingent faults, and can diagnose the simultaneous situation of various faults.
Description of drawings
Below in conjunction with accompanying drawing the present invention is made further detailed description.
Fig. 1 is a capacitance type equipment Troubleshooting Flowchart of the present invention.
As used herein the symbols:
Figure 175587DEST_PATH_IMAGE003
,
Figure 127363DEST_PATH_IMAGE001
and the ambient temperature of the gray correlation degree;
Figure 978961DEST_PATH_IMAGE001
and the ambient humidity of gray relation degree;
Figure 186083DEST_PATH_IMAGE005
, value;
Figure 799784DEST_PATH_IMAGE006
, value;
Figure 27820DEST_PATH_IMAGE008
, the correlation coefficient; x0 , normalized after
Figure 582384DEST_PATH_IMAGE001
monitor value, xj , the normalized values of environmental parameters; ρ, resolution factor; ζj (k), at the point k in sequence xj x0 sequence correlation coefficients;
Figure 763967DEST_PATH_IMAGE014
, be patient capacitive equipment fault types with various typical degree of association;
Figure 750378DEST_PATH_IMAGE016
, right coefficient;
Figure 181359DEST_PATH_IMAGE017
, correlation function value;
Figure 747469DEST_PATH_IMAGE012
, value, and environmental monitoring parameter values of the maximum; while
Figure 222761DEST_PATH_IMAGE013
,
Figure 141039DEST_PATH_IMAGE001
, and environmental monitoring parameter values in the value of the minimum;
Figure 245261DEST_PATH_IMAGE025
, matter-element;
Figure 932594DEST_PATH_IMAGE026
, things.
Embodiment
The present invention has utilized different faults type this different characteristic to the sensitivity of environment temperature, ambient humidity; Obtain the typical fault matter-element model through pretest; Through the matter-element model of follow-up equipment and the grey correlation analysis of various typical fault matter-element models, the typical fault type that the degree of association is the highest is the physical fault type then.
Grey relation analysis method
The purpose of grey correlation analysis (correlation analysis) is exactly to seek the main relation between each factor in the system, finds out the key factor that influences desired value.
The grey correlation analysis step is following:
1) confirms reference sequences x0 and comparative sequences xj
x0 = {x0(1), x0(2), …, x0(n)} (1)
xj = {xj(1), xj(2), …, xj(n)} (2)
2) compute associations coefficient
Figure 260807DEST_PATH_IMAGE009
(3)
ρ is a resolution ratio in the formula, generally gets 0.5; ζ j (k) is at the correlation coefficient of the xj of a k place sequence to the x0 sequence, 1≤k≤n.
3) ask the degree of association of xj sequence to the x0 sequence
Figure 650069DEST_PATH_IMAGE007
(4)
Change situation more near the person with reference sequences, its degree of association value is big more.
Visible by formula (3), (4), correlation coefficient, the degree of association not only directly depend on reference sequences x0 and comparative sequences xj, and depend on other all comparative sequences indirectly.
Matter-element theory
In order to describe the change procedure of objective things,, can open up to learn and introduce 3 tuples (matter-element) that constitute by things, characteristic and corresponding value, as the fundamental element of describing things the procedural formalism of the problem of resolving contradiction.The expression things with
Figure 823562DEST_PATH_IMAGE026
; The title of
Figure 365401DEST_PATH_IMAGE027
representation feature; The value that
Figure 864516DEST_PATH_IMAGE028
expression
Figure 960648DEST_PATH_IMAGE026
is got about ; Promptly
Figure 350489DEST_PATH_IMAGE029
representes matter-element,
Figure 20505DEST_PATH_IMAGE026
,
Figure 603933DEST_PATH_IMAGE027
,
Figure 384807DEST_PATH_IMAGE028
be called as the three elements of matter-element.
A things can have a plurality of characteristics; Like things
Figure 901239DEST_PATH_IMAGE026
individual characteristic
Figure 62148DEST_PATH_IMAGE031
and corresponding value are arranged, then available
Figure 17651DEST_PATH_IMAGE030
dimension matter-element can be described as:
Figure 498311DEST_PATH_IMAGE033
(5)
Wherein
Figure 321911DEST_PATH_IMAGE034
is called the branch matter-element of
Figure 460899DEST_PATH_IMAGE025
;
Figure 155186DEST_PATH_IMAGE035
is proper vector, and
Figure 337906DEST_PATH_IMAGE036
is the value of proper vector.Things can be more fully described in the introducing of multidimensional matter-element formally, also for the matter-element model of setting up fault diagnosis theoretical foundation is provided.
Matter-element theory is opened up the widely notion of distance with the notion of real variable function middle distance, introduces several important definition below:
Definition 1: point and the distance of putting: establish and be any 2 points on the real axis, claim that then
Figure 309590DEST_PATH_IMAGE038
is
Figure 389541DEST_PATH_IMAGE039
and the distance of .
Definition 2: point and interval distance: Let the real domain arbitrary point
Figure 989522DEST_PATH_IMAGE039
and finite real interval
Figure 189559DEST_PATH_IMAGE042
claimed
Figure 979660DEST_PATH_IMAGE043
(6)
For the point
Figure 750301DEST_PATH_IMAGE039
and interval
Figure 752892DEST_PATH_IMAGE044
distance.
Definition 3: position: establish interval and
Figure 502859DEST_PATH_IMAGE045
; And
Figure 275643DEST_PATH_IMAGE046
, then the place value of point
Figure 816346DEST_PATH_IMAGE039
about
Figure 974664DEST_PATH_IMAGE047
is:
Figure 106568DEST_PATH_IMAGE048
　
Can know by formula; if
Figure 569910DEST_PATH_IMAGE049
; And there is not public point, then
Figure 445462DEST_PATH_IMAGE050
; If and
Figure 262557DEST_PATH_IMAGE051
have public point, then
Figure 478775DEST_PATH_IMAGE052
.
Definition 4 can be opened up set: establish
Figure 892438DEST_PATH_IMAGE053
be domain; The mapping that
Figure 776081DEST_PATH_IMAGE054
is
Figure 453050DEST_PATH_IMAGE053
arrives real domain
Figure 422143DEST_PATH_IMAGE055
; Promptly to arbitrary element
Figure 626914DEST_PATH_IMAGE056
in
Figure 888765DEST_PATH_IMAGE053
; All there is a real number
Figure 740363DEST_PATH_IMAGE057
corresponding with it, then claims
Figure 196753DEST_PATH_IMAGE058
Can open up set for one on
Figure 952219DEST_PATH_IMAGE053
domain;
Figure 279295DEST_PATH_IMAGE059
is the correlation function of ,
Figure 523643DEST_PATH_IMAGE061
be
Figure 82800DEST_PATH_IMAGE056
degree of association about
Figure 264383DEST_PATH_IMAGE060
.
Definition 5: establish interval and
Figure 931042DEST_PATH_IMAGE045
;
Figure 497153DEST_PATH_IMAGE046
and do not have public point then claims function
Figure 64400DEST_PATH_IMAGE062
(7)
Is About interval
Figure 874410DEST_PATH_IMAGE047
the correlation function.Where and are called the classical domain and section domain.During as
Figure 10491DEST_PATH_IMAGE063
, the expression degree that
Figure 619327DEST_PATH_IMAGE039
belongs to
Figure 58398DEST_PATH_IMAGE044
; During as
Figure 600238DEST_PATH_IMAGE064
, expression
Figure 568194DEST_PATH_IMAGE039
does not belong to
Figure 444752DEST_PATH_IMAGE044
; During as
Figure 687515DEST_PATH_IMAGE065
; Be called and open up the territory; Expression still has an opportunity to belong to ; And numerical value is big more, and
Figure 337305DEST_PATH_IMAGE039
is transformed in more easily.
When formula (7) denominator is 0, get
Figure 119764DEST_PATH_IMAGE066
,
Figure 960681DEST_PATH_IMAGE067
be the length of
Figure 296984DEST_PATH_IMAGE044
.
Problem according to the invention realizes with following technical scheme steps:
(1) sets up capacitance type equipment fault diagnosis matter-element model based on
Figure 881550DEST_PATH_IMAGE001
with the grey degree of association of environment temperature, humidity.
The capacitance type equipment on-line monitoring system can obtain to reflect
Figure 721330DEST_PATH_IMAGE001
monitor value sequence of insulation status; Bigger difference is arranged but these measured values can receive Effect of Environmental, and therefore single these on-line monitoring values of utilizing judge that the fault of capacitance type equipment is very difficult.The present invention proposes a kind of new thought; Promptly adopt the degree of association of extraneous factors such as grey relation analysis method analysis
Figure 994134DEST_PATH_IMAGE001
and environment temperature, humidity; Under different insulation status, is different with the grey degree of association of environment temperature, humidity.Therefore; Available
Figure 674831DEST_PATH_IMAGE001
makes up the insulation status that a matter-element model is described equipment with the grey degree of association of environment temperature, humidity, as shown in the formula:
Figure 165856DEST_PATH_IMAGE002
Wherein:
Figure 348575DEST_PATH_IMAGE003
,
Figure 410203DEST_PATH_IMAGE004
represent
Figure 805413DEST_PATH_IMAGE001
respectively and the grey degree of association of environment temperature, humidity; ,
Figure 504564DEST_PATH_IMAGE006
represent
Figure 771597DEST_PATH_IMAGE001
respectively and the degree of association value of environment temperature, humidity. ,
Figure 950961DEST_PATH_IMAGE006
can obtain through computes:
Figure 475483DEST_PATH_IMAGE007
，
Figure 229812DEST_PATH_IMAGE008
is correlation coefficient in the following formula, confirmed by following formula:
Figure 763562DEST_PATH_IMAGE009
，
X0 is
Figure 818106DEST_PATH_IMAGE001
monitor value after the normalization in the formula; Xj representes the environment parameter value (j=1,2) here after the normalization.ρ is a resolution ratio, generally gets 0.5; ζ j (k) is at the correlation coefficient of the xj of a k place sequence to the x0 sequence, 1≤k≤n.
The processing thinking that adopts interval value is handled in normalization; Sequence
Figure 982371DEST_PATH_IMAGE068
is scaled the value on interval, and the normalization reduction formula is following:
Figure 108907DEST_PATH_IMAGE010
；
Figure 486798DEST_PATH_IMAGE011
，
Wherein:
Figure 618703DEST_PATH_IMAGE012
representes the maximal value in
Figure 862471DEST_PATH_IMAGE001
monitor value and the environment parameter value respectively, and
Figure 738023DEST_PATH_IMAGE013
representes the minimum value in monitor value and the environment parameter value respectively.
(2) the typical matter-element model of various fault types is set up
Method of introducing in the employing (1) is carried out the environmental impact test to the exemplary apparatus of known fault, obtains its typical matter-element model Rm.
Instance:
The present invention adds up all capacitance type equipment fault diagnosis example of collecting; Because some fault type sample is less or can not find; Therefore this paper has only carried out simple classification to fault type, has promptly only told and has made moist and two types of typical fault models of setting up separately of other faults.Fault for two types; Extract several groups of samples and carry out statistical computation; Calculating is under the different insulative situation; The grey degree of association of
Figure 273227DEST_PATH_IMAGE001
and environment temperature, humidity; Utilize the grey degree of association interval of different faults type pairing and environment temperature, humidity, set up the matter-element pattern of two kinds of standard faults.
(a) make moist
Choose 14 groups of
Figure 637529DEST_PATH_IMAGE001
data with a certain capacitance type equipment of the fault of making moist, as shown in table 1.
Table 1 faulty equipment
Figure 271904DEST_PATH_IMAGE001
data of making moist
Sequence number
Figure 745610DEST_PATH_IMAGE001
，% 		Temperature,
Figure 714703DEST_PATH_IMAGE070
 Humidity, %
1 0.409 7 72
2 0.544 7 72
3 0.779 7 72
4 0.62 20 55
5 0.96 20 60
6 2.4 27 75
7 0.28 22 60
8 0.72 27 68
9 0.71 25 62
10 0.61 25 62
11 0.5 25 62
12 0.41 25 62
13 0.3 25 62
14 0.23 25 62
To
Figure 400900DEST_PATH_IMAGE001
monitoring data constitutes a reference sequence
Figure 139049DEST_PATH_IMAGE071
.Constitute comparative sequences with environment temperature, humidity.
Figure 958155DEST_PATH_IMAGE001
data of standardizing later are as shown in table 2.
Figure 713621DEST_PATH_IMAGE001
data after table 2 standardization
Sequence number
Figure 571856DEST_PATH_IMAGE001
，% 		Temperature,
Figure 121786DEST_PATH_IMAGE070
 Humidity, %
1 0.082488479 0 0.85
2 0.144700461 0 0.85
3 0.252995392 0 0.85
4 0.179723502 0.65 0
5 0.33640553 0.65 0.25
6 1 1 1
7 0.023041475 0.75 0.25
8 0.225806452 1 0.65
9 0.221198157 0.9 0.35
10 0.175115207 0.9 0.35
11 0.124423963 0.9 0.35
12 0.082949309 0.9 0.35
13 0.032258065 0.9 0.35
14 0 0.9 0.35
After computing derived
Figure 534313DEST_PATH_IMAGE001
and the temperature, humidity, gray relational coefficient
Figure 844202DEST_PATH_IMAGE073
, As shown in Table 3.
The grey correlation coefficient of table 3
Figure 543354DEST_PATH_IMAGE001
and temperature, humidity
Figure 177598DEST_PATH_IMAGE073
Figure 274867DEST_PATH_IMAGE074
0.845088706 0.369606359
0.756683456 0.389509374
0.640117994 0.429797535
0.488983475 0.714599341
0.589318045 0.838917526
1 1
0.382341425 0.664737917
0.367588933 0.514760148
0.367588933 0.514760148
0.398652786 0.777468153
0.383016278 0.720132743
0.367174281 0.666098226
0.355155483 0.627570694
0.341493268 0.586134454
0.333333333 0.5625
Calculated at this time
Figure 356961DEST_PATH_IMAGE001
and the temperature, humidity, gray relational degree
Figure 514273DEST_PATH_IMAGE005
,
Figure 635813DEST_PATH_IMAGE006
, respectively:
Figure 536772DEST_PATH_IMAGE075
=0.517781962， =0.632988034
The standard deviation that calculates above sample is respectively:
Figure 21160DEST_PATH_IMAGE077
=0.21575189，
Figure 911887DEST_PATH_IMAGE078
=0.176601972，
The confidence level of the grey degree of association of
Figure 350959DEST_PATH_IMAGE001
and temperature, humidity is that 0.95 fiducial interval is respectively:
[0.393208723，0.642355201]，
[0.531019612，0.734956456]，
With this when making moist
Figure 892799DEST_PATH_IMAGE005
, the span of
Figure 860755DEST_PATH_IMAGE006
.
be other (structure, quality, technology etc.) faults (b)
Chosen 11 groups of
Figure 980075DEST_PATH_IMAGE001
data that the capacitance type equipment of fault types such as fault of construction, quality problems, technology be bad is arranged, as shown in table 4.
Figure 845263DEST_PATH_IMAGE001
data of other faulty equipments of table 4
Sequence number
Figure 515279DEST_PATH_IMAGE001
，% 		Temperature,
Figure 629865DEST_PATH_IMAGE070
 Humidity, %
1 0.04 18 37
2 0.393 27 42
3 0.286 25 68
4 0.335 25 68
5 0.346 25 68
6 0.357 26 70
7 0.435 26 70
8 0.437 26 70
9 0.729 30 60
10 0.624 30 60
11 0.749 30 60
Same data after standardization processing are as shown in table 5.
Table 5 normalized digital data
Sequence number
Figure 396013DEST_PATH_IMAGE001
，% 		Temperature,
Figure 987662DEST_PATH_IMAGE070
 Humidity, %
1 0 0 0
2 0.497884344 0.75 0.151515152
3 0.34696756 0.583333333 0.939393939
4 0.416078984 0.583333333 0.939393939
5 0.431593794 0.583333333 0.939393939
6 0.447108604 0.666666667 1
7 0.557122708 0.666666667 1
8 0.559943583 0.666666667 1
9 0.971791255 1 0.696969697
10 0.823695346 1 0.696969697
11 1 1 0.696969697
After computing derived
Figure 589545DEST_PATH_IMAGE001
and the temperature, humidity, gray relational coefficient ,
Figure 13890DEST_PATH_IMAGE074
As shown in Table 6.
The grey correlation coefficient of table 6
1 1
0.540210846 0.460973095
0.556186425 0.333333333
0.639123919 0.361443584
0.661259929 0.368418255
0.574311166 0.348853598
0.730025807 0.400780685
0.735136568 0.402316199
0.913049206 0.518730586
0.626882547 0.700368854
1 0.4943119
According to equation (4) is calculated at this time
Figure 486832DEST_PATH_IMAGE001
and the temperature, humidity, gray relational degree
Figure 181118DEST_PATH_IMAGE005
, , respectively:
Figure 940313DEST_PATH_IMAGE075
=0.725107856，
Figure 617413DEST_PATH_IMAGE076
=0.489957281，
The standard deviation that calculates above sample is respectively:
Figure 431785DEST_PATH_IMAGE077
=0.17121831，
Figure 785406DEST_PATH_IMAGE078
=0.199365442，
The confidence level of the grey degree of association of
Figure 583598DEST_PATH_IMAGE001
and temperature, humidity is that 0.95 fiducial interval is respectively:
[0.610040311，0.840175401]，
[0.356024091，0.623890471]，
With this during as other faults
Figure 782498DEST_PATH_IMAGE005
, the span of
Figure 982535DEST_PATH_IMAGE006
.
(3) correlation degree of calculating follow-up capacitance type equipment and each typical fault type
Correlation degree
Figure 756325DEST_PATH_IMAGE014
according to computes follow-up capacitance type equipment and each typical fault type.
Figure 41813DEST_PATH_IMAGE015
，
In the formula;
Figure 778825DEST_PATH_IMAGE016
is weight coefficient, generally desirable
Figure 833368DEST_PATH_IMAGE082
;
Figure 794371DEST_PATH_IMAGE017
is the correlation function value, and its value is confirmed by following formula:
Figure 35996DEST_PATH_IMAGE018
，
When denominator in the formula is 0, get:
Figure 593011DEST_PATH_IMAGE019
,
Figure 767640DEST_PATH_IMAGE020
are the burst lengths of
Figure 633965DEST_PATH_IMAGE021
.
In the formula,
Figure 362887DEST_PATH_IMAGE083
is the distance of point
Figure 972860DEST_PATH_IMAGE023
and interval .
Figure 847129DEST_PATH_IMAGE085
is
Figure 328926DEST_PATH_IMAGE084
value interval.
Instance:
Certain model is that BRDW2-72.5/630 bushing shell for transformer test data is as shown in table 7; Confirm that reference sequences is
Figure 742589DEST_PATH_IMAGE001
, comparative sequences is a temperature and humidity.
Table 7 sleeve pipe
Figure 95073DEST_PATH_IMAGE001
test data
Sequence number
Figure 568780DEST_PATH_IMAGE001
（%） 		Temperature (
Figure 288606DEST_PATH_IMAGE070
） 		Humidity (%)
1 4.09 -31 31.05
2 1.47 -20.3 27.9
3 4.55 -10 87.5
4 16.7 -7.4 93.5
5 35.03 -3.5 32.625
6 191.62 -0.7 85
7 0.8 8.5 26.2
8 570.93 10.7 99
By (a) the method to calculate
Figure 240381DEST_PATH_IMAGE001
and the temperature and humidity of gray relation degree
Figure 712951DEST_PATH_IMAGE005
,
Figure 357559DEST_PATH_IMAGE006
, respectively:
Figure 813948DEST_PATH_IMAGE075
=0.614452098， =0.742904686，
Then, the matter-element model of the present situation of description follow-up capacitance type equipment is:
Figure 880179DEST_PATH_IMAGE086
，
The compute associations functional value gets:
，
Figure 639373DEST_PATH_IMAGE088
，
Figure 667372DEST_PATH_IMAGE089
，
Figure 380113DEST_PATH_IMAGE090
，
Calculate the correlation degree of follow-up capacitance type equipment and each typical fault type.
Figure 851677DEST_PATH_IMAGE091
，
Figure 751500DEST_PATH_IMAGE092
，
Because
Figure 848769DEST_PATH_IMAGE093
, can judge the follow-up capacitance type equipment fault of possibly making moist qualitatively; Because
Figure 681596DEST_PATH_IMAGE094
, can judge that then the follow-up capacitance type equipment does not have other faults such as recurring structure defective, quality problems and technology is bad.
To finding after the sleeve pipe strip inspection that inside pipe casing obviously has water droplet to exist, this capacitance type equipment is the fault of making moist really, and diagnosis is correct.
The advantage of the inventive method:
(1) adopted the dielectric dissipation factor
Figure 573328DEST_PATH_IMAGE001
and the grey degree of association of environment temperature, humidity to set up matter-element model, discharged Effect of Environmental as characteristic quantity.
(2) adopt and can open up diagnostic method and carry out Analysis on Fault Diagnosis, explicit physical meaning, programming realizes easily.
(3) can draw multiple possible fault diagnosis result, and each result has the different grey degrees of association,, can diagnose the simultaneous situation of various faults according to the size of the grey degree of association possible order of fault that can be ranked.

Claims (2)

1. capacitance type equipment method for diagnosing faults; It is characterized in that; It adopts grey relation analysis method; Obtain the grey degree of association of capacitance type equipment dielectric dissipation factor
Figure 490350DEST_PATH_IMAGE001
and environmental factor; And the grey degree of association that will obtain is set up the matter-element model of the disconnected capacitance type equipment of follow-up as characteristic quantity; Use then and can open up the grey degree of association that the scientific principle opinion is asked for the disconnected capacitance type equipment matter-element model of follow-up and set up each good typical fault matter-element model in advance; At last these grey degrees of association are compared, the grey degree of association height of the disconnected capacitance type equipment matter-element model of follow-up and which kind of typical fault matter-element model can think there is the fault of which kind of type in this equipment.
2. capacitance type equipment method for diagnosing faults according to claim 1 is characterized in that, the concrete steps of said fault diagnosis are following:
(1) the grey degree of association with capacitance type equipment dielectric dissipation factor
Figure 664979DEST_PATH_IMAGE001
and environment temperature, humidity is a characteristic quantity, sets up capacitance type equipment fault diagnosis matter-element model:
Figure 146DEST_PATH_IMAGE002
，
Where:
Figure 260226DEST_PATH_IMAGE003
,
Figure 870198DEST_PATH_IMAGE004
denote
Figure 368176DEST_PATH_IMAGE001
and the ambient temperature, ambient humidity gray correlation degree;
Figure 421714DEST_PATH_IMAGE005
,
Figure 903511DEST_PATH_IMAGE006
denote
Figure 786016DEST_PATH_IMAGE003
and
Figure 669658DEST_PATH_IMAGE004
value,
Figure 143365DEST_PATH_IMAGE005
,
Figure 581300DEST_PATH_IMAGE006
is calculated by the following formula:
Figure 782343DEST_PATH_IMAGE007
，
In the following formula; is correlation coefficient, confirmed by following formula:
Figure 899520DEST_PATH_IMAGE009
，
In the formula, x 0For after the normalization
Figure 355909DEST_PATH_IMAGE001
Monitor value, x jEnvironment parameter value after the expression normalization, here j=1,2, ρBe resolution ratio; ζ j ( k) be at point kThe place x j Sequence is right x 0The correlation coefficient of sequence, 1≤ k≤ n
The normalization reduction formula of capacitance type equipment dielectric dissipation factor
Figure 111376DEST_PATH_IMAGE001
monitor value and environment parameter value is following:
Figure 172873DEST_PATH_IMAGE010
；
Figure 739114DEST_PATH_IMAGE011
，
Wherein:
Figure 682800DEST_PATH_IMAGE012
representes the maximal value in monitor value and the environment parameter value respectively, and
Figure 423540DEST_PATH_IMAGE013
representes the minimum value in
Figure 144371DEST_PATH_IMAGE001
monitor value and the environment parameter value respectively;
(2) adopt the method identical that the exemplary apparatus of known fault is carried out environmental impact and test, set up the typical matter-element model of various fault types with step (1) R m
(3) according to the correlation degree
Figure 44194DEST_PATH_IMAGE014
of computes follow-up capacitance type equipment and each typical fault type:
Figure 390730DEST_PATH_IMAGE015
；
In the formula, is weight coefficient;
Figure 584131DEST_PATH_IMAGE017
is the correlation function value, and its value is confirmed by following formula:
Figure 502409DEST_PATH_IMAGE018
，
When denominator in the formula is 0, get:
When denominator in the formula is 0, get:
Figure 403369DEST_PATH_IMAGE019
;
Figure 293964DEST_PATH_IMAGE020
is the siding-to-siding block length of
Figure 372910DEST_PATH_IMAGE021
In the formula;
Figure 512904DEST_PATH_IMAGE022
is the distance of point
Figure 686397DEST_PATH_IMAGE023
and interval
Figure 228236DEST_PATH_IMAGE021
, and
Figure 727351DEST_PATH_IMAGE024
is
Figure 823483DEST_PATH_IMAGE021
interval;
(4) the grey degree of association with the disconnected capacitance type equipment matter-element model of follow-up and each typical fault matter-element model compares; The grey degree of association of the disconnected capacitance type equipment matter-element model of follow-up and any typical fault matter-element model is the highest, can think there is the fault of which kind of type in this equipment.
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CN105718748A (en) * 2016-01-28 2016-06-29 许继集团有限公司 Online monitoring data processing method
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