CN108681836A - A kind of transformer insulating paper degree of aging discrimination method - Google Patents
A kind of transformer insulating paper degree of aging discrimination method Download PDFInfo
- Publication number
- CN108681836A CN108681836A CN201810692632.7A CN201810692632A CN108681836A CN 108681836 A CN108681836 A CN 108681836A CN 201810692632 A CN201810692632 A CN 201810692632A CN 108681836 A CN108681836 A CN 108681836A
- Authority
- CN
- China
- Prior art keywords
- paper
- oil
- aging
- content
- degree
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0639—Performance analysis of employees; Performance analysis of enterprise or organisation operations
- G06Q10/06395—Quality analysis or management
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/20—Administration of product repair or maintenance
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
- G06Q50/06—Electricity, gas or water supply
Abstract
The present invention relates to a kind of transformer insulating paper degree of aging discrimination methods, and steps are as follows：First, seven ageing states of transformer insulating paper are determined；Then, it is determined that transformer insulation oil, the characteristic value of insulating paper and gas aging and corresponding section；In addition, the relative membership degree and function of oily element, paper element and elemental gas to paper ageing state is built, and correspondingly builds the relative defects matrix of oily element, paper element and elemental gas；Finally, it builds generalized weighted distance function and insulating paper degree of aging recognizes function, recognized.The present invention can assess transformer insulating paper ageing state, reflect the uncertainty that transformer insulating paper ageing state characteristic value has, and provide theoretical direction for the identification of transformer insulating paper degree of aging, provide the necessary technical support for power distribution network O＆M.
Description
Technical field
The present invention relates to the technical field of Power System and its Automation more particularly to a kind of transformer insulating paper agings
Degree discrimination method.
Background technology
The correction maintenance of traditional distribution main equipment and periodic plan maintenance generally require a large amount of artificial, material resources of input, and
And the cost performance of repair is not high.With the raising of automation degree of equipment, only accounts for and set with the fault mode of the equipment of time correlation
The 6% of standby all fault modes, therefore time-based periodic maintenance strategy is only effective to 6% equipment failure mode.With fixed
The maintenance mode for determining to extend or shorten the time between overhauls(TBO) is incorporated experience into based on phase repair, achieves certain effect.
As power equipment quantity is growing day by day, equipment room incidence relation is increasingly sophisticated, and society is to power supply reliability requirement
It is higher and higher, arrange interruption maintenance increasingly difficult；Distribution Network Equipment amount multi-panel is wide, operating status is complicated and changeable, it is difficult to inspection in time
It surveys and assessment distribution master status, previous Strategies of Maintenance more payes attention to test data and seldom pay attention to operation data, it can not
Adapt to the repair based on condition of component management requirement of lean increasingly.
Number transformer is more, can exist different degrees of aging, defect and have familial and concealment, it is difficult to obtain and
When detect and assess.Because the operation time limit, environment, maintenance etc. have very big difference and by multifactor impact, increase transformer aging
The difficulty and complexity of evaluation cannot be satisfied the requirements at the higher level of precision and intelligent Evaluation.
Transformer safety reliability service has first had to severe quality guarantee, also to have enough maintenances and maintenance to ensure.Though
The generation of the failure accident event caused by pre- anti-aging or defect problem to a certain extent is capable of in right periodic preventative maintenance,
But it is difficult the defect etc. for finding that potentiality, concealment are extremely strong.Trouble hunting is a kind of passive maintenance model, is had great
Pressure and uncertainty were also easy to cause and repaiied or problem in bad repair.Repair based on condition of component has specific aim and reasonability, can be effective
Overcome the problems, such as to cross caused by periodic inspection repair with it is in bad repair, controller switching equipment aging or the extension of defect problem and tight can be taken precautions against
Change again, is the trend of the development of overhaul of the equipments from now on.
Traditionally, mostly old to assess transformer by the single factors data calculation and analysis method such as dissolved gas in paper
Change state can more accurately and reliably find the transformer latent defect gradually developed；Utilize wavelet network method, neural network
Method, fuzzy clustering algorithm, grey cluster, support vector machines, rough set method, evidential reasoning method, BAYESIAN NETWORK CLASSIFIER etc.
Mathematical method handles single factors data, calculated and is analyzed, also can more accurately and reliably assess transformer aging and
Defect state.Although neural network is handled and is calculated to high-risk data in the way of advance self-training and self study,
It is seriously affected by the state value of system or parameter, needs to carry out re -training and study once state changes, adapt to
The on the weak side and impact analysis result of property；Fault Tree decomposes the refinement of failure according to certain rule, with dissect fault type and
Its reason needs the fault message integrality refined very much and correctness, is difficult to find to potentiality failure；Support vector machines method
Layered shaping is carried out to data using certain rule, be susceptible to when data volume accidentally point, mistake grades problem；Rough set and
Fuzzy method has original advantage in terms of processing randomness and ambiguity data, but rough set can only handle dispersion number
According to fuzzy method does not have self study and adaptive ability；Bayesian network classification method can preferably handle incomplete
Data, but need to provide the determinant attribute data of enough full-order systems or parameter, otherwise it is calculated and assessment accuracy can be compared with
It is low；Evidence approach can preferably, accurately handle redundancy or data, but exist mutually between information or data
There is significant limitation applied to the differentiation of the event of evidence when contradiction.
It is low it to be easy to cause evaluation accuracy using experience, single parameter or low volume data, and then caused to repair or in bad repair etc.
Problem.On the basis of the fusion of the multi-source datas such as manufacture, monitoring, experiment, test, inspection, operation, metering, automation, according to setting
Standby type, operating condition and application environment carry out classification assessment, establish the transformer ageing state model based on data-driven, with
The redundancy analysis and correlation analysis of key index carry out state evaluation, provide technical support for the reliability service of transformer, are
The failure of transformer occurs to provide Risk-warning.
Cause transformer aging because be known as humidified insulation, iron core failure, current loop overheat, winding failure, part put
Electricity, paper banish electricity, arc discharge, insulation ag(e)ing and aging, influence transformer ageing state have it is aqueous in insulation dielectric loss, paper
Amount, paper breakdown voltage, insulation resistance absorptance, polarization index, volume resistivity, H2The parameters such as content, core inductance resistance.Become
Depressor differentiation O＆M needs total evaluation, and aging identification is related to account information, inspection information, live detection and on-line monitoring
Data, off-line testing data etc., data volume is big, and Influencing Mechanism is different, and routine assessments method lays particular emphasis on certain levels or index is ground
Study carefully, cannot be satisfied the requirement of various dimensions, big data.Using big data technology, it can reflect master status variation comprehensively simultaneously
Determine its feature and key parameters.Utilize delivery test data, defect and accident record, regular and non-periodically test data etc.
Static data utilizes the dynamic datas, including voltage, electric current, power such as the data of equipment on-line detection and real-time traffic information etc.
Real-time traffic information, the fault messages such as short trouble, lightning stroke hopscotch, familial defect, the inspections such as infrared measurement of temperature, sealing, filth
Information, the status datas such as power failures detection information such as D.C. resistance, insulation resistance, paper chromatography, dielectric loss, establish transformer, breaker,
The database of the distributions main equipment such as arrester, capacitor is explained using big data technical research master status feature evaluation method
The incidence relation of bright master status and hydrolysis, pyrolysis extracts transformer aging shape using Fuzzy C-Means Clustering analysis method
State feature.
Oil loss, Water in oil amount, gas content of oil, oil breakdown voltage, oil volume resistivity, oily conductivity, oil
Middle acid value, oil destroy furfural amount, oil colours pool etc. and insulation associated arguments, paper delivery medium in voltage, total acid number of oil, oil and are lost, in paper
In water content, paper breakdown voltage, paper conductivity, paper in acid value, the paper degree of polymerization, paper total acid number, paper furfural amount, paper color and luster etc. with it is exhausted
The relevant parameter of edge, H2Content, C2H2Content, C2H6Content, C2H4Content, CH4Content, CO are with respect to gas production rate, CO2Opposite production
Gas velocity rate, total hydrocarbon etc. and the relevant parameter of gas, core inductance resistance, iron core grounding electric current etc. and the relevant parameter number of iron core
According to, winding D.C. resistance, insulation resistance absorptance, winding D.C. resistance and its unbalance factor, winding short circuit impedance just value difference, around
Just value difference etc. and the relevant parameter of winding, high-pressure side A phases capacitance, high-pressure side B phases are electric for group insulation dielectric loss, winding capacitance
Capacitance, high-pressure side C phases capacitance, low-pressure side a phases capacitance, low-pressure side b phases capacitance, low-pressure side c phase capacitances etc. and capacitance
It is worth relevant parameter, hot(test)-spot temperature, paper temperature etc. and the relevant parameter of temperature, part when hot(test)-spot temperature, high load capacity when typical load
Discharge capacity, degree of skewness, steepness, cross-correlation coefficient, phase asymmetry number etc. and the relevant parameter of shelf depreciation, in different rings
There is different numerical value under border, meteorological condition, there is random and fuzzy uncertainty, it may be said that transformer aging is one random
With the accident or event of fuzzy uncertainty, these factors are also random and fuzzy uncertainty parameter.These influence factors
Usually all there is stochastic uncertainty or fuzzy uncertainty, or with random and fuzzy uncertainty, often with random
Exist with fuzzy uncertainty event or parameter.As it can be seen that the prior art of traditional transformer degree of aging identification is all without complete
Face considers the uncertainty and randomness of influence factor, and computational methods applicability, practicability and application are also difficult to be met.
Invention content
It is an object of the invention to overcome the deficiencies in the prior art, using a kind of transformer insulating paper degree of aging identification side
Method.The involved big number that type is more, quantity is big, correlation is complicated is recognized for how to handle transformer insulating paper degree of aging
According to problem, big data is handled and analyzed using data clusters principle on the basis of establishing large database concept；For transformer
The parameter of the involved random and fuzzy uncertainty of insulating paper degree of aging identification, at the theory using Probabilistic Fuzzy collection
Reason and analysis.
Transformer insulating paper degree of aging identification basic principle be, establish in oil, paper, paper gas associated arguments it is big
Database, relative membership degree and function and generalized weighted distance of the elements such as structure oil, paper, gas to transformer insulating paper degree of aging
Function calculates stochastic uncertainty or fuzzy uncertainty parameter and the relevant synthesized attribute of transformer insulating paper degree of aging
Value, and then determine transformer insulating paper degree of aging.
The technical proposal of the invention is realized in this way：
A kind of transformer insulating paper degree of aging discrimination method, includes the following steps：
S1：Determine seven ageing states of transformer insulating paper；
S2：Determine transformer insulation oil der alterungs-kennwert and its section；
S3：Determine transformer insulating paper der alterungs-kennwert and its section；
S4：Determine transformer gas der alterungs-kennwert and its section；
S5：Relative membership degree and function of the oily element of structure to paper ageing state；
S6：Build relative membership degree and function of the paper element to paper ageing state；
S7：Build relative membership degree and function of the elemental gas to paper ageing state；
S8：The relative defects matrix of the oily element of structure；
S9：Build the relative defects matrix of paper element；
S10：Build the relative defects matrix of elemental gas；
S11：Build generalized weighted distance function；
S12：Build insulating paper degree of aging identification function and identification condition.
Further, the step S1 from electric network database system obtain transformer and oil loss, Water in oil amount,
Acid value, oil destroy in voltage, total acid number of oil, oil in gas content of oil, oil breakdown voltage, oil volume resistivity, oily conductivity, oil
Furfural amount, oil colours pool and the relevant parameter of insulating oil, paper delivery medium loss, water content, paper breakdown voltage, paper conductivity, paper in paper
Furfural amount, paper color and luster and the relevant parameter of insulating paper, H in middle acid value, the paper degree of polymerization, paper total acid number, paper2Content, C2H2Content,
C2H6Content, C2H4Content, CH4Content, CO are with respect to gas production rate, CO2The phase of opposite gas production rate, total hydrocarbon and gas associated arguments
Data information is closed, by Fuzzy Mathematics Analysis, dissecting transformer insulating paper state has fuzzy stochastic characteristic, determines that paper is atomic old
Seven change, small aging, small aging, aging, big aging, serious aging, extreme aging fringes.
Further, the step S2 from electric network database system obtain transformer and oil loss, Water in oil amount,
Acid value, oil destroy in voltage, total acid number of oil, oil in gas content of oil, oil breakdown voltage, oil volume resistivity, oily conductivity, oil
Furfural amount, the related data information in oil colours pool determine oil medium corresponding with seven aging fringes by data analysis
Furfural amount, oil in acid value, the oily degree of polymerization, total acid number of oil, oil in loss, Water in oil amount, oil breakdown voltage, oily conductivity, oil
The elemental characteristic value of color and luster simultaneously determines characteristic value section；
Characteristic value is respectively：
oaMi(a=1,2 ..., NSOM；I=1,2 ..., NSO)
Herein, NSOM=7, NSO=9.
Determine that characteristic value section is respectively：
[oaDia,oaUi] (a=1,2 ..., NSOM；I=1,2 ..., NSO)；
The step S3 obtains transformer and water content, paper breakdown potential in paper delivery medium loss, paper from electric network database system
Furfural amount, paper color and luster related data information in acid value, the paper degree of polymerization, paper total acid number, paper in pressure, paper conductivity, paper, pass through data
Analysis, determine corresponding with seven aging fringes paper delivery medium be lost, water content in paper, paper breakdown voltage, paper conductivity,
Furfural amount in acid value, the paper degree of polymerization, paper total acid number, paper, the elemental characteristic value of paper color and luster and characteristic value section is determined in paper；
Characteristic value is respectively：
saMi(a=1,2 ..., NSPM；I=1,2 ..., NSP)
Herein, NSPM=7, NSP=9.
Determine that characteristic value section is respectively：
[saDia,saUi] (a=1,2 ..., NSPM；I=1,2 ..., NSP)；
The step S4 obtains transformer and H from electric network database system2Content, C2H2Content, C2H6Content, C2H4Contain
Amount, CH4Content, CO are with respect to gas production rate, CO2The related data information of opposite gas production rate, total hydrocarbon is determined by data analysis
H corresponding with seven aging fringes2Content, C2H2Content, C2H6Content, C2H4Content, CH4Content, CO are with respect to aerogenesis speed
Rate, CO2Opposite gas production rate, the elemental characteristic value of total hydrocarbon and determining characteristic value section；
Characteristic value is respectively：
gaMi(a=1,2 ..., NSGM；I=1,2 ..., NSG)
Herein, NSGM=7, NSG=8.
Determine that characteristic value section is respectively：
[gaDia,gaUi] (a=1,2 ..., NSGM；I=1,2 ..., NSG)。
Further, what the step S5 was built is the relative membership degree and function of 11 oily elements pair, 7 kinds of paper ageing states；
Wherein, acid in oil loss, Water in oil amount, gas content of oil, oil breakdown voltage, oil volume resistivity, oily conductivity, oil
Value, oil destroy voltage, total acid number of oil, oil in furfural amount, oil colours pool oily element for seven aging fringes left and right phase
It is respectively to membership function：
In formula, β is determined by data results, ηaLi、ηaRiFor the coefficient less than 1.
Further, what the step S6 was built is the relative membership degree and function of 9 paper elements pair, 7 kinds of paper ageing states；
Wherein, paper delivery medium loss, acid value, the paper degree of polymerization, paper total acid number, paper in water content, paper breakdown voltage, paper conductivity, paper in paper
Middle furfural amount, paper color and luster paper element be respectively for the left and right relative membership degree and function of seven aging fringes：
In formula, β is determined by data results, kaLi、kaRiFor the coefficient less than 1.
Further, what the step S7 was built is the relative defects letter of 8 elemental gas pair, 7 kinds of paper ageing states
Number；Wherein, H2Content, C2H2Content, C2H6Content, C2H4Content, CH4Content, CO are with respect to gas production rate, CO2Opposite aerogenesis speed
Rate, total hydrocarbon elemental gas be respectively for the left and right relative membership degree and function of seven aging fringes：
In formula, αaLi、αaRiFor the coefficient less than 1.
Further, the step S8 structures is oil loss, Water in oil amount, gas content of oil, oil puncture electricity
Acid value, oil destroy furfural amount, oil colours pool element pair in voltage, total acid number of oil, oil in pressure, oil volume resistivity, oily conductivity, oil
In the left and right relative defects matrix of seven aging fringes；The left and right relative defects matrix is as follows：
Step S9 structure be acid value in water content, paper breakdown voltage, paper conductivity, paper in paper delivery medium loss, paper,
Furfural amount in the paper degree of polymerization, paper total acid number, paper, paper color and luster element for seven aging fringes left and right relative defects
Matrix；The left and right relative defects matrix is as follows：
The step S10 structures are H2Content, C2H2Content, C2H6Content, C2H4Content, CH4Content, CO are with respect to aerogenesis
Rate, CO2Opposite gas production rate, total hydrocarbon elemental gas for seven aging fringes left and right relative defects matrix：It should
Left and right relative defects matrix is as follows：
Further, the step S11 introduces weight coefficient, and the generalized distance function of structure is as follows：
In formula, wLOai、wLPai、wLGai、wROai、wRPai、wRGaiRespectively with the weight coefficient of seven aging fuzzy correlations, kLO
And kLO、kLPAnd kLG、RLPAnd RLGRespectively and dLa、dLaWeight coefficient.
Further, the insulating paper degree of aging identification function of the step S12 structures is as follows：
Work as σaLess than setting value εaWhen, judgement transformer insulating paper aging has been in i states, i=1,2 ..., 7, difference
Corresponding atomic aging, small aging, small aging, aging, big aging, serious aging, extreme aging.
Compared with prior art, this programme recognizes involved type for how to handle transformer insulating paper degree of aging
Big data problem more, quantity is big, correlation is complicated, using data clusters principle to counting greatly on the basis of establishing large database concept
According to being handled and analyzed；For the ginseng of the involved random and fuzzy uncertainty of transformer insulating paper degree of aging identification
Amount, is handled and is analyzed using the theory of Probabilistic Fuzzy collection；This programme can assess transformer insulating paper ageing state, reflection
Go out the uncertainty that transformer insulating paper ageing state characteristic value has, theory is provided for the identification of transformer insulating paper degree of aging
Guidance provides the necessary technical support for power distribution network O＆M.
Description of the drawings
Fig. 1 is a kind of flow diagram of transformer insulating paper degree of aging discrimination method proposed by the invention.
Specific implementation mode
With reference to the accompanying drawings and example is combined to be described in further detail the specific implementation mode of the present invention.
As shown in Figure 1, a kind of transformer insulating paper degree of aging discrimination method, includes the following steps：
S1：Determine seven ageing states of transformer insulating paper：
Specially：From electric network database system obtain transformer and oil loss, Water in oil amount, gas content of oil,
Acid value, oil destroy furfural amount, oil colours in voltage, total acid number of oil, oil in oil breakdown voltage, oil volume resistivity, oily conductivity, oil
Pool and the relevant parameter of insulating oil, paper delivery medium is lost, acid value, paper are poly- in water content, paper breakdown voltage, paper conductivity, paper in paper
Furfural amount, paper color and luster and the relevant parameter of insulating paper, H in right, paper total acid number, paper2Content, C2H2Content, C2H6Content, C2H4
Content, CH4Content, CO are with respect to gas production rate, CO2The related data information of opposite gas production rate, total hydrocarbon and gas associated arguments,
By Fuzzy Mathematics Analysis, dissecting transformer insulating paper state has fuzzy stochastic characteristic, determines the atomic aging of paper, small old
Seven change, small aging, aging, big aging, serious aging, extreme aging fringes.
S2：Determine transformer insulation oil der alterungs-kennwert and its section：
Specially：From electric network database system obtain transformer and oil loss, Water in oil amount, gas content of oil,
Acid value, oil destroy furfural amount, oil colours in voltage, total acid number of oil, oil in oil breakdown voltage, oil volume resistivity, oily conductivity, oil
The related data informations such as pool are determined and atomic aging, small aging, small aging, aging, big aging, serious by data analysis
Aging, the corresponding oil loss of seven fringes of extreme aging, Water in oil amount, oil breakdown voltage, oily conductivity, oil
The elemental characteristics value such as furfural amount, oil colours pool and determining characteristic value section in middle acid value, the oily degree of polymerization, total acid number of oil, oil.
Characteristic value is respectively：
oaMi(a=1,2 ..., NSOM；I=1,2 ..., NSO)
Herein, NSOM=7, NSO=9.
Determine that characteristic value section is respectively：
[oaDia,oaUi] (a=1,2 ..., NSOM；I=1,2 ..., NSO)。
S3：Determine transformer insulating paper der alterungs-kennwert and its section：
Specially：From electric network database system obtain water content in the loss of transformer and paper delivery medium, paper, paper breakdown voltage,
The related data informations such as furfural amount, paper color and luster in acid value, the paper degree of polymerization, paper total acid number, paper, pass through data in paper conductivity, paper
Analysis determines and seven atomic aging, small aging, small aging, aging, big aging, serious aging, extreme aging fringes
Acid value in water content, paper breakdown voltage, paper conductivity, paper in the loss of corresponding paper delivery medium, paper, the paper degree of polymerization, paper total acid number,
The elemental characteristics value such as furfural amount, paper color and luster and determining characteristic value section in paper.
Characteristic value is respectively：
saMi(a=1,2 ..., NSPM；I=1,2 ..., NSP)
Herein, NSPM=7, NSP=9.
Determine that characteristic value section is respectively：
[saDia,saUi] (a=1,2 ..., NSPM；I=1,2 ..., NSP)。
S4：Determine transformer gas der alterungs-kennwert and its section：
Specially：Transformer and H are obtained from electric network database system2Content, C2H2Content, C2H6Content, C2H4Content, CH4
Content, CO are with respect to gas production rate, CO2The related data informations such as opposite gas production rate, total hydrocarbon pass through data analysis, determining and paper
Seven atomic aging, small aging, small aging, aging, big aging, serious aging, extreme aging corresponding H of fringe2
Content, C2H2Content, C2H6Content, C2H4Content, CH4Content, CO are with respect to gas production rate, CO2The members such as opposite gas production rate, total hydrocarbon
Plain characteristic value simultaneously determines characteristic value section.
Characteristic value is respectively：
gaMi(a=1,2 ..., NSGM；I=1,2 ..., NSG)
Herein, NSGM=7, NSG=8.
Determine that characteristic value section is respectively：
[gaDia,gaUi] (a=1,2 ..., NSGM；I=1,2 ..., NSG)。
S5：The relative membership degree and function of structure 11 oily elements pair, 7 kinds of paper abnormalities：
Specifically, oil loss, Water in oil amount, gas content of oil, oil breakdown voltage, oil volume resistivity, oil electricity
Acid value, oil destroy in voltage, total acid number of oil, oil the oily element such as furfural amount, oil colours pool for the atomic aging of paper, micro- in conductance, oil
Small aging, small aging, aging, big aging, seven serious aging, extreme aging fringes left and right relative membership degree and function
Respectively：
In formula, β is determined by data results, ηaLi、ηaRiFor the coefficient less than 1.
S6：Build the relative membership degree and function of 9 paper elements pair, 7 kinds of paper abnormalities：
Specifically, paper delivery medium loss, acid value, the paper degree of polymerization, paper in water content, paper breakdown voltage, paper conductivity, paper in paper
The paper element such as furfural amount, paper color and luster is for the atomic aging of paper, small aging, small aging, aging, big aging, tight in total acid number, paper
Again aging, seven fringes of extreme aging left and right relative membership degree and function be respectively：
β is determined by data results in formula, kaLi、kaRiFor the coefficient less than 1.
S7：Build the relative membership degree and function of 8 elemental gas pair, 7 kinds of paper abnormalities：
Specifically, H2Content, C2H2Content, C2H6Content, C2H4Content, CH4Content, CO are with respect to gas production rate, CO2Relatively
The elemental gas such as gas production rate, total hydrocarbon are for the atomic aging of paper, small aging, small aging, aging, big aging, serious aging, pole
End seven fringes of aging left and right relative membership degree and function be respectively：
In formula, αaLi、αaRiFor the coefficient less than 1.
S8：The relative defects matrix of the oily element of structure：
Oil loss, Water in oil amount, gas content of oil, oil breakdown voltage, oil volume resistivity, oily conductivity, oil
Middle acid value, oil destroy in voltage, total acid number of oil, oil the elements such as furfural amount, oil colours pool for atomic aging, small aging, small old
Change, aging, big aging, serious aging, seven fringes of extreme aging relative membership degree and function calculate corresponding degree of membership,
And it builds in oil loss, Water in oil amount, gas content of oil, oil breakdown voltage, oil volume resistivity, oily conductivity, oil
Acid value, oil destroy in voltage, total acid number of oil, oil the elements such as furfural amount, oil colours pool for atomic aging, small aging, small aging,
Aging, big aging, seven serious aging, extreme aging fringes left and right relative defects matrix：
S9：Build the relative defects matrix of paper element：
Paper delivery medium loss, acid value in water content, paper breakdown voltage, paper conductivity, paper in paper, the paper degree of polymerization, paper total acid number,
The elements such as furfural amount, paper color and luster are for atomic aging, small aging, small aging, aging, big aging, serious aging, extreme in paper
The relative membership degree and function of seven fringes of aging calculates corresponding degree of membership, and build water content in paper delivery medium loss, paper,
In paper breakdown voltage, paper conductivity, paper in acid value, the paper degree of polymerization, paper total acid number, paper the elements such as furfural amount, paper color and luster for pole
Micro- aging, small aging, small aging, aging, big aging, serious aging, the left and right of seven fringes of extreme aging are subordinate to relatively
Category degree matrix：
S10：Build the relative defects matrix of elemental gas：
H2Content, C2H2Content, C2H6Content, C2H4Content, CH4Content, CO are with respect to gas production rate, CO2Opposite aerogenesis speed
The elemental gas such as rate, total hydrocarbon are for atomic aging, small aging, small aging, aging, big aging, serious aging, extreme aging seven
The relative membership degree and function of a fringe calculates corresponding degree of membership, and builds H2Content, C2H2Content, C2H6Content, C2H4
Content, CH4Content, CO are with respect to gas production rate, CO2The elemental gas such as opposite gas production rate, total hydrocarbon are for atomic aging, small old
Change, small aging, aging, big aging, seven serious aging, extreme aging fringes left and right relative defects matrix：
S11：Build generalized weighted distance function：
Weight coefficient is introduced, atomic aging, small aging, small aging, aging, big aging, serious aging, extreme aging are wide
Adopted distance function：
In formula, wLOai、wLPai、wLGai、wROai、wRPai、wRGaiFor with atomic aging, small aging, small aging, aging, big
Aging, serious aging, the relevant weight coefficient of extreme aging, kLOAnd kLO、kLPAnd kLG、RLPAnd RLGRespectively and dLa、dLaPower
Weight coefficient.
S12：Build insulating paper degree of aging identification function and identification condition：
Build the atomic aging of insulating paper, small aging, small aging, aging, big aging, serious aging, extreme aging identification
Function：
Work as σaLess than setting value εaWhen, judgement transformer paper has been in i states (1 extremely：Atomic exception, 2：It is small different
Often, 3：Small exception, 4：It is abnormal, 5：It is big abnormal, 6：Severely subnormal, 7：It is extreme abnormal).
The involved type of transformer insulating paper degree of aging identification is more, quantity is big, mutually for how to handle for the present embodiment
The big data problem of relationship complexity is handled and is divided to big data using data clusters principle on the basis of establishing large database concept
Analysis；For the parameter of the involved random and fuzzy uncertainty of transformer insulating paper degree of aging identification, using Probabilistic Fuzzy
The theory of collection is handled and is analyzed；This programme can assess transformer insulating paper ageing state, reflect transformer insulating paper
The uncertainty that ageing state characteristic value has provides theoretical direction for the identification of transformer insulating paper degree of aging, is power distribution network
O＆M provides the necessary technical support.
The examples of implementation of the above are only the preferred embodiments of the invention, and the implementation model of the present invention is not limited with this
It encloses, therefore changes made by all shapes according to the present invention, principle, should all cover within the scope of the present invention.
Claims (9)
1. a kind of transformer insulating paper degree of aging discrimination method, which is characterized in that include the following steps：
S1：Determine seven ageing states of transformer insulating paper；
S2：Determine transformer insulation oil der alterungs-kennwert and its section；
S3：Determine transformer insulating paper der alterungs-kennwert and its section；
S4：Determine transformer gas der alterungs-kennwert and its section；
S5：Relative membership degree and function of the oily element of structure to paper ageing state；
S6：Build relative membership degree and function of the paper element to paper ageing state；
S7：Build relative membership degree and function of the elemental gas to paper ageing state；
S8：The relative defects matrix of the oily element of structure；
S9：Build the relative defects matrix of paper element；
S10：Build the relative defects matrix of elemental gas；
S11：Build generalized weighted distance function；
S12：Build insulating paper degree of aging identification function and identification condition.
2. a kind of transformer insulating paper degree of aging discrimination method according to claim 1, which is characterized in that the step
S1 obtains transformer and oil loss, Water in oil amount, gas content of oil, oil breakdown voltage, oil from electric network database system
Acid value, oil destroy furfural amount in voltage, total acid number of oil, oil, oil colours pool and insulation oil phase in volume resistivity, oily conductivity, oil
The parameter of pass, paper delivery medium loss, acid value, the paper degree of polymerization, paper total acid in water content, paper breakdown voltage, paper conductivity, paper in paper
Furfural amount, paper color and luster and the relevant parameter of insulating paper in value, paper, H2Content, C2H2Content, C2H6Content, C2H4Content, CH4Contain
Amount, CO are with respect to gas production rate, CO2The related data information of opposite gas production rate, total hydrocarbon and gas associated arguments, passes through fuzzy number
Credit is analysed, and dissecting transformer insulating paper state has fuzzy stochastic characteristic, determines the atomic aging of paper, small aging, small aging, old
Seven change, big aging, serious aging, extreme aging fringes.
3. a kind of transformer insulating paper degree of aging discrimination method according to claim 1, which is characterized in that the step
S2 obtains transformer and oil loss, Water in oil amount, gas content of oil, oil breakdown voltage, oil from electric network database system
Acid value, oil destroy furfural amount, the related data in oil colours pool in voltage, total acid number of oil, oil in volume resistivity, oily conductivity, oil
Information determines oil loss corresponding with seven aging fringes, Water in oil amount, oil puncture by data analysis
Furfural amount, the elemental characteristic value in oil colours pool and determination in acid value, the oily degree of polymerization, total acid number of oil, oil in voltage, oily conductivity, oil
Characteristic value section；
Characteristic value is respectively：
oaMi(a=1,2 ..., NSOM；I=1,2 ..., NSO)
Herein, NSOM=7, NSO=9.
Determine that characteristic value section is respectively：
[oaDia,oaUi] (a=1,2 ..., NSOM；I=1,2 ..., NSO)；
The step S3 obtains transformer and water content, paper breakdown voltage, paper in paper delivery medium loss, paper from electric network database system
Furfural amount, paper color and luster related data information in acid value, the paper degree of polymerization, paper total acid number, paper in conductivity, paper, by data analysis,
It determines in paper delivery medium loss corresponding with seven aging fringes, paper in water content, paper breakdown voltage, paper conductivity, paper
Furfural amount, the elemental characteristic value of paper color and luster and determining characteristic value section in acid value, the paper degree of polymerization, paper total acid number, paper；
Characteristic value is respectively：
saMi(a=1,2 ..., NSPM；I=1,2 ..., NSP)
Herein, NSPM=7, NSP=9.
Determine that characteristic value section is respectively：
[saDia,saUi] (a=1,2 ..., NSPM；I=1,2 ..., NSP)；
The step S4 obtains transformer and H from electric network database system2Content, C2H2Content, C2H6Content, C2H4Content, CH4
Content, CO are with respect to gas production rate, CO2The related data information of opposite gas production rate, total hydrocarbon is determined and seven by data analysis
A corresponding H of aging fringe2Content, C2H2Content, C2H6Content, C2H4Content, CH4Content, CO with respect to gas production rate,
CO2Opposite gas production rate, the elemental characteristic value of total hydrocarbon and determining characteristic value section；
Characteristic value is respectively：
gaMi(a=1,2 ..., NSGM；I=1,2 ..., NSG)
Herein, NSGM=7, NSG=8.
Determine that characteristic value section is respectively：
[gaDia,gaUi] (a=1,2 ..., NSGM；I=1,2 ..., NSG)。
4. a kind of transformer insulating paper degree of aging discrimination method according to claim 1, which is characterized in that the step
What S5 was built is the relative membership degree and function of 11 oily elements pair, 7 kinds of paper ageing states；Wherein, oil loss, Water in oil
In amount, gas content of oil, oil breakdown voltage, oil volume resistivity, oily conductivity, oil acid value, oil destroy voltage, total acid number of oil,
Furfural amount in oil, oil colours pool oily element be respectively for the left and right relative membership degree and function of seven aging fringes：
(a=1,2 ..., NSOM；I=1,2 ..., NSO)
In formula, β is determined by data results, ηaLi、ηaRiFor the coefficient less than 1.
5. a kind of transformer insulating paper degree of aging discrimination method according to claim 1, which is characterized in that the step
What S6 was built is the relative membership degree and function of 9 paper elements pair, 7 kinds of paper ageing states；Wherein, aqueous in paper delivery medium loss, paper
The paper element pair of furfural amount in acid value, the paper degree of polymerization, paper total acid number, paper in amount, paper breakdown voltage, paper conductivity, paper, paper color and luster
It is respectively in the left and right relative membership degree and function of seven aging fringes：
(a=1,2 ..., NSPM；I=1,2 ..., NSP)
In formula, β is determined by data results, kaLi、kaRiFor the coefficient less than 1.
6. a kind of transformer insulating paper degree of aging discrimination method according to claim 1, which is characterized in that the step
What S7 was built is the relative membership degree and function of 8 elemental gas pair, 7 kinds of paper ageing states；Wherein, H2Content, C2H2Content, C2H6
Content, C2H4Content, CH4Content, CO are with respect to gas production rate, CO2Opposite gas production rate, the elemental gas of total hydrocarbon are old for seven
Change fringe left and right relative membership degree and function be respectively：
(a=1,2 ..., NSGM；I=1,2 ..., NSG)
In formula, αaLi、αaRiFor the coefficient less than 1.
7. a kind of transformer insulating paper degree of aging discrimination method according to claim 1, which is characterized in that the step
S8 structures be oil loss, Water in oil amount, gas content of oil, oil breakdown voltage, oil volume resistivity, oily conductivity,
It is left and right for seven aging fringes that acid value in oil, oil destroy furfural amount in voltage, total acid number of oil, oil, oil colours pool element
Relative defects matrix；The left and right relative defects matrix is as follows：
The step S9 structures are that acid value, paper are poly- in water content, paper breakdown voltage, paper conductivity, paper in paper delivery medium loss, paper
Furfural amount in right, paper total acid number, paper, paper color and luster element for seven aging fringes left and right relative defects matrix；
The left and right relative defects matrix is as follows：
The step S10 structures are H2Content, C2H2Content, C2H6Content, C2H4Content, CH4Content, CO with respect to gas production rate,
CO2Opposite gas production rate, total hydrocarbon elemental gas for seven aging fringes left and right relative defects matrix：This is left and right
Relative defects matrix is as follows：
8. a kind of transformer insulating paper degree of aging discrimination method according to claim 1, which is characterized in that the step
S11 introduces weight coefficient, and the generalized distance function of structure is as follows：
(a=1,2 ..., NSGM)
In formula, wLOai、wLPai、wLGai、wROai、wRPai、wRGaiRespectively with the weight coefficient of seven aging fuzzy correlations, kLOWith
kLO、kLPAnd kLG、RLPAnd RLGRespectively and dLa、dLaWeight coefficient.
9. a kind of transformer insulating paper degree of aging discrimination method according to claim 1, which is characterized in that the step
The insulating paper degree of aging identification function of S12 structures is as follows：
Work as σaLess than setting value εaWhen, judgement transformer insulating paper aging has been in i states, and i=1,2 ..., 7 is corresponded to respectively
Atomic aging, small aging, small aging, aging, big aging, serious aging, extreme aging.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810692632.7A CN108681836A (en) | 2018-06-29 | 2018-06-29 | A kind of transformer insulating paper degree of aging discrimination method |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810692632.7A CN108681836A (en) | 2018-06-29 | 2018-06-29 | A kind of transformer insulating paper degree of aging discrimination method |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN108681836A true CN108681836A (en) | 2018-10-19 |
Family
ID=63812765
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201810692632.7A Pending CN108681836A (en) | 2018-06-29 | 2018-06-29 | A kind of transformer insulating paper degree of aging discrimination method |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN108681836A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111596181A (en) * | 2020-05-28 | 2020-08-28 | 华北电力大学（保定） | Transformer solid insulation aging evaluation method based on bubble escape temperature |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105405066A (en) * | 2015-11-18 | 2016-03-16 | 中国电力科学研究院 | Distribution transformer health index determination method |
| CN107831415A (en) * | 2017-10-20 | 2018-03-23 | 广东电网有限责任公司河源供电局 | The Interval Valued Fuzzy diversity method that a kind of transformer insulating paper ageing state is assessed |
| CN107843816A (en) * | 2017-10-20 | 2018-03-27 | 广东电网有限责任公司河源供电局 | A kind of transformer insulated defect state appraisal procedure for considering load factor and influenceing |
-
2018
- 2018-06-29 CN CN201810692632.7A patent/CN108681836A/en active Pending
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105405066A (en) * | 2015-11-18 | 2016-03-16 | 中国电力科学研究院 | Distribution transformer health index determination method |
| CN107831415A (en) * | 2017-10-20 | 2018-03-23 | 广东电网有限责任公司河源供电局 | The Interval Valued Fuzzy diversity method that a kind of transformer insulating paper ageing state is assessed |
| CN107843816A (en) * | 2017-10-20 | 2018-03-27 | 广东电网有限责任公司河源供电局 | A kind of transformer insulated defect state appraisal procedure for considering load factor and influenceing |
Non-Patent Citations (2)
| Title |
|---|
| 覃新闻 等: "《塔河流域干旱预警及灾害效应风险评估》", 30 June 2013 * |
| 陈守煜: "《复杂水资源系统优化模糊识别理论与应用》", 31 March 2002 * |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111596181A (en) * | 2020-05-28 | 2020-08-28 | 华北电力大学（保定） | Transformer solid insulation aging evaluation method based on bubble escape temperature |
| CN111596181B (en) * | 2020-05-28 | 2022-05-06 | 华北电力大学（保定） | Transformer solid insulation aging evaluation method based on bubble escape temperature |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN107843718B (en) | Method for evaluating aging state of transformer insulating oil | |
| CN107831415B (en) | Interval value fuzzy set method for transformer insulation paper aging state evaluation | |
| CN107843816B (en) | Transformer insulation defect state evaluation method considering load rate influence | |
| CN108680811B (en) | Transformer fault state evaluation method | |
| CN107831300B (en) | Transformer insulating oil degradation evaluation method based on three-dimensional trapezoidal probability fuzzy set | |
| CN107808044A (en) | A kind of transformer insulating paper deterioration appraisal procedure for considering running temperature and influenceing | |
| CN108802584B (en) | Method for evaluating aging state of transformer insulation paper | |
| CN105488344B (en) | A kind of general evaluation method of controller switching equipment health index | |
| CN104677997B (en) | A kind of transformer oil chromatographic on-line monitoring differentiation method for early warning | |
| CN102289590A (en) | Method for estimating operating state of SF6 high-voltage circuit breaker and intelligent system | |
| CN110688809B (en) | Box transformer fault diagnosis method based on VPRS-RBF neural network | |
| CN110609200A (en) | Power distribution network earth fault protection method based on fuzzy metric fusion criterion | |
| CN110263837A (en) | A kind of circuit breaker failure diagnostic method based on multilayer DBN model | |
| CN103699668A (en) | Power distribution network electric equipment combination state evaluation method based on data section consistency | |
| CN106682159A (en) | Threshold configuration method | |
| CN109086483A (en) | A kind of evidence fusion and Method of Set Pair Analysis of the assessment of transformer ageing state | |
| CN115169704A (en) | CVT error state prediction method and device based on increment integrated learning model | |
| CN104101795A (en) | Transformer fault control method | |
| CN108681836A (en) | A kind of transformer insulating paper degree of aging discrimination method | |
| CN108805467A (en) | A kind of Probabilistic Fuzzy set method of transformer ageing state assessment | |
| CN109086484A (en) | A kind of evidence fusion and Method of Set Pair Analysis of transformer health state evaluation | |
| CN108845285A (en) | Electric energy metering device detection method and system | |
| CN108805468A (en) | A kind of transformer insulating paper exception discrimination method | |
| CN109033198A (en) | A kind of more element Fuzzy Analysis that transformer insulating paper recognizes extremely | |
| CN109062971A (en) | A kind of transformer insulation oil exception discrimination method |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20181019 |
|
| RJ01 | Rejection of invention patent application after publication |