CN109856515A - A kind of direct current cables state of insulation judgment method and system - Google Patents
A kind of direct current cables state of insulation judgment method and system Download PDFInfo
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- CN109856515A CN109856515A CN201910212157.3A CN201910212157A CN109856515A CN 109856515 A CN109856515 A CN 109856515A CN 201910212157 A CN201910212157 A CN 201910212157A CN 109856515 A CN109856515 A CN 109856515A
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/08—Locating faults in cables, transmission lines, or networks
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/12—Testing dielectric strength or breakdown voltage ; Testing or monitoring effectiveness or level of insulation, e.g. of a cable or of an apparatus, for example using partial discharge measurements; Electrostatic testing
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Abstract
The invention discloses a kind of direct current cables state of insulation judgment methods, which comprises obtains the electric signal of cable；Characteristic parameter is obtained according to the electric signal；Obtain characteristic parameter weight；Cable insulation status is judged according to the characteristic parameter and the characteristic parameter weight.A kind of direct current cables state of insulation provided by the invention sentences method and obtains characteristic parameter and characteristic parameter weight by the electric signal of cable, cable insulation status is judged according to the characteristic parameter and the characteristic parameter weight, without changing operating status, the convenient test of cable, without contacting, charging equipment, detection is highly-safe, accuracy of judgement degree is higher.
Description
Technical field
The present invention relates to electric power safety monitoring technology, and in particular to a kind of direct current cables state of insulation judgment method and is
System.
Background technique
In recent years, the domestic and international DC power transmission line quantity that puts into operation is continuously increased, and voltage class is continuously improved, and China Nan'ao ±
The first three end flexible direct current engineering of item in 160 kilovolts of worlds, the soft straight power transmission engineering in five end Zhoushan ± 200kV and Xiamen and Dalian ±
The soft straight cable system in five end 320kV has put into operation.± 525kV XLPE the direct current cables that ABB AB has been developed that for 2014.Though
Right direct current cables technology develops on an unprecedented scale, but O&Ms and the letter such as the insulation live detection of high voltage direct current cable and attachment, fault diagnosis
Number Research on Post-processing Techniques relatively lags behind.The feature for the insulation defect hidden in detection direct current cables how is selected in the prior art
Parameter and the state of insulation that cable is rationally assessed using characteristic parameter not yet propose corresponding method.
Summary of the invention
To solve the problems mentioned above in the background art, the present invention provides a kind of direct current cables state of insulation judgment method
And system, without changing operating status, the convenient test of cable, without contacting charging equipment, detecting highly-safe, accuracy of judgement
It spends higher.
First aspect present invention provides a kind of direct current cables state of insulation judgment method, which comprises
Obtain the electric signal of cable；Characteristic parameter is obtained according to the electric signal；Obtain characteristic parameter weight；According to described
Characteristic parameter and the characteristic parameter weight judge cable insulation status.
Alternatively, the electric signal includes leakage current and local discharge signal.
Alternatively, the characteristic parameter includes leakage current characteristic parameter and local discharge characteristic parameter；
The leakage current characteristic parameter includes statistical parameter and wavelet packet character amount；The local discharge characteristic parameter includes discharge capacity
With electric discharge repetitive rate.
Alternatively, the statistical parameter include insulation resistance, leakage current dispersion, nonlinear factor and
Velocity coefficient；The wavelet packet character amount includes wavelet packet component energy, node energy mean value and node energy dispersion.
Alternatively, described to obtain each characteristic parameter weight specifically: according to the importance of characteristic parameter, to adopt
With default flexible strategy method of determination, each characteristic parameter weight is obtained；The default flexible strategy method of determination includes subjective weighting method, objective
Enabling legislation, Evaluation formula；The subjective weighting method includes analytic hierarchy process (AHP), G1 method；The objective weighted model includes CRITIC
Method entropy assessment；The Evaluation formula includes subjective weighting method and a kind of each combination of method of objective weighted model.
Alternatively, the method also includes: creation training sample database, the training sample database includes cable
The sample of each state is trained RBF neural using the training sample database；It is described according to the characteristic parameter with
And the characteristic parameter weight judges cable insulation status specifically: by RBF neural according to the characteristic parameter and
The characteristic parameter weight judges cable insulation status.
Alternatively, the state of the sample in the training sample database include it is good, general, pay attention to, be serious.
Alternatively, it is described by RBF neural according to the characteristic parameter and the characteristic parameter
Weight judges cable insulation status specifically: obtains the membership function of factor of judgment；Obtain comprehensive evaluation result vector matrix, base
In maximum membership grade principle, cable insulation status is determined.
Second aspect of the present invention provides a kind of direct current cables state of insulation and judges system, the system comprises:
Detecting signal unit, for obtaining the electric signal of cable；Characteristic parameter extraction unit, for according to the electric signal
Obtain characteristic parameter；Flexible strategy acquiring unit, for obtaining characteristic parameter weight；Cable insulation status judging unit is used for basis
The characteristic parameter and the characteristic parameter weight judge cable insulation status.
Alternatively, the system comprises sample training unit, the cable insulation status judging unit packets
RBF neural unit is included, the RBF neural unit is used to identify cable insulation shape by sample training module training
State.
The present invention has the advantages that a kind of direct current cables state of insulation provided by the invention sentences telecommunications of the method by cable
Number characteristic parameter and characteristic parameter weight are obtained, cable insulation is judged according to the characteristic parameter and the characteristic parameter weight
State, without changing operating status, the convenient test of cable, without contacting charging equipment, detecting highly-safe, accuracy of judgement degree
It is higher.
Detailed description of the invention
Fig. 1 is a kind of flow diagram of direct current cables state of insulation judgment method provided in an embodiment of the present invention；
Fig. 2 is direct current cables status assessment model provided in an embodiment of the present invention；
Fig. 3 is the structural schematic diagram that a kind of direct current cables state of insulation provided in an embodiment of the present invention judges system.
Specific embodiment
With reference to the accompanying drawings and in conjunction with specific embodiments, the present invention is described in further detail.
Embodiment one
Fig. 1 is please referred to, the embodiment of the present invention provides a kind of flow diagram of direct current cables state of insulation judgment method, should
Method includes
1) direct current cables measuring point to be checked is selected, leakage current and local discharge signal are detected；
2) it is directed to leakage current and local discharge signal, extracts characteristic parameter, constitutes factor of evaluation collection；
Further, leakage current characteristic parameter includes statistical parameter and wavelet packet character amount, and wherein statistical parameter is by exhausted
Edge resistance, leakage current dispersion, nonlinear factor, velocity coefficient are constituted；Wavelet packet character amount is by wavelet packet component energy, section
Point average energy value and node energy dispersion are constituted；Local discharge characteristic parameter is made of discharge capacity, electric discharge repetitive rate.Specific ginseng
Number is defined as:
(A) statistical parameter of leakage current
A) insulation resistance: r=U/I (8-1)
In formula, U is applied voltage under each voltage class, and I is leakage current；
B) leakage current dispersion:
In formula, s is sample standard deviation；N is leakage current sampling number；xiFor i-th of sample point of leakage current；To let out
Leakage current sample mean.
C) nonlinear factor b and velocity coefficient a:
I=aUb (8-3)
(B) characteristic quantity of leakage current wavelet packet includes the wavelet packet component energy of leakage current under each voltage class
E3,j, node energy average value EavWith node energy dispersion Eσ。
(C) local discharge characteristic parameter includes mean discharge magnitude q under each voltage class (in the voltage class pressing time
The discharge capacity summation of all anti-electric pulses is divided by discharge pulse quantity) with the ratio l=q/U of voltage U, averagely put a repetitive rate n
The ratio t=n/U conduct of (all discharge pulse quantity are divided by time, unit time/min under the voltage class) with applied voltage U
Local discharge characteristic.
Multiple voltage class are applied to every cable sample, voltage class quantity is denoted as k, then insulation resistance in sub-goal layer
Characteristic quantity beLeakage current dispersionNonlinear factor is and velocity coefficient is
s3=[a, b], 3 layers of wavelet packet component energy areNode energy average value isNode
Spread in energy degree isDischarge capacity isElectric discharge repetitive rate be
3) according to the importance of characteristic parameter, corresponding flexible strategy is taken to determine method, establishes factor of evaluation collection and each parameter
Weight.
Further, flexible strategy determine that method can be used subjective weighting method, objective weighted model, Evaluation formula and establish parameter power
Weight, subjective weighting method includes analytic hierarchy process (AHP), G1 method, and objective weighted model includes CRITIC method, entropy assessment, and Evaluation formula includes
Subjective weighting method and a kind of each combination of method of objective weighted model.
In the present embodiment, each characteristic parameter weight assignment for using Evaluation formula to concentrate for factor of evaluation.Subjective weights
Method uses analytic hierarchy process (AHP), and objective weighted model uses entropy assessment.
Subjective weighting method use on the basis of analytic hierarchy process (AHP) improved fuzzy AHP (FAHP) to individual evaluation
Factor weight is allocated.If matrix A=(aij)n×mIf A meets aij+aji=1, then matrix A is referred to as fuzzy complementary matrix.Its
In, aijIndicate factor of evaluation aiCompare ajImportant degree carries out scale, the more big then scale of importance using 0.1~0.9 scaling law
It is bigger.Then, Fuzzy consistent matrix R=(r is calculated using fuzzy complementary matrixij)n×n, matrix element calculation method is as follows
After obtaining Fuzzy consistent matrix R, the weight w of each factor of evaluation is calculated using the relationship method of weightingi′
In formula, α=(n-1)/2 is adjusting parameter.Relationship ranking method has high resolution, the difference of factor of evaluation weight bright
Aobvious feature, thus it is proper with its calculating weight.
Objective weighted model uses anti-entropy assessment, can overcome the problems, such as that index weights go to zero under extreme condition, while energy
The difference between index is embodied well.Note factor of evaluation j judges that direct current cables belongs to the probability of i-th kind of ageing state for cij∈
[0,1], and meetObtained Fuzzy consistent matrix is C=(cij)m×n.Fuzzy consistent matrix method for building up is as follows:
For factor of evaluation index sj, j=1 ..., 8 such factors of evaluation with multiple characteristic quantities use a certain amount of training sample
RBF neural is trained, sample is divided into 4 kinds of ageing states: good, general, pay attention to, is serious.Using trained
RBF neural tests a certain testing data collection, it is assumed that evaluation index sjJudge that the data belong to i-th kind of ageing state
Probability be pj(i), c is calculated using following formulaij:
Negative entropy is calculated based on evaluation index matrix:
And each index weights are determined based on negative entropy:
Finally two kinds of weights are merged to obtain the weight of combination weighting according to multiplication Integration Method
4) it establishes Model for Comprehensive and judges collection, the membership function of evaluation factor is determined using correlation method.
5) fuzzy overall evaluation result vector matrix is generated, maximum membership grade principle is based on, determines cable insulation status.
Utilize the weight W=[w obtained based on Evaluation formula1,w2,w3,w4] and evaluation index Matrix C=(cij)m×n, meter
Calculate state matrix B=WC={ b1,b2,b3,b4}.Wherein b1,b2,b3,b4Respectively represent cable insulation status state be under the jurisdiction of it is good
Good, general, attention, serious degree of membership.Wherein, each state is defined as follows table
Embodiment two
Direct current cables status assessment model provided in an embodiment of the present invention as shown in Figure 2, by the step 2) of embodiment one kind
Leakage current and local discharge signal characteristic parameter extraction are divided into destination layer, indicator layer and sub- indicator layer, and constitute factor of evaluation collection；
Each 20 groups of cable sample data under different conditions mode (5 voltage class of test every time, i.e. k=5) is taken, for building
8 sub- indexs under 3 vertical indexs；
In step 3, its weight is calculated separately using Fuzzy AHP, anti-entropy assessment, then is obtained by combination weighting
To final weight.The level precedence relation matrix that Fuzzy AHP is established is divided into destination layer-indicator layer and indicator layer-son refers to
Two groups of matrix of layer are marked, destination layer-indicator layer precedence relation matrix is Fs, the precedence relation matrix of the sub- indicator layer of indicator layer-is
ST,1、ST,2、ST,3Indicate the fuzzy complementary matrix of sub- indicator layer corresponding to three index layer parameters are as follows:
By establishing fuzzy consistent matrix, the weight that each sub- index is calculated using relationship ranking method is as shown in the table.
Table 8-2 Fuzzy AHP index weights
With certain cable testing data instance, the judgement that each evaluation index makes cable situation is as shown in table 8-3:
Certain test evaluation index result of table 8-3
The comentropy for excavating different indexs using data with existing based on anti-entropy assessment, obtains each sub- index weights after normalization
As shown in table 8-4.The weight that combination weighting obtains is as shown in table 8-5.
The anti-entropy assessment index weights of table 8-4
Each indicator combination weight of table 8-5
In step 4, overall merit is carried out using the above method and obtains each state degree of membership evaluated based on combination weighting such as
Shown in table 8-6.
Table 8-6 combination weighting evaluation result
| State | Well | Generally | Pay attention to | Seriously |
| Degree of membership | 0.0890 | 0.1818 | 0.4002 | 0.3260 |
Step 5 can be based on maximum membership grade principle, determine that cable is exhausted by generating fuzzy overall evaluation result vector matrix
Edge state.Method particularly includes:
In conjunction with table 8-3 and table 8-6, in 8 subsystem assessment indicators, only s1、s2And s4The ageing state of cable is evaluated as
" attention ", and s5It is evaluated as " general ", s3、s6、s7And s8It is evaluated as " serious ".But by combination weighting evaluation method to each evaluation
After index carries out Comprehensive Evaluation, it is believed that the degree of membership for belonging to " attention " state is 0.4002, greater than the degree of membership of other states, therefore
Model finally be evaluated as " paying attention to ", meet the actual state of cable.It can be seen that the insulation ag(e)ing of combined enabling legislation processing
State evaluation model finally remains to make correct evaluation in the case where the sub- index of majority evaluation fails to make accurate judgment,
Evaluation formula can significantly improve the robustness of ageing state evaluation system, can make more accurate evaluation to state of insulation.
Embodiment three
A kind of direct current cables state of insulation provided in an embodiment of the present invention as shown in Figure 3 judges the structural representation of system
Figure, which includes detecting signal unit, for obtaining the electric signal of cable；Characteristic parameter extraction unit, for according to
Electric signal obtains characteristic parameter；Flexible strategy acquiring unit, for obtaining characteristic parameter weight；Cable insulation status judging unit is used
In judging cable insulation status according to the characteristic parameter and the characteristic parameter weight.
Preferably, the system comprises sample training unit, the cable insulation status judging unit includes RBF nerve net
Network unit, the RBF neural unit are used to identify cable insulation status by sample training module training.
The specific work process of the system can refer to embodiment one and two, and details are not described herein.
Above-mentioned technical proposal provided in an embodiment of the present invention and attached drawing, for further explanation of the invention rather than limit
System, in addition it should be noted that those of ordinary skill in the art are it is to be understood that still can be to skill documented by previous embodiment
Art scheme is modified, or is equivalently replaced to part of or all technical features, and these are modified or replaceed, and
The essence of corresponding technical solution is not set to be detached from the range of technical solution of the present invention.
The above is only the embodiment of the present invention, are not intended to restrict the invention, all in the spirit and principles in the present invention
Within, any modification, equivalent substitution, improvement and etc. done, be all contained in apply pending scope of the presently claimed invention it
It is interior.
It should be understood by those skilled in the art that, embodiments herein can provide as method, system or computer program
Product.Therefore, complete hardware embodiment, complete software embodiment or reality combining software and hardware aspects can be used in the application
Apply the form of example.Moreover, it wherein includes the computer of computer usable program code that the application, which can be used in one or more,
The computer program implemented in usable storage medium (including but not limited to magnetic disk storage, CD-ROM, optical memory etc.) produces
The form of product.
The application is referring to method, the process of equipment (system) and computer program product according to the embodiment of the present application
Figure and/or block diagram describe.It should be understood that every one stream in flowchart and/or the block diagram can be realized by computer program instructions
The combination of process and/or box in journey and/or box and flowchart and/or the block diagram.It can provide these computer programs
Instruct the processor of general purpose computer, special purpose computer, Embedded Processor or other programmable data processing devices to produce
A raw machine, so that being generated by the instruction that computer or the processor of other programmable data processing devices execute for real
The device for the function of being specified in present one or more flows of the flowchart and/or one or more blocks of the block diagram.
These computer program instructions, which may also be stored in, is able to guide computer or other programmable data processing devices with spy
Determine in the computer-readable memory that mode works, so that it includes referring to that instruction stored in the computer readable memory, which generates,
Enable the manufacture of device, the command device realize in one box of one or more flows of the flowchart and/or block diagram or
The function of being specified in multiple boxes.
These computer program instructions also can be loaded onto a computer or other programmable data processing device, so that counting
Series of operation steps are executed on calculation machine or other programmable devices to generate computer implemented processing, thus in computer or
The instruction executed on other programmable devices is provided for realizing in one or more flows of the flowchart and/or block diagram one
The step of function of being specified in a box or multiple boxes.
Claims (10)
1. a kind of direct current cables state of insulation judgment method, which is characterized in that the described method includes:
Obtain the electric signal of cable；
Characteristic parameter is obtained according to the electric signal；
Obtain characteristic parameter weight；
Cable insulation status is judged according to the characteristic parameter and the characteristic parameter weight.
2. a kind of direct current cables state of insulation judgment method according to claim 1, which is characterized in that
The electric signal includes leakage current and local discharge signal.
3. a kind of direct current cables state of insulation judgment method according to claim 2, which is characterized in that
The characteristic parameter includes leakage current characteristic parameter and local discharge characteristic parameter；
The leakage current characteristic parameter includes statistical parameter and wavelet packet character amount；
The local discharge characteristic parameter includes discharge capacity and electric discharge repetitive rate.
4. a kind of direct current cables state of insulation judgment method according to claim 3, which is characterized in that the statistical parameter
Including insulation resistance, leakage current dispersion, nonlinear factor and velocity coefficient；
The wavelet packet character amount includes wavelet packet component energy, node energy mean value and node energy dispersion.
5. a kind of direct current cables state of insulation judgment method according to any one of claims 1 to 4, which is characterized in that institute
It states and obtains each characteristic parameter weight specifically: each spy is obtained using default flexible strategy method of determination according to the importance of characteristic parameter
Levy parameters weighting；
The default flexible strategy method of determination includes subjective weighting method, objective weighted model, Evaluation formula；
The subjective weighting method includes analytic hierarchy process (AHP), G1 method；
The objective weighted model includes CRITIC method entropy assessment；
The Evaluation formula includes subjective weighting method and a kind of each combination of method of objective weighted model.
6. a kind of direct current cables state of insulation judgment method according to any one of claims 1 to 4, which is characterized in that institute
State method further include:
Training sample database is created, the training sample database includes the sample of each state of cable,
RBF neural is trained using the training sample database；
It is described that cable insulation status is judged according to the characteristic parameter and the characteristic parameter weight specifically:
Cable insulation status is judged according to the characteristic parameter and the characteristic parameter weight by RBF neural.
7. a kind of direct current cables state of insulation judgment method according to claim 6, which is characterized in that
The state of sample in the training sample database include it is good, general, pay attention to, be serious.
8. a kind of direct current cables state of insulation judgment method according to claim 6 or 7, which is characterized in that described to pass through
RBF neural judges cable insulation status according to the characteristic parameter and the characteristic parameter weight specifically:
Obtain the membership function of factor of judgment；
Comprehensive evaluation result vector matrix is obtained, maximum membership grade principle is based on, determines cable insulation status.
9. a kind of direct current cables state of insulation judges system, which is characterized in that the system comprises:
Detecting signal unit, for obtaining the electric signal of cable；
Characteristic parameter extraction unit, for obtaining characteristic parameter according to the electric signal；
Flexible strategy acquiring unit, for obtaining characteristic parameter weight；
Cable insulation status judging unit, for judging cable insulation according to the characteristic parameter and the characteristic parameter weight
State.
10. direct current cables state of insulation according to any one of claims 7 to 9 judges system, which is characterized in that the system
System includes sample training unit, and the cable insulation status judging unit includes RBF neural unit, the RBF nerve net
Network unit is used to identify cable insulation status by sample training module training.
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| PCT/CN2019/107075 WO2020186718A1 (en) | 2019-03-20 | 2019-09-20 | Method and system for determining insulation state of direct current cable, and storage medium |
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