CN106203875A - A kind of model for power equipment health state evaluation - Google Patents
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Abstract
The invention discloses a kind of model for power equipment health state evaluation, relate to technical field of electric power, it is capable of the operation health status of power equipment is assessed accurately, it is simple to it is carried out the operation such as reasonable employment and maintenance, failure predication and distribution management.This model being used for power equipment health state evaluation includes: evaluation index module includes quantity of state index and the weight of each quantity of state index of multiple health status affecting power equipment；Comment module includes Comment gathers, for evaluating the health status of power equipment；Fuzzy evaluation module includes the membership function set up based on Comment gathers, for being combined the weight of each quantity of state index by membership function, the health status of power equipment is carried out fuzzy evaluation, obtains fuzzy evaluation conclusion；Grey correlation module includes the clear evaluation criterion set up based on Comment gathers, for fuzzy evaluation conclusion is carried out clear evaluation process, obtains health state evaluation result accurately.
Description
Technical field
The present invention relates to technical field of electric power, particularly relate to a kind of model for power equipment health state evaluation.
Background technology
Along with economic fast development, the supply of electric power situation growing tension of China, the most only because of network system
The economic loss that fault causes upper trillion, the main cause analyzing it is that the fault to network system can not be located in time
Reason.
Perform the periodic inspection system that the whole nation is unified because of China's electric power enterprise, its substitutive characteristics is simple the most always
Based on the time cycle.This pattern is clearly present and does not considers in the actual state of equipment, maintenance process that specific aim is strong, the palm
Hold equipment state not, do not meet the fault observer in existing power equipment life-span, produce the negative effect etc. of excess maintenance etc no
Good problem, it is clear that whether troubleshooting system improves the reliability level directly affecting power equipment, therefore by power equipment
Run health status characteristic to be modeled, its reasonable employment and maintenance, failure predication and distribution management etc. are operated, has
Particularly important meaning.
Summary of the invention
The technical problem to be solved is to provide the model of a kind of power equipment health state evaluation, it is possible to real
Now the operation health status of power equipment is assessed accurately, it is simple to it is carried out reasonable employment and maintenance, failure predication
And the operation such as distribution management.
For solving above-mentioned technical problem, the present invention adopts the following technical scheme that
Embodiments providing a kind of model for power equipment health state evaluation, this model includes:
Evaluation index module, described evaluation index module includes that the quantity of state of multiple health status affecting power equipment refers to
It is marked with and the weight of each quantity of state index；
Comment module, described comment module includes Comment gathers, for evaluating the health status of described power equipment；
Fuzzy evaluation module, described fuzzy evaluation module includes the membership function set up based on described Comment gathers, is used for leading to
Cross described membership function and combine the weight of each quantity of state index, the health status of power equipment is carried out fuzzy evaluation, obtains mould
Stick with paste evaluation conclusion；
Grey correlation module, described grey correlation module includes the clear evaluation criterion set up based on described Comment gathers, uses
In described fuzzy evaluation conclusion is carried out clear evaluation process, obtain health state evaluation result accurately.
Preferably, described Comment gathers includes good, normal, suspicious, exception and dangerous five kinds of comments, wherein, dangerous: 0～
60；Abnormal: 60～70；Suspicious: 70～80；Normal: 80～90；Good: 90～100.
Preferably, described membership function is triangle and trapezoidal combination distribution membership function.
Preferably, described membership function includes:
Membership function under kilter:
Membership function under normal condition:
Membership function under suspicious state:
Membership function under abnormality:
Membership function under precarious position:
Preferably, described fuzzy evaluation conclusion is characterized as { Xi}={ Xi(1),Xi(2),…Xi(5) }, wherein, Xi(1),Xi
(2),…Xi(5) it is arbitrarily to be more than or equal to 0 real number less than or equal to 1, Xi(1) characterize described power equipment and belong to kilter
Degree, Xi(2) characterize described power equipment and belong to the degree of normal condition, Xi(3) characterize described power equipment and belong to suspicious state
Degree, Xi(4) characterize described power equipment and belong to the degree of abnormality, Xi(5) characterize described power equipment and belong to dangerous shape
The degree of state.
Preferably, described clear evaluation criterion includes: kilter is [1,0,0,0,0], normal condition be [0,1,0,0,
0], suspicious state is [0,0,1,0,0], and abnormality is [0,0,0,1,0], and precarious position is [0,0,0,0,1].
Preferably, described grey correlation module includes:
Coefficient of association calculating sub module, contacts for calculating the pass of described fuzzy evaluation conclusion and each clear evaluation criterion
Number；
Calculation of relationship degree submodule, for contacting based on the calculated whole passes of described coefficient of association calculating sub module
Number, calculates the degree of association, obtains health state evaluation result accurately.
Preferably, described coefficient of association calculating sub module especially byCalculate described fuzzy
Evaluation conclusion and the coefficient of association of each clear evaluation criterion, wherein, Δi(k)=| X0(k)-Xi(k) |, X0(k) be described clearly
Element in clear evaluation criterion, k is the integer more than or equal to 1, less than or equal to 5, MminFor two-stage lowest difference, MmaxMaximum for two-stage
Difference.
Preferably, described calculation of relationship degree submodule especially byCalculate the degree of association, obtain accurately
Health state evaluation result.
Preferably, this model also includes: acquisition module, and described acquisition module is for obtaining the scoring of each quantity of state index.
In the inventive solutions, use process and the step of analytic hierarchy process (AHP), including therein such as structure two ratios
Relatively judgment matrix and the mathematical method of matrix operations, determine for certain element of last layer time, with its phase in this level
Close the importance ranking relative weight of element, calculate each layer element synthetic weight to aims of systems, etc., all with routine
Analytic hierarchy process (AHP) is identical.
Embodiments providing a kind of model for power equipment health state evaluation, this model includes that assessment refers to
Mark module, comment module, fuzzy evaluation module and grey correlation module.These modules cooperate, by complex electricity
Power equipment is divided into multiple quantity of state index, based on these quantity of state indexs, healthy to power equipment in conjunction with grey correlation module
State is made in time, is assessed accurately, it is possible to make staff understand the health status of corresponding power equipment in time, thus
It is easy to it is carried out the operation such as reasonable employment and maintenance, failure predication and distribution management.
Accompanying drawing explanation
In order to be illustrated more clearly that the embodiment of the present invention or technical scheme of the prior art, embodiment will be described below
The accompanying drawing used required in is briefly described, it should be apparent that, the accompanying drawing in describing below is only some of the present invention
Embodiment, for those of ordinary skill in the art, on the premise of not paying creative work, it is also possible to attached according to these
Figure obtains other accompanying drawing.
The structural representation of the model for power equipment health state evaluation that Fig. 1 provides for the embodiment of the present invention；
The quantity of state index schematic diagram of the cable run that Fig. 2 provides for the embodiment of the present invention；
The schematic diagram of the membership function that Fig. 3 provides for the embodiment of the present invention.
Detailed description of the invention
Below in conjunction with the accompanying drawing in the embodiment of the present invention, the technical scheme in the embodiment of the present invention is carried out clear, complete
Describe, it is clear that described embodiment is a part of embodiment of the present invention rather than whole embodiments wholely.Based on this
Embodiment in bright, the every other enforcement that those of ordinary skill in the art are obtained under not making creative work premise
Example, broadly falls into the scope of protection of the invention.
Embodiments provide a kind of model for power equipment health state evaluation, as it is shown in figure 1, this model
Including:
Evaluation index module, this evaluation index module includes the quantity of state index of multiple health status affecting power equipment
And the weight of each quantity of state index.
Comment module, this comment module includes Comment gathers, for evaluating the health status of power equipment.
Fuzzy evaluation module, this fuzzy evaluation module includes the membership function set up based on Comment gathers, for by being subordinate to
Function combines the weight of each quantity of state index, the health status of power equipment is carried out fuzzy evaluation, obtains fuzzy evaluation conclusion.
Grey correlation module, grey correlation module includes the clear evaluation criterion set up based on Comment gathers, for fuzzy
Evaluation conclusion carries out clear evaluation process, obtains health state evaluation result accurately.
Hereinafter illustrate the concrete condition of modules:
Realizing accurately and comprehensively assessing the health status of power equipment, it runs shape to need accurate assurance to reflect
The quantity of state of state, and the operability of bonding state assessment, define and comprise Test Information, operation information, patrol and examine the shape of information
State duration set, establishes power cable state evaluation index system, and this evaluation index system is stored in evaluation index module.Comment
Assessment system is specifically divided into two grades, and two-level index is quantity of state.As in figure 2 it is shown, for the power cable in power equipment
For, the present invention can use nine scales analytic hierarchy process ask for each quantity of state weight.
As a example by cable run, for cable run, the factor affecting its running status substantially can include that cable is originally
Body, cable termination, cable intermediate joint, earthed system, cable passage and auxiliary equipment etc. six, each of which Xiang Douke is the thinnest
It is divided into multinomial quantity of state index.Such as, for cable body, it can be subdivided into line load, insulation resistance, cable change
Shape, buried depth, fire protection flame retarding etc. totally five；For cable termination, it can be subdivided into filth, fire protection flame retarding, breakage and temperature
Deng totally four；For cable intermediate joint, it can be subdivided into fire protection flame retarding, breakage, temperature, running environment etc. totally four；
For earthed system, it can be subdivided into down conductor, earth resistance etc. totally two；For cable passage, it can
It is subdivided into cable shaft, cable pipe trench environment etc. totally two；For auxiliary equipment, it can be subdivided into firmness, mark together
Entirely, corrosion degree etc. totally three.
Based on the quantity of state index found, the weight in evaluation index module in the embodiment of the present invention is to pass through level
Analytic process obtains.
Analytic hierarchy process (AHP) (The Analytic Hierarchy Process, be called for short AHP) rationale here is that decision-making
Every complicated factor of object to be evaluated, according to set standard and principle, is simplified by person, and stepwise level knot is passed in foundation
Structure.Pass stepwise hierarchical structure complicated problem can be become simplified as, methodization, stratification.Pass stepwise hierarchical structure general
Including destination layer, rule layer and indicator layer three layers, destination layer refers generally to for the predetermined target that studies a question, and rule layer represents
Realize intermediate link needed for this predeterminated target；Indicator layer is to realize index, scheme that predeterminated target used etc..
In embodiments of the present invention, same layer is judged according to judgment matrix 1～9 grades of scale principles (as shown in table 1 below)
Important relationship between secondary upper two elements, obtains judgment matrix.Wherein matrix element represents each first class index element XiRelative to Xj
The quantized value of importance, wherein, i and j is integer.
Table 1 judgment matrix 1～9 grades of scale principles
For cable run as shown in Figure 2, following first class index judgment matrix A can be drawn, need explanation
It is that V1, V2, V3, V4, V5, the V6 in table 2 represents cable itself, cable termination, cable intermediate joint, earthed system, electricity respectively
Cable passage and auxiliary equipment:
Table 2 cable run first class index judgment matrix
AHP method is to be several compositing factors complicated PROBLEM DECOMPOSITION, these factors by interrelated degree and is subordinate to
Relation packet is formed with the flight aggregated(particle) structure of sequence, forms a multi-level assay model, by the side compared two-by-two
Formula determines the relative importance of each factor in level, then according to practical situation, to determine the weight coefficient of each factor.The method
Based on expert's Subjective degree to indices importance, there is certain persuasion dynamics.Analytic hierarchy process (AHP) asks for weight
Method have geometric method, arithmetical method, feature vector method, method of least square 4 kinds.
Based on judgment matrix, the weight of each quantity of state index can be readily available.But, the calculated power of AHP method
The most only pass through consistency check just can be used.
Concrete, first calculating coincident indicator CI (Consistency Index), CI can be calculated by following formula:
Wherein λmaxRepresenting the eigenvalue of maximum of judgment matrix, n represents the dimension of judgment matrix.
Secondly, consistency ration is calculated:
Wherein, RI is Aver-age Random Consistency Index, and its value can be by 3 acquisitions of tabling look-up.As CR ＜ 0.1, it is judged that matrix
Reliably；When CR >=0.1, matrix is unreliable, needs to re-establish matrix.
Table 3 Aver-age Random Consistency Index
Through calculating, the CR=0.0047 < 0.1 of the judgment matrix in table 2, therefore this judgment matrix is examined by concordance
Test.
The calculated weight of AHP method has only been passed through consistency check and just can have been used, and this has just ensured weight
Science and reasonability；Second, general objective is turned to orderly some levels and some elements, this is particularly well-suited to the body that has levels
The multiple index evaluation object of system；3rd, the operand involved by analytic hierarchy process (AHP) is little, and model is easily operated, it is simple to simplicity
Operation solve challenge；4th, total evaluation index can be quantified by analytic hierarchy process (AHP), each lower floor of quantitative study
The quantity of state index problem to the influence degree of the running status of power equipment.
It is similar to, in like manner, according to expert estimation, sets up the two-level index judgment matrix of each first class index, use maximum special
Value indicative method can obtain the weight of the corresponding quantity of state of all parts, as shown in table 4 below:
Table 4 two-level index (quantity of state) weight
Comment gathers in comment module can be arranged according to practical situation, and the embodiment of the present invention goes out from the angle of power equipment
Send out, Comment gathers is set as including following five kinds of comments: good, normal, suspicious, exception and danger.Wherein, dangerous: 0～60；
Abnormal: 60～70；Suspicious: 70～80；Normal: 80～90；Good: 90～100.Kilter refers to stable equipment operation, institute
There is quantity of state conformance with standard or away from exceptional value.Now, the probability of device fails is extremely low, can be with longtime running.Normal shape
State refers to that equipment state amount normally or wherein individual parameters shows that reliability is slightly decreased, but reaches far away exceptional value.Now, should
Overhaul according to equipment original repair schedule arrangement；Several quantity of states of suspicious state representation equipment do not meet standard, but do not affect
Equipment runs；Abnormality refer to equipment state amount close to or up the exceptional value in code, display device will or
Break down, but situation about will not have an accident in a short time.Now, the cycle of overhaul of the equipments should be reduced；Precarious position table
Show equipment state amount danger beyond exceptional value or jeopardy exception, equipment is in operation at any time it may happen that accident.Now, equipment should
This has a power failure immediately and overhauls.
The membership function in fuzzy evaluation module in the present embodiment triangle the most as shown in Figure 3 divides with trapezoidal combination
Cloth membership function, this membership function calculates relatively simple, and accuracy gap compared with complicated membership function is not very
Greatly.
In fuzzy set, the span of membership function codomain is [0,1], and membership function is as follows:
Membership function under kilter:
Membership function under normal condition:
Membership function under suspicious state:
Membership function under abnormality:
Membership function under precarious position:
Utilize the weight of above-mentioned membership function bonding state figureofmerit, the obtained health status for power equipment
Fuzzy evaluation conclusion is and is subordinate to ordered series of numbers, may be characterized as following form: { Xi}={ Xi(1),Xi(2),…Xi(5)}.Wherein, Xi
(1),Xi(2),…Xi(5) it is arbitrarily to be more than or equal to 0 real number less than or equal to 1, Xi(1) characterize power equipment and belong to kilter
Degree, Xi(2) characterize power equipment and belong to the degree of normal condition, Xi(3) characterize power equipment and belong to the journey of suspicious state
Degree, Xi(4) characterize power equipment and belong to the degree of abnormality, Xi(5) characterize power equipment and belong to the degree of precarious position.
Grey correlation theory is one of important component part of gray system theory, and be Grey System Analysis, modeling,
Prediction, the foundation stone of decision-making.Grey correlation analysis is unclear to operating mechanism and physical prototype or lacks physical prototype at all
Gray relation serializing, medelling, and then set up Grey Relation Analysis Model, make gray relation quantization, sequence, clear, energy
For the technical Analysis means that the modeling offer of complication system is important.Grey correlation theory is incorporated in fuzzy evaluation, utilizes mould
The fuzzy overall evaluation of the paste object degree of association to clear overall merit, determines the state grade of power equipment, overcomes person in servitude
The error that genus degree principle causes.
In order to obtain clear evaluation conclusion, the clear evaluation criterion in grey correlation module include kilter be [1,0,
0,0,0], normal condition is [0,1,0,0,0], and suspicious state is [0,0,1,0,0], and abnormality is [0,0,0,1,0], dangerous
State is [0,0,0,0,1]..Additionally include coefficient of association calculating sub module and calculation of relationship degree submodule.Wherein, specifically
:
Coefficient of association calculating sub module can calculate the coefficient of association of fuzzy evaluation conclusion and each clear evaluation criterion, the most logical
CrossCalculate the coefficient of association of fuzzy evaluation conclusion and each clear evaluation criterion, wherein, Δi(k)
=| X0(k)-Xi(k) |, X0K () is the element in clear evaluation criterion, k is the integer more than or equal to 1, less than or equal to 5, MminFor
Two-stage lowest difference, MmaxFor two-stage maximum difference.
Then, calculation of relationship degree submodule can based on the calculated whole coefficient of association of coefficient of association calculating sub module,
Pass throughCalculate the degree of association, this degree of association be required for the health state evaluation result accurately that obtains.
Further, in multi objective system, owing to the unit of each index is different, dimension is different, the order of magnitude is different, it is not easy to
Analyze, even can affect the result of evaluation.Therefore, for unified standard, all of evaluation index to be carried out nondimensionalization process,
To eliminate dimension, convert it into dimensionless, the differential other standard scores of incalculability, be analyzed the most again evaluating.
Degradation according to quantity of state index in the embodiment of the present invention, carries out nondimensionalization by score to quantity of state index
Processing, use hundred-mark system, score value is assigned to 100 points from 0, is divided into as danger threshold using 60, and 100 are divided into full marks each to cable run
Individual unit status is marked.Each quantity of state index score is the highest, shows that the running status of this quantity of state index is the best.
Therefore, in order to obtain scoring, the model for power equipment health state evaluation that the embodiment of the present invention provides is also
Including acquisition module, this acquisition module is for obtaining the scoring of each quantity of state index.
In a concrete application scenarios of the embodiment of the present invention, pacify bright II924 with west of a city branch office of Nanning power supply administration
The test of midium voltage cable circuit and to patrol and examine data be example, calculates its final corresponding degree of membership of various states.This track laying
Cable model be LSN 10/3.1-3X9.5m.This section of line load is the 70% of rated load；Insulation resistance test and initial value
Relatively there is no marked difference；Cable profile has little damage at two；Fire protection flame retarding all meets design requirement with buried depth；Cable termination
There is filth on surface, and slightly damaged, alternate temperature difference is 7K, and connector temperature is 70 DEG C, and fire protection flame retarding measure is perfect；In cable indirectly
Heating without exception, running environment is excellent, and medial head is without the most damaged, and fire protection flame retarding meets requirement；Down conductor outward appearance is good
Good, earth resistance is 8.7 Ω；Cable shaft is without hydrops, and cable pipe trench is without hydrops, without sinking, cable run protection zone running environment
Normally, fire protection flame retarding meets design requirement；Auxiliary equipment firmly installs, but has moderate corrosion, and mark setting height(from bottom) is not up to wanted
Ask.
Actual health status according to this section of cable run obtains each unit status and measures point as follows:
The each unit status of table 5 measures point
Final Comprehensive Evaluation result is: [0.9669,0.0369,0,0,0].Clearly pass judgment in conjunction with five kinds of states, with good
The degree of association of good state is 0.9669；It is 0.0369 with the degree of association of normal condition；It is 0 with the degree of association of suspicious state；With different
Often the degree of association of state is 0；It is 0 with the degree of association of precarious position.Therefore, provable this section of cable run operates in normal shape
State.
To sum up, embodiments providing a kind of model for power equipment health state evaluation, this model includes
Evaluation index module, comment module, fuzzy evaluation module and grey correlation module.These modules cooperate, and will more answer
Miscellaneous power equipment is divided into multiple quantity of state index, based on these quantity of state indexs, sets electric power in conjunction with grey correlation module
Standby health status is made in time, is assessed accurately, it is possible to make staff understand the healthy shape of corresponding power equipment in time
Condition, consequently facilitating carry out the operation such as reasonable employment and maintenance, failure predication and distribution management to it.
Through the above description of the embodiments, those skilled in the art is it can be understood that can borrow to the present invention
The mode helping software to add required common hardware realizes, naturally it is also possible to by hardware, but a lot of in the case of the former is more preferably
Embodiment.Based on such understanding, the portion that prior art is contributed by technical scheme the most in other words
Dividing and can embody with the form of software product, this computer software product is stored in the storage medium that can read, such as meter
The floppy disk of calculation machine, hard disk or CD etc., including some instructions with so that computer equipment (can be personal computer,
Server, or the network equipment etc.) perform the method described in each embodiment of the present invention.
The above, the only detailed description of the invention of the present invention, but protection scope of the present invention is not limited thereto, and any
Those familiar with the art, in the technical scope that the invention discloses, can readily occur in change or replace, should contain
Cover within protection scope of the present invention.Therefore, protection scope of the present invention should be as the criterion with described scope of the claims.
Claims (10)
1. the model for power equipment health state evaluation, it is characterised in that including:
Evaluation index module, described evaluation index module include the quantity of state index of multiple health status affecting power equipment with
And the weight of each quantity of state index；
Comment module, described comment module includes Comment gathers, for evaluating the health status of described power equipment；
Fuzzy evaluation module, described fuzzy evaluation module includes the membership function set up based on described Comment gathers, for by institute
State membership function and combine the weight of each quantity of state index, the health status of power equipment is carried out fuzzy evaluation, obtain fuzzy commenting
Valency conclusion；
Grey correlation module, described grey correlation module includes the clear evaluation criterion set up based on described Comment gathers, for right
Described fuzzy evaluation conclusion carries out clear evaluation process, obtains health state evaluation result accurately.
Model the most according to claim 1, it is characterised in that described Comment gathers include good, normal, suspicious, abnormal and
Dangerous five kinds of comments, wherein, dangerous: 0～60；Abnormal: 60～70；Suspicious: 70～80；Normal: 80～90；Good: 90～
100。
Model the most according to claim 2, it is characterised in that described membership function is that triangle is subordinate to trapezoidal combination distribution
Membership fuction.
Model the most according to claim 3, it is characterised in that described membership function includes:
Membership function under kilter:
Membership function under normal condition:
Membership function under suspicious state:
Membership function under abnormality:
Membership function under precarious position:
Model the most according to claim 4, it is characterised in that described fuzzy evaluation conclusion is characterized as { Xi}={ Xi(1),Xi
(2),…Xi(5) }, wherein, Xi(1),Xi(2),…Xi(5) it is arbitrarily to be more than or equal to 0 real number less than or equal to 1, Xi(1) institute is characterized
State power equipment and belong to the degree of kilter, Xi(2) characterize described power equipment and belong to the degree of normal condition, Xi(3) characterize
Described power equipment belongs to the degree of suspicious state, Xi(4) characterize described power equipment and belong to the degree of abnormality, Xi(5) table
Levy described power equipment and belong to the degree of precarious position.
6. according to the model described in any one of claim 2 to 5, it is characterised in that described clear evaluation criterion includes: good shape
State is [1,0,0,0,0], and normal condition is [0,1,0,0,0], and suspicious state is [0,0,1,0,0], abnormality be [0,0,0,
1,0], precarious position is [0,0,0,0,1].
Model the most according to claim 6, it is characterised in that described grey correlation module includes:
Coefficient of association calculating sub module, for calculating the coefficient of association of described fuzzy evaluation conclusion and each clear evaluation criterion；
Calculation of relationship degree submodule, for based on the calculated whole coefficient of association of described coefficient of association calculating sub module, meter
Calculate the degree of association, obtain health state evaluation result accurately.
Model the most according to claim 7, it is characterised in that described coefficient of association calculating sub module especially byCalculate the coefficient of association of described fuzzy evaluation conclusion and each clear evaluation criterion, wherein, Δi
(k)=| X0(k)-Xi(k) |, X0K () is the element in described clear evaluation criterion, k is whole more than or equal to 1, less than or equal to 5
Number, MminFor two-stage lowest difference, MmaxFor two-stage maximum difference.
Model the most according to claim 8, it is characterised in that described calculation of relationship degree submodule especially byCalculate the degree of association, obtain health state evaluation result accurately.
Model the most according to claim 1, it is characterised in that also include:
Acquisition module, described acquisition module is for obtaining the scoring of each quantity of state index.
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