CN105975735A - Modeling method for assessing health state of power equipment - Google Patents
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Abstract
The invention discloses a modeling method for assessing the health state of power equipment, and relates to the technical field of electric power. By means of the modeling method, the operating health state characteristics of the power equipment can be modeled, and thus the operation of reasonable use and maintenance, failure prediction, power distribution management and the like can be conveniently carried out on the power equipment. The modeling method for assessing the health state of the power equipment includes the steps that state quantity indexes reflecting the operating state of the power equipment are acquired; a judgment matrix is established through the analytic hierarchy process; the weights of the state quantity indexes are acquired based on the judgment matrix; a fuzzy assessment set suitable for the power equipment is established; the state quantity indexes are made dimensionless; the subjection degrees of the dimensionless state quantity indexes to the fuzzy assessment set are acquired, and a subjection sequence of the power equipment is established; the subjection sequence is processed based on the grey relation theory, and a model for assessing the health state of the power equipment is obtained.
Description
Technical field
The present invention relates to technical field of electric power, particularly relate to a kind of modeling method 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 make because of network system fault
The economic loss become upper trillion, the main cause analyzing it is that the fault to network system can not process in time.
Perform the periodic inspection system that the whole nation is unified because of China's electric power enterprise, its substitutive characteristics is simple with the time the most always
Based on cycle.This pattern is clearly present and does not considers in the actual state of equipment, maintenance process that specific aim is strong, grasp equipment
State not, do not meet the fault observer in existing power equipment life-span, produce the bad problem such as negative effect of excess maintenance etc,
Obviously, whether troubleshooting system improves the reliability level directly affecting power equipment, therefore by the operation health to power equipment
State characteristic is modeled, and operates for its reasonable employment and maintenance, failure predication and distribution management etc., has particularly important
Meaning.
Summary of the invention
The technical problem to be solved is to provide a kind of modeling method for power equipment health state evaluation, it is possible to
Realize the operation health status characteristic of power equipment is modeled, consequently facilitating it is pre-that it is carried out reasonable employment and maintenance, fault
Survey and distribution management etc. operates.
For solving above-mentioned technical problem, the present invention adopts the following technical scheme that
This modeling method being used for power equipment health state evaluation includes:
Obtain the quantity of state index of the running status reflecting described power equipment；
Utilize analytic hierarchy process (AHP), set up judgment matrix；
Based on described judgment matrix, obtain the weight of each quantity of state index；
Set up the fuzzy evaluation collection being applicable to described power equipment；
Each quantity of state index is carried out nondimensionalization process；
According to each quantity of state index subjection degree to described fuzzy evaluation collection, obtain the membership function of described power equipment；
Utilize grey correlation theory, weight, nondimensionalization result and membership function of based on described each quantity of state index,
Obtain being applicable to the model of described power equipment health state evaluation.
Preferably, utilize analytic hierarchy process (AHP), set up judgment matrix and include:
It is grouped based on the membership between each quantity of state index, sets up orderly flight aggregated(particle) structure；
Based on the described flight aggregated(particle) structure set up, setting up judgment matrix, the element of described judgment matrix is subordinate to for belonging to same
The comparative result of the index of quantity of state two-by-two of relation.
Preferably, based on described judgment matrix, the weight obtaining each quantity of state index includes:
Based on the judgment matrix set up, by the way of comparing two-by-two, determine each state in same membership and same level
The relative importance of figureofmerit；
According to the practical situation of described power equipment, obtain the weight of each quantity of state index.
Preferably, based on described judgment matrix, after obtaining the weight of each quantity of state index, also include:
Weight acquired in utilization, it is judged that whether described judgment matrix meets concordance；
If not meeting, need to revise the judgment matrix set up and weight.
Preferably, state the weight to each quantity of state index carry out nondimensionalization process include:
According to the degradation of each quantity of state index, by score, each quantity of state index is carried out nondimensionalization process.
Preferably, obtain the subjection degree to described fuzzy evaluation collection of each quantity of state index after nondimensionalization processes, set up described
The ordered series of numbers that is subordinate to of power equipment includes:
Set up triangle and trapezoidal combination distribution membership function；
Based on described triangle and trapezoidal combination distribution membership function, obtain each quantity of state index after nondimensionalization processes to described
The subjection degree of fuzzy evaluation collection, thus set up described power equipment be subordinate to ordered series of numbers.
Preferably, utilize grey correlation theory, described in process, be subordinate to ordered series of numbers, obtain being applicable to described power equipment health status and comment
The model estimated includes:
Set up the reference sequence concentrating arbitrary evaluation for described fuzzy evaluation；
Utilize grey correlation theory, determine described in be subordinate to the degree of association of ordered series of numbers and each reference sequence, obtain being applicable to described electric power and set
The model of standby health state evaluation.
Preferably, determine that the degree of association being subordinate to ordered series of numbers and each reference sequence includes:
Obtain each described reference sequence and the described coefficient of association being subordinate to ordered series of numbers；
Based on described coefficient of association, determine described in be subordinate to the degree of association of ordered series of numbers and each described reference sequence.
Preferably, it is applicable to the fuzzy evaluation collection of power equipment described in and includes following evaluation:
Well, normal, suspicious, exception and danger.
Preferably, described reference sequence includes:
Kilter is [1,0,0,0,0], and 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], precarious position is [0,0,0,0,1].
In the inventive solutions, use process and the step of analytic hierarchy process (AHP), including therein such as structure two multilevel iudge
Matrix and the mathematical method of matrix operations, determine for certain element of last layer time, element associated therewith in this level
Importance ranking relative weight, calculates each layer element synthetic weight to aims of systems, etc., all with conventional step analysis
Method is identical.
The invention provides a kind of modeling method for power equipment health state evaluation, first this modeling method uses level to divide
Analysis method, is the little task analyzing each quantity of state index by the big task subdivision of power equipment health state evaluation；Obtain every afterwards
The weight of one quantity of state index, understands the impact on power equipment health state evaluation of each quantity of state index；Finally, by ash
Color relevance theory, carries out clear overall merit to fuzzy overall evaluation, finally give for power equipment health state evaluation
Model accuracy is high, it is possible to make staff understand the health status of corresponding power equipment in time, consequently facilitating carry out it
Reasonable employment and maintenance, failure predication and distribution management etc. operate.
Accompanying drawing explanation
In order to be illustrated more clearly that the embodiment of the present invention or technical scheme of the prior art, required in embodiment being described below
Accompanying drawing to be used is briefly described, it should be apparent that, the accompanying drawing in describing below is only some embodiments of the present invention,
For those of ordinary skill in the art, on the premise of not paying creative work, it is also possible to obtain it according to these accompanying drawings
His accompanying drawing.
The flow chart of the modeling method 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 clearly and completely retouched
State, it is clear that described embodiment is a part of embodiment of the present invention rather than whole embodiments.Based in the present invention
Embodiment, the every other embodiment that those of ordinary skill in the art are obtained under not making creative work premise, all belong to
In the scope of protection of the invention.
Embodiments provide a kind of modeling method for power equipment health state evaluation, as it is shown in figure 1, this modeling
Method includes:
Step S101, acquisition reflect the quantity of state index of the running status of power equipment.
Realize the health status of power equipment is accurately and comprehensively assessed, need accurate assurance can reflect the shape of its running status
State amount, and the operability of bonding state assessment, define and comprise Test Information, operation information, patrol and examine the state quantity set of information
Close, establish evaluating status of electric power index system.Evaluation index system is divided into two grades, and two-level index is quantity of state.As
Shown in Fig. 2, for the power cable in power equipment, the present invention can use nine scales analytic hierarchy process ask for each state
Amount weight.
As a example by cable run, for cable run, the factor affecting its running status substantially can include cable body, electricity
Cable terminal, cable intermediate joint, earthed system, cable passage and auxiliary equipment etc. six, each of which Xiang Douke is sub-divided into
Multinomial quantity of state index.Such as, for cable body, its can be subdivided into line load, insulation resistance, distortion of the cable,
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 etc.
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 embodiment of the present invention can use analytic hierarchy process (AHP), on the healthy shape affecting power equipment
Every quantity of state index of state is analyzed.
Step S102, utilize analytic hierarchy process (AHP), set up judgment matrix.
Analytic hierarchy process (AHP) (The Analytic Hierarchy Process, be called for short AHP) rationale here is that policymaker is according to set
Standard and principle, every complicated factor of object to be evaluated is simplified, and sets up and pass stepwise hierarchical structure.Pass stepwise layer
Complicated problem can be become simplified as by aggregated(particle) structure, methodization, stratification.Pass stepwise hierarchical structure generally comprise 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 and realizes this predetermined mesh
The required intermediate link of mark；Indicator layer is to realize index, scheme that predeterminated target used etc..
In embodiments of the present invention, judge on same level according to judgment matrix 1～9 grades of scale principles (as shown in table 1 below)
Important relationship between two elements, obtains judgment matrix.Wherein matrix element represents each first class index element XiRelative to XjImportant
The quantized value of property, 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, it should be noted that
V1, V2, V3, V4, V5, V6 in table 2 represents cable itself, cable termination, cable intermediate joint, ground connection respectively
System, cable passage and auxiliary equipment:
Table 2 cable run first class index judgment matrix
Step S103, based on judgment matrix, obtain the weight of each quantity of state index.
AHP method is to be several compositing factors complicated PROBLEM DECOMPOSITION, these factors is divided by interrelated degree and membership
Group forms orderly flight aggregated(particle) structure, forms a multi-level assay model, determines layer by the way of comparing two-by-two
The relative importance of each factor in secondary, then according to practical situation, to determine the weight coefficient of each factor.The method is based on expert
Subjective degree to indices importance, has certain persuasion dynamics.Analytic hierarchy process (AHP) asks for the method for weight to be had several
What averaging 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 weight of AHP method is only
Have and passed through consistency check and 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 can
Lean on；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 passes through consistency check.
The calculated weight of AHP method has only been passed through consistency check and just can have been used, and this has just ensured the science of weight
With reasonability；Second, general objective is turned to orderly some levels and some elements, it is many that this is particularly well-suited to the system of having levels
Metrics evaluation object；3rd, the operand involved by analytic hierarchy process (AHP) is little, and model is easily operated, it is simple to easy operation
Solve challenge；4th, total evaluation index can be quantified by analytic hierarchy process (AHP), the quantity of state of each lower floor of quantitative study
The 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 eigenvalue of maximum
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
Step S103, foundation are applicable to the fuzzy evaluation collection of power equipment.
For cable run, the state demarcation of cable run is " well ", " normally ", " suspicious ", " different by the embodiment of the present invention
Often ", " dangerous " five kinds of states, i.e. determine that fuzzy evaluation collection V={ is good, normal, suspicious, exception, danger, wherein, danger
Danger: 0～60；Abnormal: 60～70；Suspicious: 70～80；Normal: 80～90；Good: 90～100.Kilter refers to equipment
Stable, all quantity of state conformance with standard or away from exceptional value.Now, the probability of device fails is extremely low, can be long-term
Run.Normal condition refers to that equipment state amount normally or wherein individual parameters shows that reliability is slightly decreased, but reaches far away abnormal
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 the equipment that do not affects runs；Abnormality refer to equipment state amount close to or up the exceptional value in code, display device will or
Person has been broken down, but situation about will not have an accident in a short time.Now, the cycle of overhaul of the equipments should be reduced；Dangerous
State representation equipment state amount danger exceeds exceptional value or jeopardy exception, and equipment is in operation at any time it may happen that accident.Now,
Equipment should have a power failure immediately and overhaul.
Step S104, each quantity of state index is carried out nondimensionalization process.
In multi objective system, owing to the unit of each index is different, dimension is different, the order of magnitude is different, be not easy to analysis, even can
The result that impact is evaluated.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.
In multiple attribute synthetical evaluation, different evaluation index often has different dimensions and dimensional unit, directly they is carried out
It is comprehensively inappropriate, also there is no practical significance.So desired value must be converted into nondimensional relative number.This remove finger
The nondimensionalization (the most unison quantization) of the process of scalar guiding principle, referred to as index, it is the premise of index comprehensive.At multiple index evaluation
In practice, often using numerical value later for indices non-dimension as metrics evaluation value, now, nondimensionalization process is exactly that index is actual
Value is converted into the process of metrics evaluation value (i.e. utility function value), and nondimensionalization method namely refers to how to realize this conversion.
Therefore, the nondimensionalization of index is an important content of overall merit, has a major impact comprehensive evaluation result.
The most common nondimensionalization method name is a lot, as composite index law, range transformation method, senior middle school's difference converter technique, low in
Difference converter technique, equalization method, Standardization Act, hydrometer method, efficiency coefficient method, exponential type efficiency coefficient method, logarithmic effect system
Number method, normal transformations method etc..
Degradation according to quantity of state index in the embodiment of the present invention, carries out nondimensionalization process by score to quantity of state index,
Using hundred-mark system, score value assigns to 100 points from 0, is divided into as danger threshold using 60,100 be divided into full marks to cable run each
Unit status is given a mark.Each quantity of state index score is the highest, shows that the running status of this quantity of state index is the best.
The each quantity of state index after step S105, the acquisition nondimensionalization process subjection degree to fuzzy evaluation collection, sets up electric power and sets
Standby is subordinate to ordered series of numbers.
The determination being subordinate to ordered series of numbers is a highly important key element in assessment.The ordered series of numbers that is subordinate to of power equipment has reacted each state
Measure the subjection degree for each Comment gathers.Subjection degree is determined by membership function.It is whether reasonable that membership function is chosen,
It is directly connected to the accuracy of final assessment result.
Embodiment of the present invention triangle the most as shown in Figure 3 and trapezoidal combination distribution membership function, this membership function calculates
Relatively simple, and accuracy gap compared with complicated membership function is not the biggest.
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:
Step S106, utilize grey correlation theory, be subordinate to ordered series of numbers described in process, obtain being applicable to power equipment health state evaluation
Model.
Grey correlation theory is one of important component part of gray system theory, and be Grey System Analysis, model, predict,
The foundation stone of decision-making.Grey correlation analysis is that the Lycoperdon polymorphum Vitt that lack physical prototype unclear or basic to operating mechanism and physical prototype is closed
System's serializing, medelling, and then set up Grey Relation Analysis Model, makes gray relation quantizations, sequence, clear, can be complexity
The modeling of system provides important technical Analysis means.Grey correlation theory is incorporated in fuzzy evaluation, utilizes fuzzy object
The fuzzy overall evaluation degree of association to clear overall merit, determines the state grade of power equipment, overcomes degree of membership principle and makes
The error become.
If reference sequence is { X0, being compared ordered series of numbers is { Xi}={ Xi(1),Xi(2),…Xi(n) }, then definition reference sequence with by than
As follows at the coefficient of association of k point compared with ordered series of numbers:
Wherein: Δi(k)=| X0(k)-Xi(k) |, MminFor two-stage lowest difference, MmaxFor two-stage maximum difference.
Then reference sequence is as follows with degree of association r being compared ordered series of numbers:
The clear judge of five reference sequences that the embodiment of the present invention uses are corresponding five kinds of different conditions.Five kinds of states are: good
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], and abnormality is [0,0,0,1,0], danger
Danger state is [0,0,0,0,1].
Obviously, the above-mentioned ordered series of numbers that compared is and is subordinate to ordered series of numbers.
In a concrete application scenarios of the embodiment of the present invention, pacify piezoelectricity in bright II924 with west of a city branch office of Nanning power supply administration
The test on cable road and to patrol and examine data be example, calculates its final corresponding degree of membership of various states.The cable-type of this track laying
Number it is LSN 10/3.1-3X9.5m.This section of line load is the 70% of rated load；Insulation resistance test compares with initial value and does not show
Write difference；Cable profile has little damage at two；Fire protection flame retarding all meets design requirement with buried depth；There is filth on cable termination surface,
Slightly damaged, alternate temperature difference is 7K, and connector temperature is 70 DEG C, and fire protection flame retarding measure is perfect；Cable intermediate joint is without exception
Heating, 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, ground connection
Resistance is 8.7 Ω；Cable shaft is without hydrops, and cable pipe trench is without hydrops, without sinking, and cable run protection zone running environment is normal, anti-
The fire-retardant satisfied design requirement of fire；Auxiliary equipment firmly installs, but has moderate corrosion, and mark setting height(from bottom) is not up to requirement.
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 kilter
The degree of association 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 abnormality
The degree of association is 0；It is 0 with the degree of association of precarious position.Therefore, provable this section of cable run operates in normal condition.
In sum, a kind of modeling method for power equipment health state evaluation, this modeling side are embodiments provided
First method uses analytic hierarchy process (AHP), is the little of each quantity of state index of analysis by the big task subdivision of power equipment health state evaluation
Task；Obtain the weight of each quantity of state index afterwards, understand each quantity of state index shadow to power equipment health state evaluation
Ring；Finally, by grey correlation theory, fuzzy overall evaluation being carried out clear overall merit, finally give sets for electric power
The model accuracy of standby health state evaluation is high, it is possible to make staff understand the health status of corresponding power equipment in time,
Consequently facilitating it is carried out the operation such as reasonable employment and maintenance, failure predication and distribution management.
Through the above description of the embodiments, those skilled in the art it can be understood that to the present invention can be by software
The mode adding 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 party
Formula.Based on such understanding, the part that prior art is contributed by technical scheme the most in other words can be with soft
The form of part product embodies, and this computer software product is stored in the storage medium that can read, such as the floppy disk of computer,
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 familiar
Those skilled in the art, in the technical scope that the invention discloses, can readily occur in change or replace, should contain at this
Within the protection domain of invention.Therefore, protection scope of the present invention should be as the criterion with described scope of the claims.
Claims (10)
1. the modeling method for power equipment health state evaluation, it is characterised in that including:
Obtain the quantity of state index of the running status reflecting described power equipment；
Utilize analytic hierarchy process (AHP), set up judgment matrix；
Based on described judgment matrix, obtain the weight of each quantity of state index；
Set up the fuzzy evaluation collection being applicable to described power equipment；
Each quantity of state index is carried out nondimensionalization process；
Obtain the subjection degree to described fuzzy evaluation collection of each quantity of state index after nondimensionalization processes, set up described power equipment
Be subordinate to ordered series of numbers；
Utilize grey correlation theory, described in process, be subordinate to ordered series of numbers, obtain being applicable to the model of described power equipment health state evaluation.
Modeling method the most according to claim 1, it is characterised in that utilize analytic hierarchy process (AHP), sets up judgment matrix bag
Include:
It is grouped based on the membership between each quantity of state index, sets up orderly flight aggregated(particle) structure；
Based on the described flight aggregated(particle) structure set up, setting up judgment matrix, the element of described judgment matrix is subordinate to for belonging to same
The comparative result of the index of quantity of state two-by-two of relation.
Modeling method the most according to claim 2, it is characterised in that based on described judgment matrix, obtains each quantity of state
The weight of index includes:
Based on the judgment matrix set up, by the way of comparing two-by-two, determine each state in same membership and same level
The relative importance of figureofmerit；
According to the practical situation of described power equipment, obtain the weight of each quantity of state index.
Modeling method the most according to claim 3, it is characterised in that based on described judgment matrix, obtains each quantity of state
After the weight of index, also include:
Weight acquired in utilization, it is judged that whether described judgment matrix meets concordance；
If not meeting, need to revise the judgment matrix set up and weight.
Modeling method the most according to claim 4, it is characterised in that the described weight to each quantity of state index carries out nothing
Dimensionization processes and includes:
According to the degradation of each quantity of state index, by score, each quantity of state index is carried out nondimensionalization process.
6. according to the modeling method described in any one of claim 1 to 5, it is characterised in that after obtaining nondimensionalization process
Each quantity of state index subjection degree to described fuzzy evaluation collection, the ordered series of numbers that is subordinate to setting up described power equipment includes:
Set up triangle and trapezoidal combination distribution membership function；
Based on described triangle and trapezoidal combination distribution membership function, obtain each quantity of state index after nondimensionalization processes to described
The subjection degree of fuzzy evaluation collection, thus set up described power equipment be subordinate to ordered series of numbers.
Modeling method the most according to claim 6, it is characterised in that utilize grey correlation theory, is subordinate to described in process
Ordered series of numbers, the model obtaining being applicable to described power equipment health state evaluation includes:
Set up the reference sequence concentrating arbitrary evaluation for described fuzzy evaluation；
Utilize grey correlation theory, determine described in be subordinate to the degree of association of ordered series of numbers and each reference sequence, obtain being applicable to described electric power and set
The model of standby health state evaluation.
Modeling method the most according to claim 7, it is characterised in that determine and be subordinate to associating of ordered series of numbers and each reference sequence
Degree includes:
Obtain each described reference sequence and the described coefficient of association being subordinate to ordered series of numbers；
Based on described coefficient of association, determine described in be subordinate to the degree of association of ordered series of numbers and each described reference sequence.
Modeling method the most according to claim 8, it is characterised in that described in be applicable to the fuzzy evaluation collection of power equipment
Including following evaluation:
Well, normal, suspicious, exception and danger.
Modeling method the most according to claim 9, it is characterised in that described reference sequence includes:
Kilter is [1,0,0,0,0], and 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], precarious position is [0,0,0,0,1].
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| CN111062500A (en) * | 2019-12-05 | 2020-04-24 | 国网电力科学研究院武汉南瑞有限责任公司 | Power equipment evaluation method based on discrete fuzzy number and analytic hierarchy process |
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| CN111612296A (en) * | 2020-04-10 | 2020-09-01 | 中国南方电网有限责任公司超高压输电公司检修试验中心 | Method for quantitatively configuring online monitoring device of power equipment of converter station |
| CN111865873A (en) * | 2019-04-26 | 2020-10-30 | 中国移动通信集团河北有限公司 | Safety early warning method, device and system |
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| CN113722656A (en) * | 2021-07-28 | 2021-11-30 | 国网浙江省电力有限公司电力科学研究院 | Method and system for evaluating real-time health degree of thermal generator set |
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Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103530823A (en) * | 2013-10-25 | 2014-01-22 | 湖南大学 | Comprehensive microgrid planning and design evaluation system based on OTFN-AHP |
| CN103617371A (en) * | 2013-12-10 | 2014-03-05 | 国家电网公司 | Method for comprehensively evaluating electric energy quality based on grey theory |
| CN103678943A (en) * | 2013-12-31 | 2014-03-26 | 国家电网公司 | Multi-index fuzzy evaluation method for grid faults caused by disasters |
| CN105225033A (en) * | 2015-09-08 | 2016-01-06 | 国家电网公司 | A kind of substation energy efficiency evaluating method based on analytical hierarchy process |
| CN105243611A (en) * | 2015-11-11 | 2016-01-13 | 国家电网公司 | Clustered building coordination capacity allocation method based on load energy efficiency evaluation |
| CN105631771A (en) * | 2016-03-01 | 2016-06-01 | 国家电网公司 | Variable weight function-based multi-parameter cable state evaluation method |
-
2016
- 2016-07-19 CN CN201610571276.4A patent/CN105975735B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103530823A (en) * | 2013-10-25 | 2014-01-22 | 湖南大学 | Comprehensive microgrid planning and design evaluation system based on OTFN-AHP |
| CN103617371A (en) * | 2013-12-10 | 2014-03-05 | 国家电网公司 | Method for comprehensively evaluating electric energy quality based on grey theory |
| CN103678943A (en) * | 2013-12-31 | 2014-03-26 | 国家电网公司 | Multi-index fuzzy evaluation method for grid faults caused by disasters |
| CN105225033A (en) * | 2015-09-08 | 2016-01-06 | 国家电网公司 | A kind of substation energy efficiency evaluating method based on analytical hierarchy process |
| CN105243611A (en) * | 2015-11-11 | 2016-01-13 | 国家电网公司 | Clustered building coordination capacity allocation method based on load energy efficiency evaluation |
| CN105631771A (en) * | 2016-03-01 | 2016-06-01 | 国家电网公司 | Variable weight function-based multi-parameter cable state evaluation method |
Cited By (34)
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| CN106447210A (en) * | 2016-10-10 | 2017-02-22 | 国家电网公司 | Distribution network equipment health degree dynamic diagnosis method involving credibility evaluation |
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