CN107832973A - A kind of method of the equipment quality management and control based on polymorphism information Comprehensive Evaluation - Google Patents
A kind of method of the equipment quality management and control based on polymorphism information Comprehensive Evaluation Download PDFInfo
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Abstract
The invention discloses a kind of method of the equipment quality management and control based on polymorphism information Comprehensive Evaluation, merge controller switching equipment integration detection and controller switching equipment online monitoring data based on physical analogy, pass through the critical index of comprehensive analysis, structure reflection controller switching equipment running quality, objective and accurate evaluation is made to controller switching equipment overall operation quality, so as to provide scientific and effective technical support for controller switching equipment running quality management and control.The key that controller switching equipment running quality is assessed is the selection of running quality evaluation index and the foundation of assessment models.For the running quality of accurate evaluation controller switching equipment, consider ambiguity and randomness existing for controller switching equipment running quality index, establish the multi-level running quality assessment models of controller switching equipment of fusion multi objective, obtain integrating comprehensive controller switching equipment running quality assessment result, so as to scientificlly and effectively provide decision assistant for controller switching equipment quality management and control.
Description
Technical field
The present invention relates to a kind of method of the equipment quality management and control based on polymorphism information Comprehensive Evaluation.
Background technology
The key that controller switching equipment running quality is assessed is the selection of running quality evaluation index and the foundation of assessment models.
For the running quality of accurate evaluation controller switching equipment, ambiguity existing for controller switching equipment running quality index and random is considered
Property, the multi-level running quality assessment models of controller switching equipment of fusion multi objective are established, obtain integrating comprehensive controller switching equipment operation
Quality assessment result, so as to scientificlly and effectively provide decision assistant for controller switching equipment quality management and control.
Because the achievement data of controller switching equipment running quality has dual uncertainty, i.e. ambiguity and randomness in itself,
So relative inferiority degree section corresponding to different conditions grade will also take into full account this dual uncertainty.
And current equipment quality management and control is less able to take into full account dual uncertainty.
The content of the invention
The present invention is in order to solve the above problems, it is proposed that a kind of equipment quality management and control based on polymorphism information Comprehensive Evaluation
Method, the present invention consider ambiguity and randomness existing for controller switching equipment running quality index, establish fusion multi objective
The multi-level running quality assessment models of controller switching equipment, obtain integrating comprehensive controller switching equipment running quality assessment result, so as to
Scientificlly and effectively to provide decision assistant for controller switching equipment quality management and control, interval border value and shape are considered using normal cloud model
Dual uncertainty between state grade.
To achieve these goals, the present invention adopts the following technical scheme that：
A kind of method of the equipment quality management and control based on polymorphism information Comprehensive Evaluation, considers controller switching equipment running quality
Ambiguity existing for index and randomness, the multi-level running quality assessment models of controller switching equipment of fusion multi objective are established, obscured
Analytic hierarchy process (AHP) carries out assignment to each index of assessment models, and confirms the degree of membership under each index different conditions, using normal state
Cloud model considers the dual uncertainty between each running status interval border value and state grade, obtains synthesis and comprehensively matches somebody with somebody
Electric equipment running quality assessment result, it is embodied as the management and control of controller switching equipment quality and decision assistant is provided.
Further, the detection project from physical simulation experiment, functions of the equipments quantity of state, online monitoring data, annex fortune
6 market condition, operation patrol record and equipment operating environment aspects choose running quality evaluation index, establish distribution terminal equipment
Multi-level running quality evaluation system, problem is divided into destination layer, item layer and rule layer by controller switching equipment Evaluation System.
Based on Fuzzy AHP to detection project, state quantity of the equipment, online monitoring data and other shapes in item layer
State data target and its under specific targets assign weight.
Specifically, being compared two-by-two each factor, Judgement Matricies and the weight for determining each factor, obscuring layer is utilized
Fractional analysis introduces Triangular Fuzzy Number and classical matrix and its scaling law reciprocal is modified, and carries out one to resulting result
Cause property is examined.
According to coincident indicator and the ratio of Aver-age Random Consistency Index, consistency ration is obtained, works as consistency ration
When meeting setting value, it is believed that otherwise the uniformity of judgment matrix should be carried out in tolerance interval to the element in judgment matrix
Appropriate amendment, and consistency check is carried out again.
After meeting consistency check, logarithmic least square priority method is taken to try to achieve each factor weight.
Further, according to Monitoring Data, power distribution automation equipment operation shape is asked for using multilevel fuzzy synthetic evaluation method
State corresponds to the degree of membership of different conditions grade.
Specifically, using multilevel fuzzy synthetic evaluation method, multilevel fuzzy synthetic evaluation is classified in controller switching equipment running quality
On the premise of, the blurring model of each specific targets in agriculture products layer, the person in servitude of each state grade is corresponded to reference to each specific targets
Category degree, the fuzzy matrix for assessment of indicator layer is established, corresponding weight, choosing are assigned according to the relative importance between level between index
After taking suitable fuzzy operator, into the judge to item layer, the Comprehensive Evaluation result until obtaining destination layer.
Handled for the particular state factor under second layer index using fuzzy distribution, by particular state factor
Quantitative data is normalized by relative inferiority degree, is established respective relative inferiority degree and is corresponded to the fuzzy of each state grade
Membership function：The trapezoidal combined type fuzzy membership function of triangle-half, by the actual relative deterioration of a certain particular state factor
Degree substitutes into membership function and produces its degree of membership for different conditions grade, is each particular state using Fuzzy AHP
Factor assigns weight, finally selects the Comprehensive Evaluation of weighted average type to obtain this three classes state index for different conditions grade
Degree of membership.
Particular state factor under second layer index is handled using fuzzy distribution, by quantifying for particular state factor
Data are normalized by relative inferiority degree, establish the fuzzy membership that respective relative inferiority degree corresponds to each state grade
Spend function.
Further, the normal cloud model in relative inferiority degree section is built, the relatively bad of states at different levels is obtained according to model
Change degree desired value, calculate the good and bad value of distribution terminal equipment running quality.
Running quality degradation value is bigger or running quality assessment result numerical value shows more greatly the deterioration journey of self-operating quality
Degree is higher.
Compared with prior art, beneficial effects of the present invention are：
The status information of the invention for having merged each critical index for influenceing terminal device operation comprehensively, refers to taking into full account
On the premise of marking the dual uncertainty of parameter, controller switching equipment integration testing result and controller switching equipment based on physical analogy are relied on
Online monitoring data, establish controller switching equipment running quality assessment models that are highly reliable and easily carrying out.For the fortune of distribution secondary device
Row quality evaluation provides a kind of new approaches, and effective technology is provided to realize that comprehensive power distribution network equips running status management and control
Support.
Brief description of the drawings
The Figure of description for forming the part of the application is used for providing further understanding of the present application, and the application's shows
Meaning property embodiment and its illustrate be used for explain the application, do not form the improper restriction to the application.
Fig. 1 is the trapezoidal combined type fuzzy membership function figure of intermediate cam-half of the present invention；
Fig. 2 is distribution terminal equipment running quality evaluation system figure in the present invention；
Embodiment：
The invention will be further described with embodiment below in conjunction with the accompanying drawings.
It is noted that described further below is all exemplary, it is intended to provides further instruction to the application.It is unless another
Indicate, all technologies used herein and scientific terminology are with usual with the application person of an ordinary skill in the technical field
The identical meanings of understanding.
It should be noted that term used herein above is merely to describe embodiment, and be not intended to restricted root
According to the illustrative embodiments of the application.As used herein, unless the context clearly indicates otherwise, otherwise singulative
It is also intended to include plural form, additionally, it should be understood that, when in this manual using term "comprising" and/or " bag
Include " when, it indicates existing characteristics, step, operation, device, component and/or combinations thereof.
In the present invention, term as " on ", " under ", "left", "right", "front", "rear", " vertical ", " level ", " side ",
The orientation or position relationship of instructions such as " bottoms " are based on orientation shown in the drawings or position relationship, only to facilitate describing this hair
Bright each part or component structure relation and the relative determined, not refer in particular to either component or element in the present invention, it is impossible to understand
For limitation of the present invention.
In the present invention, term such as " affixed ", " connected ", " connection " should be interpreted broadly, and expression can be fixedly connected,
Can also be integrally connected or be detachably connected；Can be joined directly together, can also be indirectly connected by intermediary.For
The related scientific research of this area or technical staff, the concrete meaning of above-mentioned term in the present invention can be determined as the case may be,
It is not considered as limiting the invention.
The purpose of the present invention is the running quality of accurate evaluation controller switching equipment, considers controller switching equipment running quality index
Existing ambiguity and randomness, the multi-level running quality assessment models of controller switching equipment of fusion multi objective are established, are integrated
Comprehensive controller switching equipment running quality assessment result, it is auxiliary to provide decision-making so as to scientificlly and effectively for controller switching equipment quality management and control
Help.
A kind of method of the equipment quality management and control based on polymorphism information Comprehensive Evaluation, merges the distribution based on physical analogy and sets
Standby integration detection and controller switching equipment online monitoring data, the pass of controller switching equipment running quality is reflected by comprehensive analysis, structure
Key index, objective and accurate evaluation is made to controller switching equipment overall operation quality, so as to be controller switching equipment running quality management and control
Scientific and effective technical support is provided.Controller switching equipment running quality assess key be running quality evaluation index selection and
The foundation of assessment models.For the running quality of accurate evaluation controller switching equipment, the presence of controller switching equipment running quality index is considered
Ambiguity and randomness, establish the multi-level running quality assessment models of controller switching equipment of fusion multi objective, obtain comprehensive comprehensive
Controller switching equipment running quality assessment result, so as to scientificlly and effectively provide decision assistant for controller switching equipment quality management and control.
In a kind of typical embodiment of the application, a kind of apparatus management/control strategy of polymorphism information Comprehensive Evaluation, including
Following steps：
A, based on FAHP methods to four intermediate item indexs in item layer and its under specific targets assign weight；
B, according to Monitoring Data, power distribution automation equipment running status is asked for using multilevel fuzzy synthetic evaluation method and are corresponded to
Well, suspicious, reliability decrease and the degree of membership of dangerous 4 class state grades are respectively g1、g2、g3、g4；
C, according to the normal cloud model in relative inferiority degree section, it is known that the relative inferiority degree desired value of states at different levels is
[0.1,0.3,0.55,0.85], the good and bad value of distribution terminal equipment running quality is calculated according to the following formula：
H=0.1 × g1+0.3×g2+0.55×g3+0.85×g4 (1-1)
D, the running quality assessment result of i distribution terminal equipment is tried to achieve according to above formula, running quality degradation value is bigger or transports
Row quality assessment result numerical value shows that more greatly the degradation of self-operating quality is higher.
Detailed process in step A is as follows：
A1, the detection project from physical simulation experiment, functions of the equipments quantity of state, online monitoring data, annex running situation,
Run 6 aspects of patrol record and equipment operating environment and choose running quality evaluation index, establish the multilayer of distribution terminal equipment
Problem is divided into destination layer, item layer and rule layer by secondary running quality evaluation system, controller switching equipment Evaluation System.
A2, each factor is compared two-by-two, Judgement Matricies and the weight for determining each factor：FAHP introduces Triangle Module
Paste it is several classical matrix and its scaling law reciprocal are modified, Triangular Fuzzy Number can be expressed as θ=(p, q, r), wherein p and r
Its upper and lower bound is represented respectively, and q represents the maximum of its possibility, and revised scale is as shown in table 1, and the fuzzy of construction is sentenced
Disconnected matrix is A=(aij) n × n, aijFor the ratio between factor i and factor j importance, n is factor quantity, more reasonable in order to draw
As a result, it is desirable to comprehensive multiple expertises, such as it is following it is various shown in：
aij=(pij, qij, rij) (2-1)
In above formula, m is the quantity of expert, and k represents k-th of expert.
The factor important ratio of table 1 is compared with Fuzzy Scale
A3, consistency check：Because the complexity of objective fact and the limitation of human knowledge to acquired results, it is necessary to enter
Row consistency check, defining coincident indicator CI is：
In above formula, n be judgment matrix exponent number, fuzzy matrix Maximum characteristic root ask for be still research hot issue,
The present invention, using approximation method, the Aver-age Random Consistency Index RI according to table 2, counts as the following formula from engineering viewpoint
Calculate consistency ration CR：
The Aver-age Random Consistency Index of table 2
Work as CR<When 0.1, it is believed that otherwise the uniformity of judgment matrix tackles the member in judgment matrix in tolerance interval
Element carries out appropriate amendment, and carries out consistency check again.After meeting consistency check, logarithmic least square priority method can be taken to try to achieve
Each factor weight.
Detailed process in step B is as follows：
B1, using multilevel fuzzy synthetic evaluation method, multilevel fuzzy synthetic evaluation is before the classification of controller switching equipment running quality
Put, the blurring model of each specific targets in agriculture products layer, the degree of membership of each state grade corresponded to reference to each specific targets,
The fuzzy matrix for assessment of indicator layer is established, corresponding weight is assigned according to the relative importance between level between index, chooses and close
After suitable fuzzy operator, into the judge to last layer (item layer), the Comprehensive Evaluation knot until obtaining top (destination layer)
Fruit.Comprise the following steps that：
B11, establish and judge object set of factors, the running quality evaluation system of controller switching equipment is divided into 3 levels.Destination layer Ux
It can be analyzed to 4 components in item layer, i.e. Ux=(Ux1, Ux2, Ux3, Ux4), wherein Ux1Represent detection project, Ux2Represent equipment
Quantity of state, Ux3Represent online monitoring data, Ux4Other state indexs are represented, similarly, each project component in item layer again may be used
It is further broken into index component corresponding in indicator layer；
B12, establish Comment gathers, V=(v1, v2, v3, v4)=(is good, suspicious, reliable to decline, dangerous)；
B13, the fuzzy matrix for assessment for establishing each level, if the index u in evaluation system under certain sub-projectiCorresponding Comment gathers
V fuzzy membership is rij(j=1,2,3,4), then make Ri=(ri1, ri2, ri3, ri4) represent to press index uiState estimation knot
Fruit, all index condition evaluation results under the sub-project are formed into its corresponding fuzzy matrix for assessment, in summary, by right
The fuzzy evaluation of indicator layer can obtain the fuzzy matrix for assessment R of item layerj×4(j is the project sum that item layer is included), leads to
The fuzzy evaluation result of controller switching equipment integrated operation quality can be obtained by crossing the fuzzy evaluation of item layer；
B14, the weight for determining each evaluation factor.Fuzzy AHP (FAHP) is introduced between fuzzy variable modifying factor
Comparison scale to overcome the shortcomings of traditional analysis method (AHP).
B2, each index membership function and degree of membership determination, are comprised the following steps that：
B21, quantitative target fuzzy membership function and degree of membership determination：
Handled for the particular state factor under second layer index using fuzzy distribution, by particular state factor
Quantitative data is normalized by relative inferiority degree, is established respective relative inferiority degree and is corresponded to the fuzzy of each state grade
Membership function：The trapezoidal combined type fuzzy membership function of triangle-half, by the actual relative deterioration of a certain particular state factor
Degree substitutes into membership function and produces its degree of membership for different conditions grade, is assigned using FAHP methods for each particular state factor
Weight is given, finally selects the Comprehensive Evaluation of weighted average type to obtain this three classes state index being subordinate to for different conditions grade
Degree.
B22, qualitative index fuzzy membership function and degree of membership are asked for：
Assessment for annex running situation, operating maintenance record and running environment this 3 class status consideration substantially belongs to
Qualitative analysis, it includes many tiny numerous and diverse factors, and its direct progress quantitative analysis is assessed and certain difficulty be present.Our department
Divide and this 3 class factor is assessed first with the method for expert estimation.Set distribution terminal equipment score value section for [0,
1], 10 experts are invited to be given a mark respectively for this 3 class factor of terminal device.According to the qualifications and record of service of 10 experts, to 10
Expert assigns different weights, and marking of 10 experts to equipment same class factor is weighted into summation, as final score,
Equally use fuzzy distribution, by marking value calculated instead of relative inferiority degree.
Such as this index factor is assessed to annex running situation, expert's value of giving a mark is
In above formula：X is annex running situation institute score value；aiGiven a mark value by i-th bit expert；riFor the power of i-th bit expert
Weight.
Its corresponding Comment gathers V fuzzy membership function μ (x) is respectively：
Detailed process in step C is as follows：
C1, relative inferiority degree characterize relative deterioration of the current actual motion state of controller switching equipment compared with malfunction
Degree, for cost type index, span is [0,1], and the calculation formula of relative inferiority degree is as follows：
For profit evaluation model index, the calculation formula of relative inferiority degree is as follows：
In formula：liFor the relative inferiority degree of i-th of state index；C0For the permissible value (good value) of the index；CmaxOr Cmin
For the demand value of the index；CiFor the measured value of state index；K is the influence degree of Parameters variation equipment state, and the present invention takes
1。
C2, the state grade of distribution terminal running quality is divided into 4 grades, different conditions grade is relative with state index bad
Relation between change degree is as shown in the table；
The state grade of table 3 and relative inferiority degree section corresponding relation
C3, the normal cloud model in running quality grade relative inferiority degree section：
Cloud model is the uncertain conversion between some qualitativing concept A and its quantificational expression represented with natural language value
Model, a kind of currently used cloud model evaluation method include 3 set：
Index set：U={ U0, U1, U2..., Um, U0 is purpose index, and other are to divide index；
Weight sets：V={ v0, v1, v2, vm, vi>=0 and v0+v1+v2+...+vm=1；
Comment gathers：W={ w0, w1, w2... wm}
Due to the fuzzy concept of comment always " good, in, poor " etc, can describe each to comment using One-Dimensional Normal Cloud
Language, for bilateral constraint [C be presentmin, Cmax] comment, can be with desired value constraints intermediate value, main function region is
The cloud in bilateral constraint region carrys out approximate representation this comment, and the calculation formula of cloud parameter is as follows：
Ex=(Cmin, Cmax)/2 (4-3)
En=(Cmax, Cmin)/6 (4-4)
He=k (4-5)
Because the achievement data of controller switching equipment running quality has dual uncertainty, i.e. ambiguity and randomness in itself,
So relative inferiority degree section corresponding to different conditions grade will also take into full account this dual uncertainty, using Normal Cloud mould
Type considers the dual uncertainty between interval border value and state grade.The Normal Cloud in state grade relative inferiority degree section
Model is as shown in table 4.
The normal cloud model in the relative inferiority degree section of table 4
Detailed process in step D is as follows：
H=0.1 × g1+0.3×g2+0.55×g3+0.85Xg4 (5-1)
The running quality assessment result of i distribution terminal equipment is tried to achieve according to above formula, running quality degradation value is bigger or runs
Quality assessment result numerical value shows that more greatly the degradation of self-operating quality is higher.
The preferred embodiment of the application is the foregoing is only, is not limited to the application, for the skill of this area
For art personnel, the application can have various modifications and variations.It is all within spirit herein and principle, made any repair
Change, equivalent substitution, improvement etc., should be included within the protection domain of the application.
Although above-mentioned the embodiment of the present invention is described with reference to accompanying drawing, model not is protected to the present invention
The limitation enclosed, one of ordinary skill in the art should be understood that on the basis of technical scheme those skilled in the art are not
Need to pay various modifications or deformation that creative work can make still within protection scope of the present invention.
Claims (10)
1. a kind of method of the equipment quality management and control based on polymorphism information Comprehensive Evaluation, it is characterized in that：Consider controller switching equipment
Ambiguity and randomness existing for running quality index, the multi-level running quality of controller switching equipment for establishing fusion multi objective assess mould
Type, Fuzzy AHP carries out assignment to each index of assessment models, and confirms the degree of membership under each index different conditions, adopts
The dual uncertainty between each running status interval border value and state grade is considered with normal cloud model, is obtained comprehensive complete
The controller switching equipment running quality assessment result in face, it is embodied as the management and control of controller switching equipment quality and decision assistant is provided.
2. a kind of method of the equipment quality management and control based on polymorphism information Comprehensive Evaluation as claimed in claim 1, it is characterized in that：
Detection project, functions of the equipments quantity of state, online monitoring data, annex running situation, operation inspection note from physical simulation experiment
6 aspects of record and equipment operating environment choose running quality evaluation index, establish the multi-level running quality of distribution terminal equipment
Problem is divided into destination layer, item layer and rule layer by evaluation system, controller switching equipment Evaluation System.
3. a kind of method of the equipment quality management and control based on polymorphism information Comprehensive Evaluation as claimed in claim 1, it is characterized in that：
Detection project, state quantity of the equipment, online monitoring data and other status datas in item layer are referred to based on Fuzzy AHP
Mark and its lower specific targets imparting weight.
4. a kind of method of the equipment quality management and control based on polymorphism information Comprehensive Evaluation as claimed in claim 3, it is characterized in that：
Each factor is compared two-by-two, Judgement Matricies and the weight for determining each factor, three are introduced using Fuzzy AHP
Angle fuzzy number is modified to classical matrix and its scaling law reciprocal, and carries out consistency check to resulting result.
5. a kind of method of the equipment quality management and control based on polymorphism information Comprehensive Evaluation as claimed in claim 1, it is characterized in that：
According to coincident indicator and the ratio of Aver-age Random Consistency Index, consistency ration is obtained, when consistency ration meets to set
During value, it is believed that otherwise the uniformity of judgment matrix should carry out appropriate repair in tolerance interval to the element in judgment matrix
Just, consistency check and is carried out again.
6. a kind of method of the equipment quality management and control based on polymorphism information Comprehensive Evaluation as claimed in claim 1, it is characterized in that：
According to Monitoring Data, power distribution automation equipment running status are asked for corresponding to different conditions etc. using multilevel fuzzy synthetic evaluation method
The degree of membership of level.
7. a kind of method of the equipment quality management and control based on polymorphism information Comprehensive Evaluation as claimed in claim 6, it is characterized in that：
Using multilevel fuzzy synthetic evaluation method, multilevel fuzzy synthetic evaluation is on the premise of controller switching equipment running quality is classified, it is determined that referring to
The blurring model of each specific targets in layer is marked, the degree of membership of each state grade is corresponded to reference to each specific targets, establishes indicator layer
Fuzzy matrix for assessment, assign corresponding weight according to relative importance between index between level, choose suitable fuzzy calculate
After son, into the judge to item layer, the Comprehensive Evaluation result until obtaining destination layer.
8. a kind of method of the equipment quality management and control based on polymorphism information Comprehensive Evaluation as claimed in claim 1, it is characterized in that：
Handled for the particular state factor under second layer index using fuzzy distribution, by the quantitative data of particular state factor
It is normalized by relative inferiority degree, establishes the fuzzy membership letter that respective relative inferiority degree corresponds to each state grade
Number：The trapezoidal combined type fuzzy membership function of triangle-half, the actual relative inferiority degree of a certain particular state factor is substituted into and is subordinate to
Category degree function produces its degree of membership for different conditions grade, is assigned using Fuzzy AHP for each particular state factor
Weight, finally the Comprehensive Evaluation of weighted average type is selected to obtain degree of membership of this three classes state index for different conditions grade.
9. a kind of method of the equipment quality management and control based on polymorphism information Comprehensive Evaluation as claimed in claim 1, it is characterized in that：
Particular state factor under second layer index is handled using fuzzy distribution, and the quantitative data of particular state factor is passed through
Relative inferiority degree is normalized, and establishes the fuzzy membership function that respective relative inferiority degree corresponds to each state grade.
10. a kind of method of the equipment quality management and control based on polymorphism information Comprehensive Evaluation as claimed in claim 1, its feature
It is：The normal cloud model in relative inferiority degree section is built, the relative inferiority degree desired value of states at different levels is obtained according to model, is calculated
The good and bad value of distribution terminal equipment running quality；
Running quality degradation value is bigger or running quality assessment result numerical value shows more greatly the degradation of self-operating quality more
It is high.
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