CN103389448B - GIS equipment operational condition online test method and system - Google Patents
GIS equipment operational condition online test method and system Download PDFInfo
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- CN103389448B CN103389448B CN201310330476.7A CN201310330476A CN103389448B CN 103389448 B CN103389448 B CN 103389448B CN 201310330476 A CN201310330476 A CN 201310330476A CN 103389448 B CN103389448 B CN 103389448B
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Abstract
The invention provides a kind of GIS equipment operational condition online test method and system, first the relative standard deviation values between the eigenwert of GIS device and reference characteristic value is calculated, afterwards according to described eigenwert definition space weight coefficient array, again according to described relative standard deviation values size, corresponding weight coefficient is chosen from the weight coefficient array of space, weight coefficient corresponding to relative standard deviation values for relative standard deviation values is multiplied and obtains individual deviate, choose the different detection moment and repeat above-mentioned computation process, obtain multiple individual deviate, finally individual deviate is added up, obtain space distribution statistical value, according to space distribution statistical value, determine GIS equipment operational condition.Owing to have employed the detection analysis containing weight, consider the incipient fault that the serious historical data of extent of deviation more effectively can disclose GIS device, can accurately reflect current GIS equipment running status.
Description
Technical field
The present invention relates to online measuring technique field, particularly relate to GIS equipment operational condition online test method and system.
Background technology
Intelligent gas insulation in combined electric appliance (GasInsulatedSwitchgear, GIS device) is that the construction for adapting to intelligent grid puts forward, and in electric system, play protection and control action, its reliability directly affects the safe operation of whole electrical network.The infrastructure device of intelligent grid is the primary equipment of intelligence, and the construction of intelligent grid be unable to do without the intelligent construction comprising the primary equipments such as GIS device, and GIS device intelligent construction degree direct influence intelligent substation, informationization.Along with the raising of integrated automation of transformation stations level (unmanned), the reliability of GIS device is had higher requirement.Smart machine is GIS device and the combination of relevant intelligent assembly.Intelligent assembly to measure digitizing, net control, status visualization, function integration, information interaction turn to feature, possess measurement, control, protection, metering, detect in all or part of function.Along with intelligent substation putting into operation in China, intelligent GIS equipment, as the primary element in electrical network with intelligent feature, is widely used in the construction of China's intelligent grid.
As a kind of brand-new equipment mode, intelligentized GIS device also has a lot of problem to need to inquire into further in the application.After carrying out intelligent construction, also will inevitably there are new effective means to its state evaluation in GIS device.The running status of the primary equipments such as real-time grasp GIS device, for scientific dispatch provides foundation; Can make GIS device fault type and life assessment and judging fast and effectively, run and maintenance to instruct, reduce operational management cost, reduce newborn hidden danger and produce probability, strengthen operational reliability.The accuracy of GIS device on-line operation condition adjudgement depends on its monitoring and analytical approach.GIS device on-line monitoring analytical approach is exactly the permission parameter of the characteristic parameter obtained after signal transacting and regulation or discrimination standard are compared, thus determine the duty of GIS device, the type that whether there is fault and fault and character etc., the trend that simultaneously may develop according to current data predicted state thus carry out fault trend analysis, should formulate rational criterion and strategy for this reason.
Due to the complicacy of GIS device structure and the diversity of failure mode, also fewer to the paractical research of GIS device enforcement state recognition at present.Conventional recognition methods is the simple judgment method based on threshold value compares, namely non-fault and fault severity level is had to judge and distinguish according to some simple parameters to isolating switch, the method is more single, and GIS equipment operational condition is complicated and changeable, the single online test method of tradition cannot comprehensively, accurate on-line checkingi goes out the running status of GIS device.
Summary of the invention
Based on this, be necessary the problem that comprehensively, accurately cannot detect the running status of GIS device for generally single online test method, a kind of online test method and the system that comprehensively, accurately can detect GIS equipment operational condition are provided.
A kind of GIS equipment operational condition online test method, comprises step:
Calculate the relative standard deviation values between the eigenwert of GIS device and reference characteristic value;
According to described eigenwert definition space weight coefficient array, wherein said space weight coefficient array comprises multiple weight coefficient;
According to described relative standard deviation values size, from the weight coefficient array of described space, choose corresponding weight coefficient, being multiplied by the weight coefficient that described relative standard deviation values is corresponding to described relative standard deviation values obtains individual deviate;
Choose the different detection moment and repeat above-mentioned computation process, obtain multiple described individual deviate;
Described individual deviate is added up, obtains space distribution statistical value, according to described space distribution statistical value, determine described GIS equipment operational condition.
A kind of GIS equipment operational condition on-line detecting system, comprising:
Relative standard deviation values computing module, for calculating the relative standard deviation values between the eigenwert of GIS device and reference characteristic value;
Weight coefficient group definition module, for according to described eigenwert definition space weight coefficient array, wherein said space weight coefficient array comprises multiple weight coefficient;
Individual deviate computing module, for according to described relative standard deviation values size, from the weight coefficient array of described space, choose corresponding weight coefficient, being multiplied by the weight coefficient that described relative standard deviation values is corresponding to described relative standard deviation values obtains individual deviate;
Loop module is used for, and chooses the different detection moment to repeat above-mentioned computation process, obtains multiple described individual deviate;
Results analyses module, for described individual deviate being added up, obtaining space distribution statistical value, according to described space distribution statistical value, determining described GIS equipment operational condition.
GIS equipment operational condition online test method of the present invention, utilize the eigenwert of GIS equipment operational condition, reference characteristic value and the weight coefficient corresponding to described eigenwert, analysis containing weight is carried out to GIS device, wherein, weight coefficient decides according to the statistical distribution of the eigenwert of sampling and the difference of reference characteristic value, the statistical distribution of difference is larger, then the weight coefficient given is larger.Generally speaking, whole method is from spatially comprehensively detecting analysis to GIS equipment operational condition, owing to have employed the detection analysis containing weight, consider the incipient fault that the serious historical data of extent of deviation more effectively can disclose GIS device, can accurately reflect current GIS equipment running status, thus GIS equipment operational condition online test method of the present invention be a kind of can comprehensively, the method for accurate on-line checkingi GIS equipment operational condition.
Accompanying drawing explanation
Fig. 1 is the schematic flow sheet of GIS equipment operational condition online test method of the present invention first embodiment;
Fig. 2 is the schematic flow sheet of GIS equipment operational condition online test method of the present invention second embodiment;
Fig. 3 is the structural representation of GIS equipment operational condition on-line detecting system of the present invention first embodiment;
Fig. 4 is the structural representation of GIS equipment operational condition on-line detecting system of the present invention second embodiment.
Embodiment
In order to make object of the present invention, technical scheme and advantage clearly understand, below with reference to the accompanying drawings and embodiment, the present invention is further elaborated.Should be appreciated that concrete enforcement described herein is only in order to explain the present invention, does not limit the present invention.
For the ease of explaining the technical scheme that GIS equipment operational condition online test method of the present invention and system are described, in following specific embodiment, alphabetical designated parts numerical value will be selected.
As shown in Figure 1, a kind of GIS equipment operational condition online test method, comprises step:
S200: calculate the relative standard deviation values between the eigenwert of GIS device and reference characteristic value.
In this step, need to calculate the relative standard deviation values between the eigenwert of GIS device and reference characteristic value, its computing formula is: D
i=| X
i-C
i|/C
iwherein X
ifor eigenwert, C
ifor reference characteristic value.
S400: according to described eigenwert definition space weight coefficient array, wherein said space weight coefficient array comprises multiple weight coefficient.
Space weight coefficient array defines according to eigenwert, and space weight coefficient array includes multiple weight coefficient.Can the numerical value of definition space weight coefficient array be such as (2%, 5%, 10%, 17%, 27%, 29%).
S600: according to described relative standard deviation values size, from the weight coefficient array of described space, choose corresponding weight coefficient, being multiplied by the weight coefficient that described relative standard deviation values is corresponding to described relative standard deviation values obtains individual deviate.
S800: choose the different detection moment and repeat above-mentioned computation process, obtain multiple described individual deviate.
There is a specific eigenwert in each detection moment, utilizes this eigenwert to repeat above-mentioned computation process, can obtain multiple individual deviate.
S900: described individual deviate added up, obtains space distribution statistical value, according to described space distribution statistical value, determines described GIS equipment operational condition.
Space distribution statistical value is less shows that the GIS device probability that breaks down is less, can reflect the current state of GIS device intuitively by the size of analysis space distribution statistics value.
Below by employing specific embodiment, use letter to refer to the numerical value occurred in whole step, explain the technical scheme of GIS equipment operational condition online test method of the present invention in detail.
According to formula
calculate the relative deviation E of characteristic quantity and reference value
i, the numerical value of definition space weight coefficient array is (2%, 5%, 10%, 17%, 27%, 29%), according to E
inumerical values recited, obtains the individual deviate of corresponding weight.
Each eigenwert of continuous eigenwert array all carries out above-mentioned computing.And then calculate its summation, obtain the statistical value with space distribution meaning
GIS equipment operational condition online test method of the present invention, utilize the eigenwert of GIS equipment operational condition, reference characteristic value and the weight coefficient corresponding to described eigenwert, analysis containing weight is carried out to GIS device, wherein, weight coefficient decides according to the statistical distribution of the eigenwert of sampling and the difference of reference characteristic value, the statistical distribution of difference is larger, then the weight coefficient given is larger.Generally speaking, whole method is from spatially comprehensively detecting analysis to GIS equipment operational condition, owing to have employed the detection analysis containing weight, consider the incipient fault that the serious historical data of extent of deviation more effectively can disclose GIS device, can accurately reflect current GIS equipment running status, thus GIS equipment operational condition online test method of the present invention be a kind of can comprehensively, the method for accurate on-line checkingi GIS equipment operational condition.
As shown in Figure 2, wherein in an embodiment, before described step S200 also in steps
S100: the eigenwert and the reference characteristic value that obtain each detection moment of GIS equipment operational condition according to the sense cycle preset.
Here this sense cycle preset can carry out arranging according to the needs of the needs of practical operation or operator, it can be the such as 10 seconds very short time, also it can be the such as 10 minutes long time, multiple detection moment has been contained in the sense cycle preset, it is all equal that general these detect the time of being separated by between the moment, such as, around the detection preset when 10 seconds, 10 can be separated detect the moment in whole sense cycle, namely often spend one second and just detect once.There is a corresponding eigenwert in each detection moment.
As shown in Figure 2, wherein in an embodiment, before described step S400 also in steps
S300: calculate the described weight coefficient group corresponding to described eigenwert, described weight coefficient group comprises multiple weight coefficient, and the computing formula of described weight coefficient is
wherein m=(n
3+ 5n)/6, a
nfor the weight coefficient of current sensing time point, n be from the detection number of times of current sensing time point detected.
Weight coefficient decides according to the statistical distribution of the eigenwert of sampling and the difference of reference characteristic value, and the statistical distribution of difference is larger, then the weight coefficient given is larger.
As shown in Figure 2, wherein in an embodiment, described step S900 specifically comprises step:
S920: described individual deviate added up, obtains space distribution statistical value;
S940: judge described space distribution statistical value size, described space distribution statistical value is larger, then show that described GIS equipment operational condition is poorer, and described space distribution statistical value is less, then show that described GIS equipment operational condition is better.
In the present embodiment; first obtain space distribution statistical value by cumulative for individual deviate, directly judge the size that space distribution is added up again afterwards, space distribution statistical value is larger; just show that GIS equipment operational condition is more unstable; floating spatially is very large, is easy to the abnormal conditions occurring exceeding controlled range, needs maintenance down; when space distribution statistical value more hour; illustrate that GIS equipment operational condition is spatially highly stable, float very little, substantially can keep current operating conditions.
Wherein in an embodiment, the priority of described reference characteristic value comprises successively from excellent to secondary, and product description, test findings, operating experience and expert are self-defined.
As shown in Figure 3, a kind of GIS equipment operational condition on-line detecting system, comprising:
Relative standard deviation values computing module 100, for calculating the relative standard deviation values between the eigenwert of GIS device and reference characteristic value;
Weight coefficient group definition module 200, for according to described eigenwert definition space weight coefficient array, wherein said space weight coefficient array comprises multiple weight coefficient;
Individual deviate computing module 300, for according to described relative standard deviation values size, from the weight coefficient array of described space, choose corresponding weight coefficient, being multiplied by the weight coefficient that described relative standard deviation values is corresponding to described relative standard deviation values obtains individual deviate;
Loop module 400, repeating above-mentioned computation process for choosing the different detection moment, obtaining multiple described individual deviate;
Results analyses module 500, for described individual deviate being added up, obtaining space distribution statistical value, according to described space distribution statistical value, determining described GIS equipment operational condition.
GIS equipment operational condition on-line detecting system of the present invention, utilize the eigenwert of GIS equipment operational condition, reference characteristic value and the weight coefficient corresponding to described eigenwert, analysis containing weight is carried out to GIS device, wherein, weight coefficient decides according to the statistical distribution of the eigenwert of sampling and the difference of reference characteristic value, the statistical distribution of difference is larger, then the weight coefficient given is larger.Generally speaking, whole system is from spatially comprehensively detecting analysis to GIS equipment operational condition, owing to have employed the detection analysis containing weight, consider the incipient fault that the serious historical data of extent of deviation more effectively can disclose GIS device, can accurately reflect current GIS equipment running status, thus GIS equipment operational condition on-line detecting system of the present invention be a kind of can comprehensively, the system of accurate on-line checkingi GIS equipment operational condition.
As shown in Figure 4, wherein in an embodiment, described GIS equipment operational condition on-line detecting system also comprises:
Numerical value acquisition module 600, for obtaining eigenwert and the reference characteristic value in each detection moment of GIS equipment operational condition according to the sense cycle preset.
Here this sense cycle preset can carry out arranging according to the needs of the needs of practical operation or operator, it can be the such as 10 seconds very short time, also it can be the such as 10 minutes long time, multiple detection moment has been contained in the sense cycle preset, it is all equal that general these detect the time of being separated by between the moment, such as, around the detection preset when 10 seconds, 10 can be separated detect the moment in whole sense cycle, namely often spend one second and just detect once.There is a corresponding eigenwert in each detection moment.
As shown in Figure 4, wherein in an embodiment, described GIS equipment operational condition on-line detecting system also comprises:
Weight coefficient computing module 700, for calculating the described weight coefficient group corresponding to described eigenwert, described weight coefficient group comprises multiple weight coefficient, and the computing formula of described weight coefficient is
wherein m=(n
3+ 5n)/6, a
nfor the weight coefficient of current sensing time point, n be from the detection number of times of current sensing time point detected.
Weight coefficient decides according to the statistical distribution of the eigenwert of sampling and the difference of reference characteristic value, and the statistical distribution of difference is larger, then the weight coefficient given is larger.
As shown in Figure 4, wherein in an embodiment, described results analyses module 500 specifically comprises:
Summing elements 520, for described individual deviate being added up, obtains space distribution statistical value;
Analytic unit 540, for judging described space distribution statistical value size, described space distribution statistical value is larger, then show that described GIS equipment operational condition is poorer, and described space distribution statistical value is less, then show that described GIS equipment operational condition is better.
In the present embodiment; first obtain space distribution statistical value by cumulative for individual deviate, directly judge the size that space distribution is added up again afterwards, space distribution statistical value is larger; just show that GIS equipment operational condition is more unstable; floating spatially is very large, is easy to the abnormal conditions occurring exceeding controlled range, needs maintenance down; when space distribution statistical value more hour; illustrate that GIS equipment operational condition is spatially highly stable, float very little, substantially can keep current operating conditions.
Wherein in an embodiment, the priority of described reference characteristic value comprises successively from excellent to secondary, and product description, test findings, operating experience and expert are self-defined.
The above embodiment only have expressed several embodiment of the present invention, and it describes comparatively concrete and detailed, but therefore can not be interpreted as the restriction to the scope of the claims of the present invention.It should be pointed out that for the person of ordinary skill of the art, without departing from the inventive concept of the premise, can also make some distortion and improvement, these all belong to protection scope of the present invention.Therefore, the protection domain of patent of the present invention should be as the criterion with claims.
Claims (8)
1. a GIS equipment operational condition online test method, is characterized in that, comprises step:
Calculate the relative standard deviation values between the eigenwert of GIS device and reference characteristic value;
According to eigenwert definition space weight coefficient array, wherein said space weight coefficient array comprises multiple weight coefficient, and described eigenwert comprises the eigenwert of described GIS device and described reference characteristic value;
According to described relative standard deviation values size, from the weight coefficient array of described space, choose corresponding weight coefficient, being multiplied by the weight coefficient that described relative standard deviation values is corresponding to described relative standard deviation values obtains individual deviate;
Choose the different detection moment and repeat above-mentioned computation process, obtain multiple described individual deviate;
Described individual deviate is added up, obtains space distribution statistical value, according to described space distribution statistical value, determine described GIS equipment operational condition
Wherein, describedly also to comprise according to before the step of eigenwert definition space weight coefficient array:
Calculate the described weight coefficient array corresponding to described eigenwert, described weight coefficient array comprises multiple weight coefficient, and the computing formula of described weight coefficient is
wherein m=(n
3+ 5n)/6, a
nfor the weight coefficient of current sensing time point, n be from the detection number of times of current sensing time point detected.
2. GIS equipment operational condition online test method according to claim 1, is characterized in that, before the relative standard deviation values between the eigenwert of described step calculating GIS device and reference characteristic value also in steps:
Eigenwert and the reference characteristic value in each detection moment of GIS equipment operational condition is obtained according to the sense cycle preset.
3. GIS equipment operational condition online test method according to claim 1 and 2, it is characterized in that, described individual deviate adds up by described step, obtains space distribution statistical value, according to described space distribution statistical value, determine that described GIS equipment operational condition specifically comprises step:
Described individual deviate is added up, obtains space distribution statistical value;
Judge described space distribution statistical value size, described space distribution statistical value is larger, then show that described GIS equipment operational condition is poorer, and described space distribution statistical value is less, then show that described GIS equipment operational condition is better.
4. GIS equipment operational condition online test method according to claim 1 and 2, is characterized in that, the priority of described reference characteristic value comprises successively from excellent to secondary, and product description, test findings, operating experience and expert are self-defined.
5. a GIS equipment operational condition on-line detecting system, is characterized in that, comprising:
Relative standard deviation values computing module, for calculating the relative standard deviation values between the eigenwert of GIS device and reference characteristic value;
Weight coefficient computing module, for calculating the described weight coefficient array corresponding to eigenwert, described weight coefficient array comprises multiple weight coefficient, and the computing formula of described weight coefficient is
wherein m=(n
3+ 5n)/6, a
nfor the weight coefficient of current sensing time point, n be from the detection number of times of current sensing time point detected, wherein, described eigenwert comprises the eigenwert of described GIS device and described reference characteristic value;
Weight coefficient group definition module, for according to described eigenwert definition space weight coefficient array, wherein said space weight coefficient array comprises multiple weight coefficient;
Individual deviate computing module, for according to described relative standard deviation values size, from the weight coefficient array of described space, choose corresponding weight coefficient, being multiplied by the weight coefficient that described relative standard deviation values is corresponding to described relative standard deviation values obtains individual deviate;
Loop module, repeating above-mentioned computation process for choosing the different detection moment, obtaining multiple described individual deviate;
Results analyses module, for described individual deviate being added up, obtaining space distribution statistical value, according to described space distribution statistical value, determining described GIS equipment operational condition.
6. GIS equipment operational condition on-line detecting system according to claim 5, is characterized in that, also comprise:
Numerical value acquisition module, for obtaining eigenwert and the reference characteristic value in each detection moment of GIS equipment operational condition according to the sense cycle preset.
7. the GIS equipment operational condition on-line detecting system according to claim 5 or 6, is characterized in that, described results analyses module specifically comprises:
Summing elements, for described individual deviate being added up, obtains space distribution statistical value;
Analytic unit, for judging described space distribution statistical value size, described space distribution statistical value is larger, then show that described GIS equipment operational condition is poorer, and described space distribution statistical value is less, then show that described GIS equipment operational condition is better.
8. the GIS equipment operational condition on-line detecting system according to claim 5 or 6, is characterized in that, the priority of described reference characteristic value comprises successively from excellent to secondary, and product description, test findings, operating experience and expert are self-defined.
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