CN103400308A - Online detection method and online detection system for running state of GIS (gas insulated switchgear) equipment - Google Patents
Online detection method and online detection system for running state of GIS (gas insulated switchgear) equipment Download PDFInfo
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Abstract
The invention provides an online detection method and an online detection system for a running state of GIS (gas insulated switchgear) equipment. The method comprises the following steps of firstly acquiring a characteristic value and a benchmark characteristic value of the running state of the GIS equipment as well as a weight coefficient corresponding to the characteristic value, then carrying out the weight-contained threshold value analysis, the weight-contained trend analysis and the weight-contained statistics analysis for the running state of the GIS equipment, and finally determining the running state of the GIS equipment according to the three analysis results. According to the online detection method for the running state of the GIS equipment, comprehensive online detection for the GIS equipment is carried out respectively on the aspect of the time and the aspect of the space, so that not only can the current running state of the GIS equipment be comprehensively and accurately detected, but also the trend of the running state of the GIS equipment can be detected, and the potential fault in the running process of the GIS equipment can be discovered to some extent.
Description
Technical field
The present invention relates to the online measuring technique field, particularly relate to GIS equipment running status online test method and system.
Background technology
Intelligent gas insulation in combined electric appliance (Gas Insulated Switchgear, GIS equipment) is for the construction that adapts to intelligent grid puts forward, and plays protection and control action in electric system, and 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 that comprises the primary equipments such as GIS equipment, and GIS device intelligence construction degree direct influence intelligent substation, informationization.Along with the raising of integrated automation of transformation stations level (unmanned), the reliability of GIS equipment is had higher requirement.Smart machine is GIS equipment and the combination of relevant intelligent assembly.Intelligent assembly turns to feature with measurement digitizing, control networking, status visualization, function integration, information interaction, possesses all or part of function in measurement, control, protection, metering, detection.The putting into operation of China, intelligence GIS equipment, as the primary element that has intelligent feature in electrical network, will be widely used in the construction of China's intelligent grid along with intelligent substation.
As a kind of brand-new equipment mode, intelligentized GIS equipment also has a lot of problems to need further to inquire in application.GIS equipment after carrying out intelligent construction, new effective means also will inevitably occur to its state evaluation.Grasp in real time the running status of the primary equipments such as GIS equipment, for the science scheduling provides foundation; Can make judgement fast and effectively to GIS equipment failure type and life assessment,, to instruct operation and maintenance, reduce the operational management cost, reduce newborn hidden danger and produce probability, strengthen operational reliability.The accuracy of GIS equipment on-line running status judgement depends on its monitoring and analytical approach.GIS equipment on-line monitoring analytical approach is exactly that the characteristic parameter that will be after signal is processed obtains and permission parameter or the discrimination standard of regulation compare, thereby determine duty, the type that whether has fault and fault and the character etc. of GIS equipment, thereby the trend that may develop according to the current data predicted state is simultaneously carried out the 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 equipment enforcement state recognition at present.Recognition methods commonly used is relatively as basic simple judgment method take threshold value, namely according to some simple parameters, to isolating switch, there are non-fault and the fault order of severity to judge and distinguish, the method is more single, and the GIS equipment running status is not only relevant with current running status, also relevant with the historical data of running status before, so above-mentioned detection method with the threshold value comparison can't accurately detect the GIS equipment running status.
Summary of the invention
Based on this, be necessary can't comprehensively, accurately detect the problem of GIS equipment running status for general GIS equipment running status online test method, provide a kind of and can occasionally comprehensively, accurately detect the method and system of GIS equipment running status.
A kind of GIS equipment running status online test method comprises step:
Obtain the GIS equipment running status eigenwert, reference characteristic value and with the corresponding weight coefficient of described eigenwert;
according to described weight coefficient, described eigenwert and described reference characteristic value contain the Threshold Analysis of weight to the GIS equipment running status, wherein, the described Threshold Analysis that contains weight comprises step: according to the character of the eigenwert of GIS equipment running status, capping threshold value and lower limit threshold value, it is poor that the eigenwert of described GIS equipment running status and reference characteristic value are done, obtain deviate, judge whether described deviate surpasses described upper limit threshold value or described lower limit threshold value, if surpass, directly send alerting signal, if do not surpass, described deviate be multiply by and the corresponding weight coefficient of described reference characteristic value, draw threshold value, with the total threshold value of the cumulative acquisition of all described threshold values in detection time,
according to described weight coefficient, described eigenwert and described reference characteristic value contain the trend analysis of weight to the GIS equipment running status, wherein, the described trend analysis that contains weight comprises step: with current detection constantly eigenwert and the eigenwert in the previous moment in the described current detection moment do poor, obtain the First Eigenvalue difference, the eigenwert in the previous moment in the described current detection moment and the first two in described current detection moment eigenwert are constantly done the poor Second Eigenvalue difference that obtains, to multiply by with the described current detection corresponding weight coefficient of eigenwert constantly the ratio of described the First Eigenvalue difference and described Second Eigenvalue difference, obtain current Trend value, trend statistical value in detection time is added up and get the absolute value of accumulated value, obtain the general trend value,
according to described weight coefficient, described eigenwert and described reference characteristic value contain the statistical study of weight to the GIS equipment running status, wherein, the described statistical study that contains weight comprises step: the relative deviation value between computation of characteristic values and reference characteristic value, according to described eigenwert definition space weight coefficient array, wherein said space weight coefficient array comprises a plurality of weight coefficients, according to described relative deviation value size, choose corresponding weight coefficient from the weight coefficient array of described space, described relative deviation value and the corresponding weight coefficient of described relative deviation value are multiplied each other and obtain individual deviate, choose different detections and constantly repeat above-mentioned computation process, obtain a plurality of described individual deviates, described individual deviate is cumulative, obtain the space distribution statistical value,
, according to described total threshold value, described general trend value and described space distribution statistical value, determine described GIS equipment running status.
A kind of GIS equipment running status on-line detecting system comprises:
The numerical value acquisition module, be used for obtaining the GIS equipment running status eigenwert, reference characteristic value and with the corresponding weight coefficient of described eigenwert;
the Threshold Analysis module, be used for according to described weight coefficient, described eigenwert and described reference characteristic value contain the Threshold Analysis of weight to the GIS equipment running status, wherein, the described Threshold Analysis that contains weight comprises step: according to the character of the eigenwert of GIS equipment running status, capping threshold value and lower limit threshold value, it is poor that the eigenwert of described GIS equipment running status and reference characteristic value are done, obtain deviate, judge whether described deviate surpasses described upper limit threshold value or described lower limit threshold value, if surpass, directly send alerting signal, if do not surpass, described deviate be multiply by and the corresponding weight coefficient of described reference characteristic value, draw threshold value, with the total threshold value of the cumulative acquisition of all described threshold values in detection time,
the trend analysis module, be used for according to described weight coefficient, described eigenwert and described reference characteristic value contain the trend analysis of weight to the GIS equipment running status, wherein, the described trend analysis that contains weight comprises step: with current detection constantly eigenwert and the eigenwert in the previous moment in the described current detection moment do poor, obtain the First Eigenvalue difference, the eigenwert in the previous moment in the described current detection moment and the first two in described current detection moment eigenwert are constantly done the poor Second Eigenvalue difference that obtains, to multiply by with the described current detection corresponding weight coefficient of eigenwert constantly the ratio of described the First Eigenvalue difference and described Second Eigenvalue difference, obtain current Trend value, trend statistical value in detection time is added up and get the absolute value of accumulated value, obtain the general trend value,
statistical analysis module, be used for according to described weight coefficient, described eigenwert and described reference characteristic value contain the statistical study of weight to the GIS equipment running status, wherein, the described statistical study that contains weight comprises step: the relative deviation value between computation of characteristic values and reference characteristic value, according to described eigenwert definition space weight coefficient array, wherein said space weight coefficient array comprises a plurality of weight coefficients, according to described relative deviation value size, choose corresponding weight coefficient from the weight coefficient array of described space, described relative deviation value and the corresponding weight coefficient of described relative deviation value are multiplied each other and obtain individual deviate, choose different detections and constantly repeat above-mentioned computation process, obtain a plurality of described individual deviates, described individual deviate is cumulative, obtain the space distribution statistical value,
Results analyses module, be used for according to described total threshold value, described general trend value and described space distribution statistical value, determines described GIS equipment running status.
GIS equipment running status online test method of the present invention, utilize the eigenwert of GIS equipment running status, the reference characteristic value and with the corresponding weight coefficient of described eigenwert, GIS equipment is contained the analysis of weight, wherein, weight coefficient distributes according to time sequencing, the weight coefficient that put each detection time is not identical, GIS equipment running status online test method of the present invention has comprised the Threshold Analysis method that contains weight, trend analysis method, the three kinds of methods of statistical analysis method that contain weight are carried out the quantitative test of GIS apparatus characteristic value, wherein, the Threshold Analysis method and the trend analysis method that contain weight are complete from the time, the GIS equipment running status is carried out on-line analysis comprehensively, detect the trend of its current running status and its running status, the statistical analysis method that contains weight detects the GIS equipment running status from space, so generally speaking, GIS equipment running status online test method of the present invention is carried out comprehensively online the detection to GIS equipment respectively on time and space, not only can accurately detect the current running status of GIS equipment comprehensively and can also detect the trend of its running status, the fault of hiding in to a certain degree finding the GIS equipment running process.
Description of drawings
Fig. 1 is the schematic flow sheet of first embodiment of GIS equipment running status online test method of the present invention;
Fig. 2 is the schematic flow sheet of second embodiment of GIS equipment running status online test method of the present invention;
Fig. 3 is the structural representation of first embodiment of GIS equipment running status on-line detecting system of the present invention;
Fig. 4 is the structural representation of second embodiment of GIS equipment running status on-line detecting system of the present invention.
Embodiment
In order to make purpose of the present invention, technical scheme and advantage clearer, below reach with reference to the accompanying drawings embodiment, the present invention is further elaborated.Should be appreciated that concrete enforcement described herein, only in order to explain the present invention, does not limit the present invention.
, for the ease of the technical scheme of explain GIS equipment running status online test method of the present invention and system, in following specific embodiment, will select letter to refer to part numerical value.
As shown in Figure 1, a kind of GIS equipment running status online test method comprises step:
S200: obtain the GIS equipment running status eigenwert, reference characteristic value and with the corresponding weight coefficient of described eigenwert.
What obtain here can be the eigenwert of obtaining online the GIS equipment running status, can be also the historical data that directly reads the GIS equipment running status, or the conventional data of Computer Storage directly imports and reads.
S400: according to described weight coefficient, described eigenwert and described reference characteristic value contain the Threshold Analysis of weight to the GIS equipment running status, wherein, the described Threshold Analysis that contains weight comprises step: according to the character of the eigenwert of GIS equipment running status, capping threshold value and lower limit threshold value, it is poor that the eigenwert of described GIS equipment running status and reference characteristic value are done, obtain deviate, judge whether described deviate surpasses described upper limit threshold value or described lower limit threshold value, if surpass, directly send alerting signal, if do not surpass, described deviate be multiply by and the corresponding weight coefficient of described reference characteristic value, draw threshold value, with the total threshold value of the cumulative acquisition of all described threshold values in detection time.
First-selected character according to each eigenwert of GIS equipment running status, set high alarm setting and lower limit threshold value, the eigenwert X that will obtain online afterwards
iDeduct its corresponding reference value C
i, obtain the deviation of measured value and reference value, if deviation exceeds the bound threshold value, the alert signal of directly transmitting messages,, if do not have out-of-limitly, multiply by weight coefficient a corresponding to this eigenwert to this deviation
i, acquired results A
I (threshold value)Expression, i.e. A
The i(threshold value)=a
i* (X
i-C
i), finally with each the corresponding A of eigenwert constantly that obtains in certain hour
I (threshold value)Value is cumulative, acquired results S
(threshold value)Expression, i.e. S
(threshold value)=Σ A
I (threshold value)By analyzing S
(threshold value)Size, can intuitively reflect the residing state of GIS equipment.
S600: according to described weight coefficient, described eigenwert and described reference characteristic value contain the trend analysis of weight to the GIS equipment running status, wherein, the described trend analysis that contains weight comprises step: with current detection constantly eigenwert and the eigenwert in the previous moment in the described current detection moment do poor, obtain the First Eigenvalue difference, the eigenwert in the previous moment in the described current detection moment and the first two in described current detection moment eigenwert are constantly done the poor Second Eigenvalue difference that obtains, to multiply by with the described current detection corresponding weight coefficient of eigenwert constantly the ratio of described the First Eigenvalue difference and described Second Eigenvalue difference, obtain current Trend value, trend statistical value in detection time is added up and get the absolute value of accumulated value, obtain the general trend value.
By calculating the eigenwert x of current time
iWith previous moment eigenwert X
i-1Poor, and divided by X
i-1With previous moment eigenwert X again
i-2Difference, multiply by again finally weight coefficient a corresponding to current time eigenwert
i, acquired results A
I (trend)Expression, i.e. A
I (trend)=a
i* (X
i-X
i-1)/(X
i-1-X
i-2); According to A
I (trend)The symbol of value, define a value B
I (trend)Work as A
I (trend)For on the occasion of the time, get B
I (trend)=A
I (trend)Work as A
I (trend)For non-on the occasion of the time, make B
I (trend)=0.With the A that obtains in certain hour
I (trend)Value is cumulative, acquired results S
(trend)Expression, i.e. S
(trend)=Σ B
I (trend), be namely the Trend value that contains weight.By analyzing S
(trend)Size, can intuitively reflect the residing state of GIS equipment.
S800: according to described weight coefficient, described eigenwert and described reference characteristic value contain the statistical study of weight to the GIS equipment running status, wherein, the described statistical study that contains weight comprises step: the relative deviation value between computation of characteristic values and reference characteristic value, according to described eigenwert definition space weight coefficient array, wherein said space weight coefficient array comprises a plurality of weight coefficients, according to described relative deviation value size, choose corresponding weight coefficient from the weight coefficient array of described space, described relative deviation value and the corresponding weight coefficient of described relative deviation value are multiplied each other and obtain individual deviate, choose different detections and constantly repeat above-mentioned computation process, obtain a plurality of described individual deviates, described individual deviate is cumulative, obtain the space distribution statistical value.
According to formula
The relative deviation E of calculated characteristics amount 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, obtain the individual deviate of corresponding weight.
Each eigenwert of eigenwert array is all carried out above-mentioned computing continuously.And then calculate its summation, obtain having the statistical value of space distribution meaning
S900:, according to described total threshold value, described general trend value and described space distribution statistical value, determine described GIS equipment running status.
Described total threshold value, described general trend value and described space distribution statistical value are less, show that described GIS equipment running status is better.
GIS equipment running status online test method of the present invention, utilize the eigenwert of GIS equipment running status, the reference characteristic value and with the corresponding weight coefficient of described eigenwert, GIS equipment is contained the analysis of weight, wherein, weight coefficient distributes according to time sequencing, the weight coefficient that put each detection time is not identical, GIS equipment running status online test method of the present invention has comprised the Threshold Analysis method that contains weight, trend analysis method, the three kinds of methods of statistical analysis method that contain weight are carried out the quantitative test of GIS apparatus characteristic value, wherein, the Threshold Analysis method and the trend analysis method that contain weight are complete from the time, the GIS equipment running status is carried out on-line analysis comprehensively, detect the trend of its current running status and its running status, the statistical analysis method that contains weight detects the GIS equipment running status from space, so generally speaking, GIS equipment running status online test method of the present invention is carried out comprehensively online the detection to GIS equipment respectively on time and space, not only can accurately detect the current running status of GIS equipment comprehensively and can also detect the trend of its running status, the fault of hiding in to a certain degree finding the GIS equipment running process.
As shown in Figure 2, in embodiment, described step S200 specifically comprises therein:
S220: determine the default cycle in the detection moment;
S230: obtain that in the described default detection cycle constantly, each detects eigenwert and the reference characteristic value of the GIS equipment running status of moment point;
S240: calculate and the corresponding described weight coefficient group of described eigenwert, described weight coefficient group comprises a plurality of weight coefficients, and the computing formula of described weight coefficient is
M=(n wherein
3+ 5n)/6, a
nFor the weight coefficient of current detection time point, n is from starting to detect the detection number of times of current detection time point.
Weight coefficient distributes according to time sequencing, and each, the weight coefficient of point was not identical detection time, and is larger with the weight coefficient of the nearer time point of current detection time point.For example the current detection number of times is that the 4th in the current detection cycle detects, m=16, a
4=0.375.
As shown in Figure 2, in embodiment, described step S900 specifically comprises therein:
S920: read described total threshold value, described general trend value and described space distribution statistical value;
S940: determine described GIS equipment running status according to described total threshold value and described general trend value from the time, determine described GIS equipment running status according to described space distribution statistical value from space.
Described total threshold value and the less explanation of described general trend value GIS equipment running status from the time are more stable, basically not there will be the situation of abnormal sudden change, the less explanation of described space distribution statistical value is less from the amplitude that GIS equipment running status on space changes, and basically can keep current steady state (SS).
Therein in embodiment, the priority of described reference characteristic value comprises successively from excellent to inferior, and product description, test findings, operating experience and expert are self-defined.
As shown in Figure 3, a kind of GIS equipment running status on-line detecting system comprises:
Numerical value acquisition module 100, be used for obtaining the GIS equipment running status eigenwert, reference characteristic value and with the corresponding weight coefficient of described eigenwert;
GIS equipment running status on-line detecting system of the present invention, utilize the eigenwert of GIS equipment running status, the reference characteristic value and with the corresponding weight coefficient of described eigenwert, GIS equipment is contained the analysis of weight, wherein, weight coefficient distributes according to time sequencing, the weight coefficient that put each detection time is not identical, GIS equipment running status on-line detecting system of the present invention has comprised the Threshold Analysis method that contains weight, trend analysis method, the three kinds of systems of statistical analysis method that contain weight are carried out the quantitative test of GIS apparatus characteristic value, wherein, the Threshold Analysis method and the trend analysis method that contain weight are complete from the time, the GIS equipment running status is carried out on-line analysis comprehensively, detect the trend of its current running status and its running status, the statistical analysis method that contains weight detects the GIS equipment running status from space, so generally speaking, GIS equipment running status on-line detecting system of the present invention carries out comprehensively online the detection to GIS equipment respectively on time and space, not only can accurately detect the current running status of GIS equipment comprehensively and can also detect the trend of its running status, the fault of hiding in to a certain degree finding the GIS equipment running process.
As shown in Figure 4, in embodiment, described numerical value acquisition module 100 specifically comprises therein:
Sense cycle determining unit 120, be used for determining the default cycle in the detection moment;
The numerical value reading unit, 140 are used for obtaining described default detection eigenwert and the reference characteristic value of the GIS equipment running status of each detection moment point of cycle constantly;
Weighted value computing unit 160, be used for calculating and the corresponding described weight coefficient group of described eigenwert, and described weight coefficient group comprises a plurality of weight coefficients, and the computing formula of described weight coefficient is
M=(n wherein
3+ 5n)/6, a
nFor the weight coefficient of current detection time point, n is from starting to detect the detection number of times of current detection time point.
Weight coefficient distributes according to time sequencing, and each, the weight coefficient of point was not identical detection time, and is larger with the weight coefficient of the nearer time point of current detection time point.For example the current detection number of times is that the 4th in the current detection cycle detects, m=16, a
4=0.375.
As shown in Figure 4, in embodiment, described results analyses module concrete 500 comprises therein:
Reading unit 520, be used for reading described total threshold value, described general trend value and described space distribution statistical value;
Described total threshold value and the less explanation of described general trend value GIS equipment running status from the time are more stable, basically not there will be the situation of abnormal sudden change, the less explanation of described space distribution statistical value is less from the amplitude that GIS equipment running status on space changes, and basically can keep current steady state (SS).
Therein in embodiment, the priority of described reference characteristic value comprises successively from excellent to inferior, and product description, test findings, operating experience and expert are self-defined.
The above embodiment has only expressed several embodiment of the present invention, and it describes comparatively concrete and detailed, but can not therefore be interpreted as the restriction to the scope of the claims of the present invention.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 running status online test method, is characterized in that, comprises step:
Obtain the GIS equipment running status eigenwert, reference characteristic value and with the corresponding weight coefficient of described eigenwert;
according to described weight coefficient, described eigenwert and described reference characteristic value contain the Threshold Analysis of weight to the GIS equipment running status, wherein, the described Threshold Analysis that contains weight comprises step: according to the character of the eigenwert of GIS equipment running status, capping threshold value and lower limit threshold value, it is poor that the eigenwert of described GIS equipment running status and reference characteristic value are done, obtain deviate, judge whether described deviate surpasses described upper limit threshold value or described lower limit threshold value, if surpass, directly send alerting signal, if do not surpass, described deviate be multiply by and the corresponding weight coefficient of described reference characteristic value, draw threshold value, with the total threshold value of the cumulative acquisition of all described threshold values in detection time,
according to described weight coefficient, described eigenwert and described reference characteristic value contain the trend analysis of weight to the GIS equipment running status, wherein, the described trend analysis that contains weight comprises step: with current detection constantly eigenwert and the eigenwert in the previous moment in the described current detection moment do poor, obtain the First Eigenvalue difference, the eigenwert in the previous moment in the described current detection moment and the first two in described current detection moment eigenwert are constantly done the poor Second Eigenvalue difference that obtains, to multiply by with the described current detection corresponding weight coefficient of eigenwert constantly the ratio of described the First Eigenvalue difference and described Second Eigenvalue difference, obtain current Trend value, trend statistical value in detection time is cumulative, and get the absolute value of accumulated value, obtain the general trend value,
according to described weight coefficient, described eigenwert and described reference characteristic value contain the statistical study of weight to the GIS equipment running status, wherein, the described statistical study that contains weight comprises step: the relative deviation value between computation of characteristic values and reference characteristic value, according to described eigenwert definition space weight coefficient array, wherein said space weight coefficient array comprises a plurality of weight coefficients, according to described relative deviation value size, choose corresponding weight coefficient from the weight coefficient array of described space, described relative deviation value and the corresponding weight coefficient of described relative deviation value are multiplied each other and obtain individual deviate, choose different detections and constantly repeat above-mentioned computation process, obtain a plurality of described individual deviates, described individual deviate is cumulative, obtain the space distribution statistical value,
, according to described total threshold value, described general trend value and described space distribution statistical value, determine described GIS equipment running status.
2. GIS equipment running status online test method according to claim 1, is characterized in that, described step is obtained eigenwert, the reference characteristic value of GIS equipment running status and with the corresponding weight coefficient of described eigenwert, specifically comprised:
Determine the default cycle in the detection moment;
Obtain that in the described default detection cycle constantly, each detects eigenwert and the reference characteristic value of the GIS equipment running status of moment point;
Calculate and the corresponding described weight coefficient group of described eigenwert, described weight coefficient group comprises a plurality of weight coefficients, and the computing formula of described weight coefficient is
M=(n wherein
3+ 5n)/6, a
nFor the weight coefficient of current detection time point, n is from starting to detect the detection number of times of current detection time point.
3. GIS equipment running status online test method according to claim 1 and 2, is characterized in that, described step, according to described total threshold value, described general trend value and described space distribution statistical value, determines that described GIS equipment running status specifically comprises:
Read described total threshold value, described general trend value and described space distribution statistical value;
Determine described GIS equipment running status according to described total threshold value and described general trend value from the time, determine described GIS equipment running status according to described space distribution statistical value from space.
4. GIS equipment running status 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 inferior, and product description, test findings, operating experience and expert are self-defined.
5. a GIS equipment running status on-line detecting system, is characterized in that, comprising:
The numerical value acquisition module, be used for obtaining the GIS equipment running status eigenwert, reference characteristic value and with the corresponding weight coefficient of described eigenwert;
the Threshold Analysis module, be used for according to described weight coefficient, described eigenwert and described reference characteristic value contain the Threshold Analysis of weight to the GIS equipment running status, wherein, the described Threshold Analysis that contains weight comprises step: according to the character of the eigenwert of GIS equipment running status, capping threshold value and lower limit threshold value, it is poor that the eigenwert of described GIS equipment running status and reference characteristic value are done, obtain deviate, judge whether described deviate surpasses described upper limit threshold value or described lower limit threshold value, if surpass, directly send alerting signal, if do not surpass, described deviate be multiply by and the corresponding weight coefficient of described reference characteristic value, draw threshold value, with the total threshold value of the cumulative acquisition of all described threshold values in detection time,
the trend analysis module, be used for according to described weight coefficient, described eigenwert and described reference characteristic value contain the trend analysis of weight to the GIS equipment running status, wherein, the described trend analysis that contains weight comprises step: with current detection constantly eigenwert and the eigenwert in the previous moment in the described current detection moment do poor, obtain the First Eigenvalue difference, the eigenwert in the previous moment in the described current detection moment and the first two in described current detection moment eigenwert are constantly done the poor Second Eigenvalue difference that obtains, to multiply by with the described current detection corresponding weight coefficient of eigenwert constantly the ratio of described the First Eigenvalue difference and described Second Eigenvalue difference, obtain current Trend value, trend statistical value in detection time is added up and get the absolute value of accumulated value, obtain the general trend value,
statistical analysis module, be used for according to described weight coefficient, described eigenwert and described reference characteristic value contain the statistical study of weight to the GIS equipment running status, wherein, the described statistical study that contains weight comprises step: the relative deviation value between computation of characteristic values and reference characteristic value, according to described eigenwert definition space weight coefficient array, wherein said space weight coefficient array comprises a plurality of weight coefficients, according to described relative deviation value size, choose corresponding weight coefficient from the weight coefficient array of described space, described relative deviation value and the corresponding weight coefficient of described relative deviation value are multiplied each other and obtain individual deviate, choose different detections and constantly repeat above-mentioned computation process, obtain a plurality of described individual deviates, described individual deviate is cumulative, obtain the space distribution statistical value,
Results analyses module, be used for according to described total threshold value, described general trend value and described space distribution statistical value, determines described GIS equipment running status.
6. GIS equipment running status online test method according to claim 5, is characterized in that, described numerical value acquisition module specifically comprises:
The sense cycle determining unit, be used for determining the default cycle in the detection moment;
The numerical value reading unit, be used for obtaining described default detection eigenwert and the reference characteristic value of the GIS equipment running status of each detection moment point of cycle constantly;
The weighted value computing unit, be used for calculating and the corresponding described weight coefficient group of described eigenwert, and described weight coefficient group comprises a plurality of weight coefficients, and the computing formula of described weight coefficient is
M=(n wherein
3+ 5n)/6, a
nFor the weight coefficient of current detection time point, n is from starting to detect the detection number of times of current detection time point.
7. according to claim 5 or 6 described GIS equipment running status on-line detecting systems, is characterized in that, described results analyses module specifically comprises:
Reading unit, be used for reading described total threshold value, described general trend value and described space distribution statistical value;
Analytic unit, be used for determining described GIS equipment running status according to described total threshold value and described general trend value from the time, according to described space distribution statistical value from space definite described GIS equipment running status.
8. according to claim 5 or 6 described GIS equipment running status on-line detecting systems, is characterized in that, the priority of described reference characteristic value comprises successively from excellent to inferior, and product description, test findings, operating experience and expert are self-defined.
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Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104636746A (en) * | 2015-02-04 | 2015-05-20 | 华南理工大学 | GIS (Gas Insulated Switchgear) equipment characteristic value extraction method based on local-region wavelet transformation |
| CN105045253A (en) * | 2015-05-27 | 2015-11-11 | 广东蓄能发电有限公司 | Method for quickly discriminating abnormal operating condition of electrical equipment |
| CN106441966A (en) * | 2016-10-11 | 2017-02-22 | 常州市华立液压润滑设备有限公司 | Remote problem diagnosis system of lubricating oil station and working method |
| CN106771697A (en) * | 2015-11-20 | 2017-05-31 | 财团法人工业技术研究院 | Fault evaluation method and fault evaluation device of equipment |
| CN108132418A (en) * | 2017-11-29 | 2018-06-08 | 王根平 | A kind of power equipment interconnected monitoring system, method and device |
| CN109978742A (en) * | 2017-12-27 | 2019-07-05 | 航天信息股份有限公司 | It is a kind of for obtaining the method and system of financial bill automatically |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN104636746A (en) * | 2015-02-04 | 2015-05-20 | 华南理工大学 | GIS (Gas Insulated Switchgear) equipment characteristic value extraction method based on local-region wavelet transformation |
| CN104636746B (en) * | 2015-02-04 | 2018-01-16 | 华南理工大学 | A kind of GIS device Eigenvalue Extraction Method based on regional area wavelet transformation |
| CN105045253A (en) * | 2015-05-27 | 2015-11-11 | 广东蓄能发电有限公司 | Method for quickly discriminating abnormal operating condition of electrical equipment |
| CN105045253B (en) * | 2015-05-27 | 2018-04-03 | 广东蓄能发电有限公司 | The quick discriminating method of electrical equipment misoperation operating mode |
| CN106771697A (en) * | 2015-11-20 | 2017-05-31 | 财团法人工业技术研究院 | Fault evaluation method and fault evaluation device of equipment |
| US10281362B2 (en) | 2015-11-20 | 2019-05-07 | Industrial Technology Research Institute | Method and device of measuring breakdown status of equipment |
| CN106771697B (en) * | 2015-11-20 | 2020-12-15 | 财团法人工业技术研究院 | Fault evaluation method and fault evaluation device of equipment |
| CN106441966A (en) * | 2016-10-11 | 2017-02-22 | 常州市华立液压润滑设备有限公司 | Remote problem diagnosis system of lubricating oil station and working method |
| CN106441966B (en) * | 2016-10-11 | 2018-07-17 | 常州市华立液压润滑设备有限公司 | A kind of long-range problem diagnosis system of lubricating oil station and working method |
| CN108132418A (en) * | 2017-11-29 | 2018-06-08 | 王根平 | A kind of power equipment interconnected monitoring system, method and device |
| CN109978742A (en) * | 2017-12-27 | 2019-07-05 | 航天信息股份有限公司 | It is a kind of for obtaining the method and system of financial bill automatically |
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