CN105117512A - Transformer early-warning value estimation method and apparatus - Google Patents
Transformer early-warning value estimation method and apparatus Download PDFInfo
- Publication number
- CN105117512A CN105117512A CN201510438809.7A CN201510438809A CN105117512A CN 105117512 A CN105117512 A CN 105117512A CN 201510438809 A CN201510438809 A CN 201510438809A CN 105117512 A CN105117512 A CN 105117512A
- Authority
- CN
- China
- Prior art keywords
- transformer
- distribution function
- classification
- concentration
- factor
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Landscapes
- Housings And Mounting Of Transformers (AREA)
Abstract
The present invention discloses a transformer early-warning value estimation method and apparatus. The method comprises: acquiring a cumulative distribution function of a concentration and a gas generation rate of gas dissolved in transformer oil of a transformer; determining a corresponding inverse cumulative distribution function according to the cumulative distribution function; acquiring a defect rate and/or a failure rate of the transformer; after acquiring the defect rate, estimating attention values of the concentration and the gas production rate according to the defect rate by using the inverse cumulative distribution function; after acquiring the failure rate, estimating warning values of the concentration and the gas production rate according to the failure rate by using the inverse cumulative distribution function; and outputting the attention values and the warning values. The present invention solves the technical problems that in related technologies, when the transformer is subjected to early warning, a used early warning value does not consider attribute difference of the transformer and the fault rate and the defect rate of the transformer so as to cause the condition that leakage alarm or false alarm is easy to generate when the transformer is subjected to fault early warning.
Description
Technical field
The present invention relates to electric and electronic technical field, in particular to a kind of evaluation method and device of transformer early warning value.
Background technology
Transformer is as important power transmission and transforming equipment, and its operational reliability is directly connected to the safe operation of whole electric system.At present, the on-line monitoring technique based on Gases Dissolved in Transformer Oil analysis (DissolvedGasAnalysis, referred to as DGA) realizes fault pre-alarming by the content of oil dissolved gas in Real-Time Monitoring transformer and the factor of created gase of gas.When the content of certain gas monitored and factor of created gase exceed the some values preset, monitoring system provides corresponding warning message.Therefore, set rational alarming value, effectively can avoid situations such as reporting by mistake, fail to report, and the early warning accuracy improving on-line monitoring system is had great importance.
In recent years, some were had to study to chromatography online monitoring system for transformer oil threshold value both at home and abroad.Such as, article " the oil-immerged inversed current transformer hydrogen Threshold Analysis based on significant difference " (Sun Xiang, Zhejiang electric power, 2014) utilize the amounts of hydrogen of dissolving in Oil of Current Transformer in significance difference specific analysis regional power grid to calculate the correlation parameter threshold value of hydrogen.The method only calculates a kind of correlation parameter threshold value of dissolved gas, and in computation process, do not consider failure rate and the ratio of defects of equipment, causes result of calculation inaccurate.Article " research based on the transformer diagnosis threshold value of on-the-spot oil chromatography data " (Song Anqi, North China Electric Power University, 2013) on-the-spot part oil chromatography data are utilized, calculating transformer oil dissolved gas reaches failure rate when GB demand value, minimal error critical value and least disadvantage critical value, and the critical value of Selective dissolution gas accordingly.The method does not relate to the calculating of the correlation parameter threshold value of oil dissolved gas, but lay particular emphasis on equipment failure rate calculate, and critical value be chosen at the experience depending on field personnel to a great extent, cause data decimation unreliable.Article " the transformer Reliability assessment methods based on oil chromatography data " (Zhang Yuning, power science and engineering, 2013) on-the-spot oil chromatography data are also utilized, the fiduciary level of transformer when calculating transformer oil dissolved gas reaches GB demand value, and to transformer exception state demarcation grade.The method does not relate to the calculating of the correlation parameter threshold value of oil dissolved gas yet, and in computation process, do not consider failure rate and the ratio of defects of equipment, causes result of calculation inaccurate.
In addition, patent " a kind of power market optimal hedging ratio estimation method " (Wang Yuanyuan, Institutes Of Technology Of Changsha, 2010) to the power market transaction historical data obtained, construct the electricity market Dynamic Hedging model based on T-Copula-GARCH, finally estimate Optimal Hedge Ratio.Patent " a kind of computing method of hedging efficiency of electric power future market " (simple treasure, Guangxi University, 2010) GARCH model and binary conditions G-Copula joint density function is utilized, construct the electricity market Dynamic Hedging model based on G-Copula-GARCH, calculate hedging efficiency of electric power future market.The related data that above two sections of patents are all aimed at power economy carries out calculating, and builds dynamic model, calculates corresponding estimated value.Because economic data does not relate to equipment failure rate and ratio of defects, the structure of above-mentioned model has nothing to do with failure rate and ratio of defects.
Existing both at home and abroad about the determination scheme of the standard demand value of Dissolved Gas Content in Transformer Oil and factor of created gase, ubiquity is based on the gas of kind less in transformer, to the too rough problem of transformer classification.And in transformer actual motion, by a certain or two kinds of gas contents and factor of created gase demand value, early warning is carried out to transformer, be easy to cause failing to report or reporting by mistake, and only arrange one " demand value ", make early warning system strategy too single, increase the cost of overhaul.That the classification of transformer is too rough, does not take into full account the difference between transformer arranging demand value.
For above-mentioned problem, at present effective solution is not yet proposed.
Summary of the invention
Embodiments provide a kind of evaluation method and device of transformer early warning value, with at least solve due in correlation technique when carrying out early warning to transformer, the early warning value used does not consider the attribute difference of transformer itself and the failure rate of transformer and ratio of defects, and cause easily occur when carrying out fault pre-alarming to transformer failing to report and warn or the technical matters of false alarm.
According to an aspect of the embodiment of the present invention, provide a kind of evaluation method of transformer early warning value, comprising: obtain the concentration of institute's dissolved gas and the cumulative distribution function of factor of created gase in the transformer oil of transformer; Corresponding inverse cumulative distribution function is determined according to above-mentioned cumulative distribution function; Obtain ratio of defects and/or the failure rate of above-mentioned transformer; After getting ratio of defects, above-mentioned inverse cumulative distribution function is utilized to estimate the demand value of above-mentioned concentration and above-mentioned factor of created gase according to above-mentioned ratio of defects; After getting failure rate, above-mentioned inverse cumulative distribution function is utilized to estimate the warning value of above-mentioned concentration and above-mentioned factor of created gase according to above-mentioned failure rate; Export above-mentioned demand value and above-mentioned warning value.
Further, determine that the step of above-mentioned cumulative distribution function comprises: the concentration and the factor of created gase data that obtain institute's dissolved gas in the lower transformer oil of different transformer classification; The cumulative distribution function under the classification of different transformer is determined according to above-mentioned data.
Further, the concentration and the factor of created gase data that obtain institute's dissolved gas in the lower transformer oil of different transformer classification comprise: the concentration data obtaining institute's dissolved gas in the transformer oil of all transformers in target area; Attribute information according to above-mentioned all transformers carries out differentiation classification to above-mentioned concentration data, obtains the concentration data of institute's dissolved gas in the lower transformer oil of different transformer classification; Calculate the factor of created gase of gas corresponding to such concentration data according to any two adjacent datas in the concentration data under the classification of each transformer, obtain the factor of created gase data of institute's dissolved gas in the lower transformer oil of different transformer classification.
Further, after the concentration obtaining institute's dissolved gas in transformer oil under the classification of different transformer and factor of created gase data, said method also comprises: according to the concentration numbers of institute's dissolved gas in the lower transformer oil of different transformer classification and the corresponding statistic histogram of factor of created gase Plotting data and matched curve; The concentration of institute's dissolved gas and the distributed model of factor of created gase in the lower transformer oil of each transformer classification is determined according to the above-mentioned statistic histogram drawn and above-mentioned matched curve; Using distribution function corresponding for above-mentioned distributed model as the concentration of institute's dissolved gas and the cumulative distribution function of factor of created gase in the lower transformer oil of above-mentioned each transformer classification.
Further, above-mentioned cumulative distribution function is Weibull Function, and above-mentioned inverse cumulative distribution function is the inverse function of above-mentioned Weibull Function.
Further, the ratio of defects and/or the failure rate that obtain above-mentioned transformer comprise: obtain the transformer field service information under the classification of each transformer; Ratio of defects and/or the failure rate of the transformer under above-mentioned each transformer classification is extracted from above-mentioned transformer field service information.
Further, above-mentioned inverse cumulative distribution function is utilized to estimate that the demand value of above-mentioned concentration and above-mentioned factor of created gase comprises according to above-mentioned ratio of defects: when variate-value is 1-ratio of defects, using the functional value to be obtained by above-mentioned inverse cumulative distribution function estimation as above-mentioned demand value.
Further, above-mentioned inverse cumulative distribution function is utilized to estimate that the warning value of above-mentioned concentration and above-mentioned factor of created gase comprises according to above-mentioned failure rate: when variate-value is 1-failure rate, to be worth as above-mentioned warning by the functional value obtained by above-mentioned inverse cumulative distribution function estimation.
According to the another aspect of the embodiment of the present invention, additionally provide a kind of estimating device of transformer early warning value, comprising: the first acquiring unit, for obtain transformer transformer oil in the concentration of institute's dissolved gas and the cumulative distribution function of factor of created gase; First determining unit, for determining corresponding inverse cumulative distribution function according to above-mentioned cumulative distribution function; Second acquisition unit, for obtaining ratio of defects and/or the failure rate of above-mentioned transformer; Evaluation unit, for after getting ratio of defects, utilizes above-mentioned inverse cumulative distribution function to estimate the demand value of above-mentioned concentration and above-mentioned factor of created gase according to above-mentioned ratio of defects; After getting failure rate, above-mentioned inverse cumulative distribution function is utilized to estimate the warning value of above-mentioned concentration and above-mentioned factor of created gase according to above-mentioned failure rate; Output unit, for exporting above-mentioned demand value and above-mentioned warning value.
Further, said apparatus also comprises: the second determining unit, for determining above-mentioned cumulative distribution function, above-mentioned second determining unit comprises: the first acquisition module, for obtaining concentration and the factor of created gase data of institute's dissolved gas in the lower transformer oil of different transformer classification; Determination module, for determining the cumulative distribution function under the classification of different transformer according to above-mentioned data.
Further, above-mentioned first acquisition module comprises: obtain submodule, for obtain all transformers in target area transformer oil in the concentration data of institute's dissolved gas; Classification submodule, for carrying out differentiation classification according to the attribute information of above-mentioned all transformers to above-mentioned concentration data, obtains the concentration data of institute's dissolved gas in the lower transformer oil of different transformer classification; Calculating sub module, for calculating the factor of created gase of gas corresponding to such concentration data according to any two adjacent datas in the concentration data under the classification of each transformer, obtains the factor of created gase data of institute's dissolved gas in the lower transformer oil of different transformer classification.
Further, said apparatus also comprises: image-drawing unit, for after the concentration obtaining institute's dissolved gas in transformer oil under the classification of different transformer and factor of created gase data, according to the concentration numbers of institute's dissolved gas in the lower transformer oil of different transformer classification and the corresponding statistic histogram of factor of created gase Plotting data and matched curve; 3rd determining unit, for determining the concentration of institute's dissolved gas and the distributed model of factor of created gase in the lower transformer oil of each transformer classification according to the above-mentioned statistic histogram drawn and above-mentioned matched curve, and using distribution function corresponding for above-mentioned distributed model as the concentration of institute's dissolved gas and the cumulative distribution function of factor of created gase in the lower transformer oil of above-mentioned each transformer classification.
Further, above-mentioned second acquisition unit comprises: the second acquisition module, for obtaining the transformer field service information under the classification of each transformer; Extraction module, for extracting ratio of defects and/or the failure rate of the transformer under above-mentioned each transformer classification from above-mentioned transformer field service information.
Further, above-mentioned evaluation unit also for when variate-value is 1-ratio of defects, using the functional value that obtained by above-mentioned inverse cumulative distribution function estimation as above-mentioned demand value.
Further, the functional value obtained by above-mentioned inverse cumulative distribution function estimation, also for when variate-value is 1-failure rate, is worth as above-mentioned warning by above-mentioned evaluation unit.
In embodiments of the present invention, adopt the mode in conjunction with the attributive character of transformer self and the ratio of defects of transformer and failure rate, by the concentration of institute's dissolved gas and the cumulative distribution function of factor of created gase in the transformer oil of acquisition transformer; Corresponding inverse cumulative distribution function is determined according to cumulative distribution function; Obtain ratio of defects and/or the failure rate of transformer; After getting ratio of defects, also utilize the demand value of inverse cumulative distribution function estimated concentration and factor of created gase according to ratio of defects; After getting failure rate, also utilize the warning value of inverse cumulative distribution function estimated concentration and factor of created gase according to failure rate; Export demand value and warning value, reach the object using the early warning value of the attributive character difference and the ratio of defects of transformer and the oil dissolved gas of failure rate and factor of created gase that consider transformer self to carry out early warning, thus achieve the technique effect preventing from failing to report or reporting by mistake, and then solve due in correlation technique when carrying out early warning to transformer, the early warning value used does not consider the attribute difference of transformer itself and the failure rate of transformer and ratio of defects, and cause easily occur when carrying out fault pre-alarming to transformer failing to report and warn or the technical matters of false alarm.
Accompanying drawing explanation
Accompanying drawing described herein is used to provide a further understanding of the present invention, and form a application's part, schematic description and description of the present invention, for explaining the present invention, does not form inappropriate limitation of the present invention.In the accompanying drawings:
Fig. 1 is the process flow diagram of the evaluation method of a kind of optional transformer early warning value according to the embodiment of the present invention;
Fig. 2 is statistic histogram and the matched curve of dissolving the content of hydrogen in the 220kV transformer oil according to the embodiment of the present invention;
Fig. 3 is statistic histogram and the matched curve of the factor of created gase of dissolve ethylene in the 220kV transformer oil according to the embodiment of the present invention; And
Fig. 4 is the schematic diagram of the estimating device of a kind of optional transformer early warning value according to the embodiment of the present invention.
Embodiment
The present invention program is understood better in order to make those skilled in the art person, below in conjunction with the accompanying drawing in the embodiment of the present invention, technical scheme in the embodiment of the present invention is clearly and completely described, obviously, described embodiment is only the embodiment of a part of the present invention, instead of whole embodiments.Based on the embodiment in the present invention, those of ordinary skill in the art, not making the every other embodiment obtained under creative work prerequisite, should belong to the scope of protection of the invention.
It should be noted that, term " first ", " second " etc. in instructions of the present invention and claims and above-mentioned accompanying drawing are for distinguishing similar object, and need not be used for describing specific order or precedence.Should be appreciated that the data used like this can be exchanged in the appropriate case, so as embodiments of the invention described herein can with except here diagram or describe those except order implement.In addition, term " comprises " and " having " and their any distortion, intention is to cover not exclusive comprising, such as, contain those steps or unit that the process of series of steps or unit, method, system, product or equipment is not necessarily limited to clearly list, but can comprise clearly do not list or for intrinsic other step of these processes, method, product or equipment or unit.
Embodiment 1
According to the embodiment of the present invention, provide a kind of embodiment of the method for evaluation method of optional transformer early warning value, it should be noted that, can perform in the computer system of such as one group of computer executable instructions in the step shown in the process flow diagram of accompanying drawing, and, although show logical order in flow charts, in some cases, can be different from the step shown or described by order execution herein.
Fig. 1 is the process flow diagram of the evaluation method of a kind of optional transformer early warning value according to the embodiment of the present invention, and as shown in Figure 1, the method comprises the steps:
Step S102, obtains the concentration of institute's dissolved gas and the cumulative distribution function of factor of created gase in the transformer oil of transformer;
Step S104, determines corresponding inverse cumulative distribution function according to cumulative distribution function;
Step S106, obtains ratio of defects and/or the failure rate of transformer;
Step S108, after getting ratio of defects, also utilizes the demand value of inverse cumulative distribution function estimated concentration and factor of created gase according to ratio of defects;
Step S110, after getting failure rate, also utilizes the warning value of inverse cumulative distribution function estimated concentration and factor of created gase according to failure rate;
Step S112, exports demand value and warning value.
Pass through above-mentioned steps, when utilizing distribution function to estimate the differentiation early warning value of the concentration of institute's dissolved gas in transformer oil and factor of created gase, due to factors such as the ratio of defects of the difference under having taken into full account different attribute condition between the lower transformer of different transformer classification and transformer and failure rates, therefore early warning value threshold value (comprising: demand value and warning value etc.) more accurately can be obtained, like this, when using the early warning value threshold value obtained by the present invention to carry out early warning, can prevent to fail to report the situations such as alert or false alarm.
Alternatively, determine that the step of cumulative distribution function comprises:
S2, obtains concentration and the factor of created gase data of institute's dissolved gas in the lower transformer oil of different transformer classification;
S4, determines the cumulative distribution function under the classification of different transformer according to data.
It should be noted that, can according to the attributive character of transformer (as transformer grade etc.), all transformers in the electrical network of certain specific region are carried out classification process, thus concentration and the factor of created gase data of institute's dissolved gas in the transformer oil under different transformer classification can be collected.Like this, when utilizing distribution function to estimate the differentiation early warning value of the concentration of institute's dissolved gas in transformer oil and factor of created gase, when factors such as the ratio of defects taking into full account transformer and failure rates, supplement the difference between the lower transformer of different transformer classification under considering different attribute condition again, early warning value threshold value (comprising: demand value and warning value etc.) more accurately can be obtained, making when using the early warning value threshold value obtained by the present invention to carry out early warning, can prevent to fail to report the situations such as alert or false alarm.
Further alternatively, the concentration and the factor of created gase data that obtain institute's dissolved gas in the lower transformer oil of different transformer classification comprise:
S6, obtains the concentration data of institute's dissolved gas in the transformer oil of all transformers in target area;
S8, the attribute information according to all transformers carries out differentiation classification to concentration data, obtains the concentration data of institute's dissolved gas in the lower transformer oil of different transformer classification;
S10, calculates the factor of created gase of gas corresponding to such concentration data according to any two adjacent datas in the concentration data under the classification of each transformer, obtains the factor of created gase data of institute's dissolved gas in the lower transformer oil of different transformer classification.
It should be noted that, real time on-line monitoring can be carried out by the sensor installed on the transformer, gather the online monitoring data of the transformer in a period of time, and therefrom extract the concentration data of institute's dissolved gas in the transformer oil of all kinds of transformer, and then calculate corresponding factor of created gase, obtain factor of created gase data.Such as, oil chromatography Monitoring Data 114326 is obtained altogether in the present embodiment, the form of data is as shown in table 1 (only show partial information), in original oil chromatogram monitoring data, comprise the information of the transformer that sensor is installed, the numbering of sensor, monitoring place, monitoring date, ordinal number date, the information of 8 kinds of gases (as hydrogen, carbon monoxide, carbon dioxide, methane, ethane, ethene, acetylene, total hydrocarbon) of dissolving in oil.Wherein, the ordinal number date is relative-date, and if the ordinal number date arranging correspondence on January 1st, 2013 is 1, then the ordinal number date that on January 2nd, 2013 is corresponding is then 2, the ordinal number date of correspondence on Dec 31st, 2013 is 365, and the effect on ordinal number date conveniently calculates relative factor of created gase.
Table 1
The attribute of transformer refers to the build-in attribute of transformer.Embodiment, can use this attribute of electric pressure of transformer to carry out differentiation classification process to oil chromatography Monitoring Data.Such as, 114326 above-mentioned data messages come from the transformer of 110kV, 220kV and 500kV tri-kinds of electric pressures, add up number of units and the data amount information of the transformer under each electric pressure thus, as shown in table 2 (result according to electric pressure classification):
Table 2
| Electric pressure/kV | Number of units/platform | Data volume/bar |
| 110 | 8 | 1844 |
| 220 | 173 | 51236 |
| 500 | 220 | 61246 |
| Amount to | 401 | 114326 |
During enforcement, the relative factor of created gase of the 8 kinds of gases (comprising hydrogen, carbon monoxide, carbon dioxide, methane, ethane, ethene, acetylene and total hydrocarbon) under each classification can be calculated in units of sky.The computing formula of relative factor of created gase is:
γ in formula
i+1represent the relative gas production rate of the i-th+1 day, unit is %/sky; C
i+1represent the Oil Dissolved Gases Concentration monitored for the i-th+1 day, unit is μ L/L; C
irepresent that the Oil Dissolved Gases Concentration unit monitored for i-th day is μ L/L.
Pass through the embodiment of the present invention, based on the historical data such as concentration of a large amount of Gases Dissolved in Transformer Oils, according to the self attributes of transformer, differentiation classification is carried out to data, ratio of defects and failure rate are associated with distribution function, utilize Inverse distribution function to calculate the content of 8 kinds of oil dissolved gas (hydrogen, carbon monoxide, carbon dioxide, methane, ethane, ethene, acetylene and total hydrocarbon) of transformer under different attribute classification and the demand value of factor of created gase thereof and warning value.By transformer is classified according to its attribute, reach and overcome in correlation technique owing to not considering difference between transformer attribute or according to too slightly mad during attributive classification and the inaccurate defect of threshold value that is that cause.
Alternatively, after the concentration obtaining institute's dissolved gas in transformer oil under the classification of different transformer and factor of created gase data, method also comprises:
S12, according to the concentration numbers of institute's dissolved gas in the lower transformer oil of different transformer classification and the corresponding statistic histogram of factor of created gase Plotting data and matched curve;
S14, determines the concentration of institute's dissolved gas and the distributed model of factor of created gase in the lower transformer oil of each transformer classification according to the statistic histogram drawn and matched curve;
S16, using distribution function corresponding for distributed model as the concentration of institute's dissolved gas and the cumulative distribution function of factor of created gase in the lower transformer oil of each transformer classification.
It should be noted that, cumulative distribution function is Weibull Function, and inverse cumulative distribution function is the inverse function of Weibull Function.
During enforcement, at acquisition Dissolved Gas Content in Transformer Oil, and after calculating relative factor of created gase according to formula (1), statistical study can be carried out respectively to group dissolved gas content of 8 under each classification and 8 groups of dissolved gas factor of created gase data, draw the content of oil dissolved gas and the statistic histogram of factor of created gase and matched curve, as shown in Figures 2 and 3 (to dissolve the content of hydrogen and the factor of created gase of ethene in 220kV transformer oil), also be, during enforcement, a large amount of on-the-spot oil chromatography data are carried out differentiation classification according to transformer self attributes, be about to have oil chromatography data corresponding to the transformer of a certain same alike result as a class, and the absolute factor of created gase of transformer calculate this classification in units of sky under.Afterwards, statistical study is carried out to the Oil Dissolved Gases Concentration of the transformer under each classification and factor of created gase data, builds corresponding distributed model and estimation model parameter.And then add up ratio of defects and the failure rate of transformer under each classification, and its cumulative probability with Oil Dissolved Gases Concentration and in the distributed model of factor of created gase is associated, utilize the inverse cumulative distribution function of the distributed model of oil chromatography and factor of created gase thereof to calculate corresponding demand value and warning value.
Such as, as can be seen from statistic histogram and matched curve, content and the factor of created gase thereof of oil dissolved gas meet Weibull distribution substantially, build Weibull distribution model thus, and calculate the correlation parameter of Weibull distribution model.Wherein, the probability density function of Weibull distribution and the cumulative distribution function of correspondence thereof are respectively:
Wherein, β represents Weibull slope, also claims form parameter; η characterization value, also claims scale parameter, estimates form parameter and scale parameter by maximum-likelihood method, and likelihood function corresponding to Weibull distribution model is:
Likelihood equations is:
(4) are substituted into the estimated value that (5) can obtain β and η, are also the parameter value of distribution function.
Alternatively, the ratio of defects and/or the failure rate that obtain transformer can comprise:
S18, obtains the transformer field service information under the classification of each transformer;
S20, extracts ratio of defects and/or the failure rate of the transformer under the classification of each transformer from transformer field service information.
During enforcement, the site examining and repairing data of transformer can be searched from the record of examination at scene, and extract ratio of defects and the failure rate of transformer.Due to ratio of defects and failure rate all from site examining and repairing record, therefore improve ratio of defects and failure rate reliability and validity.According to the record of examination at scene, failure rate and the ratio of defects of each voltage gradation counted are as shown in table 3:
Table 3
| Electric pressure/kV | Ratio of defects/% | Failure rate/% |
| 110 | 2.82 | 0.05 |
| 220 | 4.54 | 0.18 |
| 500 | 1.79 | 0.9 |
Alternatively, the demand value of inverse cumulative distribution function estimated concentration and factor of created gase is also utilized to comprise according to ratio of defects:
S22, when variate-value is 1-ratio of defects, using the functional value that obtained by inverse cumulative distribution function estimation as demand value.
In like manner, the warning value bag of inverse cumulative distribution function estimated concentration and factor of created gase is also utilized according to failure rate:
S24, when variate-value is 1-failure rate, is worth the functional value obtained by inverse cumulative distribution function estimation as warning.
Wherein, the inverse cumulative distribution function of Weibull function is:
x＝F
-1(p|η,β)＝-η[ln(1-p)]
1/β,p∈[0,1](6)
Wherein, p represents cumulative distribution probability, and x represents the value corresponding when cumulative probability is p.Particularly, when the cumulative probability arranging inverse cumulative distribution function equals 1-ratio of defects, the estimated value obtained is demand value, and when the cumulative probability arranging inverse cumulative distribution function equals 1-failure rate, the estimated value obtained is warning value.The content of the oil dissolved gas under each classification and the demand value of factor of created gase thereof and warning value can be drawn by formula (6).Wherein, based on table 1, table 2 and table 3 column data, the content of dissolved gas calculated according to the present invention and the demand value of factor of created gase thereof and warning value are respectively as shown in table 4 (in each grade transformer the demand value of the content of the oil dissolved gas of 7 kinds of gases and total hydrocarbon and warning value (μ L/L)) and table 5 (in each grade transformer the demand value of the factor of created gase of the oil dissolved gas of 7 kinds of gases and total hydrocarbon and warning value (%)):
Table 4
Table 5
Embodiment 2
According to the embodiment of the present invention, provide a kind of device embodiment of estimating device of transformer early warning value.
Fig. 4 is the schematic diagram of the estimating device of a kind of optional transformer early warning value according to the embodiment of the present invention, as shown in Figure 4, this device comprises: the first acquiring unit 402, first determining unit 404, second acquisition unit 406, evaluation unit 408 and output unit 410.First acquiring unit 402, for obtain transformer transformer oil in the concentration of institute's dissolved gas and the cumulative distribution function of factor of created gase; First determining unit 404, for determining corresponding inverse cumulative distribution function according to cumulative distribution function; Second acquisition unit 406, for obtaining ratio of defects and/or the failure rate of transformer; Evaluation unit 408, for after getting ratio of defects, also utilizes the demand value of inverse cumulative distribution function estimated concentration and factor of created gase according to ratio of defects; After getting failure rate, also utilize the warning value of inverse cumulative distribution function estimated concentration and factor of created gase according to failure rate; Output unit 410, for exporting demand value and warning value.。
Pass through the embodiment of the present invention, when utilizing distribution function to estimate the differentiation early warning value of the concentration of institute's dissolved gas in transformer oil and factor of created gase, due to factors such as the ratio of defects of the difference under having taken into full account different attribute condition between the lower transformer of different transformer classification and transformer and failure rates, therefore early warning value threshold value (comprising: demand value and warning value etc.) more accurately can be obtained, like this, when using the early warning value threshold value obtained by the present invention to carry out early warning, can prevent to fail to report the situations such as alert or false alarm.
Further, said apparatus also comprises: the second determining unit, and for determining cumulative distribution function, the second determining unit comprises: the first acquisition module, for obtaining concentration and the factor of created gase data of institute's dissolved gas in the lower transformer oil of different transformer classification; Determination module, for determining the cumulative distribution function under the classification of different transformer according to data.
It should be noted that, can according to the attributive character of transformer (as transformer grade etc.), all transformers in the electrical network of certain specific region are carried out classification process, thus concentration and the factor of created gase data of institute's dissolved gas in the transformer oil under different transformer classification can be collected.Like this, when utilizing distribution function to estimate the differentiation early warning value of the concentration of institute's dissolved gas in transformer oil and factor of created gase, when factors such as the ratio of defects taking into full account transformer and failure rates, supplement the difference between the lower transformer of different transformer classification under considering different attribute condition again, early warning value threshold value (comprising: demand value and warning value etc.) more accurately can be obtained, making when using the early warning value threshold value obtained by the present invention to carry out early warning, can prevent to fail to report the situations such as alert or false alarm.
Further alternatively, the first acquisition module comprises: obtain submodule, for obtain all transformers in target area transformer oil in the concentration data of institute's dissolved gas; Classification submodule, carries out differentiation classification for the attribute information according to all transformers to concentration data, obtains the concentration data of institute's dissolved gas in the lower transformer oil of different transformer classification; Calculating sub module, for calculating the factor of created gase of gas corresponding to such concentration data according to any two adjacent datas in the concentration data under the classification of each transformer, obtains the factor of created gase data of institute's dissolved gas in the lower transformer oil of different transformer classification.
It should be noted that, real time on-line monitoring can be carried out by the sensor installed on the transformer, gather the online monitoring data of the transformer in a period of time, and therefrom extract the concentration data of institute's dissolved gas in the transformer oil of all kinds of transformer, and then calculate corresponding factor of created gase, obtain factor of created gase data.Such as, oil chromatography Monitoring Data 114326 is obtained altogether in the present embodiment, the form of data is as shown in table 1 (only show partial information), in original oil chromatogram monitoring data, comprise the information of the transformer that sensor is installed, the numbering of sensor, monitoring place, monitoring date, ordinal number date, the information of 8 kinds of gases (as hydrogen, carbon monoxide, carbon dioxide, methane, ethane, ethene, acetylene, total hydrocarbon) of dissolving in oil.Wherein, the ordinal number date is relative-date, and if the ordinal number date arranging correspondence on January 1st, 2013 is 1, then the ordinal number date that on January 2nd, 2013 is corresponding is then 2, the ordinal number date of correspondence on Dec 31st, 2013 is 365, and the effect on ordinal number date conveniently calculates relative factor of created gase.
The property value of transformer refers to the build-in attribute of transformer.Embodiment, can use this attribute of electric pressure of transformer to carry out differentiation classification process to oil chromatography Monitoring Data.Such as, 114326 above-mentioned data messages come from the transformer of 110kV, 220kV and 500kV tri-kinds of electric pressures, add up number of units and the data amount information of the transformer under each electric pressure thus, as shown in table 2 (result according to electric pressure classification).
During enforcement, the relative factor of created gase of the 8 kinds of gases (comprising hydrogen, carbon monoxide, carbon dioxide, methane, ethane, ethene, acetylene and total hydrocarbon) under each classification can be calculated in units of sky.The computing formula of relative factor of created gase is formula (1).
Pass through the embodiment of the present invention, based on a large amount of oil dissolved gas historical datas, according to the self attributes of transformer, differentiation classification is carried out to data, ratio of defects and failure rate are associated with distribution function, utilize Inverse distribution function to calculate the content of 8 kinds of oil dissolved gas (hydrogen, carbon monoxide, carbon dioxide, methane, ethane, ethene, acetylene and total hydrocarbon) of the transformer under unified attribute and the demand value of factor of created gase thereof and warning value.By transformer is classified according to its property value, reach and overcome in correlation technique owing to not classify or classifying the madder and inaccurate defect of estimation result that is that cause to the monitoring parameter of oil chromatography.
Further, said apparatus also comprises: image-drawing unit, for after the concentration obtaining institute's dissolved gas in transformer oil under the classification of different transformer and factor of created gase data, according to the concentration numbers of institute's dissolved gas in the lower transformer oil of different transformer classification and the corresponding statistic histogram of factor of created gase Plotting data and matched curve; 3rd determining unit, for determining the concentration of institute's dissolved gas and the distributed model of factor of created gase in the lower transformer oil of each transformer classification according to the statistic histogram drawn and matched curve, and using distribution function corresponding for distributed model as the concentration of institute's dissolved gas and the cumulative distribution function of factor of created gase in the lower transformer oil of each transformer classification.
During enforcement, at acquisition Dissolved Gas Content in Transformer Oil, and after calculating relative factor of created gase according to formula (1), statistical study can be carried out respectively to group dissolved gas content of 8 under each classification and 8 groups of dissolved gas factor of created gase data, draw the content of oil dissolved gas and the statistic histogram of factor of created gase and matched curve, as shown in Figures 2 and 3 (to dissolve the content of hydrogen and the factor of created gase of ethene in 220kV transformer oil), also be, during enforcement, a large amount of on-the-spot oil chromatography data are carried out differentiation classification according to transformer self attributes value, be about to have oil chromatography data corresponding to the transformer of a certain same alike result as a class, and the absolute factor of created gase of transformer calculate this classification in units of sky under.Afterwards, statistical study is carried out to the Oil Dissolved Gases Concentration of the transformer under each classification and factor of created gase data, builds corresponding distributed model and estimation model parameter.And then add up ratio of defects and the failure rate of transformer under each classification, and its cumulative probability with oil chromatography and in the distributed model of factor of created gase is associated, utilize the inverse cumulative distribution function of the distributed model of oil chromatography and factor of created gase thereof to calculate corresponding demand value and warning value.
Such as, as can be seen from statistic histogram and matched curve, content and the factor of created gase thereof of oil dissolved gas meet Weibull distribution substantially, build Weibull distribution model thus, and calculate the correlation parameter of Weibull distribution model.Wherein, the probability density function of Weibull distribution and the cumulative distribution function of correspondence thereof are respectively formula (2) and formula (3), form parameter and scale parameter is estimated by maximum-likelihood method, likelihood function corresponding to Weibull distribution model is formula (4), likelihood equations is formula (5), (4) are substituted into the estimated value that (5) can obtain β and η, are also the parameter value of distribution function.
Further, second acquisition unit comprises: the second acquisition module, for obtaining the transformer field service information under the classification of each transformer; Extraction module, for extracting ratio of defects and/or the failure rate of the transformer under the classification of each transformer from transformer field service information.
During enforcement, the site examining and repairing data of transformer can be searched from the record of examination at scene, and extract ratio of defects and/or the failure rate of transformer.Due to ratio of defects and failure rate all from site examining and repairing record, therefore improve ratio of defects and failure rate reliability and validity.According to the record of examination at scene, failure rate and the ratio of defects of each voltage gradation counted are as shown in table 3.
Further, evaluation unit is also for when variate-value is 1-ratio of defects, using the functional value that obtained by inverse cumulative distribution function estimate as demand value, and for when variate-value is 1-failure rate, be worth by the functional value obtained against cumulative distribution function estimation as warning.
Wherein, the inverse cumulative distribution function of Weibull function is formula (6).Particularly, when the cumulative probability arranging inverse cumulative distribution function equals 1-ratio of defects, the estimated value obtained is demand value, and when the cumulative probability arranging inverse cumulative distribution function equals 1-failure rate, the estimated value obtained is warning value.The content of the oil dissolved gas under each classification and the demand value of factor of created gase thereof and warning value can be drawn by formula (6).Wherein, based on table 1, table 2 and table 3 column data, the content of dissolved gas calculated according to the present invention and the demand value of factor of created gase thereof and warning value are respectively as shown in table 4 (in each grade transformer the demand value of the content of the oil dissolved gas of 7 kinds of gases and total hydrocarbon and warning value (μ L/L)) and table 5 (in each grade transformer the demand value of the factor of created gase of the oil dissolved gas of 7 kinds of gases and total hydrocarbon and warning value (%)).
The invention described above embodiment sequence number, just to describing, does not represent the quality of embodiment.
In the above embodiment of the present invention, the description of each embodiment is all emphasized particularly on different fields, in certain embodiment, there is no the part described in detail, can see the associated description of other embodiments.
In several embodiments that the application provides, should be understood that, disclosed technology contents, the mode by other realizes.Wherein, device embodiment described above is only schematic, the such as division of described unit, can be that a kind of logic function divides, actual can have other dividing mode when realizing, such as multiple unit or assembly can in conjunction with or another system can be integrated into, or some features can be ignored, or do not perform.Another point, shown or discussed coupling each other or direct-coupling or communication connection can be by some interfaces, and the indirect coupling of unit or module or communication connection can be electrical or other form.
The described unit illustrated as separating component or can may not be and physically separates, and the parts as unit display can be or may not be physical location, namely can be positioned at a place, or also can be distributed on multiple unit.Some or all of unit wherein can be selected according to the actual needs to realize the object of the present embodiment scheme.
In addition, each functional unit in each embodiment of the present invention can be integrated in a processing unit, also can be that the independent physics of unit exists, also can two or more unit in a unit integrated.Above-mentioned integrated unit both can adopt the form of hardware to realize, and the form of SFU software functional unit also can be adopted to realize.
If described integrated unit using the form of SFU software functional unit realize and as independently production marketing or use time, can be stored in a computer read/write memory medium.Based on such understanding, the part that technical scheme of the present invention contributes to prior art in essence in other words or all or part of of this technical scheme can embody with the form of software product, this computer software product is stored in a storage medium, comprises all or part of step of some instructions in order to make a computer equipment (can be personal computer, server or the network equipment etc.) perform method described in each embodiment of the present invention.And aforesaid storage medium comprises: USB flash disk, ROM (read-only memory) (ROM, Read-OnlyMemory), random access memory (RAM, RandomAccessMemory), portable hard drive, magnetic disc or CD etc. various can be program code stored medium.
The above is only the preferred embodiment of the present invention; it should be pointed out that for those skilled in the art, under the premise without departing from the principles of the invention; can also make some improvements and modifications, these improvements and modifications also should be considered as protection scope of the present invention.
Claims (15)
1. an evaluation method for transformer early warning value, is characterized in that, comprising:
Obtain the concentration of institute's dissolved gas and the cumulative distribution function of factor of created gase in the transformer oil of transformer;
Corresponding inverse cumulative distribution function is determined according to described cumulative distribution function;
Obtain ratio of defects and/or the failure rate of described transformer;
After getting ratio of defects, described inverse cumulative distribution function is utilized to estimate the demand value of described concentration and described factor of created gase according to described ratio of defects;
After getting failure rate, described inverse cumulative distribution function is utilized to estimate the warning value of described concentration and described factor of created gase according to described failure rate;
Export described demand value and described warning value.
2. method according to claim 1, is characterized in that, determines that the step of described cumulative distribution function comprises:
Obtain concentration and the factor of created gase data of institute's dissolved gas in the lower transformer oil of different transformer classification;
The cumulative distribution function under the classification of different transformer is determined according to described data.
3. method according to claim 2, is characterized in that, the concentration and the factor of created gase data that obtain institute's dissolved gas in the lower transformer oil of different transformer classification comprise:
Obtain the concentration data of institute's dissolved gas in the transformer oil of all transformers in target area;
Attribute information according to described all transformers carries out differentiation classification to described concentration data, obtains the concentration data of institute's dissolved gas in the lower transformer oil of different transformer classification;
Calculate the factor of created gase of gas corresponding to such concentration data according to any two adjacent datas in the concentration data under the classification of each transformer, obtain the factor of created gase data of institute's dissolved gas in the lower transformer oil of different transformer classification.
4. method according to claim 1, is characterized in that, after the concentration obtaining institute's dissolved gas in transformer oil under the classification of different transformer and factor of created gase data, described method also comprises:
According to the concentration numbers of institute's dissolved gas in the lower transformer oil of different transformer classification and the corresponding statistic histogram of factor of created gase Plotting data and matched curve;
The concentration of institute's dissolved gas and the distributed model of factor of created gase in the lower transformer oil of each transformer classification is determined according to the described statistic histogram drawn and described matched curve;
Using distribution function corresponding for described distributed model as the concentration of institute's dissolved gas and the cumulative distribution function of factor of created gase in the lower transformer oil of described each transformer classification.
5. method according to claim 1, is characterized in that, described cumulative distribution function is Weibull Function, and described inverse cumulative distribution function is the inverse function of described Weibull Function.
6. method according to claim 1, is characterized in that, the ratio of defects and/or the failure rate that obtain described transformer comprise:
Obtain the transformer field service information under the classification of each transformer;
Ratio of defects and/or the failure rate of the transformer under described each transformer classification is extracted from described transformer field service information.
7. method according to claim 1, is characterized in that, utilizes described inverse cumulative distribution function to estimate that the demand value of described concentration and described factor of created gase comprises according to described ratio of defects:
When variate-value is 1-ratio of defects, using the functional value that obtained by described inverse cumulative distribution function estimation as described demand value.
8. method according to claim 1, is characterized in that, utilizes described inverse cumulative distribution function to estimate that the warning value of described concentration and described factor of created gase comprises according to described failure rate:
When variate-value is 1-failure rate, the functional value obtained by described inverse cumulative distribution function estimation is worth as described warning.
9. an estimating device for transformer early warning value, is characterized in that, comprising:
First acquiring unit, for obtain transformer transformer oil in the concentration of institute's dissolved gas and the cumulative distribution function of factor of created gase;
First determining unit, for determining corresponding inverse cumulative distribution function according to described cumulative distribution function;
Second acquisition unit, for obtaining ratio of defects and/or the failure rate of described transformer;
Evaluation unit, for after getting ratio of defects, utilizes described inverse cumulative distribution function to estimate the demand value of described concentration and described factor of created gase according to described ratio of defects; After getting failure rate, described inverse cumulative distribution function is utilized to estimate the warning value of described concentration and described factor of created gase according to described failure rate;
Output unit, for exporting described demand value and described warning value.
10. device according to claim 9, is characterized in that, described device also comprises: the second determining unit, and for determining described cumulative distribution function, described second determining unit comprises:
First acquisition module, for obtaining concentration and the factor of created gase data of institute's dissolved gas in the lower transformer oil of different transformer classification;
Determination module, for determining the cumulative distribution function under the classification of different transformer according to described data.
11. devices according to claim 10, is characterized in that, described first acquisition module comprises:
Obtain submodule, for obtain all transformers in target area transformer oil in the concentration data of institute's dissolved gas;
Classification submodule, for carrying out differentiation classification according to the attribute information of described all transformers to described concentration data, obtains the concentration data of institute's dissolved gas in the lower transformer oil of different transformer classification;
Calculating sub module, for calculating the factor of created gase of gas corresponding to such concentration data according to any two adjacent datas in the concentration data under the classification of each transformer, obtains the factor of created gase data of institute's dissolved gas in the lower transformer oil of different transformer classification.
12. devices according to claim 9, is characterized in that, described device also comprises:
Image-drawing unit, for after the concentration obtaining institute's dissolved gas in transformer oil under the classification of different transformer and factor of created gase data, according to the concentration numbers of institute's dissolved gas in the lower transformer oil of different transformer classification and the corresponding statistic histogram of factor of created gase Plotting data and matched curve;
3rd determining unit, for determining the concentration of institute's dissolved gas and the distributed model of factor of created gase in the lower transformer oil of each transformer classification according to the described statistic histogram drawn and described matched curve, and using distribution function corresponding for described distributed model as the concentration of institute's dissolved gas and the cumulative distribution function of factor of created gase in the lower transformer oil of described each transformer classification.
13. devices according to claim 9, is characterized in that, described second acquisition unit comprises:
Second acquisition module, for obtaining the transformer field service information under the classification of each transformer;
Extraction module, for extracting ratio of defects and/or the failure rate of the transformer under described each transformer classification from described transformer field service information.
14. devices according to claim 9, is characterized in that, described evaluation unit also for when variate-value is 1-ratio of defects, using the functional value that obtained by described inverse cumulative distribution function estimation as described demand value.
15. devices according to claim 9, is characterized in that, the functional value obtained by described inverse cumulative distribution function estimation, also for when variate-value is 1-failure rate, is worth as described warning by described evaluation unit.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201510438809.7A CN105117512B (en) | 2015-07-23 | 2015-07-23 | The evaluation method and device of transformer early warning value |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201510438809.7A CN105117512B (en) | 2015-07-23 | 2015-07-23 | The evaluation method and device of transformer early warning value |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN105117512A true CN105117512A (en) | 2015-12-02 |
| CN105117512B CN105117512B (en) | 2018-06-08 |
Family
ID=54665500
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201510438809.7A Active CN105117512B (en) | 2015-07-23 | 2015-07-23 | The evaluation method and device of transformer early warning value |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN105117512B (en) |
Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106442830A (en) * | 2016-09-29 | 2017-02-22 | 广州供电局有限公司 | Method and system for detecting alarm value of gas content of transformer oil |
| CN106596754A (en) * | 2016-11-22 | 2017-04-26 | 华北电力大学 | Assessment method and device for oil chromatographic sensor effectiveness |
| CN106771513A (en) * | 2016-11-22 | 2017-05-31 | 华北电力大学 | The determination method and device of arrester early warning value |
| CN109187809A (en) * | 2018-10-27 | 2019-01-11 | 国网山东省电力公司电力科学研究院 | A kind of Gases Dissolved in Transformer Oil data generate in real time and analysis system |
| CN109541096A (en) * | 2018-11-09 | 2019-03-29 | 福建和盛高科技产业有限公司 | 220kV Gases Dissolved in Transformer Oil volume fraction dynamic early-warning method |
| CN110674983A (en) * | 2019-09-05 | 2020-01-10 | 辽宁工程技术大学 | Working face gas early warning method based on copula function tail correlation analysis |
| CN112345678A (en) * | 2020-11-10 | 2021-02-09 | 重庆大学 | Transformer fault rate prediction model obtaining method and system and readable storage medium |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20080127714A1 (en) * | 2006-12-01 | 2008-06-05 | Josef Altmann | Quantitative Measurement of Production and Consumption of Gases in Power Transformers |
| CN104764869A (en) * | 2014-12-11 | 2015-07-08 | 国家电网公司 | Transformer gas fault diagnosis and alarm method based on multidimensional characteristics |
-
2015
- 2015-07-23 CN CN201510438809.7A patent/CN105117512B/en active Active
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20080127714A1 (en) * | 2006-12-01 | 2008-06-05 | Josef Altmann | Quantitative Measurement of Production and Consumption of Gases in Power Transformers |
| CN104764869A (en) * | 2014-12-11 | 2015-07-08 | 国家电网公司 | Transformer gas fault diagnosis and alarm method based on multidimensional characteristics |
Non-Patent Citations (2)
| Title |
|---|
| WANG XUELEI等: "Method for Caution Values Calculation of Dissolved Gases in Transformers Based on Statistical Distribution and Correlation Analysis", 《高电压技术》 * |
| 梁永亮等: "变压器油色谱在线监测周期动态调整策略研究", 《中国电机工程学报》 * |
Cited By (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106442830A (en) * | 2016-09-29 | 2017-02-22 | 广州供电局有限公司 | Method and system for detecting alarm value of gas content of transformer oil |
| CN106442830B (en) * | 2016-09-29 | 2018-04-13 | 广州供电局有限公司 | The detection method and system of gas content in transformer oil warning value |
| CN106596754A (en) * | 2016-11-22 | 2017-04-26 | 华北电力大学 | Assessment method and device for oil chromatographic sensor effectiveness |
| CN106771513A (en) * | 2016-11-22 | 2017-05-31 | 华北电力大学 | The determination method and device of arrester early warning value |
| CN106596754B (en) * | 2016-11-22 | 2019-07-23 | 华北电力大学 | The appraisal procedure and device of oil chromatography sensor availability |
| CN109187809A (en) * | 2018-10-27 | 2019-01-11 | 国网山东省电力公司电力科学研究院 | A kind of Gases Dissolved in Transformer Oil data generate in real time and analysis system |
| CN109541096A (en) * | 2018-11-09 | 2019-03-29 | 福建和盛高科技产业有限公司 | 220kV Gases Dissolved in Transformer Oil volume fraction dynamic early-warning method |
| CN110674983A (en) * | 2019-09-05 | 2020-01-10 | 辽宁工程技术大学 | Working face gas early warning method based on copula function tail correlation analysis |
| CN112345678A (en) * | 2020-11-10 | 2021-02-09 | 重庆大学 | Transformer fault rate prediction model obtaining method and system and readable storage medium |
| CN112345678B (en) * | 2020-11-10 | 2022-03-01 | 重庆大学 | Transformer fault rate prediction model obtaining method and system and readable storage medium |
Also Published As
| Publication number | Publication date |
|---|---|
| CN105117512B (en) | 2018-06-08 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN105117512A (en) | Transformer early-warning value estimation method and apparatus | |
| CN102662113B (en) | Comprehensive diagnosis method of oil-immersed transformer based on fault tree | |
| CN104764869B (en) | Transformer gas fault diagnosis and alarm method based on multidimensional characteristics | |
| CN111985561A (en) | Fault diagnosis method and system for intelligent electric meter and electronic device | |
| CN103617568B (en) | Setting method for abnormal data determination threshold in steady-state power quality early-warning mechanism | |
| Zhao et al. | Hierarchical anomaly detection and multimodal classification in large-scale photovoltaic systems | |
| CN105512474A (en) | Transformer state monitoring data anomaly detection method | |
| CN110336534A (en) | A kind of method for diagnosing faults based on photovoltaic array electric parameter time series feature extraction | |
| CN104156403B (en) | A kind of big data normal mode extracting method and system based on cluster | |
| CN111861211B (en) | System with double-layer anti-electricity-stealing model | |
| CN113011481B (en) | Electric energy meter function abnormality assessment method and system based on decision tree algorithm | |
| CN103103570B (en) | Based on the aluminium cell condition diagnostic method of pivot similarity measure | |
| CN104677997B (en) | A kind of transformer oil chromatographic on-line monitoring differentiation method for early warning | |
| CN102931728B (en) | Online identification and visualization method for power grid disturbances based on multi-resolution wavelet analysis | |
| CN101738998B (en) | System and method for monitoring industrial process based on local discriminatory analysis | |
| CN103235973A (en) | Transformer fault diagnosis method based on radial basis function neural network | |
| CN111177208A (en) | Power consumption abnormity detection method based on big data analysis | |
| CN105044497A (en) | Method for intelligently analyzing fault of traction converter | |
| CN109615273B (en) | Method and system for evaluating state of electric vehicle charging facility | |
| CN113236508B (en) | Method for detecting wind speed-power abnormal data of wind generating set | |
| CN107906375A (en) | Pipeline leakage detection method and system based on weighting arrangement entropy | |
| CN111562496A (en) | Motor running state judgment method based on data mining | |
| Sun et al. | Data augmentation strategy for power inverter fault diagnosis based on wasserstein distance and auxiliary classification generative adversarial network | |
| CN114997539A (en) | Gas pressure regulator fault prediction method and system | |
| CN103529337B (en) | The recognition methods of nonlinear correlation relation between equipment failure and electric quantity information |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |