CN112668145A - FDS and exponential decay model-based transformer oiled paper insulation moisture assessment method - Google Patents
FDS and exponential decay model-based transformer oiled paper insulation moisture assessment method Download PDFInfo
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Abstract
The invention relates to the technical field of electrical equipment fault diagnosis, and discloses a transformer oil paper insulation moisture assessment method based on an FDS (fully drawn sheet) and an exponential decay model. The method of the invention comprises the following steps: preparing samples with different water contents; FDS test is carried out to obtain a real part curve of the complex dielectric constant; fitting the curve obtained by the test by using a parameter-containing exponential decay function; establishing a quantitative relation between the fitting parameters and the water content; obtaining an exponential decay model; constructing an FDS simulation curve library; and (4) evaluating the moisture of the sample by using a proximity criterion. The invention realizes the prediction of the FDS curve under different moisture and different frequencies, and the constructed database ensures that the moisture diagnosis is more convenient and accurate, so that the power system operates more reliably, safely and stably.
Description
Technical Field
The invention relates to the technical field of electrical equipment fault diagnosis, in particular to a transformer oil paper insulation moisture assessment method based on an FDS (fully drawn SoftS) and exponential decay model.
Background
The oil paper insulation system is used as a main component of a high-voltage insulation system of the oil-immersed power transformer, and the good insulation performance of the oil paper insulation system is the basis for effective operation of the transformer and even the whole power system. It is known that the deterioration of the insulating oil can be solved by replacing the oil or filtering the oil, but no effective measure has been proposed at present for the deterioration of the insulating paper. Therefore, the service life of the transformer is mainly influenced by the insulation state of the oil-paper insulation. Excessive moisture in the insulation system can severely affect the insulation performance and have a number of consequences including accelerated aging rates, shortened insulation life, and reduced partial discharge initiation voltages. Therefore, the accurate assessment of the moisture content of the transformer oil paper insulation has important significance on the stability and the safety of the operation of a power grid system.
Traditionally, the moisture of a paper sample is directly measured by adopting a Karl Fischer titration method (KFT), so that a transformer needs to be hung and covered for sampling, the insulation structure of the transformer is damaged, and the method is considered to be unrealistic in engineering. In contrast, the cellulose-water adsorption isotherm can be used to obtain internal moisture without destroying the cellulose insulation, but its uncertainty can be as high as 200% considering various factors such as temperature, equilibration time, etc. In recent years, the development of dielectric response technology has been driven by the need for non-destructive and reliable evaluation of transformer paper-oil insulation systems. The FDS technology is considered as a powerful tool for researching the water content of the oiled paper insulation system because the FDS technology has strong anti-interference capability, the curve carries abundant insulation information and the temperature influence is easily eliminated.
In the past, methods for evaluating the insulation moisture content of the oiled paper by means of the FDS technology are available, and most of these methods depend on a limited number of samples, so that the evaluation accuracy is not high and the versatility is not strong. Therefore, a unified model is needed to be adopted to simulate FDS data, and the small sample data is expanded to a multi-curve database, so that FDS data comparison of unknown samples is realized, and the database is used for judging the moisture state of transformer oil paper insulation.
Disclosure of Invention
The invention aims to provide a transformer oil paper insulation moisture assessment method based on an FDS (fully drawn SoftS) and exponential decay model, so that the defect that the existing method for assessing the oil paper insulation moisture content by means of an FDS technology is low in assessment precision is overcome.
In order to achieve the purpose, the invention provides a transformer oiled paper insulation moisture assessment method based on an FDS and an exponential decay model, which comprises the following steps:
s1, obtaining a plurality of oil-immersed insulating paper boards with different moisture contents;
s2, respectively carrying out FDS (fully drawn wires) tests on the oil-immersed insulating paperboards to obtain real part curves of complex dielectric constants, and respectively carrying out moisture detection to obtain moisture content;
s3, fitting the real part curve of the complex dielectric constant through a parameter-containing exponential decay function to obtain a fitting curve and a fitting parameter corresponding to each oil-immersed insulating paperboard;
s4, point-tracing fitting is carried out on the fitting parameters and the water content serving as independent variables respectively to obtain a relation graph and a fitting equation between each fitting parameter and the water content;
s5, substituting the obtained fitting equations into a reference-containing exponential decay function to obtain an exponential decay model;
s6, predicting a complex dielectric constant real part curve under any water content by using the exponential decay model to construct an FDS simulation curve library;
and S7, substituting the measured complex dielectric constant real part curve of the oil-immersed insulation paper board to be identified into the FDS simulation curve library for comparison, and accordingly evaluating the water content of the oil-immersed insulation paper board.
Preferably, in the above technical solution, the parameter-containing exponential decay function in step S3 is:
in the formula (1), ∈' (ω) is a real part of the complex permittivity, n is a natural number, n is 0,1 … ∞, and represents the order of the function; ω 2 pi f, is the angular frequency; Ψ0An intercept of an exponential function; ΨiIs the coefficient of each sub-function, μiIs the attenuation coefficient, Ψ, of each subfunctioni、μiFor fitting parameters, the initial frequency ω is measured due to FDS0→ 0, and therefore, the expression for fitting an ε' (ω) curveThe formula is as follows:
preferably, in the above technical solution, the fitting equation in step S4 refers to establishing a fitting parameter (Ψ)i、μi) The quantitative relationship with the water content (mc%) is as follows:
wherein mc% is water content.
Preferably, in the above technical solution, the exponential decay model in step S5 is specifically:
the equation (4) is adjusted, namely logarithms of variables on two sides of the equation are obtained, namely, the mathematical expression of the exponential decay model is as follows:
preferably, in the above technical solution, the FDS simulation curve library in step S6 is formed by combining curves of real complex dielectric constants with a certain gradient water content predicted by an exponential decay model.
The invention has the beneficial effects that:
according to the method, the FDS curve is simulated by introducing the exponential decay model, so that the defects of the conventional moisture evaluation method based on the frequency domain dielectric response technology are overcome, limited sample data is simulated by a uniform model, the value of the model parameter is expanded through the quantitative relation between the model parameter and moisture, the purpose of predicting the FDS curve is achieved, and a multi-FDS curve library which can be used for oil paper insulation moisture evaluation is constructed. Therefore, the method has the advantages that moisture diagnosis based on the FDS technology is lossless, convenient and accurate, potential risks of the transformer oil-paper insulation system can be found, maintenance can be reasonably arranged according to the damp condition of equipment, the utilization rate of the equipment is optimized, the reliability, the safety and the stability of operation of a power system are further guaranteed, and the transformer can be maintained and repaired more conveniently.
Drawings
In order to more clearly illustrate the embodiments and technical solutions of the present invention, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained based on these drawings without inventive effort.
Fig. 1 is a flow chart of a test for preparing oil-impregnated paper boards with different water contents and for testing FDS according to an embodiment of the present invention.
FIG. 2 is a detailed diagram of an FDS testing apparatus according to an embodiment of the present invention.
FIG. 3 is a graph of a comparison of discrete values of measured ε' (ω) and fitted curves of an embodiment of the present invention, where the first measured value and the corresponding lowermost curve of the first fitted curve, and so on.
FIGS. 4 a-4 g are graphs of calculated fit parameters versus moisture for embodiments of the present invention.
FIG. 5 illustrates a library of FDS simulation curves constructed in accordance with an embodiment of the present invention.
FIG. 6 is a flow chart of a method for moisture assessment according to an embodiment of the present invention.
FIGS. 7 a-7 c are graphs of the results of the proximity calculations of the embodiment of the present invention.
Detailed Description
The preferred embodiments of the present invention will be described in detail below with reference to the accompanying drawings so that the advantages and features of the present invention can be more easily understood by those skilled in the art, and the scope of the present invention will be more clearly and clearly defined.
The embodiment discloses a moisture evaluation method of transformer oiled paper insulation based on FDS and exponential decay model, as shown in FIG. 6, comprising the following steps:
and step S1, carrying out pretreatment and moisture absorption tests on the insulating oil and the insulating paper to obtain a group of oil-immersed insulating paper boards with different water contents.
The method comprises the following specific operations: the insulating paper board is first processed into disc and then set homogeneously on the drying rack to maintain enough interval between the paper boards. And the aged steel is canned with a certain amount of insulating oil (sampling reference ratio of insulating oil to insulating paper: 20/1). Placing a drying rack with insulating paper and an aging steel tank filled with insulating oil into a vacuum oil immersion tank, firstly setting vacuum drying time at 105 ℃/50Pa for 48h, immersing the drying rack into the insulating oil after drying, setting vacuum oil immersion for 48h under the condition of 60 ℃/50Pa again, and obtaining the oil-immersed insulating paperboard with small water content after pretreatment. The oil immersion cardboard that is different water content for obtaining needs carry out the moisture absorption test, is about to wipe the surface oil of post pretreatment cardboard clean, places the moisture absorption on precision electronic balance, for accelerating moisture absorption speed, can add and establish the humidifier and improve air humidity, represents when the average number shows m on the day and reaches expectation moisture degree, concrete computational formula:
m＝m0×(1-a％)/(1-b％) (1)
wherein m is the weight of the board at the desired moisture, m0For the weight of the pretreated board, a% is the initial moisture content and b% is the expected moisture content.
A set of oil-impregnated insulating boards with different moisture contents was thus obtained for use in this example.
And step S2, respectively carrying out FDS tests on the plurality of oil-immersed insulating paper boards to obtain real parts epsilon' (omega) of complex dielectric constants, and respectively carrying out moisture detection to obtain moisture content.
Specifically, in a laboratory, the oil-immersed insulating paper board obtained in step S1 is subjected to FDS test in sequence by using a three-electrode test system to obtain a real complex dielectric constant part ∈' (ω) curve. As shown in FIG. 2, the detail view of the FDS testing device with three-electrode testing unit is shown, wherein the left side of the drawing is the real object testing chart, the middle part is the section view of the real object testing chart, and in the section view, 1 is the constant temperature box, 2 is the high voltage electrode, 3 is the oiled paper insulation sample, 4 is the protective electrode, 5 is the measuring electrode, 6 is the measuring electrodeAnd the support 7 is transformer oil and has a structure shown in the figure. Setting the measurement voltage at AC 200V-300V and the test frequency at 1X 10-4-1×104Hz. To ensure the accuracy of the measurement, two points are needed: first, the oil-impregnated insulating paper sheet should be left standing at the measurement temperature for a certain period of time before measurement (advice)>48h) So as to ensure that the paperboard and the outside reach moisture balance; secondly, any measurement has certain error, and in order to improve the accuracy of the measurement result, each paperboard needs to be measured for many times, and the average value is taken as the measurement result.
After the FDS test is finished, the moisture test is carried out on the sample immediately to ensure that the measured curves correspond to the measured moisture values one by one. The moisture test of this example was carried out in accordance with IEC60814 using a Karl Fischer moisture tester.
FIG. 1 is a flowchart of the experiment of this example, showing step S1 and step S2.
Step S3, fitting the complex dielectric constant real part epsilon' (omega) curve through a parameter-containing exponential decay function to obtain a fitting curve and a fitting parameter (psi) corresponding to each oil-immersed insulating paperboardi、μi)。
A general mathematical expression for a multi-step parametric-containing exponential decay function is known:
in the formula, n is a natural number, 0,1 … infinity, and represents a function order; ω 2 pi f, is the angular frequency; Ψ0An intercept of an exponential function; ΨiIs the coefficient of each sub-function, μiIs the attenuation coefficient of each sub-function. Since the initial frequency can be set very small, i.e. ω, for FDS measurements0→ 0. Again, considering the data of this example, the required goodness of fit has been achieved with n-3. Thus, the epsilon' (ω) curve can be fitted using the following equation:
after the fitting process, a comparison graph of the discrete values of the measured ε' (ω) and the fitted curve as shown in FIG. 3 is obtained, and 7 fitting parameters (Ψ) can also be obtainedi、μi)；
Step S4, fitting the parameters (Ψ)i、μi) And respectively carrying out point-drawing fitting with the water content (mc%) as an independent variable to obtain a relation graph and a fitting equation between each fitting parameter and the water content.
Specifically, to find the relationship between the 7 fitting parameters obtained in step S3 and the water content of the sample, a rectangular coordinate system needs to be established respectively for point tracing analysis, as shown in fig. 4a to 4g, which are fitting parameters (Ψ)i、μi) A graph of relationship to moisture, which establishes Ψi、μiQuantitative relationship between (i ═ 1,2,3) and mc%, as:
step S5, step S4 Ψi、μiSubstituting the quantitative relation with mc% into the exponential decay function containing reference to obtain the mathematical expression of the exponential decay model:
in order to facilitate the exponential decay model to simulate an epsilon' (omega) curve drawn in a logarithmic coordinate system, the above formula needs to be adjusted, namely, the logarithm is measured according to variables on two sides of an equation, and the mathematical expression of the formula is as follows:
and step S6, predicting a complex dielectric constant real part epsilon' (omega) curve under any water content by using the exponential decay model so as to construct an FDS simulation curve library.
Specifically, the exponential decay model obtained in step S5 may predict an ∈' (ω) curve under any water content, and in consideration of the actual possible moisture condition of the transformer, the water content is set to range from 0.5% to 6%. As long as the accuracy of the water content is small enough, the predicted curves are closely connected to form a smooth curved surface, as shown in fig. 5, which is considered as an FDS simulation curve library composed of predicted simulation epsilon' (ω) curves.
And step S7, substituting the measured epsilon' (omega) curve of the sample to be identified into the FDS simulation curve library for comparison, and thus evaluating the water content of the oil-immersed insulating paperboard.
Specifically, an epsilon '(omega) curve of the sample to be identified is tested (the specific operation is the same as the FDS test in the step S2), the epsilon' (omega) curve is substituted into the FDS simulation curve library constructed in the step S6, and the evaluation result of the sample to be identified is obtained by using the euclidean closeness criterion. The calculation formula of the Euclidean closeness criterion is as follows:
in the formula (f)iRepresenting frequency test points, wherein n represents the number of the frequency test points; A. b represents an epsilon '(omega) curve of the sample to be identified and an epsilon' (omega) curve in an FDS simulation curve library respectively; a larger value of N (A, B) indicates that two lines are closer together.
And selecting the maximum closeness according to a 'closeness selection principle', namely the water state of the sample to be identified. As shown in fig. 7 a-7 c, which are graphs of the results of euclidean closeness calculations, it can be seen that the maximum closeness is all above 0.88, which indicates that the recognition effect is better and the evaluation method is feasible.
Although the embodiments of the present invention have been described with reference to the accompanying drawings, various changes or modifications may be made by the patentees within the scope of the appended claims, and within the scope of the invention, as long as they do not exceed the scope of the invention described in the claims.
Claims (5)
1. A transformer oiled paper insulation moisture assessment method based on FDS and exponential decay model is characterized in that: the method comprises the following steps:
s1, obtaining a plurality of oil-immersed insulating paper boards with different moisture contents;
s2, respectively carrying out FDS (fully drawn wires) tests on the oil-immersed insulating paperboards to obtain real part curves of complex dielectric constants, and respectively carrying out moisture detection to obtain moisture content;
s3, fitting the real part curve of the complex dielectric constant through a parameter-containing exponential decay function to obtain a fitting curve and a fitting parameter corresponding to each oil-immersed insulating paperboard;
s4, point-tracing fitting is carried out on the fitting parameters and the water content serving as independent variables respectively to obtain a relation graph and a fitting equation between each fitting parameter and the water content;
s5, substituting the obtained fitting equations into a reference-containing exponential decay function to obtain an exponential decay model;
s6, predicting a complex dielectric constant real part curve under any water content by using the exponential decay model to construct an FDS simulation curve library;
and S7, substituting the measured complex dielectric constant real part curve of the oil-immersed insulation paper board to be identified into the FDS simulation curve library for comparison, and accordingly evaluating the water content of the oil-immersed insulation paper board.
2. The FDS and exponential decay model-based transformer paper oil insulation moisture assessment method according to claim 1, wherein: the parameter-containing exponential decay function in step S3 is:
in the formula (1), ∈' (ω) is a real part of the complex permittivity, n is a natural number, n is 0,1 … ∞, and represents the order of the function; ω 2 pi f, is the angular frequency; Ψ0An intercept of an exponential function; ΨiIs the coefficient of each sub-function, μiIs the attenuation coefficient, Ψ, of each subfunctioni、μiFor fitting parameters, the initial frequency ω is measured due to FDS0→ 0, therefore, forThe expression for fitting the real complex permittivity ∈' (ω) curve should be:
3. the FDS and exponential decay model-based transformer paper oil insulation moisture assessment method according to claim 1, wherein: the fitting equation in step S4 is to establish a quantitative relationship between the fitting parameters and the water content, and specifically includes:
wherein mc% is water content.
4. The FDS and exponential decay model-based transformer paper oil insulation moisture assessment method according to claim 1, wherein: the exponential decay model in step S5 is specifically:
the equation (4) is adjusted, namely logarithms of variables on two sides of the equation are obtained, namely, the mathematical expression of the exponential decay model is as follows:
5. the FDS and exponential decay model-based transformer paper oil insulation moisture assessment method according to claim 1, wherein: the FDS simulation curve library in step S6 is formed by combining curves of real complex dielectric constants with a certain gradient water content predicted by an exponential decay model.
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