阅读说明：本技术 不同温湿度油浸纤维素绝缘材料的频域介电响应预测方法 (Frequency domain dielectric response prediction method for oil-immersed cellulose insulating materials with different temperatures and humidities ) 是由 刘捷丰 张镱议 于 2020-11-30 设计创作，主要内容包括：本发明涉及电气设备故障诊断技术领域,具体公开的一种不同温湿度油浸纤维素绝缘材料的频域介电响应预测方法,包括以下步骤：通过幂级数理论基本表达式,得到用于表征频域介电谱的幂级数模型；获得油浸纤维素绝缘材料的FDS数据；应用幂级数模型对FDS曲线进行拟合；提取对水分含量和测试温度变化敏感的关键参数；解析水分含量、测试温度和关键参数三者之间的相关关系；计算已知水分含量和测试温度的油浸纤维素绝缘纸板的关键参数,通过幂级数表达式获取预测FDS曲线。本发明考虑水分含量和测试温度协同作用对油浸绝缘材料测试结果的影响作用,使应用于套管绝缘状态评估的FDS数据更加准确,使电力系统运行更可靠、安全、稳定。(The invention relates to the technical field of fault diagnosis of electrical equipment, and particularly discloses a frequency domain dielectric response prediction method of oil-immersed cellulose insulating materials with different temperatures and humidities, which comprises the following steps: obtaining a power series model for representing the frequency domain dielectric spectrum through a basic expression of a power series theory; obtaining FDS data of the oil-immersed cellulose insulating material; fitting the FDS curve by applying a power series model; extracting key parameters sensitive to moisture content and test temperature variation; analyzing the correlation among the moisture content, the test temperature and the key parameters; calculating key parameters of the oil-immersed cellulose insulating paperboard with known moisture content and test temperature, and obtaining a predicted FDS curve through a power series expression. According to the invention, the influence of the synergistic effect of the moisture content and the test temperature on the test result of the oil-immersed insulating material is considered, so that FDS data applied to the insulation state evaluation of the bushing is more accurate, and the power system is more reliable, safer and more stable in operation.)

1. A frequency domain dielectric response prediction method for oil-immersed cellulose insulation materials with different temperatures and humidities is characterized by comprising the following steps of: the method comprises the following steps:

s1, obtaining a plurality of oil-immersed cellulose insulation paper boards with different water contents;

s2, acquiring the actual FDS curves of the oil-immersed cellulose insulation paperboards at different test temperatures;

s3, establishing a power series expression of an actual FDS curve of the oil-immersed cellulose insulation paperboard;

s4, fitting the FDS curves with different water contents and different test temperatures by adopting a power series expression;

s5, extracting key parameters sensitive to moisture content and test temperature change based on the fitting result of each actual FDS curve;

s6, acquiring the variation relation among the moisture content, the test temperature and the key parameters;

and S7, calculating key parameters of the oil-immersed cellulose insulation paperboard with known moisture content and test temperature based on the change relationship, and acquiring a predicted FDS curve through the power series expression.

2. The method for predicting the frequency domain dielectric response of the oil-immersed cellulose insulating material at different temperatures and humidities according to claim 1, wherein the method comprises the following steps: step S1 specifically includes: vacuum drying insulating oil and oil-immersed cellulose insulating paper boards for 24 hours at the temperature of 105 ℃ and under the pressure of 50Pa, putting the dried oil and oil-immersed cellulose insulating paper boards together, and immersing the oil and oil-immersed cellulose insulating paper boards for 48 hours at the temperature of 60 ℃ and under the pressure of 50 Pa; placing the fully-oiled oil-immersed cellulose insulation paperboard sample under a natural condition for moisture absorption, and weighing the weight of the oil-immersed cellulose insulation paperboard sample by a precision balance so as to control the moisture absorption degree of different oil-immersed cellulose insulation paperboard samples, so as to obtain oil-immersed cellulose insulation paperboard samples with different moisture contents.

3. The method for predicting the frequency domain dielectric response of the oil-immersed cellulose insulating material at different temperatures and humidities according to claim 1, wherein the method comprises the following steps: in step S2, the oil-impregnated cellulose insulation boards are respectively placed in a thermostat capable of adjusting temperature, and then an actual FDS curve of each oil-impregnated cellulose insulation board is obtained by using a dielectric tester.

4. The method for predicting the frequency domain dielectric response of the oil-immersed cellulose insulating material at different temperatures and humidities according to claim 1, wherein the method comprises the following steps: the power series expression of the FDS curve applied to each oil-impregnated cellulose insulation paperboard in step S3 is as follows:

wherein n is the order of the power series, phi₀Is the intercept of a power series, phi_n' is the coefficient of each term, omega is the angular frequency, omega₀Is the initial frequency;

considering the coefficients of each term as variables related to moisture content and test temperature, equation (1) above can be further modified to, with an initial angular frequency of infinitesimal magnitude:

wherein T is the testing temperature, mc% is the moisture content of the tested sample, and f is the frequency corresponding to the angular frequency.

5. The method for predicting the frequency domain dielectric response of the oil-immersed cellulose insulating material with different temperatures and humidities according to claim 4, wherein the method comprises the following steps: the extraction of the key parameters sensitive to the moisture content and the test temperature variation in step S5 refers to the coefficients of the individual sub-terms of the power series.

6. The method for predicting the frequency domain dielectric response of the oil-immersed cellulose insulating material at different temperatures and humidities according to claim 1, wherein the method comprises the following steps: and in the step S6, the variation relation among the moisture content, the test temperature and the key parameters is obtained by fitting through a surface fitting technology.

Technical Field

The invention relates to the technical field of fault diagnosis of electrical equipment, in particular to a frequency domain dielectric response prediction method for oil-immersed cellulose insulating materials with different temperatures and humidities.

Background

The normal operation of the electric power casing pipe is an important prerequisite for ensuring the safe and reliable operation of power transmission and transformation. The deterioration of the cellulose insulation of the bushing due to thermal stresses etc. which the bushing is subjected to during operation is an irreversible process, and the degree of deterioration of the cellulose insulation of the bushing determines the service life of the bushing.

Since the casing is subjected to maintenance operations such as oil change and oil filtration during service, the accuracy of conventional insulation state diagnostic methods such as Dissolved Gas Analysis (DGA) and the like is seriously affected, and therefore, a method for performing state evaluation using byproducts in the solid insulation degradation process needs to be further explored. Compared with a chemical method, the frequency domain dielectric response (FDS) based on dielectric physics is widely concerned by relevant scholars due to the advantages of nondestructive detection, strong anti-interference capability, small influence of operations such as oil change and the like. The learners generally think that the test temperature can affect the FDS test curve, thereby affecting the accuracy of state evaluation, so that the research on the temperature correction method of the FDS curve plays an important role in improving the evaluation accuracy of the insulation state based on the frequency domain dielectric response.

The main curve technology is the most common temperature correction method in the dielectric field, and by researching the correlation among translation factors at different test temperatures extracted by the main curve technology, the FDS curve at the test temperature can be converted to a reference temperature, so that the influence of the temperature on the test result is eliminated. However, the prior temperature correction methods neglect the synergistic effect of moisture and temperature on the translation factor, resulting in significant errors in temperature correcting the FDS curves of cellulosic insulation materials of different moisture content. Therefore, there is a need to further improve the existing temperature correction methods or to propose new methods.

Disclosure of Invention

The invention aims to provide a frequency domain dielectric response prediction method for oil-immersed cellulose insulation materials with different temperatures and humidities, so that the defect that the conventional temperature correction method neglects the synergistic effect of moisture and temperature on a translation factor, so that obvious errors are generated when the temperature of FDS curves of the cellulose insulation materials with different moisture contents is corrected is overcome.

In order to achieve the purpose, the invention provides a frequency domain dielectric response prediction method of oil-immersed cellulose insulation materials with different temperatures and humidities, which comprises the following steps:

s1, obtaining a plurality of oil-immersed cellulose insulation paper boards with different water contents;

s2, acquiring the actual FDS curves of the oil-immersed cellulose insulation paperboards at different test temperatures;

s3, establishing a power series expression of an actual FDS curve of the oil-immersed cellulose insulation paperboard;

s4, fitting the FDS curves with different water contents and different test temperatures by adopting a power series expression;

s5, extracting key parameters sensitive to moisture content and test temperature change based on the fitting result of each actual FDS curve;

s6, acquiring the variation relation among the moisture content, the test temperature and the key parameters;

and S7, calculating key parameters of the oil-immersed cellulose insulation paperboard with known moisture content and test temperature based on the change relationship, and acquiring a predicted FDS curve through the power series expression.

Preferably, in the above technical solution, step S1 specifically includes: vacuum drying insulating oil and oil-immersed cellulose insulating paper boards for 24 hours at the temperature of 105 ℃ and under the pressure of 50Pa, putting the dried oil and oil-immersed cellulose insulating paper boards together, and immersing the oil and oil-immersed cellulose insulating paper boards for 48 hours at the temperature of 60 ℃ and under the pressure of 50 Pa; placing the fully-oiled oil-immersed cellulose insulation paperboard sample under a natural condition for moisture absorption, and weighing the weight of the oil-immersed cellulose insulation paperboard sample by a precision balance so as to control the moisture absorption degree of different oil-immersed cellulose insulation paperboard samples, so as to obtain oil-immersed cellulose insulation paperboard samples with different moisture contents.

Preferably, in the above technical solution, in step S2, each oil-impregnated cellulose insulation board is respectively placed in a thermostat capable of adjusting temperature, and then an actual FDS curve of each oil-impregnated cellulose insulation board is obtained by using a dielectric tester.

Preferably, in the above technical solution, the power series expression of the FDS curve applied to each oil-impregnated cellulose insulating paper board in step S3 is as follows:

wherein n is the order of the power series, phi₀Is the intercept of a power series, phi_n' is the coefficient of each term, omega is the angular frequency, omega₀Is the initial frequency;

considering the coefficients of each term as variables related to moisture content and test temperature, equation (1) above can be further modified to, with an initial angular frequency of infinitesimal magnitude:

wherein T is the testing temperature, mc% is the moisture content of the tested sample, and f is the frequency corresponding to the angular frequency.

Preferably, in the above technical solution, the key parameter extracted in step S5, which is sensitive to moisture content and temperature variation during testing, refers to a coefficient of each sub-term of the power series.

Preferably, in the above technical solution, the variation relationship among the moisture content, the test temperature, and the key parameter in step S6 is obtained by fitting through a surface fitting technique.

Compared with the prior art, the invention has the beneficial effects that:

according to the method, by introducing a power series theory, a frequency domain dielectric response prediction method of the oil-immersed cellulose insulating material under the influence of the test temperature and the moisture content is provided, FDS curves under different moisture contents and test temperatures can be calculated, the influence of the test temperature on an FDS test result is eliminated, the synergistic effect of the moisture and the temperature on the FDS test result is comprehensively considered, the correction result is more accurate, the accuracy and the universality of the casing pipe state diagnosis method based on the frequency domain dielectric spectrum technology are improved, an important reference basis is provided for the state overhaul and the operation maintenance of the casing pipe, and finally the operation safety and the stability of a power grid are improved.

Drawings

In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.

Fig. 1 is a flowchart of a frequency domain dielectric response prediction method for an oil-impregnated cellulose insulating material according to an embodiment of the present invention.

Fig. 2 is a diagram of implementation steps of a frequency domain dielectric response prediction method for an oil-impregnated cellulose insulating material according to an embodiment of the present invention.

Fig. 3a and 3b are graphs of partial power series fitting results according to embodiments of the present invention.

Fig. 4a and 4b are graphs comparing predicted FDS curves and tested FDS curves for a portion of samples according to an embodiment of the present invention.

In fig. 3 a-4 b, the order of the Measured values and the modulated curve is opposite to the order of the curve display, that is, the first Measured value and the modulated curve are expressed as the bottom curve.

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.

Frequency Domain Spectroscopy (FDS) is a novel insulation detection method, and the method comprises the following steps: applying a variable-frequency alternating voltage signal on the insulating material, testing the complex capacitance of the insulating material, comparing the change rules of the dielectric constant and the dielectric loss factor along with the change of the frequency, and evaluating the insulating condition of the insulating material by analyzing the change rules of the complex capacitance, the complex relative dielectric constant and the dielectric loss factor.

The FDS measurement of the insulation state of the oil immersed bushing is to expand the conventional power frequency dielectric loss and capacitance measurement of the method to low-frequency and high-frequency bands, such as 0.01mHz to 5kHz, so that the polarization and loss conditions in a wider frequency domain range can be reflected. The frequency domain parameters are closely related to the water content and the aging degree of the solid insulation of the sleeve, and the aging state of the solid insulation of the sleeve can be judged by researching the relationship between the frequency domain parameters and the aging state of the solid insulation.

In this embodiment, a frequency domain dielectric response prediction method based on oil-immersed cellulose insulating materials with different temperatures and humidities is specifically included, as shown in fig. 1 and 2, in the following steps:

and step S1, obtaining a plurality of oil-immersed cellulose insulation paper boards with different water contents.

Specifically, a plurality of groups of oil-immersed insulating paperboard samples with different moisture contents are prepared in a laboratory, and the sample preparation process comprises the following steps: firstly, carrying out vacuum drying on insulating oil and insulating paper boards for a test for 24 hours at 105 ℃ under the environment of 50 Pa; putting the dried oil and the insulating paper board together, and soaking the oil for 48 hours at the temperature of 60 ℃ and under the environment of 50 Pa; and placing the fully-oiled insulating paperboard sample under a natural condition for moisture absorption, weighing the sample weight through a precision balance, and controlling the moisture absorption degree of different paperboards to finally obtain the oil-immersed insulating paperboard sample with different moisture contents.

And step S2, acquiring the actual FDS curve of each oil-immersed cellulose insulation paperboard at different test temperatures.

Specifically, the oil-immersed insulating paperboard sample prepared in the step S1 is placed in a thermostat with adjustable temperature, an FDS curve of the oil-immersed insulating paperboard sample is tested by a dielectric tester, and test results at different test temperatures are realized by adjusting the temperature of the thermostat.

And step S3, establishing a power series expression of the actual FDS curve of the oil-immersed cellulose insulation paperboard.

And introducing a power series theory, and theoretically exploring the feasibility of applying a power series model to represent the frequency domain dielectric response test result of the oil-immersed insulating material. And (3) combining the power series theory, and expressing the comprehensive dielectric response of the insulating paperboard in a superposition form of n branched dielectric responses, wherein the test result expression of the FDS is as follows:

wherein n is the order of the power series, phi₀Is the intercept of a power series, phi_n' is the coefficient of each term, omega is the angular frequency, omega₀Is the initial frequency.

Since the DFS test result is affected by temperature and the degree of the temperature effect is directly related to the moisture content of the sample to be tested, the coefficients of the above expressions are defined as variables affected by the temperature and moisture content to be tested, and when the initial angular frequency is close to 0, the above expression can be further expressed as:

wherein T is the testing temperature, mc% is the moisture content of the tested sample, and f is the frequency corresponding to the angular frequency.

And S4, fitting the FDS curves with different water contents and different test temperatures by adopting a power series expression.

Specifically, the power series described in step S3 is used to fit the FDS curve obtained by testing under different moisture content and test temperature conditions. The higher the order of the fitting equation is, the closer the obtained fitting curve is to the test curve, however, the pursuit of too high fitting accuracy may cause overfitting of the model, and by taking the above situations into consideration, the present example fits the FDS curve by using a power series of order 3, and part of the fitting results are shown in fig. 3a and 3 b.

And step S5, extracting key parameters sensitive to moisture content and test temperature change based on the fitting result of each actual FDS curve.

Wherein key parameters sensitive to moisture content and test temperature variations are extracted based on model fitting results. And (5) taking coefficients of the fitted power series under different moisture contents and test temperatures in the step S4 as key parameters, and researching the correlation among the key parameters, the moisture contents and the test temperatures.

Step S6, with the water content and the test temperature as independent variables, phi_nAs a dependent variable, the moisture content, test temperature and phi were described based on a depth fitting technique_nThe variation relationship among the three. The partial fit results are shown below:

Φ₀＝Z₀+Z₁·T+Z₂·mc％+Z₃·T²+Z₄·mc％²

and step S7, calculating key parameters of the oil-immersed cellulose insulation paperboard with known moisture content and test temperature based on the change relationship, and acquiring a predicted FDS curve through the power series expression.

To verify the feasibility of the above model, FDS curves with known moisture content and test temperature were prepared and tested within the experiments. Substituting the moisture content and the test temperature into the fitting equation shown in step S6 to calculate each coefficient of the power series, thereby calculating a corresponding predicted FDS curve, and comparing the partial predicted curve with the calculated curve to obtain the results shown in fig. 4a and 4 b.

Step S8, the relative error is used to carry out error analysis on the prediction curve and the test curve, and the expression of the relative error is as follows:

in the formula, tan delta_m(f_i) For test results, tan. delta_p(f_i) Is a prediction result.

The error analysis result shows that the relative error between the test result and the prediction result is within an acceptable range, and the feasibility and the universality of the proposed frequency domain dielectric response prediction method based on the oil-immersed cellulose insulating materials with different temperatures and humidities are shown.

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.