CN114543896A - Capacitive equipment medium water content and aging evaluation method based on temperature drift electrical parameters - Google Patents
Capacitive equipment medium water content and aging evaluation method based on temperature drift electrical parameters Download PDFInfo
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Abstract
S1, collecting the medium electrical parameter of the tested equipment, the internal temperature of the tested equipment and the corresponding environmental temperature and humidity parameter within a certain time or under the condition of temperature/humidity rising and falling; s2, calculating the variable quantity of the medium parameters in the process of rising and falling under the temperature and/or the environmental humidity according to the acquired information; and S3, evaluating the water content and the aging degree of the tested equipment. The invention solves the prediction problem that the internal moisture or medium is migrated to change the insulation strength and cause the fault due to the temperature rise and fall in the operation process of the power equipment; the device insulation medium moisture and aging state can be evaluated under the running condition and the power failure state along with the fluctuation of the electrical parameters, the temperature and/or the humidity.
Description
Technical Field
The invention relates to water content testing and aging evaluation, in particular to a method for evaluating the water content and aging of a capacitive equipment medium based on temperature drift electrical parameters.
Background
Insulation indexes of electric and electronic equipment such as a transformer, a capacitor, a sleeve, a cable and the like are very key parameters for measuring the reliability of the equipment; the existing conventional medium parameter measuring equipment such as a capacitance instrument and a medium loss instrument cannot accurately and effectively diagnose the moisture content in the equipment, particularly under the condition of complex internal structure of the equipment, such as a multilayer wrapped oil paper insulating capacitor, an oil paper insulating transformer, an oil paper insulating sleeve, an oil insulating cable, a dry cross-linked insulating XLPE cable and the like. After the interior of the equipment is generally affected with damp, moisture preferentially exists in the solid insulating layer such as the interior of a paperboard, when water in paper is analyzed under the operation condition, the separated water can return to the paperboard after the equipment is powered off or cooled, and the actual insulating condition cannot be reflected in the conventional test.
Although the existing test method adopts a low-frequency polarization or low-frequency sweep test or a long-time polarization depolarization scheme, the test method is long in time and needs various algorithms to compensate temperature change, only data of a certain temperature point is actually measured, the migration characteristic of water cannot be sensitively reflected, the test efficiency is low (tens of minutes to several hours), and damage can be caused to equipment, for example, a high-voltage electric field can electrolyze water to generate a new reinforcement and the like.
Disclosure of Invention
The invention aims to overcome the defects of the prior art, provides a capacitive equipment medium water content and aging evaluation method based on temperature drift electrical parameters, and solves the problem of predicting faults caused by the change of an insulation strength method caused by the movement of internal moisture or medium in the operation process of power equipment; the device insulation medium moisture and aging state can be evaluated under the running condition and the power failure state.
The purpose of the invention is realized by the following technical scheme: the capacitive equipment medium water content and aging evaluation method based on the temperature drift electrical parameters comprises the following steps:
s1, collecting medium electric parameters of a tested device, the internal temperature of the tested device and corresponding environment temperature and humidity parameters within a certain time or under a temperature/humidity lifting condition;
s2, calculating the variation of the medium parameters in the process of rising and falling by temperature and/or environmental humidity according to the acquired information;
and S3, evaluating the water content and the aging degree of the tested equipment.
In step S1, the parameter acquisition includes a live acquisition mode and a power failure acquisition mode.
The acquisition process of the charged acquisition mode comprises the following steps:
monitoring the dielectric electrical parameter Dx of the equipment To be measured, and synchronously measuring the internal temperature Ti value, the ambient temperature To and the humidity Ro value of the equipment; the dielectric electrical parameter comprises at least one of capacitance, power factor, dielectric loss, power loss, insulation impedance, time domain reflection coefficient, frequency domain reflection coefficient and broadband impedance;
recording a medium electrical parameter Dx under the condition of a plurality of Ti, T0 and Ro under the running condition of the tested equipment, and drawing at least one of Dx-Ti, Dx-To and Dx-Ro curves; the recorded time is not less than 120S.
The collection process of the power failure collection mode comprises the following steps:
a1, heating the tested device; the heating mode is at least one of the following modes:
firstly, placing the tested equipment into a temperature control box body or winding and wrapping the tested equipment with temperature control heating equipment;
secondly, applying a voltage or a current source to the tested device to enable the inside to generate current and heat;
a2, monitoring dielectric electrical parameters Dx of the equipment To be tested, and synchronously measuring the internal temperature Ti value, the environmental temperature To and the humidity Ro value of the equipment; the dielectric parameter Dx is any one of capacitance, power factor, dielectric loss, power loss, time domain reflection coefficient, frequency domain reflection coefficient, broadband impedance or insulation impedance;
a3, stopping heating the tested equipment, cooling the tested equipment, and repeatedly executing the operation of the step A2 at fixed time intervals of not less than 10S;
a4, recording medium electrical parameters Dx under the conditions of multiple Ti, T0 and Ro in the temperature rising and lowering process of the tested equipment, and drawing at least one of Dx-Ti, Dx-To and Dx-Ro curves; the recorded time is not less than 120S.
Further, the step S2 includes:
in the up-and-down fluctuation process of the temperature of the tested equipment, the electric parameter values corresponding to the equivalent temperature values at different times are recorded, the difference of the electric parameter values is calculated, and analysis is carried out, specifically:
calculating the maximum value Dxmax and the minimum value Dxmin of Dx under the same corresponding temperature index Ti in the process of temperature fluctuation; calculating the variable quantity of the medium parameters: θ ═ (× ax-Dxmin)/(ζ w- ζ 0); zeta w is the water dielectric constant at Ti temperature, and zeta 0 is the standard value or reference value of the insulation layer of the tested device;
ζw＝-0.3997×t+0.00094×t2+87.74, t is the temperature value; the reference value of ζ 0 is 3.6 when the device is an oil-paper insulated transformer or an oil-paper insulated capacitor, and the reference value of ζ 0 is 2.7 when the device is a crosslinked cable.
In step S3, the calculated water content is a volume water content, and the calculation method is as follows:
alpha is 0.600-1.500, and a typical value alpha is 0.899.
Further, in the step S3, the estimation of the aging state includes the following two cases
Firstly, obtaining a rated value or a reference value of the medium parameter variation through a preliminary test of a standard test sample:
calculating the maximum temperature fluctuation quantity delta Tmax under all temperature indexes Ti, namely subtracting the lowest temperature from the maximum temperature under the temperature indexes Ti, wherein the maximum variation quantity delta Dx of Dx is Dxmax-Dxmin; calculating the variable quantity of the medium parameters: ag — θ ═ Δ Dx/β;
wherein β ═ Δ Tmax × (ζ w- ζ 0); zeta w is the water dielectric constant at Ti temperature, and zeta 0 is the standard value, factory value or reference value of the insulation layer of the tested equipment; ζ w ═ 0.3997 × t +0.00094 × t2+87.74, t is the temperature value; a typical reference value of ζ 0 is 3.6 when the device is an oil-paper insulated transformer or an oil-paper insulated capacitor, and 2.7 when the device is a crosslinked cable;
if the Ag _ theta exceeds the rated value or the reference value by more than 10%, slight aging is considered to exist, more obvious aging is considered to exist when the Ag _ theta exceeds 20%, and serious aging is considered to exist when the Ag _ theta exceeds 30%;
secondly, when the rated value or the typical reference value of the medium parameter variation cannot be obtained, calculating:
Preferably, when the insulation structure of the device to be tested is complex, alpha or
The method is characterized in that the aging state of the tested equipment is evaluated in a mode of calculating a plurality of aging correlation quantities of water content, dielectric constant and dielectric loss angle by adopting a neural network algorithm when the experience value is difficult to take, or the comprehensive dielectric constant zeta x of the tested equipment under a plurality of insulating media is required to be calculated or a more accurate aging value index is required because the complex water content of the insulating structure of the tested equipment is mainly remained in a certain layer of insulating media inside the tested equipment, and the specific process comprises the following steps:
b1, measuring the internal temperature value and the environment humidity of the equipment, counting the maximum value Dxmax and the minimum value Dxmin, and calculating the water relative dielectric constant zeta w corresponding to the average temperature and the factory or rated dielectric constant zeta 0 of the equipment to be tested in the process of power failure temperature rise of the equipment to be tested or temperature change of the equipment to be tested during operation; the temperature change process refers to a process in which the increment and decrement of temperature change are both greater than 1 degree;
in the sample training stage, gamma is set as the consistent water content in the insulating solid, zeta x is the dielectric constant or the relative dielectric constant, the dielectric constant is measured by a dielectric constant test device, delta is the dielectric loss angle, and the dielectric loss angle is obtained by a dielectric loss test instrument or a dielectric spectrum test instrument; the data properties of Dxmax and Dxmin are related to the properties of the dielectric electrical parameter testing device, and typical fluctuation intervals of the internal temperature of the tested device are as follows:
when the dielectric electrical parameter testing equipment is a capacitance tester, Dxmax is the maximum capacitance value, and Dxmin is the minimum capacitance value;
when the dielectric electrical parameter testing equipment is a dielectric spectrum tester, Dxmax is the maximum dielectric loss, and Dxmin is the minimum dielectric loss;
when the dielectric electrical parameter testing equipment is a time domain reflectometer, Dxmax is the maximum reflection time difference or the maximum reflection gain, and Dxmin is the minimum reflection time difference or the minimum reflection gain;
when the dielectric electrical parameter testing equipment is a frequency domain reflection instrument, Dxmax is the maximum reflection time difference or the maximum reflection gain, and Dxmin is the minimum reflection time difference or the minimum reflection gain;
when the dielectric electrical parameter testing equipment is insulation resistance testing equipment, Dxmax is the maximum insulation resistance, and Dxmin is the minimum insulation resistance;
when the dielectric electrical parameter testing equipment is power loss testing equipment, Dxmax is maximum power loss, and Dxmin is minimum power loss;
when the dielectric electrical parameter testing equipment is power factor testing equipment, Dxmax is the maximum power factor, and Dxmin is the minimum power factor;
when the dielectric electrical parameter testing equipment is broadband impedance testing equipment, Dxmax is a peak point of the broadband impedance or the maximum gain of the broadband impedance after Fourier transformation, and Dxmin is a valley point of the broadband impedance or the minimum gain of the broadband impedance after Fourier transformation;
setting different zeta 0 values aiming at tested equipment of different insulating materials, carrying out actual measurement under the condition of standard known water content, and obtaining not less than 3 related training samples, wherein the reference water content of typical training is not less than 1%, 5% and 10%; under the condition that the test conditions meet, a training sample is established by considering a standard test environment with the water content of 0.5-70%; when the environment humidity measurement is not available, setting the environment humidity parameter in the neural network training sample to zero or 1 or setting the parameter to be a constant;
b2, constructing a neural network: the neural network structure is MxkXN, the input layers M are defined to be 6, the output layers N are 3, the hidden layers k are 1-9 layers, and the neural network algorithm is developed on the samples based on a BBP algorithm, a RBF neural network algorithm, a linear neural network and a self-organizing neural network to obtain a learning model of the neural network;
b3, constructing measured data as a known input quantity and a known output quantity of the trained neural network model; the input quantity is: measured average value T of measured equipment temperatureavgMeasured average value H of ambient humidityavgWater relative dielectric constant zeta w corresponding to Dxmax, Dxmin and Tavg measured in a certain temperature change interval and the designed factory dielectric constant or rated dielectric constant zeta 0 of the tested equipment;
the output quantity is as follows: γ, ζ x, δ;
b4, monitoring the temperature and the Dx value of the tested equipment, when the fluctuation amount of the temperature is larger than a threshold value, wherein the threshold value is larger than or equal to 1 degree, operating the neural network model, and comparing Dxmax, Dxmin and the measured average value T of the temperature of the tested equipmentavgMeasured average value H of ambient humidityavgObtaining output quantities gamma, zeta x and delta by taking the relative dielectric constant zeta w as input quantities; wherein, gamma is the water content in the insulating solid, zeta x is the dielectric constant or relative dielectric constant, and delta is the dielectric loss angle of the tested device.
Preferably, the temperature rise and fall condition means that the temperature inside the device under test rises and falls by no less than 10% of the ambient temperature.
When the internal temperature can be converted from the device surface temperature, the temperature rise and fall condition may also mean that the device surface temperature under test rises and falls by not less than 10% of the ambient temperature.
The invention has the beneficial effects that: the invention solves the problems that the moisture content of the multilayer composite insulating medium is not uniform, the simple external capacitance or dielectric loss measurement can only measure the surface medium or comprehensive medium parameters, and the real moisture content in the medium and the aging evaluation condition cannot be met. The method solves the problem of predicting the failure caused by the change of the insulation strength method caused by the movement of internal moisture or medium in the operation process of the power equipment; the device solves the problems that the insulation medium of the equipment can be evaluated to be in a damp and ageing state under the operating condition and the power failure state; the method provides a new solution for the production, processing, calibration/verification, test and operation maintenance of high-specification and high-quality electric and electronic equipment.
Drawings
FIG. 1 is a flow chart of a method of the present invention;
FIG. 2 is a graph illustrating an electrical parameter of a medium versus temperature;
figure 3 is a schematic view of the principle of the construction device according to the invention;
FIG. 4 is a graph showing capacitance-temperature curves plotted in the examples.
Detailed Description
The technical solutions of the present invention are further described in detail below with reference to the accompanying drawings, but the scope of the present invention is not limited to the following.
As shown in FIG. 1, the method for evaluating the water content and aging of the capacitive equipment medium based on the temperature drift electrical parameters comprises the following steps:
s1, collecting medium electric parameters of a tested device, the internal temperature of the tested device and corresponding environment temperature and humidity parameters within a certain time or under a temperature/humidity lifting condition;
s2, calculating the variation of the medium parameters in the process of rising and falling by temperature and/or environmental humidity according to the acquired information;
and S3, evaluating the water content and the aging degree of the tested equipment.
In step S1, the parameter acquisition includes a live acquisition mode and a power failure acquisition mode.
The acquisition process of the charged acquisition mode comprises the following steps:
monitoring the dielectric electrical parameter Dx of the equipment To be measured, and synchronously measuring the internal temperature Ti value, the ambient temperature To and the humidity Ro value of the equipment; the dielectric electrical parameter comprises at least one of capacitance, power factor, dielectric loss, power loss, insulation impedance, time domain reflection coefficient, frequency domain reflection coefficient and broadband impedance;
recording a medium electrical parameter Dx under the condition of a plurality of Ti, T0 and Ro under the running condition of the tested equipment, and drawing at least one of Dx-Ti, Dx-To and Dx-Ro curves; the recorded time is not less than 120S.
The collection process of the power failure collection mode comprises the following steps:
a1, heating the tested device; the heating mode is at least one of the following modes:
firstly, placing the tested equipment into a temperature control box body or winding and wrapping the tested equipment with temperature control heating equipment;
secondly, applying a voltage or a current source to the tested device to enable the inside to generate current and heat;
a2, monitoring dielectric electrical parameters Dx of the equipment To be tested, and synchronously measuring the internal temperature Ti value, the environmental temperature To and the humidity Ro value of the equipment; the dielectric parameter Dx is any one of capacitance, power factor, dielectric loss, power loss, time domain reflection coefficient, frequency domain reflection coefficient, broadband impedance or insulation impedance;
a3, stopping heating the tested equipment, cooling the tested equipment, and repeatedly executing the operation of the step A2 at fixed time intervals of not less than 10S;
a4, recording medium electrical parameters Dx under the conditions of multiple Ti, T0 and Ro in the temperature rising and lowering process of the tested equipment, and drawing at least one of Dx-Ti, Dx-To and Dx-Ro curves; the recorded time is not less than 120S.
Further, the step S2 includes:
in the up-and-down fluctuation process of the temperature of the tested equipment, the electric parameter values corresponding to the equivalent temperature values at different times are recorded, the difference of the electric parameter values is calculated, and analysis is carried out, specifically:
calculating the maximum value Dxmax and the minimum value Dxmin of Dx under the same corresponding temperature index Ti in the process of temperature fluctuation; calculating the variable quantity of the medium parameters: θ ═ (× ax-Dxmin)/(ζ w- ζ 0); zeta w is the water dielectric constant at Ti temperature, and zeta 0 is the standard value or reference value of the insulation layer of the tested device;
ζw＝-0.3997×t+0.00094×t2+87.74, t is the temperature value; the reference value of ζ 0 is 3.6 when the device is an oil-paper insulated transformer or an oil-paper insulated capacitor, and the reference value of ζ 0 is 2.7 when the device is a crosslinked cable.
As shown in fig. 2, in the coordinate system, the abscissa is a dielectric parameter (one of capacitance, dielectric loss, time domain reflection amount, frequency domain reflection amount, and insulation resistance), and the ordinate is temperature Ti.
In the operation process of the tested device or in the heating process of the tested device by applying voltage/current externally, due to the double effects of heating and wetting, under the same temperature, a plurality of corresponding Dxs are provided, but the numerical values are not necessarily the same. As shown by a dotted line, the same Ti value corresponds to a plurality of Dx values under different time periods or in the temperature fluctuation process of the tested device, so that the maximum value and the minimum value are different.
In step S3, the calculated water content is a volume water content, and the calculation method is as follows:
alpha is 0.600-1.500, and a typical value alpha is 0.899.
Further, in the step S3, the estimation of the aging state includes the following two cases
Firstly, obtaining a rated value or a reference value of the medium parameter variation through a preliminary test of a standard test sample:
calculating the maximum temperature fluctuation quantity delta Tmax under all temperature indexes Ti, namely subtracting the lowest temperature from the maximum temperature under the temperature indexes Ti, wherein the maximum variation quantity delta Dx of Dx is Dxmax-Dxmin; calculating the variable quantity of the medium parameters: ag — θ ═ Δ Dx/β;
wherein β ═ Δ Tmax × (ζ w- ζ 0); zeta w is the water dielectric constant at Ti temperature, and zeta 0 is the standard value, factory value or reference value of the insulation layer of the tested equipment; ζ w ═ 0.3997 × t +0.00094 × t2+87.74, t is the temperature value; a typical reference value of ζ 0 is 3.6 when the device is an oil-paper insulated transformer or an oil-paper insulated capacitor, and 2.7 when the device is a crosslinked cable;
if the Ag _ theta exceeds the rated value or the reference value by more than 10%, slight aging is considered to exist, more obvious aging is considered to exist when the Ag _ theta exceeds 20%, and serious aging is considered to exist when the Ag _ theta exceeds 30%;
secondly, when the rated value or the typical reference value of the medium parameter variation cannot be obtained, calculating:
In the embodiment of the application, alpha or is caused when the insulation structure of the tested device is complicated
The method is difficult to evaluate, or the water content, the dielectric constant and the dielectric loss are calculated by adopting a neural network algorithm when the complex water content of the insulation structure of the tested equipment is mainly retained in a certain layer of insulation medium in the tested equipment or the comprehensive dielectric constant zeta x under a plurality of insulation media of the tested equipment needs to be calculated or a more accurate aging value index is neededEvaluating the aging state of the tested equipment in a mode of a plurality of aging associated quantities, wherein the specific process comprises the following steps:
b1, measuring the internal temperature value and the environment humidity of the equipment, counting the maximum value Dxmax and the minimum value Dxmin, and calculating the water relative dielectric constant zeta w corresponding to the average temperature and the factory or rated dielectric constant zeta 0 of the equipment to be tested in the process of power failure temperature rise of the equipment to be tested or temperature change of the equipment to be tested during operation; the temperature change process refers to a process in which the increment and decrement of temperature change are both greater than 1 degree;
in the sample training stage, gamma is set as the consistent water content in the insulating solid, zeta x is the dielectric constant or the relative dielectric constant, the dielectric constant is measured by a dielectric constant test device, delta is the dielectric loss angle, and the dielectric loss angle is obtained by a dielectric loss test instrument or a dielectric spectrum test instrument; the data properties of Dxmax and Dxmin are related to the properties of the dielectric electrical parameter testing device, and typical fluctuation intervals of the internal temperature of the tested device are as follows:
when the dielectric electrical parameter testing equipment is a capacitance tester, Dxmax is the maximum capacitance value, and Dxmin is the minimum capacitance value;
when the dielectric electrical parameter testing equipment is a dielectric spectrum tester, Dxmax is the maximum dielectric loss, and Dxmin is the minimum dielectric loss;
when the dielectric electrical parameter testing equipment is a time domain reflectometer, Dxmax is the maximum reflection time difference or the maximum reflection gain, and Dxmin is the minimum reflection time difference or the minimum reflection gain;
when the dielectric electrical parameter testing equipment is a frequency domain reflection instrument, Dxmax is the maximum reflection time difference or the maximum reflection gain, and Dxmin is the minimum reflection time difference or the minimum reflection gain;
when the dielectric electrical parameter testing equipment is insulation resistance testing equipment, Dxmax is the maximum insulation resistance, and Dxmin is the minimum insulation resistance;
when the dielectric electrical parameter testing equipment is power loss testing equipment, Dxmax is maximum power loss, and Dxmin is minimum power loss;
when the dielectric electrical parameter testing equipment is power factor testing equipment, Dxmax is the maximum power factor, and Dxmin is the minimum power factor;
when the dielectric electrical parameter testing equipment is broadband impedance testing equipment, Dxmax is a peak point of the broadband impedance or the maximum gain of the broadband impedance after Fourier transformation, and Dxmin is a valley point of the broadband impedance or the minimum gain of the broadband impedance after Fourier transformation;
setting different zeta 0 values aiming at tested equipment of different insulating materials, carrying out actual measurement under the condition of standard known water content, and obtaining not less than 3 related training samples, wherein the reference water content of typical training is not less than 1%, 5% and 10%; under the condition that the test conditions meet, a training sample is established by considering a standard test environment with the water content of 0.5-70%; when the environment humidity measurement is not available, setting the environment humidity parameter in the neural network training sample to zero or 1 or setting the parameter to be a constant;
b2, constructing a neural network: the neural network structure is MxkXN, the input layers M are defined to be 6, the output layers N are 3, the hidden layers k are 1-9 layers, and the neural network algorithm is developed on the samples based on a BBP algorithm, a RBF neural network algorithm, a linear neural network and a self-organizing neural network to obtain a learning model of the neural network;
b3, constructing measured data as a known input quantity and a known output quantity of the trained neural network model; the input quantity is: measured average value T of measured equipment temperatureavgMeasured average value H of ambient humidityavgWater relative dielectric constant zeta w corresponding to Dxmax, Dxmin and Tavg measured in a certain temperature change interval and the designed factory dielectric constant or rated dielectric constant zeta 0 of the tested equipment;
the output quantity is as follows: γ, ζ x, δ;
b4, monitoring the temperature and the Dx value of the tested equipment, when the fluctuation amount of the temperature is larger than a threshold value, wherein the threshold value is larger than or equal to 1 degree, operating the neural network model, and comparing Dxmax, Dxmin and the measured average value T of the temperature of the tested equipmentavgMeasured average value H of ambient humidityavgObtaining output quantities gamma, zeta x and delta by taking the relative dielectric constant zeta w as input quantities; wherein, gamma is the water content in the insulating solid, zeta x is the dielectric constant or relative dielectric constant, and delta is the dielectric loss angle of the tested device.
The temperature rise and fall condition means that the temperature rise and fall in the tested equipment is not lower than 10% of the ambient temperature, if the ambient temperature is 10 ℃, the rise temperature is not lower than 1 ℃, and the fall temperature is not lower than 1 ℃. If not, the collection is carried out all the time, and the step does not enter S3. If the ambient temperature is only 5 ℃, the rising temperature is not lower than 0.5 ℃, and the falling temperature is not lower than 0.5 ℃. If the environmental file is 40 degrees, the rising temperature is not lower than 4 degrees, and the falling temperature is not lower than 4 degrees.
In the embodiment of the application, the water content and aging evaluation device built by combining the method of the invention is shown in fig. 3 and comprises a microprocessor, a display, a communication module, a temperature measurement module, a tested device, a heating module and a medium electrical parameter test device; the heating equipment is provided with a timer and is used for heating the equipment to be tested according to the timer; the temperature measuring module is used for measuring the temperature of the tested equipment, and the dielectric electrical parameter testing equipment is used for measuring the dielectric electrical parameters of the tested equipment; and the microprocessor is respectively connected with the display, the communication module, the temperature measuring module and the medium electrical parameter testing equipment.
The scheme of the present application will now be further illustrated with reference to specific examples:
example 1: the insulation aging and moisture test for the transformer and the mutual inductor is carried out;
the auxiliary power supply is connected with a winding of the mutual inductor through a switch. The auxiliary power supply is a low-frequency alternating current power supply, is 0.1Hz and has the power of 200V, is applied to the secondary winding of the voltage transformer, and short-circuits the primary winding. At this time, a large current value is generated in the transformer, and the temperature starts to rise.
Measuring capacitance values between a high-voltage side or a low-voltage side of the mutual inductor and a grounding end of a mutual inductor shell at regular time, arranging a temperature sensor at a high-voltage side or a low-voltage side terminal of the mutual inductor to measure the temperature of the terminal and record the temperature value, and then analyzing a plurality of obtained temperature and capacitance values after a period of time to obtain a capacitance temperature curve; and then stopping the auxiliary power supply, and recording the capacitance and the temperature value in the temperature reduction process of the mutual inductor. The final plotted capacitance-temperature curve is shown in fig. 4.
As shown by the arrow in the figure, the downward direction of the arrow is the capacitance value (curve) during the temperature rise;
the arrow up direction is the capacitance value (curve) during the temperature drop.
Obviously, the temperature sensor in this embodiment may also be an infrared sensor, and at this time, the infrared sensor may be aligned to the transformer winding, and the temperature value inside the winding is measured, and the capacitance-temperature curve is obtained together with the measured capacitance value.
The capacitance value can be converted into parameters such as dielectric loss, capacitance internal resistance ESR measurement, time domain reflection, frequency domain reflection and the like by the same method.
Example 2: neural network computing
The dielectric parameter Dx is capacitance, the tested device is a capacitor, and a capacitance tester with 10kHz and 70V is adopted for testing, so that the capacitance tester can generate large high-frequency current and heat inside the capacitor. Establish the rated nominal value of electric capacity and be 6000pF, tracked the electric capacity data under a plurality of internal temperature environment, simulated the insulating degree of weing of condenser oilpaper, given condenser test time 10 minutes, recorded the capacitance value under a plurality of temperatures, selected three temperature point 55, 59, 65 degrees, calculated maximum capacitance, minimum capacitance, the neural network sample of establishment:
as shown in the above table, the first three sets of data in the 55 degree, 59 degree, 65 degree environment are laboratory training sample data.
After training, the fourth set of data was measured, and when the internal temperature of the capacitor was 61 degrees, the maximum value 7530 and the minimum value 7210 of the measured capacitance were obtained, and the moisture content γ was 3.55%, the dielectric constant ζ x 3.12, and the dielectric loss angle difference δ was 0.013.
Therefore, after the neural network training sample is adopted, the water content and the dielectric constant can be calculated only by collecting a capacitance value and an average temperature value for the equipment, and if the tested equipment is in an operation state, the water content and the dielectric constant can be directly obtained according to the current working temperature and the capacitance value of one point, so that the algorithm model of the neural network is suitable for power failure equipment and live equipment.
Also, even if the dielectric parameter training test Dx is a dielectric loss, when the dielectric loss measuring device is only data of one temperature point, the data cannot accurately reflect the true and stable dielectric characteristics, so the dielectric constant and the dielectric loss angle of the output end of the neural network can correct the measured value of the dielectric loss measuring device, or it can be considered that the output dielectric loss angle (or tg δ dielectric loss) based on the neural network already considers the environmental or temperature influence and is more convincing than the data of simple temperature and humidity correction.
After verification, the dielectric parameters comprise capacitance, dielectric loss, Time Domain Reflection (TDR), frequency domain impedance and the like, and finally calculated water content, dielectric constant and dielectric loss angle are basically consistent, so that the algorithm has strong universality.
Obviously, the term aging and moisture content described in this patent is only a representative index for expressing the insulation performance of the tested capacitive device, and the usage is not limited to the category of aging or service life, and is also applicable to various purposes such as defect screening, quality identification, reliability analysis, fault diagnosis and the like.
In summary, the patent fully studies the change of the internal medium of a capacitive medium (including an insulating capacitor medium of electromagnetic electrical equipment) under the influence of temperature, particularly the migration and distribution phenomena of water molecules under the influence of temperature under the damp condition, so that the research finds that the parameters of the capacitor medium tested at the same temperature Ti are inconsistent in the processes of temperature rise and temperature fall, the higher the inconsistency is, the more serious the equipment is damped or the worse the stability is, and the patent scheme is obtained after induction and analysis are performed on partial test data. The device can be used for the extended application of capacitance type, dielectric type, time domain reflection or frequency domain reflection type devices, or can be used as independent capacitive medium water content and aging test equipment, calibration equipment or state monitoring equipment with the temperature measurement check of the tested equipment.
While the foregoing description shows and describes a preferred embodiment of the invention, it is to be understood, as noted above, that the invention is not limited to the form disclosed herein, but is not intended to be exhaustive or to exclude other embodiments and may be used in various other combinations, modifications, and environments and may be modified within the scope of the inventive concept described herein by the above teachings or the skill or knowledge of the relevant art. And that modifications and variations may be effected by those skilled in the art without departing from the spirit and scope of the invention as defined by the appended claims.
Claims (9)
1. The capacitive equipment medium water content and aging evaluation method based on the temperature drift electrical parameters is characterized by comprising the following steps: the method comprises the following steps:
s1, collecting medium electric parameters of a tested device, the internal temperature of the tested device and corresponding environment temperature and humidity parameters within a certain time or under a temperature/humidity lifting condition;
s2, calculating the variation of the medium parameters in the process of rising and falling by temperature and/or environmental humidity according to the acquired information;
and S3, evaluating the water content and the aging degree of the tested equipment.
2. The method for evaluating the water content and the aging of the capacitive equipment medium based on the temperature drift electrical parameters as claimed in claim 1, wherein: in step S1, the parameter acquisition includes an electrified acquisition mode and a power-off acquisition mode.
3. The method for evaluating the water content and the aging of the capacitive equipment medium based on the temperature drift electrical parameter as claimed in claim 2, wherein: the acquisition process of the charged acquisition mode comprises the following steps:
monitoring the dielectric electrical parameter Dx of the equipment To be measured, and synchronously measuring the internal temperature Ti value, the ambient temperature To and the humidity Ro value of the equipment; the dielectric electrical parameter comprises at least one of capacitance, dielectric loss, power factor, power loss, insulation impedance, time domain reflection coefficient, frequency domain reflection coefficient and broadband impedance;
recording a medium electrical parameter Dx under the condition of a plurality of Ti, T0 and Ro under the operation condition of the tested equipment, and drawing at least one of Dx-Ti, Dx-To and Dx-Ro curves; the recorded time is not less than 120S.
4. The method for evaluating the water content and the aging of the capacitive equipment medium based on the temperature drift electrical parameter as claimed in claim 2, wherein: the collection process of the power failure collection mode comprises the following steps:
a1, heating the tested device; the heating mode is at least one of the following modes:
firstly, placing the tested equipment into a temperature control box body or winding and wrapping the tested equipment with temperature control heating equipment;
secondly, applying a voltage or a current source to the tested device to enable the inside to generate current and heat;
a2, monitoring dielectric electrical parameters Dx of the equipment To be tested, and synchronously measuring the internal temperature Ti value, the environmental temperature To and the humidity Ro value of the equipment; the dielectric parameter Dx is any one of capacitance, dielectric loss, power factor, power loss, time domain reflection coefficient, frequency domain reflection coefficient, broadband impedance or insulation impedance;
a3, stopping heating the tested equipment, cooling the tested equipment, and repeatedly executing the operation of the step A2 at fixed time intervals of not less than 10S;
a4, recording medium electrical parameters Dx under the conditions of multiple Ti, T0 and Ro in the temperature rising and lowering process of the tested equipment, and drawing at least one of Dx-Ti, Dx-To and Dx-Ro curves; the recorded time is not less than 120S.
5. The method for evaluating the water content and the aging of the capacitive equipment medium based on the temperature drift electrical parameters as claimed in claim 1, wherein: the step S2 includes:
in the up-and-down fluctuation process of the temperature of the tested equipment, the electric parameter values corresponding to the equivalent temperature values at different times are recorded, the difference of the electric parameter values is calculated, and analysis is carried out, specifically:
calculating the maximum value Dxmax and the minimum value Dxmin of Dx under the same corresponding temperature index Ti in the process of temperature fluctuation; calculating the variable quantity of the medium parameters: θ ═ (× ax-Dxmin)/(ζ w- ζ 0); zeta w is the water dielectric constant at Ti temperature, and zeta 0 is the standard value or reference value of the insulation layer of the tested device;
ζw＝-0.3997×t+0.00094×t2+87.74, t is the temperature value; the reference value of ζ 0 is 3.6 when the device is an oil-paper insulated transformer or an oil-paper insulated capacitor, and the reference value of ζ 0 is 2.7 when the device is a crosslinked cable.
6. The method for evaluating the water content and the aging of the capacitive equipment medium based on the temperature drift electrical parameters as claimed in claim 1, wherein: in step S3, the calculated water content is a volume water content, and the calculation method is as follows:
alpha is 0.600-1.500, and a typical value alpha is 0.899.
7. The method for evaluating the water content and the aging of the capacitive equipment medium based on the temperature drift electrical parameters as claimed in claim 1, wherein: in the step S3, the estimation of the aging state includes the following two cases
Firstly, obtaining a rated value or a reference value of the medium parameter variation through a preliminary test of a standard test sample:
calculating the maximum temperature fluctuation quantity delta Tmax under all temperature indexes Ti, namely subtracting the lowest temperature from the maximum temperature under the temperature indexes Ti, wherein the maximum variation quantity delta Dx of Dx is Dxmax-Dxmin; calculating the variable quantity of the medium parameters: ag — θ ═ Δ Dx/β;
wherein β ═ Δ Tmax × (ζ w- ζ 0); zeta w is the water dielectric constant at Ti temperature, and zeta 0 is the standard value, factory value or reference value of the insulation layer of the tested equipment; ζ w ═ 0.3997 × t +0.00094 × t2+87.74, t is the temperature value; a typical reference value of ζ 0 is 3.6 when the device is an oil-paper insulated transformer or an oil-paper insulated capacitor, and 2.7 when the device is a crosslinked cable;
if the Ag _ theta exceeds the rated value or the reference value by more than 10%, slight aging is considered to exist, more obvious aging is considered to exist when the Ag _ theta exceeds 20%, and serious aging is considered to exist when the Ag _ theta exceeds 30%;
secondly, when the rated value or the typical reference value of the medium parameter variation cannot be obtained, calculating:
8. The method for evaluating the water content and the aging of the capacitive equipment medium based on the temperature drift electrical parameters as claimed in claim 1, wherein: when the insulation structure of the device to be tested is complicated, alpha or
The method is characterized in that the aging state of the tested equipment is evaluated in a mode of calculating a plurality of aging correlation quantities of water content, dielectric constant and dielectric loss angle by adopting a neural network algorithm when the experience value is difficult to take, or the comprehensive dielectric constant zeta x of the tested equipment under a plurality of insulating media is required to be calculated or a more accurate aging value index is required because the complex water content of the insulating structure of the tested equipment is mainly remained in a certain layer of insulating media inside the tested equipment, and the specific process comprises the following steps:
b1, measuring the internal temperature value and the environment humidity of the equipment, counting the maximum value Dxmax and the minimum value Dxmin, and calculating the water relative dielectric constant zeta w corresponding to the average temperature and the factory or rated dielectric constant zeta 0 of the equipment to be tested in the process of power failure temperature rise of the equipment to be tested or temperature change of the equipment to be tested during operation; the temperature change process refers to a process in which the increment and decrement of temperature change are both greater than 1 degree;
in the sample training stage, gamma is set as the consistent water content in the insulating solid, zeta x is the dielectric constant or the relative dielectric constant, the dielectric constant is measured by a dielectric constant test device, delta is the dielectric loss angle, and the dielectric loss angle is obtained by a dielectric loss test instrument or a dielectric spectrum test instrument; the data properties of Dxmax and Dxmin are related to the properties of the dielectric electrical parameter testing device, and typical fluctuation intervals of the internal temperature of the tested device are as follows:
when the dielectric electrical parameter testing equipment is a capacitance tester, Dxmax is the maximum capacitance value, and Dxmin is the minimum capacitance value;
when the dielectric electrical parameter testing equipment is a dielectric spectrum tester, Dxmax is the maximum dielectric loss, and Dxmin is the minimum dielectric loss;
when the dielectric electrical parameter testing equipment is a time domain reflectometer, Dxmax is the maximum reflection time difference or the maximum reflection gain, and Dxmin is the minimum reflection time difference or the minimum reflection gain;
when the dielectric electrical parameter testing equipment is a frequency domain reflection instrument, Dxmax is the maximum reflection time difference or the maximum reflection gain, and Dxmin is the minimum reflection time difference or the minimum reflection gain;
when the dielectric electrical parameter testing equipment is insulation resistance testing equipment, Dxmax is the maximum insulation resistance, and Dxmin is the minimum insulation resistance;
when the dielectric electrical parameter testing equipment is power loss testing equipment, Dxmax is maximum power loss, and Dxmin is minimum power loss;
when the dielectric electrical parameter testing equipment is power factor testing equipment, Dxmax is the maximum power factor, and Dxmin is the minimum power factor;
when the dielectric electrical parameter testing equipment is broadband impedance testing equipment, Dxmax is a peak point of the broadband impedance or the maximum gain of the broadband impedance after Fourier transformation, and Dxmin is a valley point of the broadband impedance or the minimum gain of the broadband impedance after Fourier transformation;
setting different zeta 0 values aiming at tested equipment of different insulating materials, carrying out actual measurement under the condition of standard known water content, and obtaining not less than 3 related training samples, wherein the reference water content of typical training is not less than 1%, 5% and 10%; under the condition that the test conditions meet, a training sample is established by considering a standard test environment with the water content of 0.5-70%; when the environment humidity measurement is not available, setting the environment humidity parameter in the neural network training sample to zero or 1 or setting the parameter to be a constant;
b2, constructing a neural network: the neural network structure is MxkXN, the input layers M are defined to be 6, the output layers N are 3, the hidden layers k are 1-9 layers, and the neural network algorithm is developed on the samples based on a BBP algorithm, a RBF neural network algorithm, a linear neural network and a self-organizing neural network to obtain a learning model of the neural network;
b3, constructing measured data as a known input quantity and a known output quantity of the trained neural network model; the input quantity is: measured average value T of measured equipment temperatureavgMeasured average value H of ambient humidityavgWater relative dielectric constant zeta w corresponding to Dxmax, Dxmin and Tavg measured in a certain temperature change interval and the designed factory dielectric constant or rated dielectric constant zeta 0 of the tested equipment;
the output quantity is as follows: γ, ζ x, δ;
b4, monitoring the temperature and the Dx value of the tested equipment, when the fluctuation amount of the temperature is larger than a threshold value, wherein the threshold value is larger than or equal to 1 degree, operating the neural network model, and comparing Dxmax, Dxmin and the measured average value T of the temperature of the tested equipmentavgMeasured average value H of ambient humidityavgObtaining output quantities gamma, zeta x and delta by taking the relative dielectric constant zeta w as an input quantity; wherein, gamma is the water content in the insulating solid, zeta x is the dielectric constant or relative dielectric constant, and delta is the dielectric loss angle of the tested device.
9. The method for evaluating the water content and the aging of the capacitive equipment medium based on the temperature drift electrical parameters as claimed in claim 1, wherein: the temperature rise and fall condition means that the temperature rise and fall in the tested equipment is not lower than 10% of the ambient temperature.
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