CN114528726B - Method and equipment for correcting dielectric spectrum curve of oil paper insulation frequency domain at time-varying temperature - Google Patents
Method and equipment for correcting dielectric spectrum curve of oil paper insulation frequency domain at time-varying temperature Download PDFInfo
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Abstract
The application provides a method and equipment for correcting dielectric spectrum curves of an oil paper insulating frequency domain under time-varying temperature. The temperature distribution cloud image is a three-dimensional temperature distribution cloud image of heat dissipation of a two-dimensional axisymmetric model at different moments. And determining a corresponding first function of the two-dimensional axisymmetric model according to the temperature distribution cloud maps at different moments. And determining a second function according to the dielectric relaxation model and a plurality of preset constant temperature frequency domain dielectric spectrum FDS curves. And determining the equivalent temperature corresponding to each frequency point of the FDS curve to be corrected through a least square method according to the first function and the second function. The FDS curve to be corrected is obtained by collecting and testing the oilpaper insulating sleeve through the FDS tester. And correcting the FDS curve to be corrected according to each equivalent temperature and a preset mode.
Description
Technical Field
The application relates to the technical field of oil paper insulation, in particular to a method and equipment for correcting an oil paper insulation frequency domain dielectric spectrum curve at a time-varying temperature.
Background
The construction of the cross-regional power grid gradually becomes a necessary means for resource optimization configuration, wherein the fine management of the life cycle of the power equipment is a key for constructing the safe and efficient smart power grid. The capacitor type high-voltage bushing is taken as one of the most important equipment in the power system, namely the throat of the power system, and the residual service life of the capacitor type high-voltage bushing mainly depends on the insulation state with the internal oilpaper.
Because the oil paper insulation can be aged and damped gradually under the action of various stresses, at present, a person skilled in the art mainly adopts a return voltage method, a polarization/depolarization current method and a frequency domain dielectric spectroscopy method to detect the insulation state, and the frequency domain dielectric spectroscopy method (frequency domain spectroscopy, FDS) is more favored by users due to the characteristic of strong anti-interference capability. In the detection of the oilpaper insulation state using the frequency-domain dielectric spectroscopy, the frequency-domain dielectric spectroscopy is generally obtained at a steady-state temperature. However, in the actual use process, the device may be in a dynamic cooling process under the influence of external factors such as regions and climates, and the temperature of the device is time-varying, so that the FDS curve obtained under the condition is affected by the temperature, and the insulation state of the oilpaper cannot be accurately estimated.
Disclosure of Invention
The embodiment of the application provides a method and equipment for correcting an oil paper insulation frequency domain dielectric spectrum curve at a time-varying temperature, which are used for correcting an FDS curve at the time-varying temperature to any constant temperature condition and accurately evaluating the insulation state of the oil paper.
In one aspect, an embodiment of the present application provides a method for correcting an oiled paper insulation frequency domain dielectric spectrum curve at a time-varying temperature, the method including:
and constructing a two-dimensional axisymmetric model of the test oilpaper insulating sleeve. And determining each temperature distribution cloud picture corresponding to the two-dimensional axisymmetric model according to the two-dimensional axisymmetric model. The temperature distribution cloud image is a three-dimensional temperature distribution cloud image of heat dissipation of the two-dimensional axisymmetric model at different moments. And determining a corresponding first function of the two-dimensional axisymmetric model according to the temperature distribution cloud maps at different moments. And determining a second function according to the dielectric relaxation model and a plurality of preset constant temperature frequency domain dielectric spectrum FDS curves. Wherein the second function represents the correspondence of the FDS curve with temperature. And determining the equivalent temperature corresponding to each frequency point of the FDS curve to be corrected through a least square method according to the first function and the second function. The FDS curve to be corrected is obtained by collecting and testing the oilpaper insulating sleeve through the FDS tester. And correcting the FDS curve to be corrected according to each equivalent temperature and a preset mode.
In one implementation of the application, the two-dimensional axisymmetric model is meshed and subjected to finite element analysis, and each temperature distribution cloud image is determined. The heat dissipation of the temperature distribution cloud image at least comprises the following steps: conductive heat dissipation, convective heat dissipation, radiative heat dissipation. According to each temperature distribution cloud picture at different moments, determining a corresponding first function of a two-dimensional axisymmetric model, specifically including: and determining the heat dissipation temperature of the capacitor core of the oiled paper insulating sleeve in each temperature distribution cloud picture. And generating a temperature change curve graph according to each heat dissipation temperature of the capacitor core. And fitting the curve in the temperature change curve graph to obtain a first function.
In one implementation of the present application, the first shape parameter and the second shape parameter related to the static dielectric constant, the optical frequency dielectric constant, the relaxation time, and the relaxation time distribution are used as the particle parameters according to a dielectric relaxation model. And carrying out iterative computation on each particle according to a preset particle swarm optimization algorithm and each constant-temperature FDS curve so as to obtain parameter values of each particle parameter at different temperatures. Wherein, the different temperatures are the constant temperature temperatures corresponding to the constant temperature FDS curves. A third function is determined based on the parameter values of the respective particle parameters. Wherein the third function represents a correspondence relationship between the dielectric loss tangent and the temperature. According to the third function, a binary function using temperature as a dependent variable and using dielectric loss tangent and frequency as independent variables is determined as a second function.
In one implementation of the present application, respective parameter values for respective constant temperature are determined. And determining the functional relation between each temperature and each parameter value by cubic spline interpolation according to each parameter value corresponding to each constant temperature. And determining a third function according to the functional relationships and the corresponding formulas of the dielectric loss tangent values.
In one implementation of the present application, the initial temperature at each instant is determined according to a first function. According to the initial temperature, calculating the temperature of the oil paper insulating sleeve at each moment by a least square method and a second function, and taking the temperature of each oil paper insulating sleeve as the equivalent temperature corresponding to each frequency point of the FDS curve to be corrected. The FDS curve to be corrected is acquired by an FDS tester, the high-voltage end of which is connected with a guide rod of the test oilpaper insulating sleeve, and the low-voltage end of which is connected with the end screen of the test oilpaper insulating sleeve.
In one implementation of the present application, the first function is:
T′＝ae -mt +be -nt
wherein T' is the real-time temperature, a is the first fitting coefficient, b is the second fitting coefficient, m is the first fitting index, n is the second fitting index, and T is the time.
In one implementation of the present application, the third function is:
tanδ＝f(ε s (T),ε ∞ ,τ(T),α(T),β(T))
wherein tan delta is the dielectric loss tangent, T is the temperature, ε s Is static dielectric constant epsilon ∞ For the optical frequency dielectric constant, τ is the relaxation time, α is the first shape parameter, and β is the second shape parameter.
In one implementation manner of the method, the FDS curve to be corrected after correction in a preset manner is used as a corrected FDS curve, and the corrected FDS curve is sent to the verification terminal. Wherein the preset mode is an Arrhenius formula. And determining whether the corrected FDS curve is matched with the comparison curve based on the comparison curve stored by the verification terminal. Under the condition that the correction FDS curve is not matched with the comparison curve, reconstructing the two-dimensional axisymmetric model to re-fit the first function, and obtaining an updated first function.
In another aspect, an embodiment of the present application further provides an apparatus for correcting an oilpaper insulation frequency domain dielectric spectrum curve at a time-varying temperature, the apparatus including:
at least one processor; and a memory communicatively coupled to the at least one processor. Wherein the memory stores instructions executable by the at least one processor, the instructions being executable by the at least one processor to enable the at least one processor to:
and constructing a two-dimensional axisymmetric model of the test oilpaper insulating sleeve. And determining each temperature distribution cloud picture corresponding to the two-dimensional axisymmetric model according to the two-dimensional axisymmetric model. The temperature distribution cloud image is a three-dimensional temperature distribution cloud image of heat dissipation of the two-dimensional axisymmetric model at different moments. And determining a corresponding first function of the two-dimensional axisymmetric model according to the temperature distribution cloud maps at different moments. And determining a second function according to the dielectric relaxation model and a plurality of preset constant temperature frequency domain dielectric spectrum FDS curves. Wherein the second function represents the correspondence of the FDS curve with temperature. And determining the equivalent temperature corresponding to each frequency point of the FDS curve to be corrected through a least square method according to the first function and the second function. The FDS curve to be corrected is obtained by collecting and testing the oilpaper insulating sleeve through the FDS tester. And correcting the FDS curve to be corrected according to each equivalent temperature and a preset mode.
In one implementation of the present application, the at least one processor is further specifically capable of:
and carrying out grid division and finite element analysis on the two-dimensional axisymmetric model, and determining each temperature distribution cloud picture. The heat dissipation of the temperature distribution cloud image at least comprises the following steps: conductive heat dissipation, convective heat dissipation, radiative heat dissipation. According to each temperature distribution cloud picture at different moments, determining a corresponding first function of a two-dimensional axisymmetric model, specifically including: and determining the heat dissipation temperature of the capacitor core of the oiled paper insulating sleeve in each temperature distribution cloud picture. And generating a temperature change curve graph according to each heat dissipation temperature of the capacitor core. And fitting the curve in the temperature change curve graph to obtain a first function.
Through the scheme, the equivalent temperature corresponding to each frequency point of the FDS curve in the low frequency band can be obtained according to the simulated temperature and the corresponding relation between the FDS curve and the temperature, and further the FDS curve is adjusted to the target temperature, so that correction of the FDS curve is realized. And correcting the FDS curve under the condition that the oil paper insulation is in a real-time change temperature, so that the FDS curve at a constant temperature is obtained, and the evaluation accuracy of the oil paper insulation state is ensured.
Drawings
The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this application, illustrate embodiments of the application and together with the description serve to explain the application and do not constitute an undue limitation to the application. In the drawings:
FIG. 1 is a schematic flow chart of a method for calibrating dielectric spectrum curve of oil paper insulation frequency domain at time-varying temperature in the embodiment of the application;
FIG. 2 is a schematic diagram of a method for calibrating an oil paper insulation frequency domain dielectric spectrum curve at a time-varying temperature according to an embodiment of the present application;
FIG. 3 is a schematic diagram of another method for calibrating an oil paper insulation frequency domain dielectric spectrum curve at a time-varying temperature according to an embodiment of the present application;
FIG. 4 is a schematic diagram of another method for calibrating an oil paper insulation frequency domain dielectric spectrum curve at a time-varying temperature according to an embodiment of the present application;
fig. 5 is a schematic structural diagram of an oil paper insulation frequency domain dielectric spectrum curve correction device under time-varying temperature in an embodiment of the application.
Detailed Description
For the purposes, technical solutions and advantages of the present application, the technical solutions of the present application will be clearly and completely described below with reference to specific embodiments of the present application and corresponding drawings. It will be apparent that the described embodiments are only some, but not all, of the embodiments of the present application. All other embodiments, which can be made by one of ordinary skill in the art without undue burden from the present disclosure, are within the scope of the present disclosure.
In the actual use field of the capacitive high-voltage bushing, the heat conduction of bushing insulation, the heat convection of air and the bushing and the heat radiation of the bushing, so that the heat dissipation rate of the bushing is continuously changed. The internal temperature of the bushing or transformer cannot be easily obtained due to the limitations of the field environment. This makes the tested FDS curve error, which cannot be eliminated by temperature variation.
Based on the above, the embodiment of the application provides a method and equipment for correcting an oil paper insulation frequency domain dielectric spectrum curve at a time-varying temperature, which correct an FDS curve at the time-varying temperature to any constant temperature condition and accurately evaluate the insulation state of the oil paper.
Various embodiments of the present application are described in detail below with reference to the accompanying drawings.
The embodiment of the application provides a method for correcting an oilpaper insulation frequency domain dielectric spectrum curve at a time-varying temperature, as shown in fig. 1, the method can comprise the steps of S101-S106:
s101, the server builds a two-dimensional axisymmetric model for testing the oilpaper insulating sleeve.
It should be noted that, the server is used as an execution body of the oilpaper insulation frequency domain dielectric spectrum curve correction method under the time-varying temperature, and the execution body is only exemplary, and is not limited to the server, and the application is not limited in particular.
In the embodiment of the application, the server can establish a two-dimensional axisymmetric model of the test oilpaper insulating sleeve through simulation software COMSOL Multiphysics, and the structure and the materials of the two-dimensional axisymmetric model are the same as those of the test oilpaper insulating sleeve.
S102, the server determines each temperature distribution cloud picture corresponding to the two-dimensional axisymmetric model according to the two-dimensional axisymmetric model.
The temperature distribution cloud image is a three-dimensional temperature distribution cloud image of heat dissipation of the two-dimensional axisymmetric model at different moments. The corresponding heat dissipation process of the temperature distribution cloud picture at least comprises conduction heat dissipation, convection heat dissipation and radiation heat dissipation.
In the embodiment of the application, the two-dimensional axisymmetric model is subjected to grid division and finite element analysis, and each temperature distribution cloud image is determined. The heat dissipation of the temperature distribution cloud image at least comprises the following steps: conductive heat dissipation, convective heat dissipation, radiative heat dissipation. Specifically, after the two-dimensional axisymmetric model is constructed through simulation software, the model can be subjected to grid division, and parameters such as constant pressure heat capacity, heat conductivity coefficient and density corresponding to materials such as a guide rod, transformer oil, insulating paper and aluminum foil of the test oilpaper insulating sleeve are set, so that the parameters of the two-dimensional axisymmetric model are consistent with the parameters of the test oilpaper insulating sleeve, and the accuracy of a simulation result is ensured. The server sets a transient solver and simulation time in simulation software, sets a domain probe and acquires a three-dimensional temperature distribution cloud image of a two-dimensional axisymmetric model in the simulation time.
In the embodiment of the application, during simulation, the simulation software analyzes three heat dissipation processes, simulates a two-dimensional axisymmetric model, and the three heat dissipation processes comprise: conductive heat dissipation, convective heat dissipation, radiative heat dissipation. The temperature distribution cloud diagram obtained by the simulation software is shown in fig. 2, wherein Y1 is the temperature distribution cloud diagram at a first moment, for example, 0 moment, and Y2 is the temperature distribution cloud diagram after heat dissipation for 60 minutes at a second moment.
Through the scheme, the purpose of detecting the time-varying characteristic of the internal temperature of the oil paper insulating sleeve can be achieved, and when the temperature of the test oil paper insulating sleeve cannot be obtained under the working condition, the internal temperature of the test oil paper insulating sleeve can be accurately reflected by the scheme, so that accurate sample data are provided for correcting the FDS curve.
S103, the server determines a first function corresponding to the two-dimensional axisymmetric model according to the temperature distribution cloud maps at different moments.
In this embodiment of the present application, the determining, by the server, a first function corresponding to the two-dimensional axisymmetric model according to each temperature distribution cloud chart at different moments specifically includes:
firstly, a server determines the heat dissipation temperature of a capacitor core of an oiled paper insulating sleeve in each temperature distribution cloud picture.
The server may determine the heat dissipation temperature of the sleeve capacitor core in the cloud chart of the temperature distribution at different moments, where the heat dissipation temperature is the temperature of the capacitor core in the heat dissipation process, for example, the heat dissipation temperature at the first moment is 80 degrees celsius, the heat dissipation temperature at the second moment is 60 degrees celsius, and the heat dissipation temperature at the third moment is 40 degrees celsius.
Then, the server generates a temperature change graph from the respective heat dissipation temperatures of the capacitor cores.
The temperature change curve graph is a curve graph of heat dissipation temperature and time of the sleeve capacitor core.
The server generates a temperature change graph as shown in fig. 3, in which the abscissa of the temperature change graph is cooling time and the ordinate is temperature, based on the heat radiation temperature corresponding to each time.
And finally, the server performs fitting processing on the curve in the temperature change curve graph to obtain a first function.
The server may fit the curve shown in fig. 3 to obtain a formula of a temperature change curve, i.e. a first function, where a specific formula of the first function is:
T′＝ae -mt +be -nt
wherein T' is the real-time temperature, a is the first fitting coefficient, b is the second fitting coefficient, m is the first fitting index, n is the second fitting index, and T is the time.
According to the scheme, the first function of the temperature change curve is obtained according to the temperature of the sleeve capacitor core, and the temperature change of the oil paper insulation inside the sleeve can be accurately determined. And the bushing capacitor core is used as a research object, so that compared with the transformer oil temperature, the obtained equipment internal oilpaper insulation temperature is more accurate.
And S104, the server determines a second function according to the dielectric relaxation model and a plurality of preset constant temperature frequency domain dielectric spectrum FDS curves.
Wherein the second function represents the correspondence of the FDS curve with temperature.
In this embodiment of the present application, the server may obtain a plurality of constant temperature frequency domain dielectric spectrum FDS curves through the internet, where the constant temperature FDS curves are shown in fig. 4. The specific expression of the Havriliak-Negami dielectric relaxation model is as follows:
where j is the unit imaginary number, ω is the frequency, τ is the relaxation time, ε s Is static dielectric constant epsilon ∞ For the optical frequency dielectric constant, α is a first shape parameter (asymmetry polarization shape parameter) related to the relaxation time distribution, β is a second shape parameter (flatness polarization shape parameter) related to the relaxation time distribution, the first shape parameter and the second shape parameter are used to adjust the shape of the curve, the first shape parameter adjusts the asymmetry of the curve, the second shape parameter adjusts the flatness of the curve, 0.ltoreq.α.ltoreq.1, 0.ltoreq.β.ltoreq.1.
According to the complex analysis theory, the following formula can be obtained:
wherein tan delta is the dielectric loss tangent. The server may calculate, according to the plurality of constant-temperature FDS curves and the expression of the Havriliak-Negami dielectric relaxation model, a functional relationship between each parameter value of the expression and temperature, thereby obtaining a second function.
In the embodiment of the application, the server determines the second function according to the Havriliak-Negami dielectric relaxation model and a preset plurality of constant temperature frequency domain dielectric spectrum FDS curves, and specifically includes:
firstly, the server takes a first shape parameter and a second shape parameter related to static dielectric constant, optical frequency dielectric constant, relaxation time and relaxation time distribution as particle parameters according to a Havriliak-Negami dielectric relaxation model.
In this embodiment of the present application, the server solves, by using a particle swarm optimization algorithm, values of a static dielectric constant, an optical frequency dielectric constant, a relaxation time, and a first shape parameter and a second shape parameter related to a relaxation time distribution, where the particle may be defined as:
wherein,the position after the (k+1) th iteration of the (i) th particle is shown. In the embodiment of the present application, the population number of the particle swarm optimization algorithm may be set to 5000, and the dimension number may be set to 5, and in the actual use process, the population number and the dimension number may be adjusted, which is not specifically limited in the present application.
And secondly, the server carries out iterative computation on each particle according to a preset particle swarm optimization algorithm and each constant-temperature FDS curve so as to obtain parameter values of each particle parameter at different temperatures.
Wherein, the different temperatures are the constant temperature temperatures corresponding to the constant temperature FDS curves. For example, the constant temperature FDS curve has 30 degrees Celsius and 40 degrees Celsius, and the different temperatures have 30 degrees Celsius and 40 degrees Celsius respectively. The parameter values of the particle parameters corresponding to the constant temperature can be calculated through the constant temperature FDS curves. For example, 30 degrees celsius, corresponds to a static dielectric constant of 1.141, an optical frequency dielectric constant of 0.987, a relaxation time of 382.81, a first shape parameter of 0.554 and a second shape parameter of 0.191, respectively.
Again, the server determines a third function based on the parameter values of the respective particle parameters. Wherein the third function represents a correspondence relationship between the dielectric loss tangent and the temperature.
Specifically, the server determines a third function according to the parameter value of each particle parameter, and specifically includes:
the server determines the respective parameter values for each constant temperature.
And the server determines the functional relation between each temperature and each parameter value respectively through cubic spline interpolation according to each parameter value corresponding to each constant temperature.
In the embodiment of the application, through cubic spline interpolation, the functional relationship between the temperature and each parameter value can be obtained, and the specific functional relationship is as follows:
static permittivity as a function of temperature:
wherein N is the number of independent permanent dipoles, mu 0 For vacuum permeability, K is Boltzmann constant, k=1.38X10-23J/K, R is the relevant atomic radius, ε 0 Is vacuum dielectric constant.
Relaxation time as a function of temperature:
τ＝Ae U/kT
wherein A is a constant coefficient, and U is molecular activation energy.
First shape parameter as a function of temperature:
α＝q 1 T 6 +q 2 T 5 +q 3 T 4 +q 4 T 3 +q 5 T 2 +q 6 T+q 7
wherein q 1 、q 2 、q 3 、q 4 、q 5 、q 6 、q 7 For the coefficient value obtained under the plurality of provided constant-temperature FDS curves, the coefficient value may vary with the number of provided constant-temperature FDS curves in the actual calculation process, and the specific value of the coefficient value is not particularly limited in this application.
Second shape parameter as a function of temperature:
β＝p 1 T 6 +p 2 T 5 +p 3 T 4 +p 4 T 3 +p 5 T 2 +p 6 T+p 7
wherein p is 1 、p 2 、p 3 、p 4 、p 5 、p 6 、p 7 Is determined as above q 1 -q 7 The specific numerical values thereof are not specifically limited in this application.
The server determines a third function according to the functional relationships and the corresponding formulas of the dielectric loss tangent values.
After each functional relation is obtained, a third function can be obtained according to a calculation formula of the dielectric loss tangent tan delta, and the specific formula of the third function is as follows:
tanδ＝f(ε s (T)，ε ∞ ，τ(T)，α(T)，β(T))
wherein tan delta is the dielectric loss tangent, T is the temperature, ε s Is static dielectric constant epsilon ∞ For the optical frequency dielectric constant, τ is the relaxation time, α is the first shape parameter, and β is the second shape parameter.
Finally, the server determines a binary function with the temperature as a dependent variable, the dielectric loss tangent value, and the frequency as independent variables as a second function according to the third function.
By the third function, an inverse function of the third function, that is, a second function, can be obtained, where the second function is:
T equal =f -1 (tanδ,ω)
wherein T is equal Is equivalent temperature.
S105, the server determines the equivalent temperature corresponding to each frequency point of the FDS curve to be corrected through a least square method according to the first function and the second function.
The FDS curve to be corrected is obtained by collecting and testing the oiled paper insulating sleeve by the FDS tester. The high-voltage end of the FDS tester is connected with a guide rod for testing the oilpaper insulating sleeve, and the low-voltage end of the FDS tester is connected with a tail screen for testing the oilpaper insulating sleeve.
In this embodiment of the present application, the determining, by the server according to the first function and the second function, the equivalent temperature corresponding to each frequency point of the FDS curve to be corrected by the least square method specifically includes:
first, the server determines an initial temperature at each time according to a first function.
The server may determine the temperature of the first function at a certain moment in the FDS curve to be corrected, and take the temperature obtained by the first function as the initial temperature. For example, the server may determine the temperature of the first function at time t1, when the FDS curve to be corrected is time t1, as the initial temperature.
Since the expression of the second function cannot be represented as an explicit expression and more data is known than the solving parameters, the present application solves for the second function in the following manner.
And the server calculates the temperature of the oil paper insulating sleeve at each moment by a least square method and a second function according to the initial temperature, and takes the temperature of each oil paper insulating sleeve as the equivalent temperature corresponding to each frequency point of the FDS curve to be corrected.
The FDS curve to be corrected is acquired by an FDS tester, the high-voltage end of which is connected with a guide rod of the test oilpaper insulating sleeve, and the low-voltage end of which is connected with the end screen of the test oilpaper insulating sleeve.
The server calculates the function value of the second function by using the least square method according to the initial temperature obtained by the first function, and takes the function value as the equivalent temperature. In the embodiment of the application, the least square method is a mathematical optimization technology, which finds the best function match of the data by minimizing the sum of squares of the errors. The unknown parameters of the H-N model can be easily obtained by using a least square method, and the square sum of errors between the parameters and actual data is minimized. However, the least square method is severely dependent on an initial value, and the selection of the initial value can greatly affect a final result, so that the temperature obtained by the first function is used as the initial temperature, the equivalent temperature is calculated, and the accuracy of the correction result of the FDS curve to be corrected can be ensured.
In one embodiment of the present application, the server may determine an equivalent temperature for each frequency point of the low frequency band of the FDS curve to be corrected.
Because the low frequency band of the FDS curve is easily affected by the time-varying temperature, the frequency point of the low frequency band can be corrected, and the processing efficiency of correcting the FDS curve to the constant temperature is improved.
S106, the server corrects the FDS curve to be corrected according to the equivalent temperatures and the preset mode.
In the embodiment of the present application, the preset manner is an Arrhenius formula, and the specific expression is as follows:
wherein f is the temperature T of the corrected FDS curve s Frequency at time f 0 At equivalent temperature T equal Frequency of FDS curve to be corrected, E a For activation energy, T s Is the corrected target temperature.
In this embodiment of the present application, after the server corrects the FDS curve to be corrected according to each equivalent temperature and the Arrhenius formula, the method further includes:
firstly, the server takes the FDS curve to be corrected after correction in a preset mode as a corrected FDS curve, and sends the corrected FDS curve to the verification terminal.
The authentication terminal may be a mobile phone, a tablet computer, or other devices of the user, which is not particularly limited in this application.
Then, the server determines whether the corrected FDS curve matches the comparison curve based on the comparison curve stored by the verification terminal.
The user can obtain the comparison curve from the verification terminal according to the correction FDS curve, and send the comparison curve to the server, or directly establish connection with the server, so that the server can calculate through the verification terminal to determine whether the correction FDS curve is matched with the comparison curve.
And finally, under the condition that the correction FDS curve is not matched with the comparison curve, the server rebuilds the two-dimensional axisymmetric model to re-fit the first function, so as to obtain an updated first function.
Under the condition of reconstructing the two-dimensional axisymmetric model, the structure and parameters of the test oilpaper insulating sleeve can be redetermined, the temperature distribution cloud image is redefined through simulation software, and then the first function is redetermined.
In another embodiment of the present application, in the case where the corrected FDS curve does not match the comparison curve, the server may obtain an FDS curve that updates the constant temperature to obtain more constant temperature FDS curves, and then recalculate to obtain the second function.
According to the technical scheme, after the FDS curve insulated by the oil paper is obtained, the FDS curve is corrected according to the heat dissipation temperature of the actual oil paper insulation, so that the accuracy of the FDS curve is ensured, and the accuracy of the oil paper insulation state assessment is ensured.
FIG. 5 is a schematic diagram of a device for calibrating an oil paper insulation frequency domain dielectric spectrum curve at a time-varying temperature, the device comprising:
at least one processor; and a memory communicatively coupled to the at least one processor. Wherein the memory stores instructions executable by the at least one processor, the instructions being executable by the at least one processor to enable the at least one processor to:
and constructing a two-dimensional axisymmetric model of the test oilpaper insulating sleeve. And determining each temperature distribution cloud picture corresponding to the two-dimensional axisymmetric model according to the two-dimensional axisymmetric model. The temperature distribution cloud image is a three-dimensional temperature distribution cloud image of heat dissipation of the two-dimensional axisymmetric model at different moments. And determining a corresponding first function of the two-dimensional axisymmetric model according to the temperature distribution cloud maps at different moments. And determining a second function according to the dielectric relaxation model and a plurality of preset constant temperature frequency domain dielectric spectrum FDS curves. Wherein the second function represents the correspondence of the FDS curve with temperature. And determining the equivalent temperature corresponding to each frequency point of the FDS curve to be corrected through a least square method according to the first function and the second function. The FDS curve to be corrected is obtained by collecting and testing the oilpaper insulating sleeve through the FDS tester. And correcting the FDS curve to be corrected according to each equivalent temperature and a preset mode.
In one embodiment of the present application, the at least one processor is further specifically capable of:
and carrying out grid division and finite element analysis on the two-dimensional axisymmetric model, and determining each temperature distribution cloud picture. The heat dissipation of the temperature distribution cloud image at least comprises the following steps: conductive heat dissipation, convective heat dissipation, radiative heat dissipation. According to each temperature distribution cloud picture at different moments, determining a corresponding first function of a two-dimensional axisymmetric model, specifically including: and determining the heat dissipation temperature of the capacitor core of the oiled paper insulating sleeve in each temperature distribution cloud picture. And generating a temperature change curve graph according to each heat dissipation temperature of the capacitor core. And fitting the curve in the temperature change curve graph to obtain a first function.
All embodiments in the application are described in a progressive manner, and identical and similar parts of all embodiments are mutually referred, so that each embodiment mainly describes differences from other embodiments. In particular, for the apparatus embodiments, since they are substantially similar to the method embodiments, the description is relatively simple, and reference is made to the description of the method embodiments in part.
The devices and the methods provided in the embodiments of the present application are in one-to-one correspondence, so that the devices also have similar beneficial technical effects as the corresponding methods, and since the beneficial technical effects of the methods have been described in detail above, the beneficial technical effects of the devices are not described here again.
It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article or apparatus that comprises the element.
The foregoing is merely exemplary of the present application and is not intended to limit the present application. Various modifications and changes may be made to the present application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc. which are within the spirit and principles of the present application are intended to be included within the scope of the claims of the present application.
Claims (5)
1. A method for correcting an oiled paper insulation frequency domain dielectric spectrum curve at a time-varying temperature, the method comprising:
constructing a two-dimensional axisymmetric model of the test oilpaper insulating sleeve;
according to the two-dimensional axisymmetric model, determining each temperature distribution cloud picture corresponding to the two-dimensional axisymmetric model; the temperature distribution cloud image is a three-dimensional temperature distribution cloud image of the two-dimensional axisymmetric model for radiating at different moments;
determining a corresponding first function of the two-dimensional axisymmetric model according to each temperature distribution cloud image at different moments;
determining a second function according to the dielectric relaxation model and a plurality of preset constant temperature frequency domain dielectric spectrum FDS curves; wherein the second function represents the correspondence between the FDS curve and the temperature;
according to the first function and the second function, determining the equivalent temperature corresponding to each frequency point of the FDS curve to be corrected by a least square method; the FDS curve to be corrected is obtained by collecting the test oilpaper insulating sleeve through an FDS tester;
correcting the FDS curve to be corrected according to the equivalent temperatures and a preset mode;
wherein, according to the dielectric relaxation model and a plurality of preset constant temperature frequency domain dielectric spectrum FDS curves, determining the second function specifically comprises:
according to the dielectric relaxation model, taking a first shape parameter and a second shape parameter which are related to a static dielectric constant, an optical frequency dielectric constant, a relaxation time and a relaxation time distribution as particle parameters;
according to a preset particle swarm optimization algorithm and each constant-temperature FDS curve, carrying out iterative calculation on each particle to obtain parameter values of each particle parameter at different temperatures; wherein the different temperatures are constant temperature temperatures corresponding to the constant temperature FDS curves;
determining a third function according to the parameter value of each particle parameter; wherein the third function represents a correspondence between dielectric loss tangent and temperature;
determining a binary function taking the temperature as a dependent variable and the dielectric loss tangent and the frequency as independent variables as the second function according to the third function;
wherein, according to the parameter value of each particle parameter, determining a third function specifically includes:
determining the corresponding parameter values of the constant temperature;
according to the parameter values corresponding to the constant temperature, determining the functional relation between each temperature and each parameter value through cubic spline interpolation;
determining the third function according to the functional relationships and the corresponding formulas of the dielectric loss tangent values;
wherein the first function is:
T′＝ae -mt +be -nt
wherein T' is the real-time temperature, a is a first fitting coefficient, b is a second fitting coefficient, m is a first fitting index, n is a second fitting index, and T is time;
wherein the third function is:
tanδ＝f(ε s (T),ε ∞ ,τ(T),α(T),β(T))
wherein tan delta is the dielectric loss tangent, T is the temperature, ε s Epsilon for the static dielectric constant ∞ For the optical frequency dielectric constant, τ is the relaxation time, α is the first shape parameter, and β is the second shape parameter.
2. The method according to claim 1, wherein determining each temperature distribution cloud image corresponding to the two-dimensional axisymmetric model according to the two-dimensional axisymmetric model specifically comprises:
performing grid division and finite element analysis on the two-dimensional axisymmetric model, and determining each temperature distribution cloud picture; the heat dissipation of the temperature distribution cloud image at least comprises the following steps: conduction heat dissipation, convection heat dissipation and radiation heat dissipation;
according to each temperature distribution cloud image at different moments, determining a corresponding first function of the two-dimensional axisymmetric model, wherein the first function specifically comprises the following steps:
determining the heat dissipation temperature of a capacitor core of the oiled paper insulating sleeve in each temperature distribution cloud picture;
generating a temperature change curve graph according to each heat dissipation temperature of the capacitor core;
and fitting the curve in the temperature change curve graph to obtain the first function.
3. The method according to claim 1, wherein determining, by a least square method, an equivalent temperature corresponding to each frequency point of the FDS curve to be corrected according to the first function and the second function, specifically includes:
determining the initial temperature at each moment according to the first function;
according to the initial temperature, calculating the temperature of the oil paper insulating sleeve at each moment by the least square method and the second function, and taking the temperature of the oil paper insulating sleeve as the equivalent temperature corresponding to each frequency point of the FDS curve to be corrected; the FDS curve to be corrected is acquired by the FDS tester, the high-voltage end of the FDS curve is connected with the guide rod of the test oilpaper insulating sleeve, and the low-voltage end of the FDS curve is connected with the end screen of the test oilpaper insulating sleeve.
4. The method of claim 1, wherein after correcting the FDS curve to be corrected according to each of the equivalent temperatures and a preset manner, the method further comprises:
taking the FDS curve to be corrected in the preset mode as a corrected FDS curve, and sending the corrected FDS curve to a verification terminal; wherein the preset mode is an Arrhenius formula;
determining whether the corrected FDS curve is matched with the comparison curve based on the comparison curve stored by the verification terminal;
and under the condition that the correction FDS curve is not matched with the comparison curve, reconstructing the two-dimensional axisymmetric model to re-fit the first function, and obtaining the updated first function.
5. An oilpaper insulation frequency domain dielectric spectrum curve correction device at a time-varying temperature, the device comprising:
at least one processor; the method comprises the steps of,
a memory communicatively coupled to the at least one processor; wherein,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform a time-varying temperature oiled paper insulation frequency-domain dielectric spectrum curve correction method as set forth in any one of claims 1-4.
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| CA3006890A1 (en) * | 2015-12-01 | 2017-06-08 | General Electric Technology Gmbh | An intelligent assessment method of main insulation condition of transformer oil paper insulation |
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