CN114429069A - Modeling and fault early warning method and modeling and fault early warning system of dry reactor - Google Patents
Modeling and fault early warning method and modeling and fault early warning system of dry reactor Download PDFInfo
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Abstract
The invention provides a modeling and fault early warning method and a modeling and fault early warning system of a dry reactor, wherein the modeling and fault early warning method comprises the following steps: establishing an electromagnetic-circuit two-dimensional analysis model of the dry reactor by adopting Maxwell, wherein the model comprises a finite element magnetic field model and a circuit model, and calculating by the model to obtain the encapsulation loss; calculating the temperature field and flow field distribution of the reactor by taking the encapsulation loss as a heat source of the three-dimensional fluid-temperature field, and fusing a multi-physical field model by adopting a cyclic iteration algorithm to establish a three-dimensional fluid-temperature field finite element model; then, reducing the order of the three-dimensional fluid-temperature field finite element model by adopting a fusion algorithm of a PSO-SVM; and simulating multiple turn-to-turn short circuit faults on the basis of the model establishment to realize the identification and early warning judgment of the faults. The modeling and fault early warning method improves the accuracy of early warning, and can be widely applied to the field of design and early warning of dry-type reactor equipment.
Description
Technical Field
The invention relates to the field of dry reactor modeling and fault early warning methods based on a multi-physics coupling technology, in particular to a modeling and fault early warning method and a modeling and fault early warning system of a dry reactor.
Background
The dry-type reactor is used as a main auxiliary device of a long-distance alternating current transmission system, plays roles in compensating capacitive current, maintaining system voltage level, improving line transmission capability and the like in the system, and promotes the development of a power grid to a certain extent. The dry-type air reactor has a plurality of excellent performances and is widely applied at present, however, due to long-term operation, the dry-type air reactor is difficult to avoid various problems, and more serious, the dry-type air reactor can cause fire and burn out, so that the reactor can not work normally, and great threat is caused to the safety of a power grid. In addition, since the hot spot temperature of the reactor is directly related to the service life of the reactor, accurate calculation of the temperature field distribution of the dry reactor plays an important role for designers and field operation and maintenance personnel.
At present, most researchers at home and abroad research the temperature field of the dry-type reactor, and the study mainly includes an average temperature rise calculation method, a convection heat transfer coefficient giving method and a fluid temperature field coupling method. The average temperature rise cannot reflect the temperature rise distribution conditions of different positions of the reactor, and most of the average temperature rise is used for testing the thermal performance of the reactor in engineering. The finite element method is utilized, different convection heat transfer coefficients are given to the surface of the reactor, the temperature change of the reactor on the height of the winding is also the current common method, but the method still depends on an empirical formula for determining the convection heat transfer coefficients.
In addition, the current research also utilizes a multi-field coupling finite element theory to establish an example of a three-dimensional reactor flow field-temperature field calculation model, but the model is not fused with a magnetic circuit model, simplification and order reduction are not carried out, and the calculation complexity is high. In addition, the research of the dry-type reactor fault early warning system based on the multi-physical field coupling model is rarely reported.
In view of the above, the present invention is particularly proposed.
Disclosure of Invention
In view of the above, the invention discloses a modeling and fault early warning method for dry reactor equipment and a modeling and fault early warning system corresponding to the modeling and fault early warning method, wherein an electromagnetic-circuit two-dimensional analysis model of a dry reactor is established by adopting Maxwell, a three-dimensional fluid-temperature field finite element model is established for the dry reactor by adopting COMSOL finite element simulation software, multi-field fusion is carried out by applying a joint simulation technology, and a reduced order processing method based on an improved particle swarm optimization support vector machine temperature field model is introduced aiming at the problem of model simplification. Finally, based on the model, a dry-type reactor turn-to-turn short circuit fault early warning method based on variable fitting is provided to achieve early warning and alarming of turn-to-turn short circuit faults, the whole method improves early warning accuracy, and can be widely applied to the fields of design, early warning, fault diagnosis direction and the like of dry-type reactor equipment.
Specifically, the invention is realized by the following technical scheme:
in a first aspect, the invention discloses a modeling and fault early warning method for a dry reactor, which comprises the following steps:
establishing an electromagnetic-circuit two-dimensional analysis model of the dry reactor by adopting Maxwell, wherein the model comprises a finite element magnetic field model and a circuit model, and calculating by the model to obtain the encapsulation loss;
calculating the temperature field and flow field distribution of the reactor by taking the encapsulation loss as a heat source of the three-dimensional fluid-temperature field, and fusing a multi-physical field model by adopting a cyclic iteration algorithm to establish a three-dimensional fluid-temperature field finite element model;
then, reducing the order of the three-dimensional fluid-temperature field finite element model by adopting a fusion algorithm of a PSO-SVM;
and simulating multiple turn-to-turn short circuit faults on the basis of the model establishment to realize the identification and early warning judgment of the faults.
In a second aspect, the present invention discloses a modeling and fault early warning system for a dry reactor device, comprising:
establishing a two-dimensional analysis model module: the method comprises the steps that an electromagnetic-circuit two-dimensional analysis model of the dry type reactor is built by adopting Maxwell, the model comprises a finite element magnetic field model and a circuit model, and the encapsulation loss is obtained through calculation of the model;
establishing a three-dimensional analysis model module: the system comprises a reactor, a three-dimensional fluid-temperature field, a circulating iterative algorithm, a multi-physical field model fusion and a three-dimensional fluid-temperature field finite element model, wherein the reactor is used for calculating the temperature field and flow field distribution of the reactor by taking the encapsulation loss as a heat source of the three-dimensional fluid-temperature field;
a reduced order analysis module: the method is used for reducing the three-dimensional fluid-temperature field finite element model by adopting a fusion algorithm of a PSO-SVM;
a fault analysis module: the method is used for simulating multiple turn-to-turn short circuit faults on the basis of the model establishment to realize the identification and early warning judgment of the faults.
In a third aspect, the present invention discloses a computer readable storage medium having stored thereon a computer program which, when being executed by a processor, carries out the steps of the modeling and fault pre-warning method according to the first aspect.
In a fourth aspect, the present invention discloses a computer device, comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor executes the program to implement the steps of the modeling and fault pre-warning method according to the first aspect.
In a word, the scheme of the invention adopts Maxwell to establish a magnetic circuit analysis model of the dry-type reactor, obtains the encapsulation loss through model calculation, and calculates the temperature field and the flow field distribution of the reactor by taking the encapsulation loss as a heat source of a three-dimensional fluid-temperature field; and further establishing a three-dimensional fluid-temperature field finite element model for the dry reactor by using COMSOL finite element simulation software, and performing multi-field coupling joint simulation.
Although the multi-physical-field coupling model in the prior art can realize the characteristic description of the dry-type reactor equipment, the multi-physical-field coupling model is complex in structure and slow in calculation, and cannot meet the requirement of system real-time performance. Aiming at the problems that the temperature field calculation process is complex and does not have real-time performance, a proxy model method for improving a particle swarm optimization support vector machine (PSO-SVM) is introduced to reduce the order of a temperature field model in order to ensure the calculation accuracy of multiple physical fields, meet the calculation speed and fully consider the influences of heat transfer and heat dissipation of a reactor; and finally, completing the modeling of the dry reactor based on the multi-physical field coupling. And then, based on the model, a turn-to-turn short circuit fault early warning method for the dry type reactor is provided. Firstly, setting the faults of different degrees of turn-to-turn short circuit at different points of a simulation model; secondly, performing simulation analysis on the distribution of the space magnetic field along the central axial lead and the central transverse lead to obtain the relationship between the turn-to-turn short circuit fault and the space magnetic field; and finally, establishing a fault degree early warning function by taking the magnetic field variation of the observation point and the fault degree as fitting variables respectively and verifying the fault degree early warning function. The result shows that the absolute error between the result of the simulation function and the actual value is very small, and the relative error is in the allowable error range, so that the effectiveness of the method for early warning the fault is proved.
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Various other advantages and benefits will become apparent to those of ordinary skill in the art upon reading the following detailed description of the preferred embodiments. The drawings are only for purposes of illustrating the preferred embodiments and are not to be construed as limiting the invention. Also, like reference numerals are used to refer to like parts throughout the drawings. In the drawings:
FIG. 1 is a general block diagram of a dry reactor modeling algorithm based on a multi-physical field coupling technology;
FIG. 2 is a flow diagram of a multi-physics fusion process;
FIG. 3 is a flow chart of an improved PSO optimization SVM;
FIG. 4 is a basic structural view of a reactor;
FIG. 5 is a coupling diagram of an electromagnetic-circuit analysis model of the dry-type air-core reactor;
(a) a two-dimensional finite element model (b) external constraint circuit;
FIG. 6 magnetic field distribution diagram for reactor model simulation;
(a) an upper magnetic field distribution pattern (b) a lower magnetic field distribution pattern;
FIG. 7 is a temperature field distribution diagram after a dry-type air-core reactor is in a steady state;
FIG. 8 is a flow velocity distribution diagram of an air flow field around a dry air reactor;
FIG. 9 is an index plot of the predicted results of the improved PSO-SVM;
(a) mean square error index map (b) a square error index map;
FIG. 10 is a graph of the improved PSO-SVM proxy model response surface;
FIG. 11 is a diagram of the magnetic field distribution along the ATC direction and the early warning change of the fault degree;
(a) mean square error index map (b) a square error index map;
FIG. 12 is a graph of magnetic field distribution along the LTC direction versus the degree of failure early warning variation;
(a)s＝0.28％(b)s＝16.78％(c)s＝33.29％；
FIG. 13 fault level function fitting curve;
(a)s＝0.28％(b)s＝16.78％(c)s＝33.29％；
(a) c point fitting curve (b) E point fitting curve;
FIG. 14 is a schematic structural diagram of a prediction system according to an embodiment of the present invention;
fig. 15 is a flowchart of a computer device according to an embodiment of the present invention.
Detailed Description
Reference will now be made in detail to the exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, like numbers in different drawings represent the same or similar elements unless otherwise indicated. The implementations described in the exemplary embodiments below do not represent all implementations consistent with the present disclosure. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the present disclosure, as detailed in the appended claims.
The terminology used in the disclosure is for the purpose of describing particular embodiments only and is not intended to be limiting of the disclosure. As used in this disclosure and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It should also be understood that the term-and/or, as used herein, refers to and encompasses any and all possible combinations of one or more of the associated listed items.
It is to be understood that although the terms first, second, third, etc. may be used herein to describe various information, such information should not be limited to these terms. These terms are only used to distinguish one type of information from another. For example, first information may also be referred to as second information, and similarly, second information may also be referred to as first information, without departing from the scope of the present disclosure. Depending on context, the word as used herein-if "can be interpreted as being-at … …" or-when … … "or-in response to a determination".
The invention discloses a modeling and fault early warning method of a dry type reactor based on a multi-physical field coupling technology, which comprises the following steps:
establishing an electromagnetic-circuit two-dimensional analysis model of the dry reactor by adopting Maxwell, wherein the model comprises a finite element magnetic field model and a circuit model, and calculating by the model to obtain the encapsulation loss;
taking the encapsulation loss as a heat source of the three-dimensional fluid-temperature field to calculate the temperature field and flow field distribution of the reactor, and performing multi-physical field model fusion by adopting a cyclic iteration algorithm to establish a three-dimensional fluid-temperature field finite element model;
then, reducing the order of the three-dimensional fluid-temperature field finite element model by adopting a fusion algorithm of a PSO-SVM;
and simulating multiple turn-to-turn short circuit faults on the basis of the model establishment to realize the identification and early warning judgment of the faults.
Fig. 1 is a general operation algorithm diagram of a modeling and fault early warning method disclosed in an embodiment of the present invention, which is shown in fig. 1 and specifically performed according to the following steps:
A. modeling a two-dimensional electromagnetic-circuit model:
the method comprises the steps of establishing an electromagnetic-circuit two-dimensional analysis model of the dry type reactor by adopting Maxwell, wherein the model comprises a finite element magnetic field model and a circuit model, the dry type reactor is generally symmetrical about a central shaft, and therefore a two-dimensional finite element model comprising air, an insulating medium and a coil can be established according to the actual size of the dry type reactor. And designing a dry-type reactor model by using finite element electromagnetic analysis software Maxwell. And determining a solution domain according to the requirement of high computational efficiency and the combination of the magnetic field distribution characteristics to determine and select 1/12 circumferences of the two-dimensional model for representation. Since the triangular mesh generation has the advantage of fine smoothness for the description of the two-dimensional model, meshes of the type are adopted when each part of the dry-type reactor is generated. Meanwhile, in order to avoid the influence of the error of each discrete unit on the calculation precision during calculation, the grid density is not suitable to be too large. And connecting equivalent circuits of the coils of all layers in parallel, applying independent voltage sources to form a circuit model, and coupling the equivalent circuits of the coils with corresponding coil units respectively to obtain an electromagnetic-circuit analysis model. Further, the encapsulation loss is calculated through the analysis model by using a formula (1), and the encapsulation loss is used as a heat source of the three-dimensional fluid-temperature field to calculate the temperature field and the flow field distribution of the reactor.
Wherein, PjThe j-th layer loss of the winding mainly comprises resistive loss PajAnd eddy current loss PbjAnd gamma is the conductivity of the aluminum wire; ω is the angular frequency of the applied excitation; djThe wire diameter of the jth turn of wire; 1jIs the radius of each turn of wire；BjThe magnetic induction intensity at the center of the j turn of the wire.
B. Three-dimensional fluid-temperature field model modeling
According to the invention, COMSOL finite element simulation software is adopted to establish a three-dimensional fluid-temperature field finite element model for the dry-type reactor, and numerical boundary conditions of the model are established by analyzing the structural characteristics and the heat dissipation characteristics of the dry-type reactor.
(1) Calculation theory model
Firstly, the dry reactor is mostly in a natural convection cooling mode, the heat exchange between the reactor and air meets the basic equation of heat transfer science, and the air flow and the heat transfer follow the law of physical conservation, namely conservation of mass, momentum and energy. Under the condition of natural convection, the air around the dry-type air-core reactor is regarded as incompressible fluid, and the general control equation of the steady-state fluid under the rectangular coordinate is as follows:
where ρ is the fluid density; u is a fluid flow velocity vector;
is a fluid universal variable;
is a generalized diffusion coefficient;
is a generalized source term.
Based on the basic law of heat transfer science, the steady-state three-dimensional temperature field equation and the boundary condition of the dry-type reactor are shown in formula (3):
in the formula, Ts, TfSolid and fluid thermodynamic temperatures, respectively; lambda [ alpha ]x、λy、λzIs otherwise a solidThe thermal conductivity of the domain material in the directions of an x axis, a y axis and a z axis; q is the sum of the bulk heat source densities of the solution domain; gamma-shaped1Is a type 1 boundary condition; t isWA known wall temperature; gamma-shaped2Is a type 2 boundary condition; lambda [ alpha ]nIs a boundary gamma2Normal thermal conductivity of (d); q. q.s0A heat flux density of a boundary; gamma-shaped3Is a type 3 boundary condition; h is the convective heat transfer coefficient of the solid surface.
(2) Finite element model building
When a three-dimensional fluid-temperature field coupling calculation model is established, the following assumptions are made for the model:
1) the calculation model has axial symmetry, and the symmetric surfaces of the envelope, the rain cover and the star-shaped support can be regarded as heat insulation surfaces.
2) The temperature difference between the envelopes is small, the radiation heat transfer specific gravity is small, and the heat exchange in the reactor is mainly convection and conduction. Convection and radiation are considered in heat transfer between the outer surface of the rain cover and external cooling air, and the surface emissivity of the rain cover is 0.9. 3) The encapsulation is regarded as a material homogeneous whole, and the rain cover and the star-shaped bracket are regarded as linear materials, without considering the nonlinear relation between the material parameters and the temperature. 4) And the air domain of the calculation model is air among the reactor rain cover, the outermost layer envelope and the lower star-shaped support.
The boundary conditions of the finite-element model should, in addition to satisfying governing equation (2), also satisfy:
1) at the computation domain boundary Γ1Reactor solid and air interface Γ3Upper specification of a no slip boundary condition, i.e. Vx＝Vy＝VzThe surface emissivity was 0.9. 2) At the computation domain boundary Γ1The upper specified constant temperature boundary condition, i.e., T | Γ 1 ═ T0The ambient temperature around the reactor was set to 293.15K. 3) The acceleration of gravity was set to 9.81m/s2, the direction being the negative of the z-axis. 4) The heat source within the winding envelope is determined by the winding losses calculated from the electromagnetic field.
C. Multi-physics model fusion
The method for fusing the coupling of the dry reactor and the multiple physical fields adopts a cyclic iteration algorithm of load transfer until the convergence condition is met: because the resistivity of the conductor is related to the temperature, a two-dimensional magnetic circuit-a constraint condition of a circuit analysis model-is firstly established, the current and the loss in each envelop of the reactor at the initial temperature are calculated in an electromagnetic field, boundary conditions are applied, magnetic field analysis is carried out, and the current and the loss of each winding are calculated in a simulation manner; and finally, judging whether a convergence condition is reached, comparing the temperature difference value of two adjacent times with the temperature difference value smaller than a set value or reaching the cycle times, and stopping iteration if the convergence condition is reached to finish the multi-physical field fusion process. The whole fusion process is shown in FIG. 2.
D. Model order reduction for improved PSO-SVM
The fluid-temperature field model calculation by using the finite element method is more accurate and intuitive, but has the defects of complex construction process and slow calculation.
In order to solve the problem that a high-order complex model can meet the requirement of real-time performance while ensuring the calculation accuracy of multiple physical fields, the invention introduces a PSO-SVM fusion algorithm to realize model reduction, and the algorithm has the advantages of PSO optimization accuracy and SVM small sample prediction. However, the PSO algorithm is prone to fall into a locally optimal solution, resulting in a local convergence problem. Therefore, the invention provides an improved algorithm, namely, an information entropy is combined with a variation strategy in differential variation to solve the problem, and the improved algorithm can effectively overcome the defect that the population diversity of the PSO algorithm is rapidly reduced in later iteration. The improved PSO optimization process is shown in FIG. 3.
As can be seen from fig. 3, after the information entropy is introduced, the population can automatically determine whether differential variation is required or not by calculating the information entropy of the population and comparing the calculated information entropy with a set threshold, so that repeated variation of the population is avoided, and the particle swarm algorithm is guaranteed to fall into a local optimal solution while the calculation efficiency is improved. Wherein the information entropy is expressed by mathematical expression
In which U is a source symbol, piThe probabilities corresponding to different source symbols. After the mutation is determined, a DE/best/1/bin mutation strategy is adopted in the early stage of iteration, and a DE/rand/1/bin strategy is adopted in the later stage of iteration, so that the algorithm can focus on global search in the early stage and focus on local refined search in the later stage. In addition, the improvement also makes corrections to the inertial weight factor ω, since c1A change from 2.05 to 0.5 has a relatively good effect, and c2The effect is better from 0.5 to 2.05, and the inertia weight coefficient is corrected by adopting a self-adaptive formula.
The specific correction formula is as follows:
in the formula: c. C1maxAnd c2maxAre all 2.05, c1minAnd c2minAre all 0.5; t is the current iteration number; t is tmaxIs the maximum iteration number; omegamaxIs the maximum inertia weight factor, ωminIs the minimum inertial weight factor.
In addition, most of the traditional agent models are oriented to structural optimization design, most of input variables are structural parameters, and the agent models constructed based on the parameters can improve the optimization design speed but cannot be fused with data calculated by the system model. Therefore, in the invention, the current and the loss of the reactor are used as input parameters, the turn-to-turn short circuit fault of dry type reactor equipment which is easy to fail is used as a research object, and the average temperature of the winding is selected as a predicted value. When the whole model is started, the proxy reduced-order model can predict the target value according to the dry-type reactor operation parameters and the actual working conditions calculated by the joint simulation.
E. Variable fitting dry-type reactor turn-to-turn short circuit fault early warning
The problems that the experimental data are difficult to measure and certain economic loss is caused when the experimental fault test is carried out on the dry-type reactor entity exist, so that the destructive test on the entity can be effectively avoided by carrying out multiple turn-to-turn short circuit fault simulation on the multi-physical-field coupling model, the economic loss is reduced, and more complete fault data types and early warning grade division are obtained.
And setting turn-to-turn short circuit faults of different degrees at different positions of the multi-physical-field coupling model, adding fault current excitation into the fault model, and analyzing the spatial distribution condition of the magnetic field along the direction of a central axial lead (ATC) and the direction of a central transverse Lead (LTC) under different faults. When a turn-to-turn short circuit fault occurs in the k-layer coil, the turn-to-turn short circuit fault degree s is defined as follows:
s＝hs/Hk*100％ (6)
in the formula, HkIs the height of the kth coil, and hs is the height of the shorting ring. Because turn-to-turn short circuit faults are gradually developed from simple faults, the value range of s is generally 0-35%.
Percent change in magnetic field
Is defined as follows:
B0and BsRespectively representing the magnetic field intensity at the same point in normal operation and inter-turn fault operation.
In order to quantitatively describe the relationship between the fault degree and the magnetic field change, the magnetic field change amount and the fault degree of an observation point are respectively used as fitting variables to establish a fitting function. When a fault occurs, the fault degree s is set as an independent variable, and the magnetic field variation is set
Set as a dependent variable. Simplifying the fault degree early warning function into solving
And s is a fitted function of the degree of failure of the function to the rate of magnetic change, as shown in the following equation:
wherein the distance in the ATC direction is dADistance in LTC direction, take dLAnd simulating a curve fitting function of the magnetic field change and the fault degree of different measuring points, wherein A, B, C, D is a coefficient to be fitted.
And finally, realizing the identification and early warning judgment of the fault through the fault degree early warning function.
The multi-physical-field coupling fusion method adopts a load transfer loop iteration algorithm until a convergence condition is met. Firstly, establishing constraint conditions (encapsulation initial current and loss setting) of a two-dimensional magnetic circuit analysis model, applying boundary conditions, carrying out magnetic field analysis, and carrying out simulation calculation on the current and the loss of each winding; reading winding loss, transmitting the winding loss to a three-dimensional fluid-temperature field model, applying load and flow field temperature field boundary conditions, then performing three-dimensional fluid-temperature field finite element model simulation to obtain temperature field distribution and encapsulation temperature, finally judging whether convergence conditions are reached (the temperature difference value between two adjacent times is smaller than a set value or reaches cycle times), stopping iteration when the conditions are reached, and completing multi-field fusion.
A specific practical case is given below for a specific scenario:
A. two-dimensional electromagnetic-circuit model modeling
In the embodiment of the invention, a 35-volt dry-type air-core reactor is taken as an example for algorithm description. The main parameters of the reactor used are shown in table 1 below. The upper end and the lower end of the reactor are respectively provided with a star-shaped support which is used as an inlet and outlet line confluence and provides mechanical clamping force for encapsulation. A plurality of fine polyester supporting strips are arranged between the reactor packages in the radial direction, and air passages among the supporting strips form heat dissipation channels among the packages. The winding in the encapsulation adopts a plurality of layers of parallel coils, each layer of coil is formed by winding a plurality of strands of round aluminum wires in parallel, the surface of each turn of coil is wound with a polyester film and non-woven fabrics impregnated with epoxy glue, and the insulation material on the encapsulation surface is glass fiber reinforced epoxy resin. The basic structure is shown in fig. 4.
TABLE 1 Main parameters of Dry reactor
And introducing Maxwell according to the actual model and size of the dry-type reactor, and establishing a two-dimensional finite element model comprising air, an insulating medium and a coil, as shown in FIG. 5 (a). Further, the equivalent circuits of the coils of each layer are connected in parallel, an independent voltage source is applied to form a circuit model, and as shown in fig. 5(b), the equivalent circuits of the coils are respectively coupled with the corresponding coil units to obtain an electromagnetic-circuit analysis model. Fig. 5(b) is a schematic diagram of an external constraint circuit of the reactor, Rn is the resistance of the nth coil, Wn is a finite element module of the nth coil, and the wires in the coil layers are tightly wound and can be equivalent to the two-dimensional rectangle in fig. 5 (a). The magnetic field of the dry-type air-core reactor during operation is simulated and calculated according to the model established in fig. 5, and the obtained reactor magnetic field distribution diagrams are shown in fig. 6(a) and (b).
And then, calculating by using the analysis model and a formula (1) to obtain the encapsulation loss, and calculating the temperature field and the flow field distribution of the reactor by using the encapsulation loss as a heat source of the three-dimensional fluid-temperature field.
B. Three-dimensional fluid-temperature field model modeling
And (3) establishing a three-dimensional fluid-temperature field finite element model for the dry-type air reactor by adopting COMSOL finite element simulation software. After grid division and boundary condition application, the temperature field distribution graph after the steady state is solved is shown in figure 7, and the air flow field flow velocity distribution graph around the reactor is shown in figure 8. It can be known from the figure that the temperature of the reactor encapsulation is in a descending trend from top to bottom, the bottom air absorbs the heat at the bottom of the encapsulation and then accelerates to rise under the action of natural convection to enter the air duct at a higher speed, the convection and heat dissipation effect of the air after entering is weakened, and the speed is accelerated to a certain value and then starts to be stable.
C. Multi-physics model fusion
The method adopts a load transfer loop iteration algorithm to perform fusion of multiple physical coupling fields of the dry reactor: and setting the iteration times k to be 100, setting the percentage setting value of the temperature difference between two adjacent times to be 5%, and finishing the multi-physical-field fusion process.
D. Model order reduction for improved PSO-SVM
The average winding temperature is used as one of key indexes for measuring the working state of the reactor, and the temperature rise trend of the reactor can intuitively reflect the running condition of equipment, so that the average winding temperature is used as an output variable in the invention. The current and the loss of the reactor are used as input parameters. In order to verify and improve the prediction accuracy of a PSO-SVM surrogate model, simulation deduction is carried out under different working conditions based on a multi-physical-field model and by combining operating condition parameters of a dry-type air reactor, 90 groups of data capable of effectively reflecting input and output relation characteristics are obtained, 75 groups of data are selected as reduced-order model training data, 15 groups of data are selected as test data, the constructed reduced-order model is tested, and the error analysis mode adopts Mean Square Error (MSE) and variance R2The form of (1) is judged, the more the MSE is close to 0, R2The closer to 1.0, the higher the accuracy, the better the order reduction effect. The test results are shown in fig. 9.
It can be seen from the figure that the predicted value of the average temperature of the winding is very close to the calculated value of the model. MSE was 0.0021101, R in the training set results2Is 0.994; MSE in test set results was 8.783e-5, R2Is 0.99977. Therefore, the reduced order model established by the invention has higher confidence. And finally, selecting a proper kernel function for the trained reduced model, solving SVM coefficients, constructing a corresponding regression function, and constructing a response surface of the input and output relation according to the regression function. The form of the response surface of the improved PSO-SVM reduced order model is shown in fig. 10.
E. Variable fitting dry-type reactor turn-to-turn short circuit fault early warning
In this example, as can be known from a multi-physics field coupling model of the dry-type air-core reactor, the magnetic field intensity near the third envelope in the radial direction is close to 0, and the magnetic field intensity in the axial direction is smaller as the distance from the central point is larger, so the dry-type reactor is generally selected as a fault location point at the center of the third envelope, and a point C (1 meter along the ATC center) and a point E (3 meters along the LTC center) are selected as measurement points, and three fault degrees are set: the fault degrees corresponding to the light fault, the medium fault and the heavy fault are 0.28%, 16.78% and 33.29%, respectively. When the reactor has a fault at the same position, the change of the magnetic field is increased along with the increase of the fault degree; at the same fault level, the fault of the innermost coil has the greatest influence on the magnetic field, while the fault of the outermost coil has the least influence on the magnetic field. Graphs of the magnetic field change curves at the occurrence of a fault along the ATC and LTC are shown in fig. 11 and 12, respectively, where 1/3 defining the upper part of the reactor is-upper part, 1/3 in the middle part of the reactor is-middle part, 1/3 in the bottom part of the reactor is-bottom part, distance dA in the ATC direction and distance dL in the LTC direction are taken.
As can be seen from fig. 11, the maxima on the curve of the variation of the magnetic field in the ATC direction for all three fault degrees occur approximately at dA-0.25 m, when dA is larger than 1m, the variation of the magnetic field for reactor-middle "is larger than 0, the variation of the magnetic field for-upper" and-lower "is smaller than 0, and the variation of the magnetic field for-upper" is smaller than the variation of the magnetic field for-lower ". As shown in fig. 12, when s is 0.28%, the magnetic field variation of the near inner wall (dL 1m) of the dry air-core reactor is larger than that of the outer wall (dL 3m) along the variation curve of the magnetic field in the LTC direction. The difference in the amount of change of the inner and outer walls gradually decreases as the degree of failure increases. Under the two fault degrees of s-16.78% and s-33.29%, the magnetic field change of the near inner wall is smaller than that of the end outer wall, and the change trends of the magnetic fields at the two ends are basically consistent. When the reactor has a fault at the same position, the change of the magnetic field is increased along with the increase of the fault degree; at the same degree of failure, the magnetic field is most affected by the failure of the innermost coil, while the magnetic field is least affected by the failure of the outermost coil.
From the above analysis we obtain the relationship between turn-to-turn short fault and space magnetic field. Solving a fitting function of the fault degree and the magnetic change rate according to the formula (8) to obtain the following formula:
a curve fit of the magnetic field variation to the degree of failure was simulated for points C and E, as shown in fig. 13. The result of the fitting error is verified as shown in table 2, and it can be known from table 2 that the absolute error between the S early warning level calculated by the fault function and the actual S early warning level is less than 1, and the relative error is within the allowable error range (0-10%), so that the accuracy of the fault degree early warning function is verified, and a theoretical basis is provided for detecting turn-to-turn short circuit faults.
TABLE 2 fitting error results
As shown in fig. 14, the present invention further provides a modeling and fault early warning system of the modeling and fault early warning method, including:
establishing a two-dimensional analysis model module 101: the method comprises the steps that an electromagnetic-circuit two-dimensional analysis model of the dry type reactor is built by adopting Maxwell, the model comprises a finite element magnetic field model and a circuit model, and the encapsulation loss is obtained through calculation of the model;
the three-dimensional analysis model building module 102: the system comprises a reactor, a three-dimensional fluid-temperature field, a circulating iterative algorithm, a multi-physical field model fusion and a three-dimensional fluid-temperature field finite element model, wherein the reactor is used for calculating the temperature field and flow field distribution of the reactor by taking the encapsulation loss as a heat source of the three-dimensional fluid-temperature field;
reduced order analysis module 103: the method is used for reducing the three-dimensional fluid-temperature field finite element model by adopting a fusion algorithm of a PSO-SVM;
the fault analysis module 104: the method is used for simulating multiple turn-to-turn short circuit faults on the basis of the model establishment to realize the identification and early warning judgment of the faults.
Fig. 15 is a schematic structural diagram of a computer device disclosed in the present invention. Referring to fig. 15, the computer device 400 includes at least a memory 402 and a processor 401; the memory 402 is connected to the processor through a communication bus 403 for storing computer instructions executable by the processor 401, and the processor 301 is configured to read the computer instructions from the memory 402 to implement the steps of the modeling and fault warning method according to any of the above embodiments.
Computer-readable media suitable for storing computer program instructions and data include all forms of non-volatile memory, media and memory devices, including by way of example semiconductor memory devices (e.g., EPROM, EEPROM, and flash memory devices), magnetic disks (e.g., internal magnetic disks or removable disks), magneto-optical disks, and CD ROM and DVD-ROM disks. The processor and the memory can be supplemented by, or incorporated in, special purpose logic circuitry.
Finally, it should be noted that: while this specification contains many specific implementation details, these should not be construed as limitations on the scope of any invention or of what may be claimed, but rather as descriptions of features specific to particular embodiments of particular inventions. Certain features that are described in this specification in the context of separate embodiments can also be implemented in combination in a single embodiment. In other instances, features described in connection with one embodiment may be implemented as discrete components or in any suitable subcombination. Moreover, although features may be described above as acting in certain combinations and even initially claimed as such, one or more features from a claimed combination can in some cases be excised from the combination, and the claimed combination may be directed to a subcombination or variation of a subcombination.
Similarly, while operations are depicted in the drawings in a particular order, this should not be understood as requiring that such operations be performed in the particular order shown or in sequential order, or that all illustrated operations be performed, to achieve desirable results. In some cases, multitasking and parallel processing may be advantageous. Moreover, the separation of various system modules and components in the embodiments described above should not be understood as requiring such separation in all embodiments, and it should be understood that the described program components and systems can generally be integrated together in a single software product or packaged into multiple software products.
Thus, particular embodiments of the subject matter have been described. Other embodiments are within the scope of the following claims. In some cases, the actions recited in the claims can be performed in a different order and still achieve desirable results. Further, the processes depicted in the accompanying figures do not necessarily require the particular order shown, or sequential order, to achieve desirable results. In some implementations, multitasking and parallel processing may be advantageous.
The above description is only exemplary of the present disclosure and should not be taken as limiting the disclosure, as any modification, equivalent replacement, or improvement made within the spirit and principle of the present disclosure should be included in the scope of the present disclosure.
Claims (10)
1. A modeling and fault early warning method for a dry reactor is characterized by comprising the following steps:
establishing an electromagnetic-circuit two-dimensional analysis model of the dry reactor by adopting Maxwell, wherein the model comprises a finite element magnetic field model and a circuit model, and calculating by the model to obtain the encapsulation loss;
taking the encapsulation loss as a heat source of the three-dimensional fluid-temperature field to calculate the temperature field and flow field distribution of the reactor, and performing multi-physical field model fusion by adopting a cyclic iteration algorithm to establish a three-dimensional fluid-temperature field finite element model;
then, reducing the order of the three-dimensional fluid-temperature field finite element model by adopting a fusion algorithm of a PSO-SVM;
and simulating multiple turn-to-turn short circuit faults on the basis of the model establishment to realize the identification and early warning judgment of the faults.
2. The modeling and fault early warning method according to claim 1, wherein the method for establishing the electromagnetic-circuit two-dimensional analysis model of the dry reactor by adopting Maxwell comprises the following steps:
establishing a finite element magnetic field model of air, an insulating medium and a coil according to the actual size of the dry-type reactor, and designing by using Maxwell;
parallel connecting equivalent circuits of coils of each layer of the dry type reactor and applying an independent power supply to form a circuit model;
and coupling the equivalent circuits of the coils with the corresponding coil units respectively to obtain the electromagnetic-circuit two-dimensional analysis model.
3. The modeling and fault early warning method of claim 2, wherein the method of calculating the encapsulation loss through the electromagnetic-circuit two-dimensional analysis model comprises:
the encapsulation loss is calculated by the following formula and is used as a heat source of the three-dimensional fluid-temperature field to calculate the temperature field and the flow field distribution of the reactor:
wherein, PjRepresenting the j-th layer loss, P, of the windingajIs resistive loss, PbjThe eddy current loss is adopted, and gamma is the conductivity of the aluminum conductor; ω is the angular frequency of the applied excitation; djThe wire diameter of the jth turn of wire; 1jThe radius of each turn of wire; bjIs the magnetic induction intensity at the center of the j turn of the wire.
4. The modeling and fault early warning method of claim 1, wherein the method of establishing the three-dimensional fluid-temperature field finite element model comprises:
firstly, establishing a calculation theoretical model: the air around the dry-type reactor is regarded as incompressible fluid, and the general control equation of the steady-state fluid in the rectangular coordinate is as follows:
in the above formula, ρ is the fluid density; u is a fluid flow velocity vector;
is a fluid universal variable;
is a generalized diffusion coefficient;
is a generalized source item;
based on the basic law of heat transfer science, the steady-state three-dimensional temperature field equation and the boundary conditions of the dry-type reactor are shown as follows:
in the formula, Ts, TfSolid and fluid thermodynamic temperatures, respectively; lambda [ alpha ]x、λy、λzThe thermal conductivity coefficients of the solid domain material in the directions of an x axis, a y axis and a z axis are respectively; q is the sum of the bulk heat source densities of the solution domain; gamma-shaped1Is a type 1 boundary condition; t isWA known wall temperature; gamma-shaped2Is a type 2 boundary condition; lambdanIs a boundary F2Normal thermal conductivity of (d); q. q.s0A heat flux density of a boundary; gamma-shaped3Is a type 3 boundary condition; h is the convective heat transfer coefficient of the solid surface;
then establishing a finite element model based on the following conditions:
at the computation domain boundary Γ1Reactor solid and air interface Γ3Upper specification of a no slip boundary condition, i.e. Vx＝Vy＝VzWhen the surface emissivity is 0, the surface emissivity is 0.9; at the computation domain boundary Γ1Upper specification of constant temperature boundary conditions, i.e. T-Γ1＝T0Setting the ambient temperature of the reactor to be 293.15K; setting the gravity acceleration to be 9.81m/s2The direction is the negative direction of the z axis; the heat source within the winding envelope is determined by the winding losses calculated from the electromagnetic field.
5. The modeling and fault early warning method according to claim 4, wherein in the process of establishing the three-dimensional fluid-temperature field finite element model, the following assumptions are made for the model itself:
the calculation theoretical model has axial symmetry, and the symmetric surfaces of the envelope, the rain cover and the star-shaped support can be regarded as heat insulation surfaces; the temperature difference between the envelopes is small, the radiation heat transfer specific gravity is small, and the heat exchange in the reactor is mainly convection and conduction; convection and radiation are considered in heat transfer between the outer surface of the rain cover and external cooling air, and the surface emissivity of the rain cover is 0.9; the encapsulation is regarded as the material isotropic whole, the rain cover and the star-shaped bracket are regarded as linear materials, and the nonlinear relation between material parameters and temperature is not considered; and the air domain of the calculation model is air among the reactor rain-proof cover, the outermost layer envelope and the lower star-shaped support.
6. The modeling and fault early warning method according to any one of claims 1-5, wherein the method for performing multi-physics model fusion by using a loop iteration algorithm comprises the following steps:
firstly, establishing a two-dimensional magnetic circuit-constraint condition of a circuit analysis model, calculating current and loss in each package of the reactor at an initial temperature in an electromagnetic field, applying a boundary condition, carrying out magnetic field analysis, and carrying out simulation calculation on the current and the loss of each winding;
reading the winding loss, transferring the winding loss to a three-dimensional fluid-temperature field finite element model, and applying load and boundary conditions of a flow field temperature field;
carrying out three-dimensional fluid-temperature field finite element model simulation to obtain temperature field distribution and encapsulation temperature;
and judging whether a convergence condition is reached or not, comparing the temperature difference value of two adjacent times with the set value or reaching the cycle number, and stopping iteration if the convergence condition is reached.
7. The modeling and fault early warning method according to any one of claims 1-5, wherein the method for reducing the finite element model of the three-dimensional fluid-temperature field by using a fusion algorithm of PSO-SVM comprises:
firstly, calculating the information entropy of the population and comparing the information entropy with a set threshold, wherein the mathematical expression of the information entropy is as follows:
in which U is a source symbol, piProbabilities corresponding to different source symbols; after the variation is determined, a DE/best/1/bin variation strategy is adopted in the early stage of iteration, and a DE/rand/1/bin strategy is adopted in the later stage of iteration;
then, the inertial weight factor ω is corrected by adopting a self-adaptive formula, and the specific correction formula is as follows:
in the formula: c. C1maxAnd c2maxAre all 2.05, c1minAnd c2minAre all 0.5; t is the current iteration number; t is tmaxIs the maximum number of iterations; omegamaxIs the maximum inertia weight factor, ωminIs the minimum inertial weight factor;
the current and the loss of the reactor are used as input parameters, the turn-to-turn short circuit fault of the dry reactor equipment, which is easy to break down, is used as a research object, the average winding temperature is selected as a predicted value, and the target value is predicted according to the dry reactor operation parameters and the actual working conditions calculated by the joint simulation.
8. The modeling and fault early warning method according to any one of claims 1-5, wherein the method for realizing fault identification and early warning discrimination by multiple turn-to-turn short circuit fault simulation comprises the following steps:
respectively taking the magnetic field variation and the fault degree of the observation point as fitting variables to establish a fitting function; when a turn-to-turn short circuit fault occurs in the k-layer coil, the turn-to-turn short circuit fault degree s is defined as follows:
s＝hs/Hk*100％；
in the above formula HkIs the height of the kth coil, hs is the height of the short circuit ring;
the percent change in the magnetic field is expressed as ^ B, defined as follows:
▽B＝(Bs-B0)/B0*100％；
in the above formula B0And BsRespectively representing the magnetic field intensity of the same point when in normal operation and inter-turn fault operation;
when a fault occurs, the fault degree s is set as an independent variable, the magnetic field variation B is set as a dependent variable, and the fault degree early warning function is simplified into a fitting function for solving the function fault degree of B and s and the magnetic change rate, which is shown as the following formula:
wherein the distance in the ATC direction is dADistance in LTC direction taken as dLSimulating curve fitting functions of the magnetic field change and the fault degree of different measuring points, wherein A, B, C, D is a to-be-determined fitting coefficient;
and finally, realizing the identification and early warning discrimination of the fault through the fitting function.
9. A modeling and fault early warning system of a modeling and fault early warning method according to any one of claims 1 to 8, comprising:
establishing a two-dimensional analysis model module: the method comprises the steps that an electromagnetic-circuit two-dimensional analysis model of the dry type reactor is built by adopting Maxwell, the model comprises a finite element magnetic field model and a circuit model, and the encapsulation loss is obtained through calculation of the model;
establishing a three-dimensional analysis model module: the system comprises a reactor, a three-dimensional fluid-temperature field, a circulating iterative algorithm, a multi-physical field model fusion and a three-dimensional fluid-temperature field finite element model, wherein the reactor is used for calculating the temperature field and flow field distribution of the reactor by taking the encapsulation loss as a heat source of the three-dimensional fluid-temperature field;
a reduced order analysis module: the method is used for reducing the three-dimensional fluid-temperature field finite element model by adopting a fusion algorithm of a PSO-SVM;
a fault analysis module: the method is used for simulating multiple turn-to-turn short circuit faults on the basis of the model establishment to realize the identification and early warning judgment of the faults.
10. A computer arrangement comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor when executing the program carries out the steps of the method of modeling and fault pre-warning of a dry reactor according to any of claims 1-8.
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