Method, device, equipment and medium for evaluating insulation performance of vacuum interrupter

Abstract

The application relates to a kind of vacuum interrupter insulation performance evaluation method, device, equipment and medium, the method comprises: obtaining the field strength data of each virtual grid unit on at least one preset insulation surface of vacuum interrupter, and the topological relationship between each vacuum gap in vacuum interrupter;For each preset insulation surface, according to the field strength data of each virtual grid unit on the preset insulation surface, determine the breakdown probability data of the corresponding vacuum gap of the preset insulation surface;According to the breakdown probability data of each vacuum gap and topological relationship, determine the total breakdown probability data of vacuum interrupter;According to total breakdown probability data, determine whether the insulation performance of vacuum interrupter is qualified.The application can improve the rationality of insulation performance evaluation, thereby improving the reliability of insulation performance evaluation result.

Description

Technical Field

[0001] This application relates to the field of vacuum interrupter technology, and in particular to a method, apparatus, equipment and medium for evaluating the insulation performance of a vacuum interrupter. Background Technology

[0002] A vacuum interrupter (VI) is the "heart" of modern medium- and high-voltage power system circuit breakers, load switches, contactors, and other switching devices. Its main function is to disconnect or close the current circuit when needed (e.g., in the event of a short-circuit fault or during normal operation).

[0003] Vacuum breakdown in a vacuum interrupter refers to the phenomenon where, under a sufficiently high electric field, the originally insulating vacuum gap suddenly loses its insulating properties and becomes a conductive path. This phenomenon limits the voltage rating and performance improvement of vacuum interrupters. The key to vacuum breakdown lies in the microscopic protrusions and impurities on the insulating surface corresponding to the vacuum gap. The randomness of these microscopic protrusions and impurities directly leads to the probabilistic and dispersed nature of the vacuum breakdown phenomenon.

[0004] Currently, most methods rely on a single, defined threshold to determine whether a vacuum interrupter will experience vacuum breakdown, thereby assessing its insulation performance. However, due to the probabilistic and dispersed nature of vacuum breakdown, existing assessment methods are not reasonable, resulting in poor reliability of insulation performance evaluation results. Summary of the Invention

[0005] Therefore, it is necessary to provide a method, apparatus, equipment, and medium for evaluating the insulation performance of a vacuum interrupter, which can improve the rationality of the insulation performance evaluation and thus improve the reliability of the insulation performance evaluation results.

[0006] In a first aspect, this application provides a method for evaluating the insulation performance of a vacuum interrupter, including:

[0007] Acquire the field strength data of each virtual grid cell on at least one preset insulating surface of the vacuum interrupter, as well as the topological relationship between each vacuum gap in the vacuum interrupter;

[0008] For each preset insulating surface, the breakdown probability data of the vacuum gap corresponding to the preset insulating surface is determined based on the field strength data of each virtual grid cell on the preset insulating surface.

[0009] Based on the breakdown probability data and topological relationships of each vacuum gap, the total breakdown probability data of the vacuum interrupter is determined.

[0010] Based on the total breakdown probability data, determine whether the insulation performance of the vacuum interrupter is up to standard.

[0011] In one embodiment, determining the breakdown probability data of the vacuum gap corresponding to the preset insulating surface based on the field strength data of each virtual grid cell on the preset insulating surface includes: for each virtual grid cell, determining the breakdown probability data of the virtual grid cell based on the field strength data of the virtual grid cell; and for each preset insulating surface, determining the breakdown probability data of the vacuum gap corresponding to the preset insulating surface based on the breakdown probability data of each virtual grid cell on the preset insulating surface.

[0012] In one embodiment, determining the breakdown probability data of a virtual mesh cell based on the field strength data of the virtual mesh cell includes: acquiring the attribute data of the virtual mesh cell; and determining the breakdown probability data of the virtual mesh cell based on the field strength data and attribute data of the virtual mesh cell.

[0013] In one embodiment, determining the breakdown probability data of the vacuum gap corresponding to the preset insulating surface based on the breakdown probability data of each virtual grid cell on the preset insulating surface includes: determining the survival probability data of the corresponding virtual grid cell based on the breakdown probability data of each virtual grid cell on the preset insulating surface; determining the survival probability data of the preset insulating surface based on the survival probability data of each virtual grid cell on the preset insulating surface; and determining the breakdown probability data of the vacuum gap corresponding to the preset insulating surface based on the survival probability data of the preset insulating surface.

[0014] In one embodiment, determining the total breakdown probability data of the vacuum interrupter based on the breakdown probability data of each vacuum gap and the topological relationship includes: determining the equivalent circuit corresponding to the topological relationship, wherein the equivalent circuit includes at least one layer of circuit units; and determining the breakdown probability data of each circuit unit in each layer according to the topological type of the circuit unit and the breakdown probability data of each equivalent vacuum gap in the circuit unit, in order from the innermost layer to the outermost layer; wherein the total breakdown probability data is the breakdown probability data of the outermost circuit unit; the equivalent vacuum gap in the innermost circuit unit is the vacuum gap; and the equivalent vacuum gap in the circuit units not in the innermost layer includes the vacuum gap and / or the circuit unit of the previous layer.

[0015] In one embodiment, determining the breakdown probability data of a circuit unit based on the topology of the circuit unit and the breakdown probability data of each equivalent vacuum gap in the circuit unit includes: when the topology is a parallel type, determining the survival probability data of the corresponding equivalent vacuum gap based on the breakdown probability data of each equivalent vacuum gap in the circuit unit; determining the survival probability data of the circuit unit based on the survival probability data of each equivalent vacuum gap in the circuit unit; and determining the breakdown probability data of the circuit unit based on the survival probability data of the circuit unit.

[0016] In one embodiment, determining the breakdown probability data of a circuit unit based on the topology of the circuit unit and the breakdown probability data of each equivalent vacuum gap in the circuit unit includes: when the topology is a series type, multiplying the breakdown probability data of each equivalent vacuum gap in the circuit unit to obtain the breakdown probability data of the circuit unit.

[0017] Secondly, this application also provides a device for evaluating the insulation performance of a vacuum interrupter, comprising:

[0018] The first acquisition module is used to acquire the field strength data of each virtual grid cell on at least one preset insulating surface of the vacuum interrupter, as well as the topological relationship between each vacuum gap in the vacuum interrupter.

[0019] The first determining module is used to determine the breakdown probability data of the vacuum gap corresponding to each preset insulating surface based on the field strength data of each virtual grid cell on the preset insulating surface.

[0020] The second determining module is used to determine the total breakdown probability data of the vacuum interrupter based on the breakdown probability data and topological relationship of each vacuum gap.

[0021] The third determination module is used to determine whether the insulation performance of the vacuum interrupter is up to standard based on the total breakdown probability data.

[0022] Thirdly, this application also provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the method provided in the first aspect.

[0023] Fourthly, this application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method provided in the first aspect.

[0024] Fifthly, this application also provides a computer program product, including a computer program that, when executed by a processor, implements the method provided in the first aspect.

[0025] The aforementioned method, apparatus, equipment, and medium for evaluating the insulation performance of vacuum interrupters presuppose that the insulating surface is divided into multiple virtual grid units, each with different electric field strength data. In particular, the electric field strength data of virtual grid units with microscopic protrusions, impurities, or other defects differs significantly from that of virtual grid units without such defects. Because the electric field strength data of each virtual grid unit on the insulating surface is considered during the calculation of the breakdown probability data, the calculation rationality of the breakdown probability data is improved, thereby increasing the accuracy of the breakdown probability data of the insulating surface. This, in turn, improves the accuracy of the subsequently calculated total breakdown probability data, ultimately enhancing the reliability of the insulation performance evaluation results. Furthermore, given the probabilistic and dispersed nature of vacuum breakdown, using total breakdown probability data for insulation performance evaluation is more reasonable than using a single, fixed threshold to determine whether vacuum breakdown will occur in a vacuum interrupter, further improving the reliability of the insulation performance evaluation results. Attached Figure Description

[0026] To more clearly illustrate the technical solutions in the embodiments of this application or related technologies, the drawings used in the description of the embodiments of this application or related technologies will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0027] Figure 1 This is a flowchart illustrating a method for evaluating the insulation performance of a vacuum interrupter in one embodiment;

[0028] Figure 2 A flowchart illustrating the steps for determining the breakdown probability data of a vacuum gap in one embodiment;

[0029] Figure 3 This is a flowchart illustrating the steps for determining the breakdown probability data of a virtual grid cell in one embodiment.

[0030] Figure 4 A flowchart illustrating the steps for determining the breakdown probability data of a vacuum gap in one embodiment;

[0031] Figure 5 This is a flowchart illustrating the steps for determining the total breakdown probability data in one embodiment;

[0032] Figure 6 This is a schematic diagram of the equivalent circuit in one embodiment;

[0033] Figure 7 This is a flowchart illustrating the steps for determining the breakdown probability data of a circuit unit in one embodiment.

[0034] Figure 8 This is a flowchart illustrating the steps for determining the breakdown probability data of a circuit unit in one embodiment.

[0035] Figure 9 This is a structural block diagram of a vacuum interrupter insulation performance evaluation device in one embodiment;

[0036] Figure 10 This is an internal structural diagram of a computer device in one embodiment. Detailed Implementation

[0037] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0038] In one exemplary embodiment, a method for evaluating the insulation performance of a vacuum interrupter is provided, see [link to relevant documentation]. Figure 1 The method includes:

[0039] S110, acquire the field strength data of each virtual grid cell on at least one preset insulating surface of the vacuum interrupter, as well as the topological relationship between each vacuum gap in the vacuum interrupter.

[0040] It is understood that insulating surfaces include ceramic surfaces, shielding covers, contact rods, and other surfaces exposed to a vacuum, and may also include other insulating surfaces, which are not limited here.

[0041] In a vacuum interrupter, the gap between any two adjacent insulating surfaces can be called a vacuum gap. Since there are usually multiple insulating surfaces in a vacuum interrupter, there are multiple vacuum gaps. Therefore, one vacuum gap corresponds to two insulating surfaces.

[0042] The preset insulating surface is the insulating surface with the lower voltage among the two insulating surfaces corresponding to the vacuum gap; that is, the insulating surface that serves as the cathode. The breakdown probability data of the vacuum gap depends on the electric field strength of the preset insulating surface corresponding to the vacuum gap.

[0043] The topology is the circuit topology diagram formed by the connection relationships between the vacuum gaps in the vacuum interrupter.

[0044] In practical scenarios, the geometric model (e.g., a 3D model) of the vacuum interrupter can be meshed using finite element methods. A more refined mesh can be created for the insulating surface; these meshes are called virtual mesh elements. Then, under the set material properties and test voltage boundary conditions, the electric field strength data of each virtual mesh element is solved using an electrostatic field solver, thus obtaining the electric field distribution of the entire geometric model.

[0045] The geometric model can be constructed using relevant computer-aided design software. Virtual mesh elements can be generated using finite element analysis software. Material properties can be set, such as copper for the contacts, stainless steel for the shielding, or alumina ceramic for the insulating shell. Test voltage boundary conditions can include voltage applied across the moving and stationary contacts or lightning strikes, and other conditions are not limited here. The electrostatic field solver is software that solves the electrostatic field equations to obtain the potential and electric field intensity distribution maps for each virtual mesh element.

[0046] S120, for each preset insulating surface, determine the breakdown probability data of the vacuum gap corresponding to the preset insulating surface based on the field strength data of each virtual grid unit on the preset insulating surface.

[0047] That is, based on the field strength data of each virtual grid cell on each insulating surface, the breakdown probability data of the insulating surface is calculated, and the breakdown probability data of the insulating surface is used as the breakdown probability data of the vacuum gap corresponding to the insulating surface.

[0048] The field strength data of a virtual grid cell can be the average value of the field strength data at each location point in that virtual grid cell.

[0049] S130, based on the breakdown probability data and topological relationship of each vacuum gap, determine the total breakdown probability data of the vacuum interrupter.

[0050] That is, based on the connection relationship between each vacuum gap, the breakdown probability data of each vacuum gap is integrated, and the integrated breakdown probability data is used as the total breakdown probability data of the vacuum interrupter.

[0051] S140, based on the total breakdown probability data, determine whether the insulation performance of the vacuum interrupter is qualified.

[0052] For example, if the total breakdown probability data is greater than a preset probability threshold, the insulation performance of the vacuum interrupter is determined to be unqualified. In this case, an improvement reminder message for the vacuum interrupter can be output so that relevant personnel can further adjust the relevant dimensions and / or structure of the vacuum interrupter. If the total breakdown probability is less than or equal to the preset probability threshold, the insulation performance of the vacuum interrupter is determined to be qualified.

[0053] The aforementioned method for evaluating the insulation performance of a vacuum interrupter presupposes that the insulation surface is divided into multiple virtual grid cells, each with different electric field strength data. In particular, the electric field strength data of virtual grid cells with defects such as microscopic protrusions and impurities differs significantly from that of virtual grid cells without such defects. Because the calculation of the breakdown probability data of the insulation surface takes into account the electric field strength data of each virtual grid cell on the insulation surface, the calculation rationality of the breakdown probability data is improved, thereby increasing the accuracy of the breakdown probability data of the insulation surface. This, in turn, improves the accuracy of the subsequently calculated total breakdown probability data, ultimately enhancing the reliability of the insulation performance evaluation results. Furthermore, given the probabilistic and dispersed nature of vacuum breakdown, using total breakdown probability data for insulation performance evaluation is more reasonable than using a single, fixed threshold to determine whether vacuum breakdown will occur in a vacuum interrupter, further improving the reliability of the insulation performance evaluation results.

[0054] Based on the technical solutions provided in the above embodiments, an optional embodiment is provided, in which the step of determining the breakdown probability data of the vacuum gap in S120 is refined.

[0055] See Figure 2 The steps for determining the breakdown probability data of the refined vacuum gap include:

[0056] S210, for each virtual grid cell, determine the breakdown probability data of the virtual grid cell based on the field strength data of the virtual grid cell.

[0057] There are multiple ways to determine the breakdown probability data of virtual grid cells based on the field strength data of the virtual grid cells. In actual scenarios, the appropriate method can be selected as needed, and no limitation is made here.

[0058] S220, for each preset insulating surface, determine the breakdown probability data of the vacuum gap corresponding to the preset insulating surface based on the breakdown probability data of each virtual grid unit on the preset insulating surface.

[0059] That is, the breakdown probability data of the preset insulating surface is determined based on the breakdown probability data of each virtual grid unit on each preset insulating surface, and the breakdown probability data of the preset insulating surface is used as the breakdown probability data of the corresponding vacuum gap.

[0060] In this embodiment, the breakdown probability data of each virtual grid cell can be accurately determined based on the field strength data of each virtual grid cell. Then, based on the breakdown probability data of each virtual grid cell on each preset insulating surface, the breakdown probability data of the vacuum gap corresponding to the preset insulating surface can be accurately determined. Moreover, the above calculation process is simple and convenient, thus improving the efficiency of insulation performance evaluation.

[0061] Based on the technical solutions provided in the above embodiments, an optional embodiment is provided, in which the step of determining the breakdown probability data of the virtual grid cells in S210 is refined.

[0062] See Figure 3 The steps for determining the breakdown probability data of refined virtual mesh cells include:

[0063] S310, Obtain the attribute data of the virtual mesh cell.

[0064] The attribute data includes size data.

[0065] The size data of the virtual mesh cell can be the surface area of ​​the virtual mesh cell, or other types of size data, which are not limited here.

[0066] In real-world scenarios, it is not necessary to perform uniform division during the virtual mesh generation process. For example, more refined virtual mesh division can be performed for important locations on important insulating surfaces. Therefore, the size data of different virtual meshes may be different.

[0067] S320, based on the field strength data and attribute data of the virtual grid cell, determines the breakdown probability data of the virtual grid cell.

[0068] For example, the breakdown probability data of the virtual mesh cell can be calculated using the following first formula:

[0069]

[0070] In the formula, This represents the breakdown probability data for the i-th virtual grid cell. For the field strength data of the i-th virtual grid cell, Let i be the surface area of ​​the i-th virtual mesh cell. The reference surface area for the virtual grid cell. For scale parameters, Let be the shape parameter. The shape parameter and scale parameter are physical constants measured experimentally.

[0071] Of course, other formulas can also be used to calculate the breakdown probability data of virtual grid cells, which are not limited here.

[0072] In this embodiment, in the process of calculating the breakdown probability data of the virtual grid cell, not only the field strength data of the virtual grid cell is taken into account, but also the attribute data of the virtual grid cell, which can further improve the accuracy of the breakdown probability data of the virtual grid cell.

[0073] Based on the technical solutions provided in the above embodiments, an optional embodiment is provided, in which the step of determining the breakdown probability data of the vacuum gap in S220 is refined.

[0074] See Figure 4 The steps for determining the breakdown probability data of the vacuum gap include:

[0075] S410, based on the breakdown probability data of each virtual grid cell on the preset insulating surface, determine the survival probability data of the corresponding virtual grid cell.

[0076] Specifically, for each virtual grid cell, the survival probability data of that virtual grid cell can be obtained by subtracting 1 from the breakdown probability data of that virtual grid cell.

[0077] S420, determine the survival probability data of the preset insulating surface based on the survival probability data of each virtual grid unit on the preset insulating surface.

[0078] Specifically, for each preset insulating surface, the survival probability data of each virtual grid cell on the preset insulating surface is multiplied to obtain the survival probability data of the preset insulating surface.

[0079] For example, based on the first calculation formula above, the survival probability data of the preset insulating surface can be calculated using the following second calculation formula:

[0080]

[0081] In the formula, The survival probability data for the preset insulating surface is given, and N is the number of virtual grid cells on the preset insulating surface.

[0082] As can be seen, the preset insulating surface in this embodiment follows the "weakest link" principle, that is, if any virtual grid cell on the preset insulating surface breaks down, the preset insulating surface will fail.

[0083] S430, based on the survival probability data of the preset insulating surface, determines the breakdown probability data of the vacuum gap corresponding to the preset insulating surface.

[0084] Specifically, for each preset insulating surface, the breakdown probability data of the preset insulating surface element can be obtained by subtracting 1 from the survival probability data of the preset insulating surface element; after obtaining the breakdown probability data of a preset insulating surface, the breakdown probability data of the preset insulating surface can be used as the breakdown probability data of the vacuum gap corresponding to the preset insulating surface.

[0085] For example, using the rules of exponentiation, the multiplication in the second formula above can be converted into the sum of exponents, resulting in the following third formula:

[0086]

[0087] In the formula, This is the breakdown probability data for the preset insulating surface elements.

[0088] In this embodiment, based on the breakdown probability data of each virtual grid cell on the preset insulating surface, the survival probability data of the corresponding virtual grid cell can be accurately determined; based on the survival probability data of each virtual grid cell on the preset insulating surface, the survival probability data of the preset insulating surface can be accurately determined; and based on the survival probability data of the preset insulating surface, the breakdown probability data of the vacuum gap corresponding to the preset insulating surface can be accurately determined. In the above calculation process, determining the survival probability data of the preset insulating surface based on the survival probability data of each virtual grid cell on the preset insulating surface embodies the idea that "the breakdown of any virtual grid cell on the preset insulating surface will lead to the failure of the preset insulating surface," ensuring the rationality of the survival probability data of the preset insulating surface, thereby ensuring the rationality of the breakdown probability data of the vacuum gap corresponding to the preset insulating surface.

[0089] Based on the technical solutions provided in the above embodiments, an optional embodiment is provided, in which the step of determining the total breakdown probability data in S130 is refined.

[0090] See Figure 5 The steps for determining the detailed total breakdown probability data include:

[0091] S510 determines the equivalent circuit corresponding to the topology.

[0092] The equivalent circuit includes at least one layer of circuit units; the topology of the circuit units is either parallel or series.

[0093] That is, the vacuum gap is equivalent to a circuit element. The circuit topology formed by the connection relationship between the various vacuum gaps is equivalent to obtain an equivalent circuit. The only circuit element in the equivalent circuit is the vacuum gap.

[0094] S520, following the order from the inner layer to the outer layer, determines the breakdown probability data of each circuit unit for each layer based on the topology of the circuit unit and the breakdown probability data of each equivalent vacuum gap in the circuit unit.

[0095] The total breakdown probability data refers to the breakdown probability data of the outermost circuit unit; the equivalent vacuum gap in the innermost circuit unit is the vacuum gap; the equivalent vacuum gap in the non-innermost circuit unit includes the vacuum gap and / or the circuit unit above.

[0096] For example, see Figure 6 The innermost (first) layer of the equivalent circuit consists of circuit unit 1 and circuit unit 2. The second layer consists of circuit unit 3, which is obtained by connecting circuit unit 1 and circuit unit 2 in parallel. The outermost (third) layer consists of circuit unit 4, which is obtained by connecting the third circuit unit and gap 6 in series. Specifically, circuit unit 1 is obtained by connecting gap 1 and gap 2 in series; circuit unit 2 is obtained by connecting gap 3, gap 4, and gap 5 in series. Figure 6 The gap in the middle is a vacuum gap.

[0097] First, for the innermost layer, calculate the breakdown probability data for circuit unit 1 and circuit unit 2 respectively: calculate the breakdown probability data for circuit unit 1 based on the series type, the breakdown probability data for gap 1 and the breakdown probability data for gap 2; calculate the breakdown probability data for circuit unit 2 based on the series type, the breakdown probability data for gap 3, the breakdown probability data for gap 4 and the breakdown probability data for gap 5.

[0098] Then, for the second layer, the breakdown probability data of circuit unit 3 is calculated based on the parallel connection type, the breakdown probability data of circuit unit 1, and the breakdown probability data of circuit unit 2. Here, circuit unit 1 and circuit unit 2 represent equivalent vacuum gaps.

[0099] Finally, for the outermost layer, the breakdown probability data of circuit unit 4 is calculated based on the series connection type, the breakdown probability data of circuit unit 3, and the breakdown probability data of gap 6. Here, circuit unit 3 is the equivalent vacuum gap.

[0100] Among them, the breakdown probability data of circuit unit 4 is the total breakdown probability data.

[0101] In real-world scenarios, if there is only one layer of circuit units, it is only necessary to calculate the breakdown probability data based on the topology of that layer of circuit units, and then use the calculated breakdown probability data as the total breakdown probability data.

[0102] In one alternative implementation, see Figure 7 The steps for determining the breakdown probability data of the S520 circuit units include:

[0103] S710, in the case of a parallel topology, determines the survival probability data of the corresponding equivalent vacuum gap based on the breakdown probability data of each equivalent vacuum gap in the circuit unit.

[0104] Specifically, for each equivalent vacuum gap in the circuit unit, the difference between 1 and the breakdown probability data of the equivalent vacuum gap is used to obtain the survival probability data of the equivalent vacuum gap.

[0105] S720 determines the survival probability data of the circuit unit based on the survival probability data of each equivalent vacuum gap in the circuit unit.

[0106] The survival probability data of each equivalent vacuum gap in the circuit unit is obtained by multiplying the survival probability data of the circuit unit.

[0107] S730 determines the breakdown probability data of the circuit unit based on the survival probability data of the circuit unit.

[0108] The breakdown probability data of the circuit unit is obtained by subtracting 1 from the survival probability data of the circuit unit.

[0109] The breakdown probability data of the circuit unit can be calculated using the following fourth formula:

[0110]

[0111] In the formula, This data represents the breakdown probability of a parallel circuit unit, where M is the number of equivalent vacuum gaps in the circuit unit, k is the number of the equivalent vacuum gaps in the circuit unit, and P... total-k This represents the breakdown probability data for the k-th vacuum gap in this circuit unit.

[0112] For example, for circuit unit 3 in the second layer, the survival probability data of circuit unit 1 is obtained by subtracting the breakdown probability data of circuit unit 1 from the breakdown probability data of circuit unit 2; the survival probability data of circuit unit 2 is obtained by subtracting the breakdown probability data of circuit unit 1 from the breakdown probability data of circuit unit 2; then the survival probability data of circuit unit 1 and the survival probability data of circuit unit 2 are multiplied to obtain the survival probability data of circuit unit 3; the breakdown probability data of circuit unit 3 is obtained by subtracting the survival probability data of circuit unit 1 from the survival probability data of circuit unit 3.

[0113] Understandably, a parallel connection is defined as follows: if multiple equivalent vacuum gaps bear the same voltage, and the breakdown of any one equivalent vacuum gap will cause the entire circuit unit to fail, then these multiple equivalent vacuum gaps constitute a parallel connection. It is evident that parallel circuit units follow the "weakest link" principle.

[0114] In the above implementation, since the equivalent vacuum gaps in the parallel circuit unit are connected in parallel, the insulation performance of the entire circuit unit will fail if any one of the equivalent vacuum gaps is broken down. Therefore, the survival probability data of the circuit unit is determined based on the survival probability data of each equivalent vacuum gap in the circuit unit. It can be seen that the above implementation can ensure the rationality of the survival probability data of the circuit unit, thereby ensuring the rationality of the breakdown probability data of the circuit unit.

[0115] In one alternative implementation, see Figure 8 The steps for determining the breakdown probability data of the S520 circuit units include:

[0116] S810, when the topology is series type, multiplies the breakdown probability data of each equivalent vacuum gap in the circuit unit to obtain the breakdown probability data of the circuit unit.

[0117] For example, the breakdown probability data of the circuit unit is calculated using the following fifth calculation formula:

[0118]

[0119] In the formula, This is the breakdown probability data for series-connected circuit units.

[0120] For example, for the innermost circuit unit 1: the breakdown probability data of gap 1 and the breakdown probability data of gap 2 in circuit unit 1 are multiplied together to obtain the breakdown probability data of circuit unit 1. For the innermost circuit unit 2: the breakdown probability data of gap 3, the breakdown probability data of gap 4 and the breakdown probability data of gap 5 in circuit unit 1 are multiplied together to obtain the breakdown probability data of circuit unit 2.

[0121] For example, for the outermost circuit unit 4, the breakdown probability data of circuit unit 3 and the breakdown probability data of gap 6 are multiplied to obtain the breakdown probability data of circuit unit 4.

[0122] In the above implementation, for series-connected circuit units, the insulation performance of the circuit unit fails only when all equivalent vacuum gaps in the circuit unit are broken down. Therefore, by multiplying all equivalent vacuum gaps in the circuit unit, the breakdown probability data of the circuit unit can be accurately calculated.

[0123] Understandably, in series-type circuits: if multiple equivalent vacuum gaps are located on the same possible breakdown path, the total voltage is distributed across these multiple equivalent vacuum gaps. Each equivalent vacuum gap must be broken down to form a complete conductive path; therefore, these multiple equivalent vacuum gaps constitute a series connection. Thus, series-type circuit units follow the principles of "redundancy" or "enhancement."

[0124] In this embodiment, for a vacuum interrupter comprising multiple vacuum gaps, when the topological relationship between the vacuum gaps is complex, the topological relationship is equivalent to an equivalent circuit, and the equivalent circuit is decomposed into at least one layer of circuit units. Each circuit unit has only one topological type; that is, all vacuum gaps are equivalent to series-connected and / or parallel-connected circuit units. The breakdown probability data of the circuit units is calculated starting from the innermost layer. Then, the innermost circuit unit is used as an equivalent vacuum gap to participate in the calculation of the breakdown probability of the next layer of circuit units, until the breakdown probability of the outermost circuit unit is calculated, thus obtaining the total breakdown probability of the vacuum interrupter. Therefore, this embodiment simplifies the complex problem by equivalence and decomposition, thereby accurately and quickly calculating the total breakdown probability of the vacuum interrupter.

[0125] It should be understood that although the steps in the flowcharts of the above embodiments are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the above embodiments may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages of other steps.

[0126] Based on the same inventive concept, this application also provides a vacuum interrupter insulation performance evaluation device for implementing the above-described vacuum interrupter insulation performance evaluation method. The solution provided by this device is similar to the solution described in the above method; therefore, the specific limitations in one or more embodiments of the vacuum interrupter insulation performance evaluation device provided below can be found in the limitations of the vacuum interrupter insulation performance evaluation method described above, and will not be repeated here.

[0127] In one exemplary embodiment, a device for evaluating the insulation performance of a vacuum interrupter is provided, see [link to relevant documentation]. Figure 9 The device includes a first acquisition module 910, a first determination module 920, a second determination module 930, and a third determination module 940, wherein:

[0128] The first acquisition module 910 is used to acquire the field strength data of each virtual grid cell on at least one preset insulating surface of the vacuum interrupter, as well as the topological relationship between each vacuum gap in the vacuum interrupter.

[0129] The first determining module 920 is used to determine the breakdown probability data of the vacuum gap corresponding to the preset insulating surface based on the field strength data of each virtual grid unit on the preset insulating surface for each preset insulating surface.

[0130] The second determining module 930 is used to determine the total breakdown probability data of the vacuum interrupter based on the breakdown probability data and topological relationship of each vacuum gap.

[0131] The third determining module 940 is used to determine whether the insulation performance of the vacuum interrupter is qualified based on the total breakdown probability data.

[0132] In one embodiment, the first determining module includes: a first determining unit, configured to determine the breakdown probability data of each virtual grid cell based on the field strength data of the virtual grid cell; and a second determining unit, configured to determine the breakdown probability data of the vacuum gap corresponding to each preset insulating surface based on the breakdown probability data of each virtual grid cell on the preset insulating surface.

[0133] In one embodiment, the first determining unit is specifically used to: acquire attribute data of the virtual grid cell; and determine the breakdown probability data of the virtual grid cell based on the field strength data and attribute data of the virtual grid cell.

[0134] In one embodiment, the second determining unit is specifically used to: determine the survival probability data of the corresponding virtual grid unit based on the breakdown probability data of each virtual grid unit on the preset insulating surface; determine the survival probability data of the preset insulating surface based on the survival probability data of each virtual grid unit on the preset insulating surface; and determine the breakdown probability data of the vacuum gap corresponding to the preset insulating surface based on the survival probability data of the preset insulating surface.

[0135] In one embodiment, the second determining module includes: a third determining unit, configured to determine the equivalent circuit corresponding to the topological relationship, wherein the equivalent circuit includes at least one layer of circuit units; and a fourth determining unit, configured to determine the breakdown probability data of each circuit unit in the circuit unit according to the topological type of the circuit unit and the breakdown probability data of each equivalent vacuum gap in the circuit unit, in order from the innermost layer to the outermost layer; wherein the total breakdown probability data is the breakdown probability data of the outermost circuit unit; the equivalent vacuum gap in the innermost circuit unit is a vacuum gap; and the equivalent vacuum gap in the circuit unit not in the innermost layer includes a vacuum gap and / or the circuit unit of the previous layer.

[0136] In one embodiment, the fourth determining unit is specifically used to: determine the survival probability data of the corresponding equivalent vacuum gap based on the breakdown probability data of each equivalent vacuum gap in the circuit unit when the topology type is parallel; determine the survival probability data of the circuit unit based on the survival probability data of each equivalent vacuum gap in the circuit unit; and determine the breakdown probability data of the circuit unit based on the survival probability data of the circuit unit.

[0137] In one embodiment, the fourth determining unit is specifically used to: when the topology type is series type, multiply the breakdown probability data of each equivalent vacuum gap in the circuit unit to obtain the breakdown probability data of the circuit unit.

[0138] Each module in the aforementioned vacuum interrupter insulation performance evaluation device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device, or stored in the computer device's memory as software, so that the processor can call and execute the corresponding operations of each module.

[0139] In one exemplary embodiment, a computer device is provided, the internal structure of which can be as shown in the figure. Figure 10 As shown, the computer device includes a processor, memory, input / output interface, communication interface, display unit, and input device. The processor, memory, and input / output interface are connected via a system bus, and the communication interface, display unit, and input device are also connected to the system bus via the input / output interface. The processor provides computing and control capabilities. The memory includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage medium. The input / output interface is used for exchanging information between the processor and external devices. The communication interface is used for wired or wireless communication with external terminals; wireless communication can be achieved through Wi-Fi, mobile cellular networks, Near Field Communication (NFC), or other technologies. When the computer program is executed by the processor, it implements a method for evaluating the insulation performance of a vacuum interrupter.

[0140] Those skilled in the art will understand that Figure 10 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0141] In one exemplary embodiment, a computer device is provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the vacuum interrupter insulation performance evaluation method provided in the above embodiments.

[0142] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon, which, when executed by a processor, implements the vacuum interrupter insulation performance evaluation method provided in the above embodiments.

[0143] In one embodiment, a computer program product is provided, including a computer program that, when executed by a processor, implements the vacuum interrupter insulation performance evaluation method provided in the above embodiments.

[0144] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of the relevant data must comply with relevant regulations.

[0145] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments of the above methods. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, artificial intelligence (AI) processors, etc., and are not limited to these.

[0146] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this application.

[0147] The above embodiments are merely illustrative of several implementation methods of this application, and their descriptions are relatively specific and detailed. However, they should not be construed as limiting the scope of this application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A method of evaluating the insulation performance of a vacuum interrupter, characterized by, The method comprises the following steps: obtaining field strength data of each virtual grid unit on at least one preset insulating surface of a vacuum interrupter and topological relations between each vacuum gap in the vacuum interrupter; for each preset insulating surface, determining breakdown probability data of a corresponding vacuum gap of the preset insulating surface according to the field strength data of each virtual grid unit on the preset insulating surface; determining total breakdown probability data of the vacuum interrupter according to the breakdown probability data of each vacuum gap and the topological relations; determining whether the insulation performance of the vacuum interrupter is qualified according to the total breakdown probability data; wherein, the determination of the total breakdown probability data of the vacuum interrupter according to the breakdown probability data of each vacuum gap and the topological relations comprises: determining an equivalent circuit corresponding to the topological relations, wherein the equivalent circuit comprises at least one layer of circuit units; in order from the inner layer to the outer layer, for each layer of circuit units, determining breakdown probability data of the circuit unit according to the topological type of the circuit unit and the breakdown probability data of each equivalent vacuum gap in the circuit unit; wherein, the total breakdown probability data is the breakdown probability data of the circuit unit in the outermost layer; the equivalent vacuum gap in the circuit unit in the innermost layer is the vacuum gap; the equivalent vacuum gap in the circuit unit in the non-innermost layer comprises the vacuum gap and / or the circuit unit in the previous layer.

2. The method of claim 1, wherein, The determination of the breakdown probability data of the preset insulating surface corresponding to the vacuum gap according to the field strength data of each virtual grid unit on the preset insulating surface comprises: for each virtual grid unit, determining breakdown probability data of the virtual grid unit according to the field strength data of the virtual grid unit; for each preset insulating surface, determining breakdown probability data of a corresponding vacuum gap of the preset insulating surface according to the breakdown probability data of each virtual grid unit on the preset insulating surface.

3. The method of claim 2, wherein, The determination of the breakdown probability data of the virtual grid unit according to the field strength data of the virtual grid unit comprises: obtaining attribute data of the virtual grid unit; determining the breakdown probability data of the virtual grid unit according to the field strength data and the attribute data of the virtual grid unit.

4. The method of claim 2, wherein, The determination of the breakdown probability data of the preset insulating surface corresponding to the vacuum gap according to the breakdown probability data of each virtual grid unit on the preset insulating surface comprises: determining survival probability data of the corresponding virtual grid unit according to the breakdown probability data of each virtual grid unit on the preset insulating surface; determining survival probability data of the preset insulating surface according to the survival probability data of each virtual grid unit on the preset insulating surface; determining the breakdown probability data of the preset insulating surface corresponding to the vacuum gap according to the survival probability data of the preset insulating surface.

5. The method of claim 1, wherein, The determination of the breakdown probability data of the circuit unit according to the topological type of the circuit unit and the breakdown probability data of each equivalent vacuum gap in the circuit unit comprises: in the case that the topological type is a parallel type, determining survival probability data of the corresponding equivalent vacuum gap according to the breakdown probability data of each equivalent vacuum gap in the circuit unit; determining survival probability data of the circuit unit according to survival probability data of each equivalent real space gap in the circuit unit; determining breakdown probability data of the circuit unit according to the survival probability data of the circuit unit.

6. The method of claim 1, wherein, The determining of the breakdown probability data of the circuit unit according to the topology type of the circuit unit and the breakdown probability data of each equivalent real space gap in the circuit unit comprises: In the case that the topology type is a series type, the breakdown probability data of each equivalent real space gap in the circuit unit is multiplied to obtain the breakdown probability data of the circuit unit.

7. An apparatus for evaluating insulation performance of a vacuum interrupter, characterized by, comprise: The first acquisition module is configured to acquire field strength data of each virtual grid unit on at least one preset insulating surface of a vacuum interrupter and a topology relationship between each real space gap in the vacuum interrupter; The first determination module is configured to, for each preset insulating surface, determine breakdown probability data of a corresponding real space gap of the preset insulating surface according to the field strength data of each virtual grid unit on the preset insulating surface; The second determination module is configured to determine total breakdown probability data of the vacuum interrupter according to the breakdown probability data of each real space gap and the topology relationship; The third determination module is configured to determine whether the insulation performance of the vacuum interrupter is qualified according to the total breakdown probability data. The second determination module comprises: a third determination unit configured to determine an equivalent circuit corresponding to the topology relationship, the equivalent circuit comprising at least one layer of circuit units; and a fourth determination unit configured to, in a sequence from an inner layer to an outer layer, for each layer of circuit units, determine breakdown probability data of the circuit unit according to a topology type of the circuit unit and the breakdown probability data of each equivalent real space gap in the circuit unit; wherein the total breakdown probability data is the breakdown probability data of the circuit unit in the outermost layer; the equivalent real space gap in the circuit unit in the innermost layer is a real space gap; and the equivalent real space gap in the circuit unit in a non-innermost layer comprises a real space gap and / or a circuit unit in a previous layer.

8. The apparatus of claim 7, wherein, The fourth determination unit is configured to, in the case that the topology type is a parallel type, determine survival probability data of each equivalent real space gap in the circuit unit according to the breakdown probability data of each equivalent real space gap in the circuit unit; determine survival probability data of the circuit unit according to the survival probability data of each equivalent real space gap in the circuit unit; and determine the breakdown probability data of the circuit unit according to the survival probability data of the circuit unit. 9.A computer device, comprising a memory and a processor, wherein the memory stores a computer program, and the computer device is configured to perform the method according to any one of claims 1-8 when the computer program is executed by the processor. The processor, when executing the computer program, implements the steps of the method in any one of claims 1 to 6.

10. A computer-readable storage medium having stored thereon a computer program, characterized in that, The computer program, when executed by the processor, implements the steps of the method in any one of claims 1 to 6.

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