High temperature superconducting tape defect identification method, device, equipment and storage medium

Abstract

The present application provides a method, device, equipment and storage medium for identifying defects in high-temperature superconducting tapes. It relates to the technical field of high-temperature superconducting tapes. The method comprises: obtaining measured magnetic field data of the high-temperature superconducting tape to be tested; obtaining an inverted current density distribution based on the measured magnetic field data; obtaining a forward magnetic field distribution based on the inverted current density distribution; obtaining a corrected current density distribution based on the magnetic field difference; wherein the magnetic field difference is calculated based on the measured magnetic field data and the forward magnetic field distribution; iteratively obtaining a corrected current density distribution based on a set iteration termination condition, and determining the iterative inverted current density distribution of the high-temperature superconducting tape to be tested based on the iteratively obtained corrected current density distribution and the inverted current density distribution; determining an operator distribution based on the iterative inverted current density distribution; and determining the defect identification result of the high-temperature superconducting tape to be tested based on the operator threshold. The method of the present application accurately identifies the defect distribution of the superconducting tape.

Description

Technical Field

[0001] The present application relates to the technical field of high-temperature superconducting tapes, and in particular to a method, device, equipment and storage medium for identifying defects in high-temperature superconducting tapes. Background Art

[0002] High-temperature superconducting tapes play an important role in research fields such as high-energy physics and strong magnetic field science because of their excellent electromagnetic properties and thermal stability, especially REBCO-coated high-temperature superconducting tapes, which still maintain a high critical current density in magnetic fields above 20 T. REBCO high-temperature superconducting films have significant magnetic field anisotropy, and the current density presents a two-dimensional plane non-uniform distribution feature. The current density distribution of superconducting films plays a decisive role in the performance of high-temperature superconducting tapes.

[0003] Existing experimental methods cannot directly test the current density distribution characteristics. The magnetic field distribution results on the surface of the superconducting film can only be obtained by magnetic measurement, and the distribution characteristics of the current density in the two-dimensional film plane space can be indirectly evaluated based on the measurement results of the spatial high-resolution magnetic field. By inverting the Biot-Savart law, the two-dimensional image of the local current density distribution of the superconducting tape can be reconstructed based on the normal component of the measured magnetic field. The magnetic field above the sample can be obtained through a variety of magnetic microscopy testing techniques, such as scanning Hall probes, magneto-optical imaging, superconducting quantum interference devices, etc.

[0004] There are three main methods for inverting current density distribution based on magnetic field data. One is the discrete matrix method based on QR decomposition to directly solve the Biot-Savart law. This method has a high computational cost and is difficult to achieve synchronous and efficient inversion of real-time data. It is only applicable to ideal conditions without magnetic field noise. For actual test conditions with noise, the inversion result has a large error. In practical applications, the fast Fourier transform combined with low-pass filtering technology is often used to achieve rapid reconstruction of current density distribution based on magnetic field, but the high-frequency component, that is, the edge of the superconducting film, has a large error in inversion. In addition, the stability of the inversion result is seriously dependent on the choice of the low-pass filter cutoff frequency, and it is not generally applicable to a wide range of problems. In response to the stability problem of inversion, a regularized electromagnetic inversion method has been developed in recent years, and the generalized cross-validation method has been used to realize the automatic selection of regularization parameters. However, there is also insufficient inversion of high-frequency components, and the fluctuation of low-frequency components is significantly enhanced with the increase of noise, causing serious distortion of the inversion results.

[0005] Although some electromagnetic inversion methods have been developed, in practical applications, faced with the inevitable noisy magnetic field data source, there are still many problems in the efficient and high-precision inversion of current density, such as the dependence of inversion process parameters on experience, insufficient inversion of high-frequency components, and volatility of low-frequency component inversion results.

[0006] Accordingly, the art needs a new high-temperature superconducting tape current density inversion scheme to solve the above problems. Summary of the invention

[0007] The present application provides a method, device, equipment and storage medium for identifying defects in high-temperature superconducting tapes, so as to solve or at least partially solve the problem that the inversion of high-frequency components is insufficient and the fluctuation of low-frequency components is significantly enhanced with the growth of noise, causing serious distortion of inversion results.

[0008] In a first aspect, the present application provides a method for identifying defects in a high-temperature superconducting tape, comprising:

[0009] Acquiring measured magnetic field data of the high temperature superconducting tape to be tested;

[0010] Based on the measured magnetic field data, obtaining an inversion current density distribution;

[0011] Based on the inversion current density distribution, obtaining the forward magnetic field distribution;

[0012] Based on the magnetic field difference, a corrected current density distribution is obtained; wherein the magnetic field difference is calculated based on the measured magnetic field data and the forward modeled magnetic field distribution;

[0013] Iteratively obtain a corrected current density distribution based on a set iteration termination condition, and determine an iterative inversion current density distribution of the high-temperature superconducting tape to be tested based on the iteratively obtained corrected current density distribution and the inversion current density distribution;

[0014] Determining operator distribution based on the iterative inversion current density distribution;

[0015] Based on the operator threshold, a defect identification result of the high-temperature superconducting tape to be tested is determined; wherein the operator threshold is determined according to the operator distribution.

[0016] In a possible design, obtaining the inversion current density based on the measured magnetic field data includes:

[0017] Rewrite the magnetic field as a stream function g With kernel function K In the form of:

[0018] ;

[0019] in , is the current element coordinate, , , To measure magnetic field data The coordinates of Represents the coordinate form of the measured magnetic field data, , represents the thickness of the high-temperature superconducting tape film, represents the vacuum magnetic permeability of high-temperature superconducting tape film, Ω1 represents the current density distribution area;

[0020] Minimization , we get the regular solution of the stream function:

[0021] ;

[0022] in, is the canonical solution of the stream function, for In Fourier transform form, for The Fourier transform form of for The frequency component of the direction, for The frequency component of the direction, for norm, is the Fourier transform, is the inverse Fourier transform, is the regularization parameter;

[0023] Minimize the generalized cross-validation function to determine the regularization parameter :

[0024] ;

[0025] in, is the generalized cross validation function, K is the kernel function, To measure magnetic field data, is the product of the kernel function and the regular solution of the stream function, Determined by the following formula:

[0026] ;

[0027] According to the formula Calculate the inverse current density distribution , where ▽ represents the vector differential operator, Represents the z-direction vector.

[0028] In a possible design, the magnetic field difference is calculated by the following formula:

[0029] ;

[0030] in, represents the magnetic field difference, Represents the measured magnetic field data, represents the forward magnetic field distribution.

[0031] In a possible design, based on a set iteration termination condition, iteratively obtaining a corrected current density distribution, and determining an iterative inversion current density distribution of the high temperature superconducting tape to be tested based on the iteratively obtained corrected current density distribution and the inversion current density distribution, including:

[0032] Determine the forward magnetic field distribution of the current iteration according to the inversion current density distribution obtained in the current iteration;

[0033] Determine the magnetic field difference of the current iteration according to the forward magnetic field distribution of the current iteration;

[0034] If the magnetic field difference of the current iteration does not reach the set magnetic field difference accuracy, the magnetic field difference of the current iteration is used to determine the corrected current density distribution obtained in the next iteration;

[0035] If the magnetic field difference of the current iteration reaches the set magnetic field difference accuracy, the corrected current density distribution obtained by the current iteration is used as the corrected current density distribution obtained by the iteration;

[0036] Based on the iteratively obtained corrected current density distribution and inverted current density distribution, the iterative inverted current density distribution of the high-temperature superconducting tape to be tested is determined by the following formula:

[0037] ;

[0038] in, represents the iterative inversion current density distribution, represents the inversion current density distribution, represents the modified current density distribution obtained iteratively.

[0039] In a possible design, determining the operator distribution based on the iterative inversion current density distribution includes:

[0040] Based on the iterative inversion current density distribution, the operator distribution is determined by the following formula:

[0041] ;

[0042] in, Def represents the operator distribution, ▽ represents the vector differential operator, J ( x , y ) represents the inversion current distribution, is a constant used to prevent the denominator from being zero. Indicates the damaged area. Indicates the strip area, at Indicates that in a certain area, Represents the operator threshold, which is determined by the following formula:

[0043] ;

[0044] in, is less than the operator threshold The number of operator distribution values, is greater than the threshold The number of operator distribution values; To obtain the point corresponding to the maximum value, for the damaged area Def Operator mean, For the strip area Def Operator mean, is the coordinate form of the operator distribution.

[0045] In a possible design, based on the operator threshold, the defect identification result of the high temperature superconducting tape to be tested is determined by the following formula:

[0046] ;

[0047] in, represents the identified defect area, Indicates the strip area.

[0048] In a second aspect, the present application provides a high temperature superconducting tape defect identification device, comprising:

[0049] A measurement magnetic field data acquisition module is configured to acquire measurement magnetic field data of the high temperature superconducting tape to be tested;

[0050] An inversion current density distribution calculation module is configured to obtain an inversion current density distribution based on the measured magnetic field data;

[0051] A forward magnetic field distribution calculation module is configured to obtain a forward magnetic field distribution based on the inverse current density distribution;

[0052] A modified current density distribution calculation module is configured to obtain a modified current density distribution based on a magnetic field difference; wherein the magnetic field difference is calculated based on the measured magnetic field data and the forward magnetic field distribution;

[0053] An iterative calculation module is configured to iteratively obtain a corrected current density distribution based on a set iterative termination condition, and determine an iterative inversion current density distribution of the high-temperature superconducting tape to be tested based on the iteratively obtained corrected current density distribution and the inversion current density distribution;

[0054] An operator distribution calculation module is configured to determine operator distribution based on the iterative inversion current density distribution;

[0055] The defect identification module is configured to determine a defect identification result of the high-temperature superconducting tape to be tested based on an operator threshold; wherein the operator threshold is determined according to the operator distribution.

[0056] In a third aspect, the present application provides an electronic device comprising: at least one processor and a memory; the memory stores computer-executable instructions; the at least one processor executes the computer-executable instructions stored in the memory, so that the at least one processor executes the high-temperature superconducting tape defect identification method described in the first aspect and various possible designs of the first aspect.

[0057] In a fourth aspect, the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores computer execution instructions. When a processor executes the computer execution instructions, the high-temperature superconducting tape defect identification method as described in the first aspect and various possible designs of the first aspect is implemented.

[0058] In a fifth aspect, the present application provides a computer program product, including a computer program, which, when executed by a processor, implements the high-temperature superconducting tape defect identification method as described in the first aspect and various possible designs of the first aspect.

[0059] The high-temperature superconducting tape defect identification method, device, equipment and storage medium provided in the present application improve the situation of insufficient boundary inversion by iteratively inverting the current density distribution, realize the fast and high-precision reconstruction of the superconducting current density, and identify the defect distribution of the superconducting tape using the defect identification operator based on the iterative inversion current density, successfully improving the defect identification accuracy of the superconducting tape, which will help to further analyze the electromagnetic field microstructure characteristics of the superconducting film and the electric-magnetic-thermal-mechanical multi-field coupling mechanism. BRIEF DESCRIPTION OF THE DRAWINGS

[0060] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0061] Figure 1 A flow chart of a high-temperature superconducting tape defect identification method provided in an embodiment of the present application;

[0062] Figure 2 A flow chart for obtaining current density distribution provided in an embodiment of the present application;

[0063] Figure 3 A flow chart for obtaining the iterative inversion current density distribution of the high-temperature superconducting tape to be tested provided in an embodiment of the present application;

[0064] Figure 4 A defect recognition result diagram provided in an embodiment of the present application;

[0065] Figure 5 A schematic diagram of the structure of a high-temperature superconducting tape defect identification device provided in an embodiment of the present application;

[0066] Figure 6 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application.

[0067] The above drawings have shown clear embodiments of the present application, which will be described in more detail later. These drawings and text descriptions are not intended to limit the scope of the present application in any way, but to illustrate the concept of the present application to those skilled in the art by referring to specific embodiments. DETAILED DESCRIPTION

[0068] Exemplary embodiments will be described in detail herein, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, the same numbers in different drawings represent the same or similar elements unless otherwise indicated. The implementations described in the following exemplary embodiments do not represent all implementations consistent with the present application. Instead, they are merely examples of devices and methods consistent with some aspects of the present application as detailed in the appended claims.

[0069] In the technical solution of this application, the collection, storage, use, processing, transmission, provision and disclosure of information such as financial data or user data involved shall comply with the provisions of relevant laws and regulations and shall not violate public order and good morals.

[0070] It should be noted that in the embodiments of the present application, certain software, components, models and other existing solutions in the industry may be mentioned, and they should be regarded as exemplary. Their purpose is only to illustrate the feasibility of implementing the technical solution of the present application, but it does not mean that the applicant has or will necessarily use the solution.

[0071] The embodiment of the present application also provides a method for identifying defects in a high-temperature superconducting tape. Figure 1 Flow chart of the high temperature superconducting tape defect identification method provided in the embodiment of the present application. Figure 1 As shown, the high temperature superconducting tape defect identification method comprises:

[0072] S1. Obtaining measurement magnetic field data of the high-temperature superconducting tape to be tested.

[0073] In this embodiment, the measured magnetic field data of the high-temperature superconducting tape to be measured is obtained by measuring using a conventional measurement method, which will not be described in detail here.

[0074] S2. Based on the measured magnetic field data, the inversion current density distribution is obtained.

[0075] In this embodiment, specific steps for obtaining the inversion current density distribution are provided. Figure 2The current density distribution acquisition flow chart provided in the embodiment of the present application is as follows: Figure 2 As shown, based on the measured magnetic field data, the inversion current density distribution is obtained, which specifically includes:

[0076] S21. Rewrite the magnetic field into a stream function according to the Biot-Savart law g With kernel function K In the form of:

[0077] ;

[0078] in , is the current element coordinate, , , To measure magnetic field data The coordinates of Represents the coordinate form of the measured magnetic field data, , represents the thickness of the high-temperature superconducting tape film, represents the vacuum magnetic permeability of high-temperature superconducting tape film, and Ω1 represents the current density distribution area.

[0079] S22, Minimization Functional , we get the regular solution of the stream function :

[0080] ;

[0081] in, for In Fourier transform form, for The Fourier transform form of for The frequency component of the direction, for The frequency component of the direction, for norm, is the inverse Fourier transform, is the regularization parameter.

[0082] S23. Minimize the generalized cross validation (GCV) function to determine the regularization parameter :

[0083] ;

[0084] in, is the generalized cross validation function, Determined by the following formula:

[0085] ;

[0086] S24, according to the formula Calculate the inverse current density distribution ,in represents the current density distribution, ▽ represents the vector differential operator, Represents the z-direction vector.

[0087] Finally, the regularization parameter is realized using the above regularization inversion method. Intelligent control.

[0088] S3. Based on the inverted current density distribution, the forward magnetic field distribution is obtained.

[0089] In this embodiment, the step of obtaining the forward magnetic field distribution based on the inverse current density distribution adopts the existing technology, so it will not be described in detail here.

[0090] S4. Based on the magnetic field difference, a corrected current density distribution is obtained; wherein the magnetic field difference is calculated based on the measured magnetic field data and the forward modeled magnetic field distribution.

[0091] In some embodiments, the magnetic field difference is calculated by the following formula:

[0092] ;

[0093] in, represents the magnetic field difference, Represents the measured magnetic field data, represents the forward magnetic field distribution.

[0094] In this embodiment, the magnetic field difference is the difference between the measured magnetic field data and the forward modeled magnetic field distribution, and the relationship between the magnetic field intensity and the current is given by the Biot-Saffar law. When the relevant parameters of the high-temperature superconducting tape to be measured are known, the corrected current density distribution can be determined according to the magnetic field difference. The principle of determining the corrected current density distribution is consistent with the principle of step S2, and the essential calculation process is the same, the difference is that the value of the forward modeled magnetic field distribution used is not consistent with the value of the magnetic field distribution used in step S2.

[0095] S5. Based on the set iteration termination condition, iteratively obtain the corrected current density distribution, and based on the iteratively obtained corrected current density distribution and the inverted current density distribution, determine the iterative inversion current density distribution of the high-temperature superconducting tape to be tested.

[0096] In some embodiments, Figure 3 The iterative inversion current density distribution acquisition flow chart of the high temperature superconducting tape to be tested provided in the embodiment of the present application is as follows: Figure 3As shown, based on the set iteration termination condition, iteratively obtaining the corrected current density distribution, and based on the iteratively obtained corrected current density distribution and the inverted current density distribution, determining the iterative inversion current density distribution of the high temperature superconducting tape to be tested specifically includes:

[0097] S51. Determine the forward magnetic field distribution of the current iteration according to the inversion current density distribution obtained in the current iteration.

[0098] In this embodiment, the inversion current density distribution obtained in the first iteration is the inversion current density distribution given in step S2. It should be noted that the principle of step S51 is consistent with that of step S3, the difference being that, in the case of non-first iteration, the value of the inversion current density distribution used is not consistent with the value of the inversion current density distribution in step S3. In actual implementation, if it is the first iteration, step S51 can directly apply the result obtained in step S3.

[0099] S52: Determine the magnetic field difference of the current iteration according to the forward modeled magnetic field distribution of the current iteration.

[0100] It should be noted that the principle of step S52 is consistent with that of step S4, and the essential calculation process is the same. The difference lies in that, in the case of non-first iteration, the numerical value of the forward magnetic field distribution used is not consistent with the numerical value of the forward magnetic field distribution used in step S4. In actual implementation, if it is the first iteration, step S52 can directly apply the result obtained in step S4.

[0101] S53, determine whether the magnetic field difference of the current iteration meets the condition △ B m ≤△, where △ is the set magnetic field difference accuracy.

[0102] If the magnetic field difference of the current iteration does not reach the set magnetic field difference accuracy, the condition △ is not met. B m ≤△, then execute step S54 to determine the corrected current density distribution obtained in the next iteration based on the magnetic field difference of the current iteration.

[0103] The specific implementation steps of determining the corrected current density distribution obtained in the next iteration by using the magnetic field difference of the current iteration are as follows:

[0104] According to the corrected current density distribution obtained in the current iteration, the inverted current density distribution of the next iteration is determined by the following formula:

[0105] ;

[0106] in, Indicates the next iteration ( m +1 times) inversion current density distribution, To invert the current density distribution, it is calculated in step S2, is the corrected current density of the current iteration, subscript m is the iteration number, is the correction factor, calculated by the following formula:

[0107] ;

[0108] in, Indicates the measured magnetic field data, △ B m represents the magnetic field difference of the current iteration, represents the 2-norm of the measured magnetic field data, Represents the 2-norm of the magnetic field difference of the current iteration.

[0109] After executing step S54, the process returns to step S51, at which point the current number of iterations is m The iteration is updated to m +1 iteration, then take the m +1 iteration as the inverted current density distribution of the current iteration, and then executing step S51 again to obtain the forward magnetic field distribution of the current iteration, and then executing step S52 based on the forward magnetic field distribution of the current iteration to determine the magnetic field difference of the current iteration and the corrected current density distribution of the current iteration, and then performing the judgment process of step S53 until the condition △ is met B m ≤△.

[0110] When the magnetic field difference of the current iteration reaches the set magnetic field difference accuracy, the condition △ B m ≤△, then execute step S55, taking the corrected current density distribution obtained in the current iteration as the corrected current density distribution obtained in the iteration.

[0111] After step S55 is executed, step S56 is executed to determine the iterative inversion current density distribution of the high temperature superconducting tape to be tested based on the iteratively obtained corrected current density distribution and the inversion current density distribution by the following formula:

[0112] ;

[0113] in, represents the iterative inversion current density distribution, represents the inversion current density distribution, represents the modified current density distribution obtained iteratively.

[0114] S6. Determine operator distribution based on iterative inversion of current density distribution.

[0115] In some embodiments, based on the iterative inversion current density distribution, the operator distribution is determined by the following formula:

[0116] ;

[0117] in, Def represents the operator distribution, ▽ represents the vector differential operator, J ( x , y ) represents the inversion current density distribution, is a constant used to prevent the denominator from being zero. Indicates the damaged area. Indicates the strip area, at Indicates that in a certain area, Represents the operator threshold, which is determined by the following formula:

[0118] ;

[0119] in, is less than the operator threshold The number of operator distribution values, is greater than the threshold The number of operator distribution values; To obtain the point corresponding to the maximum value, for the damaged area Def Operator mean, For the strip area Def Operator mean, coordinate form.

[0120] S7. Determine a defect recognition result of the high-temperature superconducting tape to be tested based on an operator threshold; wherein the operator threshold is determined according to an operator distribution.

[0121] In some embodiments, in order to distinguish the defect area from the strip area, the present embodiment will be greater than the threshold Def The value is set to 1, which is less than or equal to the threshold Def The value is set to 0, so based on the operator threshold, the defect identification result of the high-temperature superconducting tape to be tested is determined by the following formula:

[0122] ;

[0123] in, represents the identified defect area, Indicates the strip area.

[0124] like Figure 4 As shown, Figure 4 A defect identification result diagram provided in an embodiment of the present application, in the case where the center of the superconducting tape contains a circular defect, DefThe operator identifies the location and size of the circular defect very well.

[0125] Figure 5 This is a schematic diagram of the structure of a high-temperature superconducting tape defect identification device provided in an embodiment of the present application. This embodiment of the present application also provides a high-temperature superconducting tape defect identification device. Figure 5 As shown, the high temperature superconducting tape defect identification device comprises:

[0126] The measured magnetic field data acquisition module 501 is configured to acquire measured magnetic field data of the high temperature superconducting tape to be tested;

[0127] An inversion current density distribution calculation module 502 is configured to obtain an inversion current density distribution based on the measured magnetic field data;

[0128] A forward magnetic field distribution calculation module 503 is configured to obtain a forward magnetic field distribution based on the inverse current density distribution;

[0129] A modified current density distribution calculation module 504 is configured to obtain a modified current density distribution based on a magnetic field difference; wherein the magnetic field difference is calculated based on the measured magnetic field data and the forward magnetic field distribution;

[0130] The iterative calculation module 505 is configured to iteratively obtain a corrected current density distribution based on a set iterative termination condition, and determine an iterative inversion current density distribution of the high-temperature superconducting tape to be tested based on the iteratively obtained corrected current density distribution and the inversion current density distribution;

[0131] An operator distribution calculation module 506 is configured to determine operator distribution based on the iterative inversion current density distribution;

[0132] The defect identification module 507 is configured to determine a defect identification result of the high-temperature superconducting tape to be tested based on an operator threshold; wherein the operator threshold is determined according to the operator distribution.

[0133] The high-temperature superconducting tape defect identification device provided in the embodiment of the present application can be used to implement the technical solution of the high-temperature superconducting tape defect identification method in the above embodiment. Its implementation principle and technical effect are similar and will not be repeated here.

[0134] Figure 6 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application. Figure 6 As shown, the electronic device may include: a processor 61 and a memory 62 , wherein the processor 61 and the memory 62 may communicate with each other; illustratively, the processor 61 and the memory 62 communicate with each other via a communication bus 63 .

[0135] The processor 61 executes the computer execution instructions stored in the memory 62, so that the processor 61 executes the scheme in the above embodiment. The processor 61 can be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it can also be a digital signal processor (DSP), an application-specific integrated circuit ASIC, a field programmable gate array FPGA or other programmable logic devices, discrete gates or transistor logic devices, and discrete hardware components.

[0136] The communication bus 63 may be a peripheral component interconnect (PCI) bus or an extended industry standard architecture (EISA) bus, etc. The system bus may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, only one thick line is used in the figure, but it does not mean that there is only one bus or one type of bus. The transceiver is used to realize the communication between the database access device and other computers (such as clients, read-write libraries, and read-only libraries). The memory may include random access memory (RAM) and may also include non-volatile memory.

[0137] The electronic device provided in the embodiment of the present application may be the terminal device of the above embodiment.

[0138] An embodiment of the present application further provides a computer-readable storage medium, in which computer instructions are stored. When the computer instructions are executed on a computer, the computer executes the technical solution of the high-temperature superconducting tape defect identification method of the above embodiment.

[0139] An embodiment of the present application also provides a computer program product, which includes a computer program stored in a computer-readable storage medium. At least one processor can read the computer program from the computer-readable storage medium. When at least one processor executes the computer program, the technical solution of the high-temperature superconducting tape defect identification method in the above embodiment can be implemented.

[0140] In the several embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic, for example, the division of modules is only a logical function division, and there may be other division methods in actual implementation, such as multiple modules can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interfaces, devices or modules, which can be electrical, mechanical or other forms.

[0141] The modules described as separate components may or may not be physically separated, and the components shown as modules may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the modules may be selected according to actual needs to implement the solution of this embodiment.

[0142] In addition, each functional module in each embodiment of the present application can be integrated into one processing unit, or each module can exist physically separately, or two or more modules can be integrated into one unit. The above-mentioned module-composed unit can be implemented in the form of hardware or in the form of hardware plus software functional units.

[0143] The above-mentioned integrated module implemented in the form of a software function module can be stored in a computer-readable storage medium. The above-mentioned software function module is stored in a storage medium, including a number of instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) or a processor to perform some steps of the methods of various embodiments of the present application.

[0144] It should be understood that the above processor can be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), etc. A general-purpose processor can be a microprocessor or any conventional processor. The steps of the method disclosed in the invention can be directly embodied as being executed by a hardware processor, or can be executed by a combination of hardware and software modules in the processor.

[0145] The memory may include a high-speed RAM memory, and may also include a non-volatile storage NVM, such as at least one disk memory, and may also be a USB flash drive, a mobile hard disk, a read-only memory, a magnetic disk or an optical disk, etc.

[0146] The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. The bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, the bus in the drawings of this application is not limited to only one bus or one type of bus.

[0147] The above storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk. The storage medium can be any available medium that can be accessed by a general or special purpose computer.

[0148] An exemplary storage medium is coupled to a processor so that the processor can read information from the storage medium and write information to the storage medium. Of course, the storage medium can also be a component of the processor. The processor and the storage medium can be located in an application specific integrated circuit (ASIC). Of course, the processor and the storage medium can also exist as discrete components in an electronic control unit or a main control device.

[0149] Those skilled in the art can understand that all or part of the steps of implementing the above-mentioned method embodiments can be completed by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When the program is executed, the steps of the above-mentioned method embodiments are executed; and the aforementioned storage medium includes: ROM, RAM, disk or optical disk and other media that can store program codes.

[0150] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit it. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present application.

Claims

1. A method for identifying defects in high-temperature superconducting tapes, characterized in that: include: Acquiring measured magnetic field data of the high temperature superconducting tape to be tested; Based on the measured magnetic field data, obtaining an inversion current density distribution; Based on the inversion current density distribution, obtaining the forward magnetic field distribution; Based on the magnetic field difference, a corrected current density distribution is obtained; wherein the magnetic field difference is calculated based on the measured magnetic field data and the forward modeled magnetic field distribution; Iteratively obtain a corrected current density distribution based on a set iteration termination condition, and determine an iterative inversion current density distribution of the high-temperature superconducting tape to be tested based on the iteratively obtained corrected current density distribution and the inversion current density distribution; Determining operator distribution based on the iterative inversion current density distribution; Determining a defect identification result of the high-temperature superconducting tape to be tested based on an operator threshold; wherein the operator threshold is determined according to the operator distribution; Based on the measured magnetic field data, an inversion current density is obtained, including: Rewrite the magnetic field as a stream function g With kernel function K In the form of: ； in , is the current element coordinate, , , To measure magnetic field data The coordinates of Represents the coordinate form of the measured magnetic field data, , represents the thickness of the high-temperature superconducting tape film, represents the vacuum magnetic permeability of high-temperature superconducting tape film, Ω1 represents the current density distribution area; Minimization , we get the regular solution of the stream function : ； in, is the canonical solution of the stream function, for In Fourier transform form, for The Fourier transform form of for The frequency component of the direction, for The frequency component of the direction, for norm, is the inverse Fourier transform, is the regularization parameter; Minimize the generalized cross-validation function to determine the regularization parameter : ； in, is the generalized cross validation function, K is the kernel function, To measure magnetic field data, is the product of the kernel function and the regular solution of the stream function, Determined by the following formula: ； According to the formula Calculate the inverse current density distribution , where ▽ represents the vector differential operator, Represents the z-direction vector.

2. The method according to claim 1, characterized in that The magnetic field difference is calculated by the following formula: ； in, represents the magnetic field difference, Represents the measured magnetic field data, represents the forward magnetic field distribution.

3. The method according to claim 1, characterized in that: Based on the set iteration termination condition, iteratively obtain the corrected current density distribution, and based on the iteratively obtained corrected current density distribution and the inverted current density distribution, determine the iterative inversion current density distribution of the high temperature superconducting tape to be tested, including: Determine the forward magnetic field distribution of the current iteration according to the inversion current density distribution obtained in the current iteration; Determine the magnetic field difference of the current iteration according to the forward magnetic field distribution of the current iteration; If the magnetic field difference of the current iteration does not reach the set magnetic field difference accuracy, the magnetic field difference of the current iteration is used to determine the corrected current density distribution obtained in the next iteration; If the magnetic field difference of the current iteration reaches the set magnetic field difference accuracy, the corrected current density distribution obtained by the current iteration is used as the corrected current density distribution obtained by the iteration; Based on the iteratively obtained corrected current density distribution and inverted current density distribution, the iterative inverted current density distribution of the high-temperature superconducting tape to be tested is determined by the following formula: ； in, represents the iterative inversion current density distribution, represents the inversion current density distribution, represents the modified current density distribution obtained iteratively.

4. The method according to claim 3, characterized in that: Based on the iterative inversion current density distribution, determining operator distribution includes: Based on the iterative inversion current density distribution, the operator distribution is determined by the following formula: ； in, Def represents the operator distribution, ▽ represents the vector differential operator, J ( x , y ) represents the inversion current distribution, is a constant used to prevent the denominator from being zero. Indicates the damaged area. Indicates the strip area, at Indicates that in a certain area, Represents the operator threshold, which is determined by the following formula: ； in, is less than the operator threshold The number of operator distribution values, is greater than the threshold The number of operator distribution values; To obtain the point corresponding to the maximum value, for the damaged area Def Operator mean, For the strip area Def Operator mean, is the coordinate form of the operator distribution.

5. The method according to claim 4, characterized in that Based on the operator threshold, the defect identification result of the high-temperature superconducting tape to be tested is determined by the following formula: ； in, represents the identified defect area, Indicates the strip area.

6. A high-temperature superconducting tape defect identification device, characterized in that: include: A measurement magnetic field data acquisition module is configured to acquire measurement magnetic field data of the high temperature superconducting tape to be tested; An inversion current density distribution calculation module is configured to obtain an inversion current density distribution based on the measured magnetic field data; A forward magnetic field distribution calculation module is configured to obtain a forward magnetic field distribution based on the inverse current density distribution; A modified current density distribution calculation module is configured to obtain a modified current density distribution based on a magnetic field difference; wherein the magnetic field difference is calculated based on the measured magnetic field data and the forward magnetic field distribution; An iterative calculation module is configured to iteratively obtain a corrected current density distribution based on a set iterative termination condition, and determine an iterative inversion current density distribution of the high-temperature superconducting tape to be tested based on the iteratively obtained corrected current density distribution and the inversion current density distribution; An operator distribution calculation module is configured to determine operator distribution based on the iterative inversion current density distribution; A defect identification module is configured to determine a defect identification result of the high-temperature superconducting tape to be tested based on an operator threshold; wherein the operator threshold is determined according to the operator distribution; The forward magnetic field distribution calculation module is further configured to rewrite the magnetic field into a stream function g With kernel function K In the form of: ； in , is the current element coordinate, , , To measure magnetic field data The coordinates of Represents the coordinate form of the measured magnetic field data, , represents the thickness of the high-temperature superconducting tape film, represents the vacuum magnetic permeability of high-temperature superconducting tape film, Ω1 represents the current density distribution area; Minimization , we get the regular solution of the stream function: ； in, is the canonical solution of the stream function, for In Fourier transform form, for The Fourier transform form of for The frequency component of the direction, for The frequency component of the direction, for norm, is the inverse Fourier transform, is the regularization parameter; Minimize the generalized cross-validation function to determine the regularization parameter : ； in, is the generalized cross validation function, K is the kernel function, To measure magnetic field data, is the product of the kernel function and the regular solution of the stream function, Determined by the following formula: ； According to the formula Calculate the inverse current density distribution , where ▽ represents the vector differential operator, Represents the z-direction vector.

7. An electronic device, characterized in that: include: A processor, and a memory communicatively connected to the processor; The memory stores computer-executable instructions; The processor executes the computer-executable instructions stored in the memory to implement the method according to any one of claims 1 to 5.

8. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer-executable instructions, which are used to implement the method according to any one of claims 1 to 5 when executed by a processor.

9. A computer program product, characterized in that The invention comprises a computer program, which implements the method according to any one of claims 1 to 5 when being executed by a processor.

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