Superconducting cable shielding layer damage detection method based on magnetic field analysis

Abstract

The invention relates to a superconducting cable shielding layer damage detection method based on magnetic field analysis, and belongs to the technical field of superconducting. The method comprises the following steps: constructing a simulation environment according to design data of the superconducting cable; the method comprises the following steps: in a simulation environment, setting a plurality of detection points on the surface of the superconducting cable, extracting time-varying data of a magnetic flux density module on the surface of the superconducting cable at each detection point, and preprocessing the extracted data; establishing a dynamic threshold range of the detection points according to the preprocessed data, identifying abnormal data according to the dynamic threshold range, and judging a fault area; and obtaining the magnetic field variation before and after the fault area, and obtaining the proportion of the number of the fault strips according to the magnetic field variation, thereby completing the damage detection of the superconducting cable shielding layer. The invention aims to solve the technical problems that the number proportion and position of fault strips cannot be positioned and the damage fault of the shielding layer of the superconducting cable is difficult to detect at low cost when the shielding layer of the existing superconducting cable is damaged.

Description

Technical Field

[0001] This invention relates to a method for detecting damage to the shielding layer of a superconducting cable based on magnetic field analysis, belonging to the field of superconducting technology. Background Technology

[0002] High-temperature superconducting cables are a promising power transmission material. Their low AC loss during transmission makes them highly valuable. As a key component of efficient power transmission, superconducting cables typically consist of a multi-layered structure. The basic structure includes: a superconducting tape layer (carrying large currents with near-zero resistance); an insulation layer (isolating the superconducting layer from the shielding layer to prevent short circuits); an electromagnetic shielding layer (confining the internal magnetic field of the cable, reducing electromagnetic interference to external equipment, and protecting the superconducting tape from external magnetic fields); and a cryogenic insulation layer (maintaining a liquid nitrogen cryogenic environment to ensure superconducting stability). Damage to the shielding layer can lead to: electromagnetic leakage, interfering with surrounding electronic equipment; localized overheating, disrupting the superconducting state and even causing loss of superconductivity; and decreased mechanical properties, affecting the long-term reliability of the cable.

[0003] Replicating the design of an equivalent superconducting cable in the laboratory is costly and challenging. Conventional methods require the construction of complex experimental equipment, consuming significant human and material resources. Existing experimental environments simulating the magnetic field around a standard superconducting cable largely rely on complex and expensive devices, making it difficult to achieve accurate simulations at a low cost. How to construct a magnetic field environment identical to that of a standard superconducting cable in the laboratory is a technical problem that urgently needs to be solved by those skilled in the art.

[0004] The limitations of existing shielding layer damage detection technologies mean that the main detection methods for superconducting cable shielding layer damage include:

[0005] Visual inspection and infrared thermography are ineffective at identifying early, minute damage due to weak infrared signals and low imaging resolution at low temperatures. Electrical parameter monitoring is susceptible to interference from factors such as superconducting tape current fluctuations and joint contact resistance. Ultrasonic testing requires coupling agents, and sensor installation is complex at low temperatures; signal analysis is difficult for multi-layered composite superconducting cables. Partial discharge (PD) detection suffers from extremely low PD signal amplitude in superconducting cables, making them easily overwhelmed by noise.

[0006] Recent studies have shown that shielding damage leads to distortion of the electromagnetic field distribution around the cable. However, existing technologies suffer from the following problems: insufficient sensor accuracy (conventional Hall sensors drift significantly at low temperatures and cannot detect weak magnetic field changes); severe noise interference (fluctuations in superconducting tape current and harmonics from the external power grid can mask damage signals); and a lack of quantitative models (an accurate mapping relationship between shielding defect size and external magnetic field distortion has not yet been established). Therefore, current methods cannot achieve high-sensitivity, high-spatial-resolution shielding damage detection. Summary of the Invention

[0007] The purpose of this invention is to provide a method for detecting damage to the shielding layer of superconducting cables based on magnetic field analysis. This method aims to solve the technical problem that existing methods cannot locate the proportion and location of faulty strips when the shielding layer of a superconducting cable is damaged, making it difficult to detect the damage to the shielding layer of a superconducting cable at a low cost.

[0008] To achieve the above objectives, the technical solution of the present invention is: a method for detecting damage to the shielding layer of a superconducting cable based on magnetic field analysis, comprising the following steps:

[0009] S1: Construct a simulation environment based on the design data of the superconducting cable;

[0010] S2: In the simulation environment, several detection points are set on the surface of the superconducting cable, and the data of the change of magnetic flux density modulus on the surface of the superconducting cable at each detection point over time are extracted, and the extracted data is preprocessed.

[0011] S3: Establish a dynamic threshold range for the detection points based on the preprocessed data, and identify abnormal data and determine the fault area based on the dynamic threshold range;

[0012] S4: Obtain the change in magnetic field before and after the fault area, and obtain the proportion of faulty tape based on the change in magnetic field to complete the damage detection of the superconducting cable shielding layer.

[0013] Optionally, the simulation environment includes cable type, voltage level, rated current, cable radius, critical current value of the strip, and winding method of the superconducting strip.

[0014] Optionally, the detection points are symmetrically distributed on the cross-sectional plane of the superconducting cable.

[0015] Optionally, the preprocessing involves linearly normalizing the data on the change of magnetic flux density modulus on the surface of the superconducting cable over time, so that the magnetic flux density modulus values ​​at each detection point are normalized to the range [0,1]. The expression is as follows:

[0016]

[0017] Where Y represents the normalized data. The values ​​before normalization; The maximum value in the data; It is the minimum value in the data.

[0018] Optionally, S3 includes:

[0019] Calculate detection points mean of several test values and standard deviation The initial dynamic threshold range is obtained. :

[0020]

[0021]

[0022] in, This is a threshold range control parameter;

[0023] The sensor is moved along the axial direction of the superconducting cable at a preset speed, or the superconducting cable is moved to change the detection position. The magnetic field data at the current position is then extracted and normalized. The normalized data is then evaluated. Is it within the initial dynamic threshold range?

[0024] If satisfied ,determination Normal data and marked as and according to The mean and standard deviation are dynamically adjusted, expressed as follows:

[0025]

[0026]

[0027] in, , These are the means before and after the update, respectively. , These are the standard deviations before and after the update, respectively, and α is a smoothing factor used to control the update speed.

[0028] Otherwise, determine Abnormal data and marked as and according to The detection point is subjected to regional consistency detection to ensure that there will be no false alarms due to momentary interference. Specifically, a fault is determined only when two or more adjacent detection points are abnormal at the same time and the abnormality lasts for multiple sampling cycles, and the area composed of all the adjacent detection points with abnormality is marked as the fault area.

[0029] Optionally, S4 includes:

[0030] For testing points Calculate the change in magnetic field before and after the fault region. :

[0031]

[0032] The change in magnetic field is normalized to a multiple of the baseline standard deviation, Z:

[0033]

[0034] The proportion of faulty strips is obtained based on the multiple Z.

[0035] Optionally, the proportion of the number of faulty strips obtained based on the multiple Z is specifically as follows:

[0036] This indicates the proportion of defective strips. ;

[0037] This indicates the proportion of defective strips. ;

[0038] This indicates the proportion of defective strips in the total number of defective strips. ;

[0039] This indicates the proportion of defective strips. ;

[0040] Among them, a1, a2, a3, and a4 are the interval division parameters of the magnetic field amplitude change, which are determined through simulation.

[0041] The beneficial effects of this invention are: by verifying the magnetic field stability of superconducting cables under rated operating conditions, this invention identifies damage to superconducting tapes caused by manufacturing defects and local magnetic field anomalies caused by partial tape quenching during operation, providing benchmark data for subsequent operation and maintenance. It has the characteristics of high stability, convenient operation and wide applicability. Attached Figure Description

[0042] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0043] Figure 1 This is a flowchart illustrating the steps of this application;

[0044] Figure 2 This is a schematic diagram of the cross-sectional structure of the superconducting cable according to Embodiment 1 of this application;

[0045] Figure 3 This is a diagram showing the distribution of the external magnetic field of a normal cable in Embodiment 1 of this application;

[0046] Figure 4 This is a schematic diagram of the local magnetic field distortion of the defective cable in Embodiment 1 of this application;

[0047] Figure 5 This is a graph showing the change in the magnetic field at the fault location in Embodiment 1 of this application.

[0048] Figure 6 This is a flowchart of the fault diagnosis process in Embodiment 1 of this application. Detailed Implementation

[0049] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of this application.

[0050] Example 1: As Figure 1 As shown, a method for detecting damage to the shielding layer of a superconducting cable based on magnetic field analysis is described. The method includes the following steps:

[0051] S1: Construct a simulation environment based on the design data of the superconducting cable.

[0052] Optionally, the design data of the corresponding superconducting cable can be obtained. The design data of the corresponding superconducting cable is used to indicate its design standards. The design data includes cable type, voltage level, rated current, cable radius, critical current value of the tape, and superconducting tape winding method. The simulation environment includes cable type, voltage level, rated current, cable radius, critical current value of the tape, and superconducting tape winding method.

[0053] Optionally, this embodiment involves experiments with superconducting cables of different rated currents, and the experimental conditions vary. To clearly understand the magnetic field changes under corresponding conditions, it is necessary to obtain the design data of cables with different rated currents to determine the cable model to be studied. This embodiment uses a high-temperature superconducting cable of model 10kV / 1800A, constructed by stacking and winding two layers of superconducting tape, as an example. The source for determining the corresponding superconducting cable design data can be determined based on existing high-temperature superconducting cable data. This embodiment does not limit the acquisition method; the data can be obtained from design manuals.

[0054] Optionally, a cable model can be established in a simulation environment using the design data of the superconducting cable, including: the cable type, voltage level, tape size, tape critical current, tape arrangement, etc. of the required superconducting cable to obtain a standard cable model.

[0055] Furthermore, assuming a standard rated current of 1800A, the required number of tapes is 30. The cable model is defined; different rated currents affect the magnetic field value on the surface of the high-temperature superconducting cable, and their variation patterns are consistent. The general basic structure of the high-temperature superconducting cable is determined, typically including the following components: support tube, superconducting layer, insulation layer, electromagnetic shielding layer, protective layer, cryostat, and armor layer. Since this embodiment studies magnetic field relationships, the support tube, insulation layer, and cryostat, which have a relatively small impact on the magnetic field results, are ignored in the simulation modeling. The determined superconducting cable model includes: superconducting layer, shielding layer, protective layer, and armor layer. Because long straight conductors do not show significant differences in the axial synthetic magnetic field, a two-dimensional cross-section of the superconducting cable is established to study the radial variation of its surface synthetic magnetic field during the modeling and simulation experiment. The two-dimensional model is as follows: Figure 2 As shown.

[0056] Specifically, the various parameters of the standard cable structure simulation model on which this embodiment 1 is based are shown in Table 1 below.

[0057] Table 1. Schematic diagram of partial cable design data

[0058]

[0059] S2: In the simulation environment, several detection points are set on the surface of the superconducting cable, and the data of the change of magnetic flux density modulus on the surface of the superconducting cable at each detection point over time are extracted, and the extracted data is preprocessed.

[0060] Optionally, the detection points are symmetrically distributed on the cross-sectional plane of the superconducting cable.

[0061] Optionally, the preprocessing involves linearly normalizing the data on the change of magnetic flux density modulus on the surface of the superconducting cable over time, so that the magnetic flux density modulus values ​​at each detection point are normalized to the range [0,1], avoiding the influence of differences in magnitude and improving the accuracy of fault diagnosis. The expression is as follows:

[0062]

[0063] Where Y represents the normalized data. The values ​​before normalization; The maximum value in the data; It is the minimum value in the data.

[0064] S3: Establish a dynamic threshold range for detection points based on the preprocessed data, and identify abnormal data and determine the fault area based on the dynamic threshold range.

[0065] Optionally, due to the large fluctuations in power system load, this embodiment uses an adaptive threshold method to dynamically calculate the statistical range of the normal-state magnetic field data to obtain the statistical range of each detection point k. Specifically:

[0066] Calculate detection points mean of several test values and standard deviation The initial dynamic threshold range is obtained. :

[0067]

[0068]

[0069] in, This is a threshold range control parameter;

[0070] The sensor is moved along the axial direction of the superconducting cable at a preset speed, or the superconducting cable is moved to change the detection position (equivalent to changing the position of the shielding strip of the cable cross-section in the simulation experiment). The magnetic field data at the current position is then extracted and normalized. The normalized data is then evaluated. Is it within the initial dynamic threshold range?

[0071] If satisfied ,determination Normal data and marked as and according to The mean and standard deviation are dynamically adjusted, expressed as follows:

[0072]

[0073]

[0074] in, , These are the means before and after the update, respectively. , These are the standard deviations before and after the update, respectively, and α is a smoothing factor used to control the update speed.

[0075] Otherwise, determine Abnormal data and marked as and according to The detection point is subjected to regional consistency detection to ensure that there will be no false alarms due to momentary interference. Specifically, a fault is determined only when two or more adjacent detection points are abnormal at the same time and the abnormality lasts for multiple sampling cycles, and the area composed of all the adjacent detection points with abnormality is marked as the fault area.

[0076] It should be understood that the theoretical basis for this embodiment is derived as follows:

[0077] This embodiment involves a magnetic field experiment around a superconducting cable, where the cable's length is much greater than its cross-sectional area. Therefore, the cable can be approximated as an infinitely long straight conductor, and the magnetic field near its cross-section can be calculated using electromagnetic induction. Maxwell's equations are a set of fundamental equations relating electric and magnetic fields to electric charge and current, describing the quantitative laws governing electromagnetic induction. Specifically, for electromagnetic induction in cables, two equations need to be considered: Faraday's law of electromagnetic induction and Ampere's circuital law.

[0078] Specifically, Faraday's law of electromagnetic induction states that when the magnetic flux through a closed loop changes, an induced electromotive force (EMF) is generated in the loop. The magnitude of the induced EMF is proportional to the rate of change of the magnetic flux with respect to time. This law also states that the curl of the electric field is equal to the negative of the rate of change of the magnetic field with respect to time. A time-varying magnetic field will induce eddy currents in a conductor, thereby generating an induced current in the shielding layer. Ampere's circuital law describes how current and a time-varying electric field generate a magnetic field on the surface of a cable. It shows that the conductor layer of a current-carrying superconducting cable, through coupling with the shielding layer, generates a current in the shielding layer. This current, through the self-inductance of the shielding layer, establishes a magnetic field outside the cable.

[0079] It is understood that this embodiment locates damage by calculating the theoretical magnetic field distribution under the intact and damaged states of the shielding layer, and by inferring abnormal changes in the strip current from the measured magnetic field. Furthermore, by quantifying the mutual inductance effect, the detection accuracy can be significantly improved.

[0080] Optionally, in this embodiment, eight detection points are set on the cable surface, and the current is applied to the rated current. The detection points are 10mm away from the cable. The magnetic field values ​​at the eight symmetrical points are as follows: The steady-state magnetic field distribution and the distribution of the detection points under this state are shown in the figure. Figure 3 As shown.

[0081] Specifically, data on the change of magnetic flux density modulus over time on the outer surface of the cable are extracted; the normalized steady-state magnetic field detection values ​​are then calculated. The statistical range of normal data for each detection point is obtained. Used as the initial value. The specific calculation results are shown in Table 2.

[0082] Table 2 Calculation results of magnetic field at each detection point

[0083]

[0084] When performing fault detection, the position of the superconducting shielding layer of the cable is changed according to the actual situation, and the magnetic field data is detected again. The current magnetic field amplitude of each detection point is calculated and compared to see if it is within the threshold range. If it meets the requirements, the mean and standard deviation are dynamically adjusted based on the current magnetic field value.

[0085] S4: Obtain the change in magnetic field before and after the fault area, and obtain the proportion of faulty tape based on the change in magnetic field to complete the damage detection of the superconducting cable shielding layer.

[0086] Optionally, for the detection point Calculate the change in magnetic field before and after the fault region. :

[0087]

[0088] The change in magnetic field is normalized to a multiple of the baseline standard deviation, Z:

[0089]

[0090] The proportion of faulty strips is obtained based on the multiple Z.

[0091] Optionally, the proportion of the number of faulty strips obtained based on the multiple Z is specifically as follows:

[0092] This indicates the proportion of defective strips. ;

[0093] This indicates the proportion of defective strips. ;

[0094] This indicates the proportion of defective strips in the total number of defective strips. ;

[0095] This indicates the proportion of defective strips. ;

[0096] Among them, a1, a2, a3, and a4 are the interval division parameters of the magnetic field amplitude change, which are determined through simulation.

[0097] Specifically, the current is applied to the rated current, the proportion of faulty cable strips with different shielding layers in phase A is set, and the changes in the magnetic field value around the cable are recorded in real time; the schematic diagram of the local distortion of the surrounding magnetic field and the division of the fault area are as follows. Figure 4 As shown in Table 3, the calculation results of the magnetic field value changes and interval division parameters of the relevant detection points obtained based on the proportion of different fault strips in the A-phase shielding layer are shown in Table 3.

[0098] Table 3 Calculation results of different damage quantities

[0099]

[0100] Based on the calculation results of the different damage ratios of the shielding strip in the table above, it can be seen that the closer the detection point is to the fault location, the greater the change in magnetic field. When the proportion of faulty strip is less than 5%, the maximum average magnetic field change is about 1.6 times the standard deviation. After retaining a certain margin, we take a1 and the interval parameter is 2. When the proportion of faulty strip is between 5% and 10%, the maximum average magnetic field change is about 2.7 times the standard deviation. After retaining a certain margin, we take a2 and the interval parameter is 3. When the proportion of faulty strip is between 10% and 20%, the maximum average magnetic field change is about 4.6 times the standard deviation. After retaining a certain margin, we take a3 and the interval parameter is 5. The calculated interval division parameters for the magnetic field amplitude are a1=2, a2=3, and a3=5.

[0101] Furthermore, a regional consistency test is performed on the corresponding detection points marked as abnormal data to determine the faulty area. An alarm signal is only output when both spatially adjacent points of the corresponding detection point are marked as abnormal. In the above steps, detection points 4, 5, 6, and 7 are tested. Only detection point 5 meets the conditions, so regions 4 and 5 are determined to be faulty.

[0102] Optionally, for the abnormal magnetic field data of all detection points corresponding to the two identified faulty areas, the proportion of faulty strips is determined, and the maximum value is output. Using the data calculated in the above steps as the basis for determining the proportion of faulty strips, the maximum value of Z is obtained after processing the magnetic field values ​​detected at actual detection points 4, 5, and 6. The equivalent interval of the faulty strip proportion that it conforms to is then determined, and the faulty strip proportion interval value is output. The detection steps are as follows... Figure 6 As shown.

[0103] Optionally, this embodiment uses a 10kV / 1800A superconducting cable as an example for illustration. The magnetic field value of the studied superconducting cable is related to the magnitude of the current. The magnitude of the combined magnetic field corresponding to different faults is significantly different from that of the normal part. Based on this, the magnetic field change curves of corresponding points near the faults of the two strips are shown in the figure. Figure 5 As shown.

[0104] Optionally, this embodiment uses COMSOL finite element simulation software to conduct experiments. By establishing a superconducting cable model, the changes in the surrounding magnetic field are detected as the basis for judgment. By establishing a numerical mapping relationship between shielding layer defects and external magnetic field distortion, and comparing the magnetic field data detected under actual conditions, the proportion of shielding layer material failures and the failure area can be determined in a short time through abnormal signals.

[0105] The specific embodiments of the present invention have been described in detail above with reference to the accompanying drawings. However, the present invention is not limited to the above embodiments. Within the scope of knowledge possessed by those skilled in the art, various changes can be made without departing from the spirit of the present invention.

Claims

1. A method for detecting damage to the shielding layer of a superconducting cable based on magnetic field analysis, characterized in that, The method includes the following steps: S1: Construct a simulation environment based on the design data of the superconducting cable; S2: In the simulation environment, several detection points are set on the surface of the superconducting cable, and the data of the change of magnetic flux density modulus on the surface of the superconducting cable at each detection point over time are extracted, and the extracted data is preprocessed. S3: Establish a dynamic threshold range for the detection points based on the preprocessed data, and identify abnormal data and determine the fault area based on the dynamic threshold range; S4: Obtain the change in magnetic field before and after the fault area, and obtain the proportion of faulty tape based on the change in magnetic field to complete the damage detection of the superconducting cable shielding layer.

2. The method for detecting damage to the shielding layer of a superconducting cable based on magnetic field analysis according to claim 1, characterized in that, The simulation environment includes cable type, voltage level, rated current, cable radius, critical current value of the strip, and winding method of the superconducting strip.

3. The method for detecting damage to the shielding layer of a superconducting cable based on magnetic field analysis according to claim 1, characterized in that, The detection points are symmetrically distributed on the cross-sectional plane of the superconducting cable.

4. The method for detecting damage to the shielding layer of a superconducting cable based on magnetic field analysis according to claim 1, characterized in that, The preprocessing involves linearly normalizing the data on the change of magnetic flux density modulus on the surface of the superconducting cable over time, so that the magnetic flux density modulus values ​​at each detection point are normalized to the range [0,1]. The expression is as follows: ； Where Y represents the normalized data. The values ​​before normalization; The maximum value in the data; It is the minimum value in the data.

5. The method for detecting damage to the shielding layer of a superconducting cable based on magnetic field analysis according to claim 1, characterized in that, S3 includes: Calculate detection points mean of several test values and standard deviation The initial dynamic threshold range is obtained. : ； ； in, This is a threshold range control parameter; The sensor is moved along the axial direction of the superconducting cable at a preset speed, or the superconducting cable is moved to change the detection position. The magnetic field data at the current position is then extracted and normalized. The normalized data is then evaluated. Is it within the initial dynamic threshold range? If satisfied ,determination Normal data and marked as and according to The mean and standard deviation are dynamically adjusted, expressed as follows: ； ； in, , These are the means before and after the update, respectively. , These are the standard deviations before and after the update, respectively, and α is a smoothing factor used to control the update speed. Otherwise, determine Abnormal data and marked as and according to The detection point is subjected to regional consistency detection to ensure that there will be no false alarms due to momentary interference. Specifically, a fault is determined only when two or more adjacent detection points are abnormal at the same time and the abnormality lasts for multiple sampling cycles, and the area composed of all the adjacent detection points with abnormality is marked as the fault area.

6. The method for detecting damage to the shielding layer of a superconducting cable based on magnetic field analysis according to claim 1, characterized in that, S4 includes: For testing points Calculate the change in magnetic field before and after the fault region. : ； The change in magnetic field is normalized to a multiple of the baseline standard deviation, Z: ； The proportion of faulty strips is obtained based on the multiple Z.

7. The method for detecting damage to the shielding layer of a superconducting cable based on magnetic field analysis according to claim 6, characterized in that, The specific proportion of the number of faulty strips obtained based on the multiple Z is as follows: This indicates the proportion of defective strips. ; This indicates the proportion of defective strips. ; This indicates the proportion of defective strips in the total number of defective strips. ; This indicates the proportion of defective strips. ; Among them, a1, a2, a3, and a4 are the interval division parameters of the magnetic field amplitude change, which are determined through simulation.

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