Axial flux gradient array detection device for dry-type air-core reactor

Abstract

The application relates to the technical field of magnetic flux gradient detection, in particular to a dry-type air-core reactor axial magnetic flux gradient array detection device. The device comprises a data acquisition module, which is used for acquiring current data of the dry-type air-core reactor at each time within a preset time window and magnetic induction intensity at multiple monitoring points on different height layers along the reactor axis; a data analysis module, which is used for acquiring coupling distortion degree, including: calculating magnetic field response deviation, spatial symmetry deviation and coupling distortion degree; a magnetic flux detection module, which is used for obtaining single-point confidence degree representing the credibility of magnetic field data, calculating axial magnetic flux gradient of adjacent two height layers and performing anti-interference detection on the axial magnetic flux gradient of the dry-type air-core reactor. The application significantly improves the accuracy and anti-interference capability of the dry-type air-core reactor axial magnetic flux gradient detection.

Description

Technical Field

[0001] This application relates to the field of magnetic flux gradient detection technology, specifically to an axial magnetic flux gradient array detection device for dry-type air-core reactors. Background Technology

[0002] Dry-type air-core reactors are core equipment in power systems. However, during long-term operation, reactor windings may develop potential defects such as inter-turn short circuits and local deformation due to factors such as insulation aging, mechanical vibration, and overcurrent impact. By monitoring the axial magnetic flux gradient inside the reactor, it is possible to effectively assess whether there are structural faults such as inter-turn short circuits in the windings.

[0003] However, under actual operating conditions, the leakage magnetic field of the reactor is easily affected by the complex external environment. For example, the switching of the power grid load can cause the excitation current to jump rapidly, causing asynchronous transient drift of the spatial magnetic field. At the same time, the adjacent electrical equipment around the reactor can generate strong spatial electromagnetic interference, which can disrupt the inherent symmetrical distribution characteristics of the internal magnetic field of the reactor, causing non-fault drift of the internal magnetic field of the reactor. This results in serious distortion of the collected magnetic field data and affects the accuracy of the detection of the axial magnetic flux gradient of the dry air-core reactor. Summary of the Invention

[0004] To address the aforementioned technical issues, an axial flux gradient array detection device for dry-type air-core reactors is provided to resolve existing problems.

[0005] The solution to the technical problem of this application is to provide an axial flux gradient array detection device for dry air-core reactors, the device comprising:

[0006] The data acquisition module is used to acquire the current data of the dry-type air-core reactor at each moment within a preset time window, as well as the magnetic induction intensity at multiple monitoring points at different heights along the reactor axis.

[0007] The data analysis module is used to obtain coupling distortion, including:

[0008] For each monitoring point, the response characteristics of magnetic induction intensity as a function of current data at different times are analyzed to quantify the deviation of magnetic field response caused by external load switching fluctuations.

[0009] By utilizing the distribution deviation of magnetic induction intensity at two symmetrical monitoring points at the same height layer, the spatial symmetry deviation caused by external electromagnetic interference intensity is quantified. Combined with the magnetic field response deviation, the coupling distortion degree characterizing the degree of disturbance to magnetic field data is determined.

[0010] The magnetic flux detection module is used to evaluate the difference in magnetic induction intensity between monitoring points at the same axially symmetrical position of the reactor at the same time. Combined with the coupling distortion, a single-point confidence level characterizing the reliability of the magnetic field data is obtained. Based on this, the gradient of magnetic induction intensity change between monitoring points at adjacent height layers is weighted and fused to calculate the axial magnetic flux gradient between two adjacent height layers, and the axial magnetic flux gradient of the dry air reactor is subjected to disturbance rejection detection.

[0011] Preferably, the calculation process for the magnetic field response deviation is as follows:

[0012] The time period consisting of each time point and multiple times points in its neighborhood is defined as the neighborhood time period;

[0013] For each monitoring point, the change in magnetic flux density caused by the unit current change between adjacent time points is analyzed, and the forward unit rate of change and the backward unit rate of change are calculated respectively.

[0014] The differences in the forward unit rate of change between each time point and all other time points in its neighboring time period are positively fused and used as the forward deviation; the differences in the backward unit rate of change between each time point and all other time points in its neighboring time period are positively fused and used as the backward deviation.

[0015] The deviation of the magnetic field response is positively correlated with both the forward deviation and the backward deviation.

[0016] Preferably, the calculation process of the forward unit change rate is as follows: for each monitoring point, calculate the difference in magnetic induction intensity between each time point and the previous time point as the forward magnetic field change; calculate the difference in current data between each time point and the previous time point as the forward current change; and take the ratio of the forward magnetic field change to the forward current change at each time point as the forward unit change rate.

[0017] Preferably, the calculation process of the backward unit change rate is as follows: for each monitoring point, calculate the difference in magnetic induction intensity between each time point and the next time point as the backward magnetic field change; calculate the difference in current data between each time point and the next time point as the backward current change; and take the ratio of the backward magnetic field change to the backward current change at each time point as the backward unit change rate.

[0018] Preferably, the calculation process of the spatial symmetry deviation is as follows: obtain the monitoring points that are radially symmetrical with each monitoring point, and define them as radial symmetry points; calculate the difference in magnetic induction intensity between each monitoring point and its radial symmetry point at the same time, and use it as the spatial symmetry deviation of each monitoring point at each time.

[0019] Preferably, the process of obtaining the radially symmetrical point is as follows: obtain the axial centerline of the dry-type air-core reactor; for each monitoring point, find the monitoring point that belongs to the same height layer and is symmetrical about the axial centerline, and define it as the radially symmetrical point.

[0020] Preferably, the coupling distortion is positively correlated with both the magnetic field response deviation and the spatial symmetry deviation.

[0021] Preferably, the calculation process for the single-point confidence level is as follows:

[0022] A monitoring point that is axially symmetrical to each monitoring point is obtained and defined as an axially symmetrical point; the difference in magnetic induction intensity between each monitoring point and its axially symmetrical point at the same time is calculated as the axial magnetic field deviation.

[0023] If the axial magnetic field deviation is less than or equal to the preset threshold, the coupling distortion of each monitoring point at each time point is negatively exponentially mapped and used as the single-point confidence level; otherwise, the single-point confidence level is set to the preset value.

[0024] Preferably, the process of obtaining the axial symmetry point is as follows: select a plane that is perpendicular to the axial centerline of the dry air reactor and passes through its midpoint, and define it as the radial symmetry plane; for each monitoring point, find the monitoring point that is symmetrical about the radial symmetry plane, and define it as the axial symmetry point.

[0025] Preferably, the calculation of the axial magnetic flux gradient between two adjacent height layers includes:

[0026] Two monitoring points located in the same radial direction between two adjacent height layers are defined as interlayer co-location pairs; the average confidence level of a single point between interlayer co-location pairs at the same time is calculated, and then normalized as a contribution weight.

[0027] Calculate the magnetic flux gradient of magnetic induction intensity between inter-layer in-situ pairs at the same time. Based on the contribution weight, sum the magnetic flux gradients of all inter-layer in-situ pairs at all times between two adjacent height layers, and use the sum as the axial magnetic flux gradient of the two adjacent height layers.

[0028] This application has at least the following beneficial effects:

[0029] This application calculates the magnetic field response deviation, which has the advantage of deeply exploring the physical synchronous response law that the leakage magnetic field and excitation current should possess under normal operating conditions. By analyzing the difference in their coordinated changes, it can accurately isolate and quantify the local asynchronous magnetic field drift caused by abnormal changes in grid load, thereby eliminating the interference of dynamic changes in grid load on magnetic field monitoring. Calculating the spatial symmetry deviation has the advantage of fully utilizing the spatial cylindrical symmetry physical characteristics that the leakage magnetic field should possess under normal operating conditions of the reactor. By comparing the magnetic field distribution deviation at symmetrical positions at the same height, it can accurately capture and quantify external spatial electromagnetic interference with directional propagation characteristics, thereby effectively distinguishing between the reactor's own signal and external spatial noise. Determining the coupling distortion degree characterizing the degree of disturbance to magnetic field data has the advantage of comprehensively and objectively reflecting the comprehensive distortion degree of the monitoring point affected by the superposition of complex external environments. Obtaining the single-point confidence degree has the advantage of introducing axial symmetry as a criterion for judging the reactor's own state, establishing a mechanism for distinguishing between external disturbances and internal faults. Thus, when the axial symmetry remains intact, the magnetic field distortion is attributed to external disturbances and should be corrected for disturbance rejection. Axial symmetry... When damage occurs, magnetic field distortion is attributed to inter-turn faults. The original characteristics should be preserved, effectively preventing the risk of mistakenly filtering out genuine physical fault features as environmental noise. This achieves strong anti-interference while maximizing the authenticity and reliability of fault diagnosis data. Weighted fusion of the magnetic flux gradient changes between monitoring points at adjacent height levels is used to calculate the axial magnetic flux gradient between two adjacent height levels. This process performs anti-interference detection on the axial magnetic flux gradient of dry-type air-core reactors. Its beneficial effect lies in the innovative use of a dynamic soft-voting mechanism where confidence level determines weights to calculate the magnetic flux gradient. This process makes the negatively affected... Data severely affected by load fluctuations or external electromagnetic interference automatically have their contribution weight reduced due to their low confidence level, effectively suppressing the contamination of flux gradient calculation results by spurious distortions. At the same time, when inter-turn faults occur, fault feature data obtains the highest weight in weighted fusion, ensuring that the true magnetic field distortion is completely preserved and output, restoring the true spatial variation law of the magnetic field inside the reactor to the greatest extent, significantly improving the accuracy and anti-interference ability of axial flux gradient detection of dry air-core reactors, and by calculating the axial flux gradient between adjacent height layers layer by layer, the axial location of the inter-turn fault occurrence area can be realized. Attached Figure Description

[0030] The following description, in conjunction with the accompanying drawings, provides a more detailed explanation of the axial flux gradient array detection device for dry-type air-core reactors of this application.

[0031] Figure 1 This is a block diagram of an axial flux gradient array detection device for a dry-type air-core reactor provided in one embodiment of this application;

[0032] Figure 2 This is a block diagram illustrating the implementation of a data analysis module according to one embodiment of this application. Detailed Implementation

[0033] The following description, in conjunction with the accompanying drawings and embodiments, provides a more detailed explanation of the axial flux gradient array detection device for dry-type hollow reactors proposed in this application.

[0034] Please see Figure 1 The diagram shows a block diagram of an axial flux gradient array detection device for a dry air reactor according to an embodiment of this application. The device includes a data acquisition module, a data analysis module, and a flux detection module.

[0035] The data acquisition module is used to acquire the current data of the dry-type air-core reactor at various times within a preset time window, as well as the magnetic induction intensity at multiple monitoring points at different heights along the reactor axis.

[0036] Dry-type air-core reactors are important reactive power compensation devices in power systems, achieving linear magnetic characteristics and high short-circuit withstand capability through their coreless structure. However, during long-term operation, inter-turn faults may occur in the reactor windings due to insulation aging, mechanical vibration, or overcurrent surges. These early faults often do not cause obvious changes in voltage and current, but they will first alter the leakage magnetic field distribution inside the reactor, especially the magnetic flux gradient along the axial direction. Therefore, high-precision detection of the axial magnetic flux gradient can more sensitively detect early abnormal states of the reactor.

[0037] Based on the above analysis, a cylindrical frame adapted to the internal cavity size of the dry-type air-core reactor is adopted. Its outer diameter is slightly smaller than the inner diameter of the reactor, and its height is consistent with the axial length of the reactor winding. The cylindrical frame is made of non-ferromagnetic insulating material, specifically epoxy resin, fiberglass or engineering plastic, to ensure that it will not interfere with the original magnetic field distribution and meet the high voltage insulation requirements after being placed inside the dry-type air-core reactor.

[0038] The surface of the cylindrical frame is divided into multiple height layers at equal intervals along the axial direction. Multiple monitoring points are selected at equal angular intervals along the circumference of each height layer. A magnetic sensor is installed at each monitoring point. In this embodiment, the axial height layer is divided into 16 equal-interval layers, with 8 monitoring points selected in each layer. The vertical distance between adjacent layers is... for ,in, The axial height of the dry-type air-core reactor. This represents the total number of floors.

[0039] The cylindrical frame with the magnetic sensor is placed inside the dry air reactor, and the axial midpoint of the cylindrical frame is precisely aligned with the axial midpoint of the dry air reactor to ensure that the sensor array can symmetrically cover the key area of ​​the magnetic field distribution inside the reactor. When the dry air reactor is running, the magnetic induction intensity of each monitoring point in the dry air reactor cavity at different times is collected in real time.

[0040] Connect the current transformer to the busbar of the dry-type air-core reactor to collect the current data of the dry-type air-core reactor at different times in real time.

[0041] In this embodiment, the data acquisition frequency is 1kHz. As for other implementation methods, the implementer can set it according to the actual situation. Secondly, the acquired data is filtered using the Savitzky-Golay filtering algorithm. The Savitzky-Golay filtering algorithm is a well-known technology and will not be described in detail here.

[0042] Multiple moments are treated as a time window to obtain the current data of the dry-type air-core reactor at different moments within the time window, as well as the magnetic induction intensity at each monitoring point.

[0043] In this embodiment, the duration of the time window is 2 seconds. As for other implementation methods, the implementer can set it according to the actual situation.

[0044] Thus, the current data of the dry-type air-core reactor at each moment within the time window and the magnetic induction intensity at each monitoring point at different heights along the reactor axis were obtained.

[0045] The data analysis module is used to obtain coupling distortion.

[0046] Furthermore, the implementation block diagram of the data analysis module provided in this application is as follows: Figure 2 As shown.

[0047] Step 1: For each monitoring point, analyze the differences in the response characteristics of magnetic induction intensity as a function of current data at different times, in order to quantify the deviation of the magnetic field response caused by fluctuations in external load switching.

[0048] Under normal operating conditions, the internal leakage magnetic field of a reactor is mainly excited by the load current in the windings according to the law of electromagnetic induction. According to the Biot-Savart law, under conditions of intact winding structure and good inter-turn insulation, the magnetic flux density at any spatial location inside the reactor exhibits a strict proportional relationship with the load current; that is, the amplitude change of the magnetic flux density is synchronous with the current change. This synchronous coupling relationship between the magnetic field and current is an important electromagnetic characteristic of normal reactor operation. However, in actual operating scenarios, due to differences in the electromagnetic coupling characteristics between the winding layers of the reactor, when a transient load anomaly occurs in the power grid system, the change in the magnetic field in the local space often cannot instantaneously and linearly follow the sudden change in the overall load current, directly disrupting the original synchronous relationship between the magnetic field and current, resulting in a non-fault-related transient drift in the measured magnetic flux density. Therefore, analyzing the inconsistency in the response of the change in magnetic flux density to the change in current and calculating the magnetic field response deviation are crucial for effectively identifying and quantifying the degree of magnetic field data distortion caused by load fluctuations. Specifically:

[0049] The time period consisting of each time point and multiple times points in its neighborhood is defined as the neighborhood time period;

[0050] In this embodiment, the neighborhood time period includes 15 time points. As for other implementation methods, the implementer can set them according to the actual situation.

[0051] For each monitoring point, the difference in magnetic induction intensity between each time point and the previous time point is calculated as the forward magnetic field change; the difference in magnetic induction intensity between each time point and the next time point is calculated as the backward magnetic field change.

[0052] In this embodiment, for each monitoring point, the absolute value of the difference between the magnetic induction intensity at each moment and the previous moment is calculated as the forward magnetic field change, and the absolute value of the difference between the magnetic induction intensity at each moment and the next moment is calculated as the backward magnetic field change.

[0053] Calculate the difference between the current data at each time point and the previous time point as the forward current change; calculate the difference between the current data at each time point and the next time point as the backward current change.

[0054] In this embodiment, the absolute value of the difference between the current data at each time point and the previous time point is calculated as the forward current change, and the absolute value of the difference between the current data at each time point and the next time point is calculated as the backward current change.

[0055] The ratio of the change in forward magnetic field to the change in forward current at each moment is taken as the forward unit rate of change.

[0056] The ratio of the change in the backward magnetic field to the change in the backward current at each moment is taken as the backward unit rate of change.

[0057] It should be noted that, in order to avoid the denominator being 0 when calculating the ratio, a parameter adjustment factor is added to the denominator. In this embodiment, the parameter adjustment factor is set to 0.1. As for other implementation methods, the implementer can set it according to the actual situation. Secondly, the forward unit change rate and the backward unit change rate reflect the magnetic field change rate caused by the unit current change. The larger the value, the more severe the local magnetic field change caused by the unit current fluctuation.

[0058] The differences in the forward unit rate of change between each time point and all other time points in its neighboring time period are positively integrated and used as the forward deviation.

[0059] The difference in backward unit rate of change between each time point and all other time points in its neighboring time period is calculated and positively fused to form the backward deviation.

[0060] It should be noted that forward fusion specifically refers to an additive relationship, a mean relationship, etc. In this embodiment, the sum of the absolute values ​​of the differences in the forward unit rate of change between each time point and all other time points in its neighboring time period is calculated as the forward deviation; the sum of the absolute values ​​of the differences in the backward unit rate of change between each time point and all other time points in its neighboring time period is calculated as the backward deviation.

[0061] The deviation of the magnetic field response at each monitoring point at each time point was positively correlated with both the forward deviation and the backward deviation.

[0062] It should be noted that a positive correlation means that the dependent variable increases as the independent variable increases and decreases as the independent variable decreases.

[0063] In this embodiment, the sum of the forward deviation and the backward deviation is used as the magnetic field response deviation of each monitoring point at each time.

[0064] It should be noted that for the first and last time moments, due to the lack of adjacent data on the left or right, it is impossible to calculate the forward unit rate of change or the backward unit rate of change simultaneously. Only the unidirectional unit rate of change can be obtained. Based on the unidirectional unit rate of change, the unidirectional deviation is calculated, and twice of it is taken as the magnetic field response deviation.

[0065] It should be noted that the larger the forward or backward deviation, the more the magnetic field change at this time is seriously inconsistent with the overall trend at other times in the neighboring time period, indicating severe transient distortion. The larger the magnetic field response deviation, the more the ratio between the magnetic field change and the current change at this monitoring point deviates significantly from the overall trend in the neighboring time period, reflecting that the magnetic field data is more severely affected by the transient abnormal fluctuations of the power grid load, and the more obvious the data drift is.

[0066] Thus, the magnetic field response deviation of each monitoring point at each time point is obtained.

[0067] Step 2: Utilize the distribution deviation of magnetic induction intensity at two symmetrical monitoring points at the same height layer to quantify the spatial symmetry deviation caused by external electromagnetic interference intensity. Combine this with the magnetic field response deviation to determine the coupling distortion degree, which characterizes the degree of disturbance to the magnetic field data.

[0068] Furthermore, under normal operating conditions, the internal leakage magnetic field of a dry-type air-core reactor not only exhibits time-stability characteristics, but also, due to its intact winding structure and uniform current distribution, displays a strictly axially and axisily symmetrical spatial magnetic field generated by the load current. Specifically: axially, the magnetic induction intensity is symmetrically distributed along the reactor's geometric midpoint, with the intensity being maximum at the midpoint and gradually decreasing towards both ends; radially, at two locations 180° apart on the same horizontal level circumference, the magnitude of the magnetic induction intensity is equal, and the direction is symmetrical about the axis. This inherent spatial symmetry is an important manifestation of the reactor's structural integrity and a crucial reference for determining whether the magnetic field data is subject to external interference.

[0069] However, high-voltage busbars, circuit breakers, and other electrical equipment are often located around reactors. These devices generate propagating electromagnetic interference during operation, which is essentially an externally added magnetic field. Unlike the regularly distributed magnetic field generated by the reactor's own excitation, external electromagnetic interference exhibits a clear directional propagation characteristic. When it intrudes into the reactor, the magnetic field superposition effect is significantly enhanced at monitoring points closer to the interference source, while the magnetic field on the side farther from the interference source is relatively less affected. This asymmetrical spatial superposition effect disrupts the original spatial symmetry of the magnetic field distribution inside the reactor.

[0070] Based on the above analysis, the spatial symmetry deviation is calculated by the difference in magnetic field strength between monitoring points with theoretical symmetry within the reactor at the same time. Specifically:

[0071] Obtain the axial centerline of the dry-type air-core reactor; for each monitoring point, find a monitoring point at the same height layer that is symmetrical about the axial centerline, and define it as a radially symmetrical point;

[0072] Calculate the difference in magnetic induction intensity between each monitoring point and the radially symmetrical point at the same time, and use it as the spatial symmetry deviation of each monitoring point at each time.

[0073] In this embodiment, the absolute value of the difference in magnetic induction intensity between each monitoring point and the radially symmetrical point at the same time is calculated as the spatial symmetry deviation.

[0074] It should be noted that the smaller the spatial symmetry deviation, the more uniform the magnetic field distribution on the circumference at the same height is, indicating that it is not affected by external factors. The larger the value, the more unilateral distortion and drift of the spatial magnetic field distribution at the two symmetrical monitoring points at the same height has occurred, reflecting the presence of directional external electromagnetic interference. In subsequent calculations, this distorted data needs to be filtered out by reducing the weight.

[0075] Furthermore, based on the deviation of the magnetic field response and the deviation of spatial symmetry, the coupling distortion is determined, specifically as follows:

[0076] The coupling distortion, magnetic field response deviation, and spatial symmetry deviation at each monitoring point at each time point are all positively correlated.

[0077] In this embodiment, the maximum-minimum normalization method is used to normalize the magnetic field response deviation and spatial symmetry deviation of all monitoring points at all times. Based on a preset first weight and a preset second weight, the normalized magnetic field response deviation and normalized spatial symmetry deviation of each monitoring point at the same time are weighted and summed to obtain the coupling distortion. The sum of the preset first weight and the preset second weight is 1. In this embodiment, the preset first weight is equal to the preset second weight, both set to 0.5. In other implementations, the implementer can set them according to the actual situation. Furthermore, the maximum-minimum normalization method is a well-known technique and will not be described in detail here.

[0078] It should be noted that the greater the coupling distortion, the more severe the superposition of abnormal fluctuations in the transient load of the power grid and external directional electromagnetic interference on the magnetic induction intensity collected at the monitoring point at this time. The data has undergone significant non-fault distortion and drift, and its reliability in reflecting the true magnetic flux gradient change is lower. Therefore, it should be given a lower weight in subsequent axial magnetic flux gradient calculations to suppress interference.

[0079] Thus, the coupling distortion of each monitoring point at each time point is obtained.

[0080] The magnetic flux detection module is used to evaluate the difference in magnetic induction intensity between monitoring points at the same axially symmetrical position of the reactor at the same time. Combined with the coupling distortion, a single-point confidence level characterizing the reliability of the magnetic field data is obtained. Based on this, the gradient of magnetic induction intensity change between monitoring points at adjacent height layers is weighted and fused to calculate the axial magnetic flux gradient between two adjacent height layers, and the axial magnetic flux gradient of the dry air reactor is subjected to disturbance rejection detection.

[0081] Furthermore, considering that a genuine inter-turn short-circuit fault in a dry-type air-core reactor will produce severe local magnetic field distortion, directly using coupling distortion to reduce the weight of all distorted data could easily lead to the false elimination of genuine fault characteristics. Therefore, in order to effectively suppress false magnetic field distortion caused by load fluctuations and external electromagnetic interference in the subsequent axial flux gradient calculation, while fully preserving the genuine magnetic field distortion characteristics caused by the inter-turn fault, it is necessary to combine the axial symmetry characteristics of the reactor for fault identification and calculate the single-point confidence level based on the coupling distortion degree, specifically:

[0082] Select a plane that is perpendicular to the axial centerline and passes through its midpoint, and define it as the radial symmetry plane; for each monitoring point, find the monitoring point that is symmetrical about the radial symmetry plane, and define it as the axial symmetry point;

[0083] Calculate the difference in magnetic induction intensity between each monitoring point and its axially symmetrical point at the same time, and use it as the axial magnetic field deviation.

[0084] In this embodiment, the absolute value of the difference in magnetic induction intensity between each monitoring point and its axially symmetrical point at the same time is calculated as the axial magnetic field deviation.

[0085] If the axial magnetic field deviation is less than or equal to the preset threshold, the coupling distortion of each monitoring point at each time moment is negatively exponentially mapped and used as the single-point confidence level; otherwise, the single-point confidence level is set to the preset value.

[0086] In this embodiment, the process of obtaining the preset threshold is as follows: A preset percentage of the average magnetic induction intensity between each monitoring point and its axially symmetrical point at the same time is used as the preset threshold. The preset percentage is set to 5%. In other implementation methods, the implementer can set this percentage according to the actual situation. Secondly, the negative mapping process is as follows: An exponential function is used for negative mapping. Let the coupling distortion be denoted as... Then let The result is used as the single-point confidence score, where, The first factor is an exponential function with the natural constant as the base; secondly, after applying a negative exponential mapping to the coupling distortion, a single-point confidence score is obtained. This score characterizes the reliability of the magnetic flux density data at each monitoring point in the axial flux gradient calculation, and its value range is [value missing]. Therefore, the preset value is set to the maximum value of 1 within the range of values. As another implementation method, the implementer can set it according to the actual situation.

[0087] It should be noted that a smaller axial magnetic field deviation indicates that the leakage magnetic field inside the reactor maintains good mirror symmetry along the height direction, and the winding structure is healthy. A larger deviation indicates that irreversible physical structural changes have occurred inside the reactor, which is highly likely to be an inter-turn short circuit fault, resulting in severe damage to the axial magnetic circuit. By comparing the axial magnetic field deviation with a preset threshold, we can distinguish between false distortions caused by external interference and true distortions caused by inter-turn faults. When the axial magnetic field deviation is less than or equal to the preset threshold, it indicates that the reactor winding structure is intact. At this time, the abnormality in the magnetic induction intensity data mainly comes from load fluctuations or external electromagnetic interference, which is a false distortion. The smaller the single-point confidence, the lower the contribution weight of the data with greater distortion in the magnetic flux gradient calculation, thus effectively eliminating interference. When the axial magnetic field deviation is greater than the preset threshold, it indicates that the reactor has experienced a true inter-turn short circuit fault. At this time, the magnetic field distortion is a real fault signal caused by damage to the winding structure. To ensure that the fault features are not smoothed out by the weighted averaging process, the single-point confidence is directly set to the maximum value of 1, so that the fault data obtains the highest weight in the magnetic flux gradient calculation, and the fault features are output as is.

[0088] Furthermore, the calculation of the axial magnetic flux gradient depends on the spatial difference between monitoring data from two adjacent height layers. Its accuracy is simultaneously limited by the data quality of the two monitoring points. Therefore, based on single-point confidence, a joint evaluation and weight allocation of the data reliability of monitoring points between adjacent height layers is performed to calculate the axial magnetic flux gradient, specifically as follows:

[0089] Two monitoring points located in the same radial direction between two adjacent height layers are defined as interlayer co-location pairs;

[0090] Calculate the average single-point confidence among the same site pairs in different layers at the same time, normalize it, and use it as the contribution weight;

[0091] In this embodiment, the normalization process is as follows: the average single-point confidence of all inter-layer corresponding point pairs at all times within the time window is summed, and the ratio between the average single-point confidence of each inter-layer corresponding point pair at each time point and the summed result is used as the contribution weight.

[0092] Calculate the magnetic flux gradient of magnetic induction intensity between the same point pairs in the same layer at the same time;

[0093] In this embodiment, the magnetic flux gradient is a well-known technique and will not be described in detail here; wherein, the magnetic flux gradient is the rate of change of magnetic induction intensity with respect to spatial distance, then... The magnetic flux gradient between points at the same location in the layer at a given time can be expressed as the rate of change of the magnetic induction intensity at the two monitoring points relative to space. ,in, for The magnetic flux gradient of interlayer sites at time t. for At time 1, the interlayer same site pair Magnetic induction intensity at each monitoring point for At time 1, the interlayer co-location pair Magnetic induction intensity at each monitoring point The spatial distance between corresponding point pairs between layers is, in this embodiment, the vertical distance between two adjacent layers.

[0094] Based on the contribution weight, the magnetic flux gradients of all inter-layer co-location pairs at all times between two adjacent height layers are weighted and summed to obtain the axial magnetic flux gradients of the two adjacent height layers.

[0095] It should be noted that the magnetic flux gradient reflects the degree of spatial attenuation of the leakage magnetic field at a specific local location at a specific instant. In order to suppress false distortions caused by load fluctuations and external electromagnetic interference, while retaining the true distortion characteristics of inter-turn faults, a larger contribution weight is set for inter-layer co-locations that are less affected by interference or contain true fault distortion characteristics. This enhances the dominant role of reliable data in the weighted summation, thereby effectively suppressing distorted data that drifts due to transient fluctuations in the power grid or external electromagnetic radiation, restoring the true spatial variation law of the magnetic field inside the reactor to the maximum extent, and significantly improving the anti-interference ability and accuracy of the final detection results.

[0096] Following the above process, calculate the number of... The height level to the first The axial magnetic flux gradient between all two adjacent height layers in a height layer, i.e. , , , This forms the magnetic flux gradient distribution vector along the axial direction of the dry-type air-core reactor; where, The axial magnetic flux gradient between the first and second height layers. The axial magnetic flux gradient between the second and third height layers. For the first The height level to the first Axial magnetic flux gradient between height layers;

[0097] The magnetic flux gradient distribution vector is used as the anti-interference detection result. The magnetic flux gradient distribution vector is compared and analyzed with the reference gradient vector established under the normal operation of the reactor. If an abnormal change in the magnetic flux gradient of a certain axis in the magnetic flux gradient distribution vector is diagnosed, the inter-turn short circuit fault of the dry air reactor at the winding position corresponding to the adjacent height layer is accurately located, and the equipment abnormality alarm command is triggered to prompt the operation and maintenance personnel to carry out maintenance.

[0098] It should be noted that the process of obtaining the reference gradient vector is as follows: during the factory test of the dry-type air-core reactor, or during the initial commissioning at the substation site and confirmed to be healthy and fault-free, the above method is used to collect and process reference data for a period of time under stable load conditions; and the calculated multiple axial magnetic flux gradient distribution vectors are averaged multiple times and stored in the database as the reference gradient vector.

Claims

1. A dry-type air-core reactor axial flux gradient array detection device, characterized in that, The device includes: The data acquisition module is used to acquire the current data of the dry-type air-core reactor at each moment within a preset time window, as well as the magnetic induction intensity at multiple monitoring points at different heights along the reactor axis. The data analysis module is used to obtain coupling distortion, including: For each monitoring point, the response characteristics of magnetic induction intensity as a function of current data at different times are analyzed to quantify the deviation of magnetic field response caused by external load switching fluctuations. By utilizing the distribution deviation of magnetic induction intensity at two symmetrical monitoring points at the same height layer, the spatial symmetry deviation caused by external electromagnetic interference intensity is quantified. Combined with the magnetic field response deviation, the coupling distortion degree characterizing the degree of disturbance to magnetic field data is determined. The magnetic flux detection module is used to evaluate the difference in magnetic induction intensity between monitoring points at the same axially symmetrical position of the reactor at the same time. Combined with the coupling distortion, a single-point confidence level characterizing the reliability of the magnetic field data is obtained. Based on this, the gradient of magnetic induction intensity change between monitoring points at adjacent height layers is weighted and fused to calculate the axial magnetic flux gradient between two adjacent height layers, and the axial magnetic flux gradient of the dry air reactor is subjected to disturbance rejection detection.

2. The axial flux gradient array detection device for dry-type hollow reactors as described in claim 1, characterized in that, The calculation process for the magnetic field response deviation is as follows: The time period consisting of each time point and multiple times points in its neighborhood is defined as the neighborhood time period; For each monitoring point, the change in magnetic flux density caused by the unit current change between adjacent time points is analyzed, and the forward unit rate of change and the backward unit rate of change are calculated respectively. The differences in the forward unit rate of change between each time point and all other time points in its neighboring time period are positively fused and used as the forward deviation; the differences in the backward unit rate of change between each time point and all other time points in its neighboring time period are positively fused and used as the backward deviation. The magnetic field response deviation is positively correlated with both the forward deviation and the backward deviation. The sum of the forward and backward deviations is taken as the magnetic field response deviation.

3. The axial flux gradient array detection device for dry-type hollow reactors as described in claim 2, characterized in that, The calculation process of the forward unit rate of change is as follows: For each monitoring point, calculate the difference in magnetic induction intensity between each time point and the previous time point as the forward magnetic field change; calculate the difference in current data between each time point and the previous time point as the forward current change; and take the ratio of the forward magnetic field change to the forward current change at each time point as the forward unit rate of change.

4. The axial flux gradient array detection device for dry-type hollow reactors as described in claim 2, characterized in that, The calculation process of the backward unit rate of change is as follows: for each monitoring point, the difference in magnetic induction intensity between each time point and the next time point is calculated as the backward magnetic field change. Calculate the difference in current data between each time point and the next time point as the backward current change; use the ratio of the backward magnetic field change to the backward current change at each time point as the backward unit rate of change.

5. The axial flux gradient array detection device for dry-type hollow reactors as described in claim 1, characterized in that, The calculation process of the spatial symmetry deviation is as follows: obtain the monitoring points that are radially symmetrical with each monitoring point and define them as radial symmetry points; calculate the difference in magnetic induction intensity between each monitoring point and its radial symmetry point at the same time, and use it as the spatial symmetry deviation of each monitoring point at each time.

6. The axial flux gradient array detection device for dry-type air-core reactors as described in claim 5, characterized in that, The process of obtaining the radially symmetrical point is as follows: obtain the axial centerline of the dry-type air-core reactor; for each monitoring point, find the monitoring point that belongs to the same height layer and is symmetrical about the axial centerline, and define it as the radially symmetrical point.

7. The axial flux gradient array detection device for dry-type air-core reactors as described in claim 1, characterized in that, The coupling distortion is positively correlated with both the magnetic field response deviation and the spatial symmetry deviation.

8. The axial flux gradient array detection device for dry-type air-core reactors as described in claim 1, characterized in that, The calculation process for the single-point confidence level is as follows: A monitoring point that is axially symmetrical to each monitoring point is obtained and defined as an axially symmetrical point; the difference in magnetic induction intensity between each monitoring point and its axially symmetrical point at the same time is calculated as the axial magnetic field deviation. If the axial magnetic field deviation is less than or equal to the preset threshold, the coupling distortion of each monitoring point at each time point is negatively exponentially mapped and used as the single-point confidence level; otherwise, the single-point confidence level is set to the preset value.

9. The axial flux gradient array detection device for dry-type air-core reactors as described in claim 8, characterized in that, The process of obtaining the axial symmetry point is as follows: Select a plane that is perpendicular to the axial centerline of the dry air reactor and passes through its midpoint, and define it as the radial symmetry plane; for each monitoring point, find the monitoring point that is symmetrical about the radial symmetry plane, and define it as the axial symmetry point.

10. The axial flux gradient array detection device for dry-type air-core reactors as described in claim 1, characterized in that, The calculation of the axial magnetic flux gradient between two adjacent height layers includes: Two monitoring points located in the same radial direction between two adjacent height layers are defined as interlayer co-location pairs; the average confidence level of a single point between interlayer co-location pairs at the same time is calculated, and then normalized as a contribution weight. Calculate the magnetic flux gradient of magnetic induction intensity between inter-layer in-situ pairs at the same time. Based on the contribution weight, sum the magnetic flux gradients of all inter-layer in-situ pairs at all times between two adjacent height layers, and use the sum as the axial magnetic flux gradient of the two adjacent height layers.

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