Fault diagnosis system and method for CT secondary circuit

Abstract

The embodiment of the invention provides a fault diagnosis system and method for a CT secondary circuit. The system comprises a multi-parameter sensing module, a data analysis module and a fault positioning module which are connected in sequence. The multi-parameter sensing module is used for acquiring shielding layer ring current and neutral point grounding current of a target CT secondary circuit, converting the shielding layer ring current and the neutral point grounding current into voltage signals and sending the voltage signals to the data analysis module; the data analysis module is used for obtaining a characteristic amplitude and a phase observation value of the target CT secondary circuit according to the received voltage signal, and calculating a judgment result of the grounding state in the target CT secondary circuit based on the characteristic amplitude, the phase observation value and a preset parameter; and the fault positioning module is used for calculating the coordinates of a fault point according to the obtained ground screen parameters and transient signals of the target secondary circuit when the judgment result is that the ground fault exists. Therefore, the real-time performance, the accuracy and the reliability of CT secondary circuit fault diagnosis are improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of power system relay protection and fault diagnosis, and particularly relates to a CT secondary circuit fault diagnosis system and method. BACKGROUND

[0002] In the operation of a power system, a current transformer (CT) as a key device undertakes the core task of accurately converting a large current on a primary side into a small current on a secondary side in proportion, and provides an accurate and reliable current signal for measurement instruments, protection devices and control equipment, and the stability and reliability of the CT secondary circuit directly relate to the safe operation of the entire power system.

[0003] However, in actual operation, the CT secondary circuit may have a multi-point grounding fault due to insulation aging, external damage, improper construction and various other factors, and such a fault may cause abnormal circulating current in the secondary circuit, thereby affecting the measurement accuracy and the correctness of the protection action, and may even cause a system accident, which seriously threatens the safe and stable operation of the power system.

[0004] The traditional CT secondary circuit fault diagnosis scheme mainly relies on periodic inspection and manual judgment, and such a method is not only inefficient, but also may cause the fault influence range to expand due to untimely troubleshooting, thereby reducing the reliability of the power system. SUMMARY

[0005] Embodiments of the present application provide a CT secondary circuit fault diagnosis system and method to solve the problem of low efficiency and accuracy of the CT secondary circuit fault diagnosis scheme in the related art, which reduces the reliability of the power system.

[0006] In a first aspect, embodiments of the present application provide a CT secondary circuit fault diagnosis system, comprising: a multi-parameter sensing module, a data analysis module and a fault positioning module connected in sequence;

[0007] The multi-parameter sensing module is arranged in a target CT secondary circuit, and is configured to obtain a shield layer circulating current and a neutral point grounding current of the target CT secondary circuit, convert the shield layer circulating current and the neutral point grounding current into a voltage signal, and send the voltage signal to the data analysis module;

[0008] The data analysis module is configured to obtain a characteristic amplitude and a phase observation value of the target CT secondary circuit according to the received voltage signal, and calculate a judgment result of a grounding state in the target CT secondary circuit based on the characteristic amplitude, the phase observation value and a preset parameter;

[0009] The fault location module is used to calculate the coordinates of the fault point based on the obtained grounding grid parameters and transient signals of the target secondary circuit when the judgment result indicates that a grounding fault exists.

[0010] In one feasible implementation, the multi-parameter sensing module includes a passive broadband composite grounding sensor and a computing unit;

[0011] The passive broadband composite grounding sensor includes a magnetic core, multiple coils, and a Hall element. It is used to collect the shielding circulating current and neutral point grounding current of the target CT secondary circuit.

[0012] The calculation unit is used to calculate the voltage signal based on the sensor parameters of the passive broadband composite grounding sensor, the shielding layer circulating current, and the neutral point grounding current.

[0013] In one feasible implementation, the sensor parameters include the number of coil turns, the effective cross-sectional area of ​​the coil, and the sensitivity of the Hall element; the calculation unit is specifically used for:

[0014] The voltage signal is calculated based on the number of coil turns, the effective cross-sectional area of ​​the coil, the sensitivity of the Hall element, the circulating current of the shielding layer, the neutral point grounding current, and the preset neutral point magnetic field reference value.

[0015] In one feasible implementation, the data analysis module includes a data processing unit and a status analysis unit;

[0016] The data processing unit is used to preprocess the received voltage signal and determine the characteristic amplitude and phase observation values ​​from the preprocessed voltage signal through time-frequency domain transformation.

[0017] The state analysis unit is used to calculate the judgment result of the grounding state in the secondary circuit of the target CT based on the characteristic amplitude, phase observation value and preset parameters.

[0018] In one feasible implementation, the data processing unit is specifically used for:

[0019] The characteristic amplitude is calculated based on the frequency of the voltage signal, the preset number of sampling points, the preprocessed signal value of the sampling points in the voltage signal, the preset sampling point index, the preset amplitude correction coefficient, and the high-frequency energy compensation factor.

[0020] In one feasible implementation, the state analysis unit is specifically used for:

[0021] The degradation acceleration of the grounding state is calculated based on the formula for calculating the grounding state degradation acceleration.

[0022] The grounding status judgment result is calculated based on the deterioration acceleration, characteristic amplitude, phase observation value and preset parameters.

[0023] In one feasible implementation, the system also includes:

[0024] The verification module is used to calculate the multi-source consistency index and multi-source data reliability weight based on the fault point coordinates, shielding layer circulating current, and neutral point grounding current; and to verify the credibility of the grounding status judgment result based on the multi-source consistency index and multi-source data reliability weight.

[0025] In one feasible implementation, the verification module is specifically used for:

[0026] The shielding layer circulating current and neutral point grounding current are calculated based on the Kappa coefficient formula to obtain the multi-source consistency index.

[0027] Secondly, embodiments of this application provide a fault diagnosis method for a CT secondary circuit, applied to a fault diagnosis system for a CT secondary circuit as described in any of the first aspects of this application. The method includes:

[0028] Collect the shielding circulating current and neutral point grounding current of the target CT secondary circuit;

[0029] Convert the shielding circulating current and neutral point grounding current into voltage signals;

[0030] Based on the voltage signal, the characteristic amplitude and phase observation values ​​of the target CT secondary circuit are calculated;

[0031] Based on the characteristic amplitude, phase observation value and preset parameters, the judgment result of the grounding state in the secondary circuit of the target CT is calculated;

[0032] When the judgment result indicates the presence of a grounding fault, the coordinates of the fault point are calculated based on the obtained grounding grid parameters and transient signals of the target secondary circuit.

[0033] In one feasible implementation, after calculating the coordinates of the fault point, the method further includes:

[0034] Based on the fault point coordinates, shielding layer circulating current, and neutral point grounding current, the multi-source consistency index and multi-source data reliability weight are calculated.

[0035] The reliability of the grounding status judgment result is verified based on the multi-source consistency index and the multi-source data reliability weight.

[0036] The fault diagnosis system and method for CT secondary circuits provided in this application construct a real-time diagnostic system for multi-point grounding faults in the CT secondary circuit by setting up a multi-parameter sensing module, a data analysis module, and a fault location module connected in sequence in the system. The multi-parameter sensing module acquires the shielding layer circulating current and neutral point grounding current of the target CT secondary circuit, converts the shielding layer circulating current and neutral point grounding current into voltage signals, and sends the voltage signals to the data analysis module, realizing accurate capture of current signals across the entire frequency band and effectively identifying weak abnormal changes in the shielding layer circulating current and neutral point grounding current.

[0037] The data analysis module obtains the characteristic amplitude and phase observation values ​​of the target CT secondary circuit based on the received voltage signal. Based on these values ​​and preset parameters, it calculates the grounding status judgment result in the target CT secondary circuit. By combining time-frequency domain energy coupling analysis technology, the characteristic amplitude and phase observation values ​​of the voltage signal are automatically extracted. Furthermore, through a dynamic hidden Markov model-based state degradation assessment mechanism, the development trend of grounding faults can be detected in advance, triggering early warnings in the initial stages of insulation performance degradation. This improves the fault identification response speed to the second level, thereby enhancing the real-time performance, accuracy, and reliability of CT secondary circuit fault diagnosis.

[0038] In addition, when the fault location module determines that a grounding fault exists, it calculates the coordinates of the fault point based on the grounding grid parameters and transient signals of the target secondary circuit. This enables high-precision location of multiple grounding faults in the CT secondary circuit and effectively solves the problem of positioning deviation caused by environmental interference in traditional methods. Attached Figure Description

[0039] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0040] Figure 1 This is a schematic diagram of the structure of the CT secondary circuit fault diagnosis system provided in the embodiments of this application;

[0041] Figure 2 This is a schematic diagram of another CT secondary circuit fault diagnosis system provided in an embodiment of this application;

[0042] Figure 3 A flowchart of a CT secondary circuit fault diagnosis method provided in an embodiment of this application;

[0043] Figure 4 A flowchart of another CT secondary circuit fault diagnosis method provided in the embodiments of this application;

[0044] Figure 5 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application.

[0045] The accompanying drawings illustrate specific embodiments of this application, which will be described in more detail below. These drawings and descriptions are not intended to limit the scope of the concept in any way, but rather to illustrate the concept of this application to those skilled in the art through reference to particular embodiments. Detailed Implementation

[0046] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, 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, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0047] Before introducing the embodiments of this application, the terms used in the embodiments will be explained first:

[0048] Current transformer (CT) secondary circuit: refers to the electrical connection between the secondary winding of the current transformer and related measuring instruments, protection equipment or control devices.

[0049] Shielding layer circulating current: refers to the circulating current flowing in the cable shielding layer, driven by the grounding potential difference.

[0050] Neutral point grounding current: In a power system, when the neutral point is grounded in some way, the current flowing between the grounding point or grounding device and the earth. The neutral point typically refers to the star connection point of a transformer or generator winding.

[0051] Next, the application background of the embodiments of this application will be explained:

[0052] In the operation of power systems, current transformers (CTs) are key equipment, undertaking the core task of accurately converting large primary currents into small secondary currents in proportion, providing accurate and reliable current signals for measuring instruments, protection devices, and control equipment. The stability and reliability of the CT secondary circuit are directly related to the safe operation of the entire power system.

[0053] However, in actual operation, the secondary circuit of the CT may experience multiple grounding faults due to various factors such as insulation aging, external force damage, and improper construction. Such faults can lead to abnormal circulating currents in the secondary circuit, which in turn affect the measurement accuracy, interfere with the correctness of protection actions, and may even cause system accidents, posing a serious threat to the safe and stable operation of the power system.

[0054] Traditional CT secondary circuit fault diagnosis methods mainly rely on periodic inspections and manual judgment. This method is not only inefficient, but also makes it difficult to achieve real-time monitoring and early warning. Specifically, periodic inspections are limited by the inspection cycle and the arrangement of inspection personnel, and cannot detect potential multi-point grounding faults in a timely manner. Especially in the early stage of the fault, the fault characteristics may not be obvious and are easily overlooked, thus missing the best time for treatment.

[0055] Secondly, human judgment is greatly affected by subjective factors. Different people may have different judgments on the same fault phenomenon, which leads to inconsistencies in the diagnostic results and reduces the accuracy and reliability of the diagnosis.

[0056] Furthermore, traditional methods lack the ability to accurately locate faults. In the event of a multi-point grounding fault, significant time and manpower are often required to investigate each point individually, increasing maintenance costs and potentially expanding the fault's impact due to delayed investigation, thus increasing system risk. Moreover, with the increasing scale and complexity of power systems, traditional diagnostic methods are no longer sufficient to meet the high safety and reliability requirements of modern power systems.

[0057] Based on this, this application proposes a CT secondary circuit fault diagnosis system with high real-time performance, high accuracy, and high reliability. The CT secondary circuit fault diagnosis system provided in this application integrates a multi-parameter sensing module, a data analysis module, a fault location module, and a verification module, realizing real-time monitoring and accurate diagnosis of the multi-point grounding status of the CT secondary circuit. In the multi-parameter sensing module, a passive broadband composite grounding sensor is used to collect current signals. Combined with a dynamic hidden Markov model and a ground grid coupling model, the grounding status is quickly determined and the fault point is located, effectively solving the problems of low efficiency and difficult location in traditional methods, and significantly improving the safety and reliability of the power system CT secondary circuit. Details not elaborated in detail are disclosed in the following embodiments.

[0058] The technical solution of this application will now be described in detail through specific embodiments. It should be noted that the following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments.

[0059] Figure 1 This is a schematic diagram of the CT secondary circuit fault diagnosis system provided in the embodiments of this application. Figure 2 This is a schematic diagram of another CT secondary circuit fault diagnosis system provided in an embodiment of this application. Please also refer to... Figure 1 and Figure 2 The system may include: a multi-parameter sensing module 110, a data analysis module 120, and a fault location module 130 connected in sequence.

[0060] The multi-parameter sensing module 110 is installed in the secondary circuit of the target CT scanner. This multi-parameter sensing module 110 can be used to acquire the shielding layer circulating current and the neutral point grounding current of the target CT secondary circuit, convert the shielding layer circulating current and the neutral point grounding current into voltage signals, and send the voltage signals to the data analysis module 120.

[0061] The data analysis module 120 is used to obtain the characteristic amplitude and phase observation values ​​of the target CT secondary circuit based on the received voltage signal, and to calculate the judgment result of the grounding state in the target CT secondary circuit based on the characteristic amplitude, phase observation values ​​and preset parameters.

[0062] The fault location module 130 is used to calculate the coordinates of the fault point based on the obtained grounding grid parameters and transient signals of the target secondary circuit when the judgment result indicates that a grounding fault exists.

[0063] In one feasible implementation, the multi-parameter sensing module 110 may include a passive broadband composite grounding sensor 1101 and a computing unit 1102. Specifically, the passive broadband composite grounding sensor 1101 may be deployed on the shielding layer and neutral grounding line of the target CT secondary circuit to collect the shielding layer circulating current and neutral grounding current of the target CT secondary circuit in real time.

[0064] Specifically, the passive broadband composite grounding sensor 1101 may include a magnetic core, multiple sets of coils, and a Hall element. The magnetic core may be made of a nanocrystalline alloy material. In one example, the initial permeability of the passive broadband composite grounding sensor 1101 should be greater than or equal to 80,000, the turns ratio of the multiple sets of coils should be in the range of 1:5 to 1:20, the linearity error of the Hall element should not exceed 0.5%, and the detection frequency range of the passive broadband composite grounding sensor 1101 should be 50Hz-1MHz.

[0065] The calculation unit 1102 in the multi-parameter sensing module 110 is used to calculate the voltage signal based on the sensor parameters of the passive broadband composite grounding sensor 1101, the shielding layer circulating current, and the neutral point grounding current. The sensor parameters include the number of coil turns, the effective cross-sectional area of ​​the coil, and the sensitivity of the Hall element. Specifically, the calculation unit 1102 can calculate the voltage signal using a broadband current-voltage composite conversion formula, that is, based on the number of coil turns, the effective cross-sectional area of ​​the coil, the Hall element sensitivity, the shielding layer circulating current, the neutral point grounding current, and a preset neutral point magnetic field reference value.

[0066] The formula for calculating the broadband current-voltage composite conversion is as follows:

[0067]

[0068] In the formula, U is the voltage signal, α is the adaptive gain, which is dynamically adjusted according to the composite sensing coefficient, ξ is the composite sensing coefficient, which is determined based on the sensing characteristics of the magnetic core and Hall element in the sensor parameters, N is the number of coil turns in the sensor parameters, S is the effective cross-sectional area of ​​the coil in the sensor parameters, and I... 环 For shielding layer circulating current (mA level), K H Here, B0 represents the Hall element sensitivity in the sensor parameters, and I represents the neutral point magnetic field reference value. 中 This is the neutral point grounding current (in μA).

[0069] In one feasible implementation, the data analysis module 120 includes a data processing unit 1201 and a state analysis unit 1202. The data processing unit 1201 preprocesses the received voltage signal and determines the characteristic amplitude and phase observation values ​​from the preprocessed voltage signal through time-frequency domain transformation. The state analysis unit 1202 calculates the judgment result of the grounding state in the target CT secondary circuit based on the characteristic amplitude, phase observation values, and preset parameters.

[0070] Specifically, the data processing unit 1201 can calculate the characteristic amplitude based on the frequency of the voltage signal, the preset number of sampling points, the preprocessed signal value of the sampling points in the voltage signal, the preset sampling point index, the preset amplitude correction coefficient, and the high-frequency energy compensation factor.

[0071] In one example, when the data processing unit 1201 calculates the characteristic amplitude, it can use the time-frequency domain energy coupling amplitude calculation formula:

[0072]

[0073] In the formula, A(f) is the characteristic amplitude, β is the amplitude correction coefficient, which is obtained by calibration with a standard signal, n is the sampling point index, N is the number of sampling points, which is usually 1024 or 2048, i(n) is the preprocessed signal value of the nth sampling point, f is the frequency, and δ is the high-frequency energy compensation factor.

[0074] When calculating the judgment result of the grounding state, the state analysis unit 1202 first calculates the degradation acceleration of the grounding state according to the grounding state degradation acceleration calculation formula. This degradation acceleration of the grounding state is used to quantify the deterioration rate of the grounding state.

[0075] The formula for calculating the grounding condition degradation acceleration is as follows:

[0076] In the formula, a is the degradation acceleration, which reflects the rate of deterioration of the grounding condition; λ is the resistance influence coefficient, whose value range can be set to, for example, 0.01-0.1; ΔR is the change in grounding resistance, that is, the difference between the grounding resistance and the reference resistance. The circulation change rate is the amount of change in circulation per unit time.

[0077] Then, based on the degradation acceleration, characteristic amplitude, phase observation value, and preset parameters, the judgment result of the grounding state is calculated. Among them, the preset parameters are historical grounding state parameters stored in the system.

[0078] In one example, after calculating the degradation acceleration of the grounding state, the degradation acceleration, characteristic amplitude, phase observation value, and historical grounding state parameters are input into the dynamic hidden Markov model. The dynamic hidden Markov model calculates the probability that the current grounding state belongs to the normal state, insulation degradation state, and multi-point grounding state through the built-in state transition probability matrix and observation probability matrix, and obtains the grounding state judgment result based on these probability values.

[0079] It should be noted that when the grounding status is determined to be normal, it indicates that the CT secondary circuit is in a normal state, and the fault location module 130 does not need to be triggered to calculate the fault point coordinates. However, when the grounding status is determined to be in an insulation deterioration state, it indicates that the CT secondary circuit is in a potential fault state; or, when the grounding status is determined to be in a multi-point grounding state, it indicates that the CT secondary circuit is in a fault state. Therefore, when the node status is determined to be in an insulation deterioration state or a multi-point grounding state, the fault location module 130 needs to be triggered to calculate the fault point coordinates.

[0080] Specifically, when the fault location module 130 determines that a grounding fault exists, it can calculate the coordinates of the fault point based on the grounding grid parameters and transient signals of the target CT secondary circuit.

[0081] The ground network parameters may include soil resistivity, linear spacing between sensors, and current-to-impedance conversion coefficient. These parameters are basic parameters obtained from pre-survey or maintenance re-survey of the power scene where the target CT secondary circuit is located. The transient signal refers to the difference in shielding current between sensors. This difference is obtained by processing the original shielding current collected by the multi-parameter sensing module 110 after processing by the data processing module.

[0082] In one example, when the fault location module 130 calculates the fault point coordinates based on the ground grid parameters and transient signals of the target CT secondary circuit, it can use the ground grid-circulating current coupling impedance calculation formula. Specifically, the ground grid-circulating current coupling impedance calculation formula is as follows:

[0083] Z ij=ρ·ln(d ij / r i )+η·I 环,ij ;

[0084] In the formula, Z ij Let ρ be the ground grid impedance coupling factor between sensors i and j, ρ be the soil resistivity, and d be the ground grid impedance coupling factor. ij Let r be the linear distance between sensors i and j. i Where η is the distance from the fault point to sensor i, and I is the circulating current-to-impedance conversion coefficient. 环,ij The difference in the circulating current of the shielding layer at sensor i and j is denoted as .

[0085] It is understandable that in the above formula for calculating the ground grid-circulating current coupling impedance, the ground grid parameters and transient signals are known quantities. The ground grid impedance coupling factor can be obtained through actual measurement or derivation. Therefore, the distance from the fault point to sensor i can be solved by reverse calculation. Then, combined with multiple distance values ​​calculated by at least two different sensors, the coordinates of the fault point can be determined based on the geometric positioning principle.

[0086] Furthermore, in order to verify the reliability of the grounding status judgment result, in this embodiment, the CT secondary circuit fault diagnosis system may also include: a verification module 140, used to calculate the multi-source consistency index and multi-source data reliability weight based on the fault point coordinates, shielding layer circulating current and neutral point grounding current; and to verify the reliability of the grounding status judgment result based on the multi-source consistency index and multi-source data reliability weight.

[0087] Specifically, the verification module 140 can calculate the shielding layer circulating current and neutral point grounding current based on the Kappa coefficient calculation formula to obtain the multi-source consistency index.

[0088] The specific calculation process includes: first, statistically analyzing the judgment results of multiple source data for the same grounding state to obtain the actual number of consistent judgments and the expected number of consistent judgments; then, calculating the Kappa coefficient using the formula... Calculate the multi-source consistency index, where, N is the total number of decisions. m is the number of grounding state categories, R i Let C be the total number of decisions for the i-th type of state. i (where is the expected number of determinations for the i-th type of state), and the Kappa coefficient ranges from -1 to 1. The multi-source data includes shielding circulating current, neutral point grounding current, and transient ground potential data.

[0089] The term "same grounding state" refers to the system's preset classification standard for the grounding state of the CT secondary circuit. Specifically, the state analysis unit 1202 defines three fixed states based on a dynamic hidden Markov model containing three states: normal state, insulation degradation state, and multi-point grounding state. This clear definition of "same" is the foundation for the verification module 104 to calculate the multi-source consistency index using the Kappa coefficient. Only with a unified state classification standard and consistent judgment objects and time periods can the number of consistent judgments of multi-source data on the "same grounding state" be accurately counted, thereby verifying the reliability of the grounding state judgment results and reducing the risk of misjudgment.

[0090] It should be noted that the reliability weight of multi-source data is determined based on the data standard deviation; the smaller the standard deviation, the greater the reliability weight. Specifically, the formula for calculating the reliability weight of multi-source data is: Where, ω k σ represents the weight of the k-th type of data, where k = 1, 2, 3 correspond to the shielding circulating current, neutral point grounding current, and transient ground potential data, respectively. k is the standard deviation of the k-th class of data, used to reflect the degree of data dispersion.

[0091] When verifying the reliability of the grounding status judgment result based on the multi-source consistency index and the multi-source data reliability weight, the specific method can be determined using the formula... The reliability is calculated. Among them, C is the reliability of the grounding status judgment result, C1 is the multi-source consistency index, C2 is the trend consistency, and C3 is the case matching score, with a value range of 0 to 1.

[0092] The trend fit was measured using the Spearman rank correlation coefficient, which was calculated as follows: the time series of multi-source data were ranked to obtain the rank sequences x1, x2, ..., x of the two sets of data. n With y1, y2, ..., y n Where n is the number of data sampling points, the difference between each pair of levels is calculated as di = xi - yi, and then the result is obtained using the formula... To calculate the trend correlation, the Spearman rank correlation coefficient ranges from -1 to 1.

[0093] The logic for determining the case matching score is as follows: First, a database containing historical multi-point grounding fault cases is constructed. Each case stores key features such as historical shielding layer circulating current, historical neutral point grounding current, and historical grounding grid transient potential, as well as the corresponding historical grounding status. In the current diagnosis, the processed real-time fault feature data is extracted and compared with the features of historical cases using a similarity algorithm to quantify the matching degree. A score ranging from 0 to 1 is assigned according to the matching degree (the higher the matching degree, the closer the score is to 1). This score is used as C3 and substituted into the credibility calculation formula of the verification module 104 to participate in the verification of the reliability of the grounding status determination result.

[0094] In one example, the confidence threshold is set to 0.85. When the confidence level C ≥ 0.85, the judgment result of the grounding status is considered valid.

[0095] The CT secondary circuit fault diagnosis system provided in this application embodiment constructs a real-time diagnosis system for multi-point grounding faults in the CT secondary circuit by setting up a multi-parameter sensing module 110, a data analysis module 120, and a fault location module 130 connected in sequence in the system. The multi-parameter sensing module 110 acquires the shielding layer circulating current and neutral point grounding current of the target CT secondary circuit, converts the shielding layer circulating current and neutral point grounding current into voltage signals, and sends the voltage signals to the data analysis module 120, realizing accurate capture of current signals across the entire frequency band and effectively identifying weak abnormal changes in the shielding layer circulating current and neutral point grounding current.

[0096] The data analysis module 120 obtains the characteristic amplitude and phase observation values ​​of the target CT secondary circuit based on the received voltage signal. Based on these characteristic amplitude and phase observation values ​​and preset parameters, it calculates the grounding status judgment result in the target CT secondary circuit. In this way, by combining time-frequency domain energy coupling analysis technology, the characteristic amplitude and phase observation values ​​of the voltage signal are automatically extracted. Furthermore, through a dynamic hidden Markov model-based state degradation assessment mechanism, the development trend of grounding faults can be detected in advance, triggering an early warning in the initial stage of insulation performance degradation. This improves the fault identification response speed to the second level, thereby enhancing the real-time performance, accuracy, and reliability of CT secondary circuit fault diagnosis.

[0097] When the fault location module 130 determines that a grounding fault exists, it calculates the coordinates of the fault point based on the grounding grid parameters and transient signals of the target secondary circuit. This achieves high-precision location of multiple grounding faults in the CT secondary circuit and effectively solves the problem of positioning deviation caused by environmental interference in traditional methods.

[0098] In addition, the system adopts a passive sensor design, which does not require external power supply, avoiding the failure risk of active equipment in strong electromagnetic fields, and improving the stability and reliability of on-site operation. The verification module 140 dynamically optimizes the diagnostic logic through multi-source data consistency analysis and historical case matching mechanism, so that the system can still maintain efficient operation under complex working conditions. It provides a highly adaptable technical solution for the intelligent operation and maintenance of substation CT secondary circuits, and significantly shortens the fault diagnosis time.

[0099] The application process of the CT secondary circuit fault diagnosis system provided in this embodiment will be described in detail below, taking two specific application scenarios as examples.

[0100] In one example, suppose the application scenario is: applying the fault diagnosis system of the CT secondary circuit to the multi-point grounding diagnosis of the CT secondary circuit in a 220kV substation.

[0101] In the distribution equipment area of ​​a 220kV substation, the secondary circuit of the CT is a key component of the relay protection and metering system. The stability of its grounding status directly affects the safe operation of the power grid. In order to realize real-time monitoring of multiple grounding points of this circuit, the operation and maintenance personnel deployed the fault diagnosis system of this embodiment.

[0102] First, passive broadband composite grounding sensors 1101 are installed on the secondary circuit shielding layer and neutral grounding line of multiple CT devices in the substation. These passive broadband composite grounding sensors 1101 cleverly utilize electromagnetic induction and thermoelectric conversion technology to obtain energy from the surrounding environment, without the need for additional cable power supply, and are perfectly adapted to the complex electrical environment of the substation.

[0103] After the multi-parameter sensing module 110 is started, the passive broadband composite grounding sensor 1101 immediately starts working, continuously capturing subtle changes in the shielding layer circulating current and the neutral point grounding current. Then, through broadband current-voltage composite conversion, these current signals are converted into voltage signals that are easy to transmit and process, and smoothly transmitted to the data processing module.

[0104] The formula for wideband current-voltage composite conversion is: Where U is the sensor output voltage, α is the adaptive gain (dynamically adjusted according to the composite sensing coefficient), ξ is the composite sensing coefficient (combining the sensing characteristics of the magnetic core and the Hall element), N is the number of coil turns, S is the effective cross-sectional area of ​​the coil, and I... 环 For shielding layer circulating current (mA level), K H Where B0 is the sensitivity of the Hall element, and I is the reference value of the neutral point magnetic field. 中 This is the neutral point grounding current (in μA).

[0105] After receiving the voltage signal, the data processing unit 1201 first performs comprehensive preprocessing: noise reduction filters out high-frequency electromagnetic interference generated by circuit breaker operation and transformer operation within the substation, making the signal cleaner; smoothing weakens sudden fluctuations in the signal, making the waveform more stable; finally, normalization is performed to unify signals of different magnitudes to the same scale, laying the foundation for subsequent analysis. After preprocessing, the data processing unit 1201 uses time-frequency domain transformation technology and a time-frequency domain energy coupling amplitude extraction method to accurately extract characteristic amplitudes and phases that reflect the circuit state from the signal. These characteristic parameters are then output as observed values ​​to the state analysis module in real time. The formula for calculating the time-frequency domain energy coupling amplitude is:

[0106] Where A(f) is the characteristic amplitude, β is the amplitude correction coefficient, n is the sampling point index, N is the number of sampling points, i(n) is the preprocessed signal value of the nth sampling point, f is the frequency, and δ is the high-frequency energy compensation factor.

[0107] The state analysis unit 1202 is pre-loaded with a dynamic hidden Markov model, which includes three states: normal state, insulation degradation state, and multi-point grounding state. This model can simulate the evolution of the loop grounding state. After receiving the characteristic amplitude and phase observations, the state analysis unit 1202 combines historical data and training parameters accumulated over many years of operation and maintenance to calculate the grounding state degradation acceleration. The formula for calculating the grounding state degradation acceleration is as follows: Where a is the degradation acceleration, λ is the resistance influence coefficient, and ΔR is the change in grounding resistance. The rate of change of circulation.

[0108] Among them, the three states correspond to the normal state, the insulation deterioration state, and the multi-point grounding state, respectively. The probability of the current state transitioning to other states and the degree of matching between the observed values ​​and each state are analyzed to clearly determine the current grounding state of the CT secondary circuit. If the judgment result shows that there is a risk of insulation deterioration or multi-point grounding, the state information is immediately transmitted to the fault location module 130.

[0109] After receiving the warning, the fault location module 130 quickly invokes the grounding grid transient potential rise-circulating current coupling model. This model is constructed based on the actual topology of the substation grounding grid (including the arrangement of grounding electrodes, the specifications of connecting conductors, etc.), the layered resistivity characteristics of the soil, and the electromagnetic coupling relationship between the grounding grid and the circuit.

[0110] Combining real-time acquired transient signals and known grounding grid parameters, the module calculates the grounding grid-circulating current coupling impedance using the following formula: Z ij =ρ·ln(d ij / r i)+η·I 环,ij Among them, Z ij Let ρ be the ground grid impedance coupling factor between sensors i and j, ρ be the soil resistivity, and d be the ground grid impedance coupling factor. ij Let r be the linear distance between sensors i and j. i Where η is the distance from the fault point to sensor i, and I is the circulating current-to-impedance conversion coefficient. 环,ij The difference in circulating current in the shielding layer at sensors i and j is used to analyze the impedance correlation between different sensors and the distance difference from the fault point to each sensor. Finally, the specific location of the fault point in the substation is accurately located, such as the damaged grounding point of a cable or the accidental short circuit point of a terminal block.

[0111] At this point, the verification module 140 begins to integrate the judgment results of the status analysis module and the coordinate information of the fault location module 130, calculates the multi-source consistency index to check the consistency of data from different sensors, evaluates the trend consistency to confirm the matching of the current state with the historical fault development trend, and performs case matching scoring to compare the current anomaly with typical fault cases in the database.

[0112] Next, reasonable weights are assigned to each indicator through multi-source data reliability weight calculation. The calculation logic of the multi-source data reliability weight formula is as follows: dynamic weights are determined based on the data standard deviation; the smaller the standard deviation, the greater the weight. Specifically, weights are assigned based on the exponential decay relationship of the data variance. The multi-source consistency index is calculated using the Kappa coefficient, and the trend consistency is measured using the Spearman rank correlation coefficient. Finally, the overall diagnostic results are verified using a comprehensive reliability calculation method. The formula for calculating the comprehensive reliability of diagnostic results is: Where C represents the reliability of the diagnostic results, C1 represents the multi-source consistency index, C2 represents the trend consistency, and C3 represents the case matching score.

[0113] The reliability threshold is set to 0.85. When C≥0.85, the diagnostic result is considered valid. If the verification passes, the system automatically generates a detailed diagnostic report, clearly indicating the fault location, severity, and suggested handling solution, and pushes it to the terminal device of the maintenance personnel. If it fails, the data is sent back to the data processing module for reprocessing to ensure that every diagnostic result is accurate and reliable.

[0114] In summary, in the 220kV substation scenario, the fault diagnosis system for the CT secondary circuit of this application achieves unpowered monitoring of critical circuits by deploying broadband composite grounding sensors. Through the collaborative work of the multi-parameter sensing module 110, data processing unit 1201, state analysis unit 1202, fault location module 130, and verification module 140, the entire process from signal acquisition to result output is fully presented. The application of key technologies such as broadband current-voltage composite conversion and time-frequency domain energy coupling amplitude extraction ensures the accuracy of signal processing. The dynamic hidden Markov model combined with grounding state degradation acceleration calculation enables accurate judgment of the circuit state. The calculation of ground grid-circulating current coupling impedance ensures the accuracy of fault location. The closed-loop verification mechanism provides dual protection for the reliability of diagnostic results through multi-source data reliability weight calculation and comprehensive reliability calculation of diagnostic results. This effectively meets the substation's need for real-time monitoring and accurate location of multi-point grounding faults in the CT secondary circuit, contributing to improved substation operation and maintenance efficiency and the safe operation level of the power grid.

[0115] In another example, suppose the application scenario is: applying the fault diagnosis system of the CT secondary circuit to the multi-point grounding diagnosis of the CT secondary circuit in a large thermal power plant.

[0116] In this scenario, the secondary circuit of the CT is connected to the protection and measurement systems of core equipment such as generators and main transformers. Once multiple grounding occurs, it may lead to serious consequences such as protection malfunction and equipment damage. Therefore, the thermal power plant uses the fault diagnosis system of this embodiment to monitor the secondary circuit of the CT around the clock.

[0117] First, passive broadband composite grounding sensors 1101 are installed on the shielding layer of the secondary circuit of the CT of each unit in the plant and on the neutral point grounding line. These passive broadband composite grounding sensors 1101 are resistant to the high temperature and high humidity of the power plant environment and do not require external power supply. They can maintain operation by collecting the electromagnetic energy during the operation of the equipment.

[0118] After the multi-parameter sensing module 110 is activated, the passive broadband composite grounding sensor 1101 continuously collects the shielding layer circulating current and the neutral point grounding current. Subsequently, it converts the current signal into a voltage signal through a broadband current-to-voltage composite converter, and transmits it to the data processing module in the central control room via a dedicated communication line. The broadband current-to-voltage composite conversion calculation formula is as follows:

[0119]

[0120] After receiving the voltage signal, the data processing unit 1201 first performs targeted noise reduction processing to filter out interference signals in specific frequency bands in response to the strong electromagnetic interference generated by equipment such as motors and fans in the thermal power plant; then it performs smoothing processing to eliminate high-frequency jitter in the signal and make the waveform more stable; finally, it performs normalization processing to unify the data format and magnitude.

[0121] After preprocessing, the data processing unit 1201 uses time-frequency domain transformation technology and a time-frequency domain energy coupling amplitude extraction method to extract characteristic amplitudes and phases from the complex voltage signal. These are then sent to the state analysis unit 1202 as characteristic amplitude and phase observations reflecting the loop state. The formula for calculating the time-frequency domain energy coupling amplitude is as follows:

[0122]

[0123] The state analysis unit 1202 is based on a dynamic hidden Markov model containing three states (normal state, insulation degradation state, and multi-point grounding state). It combines historical operating data and fault records from the secondary circuit of the thermal power plant's CT system. The grounding state degradation acceleration calculation formula is as follows: By analyzing the matching probability of the current observation value with each state and the possibility of transition between states, the grounding status of the circuit can be accurately determined. When a potential multi-point grounding hazard is found, the status information is immediately sent to the fault location module 130.

[0124] After receiving the information, the fault location module 130 invokes a pre-built grounding grid transient potential rise-circulating current coupling model. This model covers the detailed structure of the power plant's grounding grid (including the grounding grid connection methods and grounding electrode materials in different areas), the stratification characteristics of the plant's soil (considering the resistivity differences of soil at different depths), and electromagnetic coupling laws. Combining the real-time acquired grounding grid transient signals and known grounding grid parameters, the module calculates the grounding grid-circulating current coupling impedance using the formula: Z ij =ρ·ln(d ij / r i )+η·I 环,ij The correlation between the monitoring data of each sensor is analyzed, the distance difference between the fault point and each sensor is calculated, and finally the specific location of the fault point in the factory area is determined, such as the insulation damage point of a CT cable led from the generator or the abnormal connection point of the grounding terminal in the protection panel.

[0125] The verification module 140 integrates the status judgment results and fault point coordinates, calculates a multi-source consistency index to verify the consistency of data from different sensors, evaluates trend consistency to confirm the alignment between current status changes and historical fault development trends, and simultaneously performs case matching scoring. Referring to past experience in handling similar faults in thermal power plants, the weights of each indicator are determined through multi-source data reliability weight calculation. Finally, the comprehensive reliability calculation method for diagnostic results is used to verify the diagnostic results. The formula for calculating the comprehensive reliability of diagnostic results is as follows:

[0126] If the verification passes, the system generates a diagnostic report and sends it to the on-duty personnel to guide them in troubleshooting the fault in a timely manner; if it fails, the data is sent back to the data processing module for reprocessing to ensure the accuracy of the diagnostic results and provide strong support for the safe and stable operation of the thermal power plant.

[0127] In summary, in the context of large-scale thermal power plants, the fault diagnosis system of this embodiment is fully adaptable to the complex environment of high temperature, high humidity, and strong electromagnetic interference. It achieves continuous monitoring of the CT secondary circuit through the passive broadband composite grounding sensor 1101. The system's modules have clearly defined roles: the multi-parameter sensing module 110 completes signal acquisition and conversion; the data processing unit 1201 performs signal purification and feature extraction; the state analysis unit 1202 determines the circuit state based on a dynamic hidden Markov model and grounding state degradation acceleration calculation; the fault location module 130 locates the fault point based on the ground grid transient potential rise-circulating current coupling model and ground grid-circulating current coupling impedance calculation; and the verification module 140 ensures accurate results through multi-source data reliability weight calculation and comprehensive reliability calculation of diagnostic results. The entire process requires no external power supply and can accurately identify faults, providing reliable technical support for the safe operation of the CT secondary circuit in thermal power plants. This is of great significance for preventing equipment failures and production accidents caused by multi-point grounding.

[0128] The CT secondary circuit fault diagnosis system provided in the embodiments of this application has been described in detail above. The CT secondary circuit fault diagnosis method provided in the embodiments of this application will now be described with reference to the accompanying drawings.

[0129] Figure 3 This is a flowchart illustrating a CT secondary circuit fault diagnosis method provided in an embodiment of this application. This method can be applied to, for example... Figure 1 and Figure 2 The CT secondary circuit fault diagnosis system shown. Specifically, the method may include the following steps:

[0130] Step 301: Collect the shielding circulating current and neutral point grounding current of the target CT secondary circuit.

[0131] Step 302: Convert the shielding circulating current and neutral point grounding current into voltage signals.

[0132] Step 303: Calculate the characteristic amplitude and phase observation values ​​of the target CT secondary circuit based on the voltage signal.

[0133] Step 304: Based on the characteristic amplitude, phase observation value and preset parameters, calculate the judgment result of the grounding state in the secondary circuit of the target CT.

[0134] Step 305: When the judgment result indicates that a grounding fault exists, calculate the coordinates of the fault point based on the obtained grounding grid parameters and transient signals of the target secondary circuit.

[0135] Specifically, the passive broadband composite grounding sensor in the CT secondary circuit fault diagnosis system is deployed between the shielding layer and the neutral grounding line of the CT secondary circuit. The passive broadband composite grounding sensor is activated to collect the circulating current in the shielding layer and the neutral grounding current. Then, the data is converted using a broadband current-voltage composite conversion formula. It is converted into a transmittable voltage signal.

[0136] In the formula, U is the voltage signal, α is the adaptive gain, which is dynamically adjusted according to the composite sensing coefficient, ξ is the composite sensing coefficient, which is determined based on the sensing characteristics of the magnetic core and Hall element in the sensor parameters, N is the number of coil turns in the sensor parameters, S is the effective cross-sectional area of ​​the coil in the sensor parameters, and I... 环 For shielding layer circulating current (mA level), K H Here, B0 represents the Hall element sensitivity in the sensor parameters, and I represents the neutral point magnetic field reference value. 中 This is the neutral point grounding current (in μA).

[0137] After the voltage signal is calculated, it is transmitted to the data processing unit, where denoising, smoothing, and normalization processes are performed sequentially. Then, the characteristic amplitude and phase observation values ​​in the voltage signal are extracted using the time-frequency domain energy coupling amplitude calculation formula. The time-frequency domain energy coupling amplitude calculation formula is as follows:

[0138]

[0139] In the formula, A(f) is the characteristic amplitude, β is the amplitude correction coefficient, which is obtained by calibration with a standard signal, n is the sampling point index, N is the number of sampling points, which is usually 1024 or 2048, i(n) is the preprocessed signal value of the nth sampling point, f is the frequency, and δ is the high-frequency energy compensation factor.

[0140] After obtaining the characteristic amplitude and phase observations, the state analysis unit calculates the degradation acceleration of the grounding state to quantify the deterioration rate of the grounding state. Specifically, the degradation acceleration can be expressed by the formula... The calculation yields the following values: α is the degradation acceleration, reflecting the rate of grounding condition deterioration; λ is the resistance influence coefficient, which can be set to, for example, 0.01-0.1; ΔR is the change in grounding resistance, i.e., the difference between the grounding resistance and the reference resistance. The circulation change rate is the amount of change in circulation per unit time.

[0141] It is understandable that when the grounding status is determined to be normal, it indicates that the CT secondary circuit is in a normal state, and there is no need to trigger the fault location module to calculate the fault point coordinates. However, when the grounding status is determined to be in an insulation deterioration state, it indicates that the CT secondary circuit is in a potential fault state; or, when the grounding status is determined to be in a multi-point grounding state, it indicates that the CT secondary circuit is in a fault state. Therefore, when the node status is determined to be in an insulation deterioration state or a multi-point grounding state, it is necessary to trigger the fault location module to calculate the fault point coordinates.

[0142] When calculating the coordinates of the fault point, the fault location module can do so based on the acquired grounding grid parameters and transient signals of the target CT secondary circuit. The grounding grid parameters may include soil resistivity, the linear spacing between sensors, and the current-to-impedance conversion coefficient. These parameters are fundamental parameters obtained from pre-survey or maintenance re-surveys of the power environment where the target CT secondary circuit is located. The transient signal refers to the difference in shielding current between sensors. This difference is obtained by processing the original shielding current collected by the multi-parameter sensing module after processing by the data processing module.

[0143] The fault location module can calculate the fault point coordinates based on the ground grid parameters and transient signals of the target CT secondary circuit, using the ground grid-circulating current coupling impedance calculation formula. Specifically, the ground grid-circulating current coupling impedance calculation formula is as follows:

[0144] Z ij =ρ·ln(d ij / r i )+η·I 环,ij ;

[0145] In the formula, Z ij Let ρ be the ground grid impedance coupling factor between sensors i and j, ρ be the soil resistivity, and d be the ground grid impedance coupling factor. ij Let r be the linear distance between sensors i and j. i Where η is the distance from the fault point to sensor i, and I is the circulating current-to-impedance conversion coefficient. 环,ij The difference in the circulating current of the shielding layer at sensor i and j is denoted as .

[0146] It is understandable that in the above formula for calculating the ground grid-circulating current coupling impedance, the ground grid parameters and transient signals are known quantities. The ground grid impedance coupling factor can be obtained through actual measurement or derivation. Therefore, the distance from the fault point to sensor i can be solved by reverse calculation. Then, combined with multiple distance values ​​calculated by at least two different sensors, the coordinates of the fault point can be determined based on the geometric positioning principle.

[0147] The method in this embodiment enables real-time monitoring and accurate diagnosis of multi-point grounding status in the secondary circuit of a ground fault detector (CT). By utilizing a passive broadband composite grounding sensor to collect current signals and combining a dynamic hidden Markov model with a ground grid coupling model, the grounding status is quickly determined and the fault location is pinpointed. This effectively solves the problems of low efficiency and difficult location in traditional methods, significantly improving the safety and reliability of the CT secondary circuit in the power system.

[0148] Figure 4 A flowchart illustrating another CT secondary circuit fault diagnosis method provided in this application embodiment. Figure 4 As shown, the CT secondary circuit fault diagnosis method provided in this embodiment may include the following steps:

[0149] Step 401: Collect the shielding circulating current and neutral point grounding current of the target CT secondary circuit.

[0150] Step 402: Convert the shielding layer circulating current and the neutral point grounding current into voltage signals.

[0151] Step 403: Calculate the characteristic amplitude and phase observation values ​​of the target CT secondary circuit based on the voltage signal.

[0152] Step 404: Based on the characteristic amplitude, phase observation value and preset parameters, calculate the judgment result of the grounding state in the secondary circuit of the target CT.

[0153] Step 405: When the judgment result indicates that a grounding fault exists, calculate the coordinates of the fault point based on the obtained grounding grid parameters and transient signals of the target secondary circuit.

[0154] Step 406: Calculate the multi-source consistency index and multi-source data reliability weight based on the fault point coordinates, shielding layer circulating current, and neutral point grounding current.

[0155] Step 407: Verify the credibility of the grounding status judgment result based on the multi-source consistency index and the multi-source data reliability weight.

[0156] The specific implementation process of steps 401-405 can be referred to the above. Figure 3 The relevant descriptions in steps 301-305 of the illustrated embodiment will not be repeated here.

[0157] In this embodiment, to further verify the reliability of the grounding status judgment result, the shielding layer circulating current and neutral point grounding current are calculated based on the Kappa coefficient calculation formula to obtain the multi-source consistency index, and the multi-source data reliability weight is determined based on the data standard deviation. It should be noted that the smaller the standard deviation, the greater the multi-source data reliability weight.

[0158] Specifically, when calculating the multi-source consistency index, the determination results of multi-source data for the same grounding state are first statistically analyzed to obtain the actual number of consistency determinations and the expected number of consistency determinations. Then, the Kappa coefficient is calculated using the formula. Calculate the multi-source consistency index, where, N is the total number of decisions. m is the number of grounding state categories, R i Let C be the total number of decisions for the i-th type of state. i (where is the expected number of determinations for the i-th type of state), and the Kappa coefficient ranges from -1 to 1. The multi-source data includes shielding circulating current, neutral point grounding current, and transient ground potential data.

[0159] In one example, the formula for calculating the reliability weight of multi-source data is: Where, ω k σ represents the weight of the k-th type of data, where k = 1, 2, 3 correspond to the shielding circulating current, neutral point grounding current, and transient ground potential data, respectively. k is the standard deviation of the k-th class of data, used to reflect the degree of data dispersion.

[0160] Then, according to the credibility calculation formula The reliability of the grounding status judgment result is calculated. Here, C represents the reliability of the grounding status judgment result, C1 is the multi-source consistency index, C2 is the trend consistency, and C3 is the case matching score, with values ​​ranging from 0 to 1.

[0161] In practical applications, the specific calculation process for trend consistency is as follows: The time-varying sequences of multi-source data are sorted into ranks to obtain the rank sequences x1, x2, ..., x... of the two sets of data. n With y1, y2, ..., y n Where n is the number of data sampling points, the difference between each pair of levels is calculated as di = xi - yi, and then the result is obtained using the formula... To calculate the trend correlation, the Spearman rank correlation coefficient ranges from -1 to 1.

[0162] If the confidence level reaches a preset threshold, the grounding status assessment is deemed valid, and a detailed diagnostic report is generated. This report clearly indicates the fault location, severity, and recommended handling measures. If the confidence level does not reach the preset threshold, the grounding status assessment is invalid, and no diagnostic report is generated.

[0163] The method in this embodiment enables real-time monitoring and accurate diagnosis of multi-point grounding status in the secondary circuit of a ground fault detector (CT). It utilizes a passive broadband composite grounding sensor to collect current signals, and combines a dynamic hidden Markov model with a ground grid coupling model to quickly determine the grounding status and locate the fault point. Furthermore, it can verify the reliability of the grounding status determination results based on the fault point coordinates, shielding layer circulating current, and neutral point grounding current. This effectively solves the problems of low efficiency and difficult location in traditional methods, significantly improving the safety and reliability of the secondary circuit of the CT in the power system.

[0164] It should be noted that the division of the various modules in the above system is merely a logical functional division. In actual implementation, they can be fully or partially integrated into a single physical entity, or they can be physically separated. Furthermore, these modules can be implemented entirely in software through processing element calls; they can be implemented entirely in hardware; or some modules can be implemented through processing element calls in software, while others are implemented in hardware. Additionally, these modules can be integrated together or implemented independently. The processing element here can be an integrated circuit with signal processing capabilities. During implementation, the steps of the above method or the various modules can be completed through integrated logic circuits in the hardware of the processor element or through software instructions.

[0165] Figure 5 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Figure 5 As shown, the electronic device 50 provided in this embodiment includes at least one processor 501 and a memory 502. Optionally, the device 50 further includes a communication component 503. The processor 501, memory 502, and communication component 503 are connected via a bus 504.

[0166] In a specific implementation, at least one processor 501 executes computer execution instructions stored in memory 502, causing at least one processor 501 to perform the above-described method.

[0167] The specific implementation process of processor 501 can be found in the above method embodiments, and its implementation principle and technical effect are similar. It will not be repeated here.

[0168] In the above embodiments, it should be understood that the processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), etc. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the method disclosed in this invention can be directly implemented by a hardware processor, or implemented by a combination of hardware and software modules within the processor.

[0169] The memory may include random access memory (RAM) and may also include non-volatile memory (NVM), such as at least one disk storage device.

[0170] 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. Buses can be categorized as address buses, data buses, control buses, etc. For ease of illustration, the buses shown in the accompanying drawings of this application are not limited to a single bus or a single type of bus.

[0171] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the above-described method.

[0172] This application also provides a computer-readable storage medium storing computer-executable instructions, which, when executed, implement any of the methods described above.

[0173] The aforementioned readable 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 storage, flash memory, magnetic disk, or optical disk. The readable storage medium can be any available medium accessible to a general-purpose or special-purpose computer.

[0174] An exemplary readable storage medium is coupled to a processor, enabling the processor to read information from and write information to the readable storage medium. Of course, the readable storage medium can also be a component of the processor. The processor and the readable storage medium can reside in an application-specific integrated circuit (ASIC). Alternatively, the processor and the readable storage medium can exist as discrete components in the device.

[0175] The division of units is merely a logical functional division; in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be indirect coupling or communication connection through some interfaces, devices, or units, and may be electrical, mechanical, or other forms.

[0176] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0177] In addition, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0178] If a function is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0179] Those skilled in the art will understand that all or part of the steps of the above-described method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When executed, the program performs the steps of the above-described method embodiments; and the aforementioned storage medium includes various media capable of storing program code, such as ROM, RAM, magnetic disks, or optical disks.

[0180] Finally, it should be noted that other embodiments of the invention will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This invention is intended to cover any variations, uses, or adaptations of the invention that follow the general principles of the invention and include common knowledge or customary techniques in the art not disclosed herein, and is not limited to the precise structures described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of the invention is limited only by the appended claims.

Claims

1. A fault diagnosis system for a CT secondary circuit, characterized in that, include: The multi-parameter sensing module, data analysis module, and fault location module are connected in sequence. The multi-parameter sensing module is located in the target CT secondary circuit and is used to acquire the shielding layer circulating current and the neutral point grounding current of the target CT secondary circuit, convert the shielding layer circulating current and the neutral point grounding current into voltage signals, and send the voltage signals to the data analysis module. The data analysis module is used to obtain the characteristic amplitude and phase observation values ​​of the target CT secondary circuit based on the received voltage signal, and to calculate the judgment result of the grounding state in the target CT secondary circuit based on the characteristic amplitude, the phase observation values ​​and preset parameters. The fault location module is used to calculate the coordinates of the fault point based on the obtained grounding grid parameters and transient signals of the target secondary circuit when the judgment result indicates that a grounding fault exists.

2. The system according to claim 1, characterized in that, The multi-parameter sensing module includes a passive broadband composite grounding sensor and a computing unit; The passive broadband composite grounding sensor includes a magnetic core, multiple sets of coils, and a Hall element. The passive broadband composite grounding sensor is used to collect the shielding layer circulating current and the neutral point grounding current of the target CT secondary circuit. The calculation unit is used to calculate the voltage signal based on the sensor parameters of the passive broadband composite grounding sensor, the shielding layer circulating current, and the neutral point grounding current.

3. The system according to claim 2, characterized in that, The sensor parameters include the number of coil turns, the effective cross-sectional area of ​​the coil, and the sensitivity of the Hall element; the calculation unit is specifically used for: The voltage signal is calculated based on the number of coil turns, the effective cross-sectional area of ​​the coil, the sensitivity of the Hall element, the circulating current of the shielding layer, the neutral point grounding current, and the preset neutral point magnetic field reference value.

4. The system according to claim 1, characterized in that, The data analysis module includes a data processing unit and a status analysis unit; The data processing unit is used to preprocess the received voltage signal and determine the characteristic amplitude and the phase observation value from the preprocessed voltage signal through time-frequency domain transformation. The state analysis unit is used to calculate the judgment result of the grounding state in the secondary circuit of the target CT based on the characteristic amplitude, the phase observation value and the preset parameters.

5. The system according to claim 4, characterized in that, The data processing unit is specifically used for: The characteristic amplitude is calculated based on the frequency of the voltage signal, the preset number of sampling points, the preprocessed signal value of the sampling points in the voltage signal, the preset sampling point index, the preset amplitude correction coefficient, and the high-frequency energy compensation factor.

6. The system according to claim 5, characterized in that, The state analysis unit is specifically used for: The degradation acceleration of the grounding state is calculated based on the formula for calculating the grounding state degradation acceleration. The determination result of the grounding state is calculated based on the degradation acceleration, the characteristic amplitude, the phase observation value, and the preset parameters.

7. The system according to claim 1, characterized in that, Also includes: The verification module is used to calculate the multi-source consistency index and the multi-source data reliability weight based on the fault point coordinates, the shielding layer circulating current, and the neutral point grounding current. The reliability of the grounding status determination result is verified based on the multi-source consistency index and the multi-source data reliability weight.

8. The system according to claim 7, characterized in that, The verification module is specifically used for: The multi-source consistency index is obtained by calculating the shielding layer circulating current and the neutral point grounding current based on the Kappa coefficient calculation formula.

9. A fault diagnosis method for a CT secondary circuit, applied to a fault diagnosis system for a CT secondary circuit as described in any one of claims 1-8, characterized in that, The method includes: Collect the shielding circulating current and neutral point grounding current of the target CT secondary circuit; The shielding layer circulating current and the neutral point grounding current are converted into voltage signals; Based on the voltage signal, the characteristic amplitude and phase observation values ​​of the target CT secondary circuit are calculated; Based on the characteristic amplitude, the phase observation value, and the preset parameters, the judgment result of the grounding state in the secondary circuit of the target CT is calculated; When the judgment result indicates the existence of a grounding fault, the coordinates of the fault point are calculated based on the obtained grounding grid parameters and transient signals of the target secondary circuit.

10. The method according to claim 9, characterized in that, After obtaining the coordinates of the fault point through calculation, the method further includes: Based on the fault point coordinates, the shielding layer circulating current, and the neutral point grounding current, the multi-source consistency index and the multi-source data reliability weight are calculated. The reliability of the grounding status determination result is verified based on the multi-source consistency index and the multi-source data reliability weight.

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