Phase difference-based cable three-phase unbalanced current detection method

Abstract

The invention discloses a cable three-phase unbalanced current detection method based on phase difference, and relates to the field of current sensing, and the method comprises the steps: carrying out the synchronous collection of three-phase current signals of a cable, and carrying out the preprocessing of the collected signals; an improved Hilbert-Huang transform method is adopted, and the instantaneous phase of each phase of current is extracted from the preprocessed three-phase current signals; calculating an instantaneous phase difference between any two phases based on the extracted instantaneous phase of each phase of current, and determining a three-phase current balance state of the cable according to the instantaneous phase difference; when it is judged that the three-phase instantaneous phase difference is in the unbalanced state, the fault type is recognized according to the abnormal mode of the three-phase instantaneous phase difference, corresponding fault response operation is executed, self-adaptive weighted fusion phase extraction of the multi-component signals is achieved through an improved Hilbert-Huang transform method, and the fault detection accuracy is improved by combining instantaneous phase difference calculation and abnormal mode recognition. And high-precision and high-real-time online detection and fault type discrimination of the three-phase imbalance state of the cable are realized.

Description

Technical Field

[0001] This application relates to the field of current sensing technology, and in particular to a method for detecting three-phase unbalanced current in cables based on phase difference. Background Technology

[0002] Existing technologies for detecting three-phase unbalanced current in cables mainly rely on traditional symmetrical component methods or current amplitude comparison methods. These methods determine the unbalanced state by calculating the negative-sequence and zero-sequence components of the three-phase current or by comparing amplitude differences. However, the symmetrical component method requires complex coordinate transformations and sequence component calculations, resulting in poor real-time performance; the current amplitude comparison method only reflects amplitude information and cannot capture implicit unbalances caused by phase shifts, and is easily affected by load fluctuations and harmonic interference, leading to insufficient detection sensitivity and reliability.

[0003] In recent years, methods based on instantaneous phase detection have gradually attracted attention, but existing technologies mostly use Fourier transform or traditional Hilbert transform to extract phase information. Fourier transform suffers from spectral leakage and picket-fence effects, making it difficult to accurately extract the instantaneous phase of non-stationary signals. While traditional Hilbert transform can obtain the instantaneous phase, it suffers from mode aliasing and endpoint effects when processing multi-component signals, leading to a decrease in phase estimation accuracy. Furthermore, existing methods lack an adaptive weighted fusion mechanism for the energy distribution of multi-component signals, resulting in poor stability of the phase extraction results, making it difficult to meet the high-precision and high-real-time requirements of online monitoring of three-phase imbalance in cables. Summary of the Invention

[0004] To address the aforementioned challenges, this application provides a method for detecting three-phase unbalanced current in cables based on phase difference. By employing an improved Hilbert-Huang transform method, adaptive weighted fusion phase extraction of multi-component signals is achieved. Combined with instantaneous phase difference calculation and abnormal pattern recognition, this method enables high-precision, high-real-time online detection and fault type identification of three-phase unbalanced cable conditions.

[0005] To achieve the above objectives, this application provides a method for detecting three-phase unbalanced current in cables based on phase difference, comprising the following steps: S1: Synchronously acquire the three-phase current signal of the cable and preprocess the acquired signal; S2: An improved Hilbert-Huang transform method is used to extract the instantaneous phase of each phase current from the preprocessed three-phase current signal; S3: Based on the instantaneous phase of each phase current extracted, calculate the instantaneous phase difference between any two phases, and determine the three-phase current balance state of the cable based on the instantaneous phase difference. S4: When the condition is determined to be unbalanced, the fault type is identified based on the abnormal pattern of the three-phase instantaneous phase difference, and the corresponding fault response operation is executed.

[0006] Preferably, the preprocessing includes filtering and denoising; the filtering and denoising includes wavelet thresholding and morphological filtering; the morphological filtering uses a hybrid morphological filter, including opening, closing and their combinations, to suppress pulse interference in the current signal.

[0007] Preferably, wavelet thresholding denoising specifically includes: Based on the signal-to-noise ratio of the three-phase current signal, the wavelet basis function and the number of decomposition levels are adaptively selected; The high-frequency wavelet coefficients are shrunk using an improved threshold function, which is: ; in, These are wavelet coefficients. For the threshold, and To adjust the parameters.

[0008] Preferably, the improved Hilbert-Huang transform method in step S2 specifically includes: S21: Perform empirical mode decomposition on the current signal to obtain multiple intrinsic mode function components; S22: Perform Hilbert transform on each intrinsic mode function component and extract the instantaneous phase; S23: Calculate the energy entropy of each component and determine the adaptive weights; S24: The instantaneous phase of each component is weighted and fused based on adaptive weights to obtain the final instantaneous phase estimate.

[0009] Preferably, the empirical mode decomposition in step S21 specifically includes: The current signal is adaptively filtered to obtain multiple components that satisfy the intrinsic mode function conditions. The decomposition process terminates when the filtering stopping criterion is met, and a residual term is generated. The residual term does not participate in the subsequent instantaneous phase extraction and fusion process.

[0010] Preferably, step S21 further includes a component screening step: Calculate the average instantaneous frequency of each intrinsic mode function component. ; Valid components that meet the following conditions will be selected for subsequent calculations: ; in, It is 0.5 times the power system frequency. It is 10 times the power frequency of the power system.

[0011] Preferably, the specific method for extracting the instantaneous phase in step S22 is as follows: Perform a Hilbert transform on each intrinsic mode function component to construct an analytic signal; Calculate instantaneous amplitude and instantaneous phase based on analytic signals; The calculated instantaneous phase is unwound, and a continuous instantaneous phase sequence is obtained by detecting the phase jump of adjacent sampling points and compensating for integer multiples of 2π. This sequence is then used for subsequent weighted fusion.

[0012] Preferably, the method for calculating the energy entropy and determining the adaptive weights in step S23 is as follows: Discretize and statistically analyze the instantaneous amplitudes of each intrinsic mode function component to construct an amplitude probability distribution, and calculate the energy entropy value of each component based on the definition of information entropy; The energy entropy of each component is normalized to obtain adaptive weights, so that the sum of the weight coefficients is 1, and the component with higher energy contribution is given a larger fusion weight.

[0013] Preferably, the specific method for calculating the instantaneous phase difference and determining the equilibrium state in step S3 is as follows: Based on the instantaneous phase of each phase current extracted, calculate the instantaneous phase difference between any two phases, including the phase difference between phases AB, BC, and CA. Compare each instantaneous phase difference with the predetermined theoretical phase difference; A permissible deviation threshold is set. When the deviation of each instantaneous phase difference from the predetermined theoretical phase difference is within the threshold range, the cable is determined to be in a three-phase balanced state. When the deviation of any instantaneous phase difference from the predetermined theoretical phase difference exceeds the threshold range, the cable is determined to be in a three-phase unbalanced state.

[0014] Preferably, step S4 specifically includes: Based on the calculated instantaneous phase difference of the three phases, combined with the synchronously acquired current amplitude information, the deviation relationship and the coupling relationship between the phase difference and the predetermined theoretical phase difference are analyzed. The results are matched with a variety of predefined fault characteristic modes to identify specific fault types. The fault types include single-phase ground fault, two-phase short-circuit fault, two-phase ground short-circuit fault, three-phase short-circuit fault, three-phase unbalance fault, harmonic interference fault, and phase loss fault. Based on the identified fault type, the system automatically executes the corresponding preset response operations. These response operations include triggering a graded alarm mechanism, recording the three-phase current waveforms and phase difference data at the time of the fault, and uploading fault information containing the fault type and timestamp to the monitoring center.

[0015] Therefore, this application employs the aforementioned method for detecting three-phase unbalanced current in cables based on phase difference, which has the following beneficial effects: It uses an improved Hilbert-Huang transform method, adaptively decomposing the signal into multiple intrinsic mode function components through empirical mode decomposition. Adaptive weights are calculated based on energy entropy for weighted fusion, effectively suppressing mode aliasing and endpoint effects, and improving phase extraction accuracy. In the preprocessing stage, adaptive wavelet threshold denoising combined with hybrid morphological filtering is used. The wavelet basis function and decomposition level are dynamically selected according to the signal-to-noise ratio, effectively filtering out harmonic interference and impulse noise, ensuring the stability and reliability of phase difference calculation. Based on the three-phase instantaneous phase difference feature vector and its abnormal modes, fault type identification can accurately distinguish different fault types such as single-phase grounding, two-phase short circuit, and severe three-phase imbalance, providing a reliable basis for fault location and emergency response.

[0016] The technical solution of this application will be further described in detail below with reference to the accompanying drawings and embodiments. Attached Figure Description

[0017] Figure 1 This is a schematic flowchart of a method for detecting three-phase unbalanced current in a cable based on phase difference, as described in this application. Detailed Implementation

[0018] The following detailed description of the embodiments of this application provided in the accompanying drawings is not intended to limit the scope of the claimed application, but merely to illustrate selected embodiments of the application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without inventive effort are within the scope of protection of this application.

[0019] Unless otherwise defined, the technical or scientific terms used in this application shall have the ordinary meaning as understood by a person of ordinary skill in the art to which this application pertains.

[0020] The terms "comprising" or "including," as used in this application, mean that the element preceding the term encompasses the element listed after the term, and do not exclude the possibility of encompassing other elements as well. The terms "inner," "outer," "upper," and "lower," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings, and are only for the convenience of describing this application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this application. When the absolute position of the described object changes, the relative positional relationship may also change accordingly. In this application, unless otherwise expressly specified and limited, the term "attached," etc., should be interpreted broadly. For example, it can refer to a fixed connection, a detachable connection, or an integral part; it can refer to a direct connection or an indirect connection through an intermediate medium; it can refer to the internal communication of two elements or the interaction relationship between two elements. Those skilled in the art can understand the specific meaning of the above terms in this application according to the specific circumstances.

[0021] Example 1: A method for detecting three-phase unbalanced current in cables based on phase difference, such as... Figure 1 As shown, it includes the following steps: S1: Synchronously acquire the three-phase current signal of the cable and preprocess the acquired signal; In practical applications, the synchronous acquisition of three-phase current signals from cables specifically includes: installing wideband current sensors on each of the three phases of the cable. The current sensors use Rogowski coils or optical current transformers, with a bandwidth covering the frequency range of 10Hz to 10kHz, amplitude measurement accuracy better than 0.2%, and phase measurement accuracy better than 0.1°. The sensors adopt an open-loop structure, facilitating uninterrupted installation for existing cables. High-speed synchronous sampling technology triggered by the same source clock is used, and strict synchronization of the three-phase sampling clocks is achieved through GPS or the IEEE 1588 precise time protocol. The three-phase current signals are synchronously converted from analog to digital at a sampling frequency of not less than 20kHz, and the sampling clock deviation is controlled within 1μs to ensure the time alignment accuracy of the three-phase data, providing a reliable raw data foundation for subsequent instantaneous phase extraction and phase difference calculation.

[0022] Preprocessing includes filtering and denoising; filtering and denoising includes wavelet thresholding and morphological filtering. Morphological filtering employs a hybrid morphological filter, including opening, closing, and their combinations, to suppress pulse interference in current signals. The opening operation eliminates positive pulse noise by first eroding and then dilating the signal. The closing operation fills negative pulse depressions in the signal by first dilating and then eroding the signal. The combination operation uses an open-closed cascade or closed-open cascade structure, adaptively selecting the operation order and structure element length based on the polarity and intensity of the pulse interference. The structure element length is dynamically adjusted according to the current power frequency period to match the fundamental frequency period. This effectively suppresses random pulse interference while fully preserving the fundamental characteristics and phase information of the current signal, avoiding the phase shift and waveform distortion problems caused by traditional linear filters.

[0023] Wavelet thresholding denoising specifically includes: Based on the signal-to-noise ratio (SNR) of the three-phase current signal, the wavelet basis function and the number of decomposition levels are adaptively selected. Specifically, this includes: calculating the SNR of the current signal; adaptively selecting the optimal wavelet basis from the wavelet basis function library based on the SNR value (including the db, sym, and coif series wavelets); and determining the number of wavelet decomposition levels based on the ratio of the sampling frequency to the power frequency. The number of decomposition levels ensures that the frequency of the deepest detail component covers half of the power frequency, ensuring that the fundamental frequency signal is completely preserved in the approximate components and avoiding frequency aliasing caused by over-decomposition. This achieves effective separation of white noise and colored noise in the current signal, providing a high SNR input signal for subsequent empirical mode decomposition.

[0024] The high-frequency wavelet coefficients are shrunk using an improved threshold function, which is as follows: ; in, These are wavelet coefficients. For the threshold, and To adjust the parameters.

[0025] and Specifically, this can be determined through the following rules: When the signal-to-noise ratio is ≥20dB , ; When 10dB ≤ signal-to-noise ratio < 20dB , ; When the signal-to-noise ratio is <10dB , ; Among them, under the condition of signal-to-noise ratio ≥20dB, The preferred value is 0.5. The preferred value is 0.1.

[0026] Specifically, for the high-frequency detail component coefficients obtained by wavelet decomposition, thresholds for each layer are calculated, and the thresholds are adaptively determined based on the statistical characteristics of the coefficients at that layer. The high-frequency coefficients at each layer are mapped to the improved threshold function. When the absolute value of a wavelet coefficient is greater than or equal to the threshold, a sign function is used to preserve the sign of the coefficient, and the coefficient amplitude is linearly shrunk. The shrinkage amount is the product of the adjustment parameter and the threshold, appropriately reducing large coefficients to suppress residual noise. When the absolute value of a wavelet coefficient is less than the threshold, the coefficient is shrunk by multiplying it by the adjustment parameter, preserving some of the coefficient's energy and avoiding the loss of signal details caused by directly setting the traditional hard threshold function to zero. By adjusting the parameters, a balance is achieved between thorough denoising and preservation of signal details, effectively eliminating white noise and impulse noise while fully preserving the abrupt change characteristics and phase information of the current signal, thus improving the accuracy of subsequent instantaneous phase extraction.

[0027] S2: An improved Hilbert-Huang transform method is used to extract the instantaneous phase of each phase current from the preprocessed three-phase current signal; The improved Hilbert-Huang transform method in step S2 specifically includes: S21: Perform empirical mode decomposition on the current signal to obtain multiple intrinsic mode function components; Step S21, empirical mode decomposition, specifically includes: The current signal is adaptively filtered to obtain multiple components that satisfy the intrinsic mode function conditions. The decomposition process terminates when the filtering stopping criterion is met, and a residual term is generated. The residual term does not participate in the subsequent instantaneous phase extraction and fusion process.

[0028] Specifically, this involves iteratively extracting the inherent oscillation modes from the current signal using the envelope mean method. In each iteration, the upper and lower envelopes of the signal are calculated, and the envelope mean is obtained. The original signal is subtracted from the envelope mean to obtain the screening result. This process is repeated until the screening result meets the two basic conditions of the intrinsic mode function: the number of extreme points in the entire data sequence is equal to or differs by at most one from the number of zero-crossing points, and the mean of the upper envelope formed by local maxima and the lower envelope formed by local minima is zero at any given time. When these conditions are met, the screening result is separated from the original signal as an intrinsic mode function component. The above decomposition process is repeated for the remaining signal until the remaining signal becomes a monotonic function or its amplitude is less than a preset threshold. At this point, the decomposition process terminates, and the final residual term represents the trend component or DC component of the signal. In the subsequent instantaneous phase extraction and fusion process, only the intrinsic mode function components are used for Hilbert transform and weighted fusion. The residual term is not included in the calculation, thus ensuring that the phase estimation only reflects the AC oscillation characteristics of the signal and avoiding interference from the trend term on the accuracy of phase extraction.

[0029] Step S21 also includes a component filtering step: Calculate the average instantaneous frequency of each intrinsic mode function component. ; Valid components that meet the following conditions will be selected for subsequent calculations: ; in, It is 0.5 times the power system frequency. It is 10 times the power frequency of the power system.

[0030] S22: Perform Hilbert transform on each intrinsic mode function component and extract the instantaneous phase; The specific method for extracting the instantaneous phase in step S22 is as follows: Perform a Hilbert transform on each intrinsic mode function component to construct an analytic signal; the analytic signal is composed of the original component and its Hilbert transform result, thus expanding the real signal into a complex signal form.

[0031] Instantaneous amplitude and instantaneous phase are calculated based on the analytic signal; the instantaneous amplitude is the magnitude of the analytic signal, reflecting the instantaneous change in signal energy, and the instantaneous phase is the amplitude of the analytic signal, reflecting the instantaneous change in signal phase.

[0032] The calculated instantaneous phase is unwrapped. By detecting the phase difference between adjacent sampling points, a phase jump point is determined when the absolute value of the phase difference exceeds π. The phase discontinuity caused by the range limitation of the arctangent function is eliminated by compensating for integer multiples of 2π. The folded phase curve is unfolded into a continuously changing phase sequence, resulting in a continuous instantaneous phase sequence for subsequent weighted fusion. This ensures that the physical meaning of the phase estimation is clear and the time is continuous, providing a reliable phase data foundation for phase difference calculation and fault identification.

[0033] S23: Calculate the energy entropy of each component and determine the adaptive weights; The method for calculating energy entropy and determining adaptive weights in step S23 is as follows: Discretize and statistically analyze the instantaneous amplitudes of each intrinsic mode function component, divide the range of instantaneous amplitude variation into several intervals, count the frequency of amplitude occurrence in each interval, construct an amplitude probability distribution, and calculate the energy entropy value of each component according to the definition of information entropy; the energy entropy value reflects the uncertainty and contribution of the component in the composition of signal energy, the more dispersed the energy distribution, the greater the energy entropy, and the more concentrated the energy is in a specific component, the smaller the energy entropy; The energy entropy of each component is normalized to obtain adaptive weights, so that the sum of the weight coefficients is 1. Components with high energy contribution and large energy entropy value are given larger fusion weights, while components with low energy contribution and small energy entropy value are given smaller fusion weights. This achieves adaptive weighting of the energy distribution of multi-component signals, highlights the dominant oscillation mode, suppresses the influence of noise and spurious components, and improves the accuracy and stability of instantaneous phase estimation.

[0034] S24: The instantaneous phase of each component is weighted and fused based on adaptive weights to obtain the final instantaneous phase estimate.

[0035] The continuous instantaneous phase sequence of each intrinsic mode function component after unwinding is multiplied by the corresponding adaptive weight, and the weighted results of all components are summed to obtain the final fused instantaneous phase estimate. The final fused instantaneous phase estimate has a higher signal-to-noise ratio and better continuity, and can accurately reflect the instantaneous phase changes of the three-phase current of the cable. It provides a high-precision and high-reliability phase data foundation for subsequent calculation of the instantaneous phase difference between any two phases, determination of the three-phase current balance state, and identification of fault types.

[0036] S3: Based on the instantaneous phase of each phase current extracted, calculate the instantaneous phase difference between any two phases, and determine the three-phase current balance state of the cable based on the instantaneous phase difference. The specific method for calculating the instantaneous phase difference and determining the equilibrium state in step S3 is as follows: Based on the extracted instantaneous phases of each phase current, the instantaneous phase difference between any two phases is calculated, including the phase difference between phases AB, BC, and CA. Specifically, based on the extracted instantaneous phases of phases A, B, and C currents, the instantaneous phase difference between any two phases is calculated, including the phase difference between phases AB (the difference between the instantaneous phases of phases A and B), BC (the difference between the instantaneous phases of phases B and C), and CA (the difference between the instantaneous phases of phases C and A).

[0037] Each instantaneous phase difference is compared with the predetermined theoretical phase difference; the theoretical phase difference is the phase difference between two phases when the three-phase current of the cable is in an ideal equilibrium state, and its value is 120 degrees or the corresponding radian value. An allowable deviation threshold is set, which is the critical range for determining three-phase balance and imbalance. When the deviation of each instantaneous phase difference from the predetermined theoretical phase difference is within the threshold range, the cable is determined to be in a three-phase balanced state. When the absolute value of the deviation of any instantaneous phase difference from the theoretical phase difference exceeds the allowable deviation threshold range, the cable is determined to be in a three-phase unbalanced state, thereby realizing real-time monitoring and rapid determination of the three-phase current balance state of the cable.

[0038] S4: When the condition is determined to be unbalanced, the fault type is identified based on the abnormal pattern of the three-phase instantaneous phase difference, and the corresponding fault response operation is executed.

[0039] Step S4 specifically includes: Based on the calculated instantaneous phase difference of the three phases, combined with the synchronously acquired current amplitude information, the deviation relationship and the coupling relationship between the phase difference and the predetermined theoretical phase difference are analyzed. The results are matched with a variety of predefined fault characteristic modes to identify specific fault types. The fault types include single-phase ground fault, two-phase short-circuit fault, two-phase ground short-circuit fault, three-phase short-circuit fault, three-phase unbalance fault, harmonic interference fault, and phase loss fault. Specifically, a joint feature vector integrating three-phase instantaneous phase difference and current amplitude information is established. The phase difference dimension includes the instantaneous phase differences of phases AB, BC, and CA, and their deviations from the theoretical 120-degree phase difference. The amplitude dimension includes the instantaneous current amplitude of each phase and its relative rate of change. The mutual constraints between the three phase differences and the coupling relationship between phase difference and amplitude changes are monitored in real time. When a single phase difference deviates from the theoretical value while the other two phase differences maintain the theoretical relationship, and the corresponding phase current amplitude decreases relatively, with its rate of change exceeding a preset threshold, a single-phase ground fault is identified. When two phase differences simultaneously deviate from the theoretical value and exhibit complementary changes, i.e., one... When one phase difference increases and the other decreases accordingly, and the third phase difference is adjusted to maintain a 360-degree constraint for the sum of the three phases, and the current amplitudes of the two faulty phases increase synchronously while the amplitudes of the non-faulty phases remain relatively stable, it is determined to be a two-phase short-circuit fault. When all three phase differences are detected to deviate from the theoretical value and exhibit irregular fluctuations, the rate of change of each phase difference increases abnormally, and the three-phase current amplitudes exhibit an asymmetrical distribution with the relative rate of change of each phase amplitude exceeding a preset threshold, it is determined to be a three-phase unbalanced fault or harmonic interference fault. Through the above multi-dimensional feature coupling analysis, it is matched with predefined fault feature patterns to identify specific fault types, providing accurate fault category information for fault location and protection actions.

[0040] The predefined fault characteristic modes are shown in Table 1 below: Table 1

[0041] Based on the identified fault type, the system automatically executes the corresponding preset response operations. These response operations include triggering a graded alarm mechanism, recording the three-phase current waveforms and phase difference data at the time of the fault, and uploading fault information containing the fault type and timestamp to the monitoring center.

[0042] Specifically, based on the identified fault type and severity, a tiered alarm mechanism is triggered. This mechanism has three levels: a single-phase grounding fault triggers a Level 1 alarm, alerting operators to inspect the fault; a two-phase short-circuit fault triggers a Level 2 alarm and initiates a protection trip delay countdown to allow time for fault isolation; a three-phase unbalanced fault or harmonic interference fault triggers a Level 3 alarm, prompting harmonic mitigation and load adjustment. Simultaneously with alarm triggering, the system automatically records the three-phase current waveforms, instantaneous phase difference data, and the identified fault type within a preset time window before and after the fault, forming a complete fault waveform file. This file includes the timestamp of the fault occurrence, the fault duration, the current amplitude of each phase, and the phase change curve. The fault information, including the fault type, timestamp, fault severity level, and waveform file summary, is uploaded to the monitoring center in real time via wired or wireless communication. The monitoring center archives, stores, visualizes, and analyzes the fault information, enabling remote monitoring and fault early warning of cable operation status, providing data support for the safe operation and maintenance decisions of the power system.

[0043] Example 2: This embodiment establishes a test platform on a 10kV cross-linked polyethylene cable line to simulate various operating conditions, including normal operation, single-phase grounding fault, two-phase short-circuit fault, three-phase unbalanced fault, and harmonic interference. Each condition undergoes 100 independent tests, and the overall performance of the traditional detection method and the proposed method is compared. The traditional detection method uses current amplitude comparison combined with Fourier transform phase analysis to determine the unbalanced state by comparing the differences in three-phase current amplitudes. The test results are shown in Table 2 below. Table 2

[0044] As shown in Table 2, the correct identification frequency of the proposed method under various operating conditions is significantly higher than that of the traditional method, with an overall correct identification rate of 97.3%, which is 21.5 percentage points higher than the 75.8% of the traditional method, verifying the overall technical superiority of the proposed method. The correct identification rate of the proposed method fluctuates only from 90.0% to 98.0% under various operating conditions, while the fluctuation range of the traditional method is 62.0% to 88.0%, indicating that the proposed method has stronger adaptability and stability under operating conditions and can meet the reliability requirements of online monitoring of three-phase imbalance in cables.

[0045] Therefore, this application adopts the above-mentioned method for detecting three-phase unbalanced current in cables based on phase difference. By synchronous acquisition and adaptive preprocessing, signal quality is ensured. High-precision instantaneous phase extraction is achieved using an improved Hilbert-Huang transform. Balance state is determined based on instantaneous phase difference, and fault type is accurately identified by combining phase difference feature vectors. This effectively solves the technical problems of low phase extraction accuracy, poor anti-interference ability, and failure under light load conditions in traditional methods. It significantly improves the accuracy, real-time performance, and reliability of three-phase unbalanced current detection in cables, providing effective technical support for the safe operation and fault early warning of power cables.

[0046] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application and not to limit them. Although this application has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the technical solutions of this application, and these modifications or equivalent substitutions cannot cause the modified technical solutions to deviate from the spirit and scope of the technical solutions of this application.

Claims

1. A method for detecting three-phase unbalanced current in a cable based on phase difference, characterized in that, Includes the following steps: S1: Synchronously acquire the three-phase current signal of the cable and preprocess the acquired signal; S2: An improved Hilbert-Huang transform method is used to extract the instantaneous phase of each phase current from the preprocessed three-phase current signal; S3: Based on the instantaneous phase of each phase current extracted, calculate the instantaneous phase difference between any two phases, and determine the three-phase current balance state of the cable based on the instantaneous phase difference. S4: When the condition is determined to be unbalanced, the fault type is identified based on the abnormal pattern of the three-phase instantaneous phase difference, and the corresponding fault response operation is executed.

2. The method for detecting three-phase unbalanced current in a cable based on phase difference as described in claim 1, characterized in that, The preprocessing includes filtering and denoising; the filtering and denoising includes wavelet thresholding and morphological filtering; the morphological filtering uses a hybrid morphological filter, including opening, closing and their combinations, to suppress pulse interference in the current signal.

3. The method for detecting three-phase unbalanced current in a cable based on phase difference as described in claim 2, characterized in that, Wavelet thresholding denoising specifically includes: Based on the signal-to-noise ratio of the three-phase current signal, the wavelet basis function and the number of decomposition levels are adaptively selected; The high-frequency wavelet coefficients are shrunk using an improved threshold function, which is: ； in, These are wavelet coefficients. For the threshold, and To adjust the parameters.

4. The method for detecting three-phase unbalanced current in a cable based on phase difference according to claim 3, characterized in that, The improved Hilbert-Huang transform method in step S2 specifically includes: S21: Perform empirical mode decomposition on the current signal to obtain multiple intrinsic mode function components; S22: Perform Hilbert transform on each intrinsic mode function component and extract the instantaneous phase; S23: Calculate the energy entropy of each component and determine the adaptive weights; S24: The instantaneous phase of each component is weighted and fused based on adaptive weights to obtain the final instantaneous phase estimate.

5. The method for detecting three-phase unbalanced current in a cable based on phase difference as described in claim 4, characterized in that, Step S21, empirical mode decomposition, specifically includes: The current signal is adaptively filtered to obtain multiple components that satisfy the intrinsic mode function conditions. The decomposition process terminates when the filtering stopping criterion is met, and a residual term is generated. The residual term does not participate in the subsequent instantaneous phase extraction and fusion process.

6. The method for detecting three-phase unbalanced current in a cable based on phase difference as described in claim 5, characterized in that, Step S21 also includes a component filtering step: Calculate the average instantaneous frequency of each intrinsic mode function component. ; Valid components that meet the following conditions will be selected for subsequent calculations: ； in, It is 0.5 times the power system frequency. It is 10 times the power frequency of the power system.

7. The method for detecting three-phase unbalanced current in a cable based on phase difference as described in claim 6, characterized in that, The specific method for extracting the instantaneous phase in step S22 is as follows: Perform a Hilbert transform on each intrinsic mode function component to construct an analytic signal; Calculate instantaneous amplitude and instantaneous phase based on analytic signals; The calculated instantaneous phase is unwound, and a continuous instantaneous phase sequence is obtained by detecting the phase jump of adjacent sampling points and compensating for integer multiples of 2π. This sequence is then used for subsequent weighted fusion.

8. The method for detecting three-phase unbalanced current in a cable based on phase difference as described in claim 7, characterized in that, The method for calculating energy entropy and determining adaptive weights in step S23 is as follows: Discretize and statistically analyze the instantaneous amplitudes of each intrinsic mode function component to construct an amplitude probability distribution, and calculate the energy entropy value of each component based on the definition of information entropy; The energy entropy of each component is normalized to obtain adaptive weights, so that the sum of the weight coefficients is 1, and the component with higher energy contribution is given a larger fusion weight.

9. The method for detecting three-phase unbalanced current in a cable based on phase difference as described in claim 8, characterized in that, The specific method for calculating the instantaneous phase difference and determining the equilibrium state in step S3 is as follows: Based on the instantaneous phase of each phase current extracted, calculate the instantaneous phase difference between any two phases, including the phase difference between phases AB, BC, and CA. Compare each instantaneous phase difference with the predetermined theoretical phase difference; A permissible deviation threshold is set. When the deviation of each instantaneous phase difference from the predetermined theoretical phase difference is within the threshold range, the cable is determined to be in a three-phase balanced state. When the deviation of any instantaneous phase difference from the predetermined theoretical phase difference exceeds the threshold range, the cable is determined to be in a three-phase unbalanced state.

10. The method for detecting three-phase unbalanced current in a cable based on phase difference as described in claim 9, characterized in that, Step S4 specifically includes: Based on the calculated instantaneous phase difference of the three phases, combined with the synchronously acquired current amplitude information, the deviation relationship and the coupling relationship between the phase difference and the predetermined theoretical phase difference are analyzed. The results are matched with a variety of predefined fault characteristic modes to identify specific fault types. The fault types include single-phase ground fault, two-phase short-circuit fault, two-phase ground short-circuit fault, three-phase short-circuit fault, three-phase unbalance fault, harmonic interference fault, and phase loss fault. Based on the identified fault type, the system automatically executes the corresponding preset response operations. These response operations include triggering a graded alarm mechanism, recording the three-phase current waveforms and phase difference data at the time of the fault, and uploading fault information containing the fault type and timestamp to the monitoring center.

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