Submarine cable fault positioning simulation verification system and calibration method thereof

Abstract

The invention discloses a submarine cable fault positioning simulation verification system and a calibration method thereof, and belongs to the technical field of submarine cable detection. According to the system, a multi-source sensor array is deployed for data acquisition, and a multi-stage adaptive noise reduction algorithm, a time-frequency domain feature fusion technology and a land-sea environment electromagnetic field mapping model are adopted, so that magnetic field distribution features of a submarine cable in an actual marine environment can be simulated with high fidelity, and accurate positioning of a fault position is realized. By establishing a standardized calibration process, effective migration of simulation data and marine measured data is ensured, and the technical problems of complex marine noise interference and extrapolation distortion of a laboratory environment verification result are effectively solved. The scheme has the remarkable advantages of high positioning precision, strong anti-interference capability, accurate environment mapping and the like.

Description

Technical Field

[0001] This invention belongs to the field of submarine cable detection technology, and relates to a simulation verification system and calibration method for submarine cable fault location. Background Technology

[0002] With the rapid development of offshore wind power, submarine cables, as important power transmission channels, are widely used in offshore wind farms. However, fault location in submarine cables remains a complex and highly precise technical challenge. Existing submarine cable fault detection methods mainly rely on conventional voltage testing or ultrasonic testing, which have significant limitations: First, in complex marine environments, conventional detection methods are easily affected by environmental noise, leading to inaccurate signal acquisition; second, existing technologies do not adequately denoise fault signals, making it difficult to effectively separate fault characteristic signals from background noise; third, traditional methods lack effective simulation verification mechanisms, making it impossible to fully verify fault location algorithms in laboratory environments, resulting in insufficient positioning accuracy in practical applications. Especially in dynamic marine environments, sensor signals are prone to drift, and existing technologies lack effective dynamic compensation mechanisms. Furthermore, existing systems struggle to accurately establish a mapping relationship between land-based simulation platforms and the marine environment, making laboratory verification results unable to accurately reflect actual submarine cable fault conditions. Therefore, a new high-precision fault location system is urgently needed, capable of accurately locating submarine cable faults in different environments and establishing a reliable simulation verification mechanism. Existing technologies urgently need improvement to address these issues. Summary of the Invention

[0003] The purpose of this invention is to overcome the shortcomings of the prior art and provide a simulation verification system and calibration method for submarine cable fault location, which has the advantages of improving the accuracy of submarine cable fault location, enhancing anti-interference ability, and achieving accurate mapping between laboratory environment and marine environment.

[0004] To achieve the above objectives, the present invention employs the following technical solution: A calibration method for a simulation verification system for submarine cable fault location includes the following steps: S1, The land simulation platform collects position information, equipment attitude information, three-axis magnetic field strength information, and equipment height information from various sensors; the sensors are arranged in a ring array above the submarine cable. S2, the information is denoised in multiple stages by wavelet transform thresholding, adaptive Kalman filter compensation and magnetic dipole model to obtain the denoised information. S3, based on the time-frequency domain feature parameters of the noise-reduced information, integrates the improved particle swarm algorithm and impedance matrix analysis method to obtain the spatial correspondence between the abnormal magnetic field gradient change rate generated by the fault point and the current leakage point, and obtains the location of the submarine cable fault. S4. The location of the submarine cable fault is transferred from the experimental loop of the land simulation platform to the marine environment through a mapping relationship model.

[0005] A further improvement of the present invention is that: Preferably, in S1, the device attitude information includes roll, pitch, and heading; the three-axis magnetic field strength information includes magnetic flux in the X, Y, and Z directions; and the device height information is relative to sea level.

[0006] Preferably, in S2, high-frequency random noise is eliminated by wavelet transform thresholding, signal drift in dynamic environments is compensated by adaptive Kalman filtering, and geomagnetic background field is eliminated by magnetic dipole model inversion.

[0007] Preferably, the process of eliminating high-frequency random noise using the wavelet transform thresholding method is as follows: (1) Perform wavelet transform on the collected information, and select the wavelet basis function and the number of decomposition layers; (2) Thresholding is performed on the coefficients of each layer after wavelet transform; the wavelet coefficients corresponding to noise are removed by thresholding, and the coefficients corresponding to the main features of the signal are retained; (3) Perform wavelet reconstruction on the wavelet coefficients after thresholding to obtain the information after noise reduction by wavelet transform thresholding.

[0008] Preferably, the process of using adaptive Kalman filtering to compensate for signal drift in a dynamic environment is as follows: (1) Establish the state equation and observation equation of the sensor; (2) Initialize the parameters of the Kalman filter; the parameters include the initial state estimate, the initial error covariance matrix, the process noise covariance matrix, and the observation noise covariance matrix; (3) Predict the system state and error covariance matrix at the current moment based on the state equation. Calculate the Kalman gain based on the observation equation and the actual observation value, and update the system state estimate and error covariance matrix. Real-time estimation of sensor state and noise compensation are achieved through iteration and updating.

[0009] Preferably, the processing procedure for the magnetic dipole model is as follows: (1) The current in the submarine cable is assumed to be a series of magnetic dipoles; (2) Calculate the magnetic field strength generated by each magnetic dipole at the sensor position according to the magnetic field calculation formula of the magnetic dipole; (3) Superimpose the magnetic field strength generated by all magnetic dipoles at the sensor position to obtain the theoretical value of the magnetic field strength generated by the submarine cable at the sensor position under ideal conditions; (4) The actual measured magnetic field strength information after the first two stages of noise reduction is compared with the theoretical value calculated by the magnetic dipole model. The model parameters are adjusted and optimized by the least squares method to further remove residual noise and errors and obtain the final noise-reduced information.

[0010] Preferably, in S3, the process of obtaining the time-frequency domain feature parameters of the denoised information is as follows: (1) Perform time-frequency analysis on the noise-reduced information and use short-time Fourier transform to convert the time-domain signal into the time-frequency domain; (2) Extract fault feature signals from the time-frequency domain representation, and determine the feature parameters that can accurately characterize submarine cable faults by comparing and analyzing the time-frequency domain features of normal signals and fault signals.

[0011] Preferably, the process of fusing the improved particle swarm optimization algorithm with the impedance matrix analysis method is as follows: (1) Fault location estimation is obtained by fusing and improving the particle swarm algorithm; (2) The estimation results of the fault location are verified and optimized by impedance matrix analysis.

[0012] Preferably, between S1 and S2, there is also a process of filtering the information.

[0013] A simulation verification system for locating submarine cable faults using any of the calibration methods described above includes an integrated sensor array arranged in a ring above the submarine cable. The sensor includes a GPS positioning sensor, a three-dimensional device attitude sensor, a three-axis magnetic field detection sensor, and a barometric altitude sensor. The submarine cable and sensors are housed within the shielding device.

[0014] Compared with the prior art, the present invention has the following beneficial effects: This method provides a calibration approach for a simulation verification system of submarine cable fault location. It performs linear gradient extension noise reduction on the acquired signals to improve the signal-to-noise ratio and ensure the accuracy of fault location data. Through multi-level noise reduction processing, time-frequency domain feature fusion algorithms, and a land-to-sea environment mapping model, it can efficiently simulate the magnetic field signals of submarine cables in the actual marine environment, enabling precise fault location. Furthermore, through accurate calibration, the simulated data can be smoothly transferred to real-world marine measurements, effectively solving the problems of complex noise interference and inaccurate transfer of laboratory verification results. This method offers advantages such as improved positioning accuracy, enhanced anti-interference capabilities, and precise environmental mapping.

[0015] This invention also discloses a simulation verification system for submarine cable fault location using a calibration method. This system effectively reduces external electromagnetic interference and improves data acquisition accuracy through the use of external wires and shielding at both ends of the submarine cable. By employing single-phase power supply and heterogeneous frequency signal injection, interference with power grid signals is avoided, ensuring the clarity of the magnetic field signal. Furthermore, integrated GPS, attitude, triaxial magnetic field, and altitude sensors ensure more complete data acquisition and stable operation in complex environments. Linear gradient extension noise reduction technology further improves signal reliability, resulting in more accurate fault location results. Attached Figure Description

[0016] Figure 1 This is a flowchart of the calibration method of the present invention; Figure 2 This is a graph of the original triaxial and composite magnetic field data; Figure 3 It is a three-axis and composite magnetic field data graph after data processing. Detailed Implementation

[0017] Hereinafter, the terms "first," "second," "third," and "fourth" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Therefore, a feature defined as "first," "second," "third," or "fourth" may explicitly or implicitly include one or more of that feature.

[0018] The synchronization method provided in this application can be applied to terminal devices such as mobile phones, tablets, wearable devices, in-vehicle devices, augmented reality (AR) / virtual reality (VR) devices, laptops, ultra-mobile personal computers (UMPCs), netbooks, and personal digital assistants (PDAs). This application does not impose any restrictions on the specific type of terminal device.

[0019] It should be noted that the terms "first," "second," etc., used in the specification and drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0020] In existing technologies, submarine cable fault location techniques have long relied on conventional voltage testing or ultrasonic detection methods. These methods are susceptible to environmental noise interference in complex marine environments, leading to inaccurate data processing and significant deviations in fault location. Especially in dynamic marine environments, sensor signals are easily affected by the geomagnetic background field, equipment attitude changes, and random noise, making it difficult to accurately capture subtle magnetic field changes caused by current leakage. For example, traditional single noise reduction methods cannot effectively separate high-frequency noise from low-frequency drift, resulting in the submersion of fault characteristic signals and limited location accuracy.

[0021] To address the aforementioned problems, the first aspect of this invention discloses a calibration method for a simulation verification system for submarine cable fault location, comprising the following steps: S1, The land simulation platform collects position information, equipment attitude information, three-axis magnetic field strength information, and equipment height information from various sensors; the sensors are arranged in a ring array above the submarine cable. S2, the information is denoised in multiple stages by wavelet transform thresholding, adaptive Kalman filter compensation and magnetic dipole model to obtain the denoised information. S3, based on the time-frequency domain feature parameters of the noise-reduced information, integrates the improved particle swarm algorithm and impedance matrix analysis method to obtain the spatial correspondence between the abnormal magnetic field gradient change rate generated by the fault point and the current leakage point, and obtains the location of the submarine cable fault. S4. The location of the submarine cable fault is transferred from the experimental loop of the land simulation platform to the marine environment through a mapping relationship model.

[0022] The circular array of sensors refers to multiple detection units geometrically symmetrically distributed around the submarine cable. Specifically, this can be achieved using sensor groups arranged at equal angular intervals, enhancing the sensitivity of magnetic field gradient detection through synchronous multi-point spatial acquisition. The sensor array covers the simulated section of the submarine cable in a circular layout, synchronously acquiring spatial magnetic field distribution data. The raw data is first decomposed using wavelet decomposition, selecting, for example, a db4 wavelet basis for three-level decomposition, and removing high-frequency noise components through soft thresholding. Subsequently, for low-frequency drift caused by equipment movement, a state equation incorporating attitude parameters is established, and the sensor output is corrected in real time by adaptively adjusting the Kalman gain. After the first two stages of noise reduction, the ideal magnetic field distribution is calculated based on magnetic dipole theory, and residual errors from the geomagnetic background are eliminated through least-squares fitting. The processed data is then subjected to short-time Fourier transform to generate a time-frequency spectrum, and the energy change rate of the fault characteristic frequency band is extracted as the input parameter. After initializing the particle swarm algorithm, an improved particle swarm algorithm is used, and convergence is accelerated by dynamically adjusting the inertia weight. The effectiveness of candidate solutions is verified by combining the impedance matrix, and finally, the optimal fault point coordinates that satisfy the constraints are output. The positioning results are converted from the coordinates in the laboratory coordinate system to latitude and longitude information in the marine environment through a pre-established mapping model.

[0023] The method of this invention can effectively suppress the influence of composite noise on magnetic field detection, accurately extract fault feature signals, and achieve sub-meter level positioning accuracy. The improved algorithm fusion strategy shortens the calculation time for fault point coordinates while avoiding misjudgments. The establishment of the mapping model ensures that laboratory calibration results can be directly applied to marine environments, significantly improving the engineering applicability of the fault location system.

[0024] In some embodiments of the present invention, the device attitude information includes roll, pitch, and heading; the three-axis magnetic field strength information includes magnetic flux in the X, Y, and Z directions; and the device height information is relative to sea level.

[0025] Roll refers to the sensor's rotation angle around the X-axis, which can be measured using a gyroscope or accelerometer, and is used to characterize the sensor's tilt in the horizontal plane. Pitch refers to the sensor's rotation angle around the Y-axis, which can be acquired by an inertial measurement unit, and is used to reflect the sensor's attitude changes in the forward and backward directions. Heading refers to the sensor's azimuth angle around the Z-axis, which can be obtained using an electronic compass or a geomagnetic sensor, and is used to determine the sensor's orientation in the horizontal plane. Magnetic flux in the X, Y, and Z directions refers to the magnetic field components detected by the sensor in three-dimensional space, which can be achieved using a triaxial magnetoresistive sensor, and is used to comprehensively capture the magnetic field distribution characteristics around the submarine cable. Relative sea level height information refers to the vertical distance between the sensor and the sea level, which can be calculated using a barometric pressure sensor combined with a temperature compensation algorithm, and is used to eliminate the interference of terrain undulations on magnetic field measurements.

[0026] Specifically, roll, pitch, and heading data are fused using an attitude calculation algorithm to correct magnetic field measurement errors caused by sensor installation misalignment in real time. Three-axis magnetic flux data, processed through vector superposition, fully reflects the spatial magnetic field gradient characteristics generated by submarine cable current leakage. Relative sea level height information is converted from the raw height data collected by the sensors to elevation values ​​under a unified reference plane using a coordinate transformation model, ensuring comparability of measurement results under different terrain conditions. For example, when the sensor experiences roll angle shift due to wave impact, attitude information can trigger dynamic compensation of the magnetic field data, preventing distortion of the X-axis magnetic field component measurement due to equipment tilt. This invention effectively solves the problem of magnetic field data distortion caused by sensor installation misalignment and environmental interference, providing high-precision raw data input for subsequent multi-stage noise reduction processing. By fusing three-dimensional attitude information with spatial magnetic field distribution characteristics, the spatial mapping accuracy between the abnormal magnetic field gradient change rate generated at the fault point and the current leakage point can be improved, thereby enhancing the reliability of submarine cable fault location.

[0027] In some embodiments of the present invention, in S1, a multi-node sensor array is arranged in a ring within a range of 0.5-1 meters vertically above the submarine cable to simultaneously collect spatial three-dimensional magnetic field strength, equipment attitude angle, BeiDou / GPS dual-mode positioning data, and relative sea level height information.

[0028] In some embodiments of the present invention, in S2, high-frequency random noise is eliminated by wavelet transform thresholding, signal drift in dynamic environment is compensated by adaptive Kalman filtering, and geomagnetic background field is eliminated by magnetic dipole model inversion.

[0029] Furthermore, the process of eliminating high-frequency random noise using the wavelet transform thresholding method is as follows: (1) Perform wavelet transform on the collected information, and select the wavelet basis function and the number of decomposition levels. The selection of wavelet basis function should consider its ability to capture signal features and computational complexity. Commonly used wavelet basis functions include Daubechies wavelet, Symlet wavelet, etc. The number of decomposition levels is determined according to the frequency components and noise characteristics of the signal. It is generally selected through experiments or experience. For example, for a signal containing multiple frequency components, you can try decomposing it into 3-5 levels first.

[0030] (2) Thresholding is performed on the coefficients of each layer after wavelet transform; the wavelet coefficients corresponding to noise are removed by thresholding, and the coefficients corresponding to the main features of the signal are retained; the threshold size is determined by using soft thresholding or hard thresholding methods based on the estimated intensity of noise.

[0031] (3) Perform wavelet reconstruction on the wavelet coefficients after thresholding to obtain the information after noise reduction by wavelet transform thresholding.

[0032] This invention utilizes the time-frequency localization characteristics of wavelet transform to accurately separate transient noise from effective signals. In particular, when dealing with sudden electromagnetic interference collected by sensors, it can avoid excessive filtering of effective signal features, effectively solving the problem of large positioning errors caused by high-frequency noise interference in submarine cable fault detection. Through multi-scale decomposition and adaptive threshold processing, it eliminates random noise while preserving the detailed features of magnetic field gradient changes, thus significantly improving the accuracy of subsequent calculations of the magnetic field gradient change rate at fault points.

[0033] In some embodiments of the present invention, the process of using adaptive Kalman filtering to compensate for signal drift under dynamic environments is as follows: (1) Establish the state equation and observation equation of the sensor; the state equation describes the change law of the system state over time, and the observation equation describes the relationship between the sensor measurement value and the system state.

[0034] (2) Initialize the parameters of the Kalman filter; the parameters include the initial state estimate, the initial error covariance matrix, the process noise covariance matrix and the observation noise covariance matrix; the initial values ​​of the above parameters can be reasonably set according to the prior knowledge of the system and experimental data, and adaptively adjusted in the subsequent filtering process.

[0035] (3) Predict the system state and error covariance matrix at the current moment based on the state equation. Calculate the Kalman gain based on the observation equation and actual observations, and update the system state estimate and error covariance matrix. Through iteration and updating, real-time estimation of the sensor state and noise compensation are achieved. Simultaneously, based on the actual error situation during the filtering process, adaptively adjust the process noise covariance matrix and the observation noise covariance matrix to improve the accuracy and adaptability of the filtering.

[0036] This invention dynamically optimizes filtering parameters based on real-time measurement data by adaptively adjusting the process noise covariance matrix and the observation noise covariance matrix. By updating the Kalman gain in real time, it can more accurately balance the weights of predicted and observed data, reducing accumulated errors in dynamic environments. This process effectively suppresses sensor signal drift in dynamic environments, improving the stability of magnetic field strength information. Through real-time iterative updates to the system state estimate, it can accurately compensate for signal deviations caused by equipment vibration, temperature changes, or external electromagnetic interference, thus providing more reliable input data for subsequent fault location. Simultaneously, the adaptive noise parameter adjustment design avoids the overfitting or underfitting problems caused by fixed parameters in traditional methods, enhancing the system's applicability in different environments.

[0037] In some embodiments of the present invention, environmental noise (such as ocean current eddies, ship mechanical vibrations, etc.) is effectively suppressed using a magnetic dipole model. The processing procedure of the magnetic dipole model is as follows: (1) Establish a magnetic dipole model and set the current in the submarine cable as a series of magnetic dipoles.

[0038] (2) Calculate the magnetic field strength generated by each magnetic dipole at the sensor position according to the magnetic field calculation formula of the magnetic dipole; (3) The magnetic field strength generated by all magnetic dipoles at the sensor position is superimposed to obtain the theoretical value of the magnetic field strength generated by the submarine cable at the sensor position under ideal conditions; the ideal conditions are no fault and no noise.

[0039] (4) The actual measured magnetic field strength information after the first two stages of noise reduction is compared with the theoretical value calculated by the magnetic dipole model. The model parameters are adjusted and optimized by the least squares method to further remove residual noise and errors and obtain the final noise-reduced information.

[0040] This invention uses a magnetic dipole model to invert the theoretical magnetic field distribution and combines iterative optimization with measured data to effectively separate submarine cable fault signals from background interference, significantly improve the signal-to-noise ratio, and achieve accurate extraction of the magnetic field of submarine cable leakage current, providing a highly reliable data foundation for subsequent spatial location of fault points.

[0041] In some embodiments of the present invention, in S3, based on the noise-reduced time-frequency domain feature signal, the improved particle swarm optimization algorithm and impedance matrix analysis method are fused to calculate the spatial correspondence between the abnormal magnetic field gradient change rate generated by the fault point and the current leakage point. The location of faults such as insulation damage and armor layer breakage in the submarine cable is accurately located through three-dimensional coordinate inversion. The process of obtaining the time-frequency domain feature parameters of the noise-reduced information is as follows: (1) Perform time-frequency analysis on the noise-reduced information and use short-time Fourier transform to convert the time-domain signal into the time-frequency domain; (2) Extract fault feature signals from the time-frequency domain representation, and determine the feature parameters that can accurately characterize submarine cable faults by comparing and analyzing the time-frequency domain features of normal signals and fault signals.

[0042] This invention, through joint time-frequency analysis, can simultaneously analyze the temporal dynamic characteristics and frequency component evolution of signals, effectively identifying unsteady magnetic field fluctuations caused by current leakage. It can extract physically meaningful fault characteristic parameters from complex environmental noise, significantly improving the accuracy of submarine cable fault location. Through time-frequency domain feature comparison analysis, it can effectively distinguish magnetic field change patterns under normal operating conditions and fault states, avoiding misjudgments caused by environmental interference or equipment drift, and providing a reliable data foundation for subsequent spatial fault location.

[0043] In some embodiments of the present invention, the process of fusing the improved particle swarm optimization algorithm with the impedance matrix analysis method is as follows: (1) Fault location estimation is obtained by fusing and improving the particle swarm algorithm; (1.1) Initialize the particle swarm, setting the number, position, and velocity of the particles. The particle position represents the possible location of the submarine cable fault point, and the velocity represents the update step size and direction of the particle position. Based on the simulation range of the submarine cable and the expected positioning accuracy, reasonably determine the search space and initial position distribution of the particles. Define a fitness function to evaluate the quality of the fault point location represented by each particle. The fitness function is constructed based on the error between the abnormal magnetic field gradient change rate generated by the fault point and the actual measured value, and the accuracy of the spatial correspondence of the current leakage point.

[0044] (1.2) Update the particle swarm optimization algorithm by introducing an adaptive adjustment strategy for inertial weights and a particle diversity preservation mechanism; (1.3) Iteratively update the position and velocity of the particles, evaluate the new position of each particle according to the fitness function, and continuously search for the particle position with the smallest fitness function value, that is, the optimal fault point position estimate.

[0045] (2) The estimation results of the fault location are verified and optimized by impedance matrix analysis.

[0046] (2.1) Establish the impedance matrix model of the submarine cable, considering parameters such as resistance, inductance, and capacitance. Based on the cable's geometry and material properties, calculate the impedance matrix of the submarine cable at different frequencies. The impedance matrix describes the electrical relationship between various detection points on the submarine cable. The current distribution and leakage in the submarine cable are analyzed through the impedance matrix.

[0047] (2.2) Based on the fault location estimation obtained from the improved particle swarm optimization algorithm, and combined with the impedance matrix model, the spatial distribution of current leakage points is calculated. By analyzing the relationship between current leakage points and fault points, the estimation results of fault location are further verified and optimized.

[0048] (3) The fault location estimate obtained by the improved particle swarm algorithm is used as the initial input of the impedance matrix analysis method, and the fault location is further verified and corrected by the impedance matrix analysis method.

[0049] Based on the results of impedance matrix analysis, the fitness function or update rule of the particle swarm optimization (PSO) algorithm is adjusted and improved to enable the PSO algorithm to search for fault locations more accurately. Through multiple iterations, the improved PSO algorithm and impedance matrix analysis method are fused and refined until the positioning accuracy requirements are met or the maximum number of iterations is reached, thus obtaining the final location of the submarine cable fault.

[0050] This solution combines the advantages of two algorithms, using an improved particle swarm optimization algorithm to quickly locate the fault area, and then employing impedance matrix analysis to verify the candidate results using a physical model. This effectively avoids the limitations of a single algorithm while balancing computational efficiency and positioning accuracy. Through algorithm fusion and cross-validation, the reliability of the fault point's spatial coordinates is significantly improved, making it particularly suitable for the high-precision detection requirements of minute leaks in submarine cables in complex marine environments.

[0051] In some embodiments of the present invention, a filtering process for the information is further included between S1 and S2. Signal acquisition employs a quadrature modulation method with heterogeneous frequency signal injection, using a bandpass filter bank to filter out 50Hz power frequency and harmonic interference, and combining this with a digital lock-in amplifier to improve the signal-to-noise ratio of the target signal.

[0052] In some embodiments of the present invention, the construction process of the mapping relationship model in S4 is as follows: An experimental loop with parameters consistent with the actual submarine cable is constructed on a land-based simulation platform. These parameters include conductor cross-sectional area, insulation dielectric constant, and burial depth. A benchmark dataset is acquired by injecting standard fault signals. The standard fault point is a simulated break or short-circuit point at a known location. A mapping relationship model between the sensor output and the actual fault distance is established using the least squares method. Cross-validation is used to ensure the model's generalization ability under marine environmental variables such as salinity changes (3.5%→4.2%) and temperature fluctuations (10℃→30℃), ultimately achieving seamless transfer between laboratory data and actual sea measurements. The submarine cable fault location obtained in S3 is substituted into the mapping relationship model, and the corresponding location of the submarine cable fault location in the marine environment is calculated based on the parameters of the actual marine environment.

[0053] Furthermore, error analysis and evaluation are conducted on the relocated submarine cable fault location, considering the impact of factors such as the accuracy of the mapping model and the uncertainty of marine environmental parameters on the positioning results. If the error exceeds the allowable range, the mapping model can be corrected and optimized, or land simulation experiments and marine environment comparison experiments can be repeated to improve the accuracy and reliability of the location migration.

[0054] This invention also discloses a simulation verification system for submarine cable fault location, employing a high-precision integrated composite sensor module. This module integrates GPS positioning, three-dimensional attitude measurement (roll / pitch / heading), three-axis magnetic field detection (magnetic flux acquisition in the X / Y / Z directions), and barometric altitude sensing functions, enabling simultaneous monitoring of multiple physical quantities. Double-layer shielding (inner copper mesh + outer aluminum foil) is applied to the connection points at both ends of the submarine cable and the external test conductors, and EMI suppression connectors are used to reduce electromagnetic radiation interference. In a land-based laboratory simulating a marine environment (including equivalent seawater medium, a salt spray chamber, and a dynamic water pressure device), a specific frequency AC signal (preferably a carrier frequency of 100Hz / 150Hz, significantly different from the power frequency of 50Hz) is applied to the single-phase conductor of the submarine cable. An isolation transformer ensures electrical isolation between the injected signal and the mains power supply.

[0055] Among them, the GPS positioning sensor refers to a device that acquires the sensor's spatial coordinates through satellite signals, specifically implemented using a multi-band receiving module. It is used to collect the sensor's absolute position information on the land simulation platform in real time, providing a reference for subsequent magnetic field gradient calculations. The three-dimensional equipment attitude sensor refers to a device that measures the equipment's roll, pitch, and yaw angles, specifically implemented using a MEMS inertial measurement unit, used to eliminate the influence of sensor installation angle deviations on magnetic field strength measurement. The triaxial magnetic field detection sensor refers to a device that simultaneously detects magnetic flux in the X, Y, and Z directions, specifically implemented using a high-sensitivity magnetoresistive sensor array, used to capture weak magnetic field anomalies caused by submarine cable current leakage. The barometric altimeter refers to a device that calculates relative altitude through changes in atmospheric pressure, specifically implemented using a differential barometer, used to establish a vertical distance mapping relationship between the sensor and the submarine cable. The shielding equipment refers to a closed structure made of high-permeability materials, specifically implemented using a multi-layer permalloy shielding chamber, used to isolate external electromagnetic interference, ensuring that the sensor only collects target magnetic field signals generated by submarine cable faults.

[0056] To verify the effectiveness of the linear gradient extension noise reduction technique used in this invention and to further demonstrate the reliability of the method, a comparative experiment was conducted using the original data and the results after data processing. The experimental results are as follows: Figure 2 and Figure 3 As shown.

[0057] Figure 2 This paper presents raw triaxial and synthetic magnetic field data obtained directly from the submarine cable system. Due to noise in the marine environment and external electromagnetic interference, the signals contain a large amount of high-frequency noise. Both the raw triaxial and synthetic magnetic field signals are affected by noise, resulting in blurred key characteristics. Particularly in the high-frequency range, the noise overlaps with the target signal, making subsequent signal analysis and fault location difficult and inaccurate.

[0058] Figure 3 This paper presents magnetic field data after specific frequency extraction and linear gradient extension denoising. This denoising process effectively suppresses noise in the signal, making the target signal clearer. In the processed data, the main characteristics of the triaxial magnetic field signal and the synthetic magnetic field signal are more prominent, signal stability and identifiability are greatly improved, and noise interference is almost completely eliminated. This makes subsequent data analysis more accurate and provides more reliable basic data for submarine cable fault location.

[0059] By comparison Figure 2 and Figure 3 The difference before and after data processing is clearly visible. Noise in the original data significantly affects the signal quality, making it difficult to extract effective information. However, after specific frequency extraction and linear gradient extension noise reduction, the signal quality is significantly improved, the distinction between the target signal and noise is clearer, and the signal becomes purer and more stable.

[0060] These experimental results demonstrate that the method of this invention can effectively improve the quality of submarine cable magnetic field signals, reduce external interference, and enhance data reliability. The denoised data provides a more accurate basis for subsequent fault location, proving the efficiency and reliability of the method of this invention in submarine cable fault location.

[0061] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A calibration method for a simulation verification system for submarine cable fault location, characterized in that, Includes the following steps: S1, The land simulation platform collects position information, equipment attitude information, three-axis magnetic field strength information, and equipment height information from various sensors; the sensors are arranged in a ring array above the submarine cable. S2, the information is denoised in multiple stages by wavelet transform thresholding, adaptive Kalman filter compensation and magnetic dipole model to obtain the denoised information. S3, based on the time-frequency domain feature parameters of the noise-reduced information, integrates the improved particle swarm algorithm and impedance matrix analysis method to obtain the spatial correspondence between the abnormal magnetic field gradient change rate generated by the fault point and the current leakage point, and obtains the location of the submarine cable fault. S4. The location of the submarine cable fault is transferred from the experimental loop of the land simulation platform to the marine environment through a mapping relationship model.

2. The calibration method for a simulation verification system for submarine cable fault location according to claim 1, characterized in that, In S1, the device attitude information includes roll, pitch, and heading; the three-axis magnetic field strength information includes magnetic flux in the X, Y, and Z directions; and the device height information is relative to sea level.

3. The calibration method for a simulation verification system for submarine cable fault location according to claim 1, characterized in that, In S2, high-frequency random noise is eliminated by wavelet transform thresholding, signal drift in dynamic environments is compensated by adaptive Kalman filtering, and geomagnetic background field is eliminated by magnetic dipole model inversion.

4. The calibration method for a simulation verification system for submarine cable fault location according to claim 3, characterized in that, The process of eliminating high-frequency random noise using the wavelet transform thresholding method is as follows: (1) Perform wavelet transform on the collected information, and select the wavelet basis function and the number of decomposition layers; (2) Thresholding is performed on the coefficients of each layer after wavelet transform; the wavelet coefficients corresponding to noise are removed by thresholding, and the coefficients corresponding to the main features of the signal are retained; (3) Perform wavelet reconstruction on the wavelet coefficients after thresholding to obtain the information after noise reduction by wavelet transform thresholding.

5. The calibration method for a simulation verification system for submarine cable fault location according to claim 3, characterized in that, The process of using adaptive Kalman filtering to compensate for signal drift in dynamic environments is as follows: (1) Establish the state equation and observation equation of the sensor; (2) Initialize the parameters of the Kalman filter; the parameters include the initial state estimate, the initial error covariance matrix, the process noise covariance matrix, and the observation noise covariance matrix; (3) Predict the system state and error covariance matrix at the current moment based on the state equation, calculate the Kalman gain based on the observation equation and the actual observation value, and update the system state estimate and error covariance matrix; Through iteration and updates, real-time estimation of sensor status and noise compensation are achieved.

6. The calibration method for a simulation verification system for submarine cable fault location according to claim 3, characterized in that, The processing procedure for the magnetic dipole model is as follows: (1) The current in the submarine cable is assumed to be a series of magnetic dipoles; (2) Calculate the magnetic field strength generated by each magnetic dipole at the sensor position according to the magnetic field calculation formula of the magnetic dipole; (3) Superimpose the magnetic field strength generated by all magnetic dipoles at the sensor position to obtain the theoretical value of the magnetic field strength generated by the submarine cable at the sensor position under ideal conditions; (4) The actual measured magnetic field strength information after the first two stages of noise reduction is compared with the theoretical value calculated by the magnetic dipole model. The model parameters are adjusted and optimized by the least squares method to further remove residual noise and errors and obtain the final noise-reduced information.

7. The calibration method for a simulation verification system for submarine cable fault location according to claim 1, characterized in that, In S3, the process of obtaining the time-frequency domain feature parameters of the noise-reduced information is as follows: (1) Perform time-frequency analysis on the noise-reduced information and use short-time Fourier transform to convert the time-domain signal into the time-frequency domain; (2) Extract fault feature signals from the time-frequency domain representation, and determine the feature parameters that can accurately characterize submarine cable faults by comparing and analyzing the time-frequency domain features of normal signals and fault signals.

8. The calibration method for a simulation verification system for submarine cable fault location according to claim 1, characterized in that, The process of fusing the improved particle swarm optimization algorithm and the impedance matrix analysis method is as follows: (1) Fault location estimation is obtained by fusing and improving the particle swarm algorithm; (2) The estimation results of the fault location are verified and optimized by impedance matrix analysis.

9. The calibration method for a simulation verification system for submarine cable fault location according to claim 1, characterized in that, Between S1 and S2, there is also a process of filtering the information.

10. A simulation verification system for implementing the calibration method of any one of claims 1-9 for submarine cable fault location, characterized in that, The system includes an integrated sensor array arranged in a ring above the submarine cable, which includes a GPS positioning sensor, a three-dimensional device attitude sensor, a three-axis magnetic field detection sensor, and a barometric altitude sensor. The submarine cable and sensors are housed within the shielding device.

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