Method and system for monitoring scour length of pile foundation landing section of submarine cable based on optical fiber sensing

Abstract

The application relates to the technical field of optical fiber sensing data analysis, and discloses a pile foundation landing section submarine cable scour length monitoring method and system based on optical fiber sensing, which comprises the following steps: acquiring a smooth vibration sequence corresponding to a denoised original discrete vibration matrix of a submarine cable optical fiber in a specified area, decomposing into K intrinsic mode functions (IMFs) in a specified window through VMD, and obtaining each IMF component and a corresponding central frequency through ADMM iteration solution; according to M sensitive IMF components screened out according to the calculation of a correlation coefficient and an envelope compensation distance for each IMF component, linearly fusing multiple features according to a specified weight to obtain a comprehensive feature intensity curve distributed along the submarine cable; and automatically searching and positioning a trumpet mouth position and a mud entry point position on the comprehensive feature intensity curve by using off-line finite element simulation calibrated coordinates and a mapping function, acquiring the total length of a hanging section and a lying section, taking a median value in the latest sampling result, and then outputting a final length in real time, so that high-precision online monitoring of a submarine cable scour state is realized.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of optical fiber sensing data analysis, and particularly relates to a pile foundation landing section submarine cable scour length monitoring method and system based on optical fiber sensing. BACKGROUND

[0002] In modern offshore wind power and communication infrastructure construction, the landing section of the submarine cable pile foundation as the key connecting part of the submarine cable and the land facility often appears complex working conditions such as exposure, suspension or re-burial due to the action of sea current, tide and seabed scour. Once the exposed section of the submarine cable is affected by scour, the mechanical vibration and structural strength of the submarine cable will change significantly, and if it is not found and evaluated in time, it will directly threaten the mechanical integrity of the cable and the safe operation of the communication and power supply system.

[0003] At present, the monitoring of the scour state of the landing section of the submarine cable mainly relies on the following technical means: manual diving and remote visual inspection, single-point mechanical sensor, acoustic and optical remote sensing technology and distributed acoustic sensing (DAS) technology.

[0004] Among them, the first way needs divers or underwater robots to carry a camera device to regularly patrol the exposed section of the submarine cable, and to judge the scour position and depth by manual visual inspection. This way is subject to diving depth, visibility and weather sea conditions, has high cost and long cycle, and cannot realize continuous online monitoring, and is difficult to deal with sudden scour or rapidly changing seabed dynamic environment. Accelerometers, strain gauges and other single-point sensors are laid on the surface or around the submarine cable, and the local scour condition is evaluated through vibration or stress data. Since the number of sensor laying points is limited, the whole exposed submarine cable cannot be covered, and the single-point data is easily disturbed by the local environment, and it is often difficult to accurately reflect the whole scour length and its evolution over time.

[0005] The use of sonar, underwater laser scanning and other remote sensing means to measure the cross section of the seabed can obtain seabed burial depth change information to some extent. However, such devices have large size, high power consumption, and high deployment and maintenance cost, and the acoustic beam and optical detection are easily disturbed in complex seabed environment, and the measurement accuracy and resolution are limited. DAS technology can obtain vibration information along the cable by continuously measuring the phase or intensity change of the scattered signal, has the advantages of wide coverage, flexible laying and no power supply. In recent years, DAS has been applied to the health monitoring of shore-based structures or the vibration detection of the submarine cable burial section, but it still faces great challenges in the scour monitoring of the landing section of the submarine cable. SUMMARY

[0006] In order to be able to monitor the scour length of the landing section of the submarine cable in a complex seabed environment with high precision and online, the present application provides a pile foundation landing section submarine cable scour length monitoring method and system based on optical fiber sensing.

[0007] In a first aspect, the application provides a pile landing section submarine cable scour length monitoring method based on optical fiber sensing, which adopts the following technical solution:

[0008] The pile landing section submarine cable scour length monitoring method based on optical fiber sensing comprises:

[0009] Step S1, based on the pre-set DAS system, the submarine cable optical fiber in the specified area is collected at a fixed period to obtain the corresponding original discrete vibration matrix , wherein is the optical fiber spatial coordinate, is the sampling sequence number;

[0010] Step S2, the first-order time domain difference of each optical fiber spatial coordinate under each sampling sequence number of the original discrete vibration matrix is calculated , and then the Gaussian kernel weighted average is applied in the direction of the optical fiber spatial coordinate to obtain the smoothed vibration sequence after noise reduction ;

[0011] Step S3, the smoothed vibration sequence is adaptively decomposed into K intrinsic mode functions (IMFs) in a specified window using VMD, and the penalty factor and the K value are updated in a linear mapping manner according to the average tidal level of the current window and the pre-set historical maximum and minimum tidal levels;

[0012] Step S4, ADMM iteration is used to solve each IMF component and its corresponding center frequency;

[0013] Step S5, the correlation coefficient and the envelope compensation distance of each IMF component are calculated, and M sensitive IMF components related to the submarine cable scour vibration height are selected according to the adaptive double-threshold strategy;

[0014] Step S6, for the M sensitive IMF components, the transient energy , the envelope spectrum main frequency , the correlation coefficient , and the two groups of tidal quality functions of the average tidal level and the tidal level change rate extracted based on the tidal harmonic model are extracted according to each optical fiber spatial coordinate , the weighted features of the M sensitive IMF components are summed after being weighted according to the specified weight, and then linearly fused with the weighted values of the two groups of tidal quality functions to obtain the comprehensive feature intensity curve along the spatial distribution of the submarine cable ;

[0015] Step S7, the coordinate and mapping function calibrated by offline finite element simulation are used , in the integrated feature strength curve automatically search and locate the trumpet mouth position and the mud entry point position ;

[0016] Step S8, calculate the total length of the overhanging section and the lying section from the trumpet mouth to the mud entry point , in the latest sampling results, output the final length in real time after taking the median value .

[0017] Optionally, the step S2 comprises:

[0018]

[0019]

[0020] wherein, is the adjacent sampling distance, is the sliding window index, .

[0021] Optionally, the step S3 comprises:

[0022] The intrinsic modal function IMF is , by solving the following constraint optimization:

[0023]

[0024] wherein, is the Dirac impact function, the penalty factor ensures that the sum of all modes can reconstruct the original signal, is the kth mode center frequency, is the partial derivative operator with respect to time t, is the imaginary unit, is the abbreviation of the kth intrinsic modal function at any spatial point p, and the same applies to The time domain simplified expression of ;

[0025]

[0026]

[0027] wherein, and are the empirical initial values, and are the corresponding item adjustment coefficients, is the average tidal level of the current window, , is the historical maximum and minimum tidal level.

[0028] Optionally, the step S4 comprises:

[0029] Step S41, decoupling the convolution in the frequency domain with FFT, fixing updating , converting the convolution operation into multiplication in the frequency domain with fast Fourier transform, for each of the K solving :

[0030]

[0031] Step S42, fixing updating , calculating :

[0032]

[0033] wherein, is the Fourier transform of ;

[0034] Step S43, updating the Lagrange multiplier function for each of the K modalities; according to the current reconstruction residual , adjusting the Lagrange multiplier and dynamically according to to accelerate the convergence;

[0035] wherein, is the continuous time domain representation of the smoothed vibration sequence in step S2, is the penalty factor in step S3 a penalty parameter for linear correlation, used to balance the reconstruction error weight, and The standard for iterative convergence is that all modalities and frequencies satisfy and , and are preset convergence criterion thresholds.

[0036] Optionally, the step S5 comprises:

[0037] for each of the K IMFs decomposed in step S3 , performing Hilbert transform in the current time window to extract the envelope signal , wherein is the total number of N times of sampling in the selected time window;

[0038] Let the previous The mean of the static baseline envelope estimated from the non-eroding data After the length of the time window is N, the envelope compensation distance of the kth IMF component is calculated in the current window :

[0039] Wherein, is the latest sampling sequence number;

[0040] The kth IMF component is calculated from the original difference sequence The Pearson correlation coefficient in the same window :

[0041]

[0042] Set the threshold And Adopt a double-threshold adaptive updating mechanism, and each spatial coordinate of the fiber of each IMF component At the same time satisfies And The one that satisfies is reserved as a sensitive mode, and M sensitive IMF components are obtained .

[0043] Optionally, the step S6 comprises:

[0044] Step S61, construct transient energy ;

[0045] Discrete Fourier transform is performed on the envelope signal of each IMF component :

[0046]

[0047] The main frequency is That is, the frequency at which the envelope energy is the highest, The envelope spectrum of the mth sensitive IMF component, The Fourier transform is, The frequency is, The discrete sampling sequence number is, The latest sampling sequence number of the current analysis window is;

[0048] According to the following two formulas, the average tidal level And the tidal level change rate :

[0049]

[0050]

[0051] Standardize each feature into a quality evaluation function:

[0052]

[0053] wherein, is the relative energy contribution of the mth sensitive modality, is the sum of transient energy, is the closeness of the mth modality dominant frequency to the reference frequency, is the typical reference frequency of scour vibration, is the allowed frequency offset range, is the correlation quality function;

[0054] Normalized tidal feature quality evaluation function:

[0055]

[0056] weighted by Linearly weighted, finally summed up at each p for all M modalities to construct a comprehensive feature intensity sequence:

[0057]

[0058] wherein, is the normalized mean tidal level, is the normalized tidal level change rate, is the absolute value of the tidal level change rate, is the historical maximum tidal level change rate.

[0059] Optionally, the step S7 comprises:

[0060] Three-dimensional finite element stress-vibration coupling simulation is performed on the landing section of the submarine cable pile foundation to obtain the stress distribution of the J-shaped pipe section, the buried section, the suspended scouring section, and the lying section under the typical current and self-weight working conditions;

[0061] On the simulated stress gradient curve, the maximum stress gradient coordinates at the horn mouth and the maximum stress gradient coordinates at the mud entry point are respectively calibrated;

[0062] Let the mapping function convert the optical fiber space coordinates into the simulation structure coordinates The function is linearly fitted through the known optical fiber layout length and the geometric relationship of the simulation model;

[0063] Among all the optical fiber coordinates that satisfy , let be used to locate the horn mouth position;

[0064] In the interval , let be used to locate the mud entry point position;

[0065] wherein, is the mouth coordinate, is the touch point coordinate, is the simulation calibration interval tolerance, searching for the maximum value of the characteristic curve in the specified center coordinate interval.

[0066] Optionally, the step S8 comprises:

[0067] Step S81, using the spatial coordinate difference value ;

[0068] Step S82, the nearest repeatedly performing step S6 and distance calculation within the nearest , and outputting the final length using the median or weighted average method .

[0069] In the second aspect, the application provides a pile foundation landing section submarine cable scour length monitoring system based on optical fiber sensing, which runs the program of the pile foundation landing section submarine cable scour length monitoring method based on optical fiber sensing described in any one of the above.

[0070] In summary, the application has the following at least beneficial technical effects:

[0071] The application combines DAS optical fiber sensing with VMD-IMF screening algorithm, overcomes the inefficiency and subjectivity of manual visual interpretation of vibration curves in the existing verification process, fully utilizes the distributed data advantage of DAS, overcomes the limitations of traditional vibration signal processing in time and frequency domain separation, automatically extracts the scour feature points through an adaptive algorithm, and combines the stress simulation results and the processing of marine tide characteristics to realize accurate positioning of the vibration peak value, calculates and tracks the total length of the "suspended + lying section" of the submarine cable exposed section, to meet the urgent needs of submarine cable safety operation and risk warning, can automatically extract the three key vibration peak points of the mouth, touch point and entry point in an unattended state, and calculate the sum of the suspended length and the lying length from the mouth to the entry point, realize high-precision online monitoring of the submarine cable scour state, and has important engineering application value and broad application prospect. BRIEF DESCRIPTION OF DRAWINGS

[0072] Figure 1 is the flowchart of the pile foundation landing section submarine cable scour length monitoring method in the application;

[0073] Figure 2 is the key point division diagram of the pile foundation landing section in the application;

[0074] Figure 3 is the sonar scanning data mapping of the pile foundation in the application;

[0075] Figure 4is a distribution diagram of the pile foundation fusion characteristic value in the application under a typical tide level 1;

[0076] Figure 5 is a distribution diagram of the pile foundation fusion characteristic value in the application under a typical tide level 2;

[0077] Figure 6 is a distribution diagram of the pile foundation fusion characteristic value in the application under a typical tide level 3;

[0078] Figure 7 is a distribution diagram of the pile foundation fusion characteristic value in the application under a typical tide level 4;

[0079] Figure 8 is a table of scour lengths and mean values under each typical tide level in the application. DETAILED DESCRIPTION

[0080] Embodiments of the application are described in detail below, examples of which are shown in the accompanying drawings.

[0081] In the description of the present specification, the description of the terms "certain embodiments", "one embodiment", "some embodiments", "illustrative embodiments", "example", "specific example", or "some examples" means that the specific features, structures, materials or characteristics described in connection with the described embodiments or examples are included in at least one embodiment or example of the present application. In the present specification, the illustrative description of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0082] The pile foundation landing section submarine cable scour length monitoring method based on optical fiber sensing is disclosed in the embodiments of the application, referring to Figure 1 and Figure 2 , a method capable of autonomously extracting the horn mouth and the mud entry point positions according to the submarine cable vibration data characteristics, and further calculating the pile foundation side submarine cable scour length is provided, including:

[0083] Step S1, based on the pre-set DAS system, the submarine cable optical fiber in the 400m range interval of the pile foundation landing section submarine cable is collected with a fixed period of 24min to obtain the corresponding original discrete vibration matrix , ;

[0084] Specifically, is the spatial coordinate of the optical fiber, For sampling sequence number, the DAS system uses a single-mode optical fiber sensing cable and a distributed acoustic wave sensing system. The single-mode optical fiber sensing cable is covered with a waterproof and pressure-resistant sheath, and is spirally wound along the pile foundation cable optical fiber. The adjacent sampling space interval is 5m, and there are a total of 81 sampling points.

[0085] Step S2, calculate the first-order time domain difference of each optical fiber spatial coordinate under each sampling sequence number of the original discrete vibration matrix , remove the drift and suppress the measurement point noise in the spatial domain, and then suppress the small-scale spatial noise caused by the joint and uneven laying by =5 adjacent sampling points (covering the front and rear two points, and the window width is about 20m) and the Gaussian kernel width =10m as parameters, applying Gaussian kernel weighted average in the direction of the fiber spatial coordinate to obtain the smoothed vibration sequence after noise reduction , wherein .

[0086] ;

[0087] .

[0088] Step S3, the smoothed vibration sequence is decomposed into K intrinsic mode functions (IMF) in the specified window by adaptive VMD, and the penalty factor and the mode number K value are updated in a linear mapping manner according to the average tidal level of the current window and the preset historical maximum and minimum tidal level;

[0089] Specifically, the theoretical basis of VMD decomposition is an optimization problem based on continuous time domain, which is derived from a continuous mathematical model. In the following, the algorithm theory will be described in continuous time t. The intrinsic mode function (IMF) is , which is a function of spatial coordinate p and time t.

[0090] When performing VMD decomposition, the algorithm will process the time domain signal corresponding to each independent spatial coordinate point p. For the sake of brevity and consistency with the standard algorithm, the spatial parameter p will be omitted in the following description, and is used to represent the kth intrinsic mode function at any specified spatial point p. Similarly, in the formula, is a simplified representation of the time domain transformation of the smoothed vibration sequence obtained in step S2, by solving the following constrained optimization:

[0091]

[0092] where, is the Dirac impulse function, and the penalty factor Ensuring the sum of all modes can reconstruct the original signal, is the center frequency of the kth mode, is the partial derivative operator with respect to time t, is the imaginary unit; to take into account the signal bandwidth characteristics under different tidal conditions, the linear function is updated according to the current time window average tide level and the upper and lower limits of the historical typical tide level:

[0093]

[0094]

[0095] wherein, and are the empirical initial values, and are the corresponding item adjustment coefficients, is the average tide level of the current window, , are the historical maximum and minimum tide levels. Then, the updated and K are used to reinitialize the VMD parameters until convergence; this adjustment is performed once before each complete decomposition, so that VMD uses a larger and richer number of modes K during the rising tide; and a smaller and richer number of modes K during the falling tide, to adaptively balance noise suppression and signal detail extraction.

[0096] Step S4, ADMM iteration is used to solve each IMF component and its corresponding center frequency;

[0097] Specifically:

[0098] Step S41, in the frequency domain, use FFT to decouple convolution, fix update To mathematically clearly describe the iterative update process of the algorithm, the variables of different iteration steps will be distinguished by using superscripts in the following text. Specifically, the symbol represents the kth IMF component solved in the n+1th iteration, and the convolution operation is converted into multiplication in the frequency domain using fast Fourier transform. For each IMF component solved as a time-domain signal :

[0099]

[0100] Step S42, fix update , according to the spectral center of the current kth mode :

[0101]

[0102] wherein, is the Fourier transform of

[0103] Step S43, update the Lagrange multiplier function corresponding to each mode k. Wherein, the penalty parameter used by the ADMM solver corresponds to the penalty factor of the VMD model in step S3. In order to ensure the stability of the algorithm convergence, the relationship is set as in the embodiment. According to the current reconstruction residual , the Lagrange multiplier is dynamically adjusted according to to speed up the convergence;

[0104] wherein, is the VMD algorithm input original signal, a simple notation of the smoothed vibration sequence in step S2, used to balance the weight of reconstruction error in the entire optimization problem, and The standard for iterative convergence is that all modes and frequencies satisfy and , and are preset convergence criterion thresholds, and the specific numerical values are set as and .

[0105] Step S5, calculate the correlation coefficient and the envelope compensation distance for each IMF component, and select K sensitive IMF components related to the scouring vibration of the submarine cable according to the adaptive double-threshold strategy;

[0106] Specifically, in order to eliminate noise and invalid components and retain the modes sensitive to scouring vibration, the IMF components are quantitatively screened in space p and sampling number i.

[0107] Firstly, Hilbert transform is performed on each of the IMF components in the current time window to extract the envelope signal , wherein is the total number of N times of sampling in the selected time window;

[0108] Let the static baseline envelope mean estimated by the previous non-scouring data be , and the envelope compensation distance of the kth IMF component in the current window is calculated as :

[0109] wherein, The latest sampling sequence number;

[0110] Then, the data within the window is averaged, and the k-th IMF component is calculated. Compared with the original difference sequence Pearson correlation coefficient within the same window This is used to assess the correlation between the modal component and the original vibration.

[0111]

[0112] Set threshold and It adopts a dual-threshold adaptive update mechanism, which is automatically determined by historical non-scour data and updated according to the 90th percentile during operation. Updated by 10th percentile For each IMF component, each fiber spatial coordinate At the same time satisfy and Those that are selected are retained as sensitive modes; otherwise, they are discarded. After the above filtering, M sensitive IMF components are obtained. .

[0113] Step S6, for the M sensitive IMF components, based on the spatial coordinates of each fiber... Extracting transient energy Envelope spectrum dominant frequency Correlation coefficient And the average tidal level automatically extracted based on the tidal harmonic model. and tidal level change rate Two sets of tidal mass functions are linearly fused with specified weights to obtain the comprehensive characteristic intensity curve of the spatial distribution of coastal cables. ;

[0114] Specifically, step S6 includes:

[0115] Step S61, construct transient energy ;

[0116] The envelope signal for each of the IMF components Performing the discrete Fourier transform, we get:

[0117]

[0118] The main frequency is That is, the frequency at the highest point of the envelope energy. Let m be the envelope spectrum of the m-th sensitive IMF component. For Fourier transform, For frequency, For discrete sampling sequence number, the latest sampling number of the current analysis window;

[0119] The average tidal level is extracted according to the following two formulas and the tidal level change rate :

[0120]

[0121]

[0122] The features are normalized into quality evaluation functions:

[0123]

[0124] wherein, is the relative energy contribution of the mth sensitive mode, is the sum of transient energy, is the closeness of the mth mode dominant frequency to the reference frequency, is the typical reference frequency of scour vibration, is the allowed frequency deviation range, is the correlation quality function;

[0125] The normalized tidal feature quality evaluation function:

[0126]

[0127] According to the weight linearly weighted, finally at each p, the weighted features of all M modes are summed up, and the weighted values of the tidal features are linearly fused to construct a comprehensive feature intensity sequence:

[0128]

[0129] wherein, is the normalized average tidal level, is the normalized tidal level change rate, is the absolute value of the tidal level change rate, is the historical maximum tidal level change rate.

[0130] The fusion feature intensity curve along the 400m submarine cable section is calculated for a typical tidal level working condition , Figures 4-7 The main feature part of the data graph is intercepted, Figure 4 It can be seen that a pair of adjacent secondary peaks appear at p≈166.4m and p≈174.2m, corresponding to the vibration branches near the horn; the highest main peak appears at p≈243.2m, corresponding to the vibration jump before the mud entry point; and the secondary peak appearing at p≈297.3m corresponds to the secondary vibration near the mud entry point of the outlet end.

[0131] Step S7, calibrate the coordinates and mapping function using offline finite element simulation , the comprehensive characteristic intensity curve Automatically search and locate the horn mouth position And the entry point position ;

[0132] Specifically, step S7 includes:

[0133] Perform three-dimensional finite element stress-vibration coupling simulation on the landing section of the submarine cable pile foundation to obtain the stress distribution of the J-shaped pipe section, the buried section, the suspended scouring section, and the lying section under typical current and self-weight working conditions;

[0134] On the simulation stress gradient curve, calibrate the maximum stress gradient coordinates at the horn mouth and the maximum stress gradient coordinates at the entry point, respectively;

[0135] Let the mapping function Convert the optical fiber space coordinates To simulation structure coordinates This function is linearly fitted by the known optical fiber layout length and the geometric relationship of the simulation model;

[0136] Among all the optical fiber coordinates that satisfy Let Be used to locate the horn mouth position;

[0137] In the interval Let Be used to locate the entry point position;

[0138] Wherein, The simulation calibration interval tolerance. Through the above mapping and automatic peak search, the vibration peak positions of the horn mouth and the entry point can be accurately obtained in the optical fiber space coordinate system, providing accurate and reproducible basis for subsequent scouring length calculation.

[0139] Step S8, calculate the total length of the suspended section and the lying section from the horn mouth to the entry point Take the median of the latest sampling results to output the final length in real time .

[0140] Specifically, step S81, use spatial coordinate difference ;

[0141] Step S82, repeatedly perform step S6 and distance calculation within the latest sampling to obtain a series of distance values , and output the final length using the median or weighted average method It also enables integrated assessment under multiple typical tidal conditions.

[0142] When a data matrix with a new sampling sequence number is received, the algorithm locates the position in step S7. and At this location, the length of this scour is directly calculated based on the spatial coordinate difference: m, where m is the unit of measurement for meters. Tidal features automatically extracted in synchronization step S3. and The operating condition label used in this sampling is therefore used for each All correspond to their tidal characteristics and require no manual intervention. To eliminate occasional interference and short-term fluctuations, the algorithm maintains a window of length after each run. Take the median and output the final length. The analysis compares the working conditions of the algorithm under multiple typical tidal levels, and the scour length and mean value under each typical tidal level are statistically analyzed. Figure 8 The table shown.

[0143] according to Figure 3 As shown, the mud outlet and the funnel-shaped inlet correspond to the No. 1 submarine cable area, which is the part where other pile foundation submarine cables enter the pile foundation shown; the funnel-shaped inlet and the mud entry point correspond to the No. 2 submarine cable area, which is the part where the shown pile foundation submarine cables enter other pile foundations. The overall fluctuation of the unilateral scour length calculated from the four typical tide levels is ≤0.8m.

[0144] The above-described specific implementation methods demonstrate that, under unattended operation, this invention achieves high-precision online monitoring of the scour length of the submarine cable's "suspended section + horizontal section" at the pile foundation landing section through fully automated data acquisition, signal preprocessing, VMD-IMF decomposition and filtering, tidal feature fusion, simulation mapping, and peak location and length calculation. The process is logically rigorous, parameters are transparent, and it is easy to deploy in engineering applications.

[0145] This application also discloses a fiber optic sensing-based system for monitoring the scour length of submarine cables in the pile foundation landing section, including a processor running a program for the fiber optic sensing-based method for monitoring the scour length of submarine cables in the pile foundation landing section as described above.

[0146] Although embodiments of this application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting this application. Those skilled in the art can make changes, modifications, substitutions and variations to the above embodiments within the scope of this application.

Claims

1. A method for monitoring scour length of a landing section of a submarine cable based on optical fiber sensing, characterized in that, Comprising: Step S1, based on the pre-set DAS system to the specified area within the submarine cable optical fiber with fixed period Data acquisition is carried out to obtain the corresponding original discrete vibration matrix Wherein The spatial coordinates of the optical fiber are The sample serial number is Step S2, calculating the first-order time-domain difference for each fiber spatial coordinate under each sampling sequence number of the original discrete vibration matrix Then, a Gaussian kernel weighted average is applied in the direction of the fiber spatial coordinate to obtain a smoothed vibration sequence after noise reduction ; Step S3, adaptively decomposing the smooth vibration sequence into K intrinsic mode functions (IMFs) in a specified window, updating the penalty factor in a linear mapping manner according to the average tidal level of the current window and the preset historical maximum and minimum tidal levels and the value of K; Step S4, using ADMM iteration to solve each IMF component and its corresponding center frequency; Step S5, calculate the correlation coefficient for each IMF component The envelope compensation distance M sensitive IMF components highly related to the scouring vibration of the submarine cable are screened out according to an adaptive double-threshold strategy. Step S6, for M sensitive IMF components, the spatial coordinates of each optical fiber are determined according to the spatial coordinates of the optical fiber Extracting transient energy , envelope spectrum main frequency , correlation coefficient , and the average tidal level automatically extracted based on the tidal harmonic model and the rate of change of tidal level Two groups of tidal quality functions, linearly fused according to the specified weight, get the comprehensive characteristic intensity curve of the spatial distribution of the coastal cable ; Step S7, calibrate the coordinates and mapping function using offline finite element simulation , the integrated feature intensity curve The horn mouth position is automatically searched and located and the entry point position ; Step S8, calculate the total length of the overhanging section and the lying section from the trumpet mouth to the entry point In recent After taking the median value in the subsampling result, output the final length in real time .

2. The optical fiber sensing based monitoring method of the scour length of the landing section of the pile foundation of the submarine cable according to claim 1, characterized in that, The step S2 comprises: wherein, is the adjacent sampling distance, is the sliding window index, .

3. The optical fiber sensing based monitoring method of the scour length of the landing section of the pile foundation of the submarine cable according to claim 1, characterized in that, The step S3 comprises: The intrinsic mode functions IMFs are by solving the following constrained optimization: wherein, is the Dirac delta function, and ensures that the sum of all modes reconstructs the original signal, is the kth modal center frequency, is the partial derivative with respect to time t, is the imaginary unit, is a simplified representation of the eigenmode function at a single spatial coordinate p, is the input signal after the smoothing of the vibration sequence of step S2 is continued at a single spatial coordinate p; wherein, and are empirical initial values, and are the corresponding item adjustment coefficients, is the average tide level of the current window, , are the historical maximum and minimum tide levels.

4. The optical fiber sensing based monitoring method of the scour length of the landing section of the pile foundation of the submarine cable according to claim 3, characterized in that, The step S4 comprises: Step S41, decoupling convolution in frequency domain with FFT, fixing updating In frequency domain, the convolution operation is converted into multiplication by using fast Fourier transform, and each piece of solving : Step S42, fixing updating , according to the spectrum center of the current kth modality : wherein is the Fourier transform of Step S43, the Lagrange multiplier function corresponding to each modality k is updated ; According to the current reconstructed residual ; According to dynamically adjust the Lagrange multiplier to accelerate convergence; wherein, is a continuous time domain representation of the smoothed vibration sequence described in step S2, is the penalty factor described in step S3 is a linearly dependent penalty parameter for balancing the reconstruction error weights, and The criterion for iterative convergence is when all modes and frequencies satisfy and , and is a pre-set convergence criterion threshold.

5. The optical fiber sensing based monitoring method of the scour length of the landing section of the pile foundation of the submarine cable according to claim 1, characterized in that, The step S5 comprises: Decompose each of the K IMFs obtained in step S3 , do Hilbert transform in the current time window, extract the envelope signal , where is the total number of N samples in the selected time window​ Let the mean of the static baseline envelope of the non-eroded data estimates , after the time window length N, the envelope compensation distance of the k-th IMF component is calculated within the current window : wherein, is the latest sampled sequence number; Compute the kth IMF component and the original difference sequence Pearson correlation coefficient within the same window : Setting threshold And , using double threshold adaptive updating mechanism, for each IMF component, each fiber spatial coordinate satisfies and at the same time, it is retained as a sensitive mode, and M sensitive IMF components are obtained.

6. The optical fiber sensing based monitoring method of the scour length of the landing section of the pile foundation of the submarine cable according to claim 3, characterized in that, The step S6 comprises: Step S61, constructing transient energy ; a packet signal network for each of the IMF components Discrete Fourier transform gives The main frequency is is the frequency at which the envelope energy is highest, is the envelope spectrum of the m-th sensitive IMF component, is the Fourier transform, is the frequency, is the discrete sampling number, is the latest sampling number of the current analysis window; The mean tidal level is extracted according to the following two equations and the rate of change of tidal level : Normalizing each feature into a quality evaluation function: wherein, is the relative energy contribution of the m-th sensitive modality, is the sum of transient energies, is the closeness of the m-th modality dominant frequency to the reference frequency, is the typical reference frequency of the scouring vibration, is the frequency shift range of the m-th modality, is the correlation quality function; The normalized tidal feature quality evaluation function: By weight The weighted features of the M sensitive IMF components are summed up, and then linearly fused with the weighted values of the two groups of tidal quality functions to obtain a comprehensive feature intensity curve of the spatial distribution of the coastal cable : wherein, is the normalized mean water level, is the normalized rate of change of water level, is the absolute value of the rate of change of water level, is the historical maximum rate of change of water level.

7. A fibre optic sensing based method of monitoring scour length of a landing section of a pile foundation of a subsea cable as claimed in claim 6, wherein, The step S7 comprises: Performing three-dimensional finite element stress-vibration coupling simulation on the submarine cable pile foundation landing section to obtain stress distribution of the J-shaped pipe section, the buried section, the suspended scouring section and the lying section under typical current and self-weight working conditions; On the simulated stress gradient curve, the maximum stress gradient coordinates at the horn mouth and the maximum stress gradient coordinates at the mud entry point are calibrated respectively; Let the mapping function converts the optical fiber spatial coordinates to simulation structure coordinates This function is linearly fitted by known optical fiber layout length and simulation model geometry relationship; In all sets of fiber coordinates satisfying Let for positioning the mouth position; In interval, let for positioning the touch-down point position; wherein, is the coordinate of the horn, is the coordinate of the touch point, is the simulation calibration interval tolerance, searching for the maximum value of the characteristic curve within the specified center coordinate interval.

8. The optical fiber sensing based monitoring method of the scour length of the landing section of the pile foundation of the submarine cable according to claim 1, characterized in that, The step S8 comprises: Step S81, adopt spatial coordinate difference value ; Step S82, the most recent Step S6 and distance calculation are performed repeatedly within the sub-sampling to obtain a series of distance values And the final length is output in the form of median or weighted average .

9. A system for monitoring scour length of a landing section of a submarine cable based on optical fiber sensing, characterized in that, A program running has the pile foundation landing section submarine cable scouring length monitoring method based on optical fiber sensing of any one of claims 1-8.

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