An integrated system and method for submarine cable accurate positioning and acousto-optic shock state monitoring

Abstract

The application discloses a submarine cable precise positioning and acousto-optic vibration state monitoring integrated system and method, and relates to the technical field of submarine state monitoring.The method comprises the following steps: based on anchor point information located on a submarine cable and having known absolute three-dimensional coordinates, the coordinates of all points of the submarine cable are dynamically corrected by calculating the theoretical and actual arrival time deviation of an acoustic signal at the anchor point, so as to generate a self-calibration three-dimensional space reference model; taking the self-calibration three-dimensional space reference model as a space input reference, a continuously swept acoustic signal of active emission is used to excite the submarine cable, and by analyzing the frequency response spectrum of the optical fiber vibration signal of the coordinate point, an abnormal resonance peak representing a suspension state is identified, so as to diagnose the physical state of the coordinate point.The application solves the technical problem that the state monitoring result is unreliable due to the fact that the prior art cannot establish an accurate space reference, and can realize remote and deterministic diagnosis of the suspension fault of the submarine cable.

Description

Technical Field

[0001] This invention relates to the field of seabed condition monitoring technology, and in particular to an integrated system and method for precise positioning of submarine cables and acoustic-optical-seismic condition monitoring. Background Technology

[0002] Submarine cables are critical infrastructure for long-distance power and information transmission. Ensuring their structural integrity and operational safety is of paramount importance. Existing technologies typically employ distributed fiber optic sensing to monitor vibration, temperature, and other conditions along the cable route. However, this monitoring method has an inherent technical limitation: it suffers from an "inaccuracy" dilemma when diagnosing physical faults such as cable suspension that pose a serious threat to structural safety.

[0003] This predicament stems from two mutually constraining factors: First, due to seabed erosion, geological activity, and other influences, the actual three-dimensional spatial position of the submarine cable deviates from the initial laying record, lacking a real-time, accurate global spatial reference. Second, passive condition monitoring relies on the analysis of environmental vibration signals, which have fuzzy signal characteristics and low signal-to-noise ratios, making it difficult to reliably correlate an uncertain physical state (such as suspected vibration anomalies) with an uncertain spatial location. Therefore, existing technologies cannot remotely and definitively answer the core question, "At which precise location of the submarine cable is an anomaly occurring?" from a shore-based perspective, resulting in low reliability of monitoring results. On-site confirmation using costly and inefficient underwater robots is still typically required. Summary of the Invention

[0004] This invention provides an integrated system and method for precise positioning and acoustic-optical-seismic condition monitoring of submarine cables, in order to solve the technical problems in the prior art, such as unreliable condition monitoring results and inability to accurately locate faults due to the inability to establish a spatial reference that precisely corresponds to the physical entity.

[0005] In view of the above problems, in a first aspect, the present invention provides an integrated method for precise positioning and acoustic-optical-seismic status monitoring of submarine cables, comprising: The dynamic self-calibration step of the three-dimensional spatial reference model is performed. Based on the anchor point information located on the submarine cable and having known absolute three-dimensional coordinates, the coordinates of all points on the submarine cable are dynamically corrected by calculating the theoretical and actual arrival time deviation of the acoustic signal at the anchor point, so as to generate a self-calibrated three-dimensional spatial reference model. The fixed-point resonance state diagnosis step is performed. The self-calibrated three-dimensional spatial reference model is used as the spatial input reference. The submarine cable is excited by actively transmitted continuous sweep frequency acoustic signals. By analyzing the frequency response spectrum of the optical fiber vibration signal at the coordinate point on the self-calibrated three-dimensional spatial reference model, abnormal resonance peaks that characterize the suspension state are identified to diagnose the physical state of the coordinate point.

[0006] Secondly, the present invention also provides an integrated system for precise positioning and acoustic-optical-seismic monitoring of submarine cables, including a processor and a memory. The memory stores a computer program, and when the computer program is executed by the processor, it realizes an integrated method for precise positioning and acoustic-optical-seismic monitoring of submarine cables.

[0007] The technical solution provided in this application has at least the following technical effects: by first performing dynamic self-calibration based on anchor points to generate an accurate spatial reference model, and then performing fixed-point resonance diagnosis based on this model, a vague detection problem is transformed into a process of deterministic physical characteristic measurement in a precisely calibrated coordinate system. This solution achieves deep integration of submarine cable condition monitoring and precise positioning, enabling remote and deterministic identification and location of submarine cable suspension faults, thus improving the reliability and efficiency of diagnosis. Attached Figure Description

[0008] Figure 1 This is a flowchart illustrating the integrated method for precise positioning and acoustic-optical-seismic status monitoring of submarine cables in an embodiment of the present invention. Figure 2 This is a system structure diagram of the integrated system for precise positioning and acoustic-optical-seismic status monitoring of submarine cables in an embodiment of the present invention. Detailed Implementation

[0009] The above technical solutions will now be described in detail with reference to the accompanying drawings and specific embodiments to provide a better understanding of them. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. It should be understood that the present invention is not limited to the exemplary embodiments used only to explain the present invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention. Furthermore, it should be noted that, for ease of description, only the parts related to the present invention are shown in the drawings, not all of them.

[0010] Please see Figure 1 An integrated method for precise positioning and acoustic-optical-seismic condition monitoring of submarine cables includes: The dynamic self-calibration step of the three-dimensional spatial reference model is performed. Based on the anchor point information located on the submarine cable and having known absolute three-dimensional coordinates, the coordinates of all points on the submarine cable are dynamically corrected by calculating the theoretical and actual arrival time deviation of the acoustic signal at the anchor point, so as to generate a self-calibrated three-dimensional spatial reference model. The fixed-point resonance state diagnosis step is performed. The self-calibrated three-dimensional spatial reference model is used as the spatial input reference. The submarine cable is excited by actively transmitted continuous sweep frequency acoustic signals. By analyzing the frequency response spectrum of the optical fiber vibration signal at the coordinate point on the self-calibrated three-dimensional spatial reference model, abnormal resonance peaks that characterize the suspension state are identified to diagnose the physical state of the coordinate point.

[0011] In one specific embodiment of the present invention, a dynamic task orchestration and fusion module deployed in a shore-based integrated processing unit initiates a global survey task.

[0012] The module first initializes the diagnostic task by loading preset absolute three-dimensional coordinates of the anchor points from the system configuration database. Simultaneously, the module sends task commands to the marine mobile acoustic source unit via a data communication link. These commands include preset transmission parameters for navigation survey lines and acoustic pulses.

[0013] Upon receiving mission instructions, the marine mobile acoustic source unit transmits acoustic pulse signals and acquires spatiotemporal data. This process is implemented as follows: the unit's control system, based on the transmission parameters in the instructions, drives its onboard sonar transducer to transmit single-frequency acoustic pulses with a center frequency of 150 Hz to the seabed at 100-meter spatial intervals. At the instant of each acoustic pulse transmission, the ship's onboard GPS receiver simultaneously records the current timestamp and the ship's three-dimensional geospatial coordinates. The recorded timestamps and corresponding three-dimensional geospatial coordinates together constitute spatiotemporal data points. The marine mobile acoustic source unit transmits the generated spatiotemporal data point sequence back to the shore-based integrated processing unit in real time via a wireless communication link. Alternatively, the acoustic pulse transmission can be performed at preset time intervals.

[0014] While the mobile acoustic source unit at sea transmits acoustic pulses, a distributed fiber optic sensing system deployed within the shore-based integrated processing unit synchronously receives vibration signals from all optical fibers. This process is achieved as follows: the system's demodulator continuously injects laser pulses into the communication optical fiber in the submarine cable and collects backscattered Rayleigh light signals reflecting the vibration state at various points along the fiber in real time. The demodulator performs photoelectric conversion and phase demodulation on the collected backscattered Rayleigh light signals, outputting multi-channel time-domain vibration waveform data covering the entire submarine cable. Each channel corresponds to a spatial sampling point on the optical fiber. This time-domain vibration waveform data is transmitted via an internal bus to the dynamic task orchestration and fusion module for subsequent processing.

[0015] Next, the dynamic task orchestration and fusion module calculates the deviation between the theoretical and actual arrival times. This step aims to provide a quantitative basis for subsequent positioning correction. Specifically, the module first extracts the timestamp of a specific acoustic pulse emission from the received spatiotemporal data point sequence. and the three-dimensional coordinates of the launch point Subsequently, the module retrieves the known three-dimensional coordinates of the anchor point from the system configuration database. Based on the propagation speed of sound waves in a pre-defined underwater sound speed propagation model, the propagation speed from the emission point is calculated. to anchor point Theoretical propagation time Theoretical arrival time That is equal to At the same time, the module located the anchor point coordinates within the all-fiber vibration waveform data. The corresponding channel, and in the time-domain waveform of that channel, using an energy peak detection algorithm, identifies the moment of the first vibration event triggered by the acoustic pulse, defining it as the actual arrival time. Ultimately, the module calculates the difference between the two, obtaining the time deviation. ,Right now .

[0016] After calculating the time deviation Next, the dynamic task orchestration and fusion module generates and applies the positioning correction. This step is implemented as follows: the module first calculates the positioning correction for any non-anchor point on the submarine cable based on its positional relationship with the anchor point using a preset function. In one specific implementation, this preset function is a linear proportional function, meaning it adjusts the time deviation based on the distance between the non-anchor point and the anchor point along the submarine cable route. Weighted values ​​are applied to obtain a time correction value specific to the non-anchor point coordinates. Alternatively, this preset function can be a more complex nonlinear function to accommodate differences in seabed geological characteristics across different sections. The module applies the calculated time correction value to the preliminary acoustic positioning results of the non-anchor point coordinates, compensating for its arrival time data to generate corrected coordinates. This process is repeated for all non-anchor point coordinates along the submarine cable, ultimately obtaining a set of corrected coordinate points for the entire line.

[0017] After obtaining the fully corrected set of coordinate points, the dynamic task orchestration and fusion module performs the final construction of the self-calibrated 3D spatial reference model. This step is implemented as follows: the module organizes the fully corrected set of coordinate points, along with the geometric parameters of each coordinate point, such as the cable route mileage, curvature, and slope, as well as anchor point information, into a structured 3D data model. This 3D data model is the self-calibrated 3D spatial reference model. This model is stored in the system's database and assigned a unique version identifier. At this point, the entire dynamic self-calibration process of the 3D spatial reference model is completed. This self-calibrated 3D spatial reference model will serve as the spatial input reference for all subsequent diagnostic processes.

[0018] After the self-calibrated three-dimensional spatial reference model is completed, the dynamic task orchestration and fusion module then initiates the full-process implementation of fixed-point resonance state diagnosis.

[0019] This module first specifies the diagnostic area and issues a frequency sweep excitation command. This process is implemented as follows: the module loads a previously generated self-calibrated 3D spatial reference model and receives one or more target areas to be diagnosed from the operator's input on the system interface. The target areas can be defined by the start and end mileage of the submarine cable route. Based on the defined target areas, the module generates an excitation command containing frequency sweep parameters. These parameters define the start frequency, end frequency, and sweep rate; for example, a linear sweep from 10 Hz to 500 Hz at a rate of 10 Hz per second. The module then sends the generated excitation command to the marine mobile acoustic source unit via a data communication link.

[0020] Upon receiving an excitation command, the marine mobile acoustic source unit transmits continuous frequency-sweeping acoustic signals. This process is achieved as follows: the unit's control system analyzes the frequency-sweeping parameters in the command and controls its onboard sonar transducer to continuously transmit frequency-sweeping acoustic signals to the seabed according to the parameters while navigating along the target area. Simultaneously, the unit's GPS receiver records the ship's real-time position and time information and transmits this information back to the shore-based integrated processing unit.

[0021] While the mobile acoustic source unit at sea transmits continuous frequency-sweeping acoustic signals, the shore-based distributed fiber optic sensing system synchronously receives all-fiber vibration signals. The dynamic task orchestration and fusion module then performs frequency response spectrum generation and anomalous resonance peak identification. This step is implemented as follows: the module first performs spatiotemporal matching of the received time-domain vibration waveform data with a self-calibrated three-dimensional spatial reference model to obtain the vibration signal at each coordinate point within the target area. Subsequently, the module applies a fast Fourier transform algorithm to the time-domain vibration signal at each coordinate point to convert it into a frequency response spectrum. In the generated frequency response spectrum, the module uses a peak search algorithm to identify frequency peaks with energy exceeding a preset background noise threshold and marks these frequency peaks as potential anomalous resonance peaks.

[0022] Next, the dynamic task orchestration and fusion module calculates the suspension confidence score for each marked potential anomalous resonance peak. The purpose of this step is to quantitatively evaluate the potential resonance peak to distinguish between genuine suspension faults and random interference. This calculation process first includes calculating the resonance quality factor. Specifically, the module determines the center frequency of a potential anomalous resonance peak. The module calculates the two frequency points corresponding to when the peak energy drops to half of its maximum value, i.e., the full width at half maximum (FWHM). The difference between these two frequency points is defined as the bandwidth of the resonant peak. Resonance quality factor That is, through Divide by The calculation shows that, .

[0023] While calculating the resonance quality factor, the module also performs the calculation of spatial continuity weights. This process is implemented as follows: for a potential anomalous resonance peak located at a coordinate point, the module extracts the frequency response spectra of its N preceding and following coordinate points (e.g., N=5). Subsequently, the module calculates the average cross-correlation coefficient between the frequency response spectrum of the coordinate point and the frequency response spectra of these 2N adjacent points. This average cross-correlation coefficient is defined as the spatial continuity weight.

[0024] After calculating the resonance quality factor and spatial continuity weights, the dynamic task orchestration and fusion module then performs gain term generation based on exponential and hyperbolic tangent functions. This step is implemented as follows: the module first calculates the first gain term by subtracting 1 from the aforementioned resonance quality factor, multiplying it by a preset adjustment parameter, and then using the result as an exponent for calculation using an exponential function. Simultaneously, the module calculates the second gain term by multiplying the aforementioned spatial continuity weights by a preset adjustment parameter, and then using the result as the independent variable for calculation using a hyperbolic tangent function.

[0025] After generating the first and second gain terms, the dynamic task orchestration and fusion module performs the final synthesis and threshold comparison of the suspension confidence score. This process is implemented as follows: the module extracts the normalized amplitude of the potential anomalous resonance peak and multiplies this normalized amplitude with the calculated first and second gain terms; the product is the final suspension confidence score.

[0026] In one specific embodiment of the present invention, the sag confidence score ( ) is calculated using the following formula: in, For normalized amplitude, This is the resonance quality factor. The aforementioned spatial continuity weights, α and β are preset adjustment parameters used to control the degree of nonlinear response.

[0027] The module then compares the calculated suspension confidence score with a preset confidence threshold. If the suspension confidence score is greater than the threshold, the module ultimately confirms the potential abnormal resonance peak as a real suspension fault point.

[0028] For each coordinate point ultimately confirmed as a suspended fault point, the dynamic task orchestration and fusion module then performs quantization of the suspended fault parameters. The implementation path is as follows: the module uses the center frequency of the abnormal resonance peak of the fault point as a query index and matches it against a pre-existing physical model or lookup table in the system database. The aforementioned physical model or lookup table records the correspondence between different tension or suspension lengths and the resonant center frequency. Through matching queries, the module outputs the suspended fault spatial length or tension parameter corresponding to that center frequency. The module performs this quantization process for all consecutive suspended fault points and calculates the start and end coordinates and total length of the entire suspended fault segment.

[0029] After quantifying the parameters of all identified overhang faults, the dynamic task orchestration and fusion module generates and outputs diagnostic conclusions. This step is achieved by the module summarizing all confirmed overhang fault information and organizing this information into a structured diagnostic report.

[0030] After the fixed-point resonance state diagnosis process is completed, the dynamic task orchestration and fusion module can further initiate the implementation of intelligent scheduling and closed-loop verification.

[0031] This module first performs a confidence level assessment of the diagnostic conclusion. This step is achieved by the module iterating through all potential abnormal resonance peaks identified in the diagnostic process and extracting the suspension confidence score corresponding to each resonance peak. This suspension confidence score is then used as a quantitative indicator of the confidence level of the diagnostic conclusion.

[0032] Next, the dynamic task orchestration and fusion module executes a verification task trigger based on a dual-threshold comparison. The implementation path for this process is as follows: the module compares the confidence level of each potential anomalous resonance peak with two preset thresholds, namely a first threshold and a second threshold, where the first threshold is greater than the second threshold. When the confidence level of a potential anomalous resonance peak is lower than both the first and second thresholds, the module marks the target location corresponding to that resonance peak as a "region to be verified."

[0033] For each target location marked as a "region to be verified," the dynamic task orchestration and fusion module then automatically re-executes the diagnostic process for that specific target location. This step is achieved by the module automatically generating a new diagnostic task instruction for that "region to be verified." This instruction may include higher density or different angles of navigation survey lines, as well as optimized acoustic excitation parameters. The module issues this newly generated diagnostic task instruction to the marine mobile acoustic source unit and automatically and completely re-executes the three-dimensional spatial reference model dynamic self-calibration step and the fixed-point resonance state diagnostic step described in this invention to perform secondary diagnosis and verification of the target location.

[0034] In one embodiment of the present invention, an integrated system for precise positioning and acoustic-optical-seismic status monitoring of submarine cables is provided. Physically, the system includes a shore-based integrated processing unit, a marine mobile acoustic source unit, and a data communication link connecting the two.

[0035] The marine mobile sound source unit includes: A global positioning system receiver is used to acquire real-time spatiotemporal data of this unit; A programmable sonar transducer for transmitting single-frequency acoustic pulses or continuously swept-frequency acoustic signals according to instructions; The control system is configured to receive instructions from the shore-based integrated processing unit and drive the sonar transducer to operate according to those instructions.

[0036] The shore-based integrated processing unit includes a processor, memory, and a data interface for connecting to the demodulator of the distributed fiber optic sensing system. The memory stores a computer program, which, when executed by the processor, is instantiated into multiple logical functional modules, including: Dynamic task orchestration and fusion module: It is configured to load system configuration information, receive operator instructions, and issue task instructions and schedule workflows to the marine mobile sound source unit and other logical function modules within this unit.

[0037] The self-calibration positioning module is configured, under the scheduling of the dynamic task orchestration and fusion module, to receive spatiotemporal data transmitted from the marine mobile acoustic source unit and all-fiber vibration signals collected by the distributed fiber optic sensing system; and to execute the dynamic differential self-calibration algorithm based on anchor point information as described in this specification to generate a self-calibrated three-dimensional spatial reference model. The self-calibrated three-dimensional spatial reference model generated by this module is output to the dynamic task orchestration and fusion module.

[0038] The resonance diagnostic module is configured to receive a self-calibrated 3D spatial reference model generated by the self-calibration positioning module, provided by the dynamic task orchestration and fusion module, as its spatial input reference, under the scheduling of the dynamic task orchestration and fusion module. The resonance diagnostic module is further configured to: The vibration signal, which is matched to the benchmark model and acquired by a distributed fiber optic sensing system during frequency sweep excitation, is processed to generate a frequency response spectrum. Perform the calculation of the suspension confidence score, including the resonance quality factor, spatial continuity weight, and the synthesis and threshold comparison of the final score; and perform the quantification of the suspension fault parameters.

[0039] The embodiments described above are only some embodiments of the present invention, and not all embodiments. It should be noted that the present invention is not limited to the embodiments described above. Any modifications, equivalent substitutions, variations, or improvements made by those skilled in the art based on the above embodiments without creative effort, within the scope of the concept and principles of the present invention, should fall within the protection scope claimed by the claims of the present invention.

Claims

1. An integrated method for precise positioning and acoustic-optical-seismic condition monitoring of submarine cables, characterized in that, include: The dynamic self-calibration step of the three-dimensional spatial reference model is performed. Based on the anchor point information located on the submarine cable and having known absolute three-dimensional coordinates, the coordinates of all points on the submarine cable are dynamically corrected by calculating the theoretical and actual arrival time deviation of the acoustic signal at the anchor point, so as to generate a self-calibrated three-dimensional spatial reference model. The fixed-point resonance state diagnosis step is performed. The self-calibrated three-dimensional spatial reference model is used as the spatial input reference. The submarine cable is excited by actively transmitted continuous sweep frequency acoustic signals. By analyzing the frequency response spectrum of the optical fiber vibration signal at the coordinate point on the self-calibrated three-dimensional spatial reference model, abnormal resonance peaks that characterize the suspension state are identified to diagnose the physical state of the coordinate point.

2. The method according to claim 1, characterized in that, The dynamic self-calibration steps of the three-dimensional spatial reference model include: Receive the optical fiber vibration signal collected by the distributed optical fiber sensing system; Acquire acoustic pulse signals emitted by a mobile sound source unit at sea and their corresponding spatiotemporal data; The information at the anchor point is used for correction.

3. The method according to claim 2, characterized in that, The step of using the information at the anchor point for correction includes: for non-anchor point coordinates on the submarine cable, setting the positioning correction amount to a value that is a preset function relating to the time deviation calculated at the anchor point.

4. The method according to claim 1, characterized in that, The fixed-point resonance state diagnosis step further includes: calculating the suspension confidence score for the identified abnormal resonance peak, in order to assess the confidence level of the suspension fault corresponding to the abnormal resonance peak.

5. The method according to claim 1 or 4, characterized in that, The fixed-point resonance state diagnosis step further includes: matching the center frequency of the abnormal resonance peak with a pre-stored physical model or lookup table that characterizes the relationship between tension or suspension length and resonance frequency, so as to determine the spatial length or tension parameter of the suspension fault.

6. The method according to claim 4, characterized in that, The calculation of the suspension confidence score depends on the normalized amplitude of the abnormal resonance peak, the first gain term, and the second gain term. Wherein, the first gain term is calculated based on the resonance quality factor of the abnormal resonance peak; The second gain term is calculated based on the spatial continuity weight of the abnormal resonance peak.

7. The method according to claim 6, characterized in that: The first gain term is calculated on the resonant quality factor using an exponential function; The second gain term is calculated on the continuity weight using the hyperbolic tangent function.

8. The method according to claim 6 or 7, characterized in that, The sag confidence score Calculated using the following formula: in, For normalized amplitude, This is the resonance quality factor. The aforementioned continuous weights, α and β are preset adjustment parameters.

9. The method according to claim 1, characterized in that, The method further includes: when the confidence level of the abnormal resonance peak identified in the fixed-point resonance state diagnosis step is lower than the first threshold but higher than the second threshold, automatically triggering and re-executing the three-dimensional spatial reference model dynamic self-calibration step and the fixed-point resonance state diagnosis step to verify the target position corresponding to the abnormal resonance peak.

10. An integrated system for precise positioning and acoustic-optical-seismic monitoring of submarine cables, comprising a processor and a memory, wherein the memory stores a computer program, characterized in that... When the computer program is executed by the processor, it implements the method as described in any one of claims 1 to 9.

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