Marine dynamic flexible riser motion response reconstruction method based on monitoring data

Abstract

The invention relates to the technical field of flexible riser motion analysis, in particular to a marine dynamic flexible riser motion response reconstruction method based on monitoring data, which comprises the following steps of: arranging sensors in a flexible riser system by adopting a structure embedded type arrangement method or an external attachment type arrangement method, and optimizing a sensor arrangement mode; a data acquisition and transmission system is arranged on an ocean platform to obtain flexible riser motion response data, the flexible riser motion response data is converted into flexible riser displacement data based on a Timoshenko beam model and Tikhonov regularization, the flexible riser displacement data is subjected to noise reduction processing based on a wavelet threshold noise reduction method to obtain flexible riser displacement noise reduction data, and the flexible riser displacement noise reduction data is subjected to flexible riser displacement noise reduction. And motion response reconstruction is performed on the flexible riser displacement noise reduction data based on variational mode decomposition (VMD). According to the method, the data interpretability, the data reconstruction precision and the real-time performance of motion reconstruction of the flexible riser can be effectively improved.

Description

Technical Field

[0001] The present invention relates to the technical field of flexible riser motion analysis, and in particular to a method for reconstructing marine dynamic flexible riser motion response based on monitoring data. Background Art

[0002] As offshore oil and gas development continues to advance into deepwater and ultra-deepwater areas, the dynamic response behavior of flexible risers, as key equipment connecting underwater production systems with floating production platforms (such as FPSOs, semi-submersible platforms, and tension-leg platforms), has a crucial impact on the safety and reliability of the entire offshore oil and gas production system. Flexible risers are usually arranged in a free-hanging, wavy, or inverted wave shape. Their working environment is complex and changeable. They are subject to the combined effects of multiple loads such as waves, currents, swells, platform movement, and internal fluids, making them prone to large-scale vibrations, deformations, structural damage, and fatigue. Especially under coupled load conditions, the dynamic response of flexible risers exhibits highly nonlinear and strongly time-varying characteristics, and their mechanical behavior is difficult to accurately describe using traditional static models.

[0003] Currently, the status of flexible risers is primarily determined through numerical simulation, physical model testing, and online monitoring. Simulating the dynamic response of flexible risers using finite element methods or multibody dynamics models is the primary approach for studying their motion response. While this method offers high accuracy, it relies heavily on initial boundary conditions and environmental load models, resulting in high computational costs and difficulties in achieving real-time evaluation and dynamic adjustments. The motion response of flexible risers under wave and flow loads has been studied in test tanks using scaled-down physical models. However, this method is costly, time-consuming, and inadequate for the complex and variable environmental conditions found in actual operations, making it difficult to scale to field applications. In recent years, with the advancement of underwater sensors, wireless communications, and edge computing technologies, flexible riser condition monitoring has gradually evolved towards real-time and intelligent capabilities. However, due to the difficulty of deploying sensors in the marine environment and the limited number of locations, only local data from key nodes on the riser can be obtained, failing to fully capture the overall dynamic response.

[0004] Currently, with the continuous development of artificial intelligence (AI) methods, related approaches are gradually being introduced into the health monitoring of marine engineering structures. Monitoring data is reconstructed through methods such as Kalman filtering, Bayesian networks, wavelet transforms, and machine learning. However, existing technologies fail to effectively combine physical models with sensor data, resulting in insufficient interpretability, poor applicability, poor real-time performance, and low reconstruction accuracy. Summary of the Invention

[0005] The purpose of the present invention is to provide a method for reconstructing the motion response of marine dynamic flexible risers based on monitoring data, so as to solve the problems of insufficient interpretability, poor applicability, poor real-time performance and low reconstruction accuracy in the prior art.

[0006] To achieve the above object, the present invention provides a method for reconstructing the motion response of a dynamic marine flexible riser based on monitoring data, comprising the following steps:

[0007] S1. Deploy sensors in the flexible riser system using a structural embedded deployment method or an externally attached deployment method, and optimize the sensor deployment pattern based on a four-quadrant deployment strategy to obtain a sensor system.

[0008] S2. Setting up a data acquisition and transmission system on the marine platform, wherein the data acquisition and transmission system comprises the following modules: an acquisition terminal module, a photoelectric conversion module, a synchronization control module, a data transmission module, and a power supply and voltage stabilization module;

[0009] S3, obtaining flexible riser motion response data acquired based on the data acquisition and transmission system and the sensor system, and converting the flexible riser motion response data into flexible riser displacement data based on the Timoshenko beam model and Tikhonov regularization;

[0010] S4. Performing noise reduction processing on the flexible riser displacement data based on a wavelet threshold noise reduction method to obtain flexible riser displacement noise reduction data;

[0011] S5. Reconstruct the motion response of the flexible riser displacement denoised data based on variational mode decomposition (VMD).

[0012] In some embodiments of the present application, in S1, optimizing the sensor layout pattern based on the cross-sectional four-quadrant layout strategy includes:

[0013] Based on the four-quadrant layout strategy, four symmetrical layout points are determined on the typical circular cross section of the flexible riser. The four symmetrical layout points are distributed equiangularly around the pipe body to obtain a four-quadrant layout pattern.

[0014] A plurality of groups of sensor units are arranged on the axis of the flexible riser at preset intervals, and each group of sensor units includes four sensors arranged based on a four-quadrant arrangement mode.

[0015] In some embodiments of the present application, in S2, the acquisition terminal module is disposed in the control cabin or superstructure of the marine platform, and an industrial embedded data acquisition system is applied inside the module to collect monitoring data of multiple sensors and provide data caching and timestamp marking;

[0016] The photoelectric conversion module is installed in the control cabin or superstructure of the marine platform. It is used to convert the central wavelength information reflected by the sensor into a digital signal and output strain data, voltage data and frequency shift data for the acquisition terminal to read. It can also perform automatic temperature compensation and multi-channel parallel demodulation.

[0017] The synchronization control module is set in the control cabin or superstructure of the offshore platform, and is used to synchronize the acquisition and control of each data channel using a unified clock source, and to control the unified triggering and acquisition of each data channel based on the hardware interrupt mechanism;

[0018] The data transmission module is installed in the control cabin or superstructure of the offshore platform and is used to transmit the collected data from the riser end to the offshore platform end. It has the functions of automatic reconnection in case of disconnection, cache recovery and encrypted transmission.

[0019] The power supply and voltage stabilization module is installed in the control cabin or superstructure of the offshore platform to ensure the stable operation of the sensors and acquisition system.

[0020] In some embodiments of the present application, in S3, obtaining the flexible riser motion response data based on the data acquisition and transmission system and the sensor system includes:

[0021] The initial sampling frequency of the data acquisition and transmission system is set to 50 Hz, and the sampling frequency is adjusted in real time based on the adaptive adjustment mechanism;

[0022] The data acquisition and transmission system obtains the flexible riser motion response data of the sensor system in real time.

[0023] In some embodiments of the present application, in S3, converting the flexible riser motion response data into flexible riser displacement data based on the Timoshenko beam model and Tikhonov regularization includes:

[0024] S31. The bending curvature is calculated based on the Timoshenko beam model and is expressed as:

[0025]

[0026] Where R is the distance between the sensor and the center of the pipe, ε xx is the motion response data of the flexible riser, x i is the distance along the pipeline, κ z (x i ) is x i The curvature of the flexible riser in the z direction, κ y (x i ) is x i The bending curvature of the flexible riser in the y direction;

[0027] Alternatively, ignoring the axial normal strain of the offshore flexible riser, the bending curvature can be calculated using one sensor in each direction, as expressed by:

[0028]

[0029] S32. Calculate the displacement data of the flexible riser based on the bending curvature of the flexible riser:

[0030]

[0031] in, is the second-order derivative of displacement y(x) with respect to position x, κ(t) is the curvature of space bending;

[0032] S33, based on Tikhonov regularization optimization S32, the expression is:

[0033]

[0034] Among them, κ(x i ) is the discrete position x i The curvature measurement at , λ is the regularization parameter, and J(y) is the regularization objective function.

[0035] In some embodiments of the present application, in S4, performing denoising on the flexible riser displacement data based on a wavelet threshold denoising method to obtain the denoised flexible riser displacement data includes:

[0036] Based on the wavelet threshold denoising method, the signal is decomposed into different frequency bands. The target wavelet basis is selected to perform wavelet decomposition on the original strain signal with 3-5 decomposition layers. The high-frequency sub-bands are denoised using the soft threshold or hard threshold method. The denoised sub-bands are then subjected to inverse wavelet transform and smoothing to obtain the denoised data of the flexible riser displacement.

[0037] In some embodiments of the present application, in S5, reconstructing the motion response of the flexible riser displacement denoised data based on variational mode decomposition (VMD) includes:

[0038] S51. Based on variational mode decomposition (VMD), a variational constraint model is established, and the expression is:

[0039]

[0040] st Σ k u k (t) = f(t);

[0041] Among them, u k is the decomposed modal function, ω k is the center frequency of the corresponding mode function, u k (t) is the kth mode function, is the time derivative operator, δ(t) is the Dirac distribution function, and f(t) is the denoised data of the flexible riser displacement;

[0042] S52. Use the alternating direction multiplier algorithm to calculate the saddle point. The expression is:

[0043]

[0044] Among them, α is the penalty factor, λ is the Lagrangian factor, L({u k},{ω k},λ) is the augmented Lagrangian function, λ(t) is the time-varying Lagrangian multiplier;

[0045] S53. Obtain the frequency domain and center frequency of the new variational constraint model, and obtain the constrained variational optimal solution, which is expressed as:

[0046] u n+1 =argmin

[0047]

[0048] Among them, ρ is the update factor, u n+1 is the set of all modal functions after the n+1th iteration, is the center frequency of the kth mode function after the n+1th iteration, λ n+1 is the time-varying Lagrange multiplier after the n+1th iteration, The kth mode function after the n+1th iteration;

[0049] S54. Reconstruct the motion response of the flexible riser displacement denoising data based on the constrained variational optimal solution.

[0050] The advantages and beneficial effects of the present invention over the prior art are:

[0051] 1. Adopting a structurally embedded or externally attached layout method and optimizing the sensor layout pattern based on the four-quadrant layout strategy of the cross section can more comprehensively collect the motion information of the flexible riser in different directions and positions, and can accurately sense the bending, stretching and other motion states of the riser in various directions. Compared with the existing technology that does not combine sensors or only arranges sensors in a single direction, it can obtain richer and more accurate raw data, thereby providing a higher-quality data foundation for subsequent motion response reconstruction and improving data reconstruction accuracy.

[0052] 2. The data acquisition and transmission system includes an acquisition terminal module, a photoelectric conversion module, a synchronization control module, a data transmission module, and a power supply and voltage regulation module. The synchronization control module can ensure that the data collected by the sensor can be transmitted synchronously, avoiding reconstruction errors caused by inconsistent data acquisition time. The data acquisition and transmission system makes the data acquisition and transmission process more efficient, and can quickly obtain and process the motion response data of the flexible riser, greatly improving responsiveness.

[0053] 3. The motion response of the flexible riser displacement denoised data is reconstructed through variational modal decomposition (VMD). VMD can decompose the complex flexible riser motion response signal into multiple modal components. Each modal component represents the motion characteristics of the flexible riser within a specific frequency range, making the reconstructed motion response results more interpretable and enabling those in this field to better understand the motion state and stress conditions of the flexible riser.

[0054] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] Figure 1 Schematic diagram of the steps of a method for reconstructing the motion response of a marine dynamic flexible riser based on monitoring data in an embodiment of the present invention;

[0056] Figure 2 This is a flow chart of a method for reconstructing the motion response of a marine dynamic flexible riser based on monitoring data in an embodiment of the present invention;

[0057] Figure 3 This is a schematic diagram of the arrangement of sensors along the axial direction of the flexible riser according to an embodiment of the present invention;

[0058] Figure 4 is a distribution diagram of sensors in a cross section of a flexible riser according to an embodiment of the present invention;

[0059] Figure 5 Schematic diagram of the flexible riser motion response reconstruction result according to an embodiment of the present invention. DETAILED DESCRIPTION

[0060] In the description of the present invention, it should be noted that the terms "upper", "lower", "inside", "outside" and the like indicate orientations or positional relationships based on the orientations or positional relationships shown in the accompanying drawings, or the orientations or positional relationships in which the inventive product is usually placed when in use. These are only for the convenience of describing the present invention and simplifying the description, and are not intended to indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation. Therefore, they cannot be understood as limitations on the present invention. In the description of the present invention, it should also be noted that, unless otherwise expressly specified and limited, the terms "setting", "installation" and "connection" should be understood in a broad sense. For example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or an indirect connection through an intermediate medium, or it can be a communication between the internal parts of two elements. For those of ordinary skill in the art, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0061] The embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0062] like Figure 1-2 As shown, the present invention provides a method for reconstructing the motion response of a marine dynamic flexible riser based on monitoring data, comprising the following steps:

[0063] S1. Deploy sensors in the flexible riser system using a structural embedded deployment method or an externally attached deployment method, and optimize the sensor deployment pattern based on a four-quadrant deployment strategy to obtain a sensor system.

[0064] S2. A data acquisition and transmission system is set up on the marine platform. The data acquisition and transmission system includes the following modules: an acquisition terminal module, a photoelectric conversion module, a synchronization control module, a data transmission module, and a power supply and voltage stabilization module.

[0065] S3. Obtain the flexible riser motion response data based on the data acquisition and transmission system and the sensor system, and convert the flexible riser motion response data into flexible riser displacement data based on the Timoshenko beam model and Tikhonov regularization.

[0066] S4. Perform denoising on the flexible riser displacement data based on a wavelet threshold denoising method to obtain denoised flexible riser displacement data.

[0067] S5. Reconstruct the motion response of the flexible riser displacement denoised data based on variational mode decomposition (VMD).

[0068] The advantages and beneficial effects of the present invention over the prior art are:

[0069] 1. Adopting a structurally embedded or externally attached layout method and optimizing the sensor layout pattern based on the four-quadrant layout strategy of the cross section can more comprehensively collect the motion information of the flexible riser in different directions and positions, and can accurately sense the bending, stretching and other motion states of the riser in various directions. Compared with the existing technology that does not combine sensors or only arranges sensors in a single direction, it can obtain richer and more accurate raw data, thereby providing a higher-quality data foundation for subsequent motion response reconstruction and improving data reconstruction accuracy.

[0070] 2. The data acquisition and transmission system includes an acquisition terminal module, a photoelectric conversion module, a synchronization control module, a data transmission module, and a power supply and voltage regulation module. The synchronization control module can ensure that the data collected by the sensor can be transmitted synchronously, avoiding reconstruction errors caused by inconsistent data acquisition time. The data acquisition and transmission system makes the data acquisition and transmission process more efficient, and can quickly obtain and process the motion response data of the flexible riser, greatly improving responsiveness.

[0071] 3. The motion response of the flexible riser displacement denoised data is reconstructed through variational modal decomposition (VMD). VMD can decompose the complex flexible riser motion response signal into multiple modal components. Each modal component represents the motion characteristics of the flexible riser within a specific frequency range, making the reconstructed motion response results more interpretable and enabling those in this field to better understand the motion state and stress conditions of the flexible riser.

[0072] In some embodiments of the present application, in S1, optimizing the sensor layout pattern based on the cross-sectional four-quadrant layout strategy includes:

[0073] Based on the four-quadrant layout strategy, four symmetrical layout points are determined on the typical circular cross section of the flexible riser. The four symmetrical layout points are distributed equiangularly around the pipe body to obtain a four-quadrant layout pattern.

[0074] A plurality of groups of sensor units are arranged on the axis of the flexible riser at preset intervals, and each group of sensor units includes four sensors arranged based on a four-quadrant arrangement mode.

[0075] Specifically, the existing sensor layout can be selected in the following two main ways according to needs:

[0076] Method 1: Embedded layout in the flexible riser structure. During the manufacturing stage of the flexible riser, the fiber Bragg grating (FBG) strain sensor is embedded in the structure of the flexible riser. It is axially distributed close to the outside of the tensile layer or the middle interlayer of the flexible riser to form a continuous strain monitoring array. The optical fiber array can be encapsulated in a metal sheath to improve the pressure resistance and bending resistance, and at the same time, it is formed in coordination with the tensile layer by bonding or weaving. This method deforms synchronously with the flexible riser structure, has high response accuracy, and the measurement data can better reflect the actual mechanical state; it avoids direct contact with seawater, is corrosion-resistant, and has high reliability; and can achieve long-term maintenance-free monitoring. However, this method has the disadvantages of a long manufacturing cycle, high cost, is not suitable for flexible risers that have been built or are in service, cannot be replaced and maintained, and once damaged, affects the monitoring capability of the entire section.

[0077] Method 2: External attachment layout of flexible risers. During the installation or service phase of the flexible riser, the sensor is attached to the surface of the outermost coating layer (usually a polymer sheath layer) of the flexible pipe to form an attached sensing monitoring system. Surface strain gauge sensor types can be selected and laid out through flexible adhesive materials, strip-shaped fixing structures or mechanical clips. At the same time, it can be reinforced with a protective shell or waterproof module. This method is flexible to install and is suitable for flexible risers in service or already built. The position and density can be flexibly adjusted according to actual monitoring needs. It is easy to maintain and replace, and is suitable for multiple monitoring or phased deployment. However, this method has the disadvantages of being limited by the external environment, being susceptible to interference such as seawater erosion and attachment of marine organisms, and having a certain lag with the structural response. In particular, high-frequency dynamic response, loose fixation or aging of adhesive materials may affect the quality of monitoring data.

[0078] In order to improve the omnidirectional sensing capability and reconstruction accuracy of flexible riser motion monitoring, the present invention further adopts a cross-sectional four-quadrant layout strategy when arranging sensors, such as Figure 4 As shown in the figure, on the typical circular cross-section of a flexible riser, four symmetrical points (e.g., at 0°, 90°, 180°, and 270°) are selected and evenly distributed around the pipe, forming a four-quadrant layout pattern. On the axis of the flexible riser, groups of sensor units are placed at regular intervals (e.g., every 1 to 3 meters), with each group containing four sensors distributed at circumferentially symmetrical points.

[0079] In some embodiments of the present application, in S2, the acquisition terminal module is disposed in the control cabin or superstructure of the marine platform, and an industrial embedded data acquisition system is applied inside the module to collect monitoring data of multiple sensors and provide data caching and timestamp marking;

[0080] The photoelectric conversion module is installed in the control cabin or superstructure of the marine platform. It is used to convert the central wavelength information reflected by the sensor into a digital signal and output strain data, voltage data and frequency shift data for the acquisition terminal to read. It can also perform automatic temperature compensation and multi-channel parallel demodulation.

[0081] The synchronization control module is set in the control cabin or superstructure of the offshore platform, and is used to synchronize the acquisition and control of each data channel using a unified clock source, and to control the unified triggering and acquisition of each data channel based on the hardware interrupt mechanism;

[0082] The data transmission module is installed in the control cabin or superstructure of the offshore platform and is used to transmit the collected data from the riser end to the offshore platform end. It has the functions of automatic reconnection in case of disconnection, cache recovery and encrypted transmission.

[0083] The power supply and voltage stabilization module is installed in the control cabin or superstructure of the offshore platform to ensure the stable operation of the sensors and acquisition system.

[0084] In some embodiments of the present application, in S3, obtaining the flexible riser motion response data based on the data acquisition and transmission system and the sensor system includes:

[0085] The initial sampling frequency of the data acquisition and transmission system is set to 50 Hz, and the sampling frequency is adjusted in real time based on the adaptive adjustment mechanism;

[0086] The data acquisition and transmission system obtains the flexible riser motion response data of the sensor system in real time.

[0087] In some embodiments of the present application, in S3, converting the flexible riser motion response data into flexible riser displacement data based on the Timoshenko beam model and Tikhonov regularization includes:

[0088] S31. The bending curvature is calculated based on the Timoshenko beam model and is expressed as:

[0089]

[0090] Where R is the distance between the sensor and the center of the pipe, ε xx is the motion response data of the flexible riser, x i is the distance along the pipeline, κ z (x i ) is x i The curvature of the flexible riser in the z direction, κ y (x i ) is x i The bending curvature of the flexible riser in the y direction;

[0091] For offshore flexible risers, the axial normal strain can be ignored, so only one strain sensor can be used in each direction to calculate the deformation curvature. The expression is:

[0092]

[0093] During the actual operation of the grating fiber optic sensor, due to problems with the fiber optic system, some sensors may collect missing data. In order to make use of as much valid data as possible, the above formula is used to calculate the curvature for sensors with normal data collection on both sides of the riser.

[0094] If one sensor is missing, use the above formula to calculate.

[0095] S32. Calculate the displacement data of the flexible riser based on the bending curvature of the flexible riser:

[0096]

[0097] in, is the second derivative of displacement y(x) with respect to position x, κ(x) is the curvature of space;

[0098] S33, based on Tikhonov regularization optimization S32, the expression is:

[0099]

[0100] Among them, κ(x i ) is the discrete position x i The curvature measurement at , λ is the regularization parameter, and J(y) is the regularization objective function.

[0101] Specifically, direct numerical integration will continuously amplify the noise, so Tikhonov regularization is introduced to transform the problem into an optimization problem to ensure the smoothness of the solution and the fitting accuracy.

[0102] In some embodiments of the present application, in S4, performing denoising on the flexible riser displacement data based on a wavelet threshold denoising method to obtain the denoised flexible riser displacement data includes:

[0103] Based on the wavelet threshold denoising method, the signal is decomposed into different frequency bands. The target wavelet basis is selected to perform wavelet decomposition on the original strain signal with 3-5 decomposition layers. The high-frequency sub-bands are denoised using the soft threshold or hard threshold method. The denoised sub-bands are then subjected to inverse wavelet transform and smoothing to obtain the denoised data of the flexible riser displacement.

[0104] In some embodiments of the present application, in S5, reconstructing the motion response of the flexible riser displacement denoised data based on variational mode decomposition (VMD) includes:

[0105] Specifically, because sensors are deployed at a limited number of discrete measurement points on or within the flexible riser, only the motion response (displacement) of these points can be obtained. However, as the flexible riser is a continuum, a complete representation of its overall motion requires spatial interpolation and modal reconstruction techniques. This paper proposes a motion reconstruction method that combines the variable mode decomposition (VMD) algorithm to reconstruct the global response of the flexible riser from the monitoring results of a limited number of points.

[0106] The principle of VMD algorithm is to decompose the input signal f(t) into k limited bandwidth modal intrinsic functions u through adaptive quasi-orthogonal transformation. k (t), the goal is to minimize the sum of the estimated bandwidths of each mode. This method essentially transforms the signal decomposition problem into one of finding an optimal solution within constraints. The VMD algorithm has a unique advantage in removing high-frequency noise and complex nonlinear data. The VMD algorithm primarily involves establishing a variational constraint model and solving it.

[0107] S51. Based on variational mode decomposition (VMD), a variational constraint model is established, and the expression is:

[0108]

[0109] st ∑ k u k (t) = f(t);

[0110] Among them, u k is the decomposed modal function, ω k is the center frequency of the corresponding mode function, u k (t) is the kth mode function, is the time derivative operator, δ(t) is the Dirac distribution function, and f(t) is the denoised data of the flexible riser displacement;

[0111] S52. Use the alternating direction multiplier algorithm to calculate the saddle point. The expression is:

[0112]

[0113] Among them, α is the penalty factor, λ is the Lagrangian factor, L({u k},{ω k},λ) is the augmented Lagrangian function, λ(t) is the time-varying Lagrangian multiplier;

[0114] S53. Obtain the frequency domain and center frequency of the new variational constraint model, and obtain the constrained variational optimal solution, which is expressed as:

[0115] u n+1 =argmin

[0116]

[0117] Among them, ρ is the update factor, u n+1 is the set of all modal functions after the n+1th iteration, is the center frequency of the kth mode function after the n+1th iteration, λ n+1 is the time-varying Lagrange multiplier after the n+1th iteration, The kth mode function after the n+1th iteration;

[0118] S54. Reconstruct the motion response of the flexible riser displacement denoising data based on the constrained variational optimal solution.

[0119] The beneficial effects of the present invention are as follows: the present invention proposes a method for reconstructing the motion of a marine flexible riser based on monitoring data, which aims to achieve high-precision, spatiotemporal and temporal continuous reconstruction and evaluation of the overall motion state of the flexible riser under complex marine environmental conditions. The method comprehensively utilizes optical fiber strain monitoring, synchronous data acquisition, wavelet threshold noise reduction processing, strain-displacement conversion model and variable mode decomposition and reconstruction technology to achieve intelligent mapping from distributed discrete measurement point data to the overall dynamic response of the riser. The present invention can be widely used in deep-sea oil and gas exploration, submarine pipeline safety monitoring, marine engineering structure health assessment and other fields, providing key technical support for the safe operation and intelligent operation and maintenance of marine engineering equipment, and has broad application prospects.

[0120] The following describes the implementation of the present invention in detail with reference to specific examples.

[0121] Step 1: Sensor layout. The sensor can be a grating fiber strain sensor or a strain gauge. The grating fiber sensor can be pre-buried outside the tensile layer of the flexible pipe and laid along the axial direction of the flexible riser. Figure 3 As shown. The strain gauge can be laid out on the outermost cladding of the flexible pipe, also along the axial direction. Both the optical fiber and the strain gauge adopt a four-quadrant layout strategy, that is, on the typical circular cross-section of the flexible riser, four symmetrical points (such as 0°, 90°, 180°, and 270° directions) are selected and distributed equiangularly around the pipe body, as shown. Figure 5 shown.

[0122] Step 2: Data Collection. In this embodiment of the present invention, to accurately monitor the motion response of the flexible riser in the marine environment, a complete data collection and transmission system must be deployed on the marine platform. This system consists of multiple functional modules, and the functions and implementation methods of each module are as follows:

[0123] Acquisition terminal module: The acquisition terminal is installed in the control cabin or superstructure of the offshore platform and uses an industrial-grade embedded data acquisition system. This terminal should have multi-channel, high-precision analog signal acquisition capabilities, support multiple sensor interfaces, be able to stably read data from multiple sensors, and provide data caching and timestamp functions.

[0124] Photoelectric conversion module: If fiber Bragg grating (FBG) strain sensors are embedded or affixed to the flexible riser, a dedicated photoelectric demodulation module, such as a spectral demodulator, is required. This module converts the central wavelength changes reflected by the FBG sensor into a digital signal and outputs equivalent physical quantities such as strain, voltage, or frequency shift for data acquisition terminals to read. To improve system reliability, the photoelectric demodulation module should include automatic temperature compensation and multi-channel parallel demodulation capabilities.

[0125] Synchronization Control Unit: To ensure accurate time alignment of multi-channel sensor data, this system incorporates a synchronization control unit. This unit uses a unified clock source to synchronize acquisition and control of each data channel, ensuring timing consistency during subsequent reconstruction and processing. Hardware interrupts can be used to control unified acquisition triggering for each sampling channel.

[0126] Transmission module: Optical fiber transmits data from the riser end to the offshore platform. The transmission module has the ability to automatically reconnect in the event of a disconnection, cache recovery and encrypted transmission, improving data integrity and security.

[0127] Power supply and voltage stabilization module: To ensure the stable operation of sensors and acquisition systems, an industrial-grade power supply and voltage stabilization system must be configured. The power supply system should comply with the protection level and electromagnetic compatibility standards of the offshore platform and be adaptable to high salt spray, high humidity, and high vibration environments.

[0128] Sampling Frequency and Strategy: Under normal monitoring conditions, the system defaults to a sampling frequency of 50 Hz, which meets the requirements for collecting the dynamic response of flexible risers under most wave and platform excitation frequencies. The sampling frequency can be adaptively adjusted based on the operating state. For example, the sampling frequency is reduced to 10 Hz when the platform is in a static and stable state, and automatically increased to 100 Hz under severe sea conditions or sudden loads to obtain data with higher temporal resolution. Table 1 shows the strain data collected by four sensors on a specific flexible riser cross section.

[0129] Table 1 Strain data collected by sensors on a certain flexible riser section (×10-6)

[0130] time Sensor 1a Sensor 2a Sensor 3a Sensor 4a 0.019808 624.117 736.671 611.6955 526.097 0.039615 639.327 749.346 589.7255 510.042 0.059423 645.242 750.191 578.7405 514.267 0.07923 652.002 752.726 581.2755 508.352 0.099038 647.777 752.726 590.5705 519.337 0.118846 635.102 746.811 607.4705 533.702 0.138653 635.102 728.221 615.9205 549.757 0.158461 640.172 714.701 604.9355 559.052 0.178268 646.932 719.771 598.1755 559.052 …… …… …… …… ……

[0131] Step 3: Convert the collected strain into displacement. The strain data collected by the sensor is converted into displacement discrete point data through the calculation formula, as shown in Table 2.

[0132] Table 2 Displacement data of flexible riser at discrete points

[0133] Time(s) Sensor 1(m) Sensor 2 (m) …… 0.019808 -0.00437 -0.00731 …… 0.039615 -0.01044 -0.01297 …… 0.059423 -0.01719 -0.01723 …… 0.07923 -0.0242 -0.02185 …… 0.099038 -0.03167 -0.02854 …… 0.118846 -0.0391 -0.03725 …… 0.138653 -0.04621 -0.04653 …… 0.158461 -0.0526 -0.05529 …… …… …… …… ……

[0134] Step 4: Displacement noise reduction processing: Use the wavelet threshold noise reduction method to reduce the noise of the flexible riser monitoring point displacement. The wavelet noise reduction method is based on the good time-frequency local characteristics of the wavelet transform. It can decompose the signal into different frequency bands and suppress the noise in the high-frequency sub-band, thereby improving the signal-to-noise ratio while retaining the original signal characteristics. The specific process is as follows:

[0135] Wavelet decomposition: Select appropriate wavelet basis to perform multi-scale wavelet decomposition on the original strain signal. The number of decomposition layers is generally set to 3 to 5.

[0136] Threshold selection: Use soft threshold or hard threshold method to denoise high-frequency coefficients.

[0137] Coefficient processing: For the soft threshold method, the high-frequency coefficients below the threshold are set to 0, and the rest are linearly attenuated according to the distance threshold; for the hard threshold method, the high-frequency coefficients below the threshold are directly cleared.

[0138] Wavelet reconstruction: Perform inverse wavelet transform on the denoised coefficients to restore them to the smoothed time domain signal.

[0139] The results of noise reduction of flexible riser monitoring point displacement are shown in Table 3.

[0140] Table 3 Displacement noise reduction results of flexible riser monitoring points

[0141] Sensor location (m) Displacement noise reduction data (m) 2.6914 -0.00374 4.825 -0.01499 6.9586 0.027442 9.0922 0.123746 11.2258 0.266627 13.3594 0.469518 15.493 0.526915 17.6266 0.423286 19.7602 0.269591 …… ……

[0142] Step 5: Reconstruct the motion response. Use the variable mode decomposition method to reconstruct the discrete flexible riser displacement data into continuous displacement data through the calculation formula. The reconstruction result is as follows: Figure 5 shown.

[0143] In summary, the present invention proposes a method for reconstructing the motion of a marine flexible riser based on monitoring data, which aims to achieve high-precision, spatiotemporal continuous reconstruction and evaluation of the overall motion state of the flexible riser under complex marine environmental conditions. This method comprehensively utilizes optical fiber strain monitoring, synchronous data acquisition, wavelet threshold noise reduction processing, strain-displacement conversion model, and variable mode decomposition and reconstruction technology to achieve intelligent mapping from distributed discrete measurement point data to the overall dynamic response of the riser. The present invention can be widely used in deep-sea oil and gas exploration, submarine pipeline safety monitoring, marine engineering structure health assessment and other fields, providing key technical support for the safe operation and intelligent operation and maintenance of marine engineering equipment, and has broad application prospects.

[0144] In this application, unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the art of the technical field of this application. In the event of any inconsistency, the meaning described in this specification or the meaning derived from the contents recorded in this specification shall prevail. In addition, the terms used herein are only for the purpose of describing the embodiments of the present application and are not intended to limit this application.

[0145] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit the same. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that they can still modify or replace the technical solutions of the present invention with equivalents, and these modifications or equivalent replacements cannot cause the modified technical solutions to deviate from the spirit and scope of the technical solutions of the present invention.

Claims

1. A method for reconstructing the motion response of a dynamic marine flexible riser based on monitoring data, characterized in that: The following steps are involved: S1. Deploy sensors in the flexible riser system using a structural embedded deployment method or an externally attached deployment method, and optimize the sensor deployment pattern based on a four-quadrant deployment strategy to obtain a sensor system. S2. Setting up a data acquisition and transmission system on the marine platform, wherein the data acquisition and transmission system comprises the following modules: an acquisition terminal module, a photoelectric conversion module, a synchronization control module, a data transmission module, and a power supply and voltage stabilization module; S3, obtaining flexible riser motion response data acquired based on the data acquisition and transmission system and the sensor system, and converting the flexible riser motion response data into flexible riser displacement data based on the Timoshenko beam model and Tikhonov regularization; S4. Performing noise reduction processing on the flexible riser displacement data based on a wavelet threshold noise reduction method to obtain flexible riser displacement noise reduction data; S5. Reconstruct the motion response of the flexible riser displacement denoised data based on variational mode decomposition (VMD).

2. The method for reconstructing the motion response of a dynamic marine flexible riser based on monitoring data according to claim 1, characterized in that: In S1, optimizing the sensor layout pattern based on the cross-sectional four-quadrant layout strategy includes: Based on the four-quadrant layout strategy, four symmetrical layout points are determined on the typical circular cross section of the flexible riser. The four symmetrical layout points are distributed equiangularly around the pipe body to obtain a four-quadrant layout pattern. A plurality of groups of sensor units are arranged on the axis of the flexible riser at preset intervals, and each group of sensor units includes four sensors arranged based on a four-quadrant arrangement mode.

3. The method for reconstructing the motion response of a dynamic marine flexible riser based on monitoring data according to claim 2, characterized in that: In S2, the acquisition terminal module is set in the control cabin or superstructure of the marine platform. The module uses an industrial embedded data acquisition system to collect monitoring data from multiple sensors and provide data cache and time stamp. The photoelectric conversion module is installed in the control cabin or superstructure of the marine platform. It is used to convert the central wavelength information reflected by the sensor into a digital signal and output strain data, voltage data and frequency shift data for the acquisition terminal to read. It can also perform automatic temperature compensation and multi-channel parallel demodulation. The synchronization control module is set in the control cabin or superstructure of the offshore platform, and is used to synchronize the acquisition and control of each data channel using a unified clock source, and to control the unified triggering and acquisition of each data channel based on the hardware interrupt mechanism; The data transmission module is installed in the control cabin or superstructure of the offshore platform and is used to transmit the collected data from the riser end to the offshore platform end. It has the functions of automatic reconnection in case of disconnection, cache recovery and encrypted transmission. The power supply and voltage stabilization module is installed in the control cabin or superstructure of the offshore platform to ensure the stable operation of the sensors and acquisition system.

4. The method for reconstructing the motion response of a dynamic marine flexible riser based on monitoring data according to claim 3 is characterized in that: In S3, obtaining the flexible riser motion response data based on the data acquisition and transmission system and the sensor system includes: The initial sampling frequency of the data acquisition and transmission system is set to 50 Hz, and the sampling frequency is adjusted in real time based on the adaptive adjustment mechanism; The data acquisition and transmission system obtains the flexible riser motion response data of the sensor system in real time.

5. The method for reconstructing the motion response of a dynamic marine flexible riser based on monitoring data according to claim 4 is characterized in that: In S3, converting the flexible riser motion response data into flexible riser displacement data based on the Timoshenko beam model and Tikhonov regularization includes: S31. The bending curvature is calculated based on the Timoshenko beam model and is expressed as: Where R is the distance between the sensor and the center of the pipe, ε xx is the motion response data of the flexible riser, x i is the distance along the pipeline, κ z (x i ) is x i The curvature of the flexible riser in the z direction, κ y (x i ) is x i The bending curvature of the flexible riser in the y direction; Alternatively, ignoring the axial normal strain of the offshore flexible riser, the bending curvature can be calculated using one sensor in each direction, as expressed by: S32. Calculate the displacement data of the flexible riser based on the bending curvature of the flexible riser: in, is the second derivative of displacement y(x) with respect to position x, κ(x) is the curvature of space; S33, based on Tikhonov regularization optimization S32, the expression is: Among them, k(x i ) is the discrete position x i The curvature measurement at , λ is the regularization parameter, and J(y) is the regularization objective function.

6. The method for reconstructing the motion response of a dynamic marine flexible riser based on monitoring data according to claim 5, characterized in that: In S4, the flexible riser displacement data is subjected to noise reduction processing based on the wavelet threshold noise reduction method, and the obtained flexible riser displacement noise reduction data includes: Based on the wavelet threshold denoising method, the signal is decomposed into different frequency bands. The target wavelet basis is selected to perform wavelet decomposition on the original strain signal with 3-5 decomposition layers. The high-frequency sub-bands are denoised using the soft threshold or hard threshold method. The denoised sub-bands are then subjected to inverse wavelet transform and smoothing to obtain the denoised data of the flexible riser displacement.

7. The method for reconstructing the motion response of a dynamic marine flexible riser based on monitoring data according to claim 6, characterized in that: In S5, reconstructing the motion response of the flexible riser displacement noise reduction data based on variational mode decomposition (VMD) includes: S51. Based on variational mode decomposition (VMD), a variational constraint model is established, and the expression is: Among them, u k is the decomposed modal function, ω k is the center frequency of the corresponding mode function, u k (t) is the kth mode function, is the time derivative operator, δ(t) is the Dirac distribution function, and f(t) is the denoised data of the flexible riser displacement; S52. Use the alternating direction multiplier algorithm to calculate the saddle point. The expression is: Among them, α is the penalty factor, λ is the Lagrangian factor, L({u k },{ω k },λ) is the augmented Lagrangian function, λ(t) is the time-varying Lagrangian multiplier; S53. Obtain the frequency domain and center frequency of the new variational constraint model, and obtain the constrained variational optimal solution, which is expressed as: Among them, ρ is the update factor, u n+1 is the set of all modal functions after the n+1th iteration, is the center frequency of the kth mode function after the n+1th iteration, λ n+1 is the time-varying Lagrange multiplier after the n+1th iteration, The kth mode function after the n+1th iteration; S54. Reconstruct the motion response of the flexible riser displacement denoising data based on the constrained variational optimal solution.

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