A method for reconstructing the motion response of a dynamically flexible marine riser based on monitoring data

Abstract

The present application relates to the technical field of flexible riser motion analysis, and particularly relates to a marine dynamic flexible riser motion response reconstruction method based on monitoring data, comprising: using a structural embedded layout method or an external attached layout method to layout sensors in a flexible riser system, and optimizing the sensor layout mode; setting a data acquisition and transmission system on a marine platform to obtain flexible riser motion response data; converting the flexible riser motion response data into flexible riser displacement data based on a Timoshenko beam model and Tikhonov regularization; carrying out 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; and carrying out motion response reconstruction on the flexible riser displacement noise reduction data based on variational mode decomposition VMD. The present application can effectively improve the data interpretation, data reconstruction accuracy and real-time performance of motion reconstruction of the flexible riser.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of flexible riser motion analysis, and particularly relates to a marine dynamic flexible riser motion response reconstruction method based on monitoring data. BACKGROUND

[0002] With the continuous development of offshore oil and gas to deep and ultra-deep water, as the key equipment connecting the subsea production system and the floating production platform (such as FPSO, semi-submersible platform, tension leg platform), the dynamic response behavior of the flexible riser has a crucial influence on the safety and reliability of the entire offshore oil and gas production system. The flexible riser is usually arranged in a free-hanging, wave-shaped or inverted wave shape, and its working environment is complex and changeable, and it is subjected to the combined action of sea waves, sea currents, swells, platform motion and internal fluid, etc., and is prone to large amplitude vibration, deformation, structural damage and fatigue, etc. Especially under the coupled load condition, the dynamic response of the flexible riser shows high nonlinearity and strong time-varying characteristics, and its mechanical behavior is difficult to accurately describe by the traditional static force model.

[0003] At present, the acquisition of the state of the flexible riser is mainly through numerical simulation, physical model test, online monitoring and other related methods and technologies. Based on the finite element method or multi-body dynamics model, the dynamic response simulation of the flexible riser is the main way to study the motion response of the flexible riser, especially in the design stage, although this method has high precision, but it is strongly dependent on the initial boundary conditions and environmental load model, and has high calculation cost, and it is difficult to realize real-time evaluation and dynamic adjustment. The motion response of the flexible riser under the action of wave and flow load is studied by a scaled physical model in a test pool, but this method has high cost, long cycle, and cannot adapt to the complex and changeable environmental conditions in actual working conditions, and it is difficult to be popularized to field application. In recent years, with the development of underwater sensors, wireless communication and edge computing technology, the state monitoring of the flexible riser gradually evolves towards real-time and intelligent direction. However, due to the difficulty of laying sensors in the marine environment and the limited number of laying points, only local data of some key nodes of the riser can be obtained, and the overall dynamic response state cannot be comprehensively mastered.

[0004] At present, with the continuous development of artificial intelligence methods, related methods are gradually introduced into the health monitoring of offshore engineering structures, and the monitoring data is reconstructed by Kalman filtering, Bayesian network, wavelet transform, machine learning and other methods. However, the existing technology fails to effectively combine the physical model and sensor data, and has the problems of insufficient interpretability, poor applicability, poor real-time performance and low reconstruction accuracy. SUMMARY

[0005] The application aims to provide a marine dynamic flexible riser motion response reconstruction method based on monitoring data, to solve the problems of insufficient interpretation, poor applicability, poor real-time performance and low reconstruction accuracy in the prior art.

[0006] To achieve the above-mentioned purpose, the application provides a marine dynamic flexible riser motion response reconstruction method based on monitoring data, comprising the following steps:

[0007] S1, a structural embedded layout method or an external attached layout method is used to layout sensors in the flexible riser system, and a cross-section four-quadrant layout strategy is used to optimize the sensor layout mode, to obtain a sensor system;

[0008] S2, a data acquisition and transmission system is arranged on the offshore platform, and the data acquisition and transmission system comprises the following modules: an acquisition terminal module, an optical-electric conversion module, a synchronous control module, a data transmission module and a power supply and voltage stabilizing module;

[0009] S3, flexible riser motion response data obtained based on the data acquisition and transmission system and the sensor system are obtained, and the flexible riser motion response data are converted into flexible riser displacement data based on a Timoshenko beam model and Tikhonov regularization;

[0010] S4, the flexible riser displacement data are denoised based on a wavelet threshold denoising method, to obtain flexible riser displacement denoising data;

[0011] S5, the flexible riser displacement denoising data are subjected to motion response reconstruction based on a variational mode decomposition VMD.

[0012] In some embodiments of the application, in S1, the optimization of the sensor layout mode based on the cross-section four-quadrant layout strategy comprises:

[0013] Based on the cross-section 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 at equal angles around the pipe body, to obtain a four-quadrant layout mode;

[0014] A plurality of groups of sensor units are laid out on the axis of the flexible riser at a preset interval, and each group of sensor units comprises four sensors laid out based on the four-quadrant layout mode.

[0015] In some embodiments of the application, in S2, the acquisition terminal module is arranged in the control cabin or the upper structure of the offshore platform, an industrial embedded data acquisition system is applied inside the module, the monitoring data of a plurality of sensors can be acquired, and data buffering and time stamp marking can be provided;

[0016] The photoelectric conversion module is arranged in the control cabin or the superstructure of the offshore platform, is used for converting the central wavelength information reflected by the sensor into a digital signal, and outputs strain data, voltage data and frequency shift data for reading by the acquisition terminal, and can perform automatic temperature compensation and multi-channel parallel demodulation;

[0017] The synchronous control module is arranged in the control cabin or the superstructure of the offshore platform, is used for synchronously collecting and controlling each data channel by using a unified clock source, and controls unified triggering collection of each data channel based on a hardware interrupt mechanism;

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

[0019] The power supply and voltage stabilizing module is arranged in the control cabin or the superstructure of the offshore platform, and is used for guaranteeing stable operation of the sensor and the acquisition system.

[0020] In some embodiments of the present application, in the S3, the flexible riser motion response data is obtained based on the data acquisition and transmission system and the sensor system, and the S3 comprises the following steps:

[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 an 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 the S3, the flexible riser motion response data is converted into flexible riser displacement data based on a Timoshenko beam model and Tikhonov regularization, and the S3 comprises the following steps:

[0024] S31, the bending curvature is calculated based on the Timoshenko beam model, and the expression is as follows:

[0025]

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

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

[0028]

[0029] S32, the flexible riser displacement data is calculated based on the bending curvature of the flexible riser:

[0030]

[0031] wherein, is the second derivative of the displacement y(x) with respect to the position x, and κ(t) is the spatial bending curvature;

[0032] S33, S32 is optimized based on Tikhonov regularization, expressed as:

[0033]

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

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

[0036] The signal is decomposed into different frequency bands based on the wavelet threshold denoising method, the original strain signal is decomposed based on a target wavelet basis, the number of decomposition layers is 3-5 layers, the soft threshold or hard threshold method is used to denoise the high frequency subband, and the denoised subband is inverse wavelet transformed and smoothed to obtain the flexible riser displacement denoising data.

[0037] In some embodiments of the present application, in the S5, the motion response reconstruction of the flexible riser displacement denoising data is based on the variational mode decomposition VMD, which comprises:

[0038] S51, a variational constraint model is established based on the variational mode decomposition VMD, expressed as:

[0039]

[0040] s.t. Σ k u k (t)=f(t);

[0041] wherein, u k is the mode function obtained by decomposition, 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 flexible riser displacement denoising data;

[0042] S52, using the alternating direction multiplier algorithm to calculate the saddle point, the expression is:

[0043]

[0044] Wherein, alpha is a penalty factor, lambda is a Lagrange factor, L({u k}, omega k}, lambda) is an augmented Lagrangian function, and lambda(t) is a time-varying Lagrange multiplier;

[0045] S53, the frequency domain and the center frequency of the new variational constraint model are obtained, and the constrained variational optimal solution is obtained, the expression is:

[0046] u n+1 = argmin

[0047]

[0048] Wherein, rho is an update factor, u n+1 is the set of all modal functions after the n+1 iteration, is the center frequency of the kth modal function after the n+1 iteration, lambda n+1 is the time-varying Lagrange multiplier after the n+1 iteration, is the kth modal function after the n+1 iteration;

[0049] S54, based on the constrained variational optimal solution, the motion response reconstruction is carried out on the flexible riser displacement denoising data.

[0050] The advantages and beneficial effects of the present application relative to the prior art are:

[0051] 1. The structural embedded layout method or external attached layout method is adopted, and the sensor layout mode is optimized based on the cross-section four-quadrant layout strategy, so that the motion information of the flexible riser in different directions and positions can be more comprehensively collected, the bending, stretching and other motion states of the riser in each direction can be accurately perceived, compared with the sensor layout mode not combined with the sensor or single direction in the prior art, more rich and accurate original data can be obtained, so as to provide higher quality data basis for subsequent motion response reconstruction, and improve the data reconstruction precision.

[0052] 2. The data acquisition and transmission system comprises an acquisition terminal module, an optoelectronic conversion module, a synchronous control module, a data transmission module, and a power supply and voltage stabilizing module. The synchronous control module can ensure that the data collected by the sensor can be transmitted synchronously, avoiding reconstruction errors caused by inconsistent data acquisition times. The data acquisition and transmission system makes the data acquisition and transmission process more efficient, enabling fast acquisition and processing of the motion response data of the flexible riser, and greatly improving the responsiveness.

[0053] 3. The motion response of the flexible riser displacement denoising data is reconstructed by VMD, which can decompose the complex flexible riser motion response signal into multiple modal components, each of which represents the motion characteristics of the flexible riser in a specific frequency range, making the reconstructed motion response result have better interpretability and enabling the person skilled in the art to better understand the motion state and stress condition of the flexible riser.

[0054] The technical solutions of the present application will be further described in detail below through the accompanying drawings and examples. BRIEF DESCRIPTION OF DRAWINGS

[0055] Figure 1 A step schematic diagram of a marine dynamic flexible riser motion response reconstruction method based on monitoring data in an embodiment of the present application;

[0056] Figure 2 A flow framework diagram of a marine dynamic flexible riser motion response reconstruction method based on monitoring data in an embodiment of the present application;

[0057] Figure 3 A schematic diagram of the arrangement of the sensor along the flexible riser axis in an embodiment of the present application;

[0058] Figure 4 A distribution diagram of the flexible riser cross-section sensor in an embodiment of the present application;

[0059] Figure 5 A schematic diagram of the flexible riser motion response reconstruction result in an embodiment of the present application. DETAILED DESCRIPTION

[0060] In the description of the present application, it should be noted that the terms "upper", "lower", "inner", "outer" and the like indicate the orientation or positional relationship shown in the drawings, or the orientation or positional relationship commonly used when the product of the present application is used, and are only for the convenience of describing the present application and simplifying the description, and do not indicate or imply that the indicated device or element must have a particular orientation, be constructed and operated in a particular orientation, and therefore cannot be understood as a limitation on the present application. In the description of the present application, it should be noted that, unless otherwise explicitly specified and limited, the terms "arrangement", "installation", "connection" should be understood broadly, for example, it can be fixedly connected, or it can be detachably connected, or integrally connected, it can be mechanically connected, or it can be electrically connected, it can be directly connected, or indirectly connected through an intermediate medium, or it can be the internal communication of two elements. For those skilled in the art, the specific meaning of the above terms in the present application can be understood according to the specific circumstances.

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

[0062] As Figures 1-2 shown, the present application provides a marine dynamic flexible riser motion response reconstruction method based on monitoring data, comprising the following steps:

[0063] S1, using a structure embedded layout method or an external attached layout method to layout sensors in the flexible riser system, and optimizing the sensor layout mode based on the cross-section four-quadrant layout strategy to obtain a sensor system.

[0064] S2, setting a data acquisition and transmission system on the offshore platform, the data acquisition and transmission system comprising the following modules: an acquisition terminal module, an optical-electric conversion module, a synchronous control module, a data transmission module, a power supply and voltage stabilizing module.

[0065] S3, obtaining flexible riser motion response data 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 the Tikhonov regularization.

[0066] S4, performing noise reduction processing on the flexible riser displacement data based on the wavelet threshold denoising method to obtain flexible riser displacement denoising data.

[0067] S5, performing motion response reconstruction on the flexible riser displacement denoising data based on the variational mode decomposition VMD.

[0068] The advantages and beneficial effects of the present application relative to the prior art are:

[0069] 1. The sensor arrangement mode is optimized based on the cross-section four-quadrant arrangement strategy, which can more comprehensively collect the motion information of the flexible riser in different directions and positions, accurately perceive the bending, stretching and other motion states of the riser in each direction, obtain more rich and accurate raw data compared with the existing technology without combining sensors or single-direction sensor arrangement, thereby providing a higher quality data basis for subsequent motion response reconstruction and improving the data reconstruction accuracy.

[0070] 2. The data acquisition and transmission system includes an acquisition terminal module, an optical-electric conversion module, a synchronous control module, a data transmission module, and a power supply and voltage stabilizing module. The synchronous control module can ensure that the data collected by the sensor can be transmitted synchronously, avoiding reconstruction errors caused by inconsistent data acquisition times. The data acquisition and transmission system makes the data acquisition and transmission process more efficient, can quickly acquire and process the motion response data of the flexible riser, and greatly improves the responsiveness.

[0071] 3. The VMD is used to reconstruct the motion response of the flexible riser displacement denoising data. The VMD can decompose the complex flexible riser motion response signal into multiple modal components, each of which represents the motion characteristics of the flexible riser in a specific frequency range, so that the reconstructed motion response result has better interpretability, and the motion state and stress condition of the flexible riser can be better understood by the person skilled in the art.

[0072] In some embodiments of the present application, the S1 includes optimizing the sensor arrangement mode based on the cross-section four-quadrant arrangement strategy, which includes:

[0073] The cross-section four-quadrant arrangement strategy is used to determine four symmetric arrangement points on the typical circular cross-section of the flexible riser, which are distributed at equal angles around the pipe body to obtain a four-quadrant arrangement mode.

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

[0075] Specifically, the existing sensor arrangement mode can select the following two main modes according to the requirements:

[0076] The first mode is a flexible riser structure embedded arrangement. In the manufacturing stage of the flexible riser, a fiber bragg grating (FBG) strain sensor is embedded in the structure inside the flexible riser. The sensor is distributed in the axial direction close to the outside of the tensile layer or the middle interlayer of the flexible riser to form a continuous strain monitoring array. A metal sheath can be used to package the fiber array to improve the pressure resistance and bending performance, and the tensile layer is formed by adhesion or weaving. This mode is synchronous with the deformation of the flexible riser structure, has high response accuracy, and the measurement data can better reflect the true mechanical state. The mode avoids direct contact with seawater, has high corrosion resistance and reliability, and can realize long-term maintenance-free monitoring. However, this mode has the disadvantages of long manufacturing cycle, high cost, unsuitable for existing or in-service flexible risers, unable to replace and maintain, and affecting the entire monitoring capability once damaged.

[0077] The second mode is a flexible riser external attachment arrangement. In the installation or service stage of the flexible riser, the sensor is attached to the surface of the outermost coating layer (usually a high polymer sheath layer) of the flexible pipe to form a attached sensing monitoring system. The surface strain gauge sensor type can be selected, and the sensor is arranged by using flexible adhesive material, belt fixing structure or mechanical buckle. At the same time, the sensor can be reinforced by using a protective shell or a waterproof module. The mode has the advantages of flexible installation, suitable for in-service or existing flexible risers, flexible adjustment of position and density according to actual monitoring needs, easy maintenance and replacement, and suitable for multiple monitoring or phased deployment. However, the mode has the disadvantages of being limited by the external environment, being easily affected by seawater erosion, marine organism attachment and other interference, having a certain lag in structural response, especially high-frequency dynamic response, and the fixed or adhesive material aging may affect the quality of monitoring data.

[0078] To improve the omnidirectional sensing capability and reconstruction accuracy of the flexible riser motion monitoring, the present application further adopts a cross-section four-quadrant arrangement strategy when arranging the sensor, as shown in FIG. 1. Figure 4 As shown in FIG. 1, four symmetrical points (such as 0°, 90°, 180° and 270° directions) are selected on the typical circular cross-section of the flexible riser to form a four-quadrant arrangement mode. A group of sensor units are arranged on the axis of the flexible riser at a certain equal interval (such as every 1-3 meters), and each group contains four sensors distributed at the symmetrical points.

[0079] In some embodiments of the present application, the S2 is arranged in the control cabin or the upper structure of the offshore platform. An industrial embedded data acquisition system is applied in the module to acquire the monitoring data of multiple sensors and provide data caching and time stamp marking.

[0080] The photoelectric conversion module is arranged in the control cabin or the upper structure of the offshore platform 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 reading by the acquisition terminal. The module can also perform automatic temperature compensation and multi-channel parallel demodulation.

[0081] The synchronous control module is arranged in the control cabin or the superstructure of the offshore platform, and is used for synchronously collecting and controlling each data channel by using a unified clock source, and controlling unified triggering collection of each data channel based on a hardware interrupt mechanism;

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

[0083] The power supply and voltage stabilizing module is arranged in the control cabin or the superstructure of the offshore platform, and is used for guaranteeing stable operation of the sensor and the collection system.

[0084] In some embodiments of the present application, in the S3, the flexible riser motion response data is obtained based on the data collection and transmission system and the sensor system, and the S3 comprises the following steps:

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

[0086] The data collection 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 the S3, the flexible riser motion response data is converted into flexible riser displacement data based on a Timoshenko beam model and Tikhonov regularization, and the S3 comprises the following steps:

[0088] S31, the bending curvature is calculated based on the Timoshenko beam model, and the expression is as follows:

[0089]

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

[0091] For the offshore flexible riser, the axial normal strain can be ignored, and then only one strain sensor can be used to calculate the deformation curvature in each direction, and the expression is as follows:

[0092]

[0093] In the actual working process of the grating optical fiber sensor, due to the problem of the optical fiber system, part of the sensor collected data may be missing, in order to make full use of the effective data as much as possible, for the sensor with normal data collection on both sides of the riser, the curvature is calculated by using the above formula.

[0094] For the missing sensor on one side, the calculation is performed using the above formula.

[0095] S32, the flexible riser displacement data is calculated based on the bending curvature of the flexible riser:

[0096]

[0097] wherein, is the second derivative of the displacement y(x) with respect to the position x, and κ(x) is the spatial bending curvature;

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

[0099]

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

[0101] Specifically, directly using numerical integration will continuously amplify noise, therefore Tikhonov regularization is introduced. The problem is converted into an optimization problem, which guarantees the smoothness and fitting accuracy of the solution.

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

[0103] Based on the wavelet threshold denoising method, the signal is decomposed into different frequency bands, the original strain signal is decomposed by selecting a target wavelet basis, the decomposition layer is 3-5 layers, the soft threshold or hard threshold method is used to denoise the high frequency subband, and the denoised subband is inverse wavelet transformed and smoothed to obtain the flexible riser displacement denoising data.

[0104] In some embodiments of the present application, in the S5, the motion response reconstruction of the flexible riser displacement denoising data is performed based on the variational mode decomposition VMD, which comprises:

[0105] Specifically, due to the limited discrete measuring points arranged on the surface or inside of the flexible riser, only the motion responses (displacements) of the measuring points can be obtained, and the complete expression of the overall motion mode of the flexible riser as a continuum needs to rely on the spatial interpolation and modal reconstruction technology. The application proposes a motion reconstruction method combining a variable mode decomposition (VMD) algorithm, which reconstructs the global response of the flexible riser from the monitoring results of the limited points.

[0106] The principle of the VMD algorithm is to decompose the input signal f(t) into k modal intrinsic functions u k (t) through adaptive quasi-orthogonal transformation, and the target is to minimize the sum of the estimated bandwidth of each mode, which essentially converts the signal decomposition problem into an optimal solution problem with constraints. The VMD algorithm has unique advantages in removing high-frequency noise and nonlinear complex data. The VMD algorithm mainly includes two parts of establishing a variational constraint model and solving it.

[0107] S51, a variational constraint model is established based on a variable mode decomposition VMD, and the expression is:

[0108]

[0109] s.t. ∑ k u k (t)=f(t);

[0110] Among them, u k is the modal function obtained by decomposition, ω k is the center frequency of the corresponding modal function, u k (t) is the kth modal function, is the time derivative operator, δ(t) is the Dirac distribution function, and f(t) is the flexible riser displacement denoising data.

[0111] S52, the saddle point is calculated using an alternating direction multiplier algorithm, and the expression is:

[0112]

[0113] Among them, α is a penalty factor, λ is a Lagrange factor, L({u k}, {ω k}, λ) is an augmented Lagrange function, and λ(t) is a time-varying Lagrange multiplier.

[0114] S53, the frequency domain and center frequency of the new variational constraint model are obtained, and the constraint variational optimal solution is obtained, and the expression is:

[0115] u n+1 =argmin

[0116]

[0117] wherein p is an update factor, u n+1 is the set of all modal functions after the n+1th iteration, is the central frequency of the kth modal function after the n+1th iteration, λ n+1 is the time-varying Lagrange multiplier after the n+1th iteration, is the kth modal function after the n+1th iteration;

[0118] S54, reconstructing the motion response of the flexible riser displacement denoising data based on the constraint variational optimal solution.

[0119] The method provided by the application is a marine flexible riser motion reconstruction method based on monitoring data, and aims to realize high-precision and spatiotemporal continuous reconstruction and evaluation of the overall motion state of the flexible riser under complex marine environmental conditions. The method comprehensively uses fiber strain monitoring, synchronous data acquisition, wavelet threshold denoising processing, strain-displacement conversion model and variable modal decomposition reconstruction technology, and realizes intelligent mapping from distributed discrete point data to the overall dynamic response of the riser. The application can be widely applied to deep-sea oil and gas exploitation, submarine pipeline safety monitoring, marine engineering structure health evaluation and other fields, and provides key technical support for safe operation and intelligent operation and maintenance of marine engineering equipment, and has a wide application prospect.

[0120] The embodiments of the application will be described in detail below with reference to specific examples.

[0121] Step 1, sensor layout, the sensor can adopt a grating fiber strain sensor or a strain gauge. The grating fiber sensor can be pre-embedded on the outside of the flexible pipe tensile layer and arranged along the axial direction of the flexible riser, as shown in FIG. 1. Figure 3 The strain gauge can be arranged on the outermost coating layer of the flexible pipe and also arranged along the axial direction. The fiber and the strain gauge adopt a four-quadrant cross-section layout strategy, that is, four symmetrical points (such as 0°, 90°, 180° and 270° directions) are selected on the typical circular cross-section of the flexible riser, and are distributed at equal angles around the pipe body, as shown in FIG. 2. Figure 5

[0122] Step 2, data acquisition, in the embodiment of the application, in order to realize accurate monitoring of the motion response of the flexible riser in the marine environment, a complete data acquisition and transmission system needs to be deployed on the offshore platform. The system is composed of multiple functional modules, and the functions and implementation modes of the modules are as follows:

[0123] ​Data Acquisition Terminal Module: The data acquisition terminal is installed in the control cabin or superstructure of the offshore platform and adopts an industrial-grade embedded data acquisition system. This terminal should have the ability to acquire multi-channel high-precision analog signals, support multiple sensor interfaces, stably read data from multiple sensors, and provide functions such as data buffering and timestamp marking.

[0124] Photoelectric conversion module: If a fiber optic strain gauge (FBG) sensor is embedded or bonded in the flexible riser, a dedicated photoelectric demodulation module, such as a spectral demodulator, is required. This module converts the change in the center wavelength reflected by the FBG sensor into a digital signal and outputs equivalent physical quantities such as strain, voltage, or frequency shift for the acquisition terminal to read. To improve system reliability, the photoelectric demodulation module should have automatic temperature compensation and multi-channel parallel demodulation capabilities.

[0125] Synchronization Control Unit: To ensure accurate alignment of multi-channel sensor data on the time axis, this system introduces a synchronization control unit. A unified clock source is used to synchronously control the acquisition of data from each channel, ensuring timing consistency during subsequent reconstruction and processing. The system can control the unified triggering of acquisition across all sampling channels via a hardware interrupt mechanism.

[0126] Transmission module: The optical fiber transmits data from the riser to the offshore platform. The transmission module has the capabilities of automatic reconnection after disconnection, buffer recovery, and encrypted transmission, which improves data integrity and security.

[0127] Power supply and voltage regulation module: To ensure the stable operation of the sensor and data acquisition system, an industrial-grade power supply and voltage regulation system is required. The power supply system should meet the protection level and electromagnetic compatibility standards of marine platforms and be adaptable to high salt spray, high humidity and high vibration environments.

[0128] Sampling Frequency and Strategy: Under normal monitoring conditions, the system default sampling frequency is set to 50Hz, which can meet the data acquisition requirements of the dynamic response of the flexible riser under most wave and platform excitation frequencies. The sampling frequency can be adaptively adjusted according to the operating status. For example, when the platform is in a static and stable state, the sampling frequency is reduced (to 10Hz), and under severe sea conditions or sudden load conditions, the frequency is automatically increased (to 100Hz) to obtain data with higher time resolution. The strain data collected by four sensors at a certain flexible riser cross section is shown in Table 1.

[0129] Table 1. Strain data collected by a sensor at a cross-section of a flexible riser (×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 discrete displacement data through calculation formula, as shown in Table 2.

[0132] Table 2 flexible riser displacement discrete point data

[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, through the wavelet threshold denoising method, the displacement of the flexible riser monitoring point is denoised. The wavelet denoising method is based on the good time-frequency local characteristics of wavelet transform, which can decompose the signal into different frequency bands, suppress noise in high frequency subband, and improve the signal-to-noise ratio while retaining the original signal characteristics. The specific process is as follows:

[0135] Wavelet decomposition: select an appropriate wavelet basis to perform multi-scale wavelet decomposition on the original strain signal, and the decomposition layer is generally set to 3-5 layers;

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

[0137] Coefficient processing: for soft threshold method, the part of high frequency coefficient below the threshold is set to 0, and the rest is attenuated linearly according to the distance from the threshold; for hard threshold method, the high frequency coefficient below the threshold is directly removed.

[0138] Wavelet reconstruction: inverse wavelet transform is performed on the denoised coefficients to restore the time domain signal after smoothing processing.

[0139] The displacement denoising result of the flexible riser monitoring point is shown in Table 3.

[0140] Table 3 displacement denoising result of flexible riser monitoring point

[0141] Sensor position (m) Displacement denoised 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, motion response reconstruction, using variable mode decomposition method, the discrete flexible riser displacement data is reconstructed into continuous displacement data by calculation formula, and the reconstruction result is shown in Figure 5 .

[0143] In summary, the present application proposes a kind of marine flexible riser motion reconstruction method based on monitoring data, to realize the high-precision, space-time continuous reconstruction and evaluation of the overall motion state of flexible riser in complex marine environment conditions. The method comprehensively uses fiber strain monitoring, synchronous data acquisition, wavelet threshold denoising processing, strain-displacement conversion model and variable mode decomposition reconstruction technology, realizes the intelligent mapping from distributed discrete point data to riser overall dynamic response. The present application can be widely applied to deep sea oil and gas exploitation, submarine pipeline safety monitoring, marine engineering structure health evaluation and other fields, provides key technical support for the safe operation and intelligent operation and maintenance of marine engineering equipment, and has broad application prospect.

[0144] In the present application, unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. If there is a conflict between the definitions in the specification and those in the patent specification, the definitions in the specification are intended to prevail. In addition, the terms used herein are merely for the purpose of describing the embodiments of the present application and are not intended to limit the present application.

[0145] Finally, it should be noted that the above examples are only used to illustrate the technical solutions of the present application, but not to limit the present application. Although the present application has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present application can still be modified or equivalently replaced, and these modifications or equivalent replacements should not make the modified technical solutions deviate from the spirit and scope of the technical solutions of the present application.

Claims

1. A method for reconstructing the motion response of a marine dynamic flexible riser based on monitoring data, characterized in that, Includes the following steps: S1. Sensors are deployed in the flexible riser system using either a structural embedded deployment method or an external attachment deployment method. The sensor deployment pattern is then optimized based on a cross-sectional four-quadrant deployment strategy to obtain the sensor system. S2. A data acquisition and transmission system is set up on the marine platform. The data acquisition and transmission system includes the following modules: acquisition terminal module, photoelectric conversion module, synchronization control module, data transmission module, and power supply and voltage stabilization module. S3. Obtain the motion response data of the flexible riser based on the data acquisition and transmission system and the sensor system, and transform the motion response data of the flexible riser into the displacement data of the flexible riser based on the Timoshenko beam model and Tikhonov regularization. In S3, the flexible riser motion response data is transformed into flexible riser displacement data based on the Timoshenko beam model and Tikhonov regularization, including: S31. The bending curvature is calculated based on the Timoshenko beam model, and its expression is: in, The distance between the sensor and the center of the pipe. For the motion response data of flexible risers, Distance along the pipeline for The bending curvature of the flexible riser in the z-direction. for The bending curvature of the flexible riser in the y-direction at point ; Alternatively, ignoring the axial normal strain of the marine flexible riser, the bending curvature is calculated using a sensor in each direction, expressed as: S32. The displacement data of the flexible riser is obtained based on the bending curvature calculation: in, displacement Position The second derivative, For spatial curvature; S33. S32 is optimized based on Tikhonov regularization, and the expression is: in, Discrete position Curvature measurement at that point For regularization parameters, Let the regularization objective function be used. S4. The displacement data of the flexible riser is denoised based on the wavelet threshold denoising method to obtain the denoised displacement data of the flexible riser. S5. Motion response reconstruction of displacement noise reduction data of flexible riser based on variational mode decomposition (VMD).

2. The method for reconstructing the motion response of a marine dynamic flexible riser based on monitoring data according to claim 1, characterized in that, In step S1, optimizing the sensor deployment mode based on the cross-sectional four-quadrant deployment 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 at equal angles around the pipe body to obtain the four-quadrant layout pattern. Multiple sensor units are arranged at preset intervals along the axis of the flexible riser. Each sensor unit includes four sensors arranged in a four-quadrant pattern.

3. The method for reconstructing the motion response of a marine dynamic flexible riser based on monitoring data according to claim 2, characterized in that, In S2, the data acquisition terminal module is installed in the control cabin or superstructure of the marine platform. The module uses an industrial embedded data acquisition system, which can acquire monitoring data from multiple sensors and provide data caching and timestamp marking. The photoelectric conversion module is installed in the control cabin or superstructure of the marine platform. It is used to convert the center 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 located in the control cabin or superstructure of the offshore platform. It is used to synchronously acquire and control each data channel using a unified clock source, and to control the unified trigger acquisition of each data channel based on a hardware interrupt mechanism. The data transmission module is located in the control cabin or superstructure of the offshore platform. It is used to transmit the collected data from the riser end to the offshore platform end, and has functions such as automatic reconnection after disconnection, cache recovery and encrypted transmission. The power supply and voltage stabilization module is located in the control cabin or superstructure of the offshore platform to ensure the stable operation of the sensors and data acquisition system.

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

5. The method for reconstructing the motion response of a marine dynamic flexible riser based on monitoring data according to claim 4, characterized in that, In step S4, the flexible riser displacement data is denoised using the wavelet threshold denoising method to obtain the denoised flexible riser displacement data, including: The signal is decomposed into different frequency bands based on the wavelet thresholding method. The target wavelet basis is selected to perform wavelet decomposition on the original strain signal. The number of decomposition layers is 3-5. The high-frequency sub-bands are denoised using soft thresholding or hard thresholding. The denoised sub-bands are then subjected to inverse wavelet transform and smoothing to obtain the displacement denoised data of the flexible riser.

6. The method for reconstructing the motion response of a marine dynamic flexible riser based on monitoring data according to claim 5, characterized in that, In step S5, motion response reconstruction of the flexible riser displacement noise reduction data based on variational mode decomposition (VMD) includes: S51. Establish a variational constraint model based on Variational Mode Decomposition (VMD), with the following expression: ； ； in, The resulting mode functions are obtained from the decomposition. The center frequency of the corresponding modal function. For the first k One modal function, For time derivative operators, Let be the Dirac distribution function. Noise reduction data for flexible riser displacement; S52. Calculate the saddle point using the alternating direction multiplier algorithm, the expression is: ； in, As a penalty factor, For Lagrange factors, To augment the Lagrange function, For time-varying Lagrange multipliers; S53. Obtain the frequency domain and center frequency of the new variational constraint model, and obtain the constraint variational optimal solution, expressed as: ； ； ； in, For the update factor, For all modal functions in the th... n+1 The set after the next iteration For the first k The modal function at the th ... n+1 The center frequency after the next iteration For the first n+1 The time-varying Lagrange multipliers after the next iteration In the n+1 After the nth iteration k One modal function; S54. Motion response reconstruction of flexible riser displacement noise reduction data based on constrained variational optimal solution.

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