Real-time evaluation method for sea condition adaptability of floating hydrogen production platform based on digital twinning

Abstract

The invention belongs to the technical field of ocean engineering and water electrolysis hydrogen production. In order to solve the problem that a traditional model is difficult to deal with dynamic sea conditions, a platform-environment coupling digital twin model is constructed, multi-source monitoring data is fused, and platform motion response is predicted through deep reinforcement learning. And generating anti-storm strategies such as ballast water regulation based on a prediction result, and realizing real-time optimization. According to the method, the evaluation accuracy is improved by 25%, and the strategy response time is lt; under the conditions of 8-level wind and 1.2 m wave height, the motion amplitude of the platform is reduced by 28%, the shutdown frequency of a hydrogen production system is reduced by 75%, and operation and maintenance of the floating platform are promoted to be upgraded to intelligent.

Description

Technical Field

[0001] The present invention belongs to the technical fields of marine engineering and water electrolysis hydrogen production, and in particular relates to a real-time assessment method for the sea condition adaptability of a floating hydrogen production platform based on digital twins. Background Art

[0002] Against the backdrop of global energy transition, floating platform offshore hydrogen production technology is developing rapidly. Offshore wind power resources are abundant, and combining them with hydrogen production technology offers significant advantages. For example, a test prototype of an offshore wind power hydrogen production and storage system, developed by my country Three Gorges Corporation, completed 720 hours of continuous full-machine field testing in the Yazhou Bay offshore test area in Sanya, demonstrating the feasibility and potential of offshore wind power hydrogen production. Furthermore, the world's first offshore wind power in-situ direct electrolysis of hydrogen without desalination, jointly developed by Shenzhen University and Dongfang Electric Corporation, also successfully completed sea trials in Fujian, validating the reliability of direct electrolysis of hydrogen without desalination in real marine environments. All of this demonstrates that floating platform offshore hydrogen production technology is gradually moving from theory to practice.

[0003] Digital twin technology, as an emerging technology, has also been applied in the field of floating hydrogen production platforms. By constructing virtual models corresponding to physical entities in virtual space, it can reflect the status of physical entities in real time and assist in decision-making. For example, the real-time dynamic twin system of the "Deep Sea No. 1" energy station floating facility developed by the CNOOC Research Institute includes intelligent technologies such as visualization and early warning of monitoring data, and real-time dynamic mechanism model twinning. However, in floating hydrogen production platforms, digital twin technology has limitations in real-time assessment of sea state adaptability. On the one hand, the current model cannot accurately reflect the dynamic response of the platform and hydrogen production equipment under complex and changing sea conditions; on the other hand, the real-time assessment accuracy of key indicators such as hydrogen production efficiency and equipment stability under different sea conditions is insufficient.

[0004] Research has been conducted at home and abroad on the real-time assessment method of sea state adaptability of floating hydrogen production platforms based on digital twins. Chen et al. (Energies 2024, 17(8), 1964) analyzed the application of digital twin technology in improving the reliability of offshore wind turbines, but the research on real-time assessment of sea state adaptability is not in-depth enough. In the research in this field, the number of patents is limited, and most of them do not fully consider the impact of multi-factor coupling under complex sea conditions on floating hydrogen production platforms. Some studies only focus on the impact of sea conditions on the structural stability of the platform, ignoring the comprehensive assessment of hydrogen production processes and equipment operating status. In actual cases, some early offshore hydrogen production demonstration projects suffered a significant decrease in hydrogen production efficiency and frequent equipment failures under severe sea conditions due to inaccurate real-time assessment of sea state adaptability. For example, when a certain offshore wind power hydrogen production pilot project encountered a strong typhoon, the hydrogen production equipment was severely damaged due to insufficient prediction of sea state changes, and the repair cost was high. This highlights the shortcomings of the current assessment method in terms of accuracy and comprehensiveness, which urgently needs to be improved and perfected.

[0005] In general, the existing real-time assessment technology for hydrogen production platform sea state adaptability still has the following defects to be overcome:

[0006] 1) The real-time and accuracy of multi-dimensional data collection, such as the omnidirectional wave energy spectrum, are insufficient to meet the needs of complex sea condition assessment.

[0007] 2) The accuracy and cross-scale processing capabilities of wavefront reconstruction and multi-physics field coupling modeling are insufficient, affecting the accuracy of the assessment.

[0008] 3) There are obvious limitations in the intelligence and broadband adaptability of platform vibration suppression, dynamic evaluation and self-healing response. Summary of the Invention

[0009] The present invention is made in view of the problems existing in the prior art. The present invention constructs an innovative real-time assessment system for the adaptability of floating hydrogen production platforms to sea conditions from multiple dimensions. At the data acquisition and processing level, advanced sensor arrays and data fusion algorithms are adopted. Based on the multi-physics field coupling theory, advanced algorithms such as optical flow method and particle filter algorithm are introduced to deeply fuse and pre-process the collected multi-source data such as omnidirectional wave energy spectrum, wind speed and direction, and ocean current. Taking the optical flow method as an example, it can accurately track the motion trajectory of the characteristic points on the wave surface by analyzing the motion of pixels in the image sequence. Combined with the particle filter algorithm, it can effectively filter out noise interference and provide an accurate data basis for subsequent sea condition analysis. In terms of wavefront reconstruction and multi-physics field coupling modeling, a method combining high-order boundary element method (HOBEM), computational fluid dynamics (CFD) and finite element method (FEM) is used. Based on potential flow theory, HOBEM was used to accurately determine the velocity potential of wave motion and reconstruct the complex wave surface. Simultaneously, CFD simulated the flow field in detail, accounting for the impact of factors such as fluid viscosity on the flow field around the platform. FEM was then used to perform mechanical analysis of the platform structure, enabling efficient coupled modeling of multiple physical fields. This cross-scale, multi-physical field collaborative modeling approach accurately describes the interaction between the platform and the environment under varying sea conditions, significantly improving assessment accuracy.

[0010] In the platform response prediction and dynamic evaluation link, the present invention introduces the recurrent neural network (RNN) and its variant long short-term memory network (LSTM) in deep learning. By constructing a large number of training sets of sea condition samples and platform response data, RNN and LSTM can effectively capture the complex time series relationship between sea condition changes and platform response, and learn the platform vibration, displacement, stress and other response characteristics under different sea conditions. At the same time, combined with adaptive control theory, based on real-time monitoring and prediction results, the platform attitude adjustment, hydrogen production equipment operating parameters, etc. are dynamically optimized to achieve adaptive stable operation and efficient hydrogen production of the platform under complex sea conditions, greatly improving the platform's sea condition adaptability and operational reliability, and comprehensively innovating the real-time assessment method of sea condition adaptability of floating hydrogen production platforms.

[0011] In order to achieve the above objectives, the technical solution of the present invention is a real-time assessment method for sea state adaptability of a floating hydrogen production platform based on digital twin, which is characterized by comprising the following steps:

[0012] Step 1: Build a high-resolution sea state perception system. This system uses a lidar wavefront scanner with a spatial resolution of no more than 0.5m and a millimeter-wave radar array with a sampling frequency of no less than 100Hz to collect omnidirectional wave energy spectra, three-dimensional current profiles, and turbulent wind field vector data in real time. Simultaneously deploy a salt spray corrosion-resistant microelectrode array and a high-frame-rate multispectral imaging system to monitor the overpotential distribution of the anode and cathode of the electrolytic cell, the density of catalyst active sites, and the dynamic parameters of bubble precipitation in real time. The end-to-end latency of data acquisition is controlled within 8ms.

[0013] Step 2: Build a dynamic wavefront reconstruction engine, using an improved iterative inversion algorithm to analyze lidar point cloud data, fuse millimeter-wave radar echoes with microelectrode array electrochemical signals, and separate the wave's main frequency components using adaptive variational mode decomposition technology. The root mean square error of the reconstructed wavefront spatial distribution does not exceed 4%;

[0014] Step 3: Construct a multi-physics field coupled digital twin core. Based on the transient large eddy simulation method and the electrochemical transfer equation, a cross-scale coupling solution framework is established: adaptive mesh refinement technology is used in the near field, with the mesh size not exceeding 1 / 60 of the characteristic wavelength λ; the discrete eddy method is used in the far field, with the mesh size not exceeding 1 / 12 of λ. A micro-nano bubble group evolution model is introduced to quantify the nonlinear effect of the gas-liquid interface phase change on the mass transfer efficiency;

[0015] Step 4: Construct a multi-dimensional dynamic assessment matrix and define three core indicators: the sea state chaos index, the electrolysis efficiency robustness factor, and the platform stability health. The sea state chaos index characterizes the intensity of environmental disturbances through the entropy of the wave-current-wind field coupled energy spectrum. The electrolysis efficiency robustness factor reflects the ability to maintain hydrogen production efficiency under variable operating conditions. The platform stability health is quantified by the combined attitude angle deviation and vibration energy.

[0016] Step 5: Based on the above evaluation system, an integrated space-ground communication architecture is deployed. Encrypted data streams are transmitted through dual redundant links between the 5G private network and the low-orbit satellite constellation. A dynamic rotation key management mechanism is used to ensure that the clock synchronization error between the digital twin and the physical platform does not exceed 5ms, and the key update cycle is compressed to within 3 minutes.

[0017] Step 6: Establish an intelligent hierarchical self-healing mechanism. When the platform's stability health falls below 85 points, a first-level response is triggered, activating the local force adaptive enhancement mode. When it falls below 70 points, a second-level response is initiated, performing dynamic reconstruction of the metamaterial lattice topology. When it falls below 55 points, a third-level response is enforced, initiating the electrolyzer safe off-grid protocol and the hydrogen and oxygen staged discharge system.

[0018] Step 7: Implement the twin autonomous evolution system, generate a multimodal dataset of extreme sea conditions every 36 hours through a physical constraint-generated adversarial network, drive the online evolution of the digital twin model parameters, and ensure that the statistical characteristics of the generated data do not differ from the measured data by more than 0.02.

[0019] On the basis of the above technical solution, it is further defined that the high frame rate multispectral imaging system described in step 1 adopts 500fps high-speed camera and narrow-band hydrogen and oxygen characteristic spectral filter to invert the local water saturation of the proton exchange membrane by precipitating bubble size distribution, with a measurement accuracy of 95%; the salt spray corrosion-resistant microelectrode array adopts a nanoporous iridium-platinum composite electrode structure, covering a wide frequency band of 0Hz to 2MHz, and real-time analysis of the catalyst activity attenuation gradient.

[0020] On the basis of the above technical solution, it is further defined that the micro-nano bubble group evolution model in step 3 includes a phase change driving force coefficient of 1.6 to 2.2 and a turbulent diffusion correction factor of 0.08 to 0.15, and describes the dynamic behavior of the bubble group through the coupling mechanism of vapor pressure gradient and vortex shedding.

[0021] On the basis of the above technical solution, it is further defined that the dynamic reconstruction of the metamaterial lattice topology in step 6 adopts a shape memory alloy-piezoelectric ceramic composite drive unit to achieve a controllable deformation of the lattice constant of 10% to 30% within 150ms, so that the band gap center frequency accurately matches the 1.8 to 2.2 octaves of the wave main frequency.

[0022] On the basis of the above technical solution, it is further defined that the physical constraint generative adversarial network described in step 7 embeds the incompressible flow continuity equation, turbulent kinetic energy transport equation and electrochemical charge conservation law as strong constraints into the generator loss function to ensure that the generated data satisfies the multi-physical field coupling conservation law.

[0023] The present invention is beneficial in that:

[0024] 1) Through the triple fusion perception system of lidar, millimeter-wave radar, and multispectral imaging, full-section scanning of the wave field and simultaneous monitoring of the microbubble distribution in the electrolytic cell are achieved. Combined with the physical model of the evolution of micro-nano bubble groups, the error in wave force calculation is reduced from the traditional 22% to 6.5%, and the accuracy of mass transfer efficiency prediction is improved by 40%.

[0025] 2) A multi-dimensional dynamic evaluation matrix integrating the sea state chaos index and electrolysis efficiency robustness factor is combined with an integrated air-space-ground communication architecture (synchronization error ≤ 5ms); a hierarchical self-healing mechanism achieves millisecond-level response from local vibration suppression to emergency off-grid, improving the platform stability health score to 89 points and reducing the risk of equipment damage by 50%. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Various other advantages and benefits will become apparent to those skilled in the art upon reading the detailed description of the preferred embodiment below. The accompanying drawings are for illustration purposes only and are not to be considered as limiting the present invention. The same reference symbols are used throughout the drawings to represent the same components. In the drawings:

[0027] Figure 1 This is the overall flow chart of the real-time assessment method for sea condition adaptability of floating hydrogen production platform based on digital twin.

[0028] Figure 2 This is a diagram of the data collection and transmission architecture of the high-resolution sea condition perception system.

[0029] Figure 3 This is the algorithm logic and precision control flow chart of the dynamic wavefront reconstruction engine.

[0030] Figure 4 Flowchart of the core modeling approach for multi-physics coupled digital twins.

[0031] Figure 5 This is the response logic and threshold triggering flowchart of the intelligent hierarchical self-healing mechanism. DETAILED DESCRIPTION

[0032] Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments described herein. Rather, these embodiments are provided to enable a more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art.

[0033] As an embodiment of the present invention, a method for dynamic stability assessment of a floating hydrogen production platform coupled with multi-modal sea conditions is provided. The general process is as follows: Figure 1 As shown, the specific steps include:

[0034] Step 1: Build a high-resolution sea state perception system (see attached Figure 2 As shown), through a laser radar wavefront scanner with a spatial resolution of no more than 0.5m and a millimeter wave radar array with a sampling frequency of no less than 100Hz, real-time collection of omnidirectional wave energy spectrum, three-dimensional ocean current profile and turbulent wind field vector data; synchronous deployment of salt spray corrosion-resistant microelectrode array and high frame rate multispectral imaging system, real-time monitoring of the anode and cathode overpotential distribution of the electrolytic cell, the density of catalyst active sites and the bubble precipitation kinetic parameters, the end-to-end delay of data acquisition is controlled within 8ms; wherein, the high frame rate multispectral imaging system adopts 500fps high-speed camera and narrow-band hydrogen and oxygen characteristic spectral filter, and the local water saturation of the proton exchange membrane is inverted by the precipitated bubble size distribution, with a measurement accuracy of 95%; the salt spray corrosion-resistant microelectrode array adopts a nanoporous iridium-platinum composite electrode structure, covering a wide frequency band of 0Hz to 2MHz, and real-time analysis of the catalyst activity attenuation gradient.

[0035] Step 2: Establish a dynamic wavefront reconstruction engine, use an improved iterative inversion algorithm to analyze the lidar point cloud data, fuse the millimeter wave radar echo and the electrochemical signal of the microelectrode array, separate the wave main frequency component through the adaptive variational mode decomposition technology, and reconstruct the wavefront spatial distribution with a root mean square error of no more than 4% (see the attached Figure 3 shown);

[0036] Step 3: Construct a multi-physics field coupled digital twin core, and establish a cross-scale coupling solution framework based on the transient large eddy simulation method and the electrochemical transfer equation: the near-field area uses adaptive grid encryption technology, and the grid size does not exceed 1 / 60 of the characteristic wavelength λ; the far-field area uses the discrete eddy method, and the grid size does not exceed 1 / 12 of λ. The micro-nano bubble group evolution model is introduced to quantify the nonlinear effect of the gas-liquid interface phase change on the mass transfer efficiency; wherein, the micro-nano bubble group evolution model includes a phase change driving force coefficient of 1.6 to 2.2 and a turbulent diffusion correction factor of 0.08 to 0.15, and the bubble group dynamic behavior is described by the vapor pressure gradient and vortex shedding coupling mechanism (such as the attached Figure 4 shown).

[0037] Step 4: Construct a multi-dimensional dynamic assessment matrix and define three core indicators: the sea state chaos index, the electrolysis efficiency robustness factor, and the platform stability health. The sea state chaos index characterizes the intensity of environmental disturbances through the entropy of the wave-current-wind field coupled energy spectrum. The electrolysis efficiency robustness factor reflects the ability to maintain hydrogen production efficiency under variable operating conditions. The platform stability health is quantified by the combined attitude angle deviation and vibration energy.

[0038] Step 5: Deploy an integrated space-ground communication architecture, transmit encrypted data streams through dual redundant links between the 5G private network and the low-orbit satellite constellation, and use a dynamic rotation key management mechanism to ensure that the clock synchronization error between the digital twin and the physical platform does not exceed 5ms, and the key update cycle is compressed to within 3 minutes;

[0039] Step 6: Establish an intelligent hierarchical self-healing mechanism (see Figure 1) Figure 5 As shown in the figure, when the platform stability health is lower than 85 points, the first-level response is triggered and the local actuation force adaptive enhancement mode is activated; when it is lower than 70 points, the second-level response is started and the dynamic reconstruction of the metamaterial lattice topology is executed; when it is lower than 55 points, the third-level response is forced to be executed, and the electrolyzer safe off-grid protocol and the hydrogen and oxygen staged discharge system are started; wherein, the dynamic reconstruction of the metamaterial lattice topology adopts a shape memory alloy-piezoelectric ceramic composite drive unit to achieve a controllable deformation of the lattice constant of 10% to 30% within 150ms, so that the band gap center frequency accurately matches the 1.8 to 2.2 octaves of the wave main frequency.

[0040] Step 7: Implement the twin autonomous evolution system. Every 36 hours, a multimodal dataset of extreme sea conditions is synthesized through a physically constrained generative adversarial network (GAN). This data drives the online evolution of the digital twin model parameters, ensuring that the statistical characteristics of the generated data do not differ from the measured data by more than 0.02. The GAN incorporates the incompressible flow continuity equation, the turbulent kinetic energy transport equation, and the electrochemical charge conservation law as strong constraints into the generator's loss function, ensuring that the generated data satisfies the multi-physics coupled conservation laws.

[0041] The following further describes the implementation of the present invention in conjunction with specific examples.

[0042] Example 1

[0043] In an open sea area in the South China Sea with a water depth of 50m and an average of 3-4 typhoons passing through it annually, a 100m×50m rectangular floating hydrogen production platform was deployed, integrating 12 sets of single tanks with a production capacity of 500Nm 3 / h electrolyzer module. Traditional solutions use single-point lidar (resolution 1.2m), low-frequency acoustic sensors (sampling frequency 20Hz), and fixed-grid fluid models. These solutions lack cross-physics field coupling assessment capabilities. Historical typhoon conditions have resulted in serious failures such as a 45% drop in electrolysis efficiency and platform vibration amplitude exceeding the safety threshold by 220%.

[0044] The present invention implements high-resolution sea condition perception, deploys a lidar wavefront scanner with a spatial resolution of 0.3m, a 128-channel millimeter-wave radar array (sampling frequency 150Hz), etc., with an end-to-end data delay of 6.8ms and a bubble size inversion accuracy of 96.2%. An improved iterative inversion algorithm is used to analyze the point cloud, combined with adaptive variational mode decomposition to separate the wave main frequency (error ±0.05Hz), with a root mean square error of 3.7% for wavefront reconstruction, and a cross-scale coupling model is constructed. The λ / 80 adaptive encrypted grid in the near field and the discrete vortex method in the far field reduce the calculation error of the gas-liquid interface mass transfer efficiency by 28%. The acoustic metamaterial substrate achieves a continuously adjustable band gap of 0.03-800Hz, the dielectric elastomer actuator has a response time of 32ms, the spatiotemporal graph convolutional neural network predicts the platform motion trajectory with a root mean square error of 2.8%, outputs a 22-channel actuation force curve (range 0.15-28kN), and the broadband vibration transmissibility is reduced to 0.105, multi-dimensional evaluation matrix calculates multi-dimensional indicators in real time.

[0045] The communication and self-healing mechanism utilizes dual-link data transmission via a 5G private network (8ms latency) and a low-orbit satellite (12min revisit period). The dynamic key rotation update cycle is 2.5 minutes, and the clock synchronization error is 4.2ms. During a typhoon's passage, the first and second level responses are triggered sequentially, without reaching the threshold for the third level response. Extreme sea condition datasets are generated every 36 hours, and a physically constrained generative adversarial network embeds strong constraints. The generated data has a statistical difference of 0.018 from the measured data, driving iterative optimization of model parameters.

[0046] Compared with traditional technologies, this invention achieves data acquisition latency of less than 8ms, improving the accuracy of key parameters by 2-5 times; modeling error of less than 5%, and reducing gas-liquid mass transfer simulation error by 28%. The intelligent vibration suppression system dynamically adjusts within 40ms, reducing vibration transmissibility by 58%. The hydrogen production efficiency maintenance rate during typhoons exceeds 85%, and the failure rate of key platform components is reduced by 91%. Through comprehensive technological breakthroughs and the construction of a closed-loop evaluation system, this approach addresses the core issues of traditional methods such as data distortion, model inaccuracy, and delayed response in complex sea conditions, providing a revolutionary technical solution for the safe and efficient operation of floating hydrogen production platforms in extreme marine environments.

[0047] Example 2

[0048] A 60m x 40m circular floating hydrogen production platform, integrating eight electrolyzer modules, was deployed in a coastal area of ​​the Bohai Sea, located at a water depth of 20m and with winter ice thicknesses of 0.3-0.8m. The traditional solution, which employed a single-point ultrasonic ice detector (0.5m resolution), a mechanical vibration sensor (50Hz sampling frequency), and a static ice load model, was unable to analyze ice-wave-platform coupled vibrations in real time. Historically, ice vibrations had caused frequent leakage failures at the electrolyzer interfaces, resulting in a 35% downtime rate.

[0049] The implementation scheme of the present invention deploys an ice-resistant lidar (resolution 0.4m, low temperature resistance -30°C) and a 96-channel millimeter-wave radar (sampling frequency 120Hz), equipped with a salt spray corrosion-resistant microelectrode array (operating temperature -25°C to 80°C) and a 400fps multispectral imaging system. An improved iterative inversion algorithm is used to fuse ice surface echo data, and the root mean square error of wavefront reconstruction is 3.9%; the band gap of the acoustic metamaterial substrate is adjusted to 0.1-500Hz, the response time of the dielectric elastomer actuator is 35ms, and the spatiotemporal graph convolutional neural network is combined to predict the ice vibration trajectory (root mean square error 3.2%), and the vibration transmissibility is reduced to 0.11. The robustness factor of the electrolysis efficiency during the icing period reaches 88%, the platform stability health is maintained at more than 90 points, and the failure rate of key components is reduced by 85% compared with the traditional solution. Data acquisition, communication architecture and twin evolution mechanism are not described in detail.

[0050] Example 3

[0051] A 120m x 60m rectangular floating hydrogen production platform, equipped with 16 electrolyzer modules, was deployed in a strong current zone in the East China Sea, located at a depth of 80m and with a maximum velocity of 2.5m / s. Traditional solutions, using low-precision acoustic Doppler velocimeters (accuracy ±0.15m / s) and a fixed-grid flow model, were unable to capture the vortex-induced vibrations (VIVs) induced by strong currents. Historically, the platform's sway displacement exceeded safety limits by 180%, and electrolyzer catalyst activity plummeted by 30%.

[0052] During the implementation of the present invention, a three-dimensional ocean current profile radar (accuracy ±0.05m / s, sampling frequency 100Hz) was deployed, a λ / 100 adaptive encrypted grid (λ is taken as the characteristic wavelength of strong current) was used in the near field, and a micro-nano bubble model with a turbulent diffusion correction factor of 0.15 was embedded. The calculation error of gas-liquid mass transfer efficiency was reduced by 32%. The band gap of the acoustic metamaterial substrate covers 0.05-600Hz, the actuator output force range is 0.2-30kN, and the broadband vibration transmissibility is 0. 0.12. Under strong current conditions, the electrolysis efficiency maintenance rate is 91%, and the platform posture The state angle deviation is ≤4.0°, the vibration energy is reduced by 62% compared with the traditional solution, and no catalytic The activity of the chemical agent has abnormally decreased. Data collection delays, self-healing mechanisms, and twin evolution will not be elaborated on.

[0053] Example 4

[0054] In a 40m-deep area of ​​the Yellow Sea, where typhoons and extratropical cyclones alternate annually, an 80m×50m polygonal floating hydrogen production platform with 10 electrolyzer modules was deployed. Traditional solutions employ split sensor arrays (latency > 50ms) and independent modeling of single physical fields. This results in an evaluation lag exceeding 100ms in mixed sea conditions, and historical data shows that hydrogen production efficiency fluctuates by as much as ±25%.

[0055] During the implementation of the present invention, a sensor network with synchronous clock calibration (delay of 6.5ms) is used, and dynamic wavefront reconstruction fuses wave and cyclone wind field data with a root mean square error of 3.8%. The multi-physics field coupling model introduces the variable working condition electrochemical transfer equation, and the electrolysis efficiency robustness factor calculation error is ±3%. The intelligent vibration suppression system combines the wave and cyclone frequency characteristics, and adjusts the band gap center frequency to 1.8 octaves of the main frequency in real time, with a vibration transmission rate of 0.108. The fluctuation of hydrogen production efficiency under mixed sea conditions is controlled within ±8%, and the platform stability health is always greater than 85 points. The data transmission delay and key management mechanism are no longer described.

[0056] Example 5

[0057] In a high-latitude area of ​​Northern Europe with a water depth of 60 meters, an average annual temperature of –15°C to 5°C, and wave heights of 2-4 meters, a 90m x 50m diamond-shaped floating hydrogen production platform was deployed, integrating 12 sets of low-temperature-resistant electrolyzer modules. Conventional solutions have a low-temperature sensor failure rate exceeding 20%, and the model fails to account for the impact of temperature on electrolyte conductivity, resulting in an electrolysis efficiency prediction error exceeding 20%.

[0058] During the implementation of the present invention, the sensor array uses a heated lidar (working temperature -20°C to 60°C) and a low-temperature resistant microelectrode array (impedance temperature drift <0.5% / °C), with a data acquisition delay of 7.2ms. The multi-physics field model is embedded in the temperature-conductivity coupling equation, and the deviation between the measured and predicted values ​​of the electrolysis efficiency robustness factor is <5%. The acoustic metamaterial substrate achieves an adjustable band gap of 0.04-700Hz at low temperatures, the actuator response time is 38ms, and the vibration transmission rate is 0.115. The platform stability health maintains 88 points under extreme low temperature conditions, the electrolysis efficiency is improved by 18% compared with the traditional solution, and the sensor failure rate is <3%.

[0059] Example 6

[0060] In a deep-sea area of ​​the Indian Ocean, with water depths of 100 meters and an average of 5-6 tropical storms annually, a large 150m x 70m floating hydrogen production platform integrating 20 electrolyzer modules was deployed. Traditional solutions lack the ability to simulate extreme sea conditions, with model parameter update cycles exceeding 72 hours. Delayed response during historical storms has resulted in safety disconnection failures and equipment damage rates exceeding 40%.

[0061] During the implementation of the present invention, the twin autonomous evolution system generates a tropical storm multimodal data set (including storm conditions of level 10 and above) every 24 hours, and the physical constraint generation adversarial network is embedded in the turbulence equation to generate data with a difference of 0.015. The intelligent hierarchical self-healing mechanism completes the model parameter update 48 hours before the storm arrives. When the stability health drops to 72 points, the secondary response is triggered (lattice constant adjustment of 25%), and when it drops to 58 points, the tertiary response is activated (off-grid time <5 minutes). The measured vibration transmission rate during the storm was 0.12, the electrolysis efficiency maintenance rate was 83%, and the equipment damage rate was <5%. The key parameter monitoring and vibration suppression system will not be described in detail.

[0062] The specific embodiments described above are only used to specifically illustrate the spirit of the present invention, and the scope of protection of the present invention is not limited thereto. For those skilled in the art, it is of course possible to easily make other embodiments by changing, replacing or modifying the technical contents disclosed in this specification, and these other embodiments should all be included in the scope of protection of the present invention.

Claims

1. A real-time assessment method for sea state adaptability of a floating hydrogen production platform based on digital twins, characterized in that: The following steps are involved: Step 1: Build a high-resolution sea state perception system. This system uses a lidar wavefront scanner with a spatial resolution of no more than 0.5m and a millimeter-wave radar array with a sampling frequency of no less than 100Hz to collect omnidirectional wave energy spectra, three-dimensional current profiles, and turbulent wind field vector data in real time. Simultaneously deploy a salt spray corrosion-resistant microelectrode array and a high-frame-rate multispectral imaging system to monitor the overpotential distribution of the anode and cathode of the electrolytic cell, the density of catalyst active sites, and the dynamic parameters of bubble precipitation in real time. The end-to-end latency of data acquisition is controlled within 8ms. Step 2: Build a dynamic wavefront reconstruction engine, using an improved iterative inversion algorithm to analyze lidar point cloud data, fuse millimeter-wave radar echoes with microelectrode array electrochemical signals, and separate the wave's main frequency components using adaptive variational mode decomposition technology. The root mean square error of the reconstructed wavefront spatial distribution does not exceed 4%; Step 3: Construct a multi-physics field coupled digital twin core. Based on the transient large eddy simulation method and the electrochemical transfer equation, a cross-scale coupling solution framework is established: adaptive mesh refinement technology is used in the near field, with the mesh size not exceeding 1 / 60 of the characteristic wavelength λ; the discrete eddy method is used in the far field, with the mesh size not exceeding 1 / 12 of λ. A micro-nano bubble group evolution model is introduced to quantify the nonlinear effect of the gas-liquid interface phase change on the mass transfer efficiency; Step 4: Construct a multi-dimensional dynamic assessment matrix and define three core indicators: the sea state chaos index, the electrolysis efficiency robustness factor, and the platform stability health. The sea state chaos index characterizes the intensity of environmental disturbances through the entropy of the wave-current-wind field coupled energy spectrum. The electrolysis efficiency robustness factor reflects the ability to maintain hydrogen production efficiency under variable operating conditions. The platform stability health is quantified by the combined attitude angle deviation and vibration energy. Step 5: Based on the above evaluation system, an integrated space-ground communication architecture is deployed. Encrypted data streams are transmitted through dual redundant links between the 5G private network and the low-orbit satellite constellation. A dynamic rotation key management mechanism is used to ensure that the clock synchronization error between the digital twin and the physical platform does not exceed 5ms, and the key update cycle is compressed to within 3 minutes. Step 6: Establish an intelligent hierarchical self-healing mechanism. When the platform's stability health falls below 85 points, a first-level response is triggered, activating the local force adaptive enhancement mode. When it falls below 70 points, a second-level response is initiated, performing dynamic reconstruction of the metamaterial lattice topology. When it falls below 55 points, a third-level response is enforced, initiating the electrolyzer safe off-grid protocol and the hydrogen and oxygen staged discharge system. Step 7: Implement the twin autonomous evolution system, generate a multimodal dataset of extreme sea conditions every 36 hours through a physical constraint-generated adversarial network, drive the online evolution of the digital twin model parameters, and ensure that the statistical characteristics of the generated data do not differ from the measured data by more than 0.

02.

2. A real-time assessment method for sea state adaptability of a floating hydrogen production platform based on digital twins according to claim 1, characterized in that: The high frame rate multispectral imaging system described in step 1 uses 500fps high-speed video and narrow-band hydrogen and oxygen characteristic spectral filters to invert the local water saturation of the proton exchange membrane by extracting the bubble size distribution, with a measurement accuracy of 95%; the salt spray corrosion-resistant microelectrode array uses a nanoporous iridium-platinum composite electrode structure, covering a wide frequency band of 0Hz to 2MHz, and analyzing the catalyst activity attenuation gradient in real time.

3. The method for real-time assessment of sea state adaptability of a floating hydrogen production platform based on digital twin according to claim 1, characterized in that: The micro-nano bubble group evolution model described in step 3 includes a phase change driving force coefficient of 1.6 to 2.2 and a turbulent diffusion correction factor of 0.08 to 0.15, and describes the dynamic behavior of the bubble group through the coupling mechanism of vapor pressure gradient and vortex shedding.

4. A real-time assessment method for sea state adaptability of a floating hydrogen production platform based on digital twins according to claim 1, characterized in that: The dynamic reconstruction of the metamaterial lattice topology described in step 6 uses a shape memory alloy-piezoelectric ceramic composite drive unit to achieve a controllable deformation of the lattice constant by 10% to 30% within 150ms, so that the band gap center frequency accurately matches the 1.8 to 2.2 octaves of the wave main frequency.

5. The method for real-time assessment of sea state adaptability of a floating hydrogen production platform based on digital twin according to claim 1, characterized in that: The physical constraint generative adversarial network described in step 7 embeds the incompressible flow continuity equation, turbulent kinetic energy transport equation and electrochemical charge conservation law as strong constraints into the generator loss function to ensure that the generated data satisfies the multi-physics field coupling conservation law.

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