8609 results about "Electrolysis" patented technology

The invention relates to the technical field of equipment monitoring, in particular to an equipment corrosion evaluation and life prediction method and application, and the method comprises the following steps: deploying a sensor network in an easily-corroded area of coal chemical equipment, and collecting multi-dimensional data; carrying out abnormal value elimination, data compression, time synchronization and space-time alignment preprocessing on the collected multi-source data; image features are extracted through a convolutional neural network, processed data are analyzed through an LSTM-attention model, and a fuzzy comprehensive evaluation matrix is established to evaluate the corrosion level; a physical model based on the Faraday electrolysis law and a data driving model based on the Transform network are constructed, and the residual life is predicted through Bayesian network fusion output and Monte Carlo simulation. Through fusion of multi-source data and an intelligent algorithm, accurate evaluation of the corrosion state of the equipment and accurate prediction of the residual life are realized, and safe and efficient operation of the coal chemical equipment is guaranteed.

The invention relates to the technical field of process parameter design, and discloses a silver electrolysis process parameter design method and system based on multi-objective optimization. The method comprises the following steps: performing differential time sequence parameter decomposition on operation data of the silver electrolysis process to obtain a sensitive parameter set and a reference parameter set; performing reweighted periodic feature extraction on the sensitive parameter set and the reference parameter set, and establishing a dynamic mathematical model of the silver electrolysis process parameters; based on the dynamic mathematical model of the silver electrolysis process parameters, physical and chemical process numerical simulation is conducted through COMSOLMultiphysics software, and a response curved surface model is obtained; and according to the response curved surface model, a process parameter combination evaluation value sequence is generated, silver electrolysis process parameter multi-objective optimization is carried out based on the process parameter combination evaluation value sequence, and a silver electrolysis process parameter optimization scheme is output. According to the application, multi-physical-field collaborative simulation of electrode reaction, ion transmission, heat conduction and the like is realized, and performance index responses under different process parameters are accurately predicted.

The invention discloses an extrusion production process for an aluminum alloy multi-cavity profile. The extrusion production process comprises the following steps that S1, raw materials are prepared; s2, designing and manufacturing a mold; s3, pretreatment before extrusion; s4, extrusion forming; s5, cooling treatment; s6, straightening and finishing; s7, aging treatment; and S8, detecting and packaging. According to the invention, the friction is further reduced by adopting a special high-temperature lubricant and an ultrasonic vibration device in the pre-extrusion pretreatment, the precise control is realized by arranging real-time monitoring and feedback systems such as a laser range finder and an infrared thermometer in the extrusion forming process, and the cooling treatment is realized by automatically adjusting parameters by adding a corrosion inhibitor and arranging a sensor, so that the production efficiency is improved. The cooling quality of the profile is ensured; laser scanning and electrolytic polishing technologies are adopted for straightening and finishing, the straightening precision and the surface quality are improved, a circulating hot air system and a segmented aging mode are adopted for aging treatment, and the aging effect is improved.

The invention provides a flexible preparation system and method for sustainable aviation fuel, and the system comprises a green power supply module which is used for outputting fluctuating green electric energy; the process execution device is connected with the green power supply module and comprises five process modules, namely an air carbon capture module, a co-electrolysis module, a Fischer-Tropsch synthesis module, a hydrogen production module and a hydrogenation refining module; the data acquisition module is used for acquiring the temperature, the pressure, the liquid level, the raw material input flow and / or the product output flow of each process module in the process execution device; and the decision control module is used for predicting the future power supply condition of the green electricity based on the historical weather data of the green electricity location, adjusting the distribution of the power in each process module according to the future power supply condition, and adjusting the temperature, pressure and / or raw material input flow in each process module. According to the invention, the cost, the reliability, the operation and maintenance performance, the product quality and the green power utilization rate can be substantially improved at the same time, and the flexible and stable operation of the system under the green power condition is realized.

The invention relates to the technical field of path planning, and discloses a path planning method and system of an AGV (Automatic Guided Vehicle) for a silver electrolysis process workshop. The method comprises the following steps: carrying out environment characteristic acquisition and electronic map construction on a silver electrolysis process workshop to obtain a silver electrolysis process workshop electronic map; calculating an initial optimal path of the AGV from the current position to the target workstation; detecting the actual driving resistance in the execution process of the initial optimal path to obtain a path correction parameter; performing local adjustment to obtain an energy-saving safe path; and in the process that the AGV executes the energy-saving safe path, the front moving obstacle and the electrolyte leakage area are monitored in real time, and a temporary detour path is generated. According to the application, the path planning is more suitable for the actual environment characteristics of the silver electrolysis workshop, the emergency situation of the silver electrolysis workshop can be timely handled, the equipment safety and the production continuity are guaranteed, the no-load rate of the AGV is reduced, and the overall logistics efficiency of the silver electrolysis workshop is improved.

The invention discloses a preparation process of a modified porous carbon material catalyst. The preparation process comprises the following steps: (1) mixing and calcining a biomass precursor and a template agent to prepare graded porous carbon; (2) low-frequency plasma pretreatment and high-frequency plasma fluorination modification are adopted; (3) introducing the pulse plasma into a nitrogen doping site; (4) spraying ionic liquid and activating H2 plasma to form a B / F co-doped layer; and (5) loading alloy nanoparticles such as PtRu through pulse electrodeposition. According to the obtained catalyst, biomass derived porous carbon serves as a carrier, a fluorine / nitrogen co-doped active layer is constructed on the surface of the carrier through multi-frequency plasma synergistic modification and ionic liquid auxiliary modification, superfine precious metal nanoparticles are loaded, the hydrogen evolution overpotential of the catalyst is smaller than or equal to 28 mV under the current density of 10 mA / cm < 2 >, the activity attenuation is smaller than 5% after 1000 times of circulation, and the catalyst has a good catalytic activity. The water electrolysis hydrogen production device is suitable for a large-scale water electrolysis hydrogen production device.

The invention relates to the technical field of comprehensive application of renewable energy sources and hydrogen energy, in particular to a wind-solar-hydrogen multi-energy complementary intelligent scheduling platform. According to the technical scheme, the wind-light-hydrogen multi-energy complementary intelligent scheduling platform comprises a wind-light power generation unit which monitors wind power and photovoltaic power fluctuation in real time; the hybrid energy storage unit comprises a super capacitor and a flywheel for energy storage and respectively responds to millisecond-level and second-level power fluctuations; the hydrogen energy subsystem comprises an electrolytic hydrogen production device, a hydrogen storage tank and a fuel cell and responds to minute-level power scheduling; and the multi-time scale controller is configured to execute millisecond-level, second-level and minute-level cooperative control and dynamically match the wind-light fluctuation and the hydrogen energy response speed. According to the method, through multi-time scale dynamic cooperative control, the matching problem between the wind-solar power generation volatility and the hydrogen energy response lag is effectively solved, and seamless connection between second-level high-frequency fluctuation suppression and minute-level energy scheduling is achieved.

The invention discloses a photovoltaic hydrogen production power supply topological structure based on MPPT and a control method, and relates to the technical field of renewable energy electrolysis hydrogen production, and the photovoltaic hydrogen production power supply topological structure mainly comprises a photovoltaic power module, a direct current bus, a water electrolysis hydrogen production unit, an energy storage unit and a control unit. The photovoltaic power modules are connected in parallel to the direct current bus through the independent DC / DC converter, and are matched with the automatic identification and scheduling functions of the control unit, the system operation strategy is automatically adjusted when the modules are newly added or faults exit, and plug-and-play, fault isolation and power reconstruction of the photovoltaic power modules can be supported; the duty ratio change step length of the DC / DC converter is limited when the current rapidly fluctuates due to the change of the photovoltaic output power, the current change rate of the electrolytic cell stack is effectively controlled, the service life protection of the electrolytic cell can be considered, the high modular access capability is achieved, multi-source collaborative scheduling is supported, and bus voltage stabilization and system current sharing optimization can be achieved.

The invention discloses a fuel cell coupled flow battery energy supply system and an operation control method thereof. The energy supply system comprises a basic energy supply unit, an energy storage peak regulation unit, a renewable energy power generation unit, an electrolytic hydrogen production unit, a hydrogen storage unit, a first-stage waste heat recycling unit, a second-stage waste heat recycling unit and a heat storage unit. The basic energy supply unit is used for providing a basic power load of the target building group; the energy storage peak regulation unit is used for providing fluctuation power load of the target building group; the first-stage waste heat recycling unit receives first-stage waste heat generated by power generation of the fuel cell and is used for indoor heating or indoor refrigeration. And the second-stage waste heat recycling unit directly receives the first-stage waste heat or second-stage waste heat from the first-stage waste heat recycling unit and is used for preheating the electrolyzed water and / or the hydrogen storage unit. By arranging the first-stage waste heat recycling unit and the second-stage waste heat recycling unit, waste heat is utilized in a multi-stage mode according to requirements, and the waste heat utilization rate is high.

The invention discloses an electrochemical descaling process ion concentration dynamic balance control method and system, and relates to the field of water treatment of a circulating cooling water system.The method comprises the steps that a multi-parameter sensor is deployed to collect calcium and magnesium ion concentration, pH, conductivity, flow and other multi-dimensional data in real time, and an electrochemical deposition dynamic model is combined; dynamically evaluating the time sequence change trend of the ion concentration; according to the method, an ion concentration dynamic balance control algorithm is constructed, and the current density adjusting quantity is calculated by synthesizing ion concentration deviation and historical integral deviation, so that the target current density of the electrochemical reactor is adaptively adjusted, and the system is always maintained in a target concentration interval under different inlet water quality and load conditions; precise electrolysis control is achieved by periodically adjusting power output, and the descaling efficiency and energy consumption are effectively balanced. Therefore, the self-adaptive adjustment of the electrochemical descaling process is realized, and the stability and the self-adaptability of the descaling process are remarkably improved.

The embodiment of the invention relates to the technical field of new energy, and provides a multi-physics field coupling optimization method of a co-electrolysis system and a related product, and the method comprises the following steps: obtaining a coupling mathematical model and a fractal porous medium permeability model in the operation process of the co-electrolysis system; based on physical field parameters output by the electrochemical kinetics calculation model, the non-Darcy seepage simulation model and the thermal stress field calculation model, corrected control parameters of the co-electrolysis system are obtained; the optimized permeability is obtained by adjusting fractal parameters of the fractal porous medium permeability model; the optimized permeability is provided for a non-Darcy seepage simulation model to update flow field pressure distribution; based on the physical field parameters updated in real time by the electrochemical kinetics calculation model, the non-Darcy seepage simulation model and the thermal stress field calculation model, performing multi-objective optimization on the coupling mathematical model to obtain an optimized coupling mathematical model. According to the embodiment of the invention, multi-physical field coupling of the co-electrolysis system can be optimized, and the method is suitable for complex working condition regulation.

The invention discloses an intelligent gas valve remote control and early warning system based on the Internet of Things, and relates to the technical field of valve monitoring. The valve processing module is used for preparing an intelligent valve through 316N stainless steel subjected to grain boundary processing, and a sealing ring, a fiber grating array and a QCM sensor are arranged on the intelligent valve; and the intelligent control module is used for acquiring the strain size of the fiber bragg grating and vulcanized film data through the fiber bragg grating array and the QCM sensor, and determining the lubricant release amount and the current regulation density. Strain of the valve rod is monitored in real time through the fiber bragg grating array, segmented friction force is obtained, and a nano lubricant is automatically released according to the friction force, so that the friction coefficient can be reduced, flexible opening and closing of the valve are ensured, and meanwhile, the surface density change of a vulcanized film is detected through the QCM sensor; and the valve rod is automatically triggered to rotate for self-cleaning or electrolytic polishing treatment, so that corrosion development can be effectively inhibited.

The invention discloses a water electrolysis hydrogen production intelligent control system and method based on artificial intelligence. The system and method are suitable for a large-scale water electrolysis hydrogen production scene under the power supply condition of fluctuating renewable energy sources such as wind power and photovoltaic. The system comprises a data acquisition layer, an edge calculation layer, an intelligent control layer and an execution layer. Dynamic modeling of the running state of the hydrogen production system is achieved through multi-parameter real-time monitoring and feature extraction. The intelligent control layer fuses an LSTM prediction module and a reinforcement learning controller, the LSTM prediction module is used for predicting future renewable energy input and hydrogen demand trends, and the reinforcement learning controller calculates an optimal current density set value based on a prediction result so as to maximize hydrogen production efficiency per unit energy consumption. And meanwhile, a digital twinning technology and a safety protection mechanism are combined, thermoelectric dual regulation and control of the electrolysis process are achieved, and the control response speed and the system stability are improved. According to the invention, energy consumption can be effectively reduced, the service life of the stack is prolonged, and the operation efficiency and reliability of the hydrogen production system under complex load are improved.

Provided is a laminate capable of electrolyzing an oxygen compound gas represented by CO2 with high conversion efficiency and suppressing deterioration in electrolytic performance. In this laminate having a structure in which an electrolyte layer is sandwiched between an anode catalyst layer and a cathode catalyst layer, a perovskite oxide and CuFe2O4 are contained in the cathode catalyst layer, and the content of CuFe2O4 in the cathode catalyst layer is at least 10 mass%.

The invention provides a novel polynorbornene anion exchange ionomer containing a polar functional group as well as a preparation method and application of the novel polynorbornene anion exchange ionomer. The polynorbornene has excellent thermal stability and chemical stability. Meanwhile, the AEI main chain of the polynorbornene has no aryl group, so that the adsorption influence caused by the aryl group is avoided. The synthesized addition polynorbornene AEI in the form of quaternary ammonium salt can be dissolved in a low-boiling-point solvent, and it is ensured that a membrane electrode can be prepared through a solvent casting method. Besides the solubility of the AEI, the addition polynorbornene-based AEI in the form of quaternary ammonium salt is modified by utilizing a thiol-ene click reaction, an anion exchange ionomer containing a polar functional group can be prepared, the interaction between the AEI and an electrolytic catalyst is improved, the reaction is simple and easy to operate, the universality is high, and the method is suitable for industrial production. And the current density in the AEMWE system containing the AEI can be effectively improved.

The invention provides a fault map learning-based early abnormality diagnosis method and system for an anion exchange membrane electrolysis system, and relates to the technical field of fault diagnosis. The method comprises the following steps of: acquiring multi-working-condition operation measurement and constructing a time sequence characteristic fragment, establishing a fault map containing parts, working conditions and measurement nodes by combining a part relationship and working condition dependency, training and calibrating a map learning model on the fault map, and extracting a self-adaptive baseline; and projecting the feature fragments to a fault map, outputting multi-level risk indexes, generating a comprehensive risk score and an anomaly candidate set, and implementing multi-scale threshold judgment and stability test in combination with a baseline to form early warning and disposal suggestions. And performing further attribution analysis on the abnormal candidate set, identifying key components, and reinjecting maintenance feedback to update the atlas and the model to form a continuously optimized knowledge base. According to the method, causal correlation modeling and interpretable diagnosis are realized, and the accuracy and timeliness of early abnormality identification of the AEM electrolysis system are effectively improved.

The invention belongs to the technical field of electrochemistry, and discloses a multi-physical field coupling analysis method for a common electrolysis cell stack and a related device thereof, and the method comprises the following steps: fusing a velocity field, a potential field and a temperature field to obtain a physical field tensor; mapping the physical field tensor into an initial state of the Hamiltonian system, and obtaining a physical field state prediction value through prediction of a physical field prediction model; taking the statistical characteristics of the physical field state predicted value as macroscale parameters, and inputting a velocity field and the macroscale parameters in the physical field state predicted value into a graph attention network to obtain mesoscale parameters; carrying out sampling and expected value calculation on mesoscopic bubble transportation data to obtain microscopic scale parameters; and inputting the macroscopic, mesoscopic and microscopic scale parameters, the physical field state predicted values and the corresponding physical field measured values into the correction model to obtain correction values of the multiple physical fields, and correcting the physical field state predicted values through the correction values of the multiple physical fields. According to the invention, the accuracy of multi-physical field state prediction is improved.

The embodiment of the invention relates to the technical field of electrolytic copper foil testing, and particularly discloses a continuous testing method and system for warping of an electrolytic copper foil. The method comprises the following steps: periodically cutting an electrolytic copper foil sample; adjusting a test environment, and carrying out leveling positioning and reference calibration on the electrolytic copper foil sample; performing three-dimensional panoramic scanning and multi-point scanning supplement on the electrolytic copper foil sample; reconstructing a three-dimensional surface model, carrying out reference comparison, and calculating a plurality of warping key indexes; and performing qualification judgment and trend analysis on the plurality of warping key indexes, generating a warping test report, and performing feedback control of a continuous test. According to the method, the defect evolution rule is visually presented by automatically generating the three-dimensional surface diagram and the distribution curve visual report; the electroplating parameters are dynamically adjusted by triggering the process feedback control module, a test-analysis-regulation closed loop is formed, the warping degradation trend is inhibited from the source, and the product yield and the production continuity are improved.

The invention discloses a dynamic efficiency optimization management and control method for a wind-light hydrogen storage system, which comprises the following steps of: acquiring operating parameters of an electrolytic bath based on a water electrolysis hydrogen production simulation framework of an alkali liquor medium, and analyzing joint probability distribution and correlation coefficients of historical wind-light data through a wind-light photovoltaic synergistic effect model; constructing a system load accommodating setting model; when the frequency or voltage fluctuation of the power grid is detected, starting a quasi-synchronous electric element regulation and control framework PSEERA, and adjusting the output power through a droop control equation; the comprehensive performance indexes are optimized by adopting a Ling-tuned chaos infinitesimal search (SACMESA) algorithm, and main control factors are extracted through a multi-element optimization evolution (BKEAMOEA) algorithm analyzed according to key elements to carry out multi-objective optimization; implementing a scattered point type cooperative control strategy including bottom-layer equipment control, middle-layer energy management and upper-layer system scheduling, and realizing cross-level dynamic optimization; the peak regulation and frequency modulation capability, the safety and the stability of the power grid are remarkably improved.

The invention relates to the technical field of electrolytic hydrogen production, and discloses a PEM electrolytic cell energy-economy collaborative optimization method based on digital twinning, which comprises the following steps: S1, calibrating parameters of a membrane electrode mathematical model by using a standard test for a single cell of a PEM electrolytic cell, and establishing a high-precision physical simulation model; s2, constructing a high-precision digital twin system based on the high-precision physical simulation model; s3, inputting multi-dimensional data of electricity price fluctuation, hydrogen demand prediction and equipment state, and performing collaborative optimization analysis through an optimization decision algorithm; s4, forming a PEM electrolytic cell control optimization instruction; and S5, the physical entity PEM electrolytic bath executes the instruction. According to the method, the'electricity price-demand-equipment 'dynamic relation is planned as a whole from the global perspective, the process steps cover data-driven modeling, multi-target decision, digital twinning cooperation and closed-loop feedback, balance needs to be achieved among algorithm efficiency, model precision and engineering feasibility, and energy-economy-life multi-target cooperation is achieved.

The invention relates to the technical field of rare earth metal electrolysis cathode protection coatings, in particular to a high-temperature-corrosion-resistant yttrium-stabilized zirconia gradient coating on the surface of a tungsten cathode. A metallurgically bonded strong bonding bottom layer is constructed on a tungsten substrate through surface pretreatment and reactive sintering, then an atmosphere plasma technology is adopted to spray a creep-resistant gradient layer with continuous components to buffer thermal stress, and finally a sol-gel technology is utilized to construct an extremely compact corrosion-resistant surface layer in a superposition mode. The high-temperature-corrosion-resistant yttrium-stabilized zirconia gradient coating is constructed through a multi-scale and multi-mechanism synergistic effect, the problems that a tungsten cathode coating is insufficient in binding force and poor in thermal shock resistance are fundamentally solved, molten salt permeation can be blocked, and the service life of a tungsten cathode in a severe environment is remarkably prolonged.

The invention belongs to the technical field of high-energy-consumption industrial energy conservation and carbon reduction, and particularly relates to an electrolysis process waste heat gradient utilization and green electricity energy storage coupling system and a regulation and control method thereof. An electrolysis process waste heat gradient utilization and green electricity energy storage coupling system comprises a waste heat recovery module used for recovering and gradient utilization of electrolysis high-temperature and medium-low-temperature waste heat for power generation or heat supply; the green electricity direct supply module comprises a photovoltaic unit, a hybrid energy storage unit and an electricity-heat conversion unit and is used for preferential direct supply, fluctuation absorption and storage of green electricity; and the multi-energy coupling regulation and control module is in communication connection with each module and a power grid, and dynamically optimizes and coordinates energy distribution among waste heat power, green power, energy storage and the power grid based on a preset algorithm.

The invention discloses deep eutectic gel polymer electrolyte as well as preparation and application thereof, belongs to the technical field of battery electrolyte, solves the problems of low thermal stability, low ionic conductivity and poor mechanical property in the prior art, and comprises a bimetallic salt-eutectic solvent and a polymer chain which are dynamically crosslinked and constructed, the bimetallic salt-eutectic solvent comprises lithium ions, heterogeneous metal salt and Lewis base, and the polymer chain is formed by free radical polymerization, atom transfer radical polymerization (ATRP) or reversible addition-fragmentation chain transfer radical polymerization (RAFT). According to the invention, the deep eutectic solvent is introduced as a reaction solution, so that the organic gel monomer is subjected to photopolymerization or thermal polymerization in the solution, the elongation at break can reach more than 500%, the organic gel has excellent mechanical stretchability, a polymer network is formed by utilizing a long-chain molecular formula of a polymer chain, the deep eutectic solution is wrapped in the polymer network, and the organic gel has excellent thermal stability; and the good ionic conductivity of the electrolyte is ensured.

The invention belongs to the technical field of ocean engineering and water electrolysis hydrogen production. In order to solve the problems that a traditional water cooling system is large in size and low in heat dissipation efficiency, a multi-scale thermal sensing network is deployed to collect data; establishing a multi-phase-change cross-scale heat transfer model; constructing a two-stage gradient composite cooling module; constructing and optimizing a cooling decision algorithm; designing a cooperative control loop; deep reinforcement learning control is implemented; creating a functional surface; and constructing a dynamic optimization system. The characteristics of part of the steps are limited, efficient heat management can be achieved, and stable operation of the floating type offshore hydrogen production platform cooling system is guaranteed.

A green ammonia production hydrogen load prediction method based on sparse attention variational Bayes comprises the following steps: acquiring historical data of a green ammonia electrolysis hydrogen production industry through an acquisition sensor, and dividing the historical data into a training set, a verification set and a test set; performing standardization processing on the training set, and constructing an SVAE soft measurement training model; determining a final objective function suitable for SVAE; and performing real-time online prediction on the output target variable by using the current input characteristic variable by adopting the trained SVAE. The SVAE combines CNNs, PSSAM and a cross attention mechanism, and captures a long-term dependency relationship and a complex mutual relationship in industrial data. An optimized objective function is formulated in combination with variational reasoning and a Monte Carlo method and is used for offline training. The SVAE has remarkable advantages in the process of accurately predicting the hydrogen flow and optimizing the production process of the green ammonia, the production efficiency is improved, and the energy consumption is reduced.

The invention relates to an electrolytic hydrogen production and fuel cell waste heat gradient utilization system and method based on an organic Rankine cycle, and belongs to the field of new energy. The system comprises a wind power generation unit, a photovoltaic power generation unit, a storage battery energy storage system, an electrolytic hydrogen production device, a hydrogen storage system, a fuel cell power generation unit, a waste heat utilization unit and an organic Rankine cycle device, and can be used for realizing multi-element consumption and gradient utilization of renewable energy sources. The method specifically comprises the following steps: establishing equipment models in a system, wherein an electrolytic bath considers five states of shutdown, cold start, standby, hot start and standby; on the basis of a mixed integer linear programming method, operation constraints of all equipment, renewable energy output prediction and electricity, heat and hydrogen load requirements are integrated, an optimization scheduling model meeting the electricity, heat and hydrogen load requirements and economical efficiency of the system is constructed, output of all the equipment is coordinated, and finally the optimization targets of maximizing the economical efficiency of the system and meeting the electricity, heat and hydrogen load requirements of the system are achieved.

The invention discloses an ultraviolet laser enhanced plasma electrolytic polishing method for an aluminum-based silicon carbide composite material, which is characterized in that the conductive performance of a reinforced phase SiC material is locally improved by utilizing the synergistic effect of the local thermal effect and the photoelectric effect of ultraviolet laser, and meanwhile, uniform-speed polishing of a metal aluminum matrix and the reinforced phase SiC material is achieved by virtue of plasma discharge. And the machining efficiency is obviously improved, a machined surface with higher quality compared with traditional machining and single plasma electrolytic polishing is obtained, and further application and popularization of the aluminum-based silicon carbide composite material are facilitated.

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.

The present invention provides a catalyst-layer-equipped electrolyte membrane and an application of the same, said catalyst-layer-equipped electrolyte membrane comprising: an anode catalyst layer containing an ionomer and an anode catalyst component that is composed of iridium-containing manganese dioxide, the molar ratio of iridium to manganese in the anode catalyst component being 0.011-0.182, and the logarithm log(amount of ionomer / amount of anode catalyst component) of the ratio of the amount of the ionomer to the amount of the anode catalyst component being −1.40 to −0.46; a proton exchange membrane; and a cathode catalyst layer.

An alternating current (AC) impedance spectroscopy method includes providing an AC impedance spectroscopy ripple from power electronics into an electrochemical device, and absorbing the ripple in the power electronics.