2085results about How to "High feasibility" patented technology

The invention provides a DCS system autonomous controllable upgrading and system fault prediction method and system, and relates to the technical field of fault prediction, and the method comprises the steps: obtaining historical operation data and real-time operation data of a DCS system, carrying out the preprocessing, and generating an autonomous controllable upgrading scheme through a deep reinforcement learning algorithm; the method comprises the following steps of: setting specified time for upgrading time, carrying out consistent backup on the state of the DCS, executing software updating, hardware configuration adjustment and system parameter optimization according to upgrading steps, analyzing indexes of the DCS in real time in the process of executing the autonomous controllable upgrading scheme, and recovering the DCS to the state before upgrading when an abnormal condition is detected. And verifying and optimizing the real-time fault prediction result based on a knowledge graph, and generating an explanatory report including a fault prediction and upgrade decision process according to the optimized fault prediction result and the autonomous controllable upgrade scheme.

The invention relates to the technical field of unmanned aerial vehicles, in particular to a flight mission planning and management system and method for cooperation of multiple unmanned aerial vehicles, and the method comprises the steps: decomposing a flight region of an unmanned aerial vehicle based on a flight mission of the unmanned aerial vehicle, and dividing the flight region; path planning is carried out in the flight area of the unmanned aerial vehicle, global flight path planning is carried out by adopting a genetic algorithm, and local flight path planning is carried out by adopting an A * algorithm after the global path planning; an obstacle avoidance strategy of the unmanned aerial vehicle in the flight process is constructed, and after the obstacle avoidance strategy is triggered, local flight path planning is carried out again; according to unmanned aerial vehicle flight task constraints, a priority judgment criterion of multiple unmanned aerial vehicle tasks is formulated, and unmanned aerial vehicle resources are allocated and dispatched. The intelligent level of unmanned aerial vehicle task planning can be remarkably improved, the adaptability to complex environments is enhanced, flight safety and efficient task execution are ensured, and a landing technical support is provided for actual application of the unmanned aerial vehicle.

The invention relates to the technical field of space positioning and path planning, in particular to a three-dimensional space positioning and path planning method for an unmanned aerial vehicle tower. The method comprises the following steps of performing accurate longitude and latitude height data acquisition based on a laser range finder to generate accurate longitude and latitude height data; obtaining tower equipment parameters; performing inspection point three-dimensional coordinate calculation according to the tower equipment parameters and the tower three-dimensional coordinate system to generate inspection point three-dimensional coordinate data; cruise point comprehensive constraint range data are obtained according to the unmanned aerial vehicle flight association data and the polling area terrain data, and cruise point comprehensive constraint range data are generated; performing cruise node three-dimensional coordinate design on the three-dimensional coordinate data of the inspection point according to the cruise point comprehensive constraint range data to generate cruise point three-dimensional coordinate data; and performing optimized cruise path planning processing according to the cruise point three-dimensional coordinate data to generate optimized cruise path data. According to the invention, more accurate unmanned aerial vehicle tower space positioning and path planning are realized.

The invention discloses a network threat deduction system and method based on Transform and a graph attention network model. The system mainly comprises four modules including a threat intelligence extraction module, a network threat entity construction module, a network threat deduction module and a deduction result application module. The method comprises the following steps: preprocessing and mining network security threat intelligence data by utilizing a graph attention network (GAT) model, constructing a complete network threat intelligence knowledge graph based on a data association relationship, and determining a vulnerability utilization weight in the graph; modeling is carried out on a reasoned path sequence based on a Transform model, a next reasoning sequence is predicted in a generative mode, and rapid and efficient network threat intelligence reasoning is achieved. According to the method, the complexity of attack deduction calculation is reduced, the deduction efficiency is improved, and security risk investigation and early warning can be carried out for a large-scale network environment.

The invention discloses a robust model prediction control method for mechanical arm trajectory tracking control, and relates to the field of multi-degree-of-freedom mechanical arm trajectory tracking control. According to the method, disturbance and parameter perturbation of a mechanical arm system are converted into lumped disturbance, a mechanical arm system error model is established, and feedback linearization is conducted on an error system based on an inverse dynamics method; based on a mechanical arm system error model, a nominal system model prediction controller is designed, a terminal area, a terminal control law and corresponding terminal cost are designed, and the feasibility of rolling interval optimization in each time step is guaranteed. According to the method, the uncertainty and disturbance of the mechanical arm system can be processed, it is guaranteed that system constraints are met, and high-precision trajectory tracking control and input torque optimization are achieved.

The invention relates to the technical field of artificial intelligence, in particular to a charging pile construction planning method and system based on artificial intelligence. The method comprises the following steps: acquiring existing power infrastructure data and multi-source heterogeneous data, wherein the multi-source heterogeneous data comprises traffic data, geographic data, vehicle data and charging behavior data; performing time sequence feature extraction on the multi-source heterogeneous data, and performing cross-time scale fusion on different data source features by using a preset hierarchical attention network model to obtain factor weight data; and constructing a long-term charging demand prediction model through a sequence-to-sequence model according to the factor weight data and the multi-source heterogeneous data. According to the site selection method based on the risk minimum set coverage problem, initial site selection scheme data is generated by combining multi-objective optimization of the coverage rate, the service radius and the accessibility, and more scientific charging pile layout is achieved.

The invention relates to the technical field of valve internal leakage identification, aims to solve the problem of low leakage rate prediction precision in valve internal leakage acoustic emission detection, and discloses a nuclear power valve internal leakage detection method based on acoustic emission signal time-frequency characteristics. Extracting the characteristics of the time domain, the frequency domain and the time-frequency domain of the leakage signal, analyzing the linear relation between the characteristics and the leakage rate of the valve, and predicting the leakage rate and the leakage grade. According to the invention, remote online detection can be carried out on the internal leakage state of the valve, meanwhile, the internal leakage rate of the valve is predicted, the safety of maintenance personnel is guaranteed, the scheme feasibility is high, the measurement is accurate, the applicability is high, the improvement of automation and intelligence levels is facilitated, and good practicability and safety benefits are achieved.

The invention relates to the technical field of circuit board line planning, in particular to an automatic design arrangement and path planning method and system for a double-sided board and multi-layer board printed circuit. The method comprises the following steps: acquiring input parameters of a circuit board, and analyzing to generate an initial structure of a wiring grid diagram; abstracting a wiring problem into a graph model, and extracting a wiring topological structure and density distribution characteristics; a deep reinforcement learning algorithm is adopted to optimize and generate a wiring path, and factors such as a wiring direction, layer selection and path length are considered at the same time; detecting, adjusting and optimizing wiring design rule conflicts on the basis of generating the wiring path; a comprehensive evaluation system of a wiring path planning scheme is established, indexes such as wiring efficiency, density and interlayer balance are considered, preset quality requirements are met through iterative optimization, and an optimized wiring path is output. According to the method, the wiring strategy can be adaptively learned and improved, and the reliability, efficiency and quality of wiring planning are improved.

The invention relates to a transmission and storage multi-stage collaborative planning method considering power transmission network structure optimization, belongs to the technical field of power system planning, and solves the problem that an existing planning scheme is not high in feasibility and reliability. The method comprises the following steps: predicting a wind-light output sequence and a load sequence of each time period in a planning period and putting the sequences into a data set; a clustering algorithm is used for clustering the data set to obtain a plurality of operation scenes, and the occurrence probability of each operation scene is calculated; constructing a first target function and a first constraint condition for minimizing the sum of the total input and storage investment construction cost and the total annual operation cost as an upper layer model; constructing a second objective function and a second constraint condition for minimizing the total annual operation cost according to the wind and light output sequence, the load sequence and the occurrence probability of each operation scene, and taking the second objective function and the second constraint condition as a lower-layer model; the upper-layer model and the lower-layer model are combined into a transmission and storage double-layer model; and iteratively solving the transmission and storage double-layer model to obtain a transmission and storage multi-stage collaborative planning scheme. The feasibility and reliability of the planning scheme are improved.

The invention discloses a single-channel wallboard damage positioning method based on a Lamb wave coding metamaterial interface. The method comprises the following steps: constructing a prior database for wallboard damage detection; the prior database stores an arrangement form of a damage monitoring area on the wallboard, arrangement parameters of a coding unit, Lamb wave parameters of an excitation signal applied during damage detection, an echo signal of the wallboard in a healthy state and a neural network model used for identifying a damage direction; for the wallboard to be subjected to damage positioning, arranging a coding unit and an exciter according to the information in the prior database, applying an excitation signal, and then collecting an echo signal; a polar angle region corresponding to the damage is obtained based on a neural network model, and orientation identification of the damage is achieved; the flight time of Lamb waves is obtained based on signal processing, so that the distance from the damaged part to the center of the damage monitoring area is determined, and the damage distance is determined; and finally, wallboard damage positioning under single-channel data acquisition is realized.

The invention provides an optical imaging lens, the optical imaging lens has eight lenses with focal power, and the optical imaging lens comprises a lens group, a spacing element group and a lens barrel group, the effective focal length f7 of the seventh lens and the interval EP67 between the sixth spacing element and the seventh spacing element in the direction of the optical axis of the optical imaging lens meet the following condition: f7 / EP67 is more than or equal to-8.25 and less than or equal to-6.82; the curvature radius R15 of the object side face of the eighth lens and the inner diameter d7m of the image side face of the seventh spacing element meet the condition that R15 / d7m is larger than or equal to 1.31 and smaller than or equal to 2.28. The multi-group optical imaging lens solves the problems that in the prior art, the rear end forming yield of the multi-group optical imaging lens is low, and stray light is serious.

The invention discloses a control method of a mechanical arm, the mechanical arm and a computer readable storage medium. The method comprises the steps of receiving a task instruction and an environment image; wherein the environment image has depth information; inputting the task instruction and the environment image into a large language model, so that the large language model outputs natural language instructions corresponding to the sub-tasks in sequence; wherein the large language model does not have code generation capability; wherein each subtask is predicted when the execution of the previous subtask is completed; and the natural language instructions are sequentially input into the mechanical arm control model according to the sequence, so that the mechanical arm control model controls the mechanical arm to execute corresponding actions based on the natural language instructions until all the subtasks are completed. By means of the mode, the problem that in the related technology, understanding of action semantics is insufficient can be solved.

The invention discloses a carbon-coated sodium ferrous sulfate phosphate positive electrode material as well as a preparation method and application thereof. The carbon-coated sodium ferrous sulfate phosphate positive electrode material is square flaky particles formed by coating sodium ferrous sulfate phosphate with a conductive carbon material and irregular aggregates of the square flaky particles. The molecular formula of the sodium ferrous sulfate phosphate is Na (6-2x + y) Fex( SO4) (3-y) (PO4) y, x is more than 0 and less than 3, and y is more than 0 and less than or equal to 0.5. The invention also discloses a preparation method and application of the carbon-coated sodium ferrous sulfate phosphate positive electrode material. The positive electrode material has the advantages of phosphate and sulfate positive electrode materials, the voltage platform is high, the conductivity is excellent, the air stability is good, and the assembled battery has excellent chemical sodium storage performance, high discharge specific capacity, highly reversible charge-discharge reaction and good cycle performance. The method is simple in process, high in feasibility, low in raw material cost and easy to realize industrial production through a solution system.

The invention discloses a coal power multi-path transformation and new energy combination decision-making method under low-carbon transformation. The method comprises the following steps: firstly, constructing a system comprising first-level effect indexes such as environmental influence, economic benefit, energy safety and technical innovation and corresponding second-level indexes; then, alternative schemes of various coal power transformation technology and new energy project type combinations are generated; then quantitatively evaluating the effect index of each scheme, and calculating a comprehensive utility value by using multi-criterion decision analysis; identifying potential risk factors, and performing uncertainty analysis through Monte Carlo simulation; and finally, according to the low-carbon transformation target and policy evaluation scheme conformity, selecting a scheme which most conforms to the policy target, and continuously monitoring and adjusting. The coal-electricity multi-path transformation and new energy combination decision-making method under low-carbon transformation is beneficial to promoting energy low-carbon transformation, optimizing resource allocation, improving economic benefits, promoting technical innovation, enhancing risk management capability and ensuring that a project is consistent with policy orientation.

The invention discloses a hydraulic mass concrete mix proportion intelligent optimization design method and system, and the method comprises the following steps: S1, inputting actually needed concrete indexes into a pre-trained and optimized intelligent hybrid prediction model, the concrete indexes at least comprising indexes related to strength and durability; s2, outputting an optimal concrete mix proportion through the intelligent mixing prediction model; the intelligent hybrid prediction model is an index feature weight determined according to the feature difference of concrete indexes, and is a high-generalization concrete macroscopic performance intelligent hybrid prediction model which is pre-constructed by fusing a plurality of neural network learning algorithm models in a weighting mode. The intelligent design of the concrete mix proportion can be rapidly and efficiently completed, and the scientificity and feasibility of the hydraulic mass concrete mix proportion design are improved.

The invention discloses an underwater target identification method for an underwater intelligent robot, which comprises the following steps: firstly, enhancing the definition and color restoration effect of an underwater image through image enhancement processing, and then utilizing an underwater target identification network model which is designed in a targeted manner and is improved based on a feature fusion attention network framework to identify the underwater target. A new defogging target detection model is obtained, a clear fog-free image is output in an end-to-end mode, and recognition of an underwater target is achieved; according to the method, a good foundation is laid for the underwater intelligent robot to carry out underwater tasks, and an underwater target recognition network model improved based on a feature fusion attention network framework is deployed in a detection module of the underwater intelligent robot, so that the feasibility of deploying an underwater target recognition algorithm in mobile terminals such as the underwater intelligent robot is improved; the accuracy and real-time performance of underwater target recognition in an underwater intelligent robot are improved, and the universality and practicability of an underwater target recognition algorithm based on a neural network in mobile terminal equipment are improved.

The invention discloses an abnormal battery cell identification method, computer equipment and a computer readable storage medium, and belongs to the technical field of power batteries, the identification method comprises the following steps: obtaining voltage data of a plurality of battery cells, and calculating a voltage drop of each battery cell under a standing condition based on the voltage data; for each battery cell, polymerizing the voltage drops under the plurality of standing working conditions in a first preset time period to obtain a polymerization result; and identifying an abnormal battery cell from the plurality of battery cells based on the aggregation result of each battery cell. The abnormal battery cell data is identified by using the outlier degree of the voltage drop of the battery cells in the battery pack under the standing working condition, the data validity is good, the identification result accuracy is high, and the use safety of the battery pack is ensured.

According to the energy storage coupling heat pump steam generation method and system, the mode that the heat pump device and the energy storage device cooperatively operate is adopted, and efficient and economical steam supply is achieved. The method comprises the steps that high-temperature water is prepared and stored in the off-peak electricity period through the heat pump device, and the high-temperature water is further heated through the energy storage device to generate superheated steam for a user to use. The energy storage device comprises a plurality of energy storage modules, and a heat exchange pipeline of the energy storage device can be switched between a parallel connection mode and a series connection mode through switching, so that deep heat release and flexible regulation and control are achieved. According to the method, the energy storage capacity and heat release power of the energy storage module are dynamically adjusted, enthalpy increment distribution of the heat pump and the energy storage device is optimized in combination with load prediction, and diversified steam requirements are met. And meanwhile, preheating or dynamic supplement is conducted on the energy storage module through the heat pump device, waste heat recovery is achieved, and the energy efficiency is improved. According to the method, the operation cost is remarkably reduced, the capacity of the system for adapting to load fluctuation is enhanced, and the method is suitable for industrial steam use scenes and has the advantages of being efficient, stable and flexible.

The invention provides a process window optimization method and device, a medium, a program product and a terminal, and solves the problems of low light intensity contrast ratio, limited process window and high finished product defect rate of weak point and dead pixel areas through an objective function optimization and numerical programming solution method. And establishing a reasonable optimization model by taking the sum of squares of light intensity logarithmic slopes of weak and dead pixel areas as an optimization target and combining an edge section moving range, an edge position error and mutual influence factors. And meanwhile, a plurality of matrix methods such as a sparse matrix and a dense matrix are introduced, so that the optimization efficiency and precision are improved, the accurate optimization of the mask pattern is realized, the process window is expanded, the defect rate is reduced, the process stability and adaptability are enhanced, and the production efficiency and the product quality are remarkably improved.

The invention belongs to but is not limited to the technical field of seabed monitoring, and particularly relates to a strain test method and system for subsurface buoy shell strength, and the method comprises the steps: S1, selecting points on the surface of a shell, and pasting strain gauges; s2, putting into a sealed kettle, and injecting water and pressurizing; s3, testing the strain condition of the shell by using a strain tester; and S4, the pressure tolerance degree of the shell is analyzed through calculation. The buoyancy provided by the floating body shell and the overall weight of the subsurface buoy are calculated in detail, and the needed ballast balance weight is accurately measured and calculated. Buoyancy and gravity balance is verified through dynamic simulation, it is ensured that the subsurface buoy can stably suspend or settle in water, and the design feasibility and the actual application effect are improved.

The invention discloses a flood season ship scheduling optimization method and system based on channel-ship lock coordination, and belongs to the technical field of water transportation traffic intelligent management, and the method comprises the steps: obtaining ship information, ship lock attribute information and flood season channel navigation requirement information of a water transportation junction; taking minimization of the total waiting time of the ship in the anchorage ground as an optimization target, constructing a ship scheduling optimization model, and establishing constraint conditions satisfied by ship lockage scheduling in the flood season; solving the ship scheduling optimization model based on a dynamic multi-population particle swarm optimization algorithm of recombination learning and mixed mutation to obtain an optimized flood season ship scheduling scheme; estimating the carbon emission of the ship, and verifying the low carbon and sustainability of the ship scheduling scheme in the flood season. According to the method, the ship off-anchor time and channel-ship lock coordination decision problem can be solved, the defect of shortage of a flood season scheduling method is overcome, and an effective reference is provided for reducing the ship navigation risk and improving the ship scheduling efficiency.

The invention provides an intelligent planning and budget evaluation method for high-standard farmland construction in hilly and mountainous areas. The method comprises the following steps: collecting current live data of a to-be-planned area; establishing an evaluation model of each planning index for predicting and evaluating each planning index value after different planning schemes are implemented, integrating the values into a multi-objective optimization algorithm, generating a plurality of different planning schemes based on live data, and finding an optimal planning scheme through iteration; values of decision variables are extracted from the optimal planning scheme, layer parameters are adjusted, and optimized planning maps are obtained and fused to obtain a final planning map; and generating an image set according to the final planning image, providing data for a metering center, and generating a budget file according to the data of the metering center and the budget template. According to the method, scientific, reasonable, efficient and accurate planning of the high-standard farmland in the hilly and mountainous areas is realized through the evaluation model and the multi-objective optimization algorithm, and meanwhile, budget management and resource allocation of the farmland construction project are performed in combination with budget evaluation.

The invention belongs to the field of battery testing, and particularly relates to a method for judging SEI film performance difference, battery formation and aging time and a lithium ion battery. The judgment method comprises the following steps of: testing the Rct resistance value of the battery and judging the voltage drop by using an EIS; the larger the Rct resistance value and the larger the voltage drop of the EIS test are, the poorer the performance of the SEI film is; the smaller the Rct resistance value and the smaller the voltage drop are, the better the SEI film performance is. The method is high in accuracy and feasibility, the difference of different formation processes and the shortest time of the aging process are effectively judged while the performance and quality of the battery are guaranteed, the production efficiency of the battery is improved, and the production cost of the battery is reduced.

The invention provides a stratosphere aircraft cross-day and cross-night task trajectory planning method and system in a dynamic wind field environment. The method comprises the steps that a task target and task constraints are acquired; acquiring external wind field information; constructing a motion model and a cost function of the stratosphere aircraft in the dynamic wind field; and outputting the lowest feasibility requirement of the cross-day and cross-night task under the dynamic wind field condition and the optimal trajectory when the task is completed by using a level set method in combination with particle swarm optimization. The method has the advantages that a combination framework of the level set algorithm and the particle swarm algorithm is innovatively provided, the problem that the level set algorithm has strong dependence on initial conditions is solved, meanwhile, the search space dimension is reduced, and the probability that the algorithm falls into a local optimal solution is reduced; by flexibly designing a fitness function, conditions such as speed constraint, energy consumption constraint and task feasibility of a stratosphere aircraft cross-day and cross-night arrival or residence task can be comprehensively considered, and the globality and constraint compatibility of trajectory optimization are realized.

The invention discloses a geothermal hot spring pool thermovolt power generation and water temperature regulation and control combined system which comprises a hot spring pool and a thermovolt power generation device. A thermal insulation wall is arranged in the hot spring pool, the hot spring pool is divided into a hot spring power generation battery and a hot spring recuperating pool through the thermal insulation wall, and the thermovolt power generation device is arranged in the hot spring power generation battery; a geothermal water inlet is formed in the hot spring generating battery, and high-temperature geothermal water enters the hot spring generating battery through the geothermal water inlet; a temperature control valve system is arranged in the hot spring recuperation pool and used for controlling the temperature of hot water entering the hot spring recuperation pool. The pulsating heat pipe and the thermovolt power generation technology are creatively integrated, natural hot spring heat energy is fully utilized, temperature difference energy between hot spring water and cold water is utilized to the maximum extent before the temperature is reduced to the comfortable temperature of a human body, and the pulsating heat pipe is utilized to effectively increase the heat exchange area and heat extraction capacity; meanwhile, the thermovolt power generation chip is adopted to directly convert hot spring heat energy into electric energy, and the dual functions of hot spring water temperature adjustment and geothermal power generation utilization are achieved.

The invention discloses a combustion chamber wall surface pit array structure design method and a combustion chamber. The method comprises the following steps: extracting a three-dimensional fluid model and carrying out bench test; establishing and verifying an in-cylinder combustion and emission simulation model; performing temperature field bench test on the cylinder cover, the piston and the cylinder sleeve; establishing and verifying a heat transfer simulation model; establishing a heat engine coupling simulation model; parameterization design is conducted on the pit array structures on the piston, the cylinder sleeve and the cylinder cover, a collaborative optimization mathematical model of pit array structure design is established, an optimal solution set is obtained, and typical solutions are selected; key parts in the typical solution are machined, an installation test is carried out, and the optimal pit array structure design scheme is obtained through the test. According to the pit array structure obtained through the collaborative optimization design method, the weight of components can be reduced, a turbulent layer can be formed on the near wall face of the combustion chamber to promote oil-gas mixing, then nitric oxide and particulate matter are reduced, and the combustion performance of an engine is improved.

The invention discloses an intelligent welding process evaluation optimization system based on an artificial intelligence big language model, and aims to improve the screening and optimization efficiency of a welding process evaluation report. According to the system, a natural language processing technology is used for analyzing welding requirements input by a user, relevant parameters are automatically extracted from a welding process evaluation report database, and evaluation reports are intelligently sorted and screened through a multi-dimensional data analysis module. The system generates optimized welding process suggestions according to multiple factors such as welding materials, process parameters and structural complexity. Meanwhile, the system has a self-adaptive learning function, process optimization adjustment can be carried out based on historical data and simulation results, and continuous improvement of the recommended process is ensured. The system can also be integrated with welding simulation tools (such as ANSYS and SYSWELD), the feasibility of a recommended process is verified, and the system is suitable for welding process selection and optimization of key structures such as pressure containers and pipelines in complex welding projects. According to the method, the efficiency, accuracy and reliability of welding process evaluation are remarkably improved, and the method has wide industrial application prospects.

The invention relates to the technical field of target detection, and particularly provides a semi-supervised learning-based target detection method, system and device and a storage medium, and the method comprises the steps: obtaining a data set which comprises a marked image and an unmarked image; generating a pseudo label for the unmarked image based on the marked image by using a dense detector; dividing the pseudo labels into reliable labels and soft labels according to the scores of the pseudo labels by using a pseudo label distributor; the pseudo label is updated to the data set, the updated data set is utilized to train a target detection model, and the target detection model identifies a target object in the sample image after training; the soft label is set to only participate in the preset partial loss calculation in the training process so as to reduce the training error caused by the soft label. According to the invention, an efficient semi-supervised learning target detection framework is constructed, and the accuracy of a target detection model is improved.

The invention relates to the field of vacuum coating, in particular to a crystal hot-fix rhinestone vacuum coating device and a crystal hot-fix rhinestone vacuum coating process. The invention aims to solve the technical problem that the coating quality is reduced in the next coating process due to the fact that original coating materials are easy to accumulate and remain on the surface and in the heating container in the long-term high-temperature state and coating process of the heating container. In order to solve the technical problem, the vacuum coating device for the crystal ironed diamonds comprises a main box body, vacuum equipment is arranged at one end in the main box body, the vacuum equipment comprises a tank body, a plating material evaporation device is arranged in the tank body, the plating material evaporation device comprises a fixing column, the bottom of the fixing column is fixedly connected with the tank body, and the bottom of the fixing column is fixedly connected with the tank body. Threads are arranged outside the lower ends of the fixing columns. The evaporation disc can be replaced through the coating material evaporation device, and the replaced evaporation disc is cleaned, so that the phenomenon that the previous coating raw materials are easy to remain and accumulate around the evaporation disc in the long-term coating process is avoided.

The invention relates to the technical field of hydrogen storage performance calculation and evaluation, and discloses a method and a system for calculating and evaluating the hydrogen storage performance of a solid hydrogen storage material. Analyzing and designing the mechanical property, electron distribution, heat-conducting property, heat stability and the like of the material; the hydrogen adsorption performance of the newly designed hydrogen storage material is calculated by calculating the adsorption state and adsorption energy of hydrogen molecules on the hydrogen storage material and the hydrogen adsorption capacity of the material under different pressures and temperatures; and drawing a hydrogen adsorption dynamic curve of the solid hydrogen storage material so as to calculate and evaluate the hydrogen storage dynamic performance of the material. The system comprises a performance analysis module, a performance calculation module and a performance evaluation module. The research and development efficiency and hydrogen storage performance of the solid hydrogen storage material can be comprehensively improved in theory and practical application. Each step provides important theoretical support and data basis for solving technical challenges in different aspects.