79 results about "Arctic" patented technology

The invention provides a similarity identification method for independent floating ice in an arctic sea ice marginal area and a related device, and relates to the field of meteorology. The method comprises the following steps: the electronic equipment acquires a first image and a second image which are sequentially shot for a target area; identifying a first independent floating ice in the first image; identifying at least one second independent floating ice in the second image; and determining a target floating ice most similar to the first independent floating ice from the at least one second independent floating ice according to the Hauschoff distance between the first independent floating ice and each second independent floating ice. Therefore, compared with a traditional algorithm which is easily influenced by shape change and position drift, the method has the advantages that the characteristic that the farthest point distance between the two sets can be effectively measured by using the Hauschoff distance is utilized, so that the similarity between the floating ice can be evaluated more accurately.

The invention discloses an ice trapping risk early warning method and system for independent navigation ships in an ice region of the arctic pole. The method comprises the following steps: collecting multi-source monitoring data of the independent navigation ships in the ice region; performing standardization processing on the collected monitoring data to generate a standardized data set including key risk factors and corresponding states thereof; constructing a risk early warning model based on the fault tree structure; determining an implementation rule of the risk early warning model; determining a state corresponding to each intermediate event according to the implementation rule and the standardized data set, and determining an ice trapping early warning level of the current ship in combination with a set early warning evaluation standard; the occurrence probability of each state of the basic event is determined, and the ship ice trapping probability of each state level is calculated by combining the implementation rule and the risk early warning model; and finally generating an evaluation report. Based on the evaluation report, safety early warning information is generated, and the ship bridge is notified; model parameters are optimized through a Bayesian network and a cumulative reward mechanism, so that the ice trapping risk is accurately and efficiently predicted.

The invention provides an arctic navigation channel ship navigation risk dynamic assessment method based on a dynamic Bayesian network, and belongs to the technical field of ship navigation safety. The arctic navigation channel ship navigation risk factors are identified from three aspects of environment, people and ship; establishing an arctic navigation channel ship navigation risk grade standard; constructing a static Bayesian network graph model of the ship navigation risk of the arctic navigation channel; determining parameters of a static Bayesian network model, and constructing a dynamic Bayesian network of the ship navigation risk of the arctic navigation channel; dynamically evaluating the ship navigation risk of the arctic navigation channel based on a dynamic Bayesian network; according to the method, environment, ship and human factors are considered, years of marine meteorological reanalysis data and expert knowledge are combined, updating can be carried out according to past, current and future conditions, and the risk of ice trapping and ship-ice collision of the arctic waterway is dynamically evaluated.

The invention discloses a north pole sea ice concentration prediction method based on Swin Transform, and belongs to the technical field of remote sensing data analysis. According to the method, the land mask image is generated to shield the land area, the spatial-temporal feature processing is fused, and the Swin Transform network structure is utilized to reduce the model calculation amount and enhance the perception ability of the model to the spatial-temporal features, so that the model has relatively high robustness. According to the invention, through analyzing the temporal and spatial change rule of sea ice coverage, accurate prediction and monitoring of the sea ice concentration in a period of time in the future are realized, and a reliable decision basis is provided for the fields of shipping safety, resource development, ecological environment protection, marine resource management and the like of the arctic sea area.

The invention discloses an arctic sea area climate state data set construction method, device and equipment, and belongs to the technical field of sea area data analysis, and the method comprises the steps: obtaining original observation data of a plurality of data sources of an arctic sea area, and carrying out the duplicate removal of the original observation data according to a preset rule, and obtaining first effective data; performing standardization preprocessing on the first effective data, and performing first quality control based on high-latitude temperature-salinity characteristics to obtain second effective data; interpolating the second effective data to a standard layer, and performing second quality control on the interpolated data based on high-latitude thermohaline characteristics to obtain third effective data; and based on the third effective data, space-time standardization grid interpolation is carried out, and an arctic sea area climate state data set is constructed by adopting a cross objective analysis method. According to the invention, a set of accurate, comprehensive and unified grid climate state data set for the north sea area is established.

The invention belongs to the technical field of prediction of the thickness of sea ice in the arctic region, and particularly relates to an intelligent prediction method for the thickness of sea ice in a polar region based on multi-layer stacking space-time Transform. The method comprises the following steps: step 1, based on polar region sea ice thickness reanalysis data information of a target sea area, extracting a feature matrix in ocean SIT reanalysis data and constructing a space-time sequence forecast supervision data set; 2, preprocessing data of a background field and a target field; 3, an HSS-Transform model is constructed, and the HSS-Transform model is constructed; 4, inputting the sea ice thickness background field space-time sequence into an HSS-Transform model to obtain a sea ice thickness prediction space-time sequence in the next 15 days; step 5, carrying out reverse normalization operation on the obtained prediction space-time sequence, and restoring the land point; according to the method, the spatial-temporal characteristics of the sea ice thickness data can be extracted and processed at the same time on multiple time scales and spatial scales, the extension period intelligent prediction of the polar region sea ice thickness spatial-temporal sequence is realized, and the prediction level of the sea ice thickness is remarkably improved.

The invention discloses a fire coal SO2 gas concentration prediction method based on combination of photoacoustic spectroscopy and a Stacking model. The fire coal SO2 gas concentration prediction method comprises the following steps: acquiring a spectral data set of SO2 gas through an experiment; dividing the collected spectral data set into a training set and a test set according to a ratio of 8: 2; carrying out wavelet transform denoising on the divided spectral data, and then carrying out SPA wavelength screening on the denoised data; establishing a Stacking model of the SO2 gas concentration of the photoacoustic spectrum; optimizing the Stacking model by using an improved Arctic Sea-Sharrow algorithm (IPAO); and inputting spectral data to test the model. According to the fire coal SO2 gas detection method based on the SPAO optimized Stacking model, the photoacoustic spectrometry technology is utilized, the Stacking model constructed through the method has the advantage of efficiently processing complex data, and accurate prediction of the concentration of fire coal SO2 gas is achieved; therefore, the method is very suitable for the demand of accurately predicting the SO2 gas concentration in industrial production field and environment detection.

The invention discloses a generative arctic waterway daily navigation risk prediction method and device and a medium, and the method comprises the steps: constructing a historical daily navigation risk data set of an arctic waterway according to historical daily environment data and navigation ship parameters; according to the historical daily navigation risk data set, constructing a generative daily navigation risk monthly covariance forecasting model; constructing a monthly navigation risk forecasting model according to the historical daily navigation risk data set and the navigation ship parameters; according to the generative daily navigation risk monthly covariance forecasting model and the timestamp information, generating a daily navigation risk monthly covariance in a corresponding month; and generating a daily navigation risk value of the navigation risk in the prediction time window through the monthly navigation risk prediction model and the daily navigation risk monthly covariance. The method can achieve the prediction of the long-term North Navigation risk, reduces the cost of North Navigation risk prediction, and can be widely used in the technical field of ship navigation safety.

The invention relates to a north pole region under-ice acoustic guidance control method for an AUV (Autonomous Underwater Vehicle), which is used for realizing autonomous recovery of an autonomous underwater robot after the end of under-ice detection. The method includes the following steps that firstly, after an AUV ends a mission, fault information of a submersible is obtained, and small floating weights are rejected in a time-sharing mode; 2, acquiring the position of a set beacon which changes at any time in an ultra-short array coordinate system through an ultra-short positioning array carried by the AUV, and calculating the longitude and latitude of the beacon; and 3, the AUV takes the beacon longitude and latitude position as a navigation target position, and finally, the navigation target position is dynamically positioned at the beacon position within an allowable range, and waits for a remote control instruction or carries out time-sharing load rejection on the large floating weight. The method is convenient to transplant and can be suitable for various underwater robots.

The embodiment of the invention discloses an arctic navigation channel seaworthiness evaluation method based on a knowledge graph, and relates to the technical field of knowledge graphs, and the method comprises the steps: obtaining to-be-analyzed data of an arctic region; extracting a plurality of triads through the constructed arctic navigation channel evaluation index knowledge graph and arctic navigation channel seaworthiness knowledge graph, determining the associated triads based on the position coordinates of each pixel unit on the remote sensing image, and generating a graph chain corresponding to the pixel units; and determining a seaworthiness evaluation value of each graph chain based on the constructed knowledge graph, determining a seaworthiness evaluation result of each pixel unit, and outputting a seaworthiness evaluation result distribution map of the north pole region. According to the method, the seaworthiness of each graph chain can be quantified through the knowledge graph to obtain the seaworthiness evaluation value, so that the seaworthiness evaluation result of each pixel unit can be quickly obtained, and the seaworthiness evaluation result distribution diagram of the north pole region is efficiently output.

1. Name of the designed product: ceiling lamp (North Pole Glacier series C185). 2. Use of the designed product: for lighting. 3. Design points of the designed product: in shape. 4. Picture or photo best indicating the design points: perspective view.

The invention discloses a sea ice coverage on-satellite detection and updating method and device for a synthetic aperture radar (SAR) image, and belongs to the technical field of satellite remote sensing marine monitoring, and the method comprises the steps: carrying out the preprocessing of a dual-polarization SAR image on the ground, training a super-resolution model, and carrying out the knowledge distillation and lightweight processing, and deploying the super-resolution model to a spaceborne computer. After a satellite obtains a real-time SAR image in an on-orbit mode, preprocessing can be completed on the satellite, and a sea ice coverage binary image is directly output. In order to adapt to different satellite wave band data, the ground only needs to finely adjust part of parameters of the model and upload and update the parameters in a differential packet form, so that the whole packet is prevented from being retransmitted. According to the method, a closed loop of ground pre-training-on-satellite reasoning-differential updating is realized, the method has the characteristics of fast response, light weight, easy expansion and the like, and the sailing safety of the arctic navigation channel can be remarkably improved.

The invention discloses a bulb sound source release device applied to an arctic ice region, and relates to the technical field of underwater acoustic engineering. Aiming at low temperature, no power supply, deepwater and ice hole operation limitation in the arctic ice region, the device is driven by mechanical impact, and accurate breaking of the underwater vacuum bulb can be realized without a power supply. The device comprises a vacuum bulb cavity, a guide steel wire rope, a drop hammer, a firing pin assembly and an ice hole clamping frame. The vacuum bulb cavity comprises a pressure protection balance cavity, a pressure guide hole and a controllable knob; the drop hammer is released to fall freely along the steel wire rope, the firing pin is driven to break a vacuum bulb glass shell placed in an environment with the water depth larger than 50 m, implosion is triggered, and broadband sound waves are radiated. The device adopts a pressure protection balance cavity to counteract pre-compression of water pressure on the bulb, and the breaking reliability is ensured. The device is free of power supply, simple in structure, easy to arrange, large in action depth, good in generated sound source effect, and suitable for acoustic experiments and research in the Arctic ice region and the like.

The invention discloses an arctic region soil freeze-thaw state inversion method in combination with observation data of a Chinese Tianmu-1 satellite-borne BDS-R and an SMOS radiometer, namely a method for inversing the arctic region soil freeze-thaw state based on an Attention mechanism and a Multiscale CNN-BiLSTM hybrid model of ResNet, the method is based on the Attention mechanism and the Multiscale CNN-BiLSTM hybrid model of ResNet, the model is mainly composed of three core modules, and the core modules are connected with the Attention mechanism and the Multiscale CNN-BiLSTM hybrid model of ResNet. The hybrid model comprises a ResNet and CNN-based multi-scale feature extraction module, a BiLSTM network-based feature relationship reasoning module and an Attention mechanism-based multi-feature parameter fused full-connection network module, and the hybrid model can significantly improve F / T inversion precision and is helpful to provide data supplement for the arctic region in a severe environment.

The invention relates to a ship-shore communication selection model establishment method and system and a ship-shore communication method. Three main factors which influence polar region communication are selected based on a Lasso linear regression method, wherein the three main factors include the communication range, the communication cost and the communication reliability; according to the communication range, the communication cost and the communication reliability of each communication device, summarizing to form a communication device evaluation table; analyzing a communication equipment evaluation table, comprehensively comparing communication characteristics of the communication equipment evaluation table, and proposing a priority criterion of equipment selection according to the current situation of communication in the north pole region; and finally, establishing a ship-shore communication equipment selection model suitable for the north pole region based on expert experience. According to the scheme, the problem of reasonably selecting communication systems in high-latitude and alpine regions can be solved, the success rate and reliability of communication system connection are improved to a certain extent, a convenient selection scheme is provided for a user, and the life and property safety of employees is guaranteed.

The application discloses a kind of based on multi-scale sea level pressure field Arctic cyclone automatic detection and continuous tracking method, device and storage medium, belong to polar meteorology and climate data processing technical field.The method includes the following steps: (1) obtaining sea level pressure field data and pre-processing;(2) construct local pressure anomaly field;(3) identify candidate low pressure center;(4) calculate sea level pressure field curvature;(5) calculate local depth and background gradient parameter;(6) carry out multi-center cyclone identification and repeated center combination;(7) establish trajectory matching cost matrix;(8) cyclone continuous trajectory matching is realized using hungarian algorithm;(9) trajectory conflict optimization is carried out;(10) implement trajectory quality control.The application can improve the accuracy of arctic cyclone identification and trajectory continuity, reduce the false detection and false association problems caused by random noise, multi-center system and trajectory intersection.

The application discloses a collaborative scheduling method based on an arctic sea parrot optimization algorithm and peak-valley time-of-use electricity price, belongs to the technical field of micro-grid intelligent scheduling and renewable energy management, and comprises the following steps: step S1, a micro-grid system model is established; step S2, operation constraint conditions are constructed, including the power balance and the upper and lower limit constraints of the power of each component of the micro-grid and the state constraints of the storage battery which need to be satisfied by the wind turbine, the photovoltaic, the gas turbine, the fuel cell, the storage battery and the power exchange with the power grid in the micro-grid; step S3, an objective optimization function of operation cost and pollutant emission is constructed; and step S4, the optimal scheduling scheme is output by applying the objective optimization function. The collaborative scheduling method based on the arctic sea parrot optimization algorithm and the peak-valley time-of-use electricity price can significantly improve the optimization precision and convergence efficiency of the system, meanwhile, the high reliability and robustness of the scheduling process are ensured, and finally, the intelligent collaborative scheduling of the micro-grid energy is realized.

Synthetic aperture radar (SAR) is a type of imaging technology that can be used for a variety of applications such as Earth observation, mapping, object tracking, change detection (e.g., in arctic ice), natural catastrophe monitoring, and many other applications. A high-altitude, unmanned aircraft, for performing synthetic-aperture radar (SAR) imaging, includes a fuselage, wings connected to the fuselage and for providing lift to the aircraft, one or more electrically-powered propellers for providing thrust to the aircraft, a SAR payload for performing SAR imaging of the surface of the Earth when the aircraft is in flight, solar cells for generating electricity to drive the one or more electrically-powered propellers and to operate the SAR payload, and one or more batteries for storing electrical energy generated by the solar cells.

1. The name of the design product: balm round can (Arctic Ocean). 2. The use of the design product: for placing in the car, removing odor, for freshening the air, long-lasting fragrance. 3. The design points of the design product: in the combination of shape, pattern and color. 4. The picture or photo that best indicates the design points: perspective view. 5. The design claimed contains color.

Synthetic aperture radar (SAR) is a type of imaging technology that can be used for a wide range of applications, including Earth observation, mapping, object tracking, change detection (e.g., Arctic ice), natural disaster monitoring, and many other uses. A high-altitude unmanned aerial vehicle for performing synthetic aperture radar (SAR) imaging comprises a fuselage, wings attached to the fuselage to provide lift to the aircraft, one or more electric propellers to provide thrust to the aircraft, a SAR payload for SAR imaging the Earth's surface as the aircraft flies, solar cells to generate power to drive one or more electric propellers and operate the SAR payload, and one or more batteries to store the electrical energy generated by the solar cells.

The present invention relates to a sea ice mapping method, which belongs to the field of Arctic sea ice mapping and monitoring technology, and solves the problem of low sea ice detection accuracy in existing ice-water mixed areas and ice or water areas covered by clouds. The method is applied to the Arctic, and includes the following steps: obtaining multiple MODIS L1B image data collected daily in the study area and preprocessing; classifying each preprocessed image data to obtain a classification result matrix for each image data; the classification categories include sea ice, water and cloud; each pixel in the classification result matrix stores the category label corresponding to the pixel; obtaining the total number of non-cloud categories and the mode of non-cloud categories of pixels corresponding to the same position in multiple classification result matrices, and obtaining a daily water and ice distribution map based on the total number of non-cloud categories and the mode of non-cloud categories; fusing the daily water and ice distribution maps to obtain a daily synthetic ice map.

This invention provides a green and low-carbon intelligent planning method and system for Arctic shipping routes. The method includes: constructing a gridded environmental model of the Arctic sea area; establishing a mapping relationship between ship navigation resistance and propulsion power based on a semi-empirical ice resistance formula to construct an ice resistance-power-carbon emission coupled model, and determining the carbon emissions per unit distance; constructing a multi-objective reward function, including a carbon emission penalty term based on the estimated carbon emissions and a time penalty term based on navigation time; and performing path training and strategy optimization based on the gridded environmental model and the multi-objective reward function to output the optimal route that satisfies the multi-objective constraints. This invention, by constructing an ice resistance-power-carbon emission coupled model and introducing an equivalent turning time mechanism, achieves synergistic optimization of navigation efficiency and carbon emission control in complex ice-covered environments, improving the engineering feasibility and green and low-carbon level of planned routes, and is suitable for intelligent decision-making in Arctic mixed ice and water navigation scenarios.

The application provides an Arctic sea wave prediction method based on automatic fusion of sea ice density, and belongs to the technical field of weather prediction. The wind field data automatic acquisition system is established to ensure the continuity of the wind field driving data. The sea ice wave interaction optimization model is applied to dynamically adjust the IC4M2 sea ice wave parameterization scheme. The open boundary line is set in the high latitude sea area of the North Atlantic, and the radiation boundary condition algorithm is combined with the sponge layer absorption technology to process the boundary wave propagation. The WAVEWATCH III sea wave numerical model is started, the fourth-order precision finite difference discrete format is combined with the adaptive artificial viscosity control algorithm to calculate the Arctic sea wave field, and the sea wave prediction product business processing system is established, so that the technical problem of low accuracy of the Arctic sea wave prediction caused by the insufficient parameterization precision of the sea ice wave interaction is solved.

This application provides a method and apparatus for inverting the extent and type of Arctic sea ice. The method includes: acquiring a first identification model; the first identification model is a model established based on first observation data and the corresponding ice-water classification results; the first observation data is observation data collected by a satellite the previous day; acquiring second observation data; the second observation data is observation data collected by the satellite on the current day; and determining the ice-water classification results corresponding to the second observation data based on the first identification model and the second observation data. This method aims to improve the accuracy, timeliness, and efficiency of sea ice identification.

The present invention relates to a technology for liquefying natural gas, which is subsequently transported by rivers and oceans and ultimately regasified. Pretreated natural gas is compressed by a compressor 1, the heat of compression is removed in an air or water cooler 2, and multi-stage pre-cooling is subsequently performed by evaporating a heavy refrigerant in an evaporator 3. The light refrigerant vapor and its pre-evaporation cold are recovered in a shell-and-tube heat exchanger 7, where the pressure of the gas to be liquefied is reduced by a pressure reducer 10, unliquefied gas is separated, and liquefied natural gas is discharged. The heavy refrigerant obtained by evaporation is compressed by a compressor 4, condensed in an air or water cooler 5, and reused in the multi-stage pre-cooling of natural gas. A light refrigerant is compressed by at least two compressors 11, the heat of compression is removed in an air or water cooler 12, and then passes through continuous cooling by a low-pressure light refrigerant in a double-flow superheater 12 and an evaporating heavy refrigerant in an evaporator 3. The high-pressure light refrigerant is then split into two streams. The first stream is expanded through an isentropic process in an expander 14. The second stream passes through continuous cooling in a shell-and-tube heat exchanger 7, then expanded through an isenthalpic process in a throttle valve 15, and evaporated by subcooling natural gas in an evaporator 8. The streams are then mixed at equal pressure and used as a single stream of low-pressure light refrigerant to cool the second stream of light refrigerant before expansion and evaporation in the isenthalpic process with natural gas in the shell-and-tube heat exchanger 7, and to cool a single stream of high-pressure light refrigerant in a double-flow superheater 13. The present invention provides stronger cooling of the natural gas, reduces the amount of boil-off gas and the work required for its recompression and recycling, and provides a simpler hardware design for the heat exchanger.

1. Name of the designed product: down jacket (arctic region). 2. Use of the designed product: for wearing. 3. Design points of the designed product: combination of shape and pattern. 4. Picture or photo best indicating the design points: front view. 5. Omitted views: the bottom surface of the designed product is a part that is not easily seen or cannot be seen when in use, so the top view is omitted; the content of the view has been expressed in other submitted views, so the plan view is omitted.

1. Name of the design product: Beverage bottle (Arctic Ocean PET480). 2. Use of the design product: This design product is used for holding beverages. 3. Design key points of the design product: Lies in the shape. 4. Picture or photograph that best shows the design key points: Front view.

The invention provides a ship target fusion detection method in a polar region channel based on SAR and optical images, and belongs to the field of remote sensing image processing and target detection. In order to solve the problems of difficulty in moving target association and high sea ice false alarm rate in different-time-phase images of the arctic ice region, the technical scheme comprises the following steps: respectively carrying out target initial detection on SAR and optical images, and extracting features to remove sea ice false alarms; secondly, saliency detection is carried out on the image to extract a channel area, and target parameters such as the target main axis angle, the position and the intersection-to-union ratio are calculated; meanwhile, the motion state is judged according to the target parameter difference, and the maximum correlation area is determined by combining the maximum speed constraint; and finally, target matching is completed in the region, and decision-level fusion is carried out by adopting a D-S evidence theory. According to the method, accurate correlation and fusion detection of the SAR and the time-shifting ship target in the optical image are realized, background interference is effectively overcome by comprehensively utilizing bimodal information, and the method has important application value in the fields of polar region navigation safety monitoring and the like.

The application discloses a micro-grid scheduling optimization method and system based on a multi-target arctic sea parrot optimization algorithm, and the method comprises the following steps: establishing a multi-target optimization scheduling model of a micro-grid, wherein at least an operation and maintenance cost target function and an environmental protection cost target function are included in the multi-target optimization scheduling model; solving the multi-target optimization scheduling model by using a multi-strategy fusion multi-target arctic sea parrot optimization algorithm to obtain a Pareto optimal solution set; and determining an optimal output strategy of each distributed power generation unit in the micro-grid according to the Pareto optimal solution set. The algorithm has space exploration ability in the early stage and optimization precision in the later stage, and the optimization effect of micro-grid scheduling is improved.

The embodiment of the present application discloses a method for evaluating the navigability of an Arctic route based on a knowledge graph, and relates to the field of knowledge graph technology. The method includes: obtaining data to be analyzed in the Arctic region; extracting multiple triples through a constructed knowledge graph of Arctic route evaluation indicators and an Arctic route navigability knowledge graph, determining associated triples based on the position coordinates of each pixel unit on the remote sensing image, and generating a graph chain corresponding to the pixel unit; determining the navigability evaluation value of each graph chain based on the constructed knowledge graph, determining the navigability evaluation result of each pixel unit, and outputting a distribution map of the navigability evaluation results of the Arctic region. The present application can quantify the navigability of each graph chain through the knowledge graph, obtain an navigability evaluation value, and then quickly obtain the navigability evaluation result of each pixel unit, and efficiently output a distribution map of the navigability evaluation results of the Arctic region.