46 results about "The arctic" patented technology

The invention provides a north pole atmosphere coupling forecasting method capable of automatically fusing sea ice concentration and thickness, which belongs to the technical field of meteorology, and comprises the following steps: firstly, acquiring GFS background field data and correcting by applying an ice-sea heat exchange correction equation; and then sea ice concentration and thickness information is extracted, and physical consistency verification is carried out based on a thermodynamic equilibrium equation. Performing multi-element fusion through an Arctic ice sea assimilation model, calculating the sea ice surface temperature by applying a polar region sea ice heat flux equation, and establishing a sea ice concentration thickness boundary layer interaction equation set to describe the modulation effect of sea ice on a boundary layer; the method comprises the core steps of performing deep fusion on various sea ice features by applying a feature fusion model, adaptively adjusting the weight based on an ice-gas interface balance index, generating an optimized mode initial field and boundary conditions, and finally setting a parameter scheme to execute an integral program to obtain a forecasting result. The technical problem of low forecasting accuracy caused by insufficient physical consistency of sea ice information is solved.

The invention discloses an arctic channel route planning system and method based on a visual sea ice risk, and the system comprises a future sea ice data obtaining module which is used for obtaining the sea ice data of an arctic region in the future N days; the sea ice risk grade determination module is used for calculating to obtain a sea ice risk grade; the sea ice risk display module is used for displaying sea ice risk levels corresponding to different areas of the north pole; the route preliminary planning and drawing module is used for drawing an initial global route; and the route prediction display module is used for obtaining the risk condition of the initial global route in the cross-day period. Aiming at the complex ice condition environment of the ice area, the ship route design is carried out by considering the influence of sea ice on ship navigation, so that the whole ship route design process is visually displayed, the ship route can be flexibly adjusted, a more efficient, more economical and safer ship route is provided for ship navigation in the north pole, and the ship route design efficiency is improved. And the sailing safety and efficiency of the ship in the Arctic ice region are improved.

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 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 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 invention relates to a ship ice region navigation risk and toughness evaluation method. The method comprises the following steps: S1, obtaining a current sea ice environment analysis result; s2, based on historical accident data, identifying ship navigation accident scenes and risk factors in the Arctic ice region; s3, based on the sea ice environment analysis result and the identified risk factors, calculating a probability index and a consequence index of each accident scene occurring in ship navigation in the ice region to obtain a risk index; s4, acquiring current state data of the ship; and S5, obtaining a risk control scheme based on the current state data and the risk index, and carrying out toughness evaluation and sorting on the risk control scheme to obtain a toughness evaluation result. Compared with the prior art, the method has the advantages of improving the comprehensiveness and accuracy of ship ice region navigation risk management and the like.

The invention discloses an India Ocean dipole-based sea temperature prediction method and system, and the method comprises the steps: obtaining the monthly average prediction height of the sea surface of the India Ocean in the spring of a target year and the winter north pole sea ice observation data of the last year; inputting the monthly average prediction height of the sea surface of the India Ocean in the spring of the target year and the north pole sea ice observation data in the winter of the last year into a pre-trained India Ocean dipole prediction model to obtain an India Ocean dipole index of the target year; and determining the sea temperature of the India Ocean in the target year according to the dipole index of the India Ocean in the target year. According to the method, the India Ocean dipole index of the target year is predicted based on the monthly average prediction height of the India Ocean sea surface in the spring of the target year and the north pole sea ice observation data in the winter of the last year, and the accurate India Ocean sea temperature of the target year is obtained based on the accurately predicted India Ocean dipole index.

To provide a device and method that can provide an environment in which participants in a "space" for thinking and discussing can consider things from a wide variety of perspectives. [Solution] According to this embodiment, the map classifies fields related to society in the first direction, classifies the level of each field in the second direction (social domain in the Arctic direction), and classifies words related to individuals in the third direction (personal domain in the Antarctic direction). Multiple nodes with semantic content are placed in the social domain and the personal domain according to the words (attribute information) at their placement location.

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 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.

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 present invention discloses a method, device and equipment for constructing a climate state data set in the Arctic sea area, and the technical field of sea area data analysis, including: obtaining original observation data from multiple data sources in the Arctic sea area, and removing duplicates from the original observation data according to preset rules to obtain first valid data; performing standardized preprocessing on the first valid data, and performing first quality control based on high-latitude temperature-salinity characteristics to obtain second valid data; interpolating the second valid data to a standard layer, and performing second quality control on the interpolated data based on high-latitude temperature-salinity characteristics to obtain third valid data; based on the third valid data, performing spatiotemporal standardized grid interpolation, and adopting a cross-objective analysis method to construct a climate state data set in the Arctic sea area. The present invention establishes an accurate, comprehensive and unified gridded climate state data set in the Arctic sea area.

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.

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.

The present invention discloses a method for predicting Arctic sea ice density based on deep learning, specifically, step 1: obtaining Arctic sea ice density data and ERA5 meteorological factor data; step 2: preprocessing the meteorological factor data; step 3: splicing the Arctic sea ice density data and meteorological factor data at the same time in the channel dimension to obtain multi-source fusion data; step 4: dividing the multi-source fusion data in step 3 into n groups according to time, and establishing a feature extraction network; the feature extraction network includes n feature extraction modules, step 5: inputting the nth group of multi-source fusion data into the nth feature extraction module of the feature extraction network, extracting the spatiotemporal features of the multi-source fusion data group, and step 6: inputting the output of the feature extraction network into the adaptive weight allocation network to obtain the sea ice density prediction value. The present invention solves the problem that the traditional time series prediction model focuses on the end, and effectively improves the accuracy of the prediction.

The invention provides a synthetic aperture radar-based one-dimensional sea wave spectrum inversion method for an arctic sea area. The method comprises the following steps: acquiring a Sentinel-1 dual-polarized SAR image, sea ice concentration data and a WAVEWATCH-III simulated one-dimensional sea wave spectrum of the arctic sea area; estimating sea ice concentrations from the SAR image by using a K-means clustering algorithm, grouping the sea ice concentrations, and adopting different hydrodynamic modulation transfer function parameters for different groups of sea ice concentrations and polarization modes; an XGBoost machine learning model is adopted, and an SAR one-dimensional sea wave spectrum inversion algorithm in the north pole sea area is established; and the accuracy of the SAR one-dimensional sea wave spectrum inversion algorithm in the arctic sea area is verified. According to the method, the problems that traditional one-dimensional sea wave spectrum inversion depends on an initial guess spectrum, and sea ice influences modeling are complex are solved, and high-precision one-dimensional sea wave spectrum inversion of the arctic sea ice coverage area is achieved.

The application discloses an Arctic shipping route navigation safety evaluation method and system based on multi-source data fusion and ship adaptability, and relates to the cross technical field of marine navigation safety guarantee, meteorological and hydrological data analysis and intelligent navigation. The method comprises the following steps: collecting multi-source data of the Arctic shipping route, dynamically fusing weights in combination with real-time reliability calculation of the data source after preprocessing and space-time alignment, completing confidence dynamic weighted fusion to obtain comprehensive environmental data; constructing a coupled physical stress model based on the data and inherent parameters of the target ship, introducing ice type and sea current factors to quantify real-time navigation risk, and generating a voyage full-cycle dynamic risk corridor; planning a route based on the risk corridor by using a hybrid heuristic algorithm, and combining a multi-index judgment mechanism with a self-defined weight to realize navigation safety grade judgment and global optimal route output. The application improves evaluation accuracy and ship adaptability, prolongs the dynamic prediction period, realizes global optimal route planning, and has strong operability in decision support.

The invention discloses an improved ant colony algorithm-based arctic channel path planning method, which belongs to the technical field of navigation, and comprises the following steps of: (1) calculating a navigable area of an icebreaker in an arctic region by combining ice condition data, meteorological data and the level of the icebreaker; (2) initializing pheromone concentration for effective nodes in the navigable area; (3) finding out a next-step transferable node set naavi of the kth ant starting from the current node i at the moment t, and calculating the probability of the ant starting from the node i to the node j in the naavi according to the pheromone concentration; completing one iteration; and (4) updating the pheromone concentration on the path from the node i to the node j, and entering the next iteration until a termination condition is met. According to the north pole channel path planning method based on the improved ant colony algorithm, the initial pheromone concentration is optimized while the characteristics of the ant colony algorithm are reserved, the early blind search is remarkably reduced, the calculation amount is reduced, and the search efficiency is improved.

The present disclosure relates to methods, apparatuses, and systems for unmanned underwater vehicles capable of operation in the Arctic region. An example unmanned underwater vehicle includes: a hull; one or more guide rails extending from the hull and attached to the hull by one or more legs; a vertically-deployed mast, wherein the vertically-deployed mast is configured to penetrate through an ice sheet; and a communications antenna, wherein the communications antenna is deployed with the vertically-deployed mast and enables communication above the ice sheet. The dorsally-located guide rails of an example define an extended position and a retracted position, wherein the guide rails disposed in the extended position are disposed further from the hull than the guide rails disposed in the retracted position. Embodiments described herein include systems employing air-deployable buoys, water-deployed buoys and small UUVs, and ice-penetrating buoys to support communications in the Arctic region.

To provide a device and method that can provide an environment in which participants in a "space" for thinking and discussing can consider things from a wide variety of perspectives. [Solution] According to this embodiment, the map classifies fields related to society in the first direction, classifies the level of each field in the second direction (social domain in the Arctic direction), and classifies words related to individuals in the third direction (personal domain in the Antarctic direction). Multiple nodes with semantic content are placed in the social domain and the personal domain according to the words (attribute information) at their placement location.

The invention discloses a two-parameter approximate representation and rapid inversion method of a north pole double-track sound velocity profile, and relates to marine environment parameter inversion. Comprising a two-parameter approximate representation method of a dual-track sound velocity profile, a surface refraction type normal wave cross-type dispersion curve extraction method, a horizontal invariant dual-track sound velocity profile rapid inversion method and a horizontal variation dual-track sound velocity profile rapid inversion method. According to the overall change characteristics of the north pole dual-track sound velocity profile, linear approximation is carried out on the sound velocity profile, and the dual-track sound velocity profile is represented through two parameters influenced by width and strength. Because a sound signal frequency dispersion structure crossing phenomenon is caused by the north deep sea surface double-channel sound velocity profile, and the stronger the double-channel intensity is, the more serious the crossing phenomenon is, the north deep sea double-channel sound velocity profile can be inverted by comparing simulated and actually measured sound field cross-type frequency dispersion curves and combining a double-parameter representation method of the double-channel sound velocity profile. The method can be realized by using a single hydrophone.

This invention provides a tolerance-based distance estimation method and system for dual-channel acoustic imaging in Arctic ice regions based on normal mode-constrained modes. The method includes: using a normal mode model to simulate and predict the frequency domain sound pressure, phase velocity, group velocity, and mode covariance matrix of the experimental sea area in the Arctic ice region; using Fast Fourier Transform (FFT) to transform the time-domain signal received by the vertical array in the ice region into frequency-domain data; obtaining the sound velocity and depth corresponding to the upper boundary, channel axis, and lower boundary of the Beaufort waveguide based on the dual-channel sound velocity profile of the experimental sea area; obtaining the order index of the Beaufort waveguide modes based on the intersection of the phase velocity dispersion curve with the sound velocity at the upper boundary and channel axis of the Beaufort waveguide; performing mode separation using a matched filtering mode filtering method to extract the modes confined in the Beaufort waveguide; and constructing a tolerance-based distance estimation operator for ice and seabed based on the extracted modes in the Beaufort waveguide to achieve tolerance-based estimation of underwater target distances.

The application provides a sea ice extraction method based on multi-feature superpixel segmentation, comprising the following steps: step 1, obtaining a dual-polarization SAR image of a target sea area and performing image preprocessing to obtain a preprocessed image; step 2, extracting a backscattering coefficient feature, a normalized feature, a morphological feature set, an OTSU feature and a texture feature from the preprocessed image and fusing them to obtain a multi-dimensional data feature set; step 3, using an SNIC superpixel segmentation method to segment the multi-dimensional data feature set to obtain a superpixel block set; and step 4, inputting the superpixel block set into a supervised training machine learning classifier to classify sea water and sea ice to extract sea ice. The application can effectively improve the sea ice classification precision and robustness, can generate a sea ice distribution feature set with a spatial resolution of 40 meters, and can effectively support the monitoring of the interannual and intermonthly changes of the Arctic sea route sea ice.

To provide a device and method that can provide an environment in which participants in a "space" for thinking and discussing can consider things from a wide variety of perspectives. [Solution] According to this embodiment, the map classifies fields related to society in the first direction, classifies the level of each field in the second direction (social domain in the Arctic direction), and classifies words related to individuals in the third direction (personal domain in the Antarctic direction). Multiple nodes with semantic content are placed in the social domain and the personal domain according to the words (attribute information) at their placement location.

The invention discloses a method for diagnosing the abnormal sea temperature of the subsurface layer of the Eurasian basin of the Arctic Ocean caused by Arctic cyclones, and belongs to the technical field of sea temperature abnormity diagnosis. The method provides a set of systematic diagnosis steps: (1) acquiring air pressure data, and tracking a north cyclone path and intensity through a cyclone detection algorithm; (2) acquiring data of wind speed, sea ice concentration, seawater temperature and salinity during the passing period of the arctic cyclones; (3) considering the effect of sea ice, and calculating the influence depth of the north cyclone on the European Asia north ice ocean; (4) calculating the depth of the cold-salt spring layer of the European Arctic Ocean; (5) comparing the difference between the cyclone influence depth and the cold salt spring layer depth; and (6) when the arctic cyclone influence depth is greater than the cold salt spring layer depth, judging that the phenomenon of abnormal temperature rise of the subsurface seawater occurs. According to the method, the influence of unique ocean stratification and sea ice of the Eurasian basin of the Arctic Ocean is fully considered, a diagnosis method is provided for scientifically evaluating the response of the Eurasian basin of the Arctic Ocean to the Arctic cyclones, and the method has remarkable scientific value and practical application prospects.

The present invention provides an Arctic waterway fleet scheduling optimization method based on BeiDou III, comprising: designing an Arctic waterway multi-base station fleet information service framework based on BeiDou III, reshaping the information interaction process between ships and between ships and shores under BeiDou service; constructing an Arctic waterway fleet scheduling optimization model based on BeiDou III based on the designed Arctic waterway multi-base station fleet information service framework; and improving the differential evolution algorithm to solve the non-deterministic polynomial problem in the fleet scheduling process. The present invention designs a BeiDou-based multi-base station fleet information service framework to provide support for the dynamic scheduling of Arctic waterway fleets, solving the problem of difficulty in real-time information interaction on Arctic routes. With the support of the BeiDou multi-base station fleet information service framework, the information obtained by the framework is used to solve the dynamic scheduling optimization model of the Arctic waterway fleet. The model enables the fleet to quickly modify the freight scheduling plan after the navigation environment information is distorted, thereby reducing economic losses.

The application discloses an unmanned underwater ice-breaking vehicle, which comprises a vehicle body, a pop-up device, front and rear battery cabin devices, a folding wing device, a water tank device, an electronic cabin device, a motor device and a tail device; the water tank device, the pop-up device and the front and rear battery cabin devices are arranged at the middle part of the vehicle body, the pop-up device is arranged above the water tank device, the front and rear battery cabin devices are arranged in front of and behind the water tank device; the folding wing device is arranged at the two side parts of the vehicle body, the electronic cabin device is arranged at the front end of the vehicle body, and the tail device is arranged at the tail end of the vehicle body; and the motor device is arranged at the rear part of the vehicle body and in front of the tail device. The application has the advantages of low cost, small noise, strong concealment, autonomous work, high safety, complete functions, simple maintenance and the like. The application can effectively break ice and provide support for civil and military tasks in the Arctic Ocean and other ice-covered sea areas, and has high practical value.