87 results about "Maritime navigation" patented technology

The invention relates to the technical field of maritime navigation and intelligent shipping, in particular to an electronic chart shipping relation network construction and dynamic updating method and system based on a chart database, and the method comprises the steps: obtaining electronic chart static data and shipping dynamic information, and carrying out standardized preprocessing to unify a space reference and an attribute format; defining node types and edge relation types of channel space elements based on the graph database, and constructing a shipping relation network; shipping dynamic information is accessed in real time, and the weight and the attribute of the side relation are dynamically updated to reflect the real-time state of the navigation channel; and receiving a user path planning query request, executing a path planning algorithm fused with the navigation constraint condition based on the updated network, and generating and outputting an optimal route, thereby effectively solving the problems of weak data association, difficult cross-scale fusion and poor dynamic adaptability of a traditional electronic chart, realizing intelligent management and accurate path planning of a channel relationship, and improving the user experience. And the shipping efficiency and safety are improved.

The invention belongs to the technical field of marine environment monitoring, and particularly relates to an air-sea cooperation-based enteromorpha identification and density estimation method and system, and the method comprises the steps: carrying out the aerial survey of a target sea area through an unmanned plane, collecting a sequence image, processing the sequence image based on a deep learning model, and generating an enteromorpha distribution probability graph and a density estimation graph; carrying out marine navigation and fixed-point sampling through an acoustic sensor carried by an unmanned ship to obtain actually measured density data of enteromorpha; the unmanned aerial vehicle sends the generated enteromorpha distribution probability graph and / or density estimation graph to the unmanned ship, the unmanned ship receives the enteromorpha distribution probability graph and / or density estimation graph, plans a navigation path and sampling points according to the enteromorpha distribution probability graph and / or density estimation graph, and goes to a high-probability or high-uncertainty area for fixed-point sampling; and the unmanned aerial vehicle receives actually measured density data returned by the unmanned ship and fuses the actually measured density data with own identification and estimation results so as to update and optimize the deep learning model and form an air-sea collaborative monitoring closed loop.

The invention belongs to the field of traditional Chinese medicines, and relates to a traditional Chinese medicine composition for treating insomnia and a preparation method and application thereof. The traditional Chinese medicine composition for treating insomnia disclosed by the invention is derived from a classic famous prescription combination, and provides an effective prescription for solving the problem of insomnia of marine navigation personnel, so that the health guarantee ability of people such as navy long-voyage and underwater navigation officers and soldiers, marine exploration personnel, fishermen and ocean crew in China is improved.

The invention discloses an automatic ship collision avoidance decision-making system, and relates to the technical field of ships, and the technical scheme is characterized in that the method comprises the steps: collecting environment data of a target ship in a navigation region and target ship dynamic data of the target ship in a navigation process; dividing the navigation area into navigation area blocks according to the risk level and the environmental data, and performing feature extraction on the dynamic data of the target ship to obtain dynamic feature parameters; analyzing and determining the normal variation range of the influence coefficients of the navigation region blocks with different risk levels to obtain a reference interval value; according to the reference interval value, performing statistics on influence coefficients between the current target ship and the surrounding environment and between the current target ship and other ships in the sailing process to obtain a statistical result, and comparing the statistical result with the reference interval value to obtain a collision avoidance risk early warning or continuous analysis instruction; the method has the effects of reducing the occurrence rate of collision accidents and improving the safety and orderliness of marine navigation.

The invention provides an intelligent monitoring and early warning system based on a marine navigation mark, and relates to the technical field of monitoring and early warning, and the system comprises a navigation mark data collection module which is used for obtaining various data according to a preset navigation mark monitoring interval. And the risk assessment module is used for obtaining a position offset risk value according to the influence of the interference factor data on the navigation mark position. And the deviation early warning module is used for setting a position deviation threshold value according to the historical pose data in combination with the external factor data, judging whether the position deviation risk value of each navigation mark exceeds the position deviation threshold value or not, and generating a preliminary early warning signal if the position deviation risk value of each navigation mark exceeds the position deviation threshold value. And the ship influence early warning module is used for calculating a ship navigation influence coefficient according to the navigation data of the surrounding ship sending the preliminary early warning signal navigation mark in combination with the real-time position parameter, and generating early warning information in combination with the position offset risk value. The navigation mark monitoring precision is improved, the early warning timeliness is enhanced, the operation and maintenance cost is reduced, and the method can automatically adapt to different environments and scenes.

The self-adaptive dynamic optimization system comprises a plurality of key modules, a signal acquisition and monitoring module receives signals through a multi-band antenna, acquires ship and environment data and then transmits the ship and environment data to an analysis and decision module, and the analysis and decision module judges the condition of a blind area through an intelligent algorithm, formulates a strategy and issues an instruction; the antenna adaptive adjustment unit regulates and controls antenna parameters and detects and corrects when encountering obstacles; the communication link intelligent switching unit ensures stable switching of links; the data dynamic optimization processing module optimizes transmission; the power management and energy-saving module performs intelligent power management; and the man-machine interaction and early warning module realizes information interaction and storage. The problem of a ship-borne communication blind area is solved, the system stability is enhanced, the energy efficiency is improved, and marine navigation, operation and scheduling are guaranteed.

The invention discloses a fishing boat impact force prediction method based on AI, and belongs to the technical field of fishing boat impact, and the method comprises the steps: constructing a multi-boat motion state data set; calculating a relative distance and a relative azimuth angle of each pair of fishing boats according to the multi-boat motion state data set, and extracting a distance change rate and an azimuth angle change rate; if the relative distance of each pair of fishing boats is lower than a preset safety distance threshold value, the collision risk probability of each pair of fishing boats is obtained in combination with the azimuth angle change rate; the collision force is predicted through the collision risk probability; according to the impact force value and the collision risk probability, generating a collision risk level of each boat, and dynamically grouping the fishing boats to obtain an optimized formation structure; and according to the optimized formation structure, the avoidance course adjustment angle and speed variation of each ship are calculated, an emergency avoidance instruction is generated, and the executed multi-ship cooperative motion state is obtained. According to the invention, intelligent collaborative collision avoidance of the fishing boat group is realized, and the safety of marine navigation is obviously improved.

The invention relates to the field of marine navigation, and provides a satellite positioning continuous compensation method, system and device based on multi-source data and a medium, and the method comprises the following steps: obtaining navigation data through a navigation device, determining a reference timestamp, selecting a time window according to the reference timestamp, and carrying out data alignment to obtain satellite navigation data, log data, inertial navigation data and compass data; the yaw angle is calculated through satellite navigation data and compass data, the water flow speed is calculated through the satellite navigation data and log data, and continuous compensation is conducted through the water flow speed and the yaw angle; calculating a position offset according to the inertial navigation data, and calculating a longitude variation and a latitude variation through the position offset to obtain high-frequency satellite navigation data; the high-frequency satellite navigation data is used for calculating the position deviation, the track direction deviation and the track speed deviation, the satellite navigation data are verified through the position deviation, the track direction deviation and the track speed deviation, and the satellite navigation data can be supplemented and verified.

The invention provides an offshore area navigation safety control and optimization method, which comprises the following steps of: 1, acquiring multi-source observation data of an offshore navigation target, and preprocessing the multi-source observation data to obtain a space-time observation association diagram; 2, evaluating the dynamic credibility of each observation node by using a multi-modal consistency graph neural network; constructing an adaptive weighted factor graph model according to the obtained dynamic credibility, and solving a system state to obtain an optimal fusion track, a corrected environmental parameter and a posterior error covariance matrix; 3, constructing a regional risk field based on the optimal fusion track, the corrected environmental parameters and a posterior error covariance matrix; 4, on the basis of the regional risk field, a multi-target collaborative optimization model is constructed and solved, and navigation control parameters are obtained; and 5, executing the navigation control parameters, and performing adjustment and optimization by adopting multi-level closed-loop feedback to complete the navigation safety control and optimization of the offshore area.

The embodiment of the invention provides a maritime communication method based on a Beidou short message, which is applied to the technical field of communication, and comprises the following steps: S1, collecting maritime navigation original data of a ship in real time, and carrying out space-time alignment and normalization processing on the maritime navigation original data to generate a multi-modal data set; s2, performing data preprocessing on the multi-modal data set, extracting feature vectors of single-modal data, and combining the feature vectors to generate a feature vector data set; s3, performing data fusion on the feature vector data set to generate a fused feature vector data set; s4, encoding, compressing and packaging the fusion feature vector data set to generate a Beidou short message data packet, and sending the Beidou short message data packet to a shore-based monitoring center; and S5, the shore-based monitoring center generates a decision suggestion based on the received Beidou short message data packet. In this way, the technical problem of multi-modal data fusion is solved, the integrity and accuracy of data are improved, and the efficiency of data transmission is improved.

The utility model discloses a stress relief flat iron expansion joint, which relates to the technical field of ship manufacturing and comprises oil retaining flat iron which surrounds a deck and is vertically and fixedly connected to the deck of a ship, a plurality of expansion joints are mounted among the oil retaining flat iron at intervals, and each expansion joint comprises a body connected with the oil retaining flat iron. The arch-shaped bulge is formed by bending outwards from the middle part of the body and has a wide upper part and a narrow lower part; the expansion joints are arranged at the gunwale oil blocking flat iron at certain intervals, stress generated by deformation of the oil tanker under different working conditions when the oil tanker sails on the sea is absorbed, and the oil blocking flat iron is prevented from being broken and damaged.

The invention provides a route planning system capable of improving the operation efficiency of a power generation floating body. A route planning system plans the route of a power generation floating body that generates power while sailing on the sea. This course planning system is provided with a planning means for planning, as a course, a course in which a power generation floating body circulates between a meeting point between a transport ship for recovering power generation energy from the power generation floating body and the power generation floating body and a turning point different from the meeting point. The planning means changes, on the basis of at least one of the weather prediction accuracy and the sea image prediction accuracy, the number of turns in which the power generation floating body travels around the course until the power generation floating body meets the transport ship.

The invention provides an intelligent ship operation mode switching method and device, electronic equipment and a storage medium, and the method comprises the steps: switching a driving mode to a manual driving mode under the condition that a ship is detected to be in a berthing and unberthing stage; in the berthing and leaving process of the ship, first environment information around the ship is obtained in real time, and under the condition that the first environment information meets the first mode switching condition, the driving mode is switched to the auxiliary driving mode from the manual driving mode; under the condition that the ship is detected to be in the port entering and leaving stage, the driving mode is switched to a remote driving mode; and under the condition that the ship is detected to be in the marine sailing stage, the driving mode is switched to the autonomous sailing mode. Dynamic mode switching of the ship can be carried out according to different navigation environments and conditions, limitation of a traditional single operation mode is avoided, and adaptability and safety of the intelligent ship are improved.

The embodiment of the invention provides a marine diesel engine interactive intelligent agent device based on cooperation of large and small models and a temporary first-aid repair method, and aims to solve the problems of rapid diagnosis, emergency decision and first-aid repair guidance when a marine diesel engine breaks down suddenly. The device comprises a large language model serving as a core and responsible for task decomposition, decision generation and information integration; the professional small model carries out optimization analysis on tasks such as fault positioning, emergency decision making, spare part replacement and time prediction; the interactive agent core module supports voice and text input and provides real-time feedback; the multi-modal data real-time fusion module integrates various data sources and dynamically allocates weights; and the knowledge graph and inference engine module provides accurate first-aid repair guidance. The large language model is innovatively taken as a core to be deeply cooperated with a plurality of professional small models, so that the rapid diagnosis, emergency decision and temporary repair guidance of sudden faults of the marine diesel engine in the marine navigation process are realized, and the blank of the intelligent temporary repair technology of the marine diesel engine is filled.

The present application provides a kind of offshore area navigation safety control and optimization method, comprising: step 1, the multi-source observation data of offshore navigation target is collected, and pre-processing is carried out, to obtain the space-time observation correlation graph;Step 2, the dynamic credibility of each observation node is evaluated using multi-modal consistency graph neural network;According to the obtained dynamic credibility, an adaptive weighted factor graph model is constructed, and the system state is solved to obtain the optimal fusion track, the corrected environmental parameter and the posterior error covariance matrix;Step 3, based on the optimal fusion track, the corrected environmental parameter and the posterior error covariance matrix, a regional risk field is constructed;Step 4, based on the regional risk field, a multi-objective collaborative optimization model is constructed and solved to obtain the navigation control parameter;Step 5, execute navigation control parameter, and adopt multilevel closed loop feedback to optimize, complete offshore area navigation safety control and optimization.

The application relates to the technical field of maritime navigation and information security, in particular to an intelligent management method and management system for encrypted issuance of electronic charts, which comprises the following steps: when receiving an original electronic chart file, outputting an encrypted file; generating an identifier and a corresponding encrypted storage certificate; when receiving an order request of a client, extracting order core information and verifying identity authority; when the verification is passed, associating the order core information with the encrypted storage certificate and marking the order as a to-be-paid state; when detecting that the order is changed into a payment completion state, generating an electronic license and an unlocking key; when distributing encrypted data packets to the client based on an encrypted transmission channel, outputting a distribution confirmation notification; continuously monitoring the encrypted data packets and the use of the client, executing corresponding security operations based on the monitoring results, and outputting corresponding processing results. The application has the effects of improving work efficiency, ensuring data security, reducing human errors and improving customer experience.

The application discloses a neural network prediction method for optimal working angle of a marine ship photovoltaic panel. The method considers the influence of sea wave fluctuation and solar position change on the ship photovoltaic power generation system, collects the operation data of the ship photovoltaic panel under different conditions, and establishes a neural network model to learn the output power curve of the ship photovoltaic panel on the basis, and then the trained ship photovoltaic panel power fluctuation neural network model is used to predict the output power of the photovoltaic panel under the current condition. According to the prediction result, the characteristics of the ship photovoltaic panel power fluctuation curve are analyzed to determine the optimal inclination angle of the current ship photovoltaic panel. The application can quickly obtain the optimal inclination angle of the photovoltaic panel to track the sun during the ship sailing process, effectively suppress the power fluctuation of the photovoltaic panel during the ship sailing at sea, reduce the power loss, and improve the output power.

1. The name of the design product: flexible impeller pump. 2. The use of the design product: for conveying medium containing solid particles and / or gas or high viscosity liquid, such as conveying acid, alkali, salt, oil, alcohol and other medium in chemical industry, conveying food or nutrient fluid or semi-fluid, or cooling engine for small yacht sailing on sea, etc. 3. The design points of the design product: in shape. 4. The picture or photo best indicating the design points: perspective view 1.

The utility model discloses an ocean platform towing device relates to ocean engineering technical field, including towing system and wave resistance reduction device, towing system is used for connecting between tugboat and ocean platform to make tugboat can drag ocean platform sailing, wave resistance reduction device is provided on the mooring rope of towing system, and wave resistance reduction device is provided on the mooring rope of towing system. In the marine navigation process following the towing system, waves on a towing path can be broken, namely, waves facing the towing direction can be broken. According to the utility model, larger waves are broken and the wave height is reduced firstly, so that the wave resistance at the head part of the ocean platform during towing can be reduced, the stress of a towing system is reduced, the towing safety is ensured, and the capability of resisting severe sea conditions during towing of the platform is improved.

The invention discloses a method for detecting an offshore wind driven generator by a maritime radar, which comprises the following steps of: 1, starting the maritime radar and preheating the maritime radar, and starting scanning by an antenna; 2, during antenna scanning, recording N pulse echo powers of a given distance gate in a certain direction in a coherence interval; 3, periodically detecting and analyzing non-stationary signals of the time sequence; 4, obtaining a periodic index through the periodic detection analysis in the step 3; 5, the periodic indexes are judged; 6, when the periodic index is larger than or equal to a preset threshold value, the target in the specific distance door is judged to be the offshore wind turbine; according to the method, the power time sequence data is acquired through the single and multiple scanning speed modes of the antenna, the characteristic indexes are comprehensively extracted in combination with multiple periodic detection algorithms, the wind driven generator target can be accurately identified, and the method has the characteristics of improving the detection accuracy, reducing the radar false alarm rate, guaranteeing the marine navigation safety and being wide in applicability.

The invention discloses a multi-communication integrated ship-shore cloud collaborative ship navigation auxiliary system and an information data interaction method. The system comprises a shore cloud system and a ship-end navigation aid system. The ships can communicate with each other through four communication modes of the ship end navigation aid system; the shore cloud system and the ship-end navigation aid system realize ship-shore communication through mobile internet communication or Tiantong satellite communication; the shore cloud system automatically pushes sailing safety auxiliary prompts such as ship crossing a bridge area and ship deviating from a port entering and leaving channel to the ship end navigation aid system through mobile internet communication. According to the invention, an information collaboration method between ships and between ships and shore cloud is realized, and emergency information, marine navigation safety information and hydro meteorological information can be directly communicated; sailing safety auxiliary reminding such as ship crossing a bridge area and ship deviating from a port entering and exiting channel is carried out; the system method can be applied to an intelligent port and navigation informatization supervision system and a ship fleet safety operation system.

This invention provides a method, apparatus, computer equipment, and storage medium for identifying mesoscale eddies, belonging to the field of eddy recognition technology. The method includes: acquiring SLA data; dividing the SLA data into multiple initial SLA splines based on multiple SLA extreme points; filtering the multiple initial SLA splines according to preset screening conditions to obtain multiple first quasi-eddy SLA splines; selecting those belonging to the mesoscale eddy from the multiple first quasi-eddy SLA splines to obtain multiple second quasi-eddy SLA splines; determining the eddy boundary and eddy center of the mesoscale eddy based on the multiple second quasi-eddy SLA splines; and determining basic attribute features based on the eddy boundary and eddy center of the mesoscale eddy. This invention only processes SLA data, enabling rapid and efficient mesoscale eddy identification, providing timely and efficient service support for marine field observation and maritime navigation.

The invention provides a maritime navigation data processing method and device, equipment and a medium. According to the method, after to-be-screened maritime navigation data sent by a plurality of first monitoring stations is obtained, the to-be-screened maritime navigation data is screened according to the end moment of a sending period and the satellite sending moment in each piece of to-be-screened maritime navigation data, and first maritime navigation data is obtained. According to satellite data in each piece of first maritime navigation data, pseudo-range correction data and pseudo-range correction deviation are calculated, and then according to each pseudo-range correction deviation, the pseudo-range correction data are screened to obtain target correction data. According to the scheme, the to-be-screened maritime navigation data is screened to obtain the first maritime navigation data, and the pseudo-range correction data is screened according to the pseudo-range correction deviation calculated by the first maritime navigation data to obtain the target correction data, so that the accuracy of the correction data is effectively improved.

This invention relates to the field of maritime navigation, providing a method, system, device, and medium for satellite positioning follow-up based on multi-source data. The method includes acquiring navigation data through navigation equipment, determining a reference timestamp, selecting a time window based on the reference timestamp and aligning the data to obtain satellite navigation data, log data, inertial navigation data, and compass data; calculating the yaw angle using the satellite navigation data and compass data, calculating the current velocity using the satellite navigation data and log data, and using the current velocity and yaw angle for follow-up; calculating the position offset based on the inertial navigation data, calculating the longitude and latitude changes using the position offset to obtain high-frequency satellite navigation data; calculating the position deviation, course deviation, and track speed deviation using the high-frequency satellite navigation data, and verifying the satellite navigation data using the position deviation, course deviation, and track speed deviation. This invention can both follow up and verify satellite navigation data.

This invention belongs to the field of intelligent perception and simulation training technology for maritime navigation. It discloses a method and system for realistic training and evaluation of ship collision avoidance rules at sea. By constructing a hierarchical question bank, it generates scenario assembly lists and uniformly schedules ship motion simulation, 3D visual scenes, radar / AIS fusion display, and voice communication interaction. During training, it collects control inputs, motion states, target information, and communication records to form a traceable chain of evidence, and aligns sampling based on evaluation anchor points. An automatic scoring model is established based on result and process indicators, outputting an evaluation report with sub-scores, evidence location, a list of violations, and retraining suggestions. It is suitable for teaching, retraining, and assessment, improving the efficiency and achievement rate of collision avoidance decision-making training.

The application belongs to the technical field of offshore platforms, and particularly relates to a method for installing a depth finder and a log transducer of a flat-bottom self-propelled self-elevating platform, which comprises the following steps: S1, installing a support on the bottom surface in front of a bow side thruster cabin of the platform; S2, loading the depth finder or the log transducer into a cylinder; S3, inputting parameter data of the bow side thruster cabin into a neural network model for self-learning, and then determining the vertical installation depth of the cylinder according to the parameters output by the neural network model; and S4, determining the vertical installation depth data. The method for installing the depth finder and the log transducer of the flat-bottom self-propelled self-elevating platform can prevent the transducer from being affected by bubbles during navigation and enable the transducer to work normally by installing the transducer in front of the bow side thruster cabin of the platform. The neural network model is arranged to associate the draft of the bow side thruster cabin, wave data and the installation depth of the log transducer, so that the method can be applied to the installation of transducers on all offshore navigation platforms.

1. Name of the Design Product: Signal Lamp. 2. Use of the Design Product: To provide signals for ships during sea voyages. 3. Design Key Points of the Design Product: Lies in the shape. 4. Picture or Photograph that Best Illustrates the Design Key Points: Perspective View 1.

The present invention discloses a method for predicting the route of a maritime target, comprising the following steps: (1) collecting and preprocessing historical AIS data, calculating and introducing new features, considering the influence of the own ship under complex scenarios; dividing the training set, validation set and test set; (2) using a convolutional neural network to extract local spatio-temporal correlation features; (3) using a bidirectional long short-term memory network to model the temporal dependence of the target; (4) using an attention mechanism to weight and extract critical moments or features; (5) independently training each model and evaluating the performance of the fused model on the test set; (6) using a moving window technique to extract and output fixed-length data to complete the prediction from one time period to another; the present invention can accurately predict the future route of the target ship, provide strong decision-making support for ship drivers, and thus effectively improve the safety of maritime navigation.