272 results about "Ship safety" patented technology

The invention relates to a ship safety monitoring method, system and device based on data fusion, and relates to the technical field of ship navigation safety, and the ship safety monitoring method comprises the steps: collecting multi-source heterogeneous data; preprocessing the multi-source heterogeneous data; carrying out fusion processing on the multi-source heterogeneous data based on an information entropy theory; a ship safety domain model is constructed, trajectory prediction is executed, a collision risk index is calculated, and the ship collision risk is evaluated; and performing anomaly detection on the ship equipment operation data based on manifold learning and a thermodynamic model. According to the invention, a multi-source heterogeneous data fusion technology is adopted, multi-dimensional data sources are integrated, and omnibearing ship safety situation awareness is constructed. The early warning time is prolonged to 8-10 minutes, which is far better than the early warning time of 3-5 minutes in the prior art. The system thoroughly solves the problem that subsystems in a traditional ship monitoring system operate independently and do not communicate with one another, the crew information acquisition cost is reduced, and the number of times of interactive operation is reduced by 42%.

The invention provides an LNG ship containment system monitoring system and method based on a fiber bragg grating sensor, and belongs to the crossing field of fiber sensing technology and ship safety engineering, the system comprises a fiber bragg grating sensor and a demodulation device, the fiber bragg grating sensor is used for collecting optical signals, and the demodulation device converts the optical signals into electric signals and processes the electric signals. The fiber bragg grating sensor adopts a double-grating structure and is respectively used for stress monitoring and temperature compensation so as to realize omnibearing real-time monitoring. The fiber grating sensor comprises a tail fiber, a protective tube, a base, and a strain grating, a spring and a temperature grating which are located in the protective tube. According to the invention, the monitoring precision and safety of the LNG ship containment system can be improved; through a double-grating temperature compensation technology, the influence of temperature change on stress measurement is eliminated, and the accuracy and reliability of data are ensured; in addition, stress information in different directions can be obtained in real time through the three-dimensional stress monitoring scheme, the stress condition of the structure is comprehensively reflected, and the flexibility and adaptability of monitoring are improved.

The invention provides a ship collision risk analysis method and system based on a fault tree and a Bayesian network, and relates to the technical field of ship safety. The method comprises the following steps: determining that main risk factors are human factors, ship factors, environment factors and management factors by analyzing ship collision accident cases; taking ship collision as a top event, performing deductive reasoning according to occurrence logic, and constructing a fault tree structure; the mapping relation between the fault tree and the Bayesian network is utilized, the Bayesian network of ship collision is established, and basic events, middle events and top events correspond to root nodes, middle nodes and leaf nodes respectively; the prior probability of a root node and the conditional probability of an intermediate node are determined through statistical analysis of main risk factors, and a Bayesian network model is formed; based on the model, a collision risk rate is calculated through forward reasoning, key risk factors are diagnosed through backward reasoning, and a main risk path causing collision is identified. According to the scheme, the complex relation between the risk factors can be accurately and objectively subjected to deep analysis and quantitative description.

The invention discloses a hydrogen fuel cell ship safety protection system and method, and relates to the technical field of ship safety, and the method comprises the steps: starting a multi-mode sensor of each region, embedding an edge processing unit, and executing self-inspection and calibration; the edge processing unit preprocesses the sensor data by using adaptive filtering to obtain original data; building a three-dimensional virtual model of the ship and each area based on the original data, and simulating a hydrogen diffusion and fire evolution process in combination with real-time CFD simulation to obtain a risk prediction parameter and a preset safety threshold; according to the active scheduling control command, an emergency response plan is triggered according to risk grade classification; comparing the field feedback information with the execution state verification emergency response plan, and forming a safety protection report; according to the method, the emergency response plan is dynamically adjusted through the risk index, the safety, the response speed and the protection capability of the hydrogen fuel cell ship in a complex environment are effectively improved, and potential safety risks are reduced.

The invention provides a ship video concentration and intelligent retrieval method and system based on edge nodes, and belongs to the technical field of edge computing, and the method comprises the steps: S1, collecting ship video data; s2, an edge node generates a concentrated video and metadata through an improved Gaussian mixture model, an improved DeepSORT algorithm and a dynamic concentration proportion adjustment algorithm; s3, synchronously concentrating the index information of the videos and the metadata by each edge node through a publishing-subscribing mode; s4, training a lightweight intelligent retrieval model through a knowledge distillation algorithm; s5, calling the lightweight intelligent retrieval model to match the corresponding concentrated video clip, and returning a retrieval result; and S6, collecting feedback information of the user on the retrieval result, and performing incremental optimization on the lightweight intelligent retrieval model through an elastic weight consolidation algorithm. According to the invention, efficient monitoring management is realized through edge localization processing, cross-node cooperation and closed-loop optimization architecture, and the actual requirements of ship safety monitoring and operation management are met.

The invention discloses a LoRa-based ship environment multi-parameter intelligent wireless monitoring system, which is characterized in that environment state data and ship operation auxiliary data are acquired through a data acquisition module, and a data processing module is used for preprocessing and standardizing the acquired data to obtain a standardized data frame; the environment safety quantification module calculates a single parameter safety score, a comprehensive safety index and a safety situation level SL, the intelligent LoRa communication module dynamically selects a communication strategy according to the SL and the current link quality and generates and sends a safety data packet, the LoRa gateway receives the safety data packet, redundancy filtering is carried out, receiving metadata is added, a final data record is formed and uploaded, and the LoRa gateway sends the final data record to the intelligent LoRa communication module. And the data center performs visual display and data storage on the final data record, and generates a network optimization instruction based on the network performance data, so that the problem that transmission reliability, real-time performance and low power consumption are difficult to consider in ship environment monitoring is solved, and the intelligent level of ship safety management is improved.

The invention discloses a sailing ship safety situation awareness system, and belongs to the technical field of data analysis. The method is used for solving the technical problem that in an existing scheme, multi-dimensional data analysis and timely and reliable early warning cannot be carried out on complex sea conditions, and consequently the coping capacity of the complex sea conditions is weak. Through the whole process of biological anchoring anomaly suppression, data fusion and dynamic feature extraction, the limitation that traditional ship perception depends on a physical sensor can be broken through, high-precision perception of environmental risks and ship states under complex sea conditions is achieved, and compared with a traditional method, the abnormal sea conditions can be recognized in advance, and the method has the advantages of being high in practicability. The robustness of the data and the detection rate of small probability and high influence events can be effectively improved; cross-scale modeling is realized through deep coupling of a microscopic physical mechanism and macroscopic data features; the constructed multi-dimensional risk assessment matrix not only can output a risk value, but also can provide a risk propagation path, and can effectively improve the risk assessment precision of the ship under a complex sea condition.

The invention relates to the technical field of ship navigation risk assessment, in particular to a ship navigation risk assessment system based on multi-source heterogeneous data fusion, which comprises a multi-source data integration module, a spatial-temporal feature mapping module, a dynamic risk detection module, a linkage decision control module and a feedback optimization module. According to the method, standardized operation data is generated through multi-source data cleaning and fusion, a spatial-temporal feature distribution map is generated by using a multi-dimensional dynamic clustering algorithm, a risk index set is extracted in combination with adaptive boundary adjustment and a nonlinear optimization algorithm, and accurate path planning and real-time regulation are realized. In addition, a global sensitivity analysis framework and an early warning module are introduced into the system, and the ship navigation safety and reliability are improved. According to the method, the risk prediction accuracy can be remarkably improved, the navigation accident probability is reduced, the navigation efficiency is optimized, and safe operation of the ship is guaranteed.

The invention discloses an under-actuated unmanned surface vehicle safe formation tracking control method based on robust obstacle control. The method comprises the following steps: establishing a multi-unmanned ship group and performing real-time communication, and enabling each follower to follow a leader according to a formation configuration and to avoid an obstacle; a safe formation tracking control framework of the underactuated unmanned surface vehicle is established, during formation tracking, followers input state information into the control framework, processing is carried out according to a reference trajectory of a leader and real-time information of a current follower and an obstacle, and forward and steering control torque instructions are output to control the current follower. Obstacles are avoided and formation configuration is restored to continue following the leader. According to the method, the underactuation characteristic problem of the unmanned surface vehicle is solved, the worst case error generated when the neural network approaches the unknown dynamic state can be effectively compensated, it is ensured that the unmanned surface vehicle can strictly avoid collision with the obstacle in the complex environment, and meanwhile the formation tracking performance is optimally kept.

The invention discloses a ship safety monitoring intelligent abnormity alarm system based on multi-dimensional analysis, and relates to the technical field of shipping safety monitoring, the ship safety monitoring intelligent abnormity alarm system comprises a safety monitoring center, the safety monitoring center is in communication connection with the following modules: a data acquisition and analysis module used for collecting ship operation data from each sensor and equipment of a ship, and sending the collected ship operation data to an alarm module; feature analysis is carried out, alarm features reflecting ship abnormity are extracted, and an alarm feature sequence table is obtained through integration. According to the method, the ship operation data is collected and preprocessed from each sensor and equipment of the ship, and the abnormal condition in the ship operation can be accurately identified by combining the abnormal identification model and the alarm feature sequence table constructed based on the neural network model, so that the limitation possibly brought by a single data source is avoided; the accuracy of anomaly detection is improved, potential safety hazards can be found in time, and accidents are prevented.

The invention discloses a dynamic feature and physical gating fused wave height prediction system and method, belongs to the technical field of artificial intelligence and machine learning, is used for marine environment monitoring, and comprises a data acquisition and preprocessing module, a feature screening module and a model prediction module. The method comprises the steps of obtaining and preprocessing marine meteorological variable data, constructing a Shapley additive interpretation lightweight gradient elevator regression model to screen a core variable set, constructing a physical guidance gating feature perception Transform prediction model, constructing a mixed loss function constraint prediction model, and outputting a sea wave significant wave height prediction value after prediction model training is completed. According to the method, through a feature screening and dynamic weight distribution mechanism, the utilization efficiency and scene adaptability of multi-source marine meteorological features are remarkably improved, the method can be flexibly expanded to sea wave prediction tasks of different sea areas and spatial-temporal scales, and high-precision and high-reliability technical support is provided for ocean engineering, shipping safety and disaster early warning.

The invention discloses an early warning method and system for the distance between ships in a navigable tunnel and a medium. Relates to the technical field of ship safety spacing design. Matching a safety spacing calculation mechanism corresponding to the current ship according to the position of the current ship in the navigable tunnel and the ship type quantitative characteristics of the current ship; calling a safety distance calculation mechanism corresponding to each ship to obtain a calculated safety distance of each ship, and performing adjacent correction to obtain a safety distance; when the measurement distance between the adjacent ships exceeds the safety distance, an alarm prompt is given in time; according to the scheme, the method is improved on the basis of a traditional ship safety spacing design technology, and a safety spacing calculation mechanism corresponding to the current ship is matched according to the position of the current ship in the navigable tunnel and the ship type quantitative characteristics of the current ship based on the special environment of the navigable tunnel; and the safe spacing of the ships in the navigable tunnel is calculated by using a safe spacing calculation mechanism, so that technical support is provided for safe and efficient operation of the navigable tunnel.

The invention relates to the technical field of ship safety monitoring, in particular to an urban inland river pleasure boat driving dynamic safety monitoring method and system based on multi-modal sensing, and the method comprises the steps: carrying out the data preprocessing and synchronization based on multi-source heterogeneous data collected by a multi-modal sensor network in real time, and outputting the multi-source heterogeneous data with time-space alignment; performing cross-modal attention model feature fusion based on the multi-source heterogeneous data of space-time alignment, and outputting fused multi-dimensional state features; based on the fused multi-dimensional state features, dynamic risk assessment is executed, and a final risk level is output; based on the final risk level and the historical risk data, the risk type is judged, and whether emergency response is activated or not is judged; when the emergency response is activated, risk avoiding operation is executed, and a feedback report is generated. The method has the effects of effectively preventing navigation risks and reducing potential accident loss.

The invention discloses a high-ice-condition avoidance path planning method considering motion characteristics of a ship in an ice region, and relates to the technical field of safe navigation of ships, and the method comprises the steps: constructing a coarse-scale grid map and a fine-scale grid map, and determining a high-ice-condition grid; determining an initial navigation path by using a global path planning algorithm based on the coarse scale grid map; determining an external exciting force and substituting the external exciting force into the three-degree-of-freedom manipulation motion equation to solve motion state parameters; based on the fine-scale grid map and the motion state parameters, taking each global path point of the initial navigation path as a sub-target point, generating a plurality of local paths, and combining the local paths to obtain candidate navigation paths; and repeatedly executing the step of generating the initial navigation path and the candidate navigation path until the candidate navigation path meets the navigation requirement, thereby obtaining an optimal navigation path. According to the method, global direction control and local motion capability analysis are both considered, and the accuracy and reliability of the optimal navigation path obtained through planning are effectively improved.

A safety system for a boat, watercraft or other vehicle includes a kill switch connected to the motor for preventing the motor from running under dangerous circumstances. The system may include proximity sensors operatively connected to the kill switch, so that the motor only runs when the proximity sensor detects a person properly positioned at the captain's console. Other sensors may form an array to communicate with the kill switch, to automate certain features and systems, or to otherwise provide alarms upon detection of dangerous situations, including a carbon monoxide detection sensor system, gate sensors, anchor-down sensors, ladder sensors, ambient light sensors, optical rain sensors for operating an automated windshield wiper safety system, an array of cameras strategically positioned around the periphery of the watercraft for monitoring purposes, and an automated anchor / navigation light system.

A large ship safety supervision system, configured to realize shipmen monitoring and ship safety supervision, wherein shipmen monitoring comprising monitoring of real time positions of shipmen in cabins and shipmen health data, and ship safety supervision comprises oceanic condition warning, on board devices running condition monitoring, ship navigation / construction monitoring and ship remote guidance. Data transmission in between ships and shores is realized by the hybrid self-adaptive compression technology based on model classification and the data transmission link intelligent selection technology based on fuzzy neural network creatively, in the meanwhile, real time safety management and supervision and ship remote work analysis and guidance can be realized.

The invention relates to an AI intelligent management platform for maintenance of ship safety lifesaving emergency equipment. The AI intelligent management platform comprises a front-end function system and a rear-end storage system. The front-end function system comprises a sailor training module, an intelligent inspection module, a third-party maintenance supervision module and the like. Wherein the sailor training module adopts a panoramic VR camera to carry out live-action shooting on a scene on a ship, a virtual reality (VR) technology is applied to provide real scene boarding experience, sailors are helped to remotely realize immersive ship visiting, and a real ship environment is comprehensively understood; through the combination of videos and characters, skill training of sailors before on-ship work is provided. The sailors can remotely realize immersive ship visiting through the sailors training module, comprehensively understand the actual ship environment and remarkably improve the practical operation skills of the sailors; the personalized training path system customizes an exclusive training plan for each sailor through AI algorithm intelligent analysis according to the post demand, experience level and skill weakness of the sailor, and achieves the precision and high efficiency of training.

The invention discloses a ship intelligent video monitoring system, and belongs to the technical field of computers. The system comprises a data acquisition unit used for acquiring various modal data of a ship; the data fusion unit is used for determining reference information, adaptively determining to-be-fused target modal data in the multiple modal data based on the reference information, and fusing the target modal data to obtain multi-modal fusion data; the data processing unit is used for determining abnormal information based on the multi-modal fusion data, a pre-constructed ship safety rule base and an abnormal detection model, and the abnormal information comprises ship safety equipment abnormal information, ship personnel action abnormal information, sensor abnormal information and ship traveling track abnormal information; and the alarm unit is used for processing the abnormal information to obtain the abnormal level of the abnormal information, and determining alarm information by using the abnormal level and the abnormal information. According to the invention, the safety and standardization of the ship in the sailing process can be improved.

The invention relates to the technical field of ship safety, and discloses a ship safety management monitoring system based on the Internet and a Beidou satellite, the system comprises a coordinate analysis module, a ship state module, a data fusion module, an abnormity identification module and an early warning message sending module, a satellite positioning signal is analyzed, and real-time latitude and longitude coordinates of a ship are obtained; generating comprehensive operation parameters of the ship according to the attitude, the navigational speed, the load and the main engine operation parameters of the ship; performing data fusion on the longitude and latitude coordinates after timestamp alignment and the comprehensive operation parameters to obtain an operation feature vector of the ship; performing abnormal mode identification on the operation feature vector based on historical navigation data and a preset safety threshold to obtain a risk category of the ship; when a risk category occurs, generating a treatment measure message of the risk category, and sending the treatment measure message to a ship-end display terminal and a shore-based management terminal through communication between the Internet and a Beidou short message; the ship safety management efficiency can be improved.

The invention provides a ship liquefied natural gas leakage analysis and personnel evacuation guiding device system and method, and belongs to the technical field of ship safety. According to the ship liquefied natural gas leakage analysis and personnel evacuation guiding method, firstly, whether liquefied natural gas leakage occurs on a ship or not is monitored; if yes, collecting leakage state parameters of liquefied natural gas and current environmental data of a sea area where the ship is located; then different leakage consequence databases are matched according to the leakage state parameters, the environment data and whether the liquefied natural gas is combusted and exploded or not, corresponding leakage consequence conditions are obtained, and finally a safe personnel evacuation route is given to guide personnel in the ship to be evacuated rapidly. And the safety when the liquefied natural gas of the ship leaks is improved.

A large ship safety supervision system, configured to realize shipmen monitoring and ship safety supervision, wherein shipmen monitoring comprising monitoring of real time positions of shipmen in cabins and shipmen health data, and ship safety supervision comprises oceanic condition warning, on board devices running condition monitoring, ship navigation / construction monitoring and ship remote guidance. Data transmission in between ships and shores is realized by the hybrid self-adaptive compression technology based on model classification and the data transmission link intelligent selection technology based on fuzzy neural network creatively, in the meanwhile, real time safety management and supervision and ship remote work analysis and guidance can be realized.

The embodiment of the invention discloses a ship AI safety monitoring model training data processing method and system. The method comprises the following steps: acquiring ship image data and image metadata in real time through a camera, and performing associated storage; performing service information labeling on the ship image data; performing data cleaning, association integration and structured conversion on the annotation information to generate training data available for the AI model; classifying and storing the data, and establishing an index; and outputting the training data to the ship AI safety monitoring model through the interface for training. The method has the following advantages: (1) the scene adaptability of the AI model is improved; (2) the training data acquisition cost is reduced; (3) seamless connection of business data and training data is realized; and (4) supporting multi-subject data multiplexing and model iteration.

The invention relates to a safety early warning communication method and system among multiple ships. The method comprises the following steps: acquiring real-time dynamic data of a running ship in a current running state; performing quality score determination on the real-time dynamic data; when the quality score is lower than a first threshold value, performing feature reconstruction compensation on the real-time dynamic data corresponding to the quality score; conflict perception attention weighted fusion is carried out on the high-quality modal data, and a risk confidence coefficient and a conflict flag bit corresponding to a ship driving risk event are generated; based on the risk event and the high-quality modal data, generating driving early warning information; and switching a networking router network link required by data transmission based on the risk confidence and the conflict flag bit, and sending driving early warning information to the driving ship by the own ship. The low-quality mode is converted into the high-quality mode, the fusion strategy is carried out through the high-quality mode, the safety early warning information is obtained, and the technical effect of reducing the influence of the low-quality mode on the subsequent decision accuracy is achieved.

The invention relates to the technical field of ship lock automatic control, in particular to a ship lock miter gate automatic control method based on water flow pulsating pressure, and the method comprises the steps: judging the current working condition of a ship lock miter gate, and obtaining the initial control strategy of the current working condition of the ship lock miter gate; processing to obtain an abnormal state evaluation value of the ship lock miter gate control equipment; comprehensive performance evaluation indexes of the ship lock miter gate are obtained through comprehensive analysis; a ship lock bearing pressure evaluation threshold value is obtained through matching according to the ship lock miter gate comprehensive performance evaluation indexes, and feedback early warning is conducted on the ship lock miter gate comprehensive performance; according to the ship lock miter gate automatic control method based on the water flow pulsating pressure, a ship lock bearing pressure evaluation value is obtained through analysis, the ship lock bearing pressure evaluation value is compared with a ship lock bearing pressure evaluation threshold value, and a current working condition initial control strategy is adjusted according to a comparison result. Therefore, the operation quality and safety of the ship lock can be improved.

The invention relates to the technical field of ship safety, in particular to a ship navigation monitoring management system and method based on edge computing, and the system comprises seven cooperation modules: a data collection module synchronously obtains ship multi-source data, and a processing storage module achieves the data compression, marking and storage. The encryption security module completes full-process AES-256 encryption through a hardware encryption chip, the dual-power supply module guarantees stable power supply, the satellite positioning module obtains accurate positioning through Beidou / GPS dual modes, the self-inspection maintenance module monitors faults in real time, and the AI edge calculation unit achieves channel object recognition, track analysis and violation warning through a deep neural network model. According to the method, closed-loop processes of data acquisition, encryption, processing, intelligent analysis and fault handling are completed through module cooperation; the invention aims to solve the problems of high monitoring delay, insufficient data security, unreliable power supply and the like of the existing system.

The invention discloses a dynamic positioning floating ship entering control method and system based on image recognition, and aims at solving the problems that manual operation is poor in precision, low in efficiency, insufficient in safety and the like. According to the method, a camera is arranged on a jacket to collect images, image recognition is performed after preprocessing, image features of the jacket and a floating mounting ship are extracted, and the relative position and posture of the ship relative to the jacket are estimated according to the image features. And the system generates a control instruction by using a dynamic positioning control algorithm based on the position attitude information, automatically controls a ship propeller, and realizes accurate entering of the floating mounting ship to the preset position of the jacket. And the system continuously monitors and adjusts a control instruction in real time to form closed-loop control, so that the ship is ensured to safely and accurately complete a floating ship entering task. The positioning precision, the operation efficiency and the safety of floating ship entering are effectively improved, and automatic control is achieved.

The present disclosure relates to a ship safety control method and ship safety control system. According to an embodiment of the present disclosure, the ship safety control method may include determining a sea condition in an area, in which a ship is located, based on a video feature of a first video of a ship situation, preprocessing the first video based on the sea condition, designating a control area in a second video based on the second video generated through the preprocessing, and detecting at least one of an object and occurrence of an event within the control area.

The present invention discloses a method for detecting abnormal ship status based on AIS data, comprising the following steps: obtaining raw AIS data, preprocessing the raw AIS data to obtain the original trajectory of the ship, and segmenting the original trajectory to obtain straight and curved segments of the original trajectory; after extracting the curved and straight segments, using a trajectory similarity measurement algorithm to eliminate abnormal trajectories, and using a Bi-LSTM model to predict on the basis of the absence of abnormal trajectories; and constructing a prediction-based anomaly detection model based on the straight and curved segments using a Bi-LSTM deep learning model to complete the detection of abnormal ship status. The present invention monitors the ship's navigation status in real time, automatically detects anomalies, and issues timely warnings, effectively reducing the reliance of safety supervision on manpower and having important significance in ensuring the safe navigation of ships and the prosperity and development of maritime trade.

The application discloses a kind of ship's multiple propeller collaborative propulsion control method and system, it is related to ship automation control technical field.For by the control system of ship collaborative control multiple propeller to carry out ship propulsion, collaborative propulsion control method includes: obtaining the speed of ship, main station handle position and power station available power;Based on speed and main station handle position, identify the current navigation condition of ship;Based on the matching relationship of pre-set, obtain the operation mode matched with navigation condition;Based on navigation condition, operation mode and the switching control strategy between different navigation conditions of pre-set, available power of power station is distributed to multiple propeller, and the collaborative propulsion of ship is carried out.Such, by based on speed and main station handle position, identify navigation condition, and match operation mode, to distribute available power of power station to multiple propeller, improve the response speed of ship propulsion control, improve the adaptability to complex navigation environment, improve ship safety.

The invention relates to the technical field of unmanned ship safety control, and discloses an anti-spoofing-attack self-adaptive sliding mode control method and system for an unmanned ship and a medium, and the method comprises the steps: S1, constructing an unmanned ship T-S fuzzy model under the spoofing attack and external disturbance; s2, designing a dual-adaptive sliding mode observer based on the unmanned ship T-S fuzzy model constructed in S1; s3, designing a sliding mode controller based on S1 and S2; and S4, forming a closed-loop control system based on S1-S3 to perform sliding mode control: integrating the unmanned ship T-S fuzzy model constructed in S1, the dual-adaptive sliding mode observer designed in S2 and the sliding mode controller designed in S3 to form the closed-loop control system, and realizing sliding mode control. According to the method, the dynamic suppression capability of the composite threat can be remarkably improved, precise compensation of a spoofing attack signal and external disturbance of the ocean is realized, high-precision zero-flutter control is realized under the coexistence of the spoofing attack and the external disturbance, and an autonomous control solution with safety, robustness and real-time performance is provided for the unmanned ship.