321 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.

An intelligent safety supervision system applied to a ship is provided. An image acquisition module is configured to acquires high-definition images in real time. An automatic recognition module is configured to obtains ship dynamic and static data. A ship server to-performs feature recognition on the ship dynamic and static data to obtain a data processing result, to-transmits the ship dynamic and static data and the data processing result, and receives alarm indication information. An alarm module outputs an alarm. A ship client displays the data processing result, and determines whether to transmit the alarm indication information according to the data processing result. A communication module receives and transmits the ship dynamic and static data and the data processing result. A shore-side supervision system includes a ship safety supervision big data analysis platform for performing secondary feature recognition on the ship dynamic and static data, so as to obtain a secondary data processing result.

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 discloses an intelligent emergency control system of an arrangement ship steering oar, and belongs to the technical field of arrangement ship steering oar control. An intelligent emergency control system of an arrangement ship steering oar comprises a main control module, a steering oar driving module and a steering oar control module. The problem that in the prior art, when a main steering system breaks down, a ship is prone to being out of control, colliding or other safety accidents are caused is solved, the steering oar driving module is used for conducting driving operation on the arrangement ship steering oar in an emergency mode, the state of the arrangement ship steering oar is monitored in real time, and the safety of the arrangement ship steering oar is improved. When potential problems and fault trends exist in the arrangement ship steering oar, a control instruction of the arrangement ship steering oar is adjusted so as to ensure safe operation of the arrangement ship steering oar, quick response can be made and an emergency mode can be started in emergency, dangerous situations such as out-of-control of the ship can be effectively avoided, remote monitoring and management can be achieved, and the safety of the arrangement ship steering oar is improved. Safety and management efficiency of the ship are improved, and safe driving of the ship is effectively guaranteed.

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 ship encounter space-time risk assessment method and system considering navigation environment influence, and belongs to the technical field of ship safe driving. The invention aims to solve the problem that the collision avoidance action opportunity of a complex marine environment collision avoidance scene cannot be accurately determined. According to the invention, through a ship environment sensing module and a positioning module, channel environment information of a ship navigation area and position, course and speed information of a ship are obtained; calculating the nearest meeting distance of the intersection of the two ships, the meeting time of the ships sailing from the current position to the nearest intersection of the two ships, the safe meeting distance of the two ships, the absolute safe meeting distance, the latest avoiding distance and the distance capable of taking measures for avoiding; calculating the collision danger degree in the spatial position and the collision danger degree of the two ships in the time dimension; combining the space risk factor and the time risk factor by using a synthesis operator, and calculating the space-time collision risk factor; and evaluating the risk degree of ship collision according to the risk degree. The method is suitable for ship encounter space-time risk assessment.

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 provides a ship escape route dynamic indication method and device, equipment and a medium, and relates to the technical field of ship safety control, and the method comprises the steps: obtaining the current position of a target person on a ship, and a plurality of escape routes of the target person from the current position to a preset escape collection point of the ship; for any escape route, acquiring various types of environment state parameters of the escape route; determining a passable state of the escape route based on the various types of environment state parameters; if there is more than one escape route in the passable state, determining an optimal escape route from the plurality of escape routes according to the current position and the various environmental state parameters corresponding to the plurality of escape routes in the passable state; and dynamic emergency indication equipment on the optimal escape route is controlled to be started so as to indicate the optimal escape route for the target personnel to go to the escape gathering point. According to the invention, the dynamic indication of the escape route under the emergency condition of the ship can be realized.

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 discloses a multi-propeller cooperative propulsion control method and system for a ship, and relates to the technical field of ship automation control. The cooperative propulsion control method is used for cooperatively controlling a plurality of propellers through a control system of a ship to propel the ship and comprises the steps that the navigational speed of the ship, the position of a main station handle and the available power of a power station are obtained; identifying the current navigation condition of the ship based on the navigational speed and the main station handle position; based on a preset matching relationship, obtaining an operation mode matched with the navigation working condition; and on the basis of the navigation working conditions, the operation modes and a preset switching control strategy among different navigation working conditions, the available power of the power station is distributed to the multiple propellers, and cooperative propulsion of the ship is carried out. Thus, the navigation working condition is recognized based on the navigation speed and the position of the main station handle, the operation mode is matched, the available power of the power station is distributed to the multiple propellers, the response speed of ship propulsion control is increased, the adaptability to the complex navigation environment is improved, and the ship safety is improved.

The invention relates to the technical field of ship systems, and discloses a ship safety monitoring method, device and equipment, a medium and a program product. The method comprises the following steps: obtaining a ship monitoring video, and carrying out window segmentation on the ship monitoring video to obtain a plurality of video clips; obtaining a mean value score and a standard deviation score corresponding to each video clip by calculating the similarity degree between the adjacent video clips, and performing clustering analysis on the plurality of video clips according to the mean value score and the standard deviation score to obtain a video clustering result; and according to a video clustering result, if it is detected that the target video clip belongs to a scene change class, carrying out ship safety alarm. According to the scheme of the embodiment, ship safety early warning is realized based on dynamic scene change detection, the labor cost and the time cost can be reduced, missing report and false report of ship safety abnormity can be avoided, and the reliability of ship safety monitoring can be improved.

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.

The present invention discloses an intelligent detection method and system for non-destructive testing of the sealing of a ship's cabin, the method comprising: real-time monitoring of the change in gas concentration in the cabin, and calculation of the spatiotemporal distribution of gas concentration in combination with a diffusion model, using a sealing state calculation formula, combining sensor weights, gas concentration distribution and time decay characteristics, quantitatively evaluating the cabin's sealing condition; in the leakage detection link, accurately locating the leakage source through weighted calculation of gas concentration and air pressure changes, and determining the leakage point in combination with gas diffusion characteristics; the system further calculates the repair intensity, dynamically adjusts the repair intensity, and after the repair is completed, updates the gas concentration in the cabin, and finally performs comprehensive sealing verification. The present invention can realize high-precision, real-time, and non-destructive ship cabin sealing detection, is suitable for ship safety detection, airtightness assessment and intelligent maintenance fields, and improves the intelligence level and detection efficiency of sealing detection.

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 discloses a method for calculating a ship safety risk level based on big data, and relates to the technical field of data processing, and the method comprises the steps: collecting ship state data and environment parameters in real time through a computer, and carrying out the multi-dimensional fusion and local uploading of the collected data parameters; monitoring and analyzing the integrated and uploaded data stream in real time, and automatically triggering a data acquisition self-adaptive adjustment mechanism when the system detects that the ship data is uploaded abnormally or interrupted; generating a statistical model of the environmental parameters, and associating the model with the ship performance data to identify the influence of the environmental factors on the safety performance and form quantitative evaluation of the influence of the environmental conditions on the safety performance; performing environment compensation on a safety characteristic curve of the ship by utilizing a machine learning model based on the quantitative evaluation of the calculated environmental condition on the safety influence; and based on the safety characteristic curve after environment compensation, calculating to obtain the comprehensive risk level of the ship. And the evaluation is compensated, so that the credibility of the evaluation is improved.

The invention discloses a cooperative control system for a marine power lithium battery device and a control method of the cooperative control system. The system is based on a general control, master control and slave control three-level control mode, considers the problem of collaborative control of a power system of the whole ship, solves the problem of collaborative control and management of a ship lithium battery pack through internal grading and external collaborative strategies, and ensures that a lithium battery device provides guarantee for safe operation of the ship; a modularized data acquisition unit is arranged, different sensing devices are matched with a processing circuit, the requirement for multi-type data or signal acquisition is met, and the system supports data processing of the battery state and SOC / SOH estimation of the battery state of charge of a battery pack; the real-time data information of the slave control battery is acquired and processed through a CAN (Controller Area Network); management and control of charging and discharging of the battery pack are achieved after processing is completed; two paths of total voltage detection of the battery end and the load end are adopted, voltage sampling is reliable, detection errors are small, and overvoltage and undervoltage protection is supported through threshold value comparison.

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.