Combined fleet safety risk assessment method and system based on data processing

Abstract

The invention provides a combined fleet safety risk assessment method and system based on data processing, and relates to the technical field of data processing, and the method comprises the steps: 1, collecting four types of data through sensors on a main propulsion ship, a barge and an auxiliary function ship, comprising ship state data, connecting device working condition data, navigation environment data and cargo safety parameters; 2, transmitting the four types of data through a data interaction channel of an inter-ship connecting device, discretizing the data into spatial distribution data of a ship key area after space-time alignment, and generating six groups of position data sets with three-dimensional space coordinate labels; according to the method, the space mapping is established, the risk coefficient is quantified, and the navigation data is fused, so that the accurate assessment and targeted early warning of the dynamic risk of the full flight segment of the combined fleet are realized, and the transportation safety and the emergency response efficiency are improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of data processing, in particular to a combined fleet safety risk assessment method and system based on data processing. BACKGROUND

[0002] In the near-shore bulk cargo (such as coal, iron ore) transportation, when the combined fleet formation mode of the main propulsion ship providing core power, multiple barges carrying cargo, and auxiliary functional ships responsible for dangerous cargo monitoring and emergency support is coordinated to sail, there is certain room for improvement in the comprehensive evaluation of dynamic coupling risks in the existing technology, which is specifically manifested in: When the fleet sails to complex offshore waters (such as the bay mouth area with multiple waves, and the offshore channel with dense ship traffic), it needs to frequently respond to dynamic working conditions such as wave height changes, heading adjustments, and surrounding ship avoidance. Real-time working condition monitoring of the inter-ship connecting device is still insufficient. The existing monitoring only focuses on mechanical lock buckle basic stress data collection, lacks real-time continuous monitoring of hydraulic circuit pressure fluctuation values (such as the difference between instantaneous peak and valley values of hydraulic oil pressure), and power transmission stability indicators (such as voltage deviation rate and current fluctuation frequency), resulting in key risks such as instantaneous overload damage of the connecting device caused by wave impact and fatigue hidden dangers caused by long-term high-frequency stress, which may be missed due to insufficient data support. SUMMARY

[0003] The technical problem to be solved by the present application is to provide a combined fleet safety risk assessment method and system based on data processing, which effectively reduces safety hazards and ensures transportation safety.

[0004] To solve the above technical problems, the technical solution of the present application is as follows: In a first aspect, a combined fleet safety risk assessment method based on data processing, the method comprising: Step 1: Collecting four types of data through sensors on the main propulsion ship, barges and auxiliary functional ships, including ship state data, connecting device working condition data, navigation environment data and cargo safety parameters; Step 2: Transmitting the four types of data through the data interaction channel of the inter-ship connecting device, and discretizing the spatial distribution data of the key areas of the ships after time and space alignment to generate six groups of position data sets with three-dimensional space coordinate labels; Step 3: Based on the six groups of position data sets with three-dimensional space coordinate labels, performing regional feature analysis through pre-designed calculation logic to generate structure connection failure risk coefficient, cooperative operation out-of-control risk coefficient and special transportation safety risk coefficient; Step 4: Fusing the three types of risk coefficients with voyage planning data and sea state prediction data to generate full-segment dynamic risk assessment results and output risk warning instruction set containing regional compensation parameters.

[0005] In a second aspect, a data processing-based combined fleet safety risk assessment system comprises: a data acquisition module configured to acquire four types of data, i.e., ship state data, connecting device working condition data, navigation environment data and cargo safety parameters, through sensors on the main propulsion ship, the barge and the auxiliary function ship; a conversion module configured to transmit the four types of data through a data interaction channel of a connecting device between ships, discretize the data into spatial distribution data of key areas of the ships after spatio-temporal alignment, and generate six sets of position data sets with three-dimensional spatial coordinate labels; a calculation module configured to perform area feature analysis based on the six sets of position data sets with three-dimensional spatial coordinate labels through pre-designed calculation logic, and generate a structure connection failure risk coefficient, a collaborative operation out-of-control risk coefficient and a special transportation safety risk coefficient; an instruction generation module configured to fuse the three types of risk coefficients with voyage planning data and sea state prediction data, generate a full voyage dynamic risk assessment result, and output a risk warning instruction set containing area compensation parameters.

[0006] In a third aspect, a computing device comprises: one or more processors; a storage device configured to store one or more programs, when the one or more programs are executed by the one or more processors, the one or more processors implement the method.

[0007] In a fourth aspect, a computer readable storage medium stores a program, when the program is executed by a processor, the method is implemented.

[0008] The above-mentioned scheme of the present application at least has the following beneficial effects: Four types of core data are acquired through sensors of multiple types of ships, covering the ship's own state, connecting device working condition, external environment and cargo safety, providing comprehensive and key data support for risk assessment and reducing information blind spots; after spatio-temporal alignment and key area discretization, the data are associated with three-dimensional spatial coordinates of the ship, precise mapping of data and physical areas is established, the problem of fuzzy matching of data and risk positions is solved, and risk analysis can focus on specific key areas. Based on the spatialized data, three types of special risk coefficients are generated, respectively accurately quantifying core safety risks such as structure connection, collaborative operation and special transportation, realizing refined identification and quantitative evaluation of risks. The full voyage dynamic assessment result is generated by fusing voyage planning and sea state prediction data, and the warning instruction set containing area compensation parameters is output, so that the risk response is more targeted and forward-looking, and the fleet can take measures such as reinforcement, power optimization and emergency scheduling in time, effectively reducing safety hazards and ensuring transportation safety. BRIEF DESCRIPTION OF DRAWINGS

[0009] Figure 1is a flowchart of a combination ship fleet safety risk assessment method based on data processing provided by an embodiment of the present application.

[0010] Figure 2 is a schematic diagram of a combination ship fleet safety risk assessment system based on data processing provided by an embodiment of the present application. DETAILED DESCRIPTION

[0011] Exemplary embodiments of the present disclosure will be described in greater detail below with reference to the accompanying drawings. Although exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments set forth herein. Rather, these embodiments are provided so that the present disclosure can be more thoroughly understood and the scope of the present disclosure can be accurately conveyed to those skilled in the art.

[0012] As Figure 1 shown, an embodiment of the present application proposes a combination ship fleet safety risk assessment method based on data processing, which comprises the following steps: Step 1: Collect four types of data through sensors on the main propulsion ship, the barge and the auxiliary function ship, including ship state data, connection device working condition data, navigation environment data and cargo safety parameters; Step 2: Transmit the four types of data through the data interaction channel of the inter-ship connection device, and after time-space alignment, discretize the spatial distribution data of the key areas of the ship to generate six groups of position data sets with three-dimensional space coordinate labels; Step 3: Based on the six groups of position data sets with three-dimensional space coordinate labels, perform regional feature analysis through pre-designed calculation logic to generate structure connection failure risk coefficient, cooperative operation out-of-control risk coefficient and special transportation safety risk coefficient; Step 4: Fuse the three types of risk coefficients with voyage planning data and sea state prediction data to generate full-segment dynamic risk assessment results and output risk warning instruction set containing regional compensation parameters.

[0013] In the embodiment of the present application, four types of core data are collected through sensors of the multi-type ship, covering the ship's own state, the connecting device working condition, the external environment and the cargo safety, providing comprehensive and key data support for risk assessment and reducing information blind area; through space-time alignment and key area discretization, the data is associated with the three-dimensional space coordinates of the ship, the precise mapping of data and physical area is established, the problem of fuzzy matching of data and risk position is solved, and the risk analysis can focus on specific key areas. Based on the spatialized data, three types of special risk coefficients are generated, which accurately quantify the core safety risks such as structural connection, cooperative operation and special transportation, realizing the refined identification and quantitative evaluation of risks. The voyage planning and sea state prediction data are fused to generate dynamic evaluation results for the whole voyage section, and the warning instructions containing regional compensation parameters are output, so that the risk response is more targeted and forward-looking, and the ship fleet can take measures such as reinforcement, power optimization and emergency scheduling in time, effectively reducing the safety hidden danger and ensuring the safety of transportation.

[0014] In a preferred embodiment of the present application, the above step 1 collects four types of data through sensors on the main propulsion ship, the barge and the auxiliary function ship, including ship state data, connecting device working condition data, navigation environment data and cargo safety parameters; the connecting device working condition data includes mechanical lock stress value, hydraulic circuit pressure fluctuation value and power transmission stability index.

[0015] In the embodiment of the present application, the main propulsion ship is equipped with an engine sensor to record the engine speed at an interval of 5 seconds, with the unit of revolutions per minute; the engine running stability is judged by continuously tracking the speed change, and the specific judgment standard is that if the speed fluctuation amplitude exceeds ±50 revolutions per minute within 1 minute, the engine state is marked as abnormal, and at the same time, the sensor synchronously records the fuel consumption rate; the barge is equipped with a hull inclination sensor to monitor the transverse inclination angle and the longitudinal inclination angle of the hull in real time, and the data recording interval is 1 second; when the inclination angle is monitored to exceed 5 degrees for 30 seconds continuously, it is judged that the hull is unevenly stressed, at which time the cargo distribution data of the barge needs to be retrieved for further analysis of the cause of uneven stress and investigation of whether the hull imbalance is caused by cargo displacement; the auxiliary function ship is installed with a navigation sensor to obtain its real-time speed and heading angle through satellite positioning technology, and the speed and heading angle data of the auxiliary function ship are compared with the corresponding data of the main propulsion ship to calculate the deviation value, for example, when the speed of the auxiliary function ship is 0.5 knots slower than that of the main propulsion ship and the heading deviation is 3 degrees, the deviation value can intuitively reflect the coordination of the overall navigation of the combined ship fleet.

[0016] For the mechanical-hydraulic connecting device, special sensors are deployed to accurately monitor three core indicators. The specific collection methods are as follows: a strain gauge sensor is installed at the metal connection of the mechanical lock. This sensor can real-time sense the deformation degree of the lock when it bears the towing force of the fleet and the impact force of the sea waves, and convert the deformation data into corresponding stress values, including tensile stress and compressive stress. The instantaneous stress is recorded every 0.1 seconds, and the average stress value and the maximum stress value within 10 seconds are dynamically calculated. When the maximum stress value reaches 90% of the design load limit of the lock, the mechanical lock state is marked as high risk, prompting timely inspection or maintenance. Pressure sensors are installed at the outlet of the hydraulic pump and the inlet of the hydraulic cylinder to continuously collect the real-time pressure of the hydraulic oil, with the unit being megapascal. The pressure fluctuation amplitude is calculated every 1 second, which is the difference between the maximum and minimum pressure values monitored within that second. For example, if the normal pressure range of the hydraulic system is 10-12 megapascal, and the pressure fluctuates to 9-13 megapascal within a certain 1 second, the pressure fluctuation value for that second is 4 megapascal. The larger the pressure fluctuation value, the worse the sealing performance of the hydraulic system or the more unstable the pump body operation. Voltage and current sensors are installed at the power interface of the connecting device to record the voltage and current values at intervals of 0.5 seconds. By comparing the rated voltage and the actual voltage, the voltage deviation rate is calculated. First, the difference between the actual measured voltage and the rated voltage is calculated, then the absolute value of the difference is divided by the rated voltage, and finally the result is multiplied by 100% to obtain the voltage deviation rate. For example, if the rated voltage of the connecting device power interface is 380 volts and the actual measured voltage is 360 volts, the difference between the actual voltage and the rated voltage is calculated, which is 360 volts minus 380 volts, resulting in a difference of -20 volts. Then, the absolute value of the difference (20 volts) is divided by the rated voltage of 380 volts, resulting in a value of approximately 0.0526. Finally, multiplying this result by 100% gives a voltage deviation rate of 5.3%. Next, the number of current fluctuations is counted, with 1 minute as a statistical period. The number of times the current value changes significantly, i.e., exceeds the normal stable range, is recorded within that period. For example, within a certain 1 minute, the current sensor monitors that the current value changes significantly more than 5 times, i.e., the current fluctuation frequency within that period is more than 5 times. Finally, the power transmission state is divided based on the voltage deviation rate and the current fluctuation frequency. The specific division criteria are as follows: when the voltage deviation rate is less than 3% and the current fluctuation frequency within 1 minute is less than 2 times per minute, the power transmission state is determined to be stable; when the voltage deviation rate is between 3% and 5% and the current fluctuation frequency within 1 minute is between 2 and 5 times per minute, the power transmission state is determined to be slightly fluctuating; when the voltage deviation rate is greater than 5% and the current fluctuation frequency within 1 minute is greater than 5 times per minute, the power transmission state is determined to be severely fluctuating.

[0017] Through the main propulsion ship and auxiliary function ship with environmental monitoring equipment, all-around collection of external navigation conditions data, specifically, in the main propulsion ship bow bottom installation wave sensor, every 2 seconds measure once wave vertical height, unit is meter, take 1 minute all measurement value average value as current wave height value, for example, after 10 wave height continuous measurement calculate average value; At the same time record 1 minute in monitoring the maximum wave height value; In the auxiliary function ship's mast top installation wind speed and direction sensor, every 1 second record once horizontal wind speed and wind direction, that is, with the north direction as 0 degrees, according to clockwise rotation angle calculation, to wind speed data carry out grade division, wherein wind speed < 5 m / s is breeze, wind speed is 10-15 m / s is strong wind, combine wind direction data judge its influence on the ship formation navigation resistance, for example, when the ship formation is in the state of sailing against the wind, the greater the wind speed, the greater the sailing resistance, need according to this adjust power output; Through satellite navigation system obtains the latitude and longitude data of the current position of the combined ship formation, associates the latitude and longitude data with the electronic chart database, extracts the key parameters of the current channel, including channel depth, unit meter, channel width, unit meter and obstacle distribution information, such as the specific location coordinates of reefs and shoals, when the actual channel depth extracted is less than 1.2 times, mark the channel position as a channel risk point, remind the fleet to adjust the route to avoid risks; according to different types of goods carried by the barge, deploy special sensors in the cargo hold and the surrounding area to monitor key safety indicators; for the open barge loaded with bulk cargo, install a laser ranging sensor inside the cargo hold, measure the accumulation height of the cargo in the cargo hold every 5 minutes, and calculate the change rate of the cargo accumulation height, for example, if the cargo accumulation height decreases by 5% in 1 hour, it is judged that there may be cargo displacement, at the same time, install a vibration sensor at the bottom of the cargo hold to record the vibration frequency of the cargo hold, when the vibration frequency exceeds 30% of the normal navigation vibration frequency of the ship, it is determined that the cargo accumulation is unstable, and timely fixation measures need to be taken; for the barge loaded with containers, install a tension sensor at the container fixing lock to monitor the fixing tension of the lock on the container in real time, in kilonewtons, when the monitoring value is lower than 80% of the rated tension value of the lock, it is determined that the container fixing is loose, at the same time, install a temperature sensor inside each container to record the internal temperature of the container and compare it with the external environment temperature, if the temperature difference between the two exceeds 10℃ and the internal temperature of the container continues to rise, further investigation is needed to determine whether there is a cargo heating problem to avoid safety accidents caused by cargo heating; for the sealed cargo hold transporting dangerous goods, install corresponding gas concentration sensors according to the type of dangerous goods, for example, install an electrochemical sensor for toxic gas and a catalytic combustion sensor for flammable gas, detect the concentration of the corresponding gas in the cargo hold every 10 seconds, in ppm, compare the detected gas concentration with the preset safety threshold, for example, the safety threshold of a certain toxic gas is 50ppm, if the measured value reaches 60ppm, an early warning is triggered immediately, at the same time, install a pressure sensor inside the cargo hold to monitor the air pressure in the cargo hold, in kilopascals, when the air pressure fluctuation amplitude exceeds ±2 kilopascals / hour, combined with the temperature change data in the cargo hold, it is comprehensively judged whether there is a dangerous goods leakage.

[0018] In a preferred embodiment of the present application, step 2 comprises: Step 200, based on the central control unit clock, time synchronization is performed on the sensor data of the six positions of the main propulsion ship bow connection part, the main propulsion ship stern connection part, the barge power transmission unit, the barge steering control unit, the auxiliary function ship dangerous goods monitoring unit, and the auxiliary function ship emergency execution unit, to obtain the synchronized data. Step 201, mapping the synchronized data to the physical space coordinates of the ship, wherein the data of the bow connection of the main propulsion ship is associated with the longitudinal 0-15% area of the ship body, the data of the stern connection of the main propulsion ship is associated with the longitudinal 85-100% area of the ship body, the data of the barge power transmission unit is associated with the length direction 25-35% area of the barge, the data of the barge steering control unit is associated with the length direction 75-85% area of the barge, the data of the dangerous goods monitoring unit of the auxiliary function ship is associated with the 40-60% area of the ship's amidships, and the data of the emergency execution unit of the auxiliary function ship is associated with the 5-15% area of the bow of the ship. Step 202, output six sets of position data sets with three-dimensional space coordinate labels, wherein the coordinate labels include longitude, latitude, height, physical area and timestamp information.

[0019] In the embodiment of the application, the central control unit first establishes a unified reference clock accurate to the millisecond level, which is calibrated with the local clocks of the main propulsion ship, the barge and the auxiliary function ship through a time synchronization protocol inside the ship, such as the NTP protocol. After calibration, the clock deviation of all ships is controlled within 0.1 seconds. After completing the clock calibration, the system performs time alignment operation on the sensor data of the six key positions, that is, for the sensors of the bow connection of the main propulsion ship and the stern connection of the main propulsion ship, such as stress sensors and pressure sensors, when acquiring the collected data, a reference timestamp of the central control unit is added to each data. For example, the time recorded when a certain stress data is collected locally on the main propulsion ship is 14:30:05.123, and after calibration with the reference clock, it is uniformly marked as the reference time 14:30:05.120. For the data collected by the barge power transmission unit, such as power sensors, and the barge steering control unit, such as angle sensors, the local collection time is also calibrated according to the reference clock, so as to eliminate the time difference caused by the communication delay between the ships. For example, the barge data transmission to the central control unit needs 0.05 seconds, so that the data timestamp is matched with the reference clock by adding 0.05 seconds to the local collection time of the barge. The data of the dangerous goods monitoring unit of the auxiliary function ship, such as temperature sensors, and the emergency execution unit of the auxiliary function ship, such as response time sensors, are added with reference timestamps according to the same time calibration logic. Through the above operation, all sensor data are unified as the reference time of the central control unit, forming a time-synchronized data set, which effectively avoids subsequent analysis errors caused by time misalignment.

[0020] In step 201, the system first acquires the real-time physical parameters of each ship, specifically, the overall length of the main propulsion ship, barge and auxiliary function ship is preset in advance through the ship design parameters, for example, the overall length of the main propulsion ship is 100 meters, the overall length of the barge is 80 meters, and the overall length of the auxiliary function ship is 50 meters. After obtaining the overall length of the ship body, the time-synchronized data is associated with the specific physical area of the ship, that is, according to the overall length of the main propulsion ship body in the longitudinal direction, which is 100 meters, the physical range corresponding to the 0-15% area of the ship body in the longitudinal direction is calculated to be from the bow to the 15-meter position, and the calculation method is to multiply 100 meters by 15%. The data such as the stress of the connecting device and the hydraulic pressure collected by the sensor in this area are bound to this physical interval; the physical range corresponding to the 85-100% area of the ship body in the longitudinal direction is from the 85-meter position to the 100-meter position of the stern, and the calculation method is to multiply 100 meters by 85% to get 85 meters. The data such as the lock stress, power transmission stability index collected by the sensor in this area are associated with this physical interval; according to the overall length of the barge, which is 80 meters, the physical range corresponding to the 25-35% area of the barge in the length direction is calculated to be from the 20-meter position to the 28-meter position, and the calculation method is to multiply 80 meters by 25% to get 20 meters, and to multiply 80 meters by 35% to get 28 meters. The data such as the power distribution value and the power output stability collected by the sensor in this area are bound to this physical interval; the physical range corresponding to the 75-85% area of the barge in the length direction is from the 60-meter position to the 68-meter position, and the calculation method is to multiply 80 meters by 75% to get 60 meters, and to multiply 80 meters by 85% to get 68 meters. The data such as the steering angle, rudder operating state collected by the sensor in this area are associated with this physical interval; the physical range corresponding to the 40-60% area of the auxiliary function ship in the length direction is from the 20-meter position to the 30-meter position, and the calculation method is to multiply 50 meters by 40% to get 20 meters, and to multiply 50 meters by 60% to get 30 meters. The data such as the temperature, pressure and gas concentration of dangerous goods collected by the sensor in this area are bound to this physical interval; the physical range corresponding to the 5-15% area of the auxiliary function ship in the bow part is from the 2.5-meter position to the 7.5-meter position, and the calculation method is to multiply 50 meters by 5% to get 2.5 meters, and to multiply 50 meters by 15% to get 7.5 meters. The data such as the emergency response time and equipment start state collected by the sensor in this area are associated with this physical interval. Through the mapping operation of the above data and physical area, each time-synchronized data is assigned a clear physical area attribute, realizing the accurate correspondence between data and position.

[0021] In step 202, the system combines the real-time positioning information of each ship with the associated physical area attributes to add three-dimensional spatial coordinate labels to each piece of data, that is, by means of the GPS positioning systems carried by the main propulsion ship, the barge, and the auxiliary function ship, the longitude and latitude data of each ship are obtained in real time, wherein the accuracy of the longitude and latitude is controlled to be 6 decimal places, for example, 120.123456° east longitude and 30.654321° north latitude, which are used as the reference coordinates of the position of each ship itself. On the basis of obtaining the longitude and latitude of each ship itself, the relative positional relationship between the ships is determined, such as the barge being located 100 meters behind the main propulsion ship and the auxiliary function ship being located 50 meters to the left of the dangerous goods barge. The real-time longitude and latitude of each key area are calculated through spatial position. In the specific calculation, the longitude and latitude of each ship itself are set as the reference point coordinates, such as the longitude and latitude of the main propulsion ship as the reference point of the associated key area, and the longitude and latitude of the barge as the reference point of the associated key area. Then, the azimuth is determined according to the direction parameter in the relative positional relationship between the ships, for example, the barge is 180° azimuth relative to the rear of the main propulsion ship, that is, the south direction in the south-north direction; the auxiliary function ship is 270° azimuth relative to the left of the dangerous goods barge, that is, the west direction in the east-west direction. At the same time, the relative distance parameter is determined, which refers to the relative distance between each ship and the reference ship, such as the relative distance between the barge and the main propulsion ship being 100 meters, and the relative distance between the auxiliary function ship and the dangerous goods barge being 50 meters. Subsequently, the relative distance is decomposed into the distance components in the south-north direction and the east-west direction according to the determined azimuth, that is, the distance component in the south-north direction is used to calculate the latitude difference, 1 degree of latitude corresponds to an actual distance of about 111319 meters, so the latitude difference is equal to the distance component in the south-north direction divided by 111319 meters; the distance component in the east-west direction needs to be combined with the latitude of the reference point to calculate the longitude difference, that is, 1 degree of longitude corresponds to an actual distance of about 111319 meters multiplied by the cosine of the latitude, so the longitude difference is equal to the distance component in the east-west direction divided by (111319 meters multiplied by the cosine of the latitude of the reference point). If the key area is located north of the reference point, the distance component in the south-north direction is positive, the latitude difference is positive, and the latitude of the reference point is added; if the key area is located south of the reference point, the distance component in the south-north direction is negative, the latitude difference is negative, and the latitude of the reference point is subtracted (that is, subtraction); if the key area is located east of the reference point, the distance component in the east-west direction is positive, the longitude difference is positive, and the longitude of the reference point is added; if the key area is located west of the reference point, the distance component in the east-west direction is negative, the longitude difference is negative, and the longitude of the reference point is subtracted (that is, subtraction). Through such calculation, the real-time longitude and latitude corresponding to each key area of the ship are obtained, ensuring that the spatial coordinates of the six key areas can accurately reflect their actual positions.

[0022] Using sea level as the reference height, the initial elevation of six key areas is determined by combining the hull design parameters of each vessel. For example, the bow connection of the main propulsion vessel is 5 meters above sea level, and the power transmission unit of the barge is 3 meters above sea level. At the same time, the hull draft is monitored in real time by pressure sensors. The initial elevation is corrected based on the monitored draft data. For example, if the hull sinks by 0.5 meters due to draft, the initial elevation of that area is subtracted by 0.5 meters to obtain the corrected actual elevation. The system integrates all data from each key region according to a fixed format of longitude, latitude, altitude, physical region, and timestamp, ultimately generating six independent location datasets. Taking the dataset of the bow connection of the main propulsion ship as an example, it contains complete information such as longitude 120.123456°E, latitude 30.654321°N, altitude 5 meters, longitudinal 0-15% region of the hull, 14:30:05.120, and stress value XXX. The datasets of the other five key regions are also integrated in the same format to ensure that each dataset is complete and structurally consistent.

[0023] By using a unified reference clock to eliminate time discrepancies among various ship sensors, analysis errors caused by misaligned data acquisition times are avoided. Data is directly associated with key physical areas of the ship, such as connections and power units, clarifying the specific locations corresponding to the data and resolving the problem of ambiguity between data and risk point locations, enabling risk analysis to focus on specific areas.

[0024] In a preferred embodiment of the present invention, step 3 includes: Step 300: Based on six sets of location datasets with three-dimensional spatial coordinate labels, perform regional feature analysis to generate three types of risk coefficients. The generation process of the three types of risk coefficients is as follows: Step 301: Extract the location datasets of the 0-15% and 85-100% longitudinal regions of the hull. Combine the wave height and wind speed parameters in the navigation environment data, and calculate the structural connection failure risk coefficient by weighted superposition of the real-time stress value of the mechanical latch and the wave height and wind speed parameters. Step 302: Extract the location datasets of the 25-35% and 75-85% areas of the barge. Calculate the deviation between the actual power distribution values ​​recorded by the power transmission unit and the planned power values. Overlay the maximum error value between the real-time steering angle and the commanded angle recorded by the steering control unit. Generate a coordinated operation runaway risk coefficient according to a preset ratio, specifically including: Based on the location dataset of the 25-35% area of ​​the barge, the dynamic deviation between the actual power value allocated by the power transmission unit and the planned power value issued by the central control unit is calculated; based on the location dataset of the 75-85% area of ​​the barge, the maximum error value between the real-time steering angle of the steering control unit and the command angle of the central control unit during the coordinated operation is extracted. The dynamic deviation degree is taken as a first input factor, the maximum error value is taken as a second input factor, and weighting calculation is performed through preset first and second weight coefficients to generate a cooperative operation out-of-control risk coefficient representing the ship fleet power and turning collaborative out-of-control risk; In step 303, the temperature and pressure monitoring data of the dangerous goods in the 40-60% area of the ship center and the emergency response time record in the 5-15% area of the ship bow are extracted, and when the temperature and pressure data exceed the preset safety threshold, a special transportation safety risk coefficient is generated according to the corresponding relationship between the exceeding threshold amplitude and the emergency response time, specifically including: The temperature and pressure monitoring data in the 40-60% area of the ship center are subjected to threshold judgment, and when any parameter continuously exceeds the preset safety threshold, the exceeding amplitude value and the duration are recorded; the emergency response time record in the position data set in the 5-15% area of the ship bow is extracted, and the emergency response time is the measured time delay from triggering the early warning to starting the emergency operation of the auxiliary function ship; According to the product relationship of the exceeding amplitude value, the exceeding duration and the emergency response time, a special transportation safety risk coefficient representing the dangerous goods transportation out-of-control risk is generated.

[0025] In the embodiment of the application, the system selects the region data directly related to the three types of risks from six groups of position data sets with three-dimensional space coordinate tags, that is, the data of the 0-15% area of the ship body longitudinal direction of the main propulsion ship, that is, the ship head connection part, the 85-100% area, that is, the ship tail connection part, which are used to calculate the structure connection failure risk; the data of the 25-35% area of the barge, that is, the power transmission unit, the 75-85% area, that is, the turning control unit, which are used to calculate the cooperative operation out-of-control risk; the data of the 40-60% area of the auxiliary function ship, that is, the dangerous goods monitoring unit, the 5-15% area, that is, the emergency execution unit, which are used to calculate the special transportation safety risk, after the screening is completed, for each group of region data, the feature analysis is performed according to the preset logic, and finally three types of risk coefficients are generated, and the specific calculation process is divided into three steps: Step 301, first from the main propulsion ship hull longitudinal 0-15% area, that is, the position data set of the ship head connecting part, the real-time stress value of the mechanical lock is extracted, such data is recorded once every 0.5 seconds, including the tension, pressure and other parameters borne by the lock; At the same time, from the 85-100% area, that is, the position data set of the ship tail connecting part, the real-time stress value of the same type of mechanical lock is extracted, in addition, the current real-time wave height is extracted from the navigation environment data, such as the average wave height of 1.5 meters and the wind speed, such as the average wind speed of 10 meters / second, according to the historical navigation data and the ship design standard, different weights are given to the wave height and the wind speed, that is, the direct impact force of the wave height on the ship connecting part is greater, and the weight is set to 60%; The wind speed indirectly increases the load of the connecting part by affecting the ship sway, and the weight is set to 40%, the environmental influence value is calculated first, the calculation method is that the wave height is multiplied by the corresponding weight, and then the wind speed is multiplied by the corresponding weight, the higher the environmental influence value, the greater the load of the environment on the connecting part; Then calculate the structure stress basic value, take the average value of the mechanical lock stress value of the ship head connecting part and the ship tail connecting part, take the ship head stress value 200MPa and the ship tail stress value 180MPa as an example, first add the two stress values, get 380MPa, then divide by 2, get the average value 190MPa, this average value is the structure stress basic value, finally calculate the comprehensive value, since the structure stress itself is the core risk source, the environmental influence value and the structure stress basic value are superimposed according to the proportion of 1:9, that is, the environmental influence value is multiplied by 1, and then the structure stress basic value is multiplied by 9, the result is the comprehensive value, the higher the comprehensive value, the greater the possibility of structure connection failure, according to this, the structure connection failure risk coefficient is generated, if the comprehensive value is in the range of 0 to 500, it corresponds to low risk; If in the range of 501 to 1000, it corresponds to medium risk; If above 1000, it corresponds to high risk.

[0026] Step 302, the cooperative operation out-of-control risk coefficient calculation is divided into three links of dynamic deviation degree calculation, maximum steering angle error calculation and weighted risk coefficient calculation. From the barge 25-35% area, i.e. the position data set of the power transmission unit, the actual power distribution value is extracted, for example, the actual power transmitted to the barge at a certain moment is 800kW; At the same time, the planned power value at the same time is called from the central control unit, for example, the planned power value is 1000kW, the calculation method of dynamic deviation degree is to calculate the difference between the planned power value and the actual power value first, then divide the difference by the planned power value, and finally multiply the result by 100%; From the barge 75-85% area, i.e. the position data set of the steering control unit, the real-time steering angle within 5 minutes is extracted, for example, the actual steering angles are 28 degrees, 29 degrees and 27 degrees when the instruction requires steering 30 degrees; Then compare these real-time steering angles with the instruction steering angle issued by the central control unit, such as 30 degrees, calculate the difference between each real-time angle and the instruction angle, and then find the maximum value from these differences, which is the maximum steering angle error. For example, the real-time angles 27 degrees, 28 degrees and 29 degrees are compared with the instruction angle 30 degrees, the differences are 3 degrees, 2 degrees and 1 degree respectively, and the maximum difference is 3 degrees, i.e. the maximum steering angle error is 3 degrees; A first weight coefficient is preset, corresponding to a power deviation degree of 60%, because power distribution is the core of cooperative operation; A second weight coefficient is preset, corresponding to a steering angle error of 40%, because steering accuracy will affect the overall heading of the fleet; When calculating, first multiply the dynamic deviation degree by the first weight coefficient, for example, 20% multiplied by 60% gives 12%; Then process the maximum steering angle error, assuming that each degree of angle error corresponds to a risk proportion of 1%, first multiply the maximum steering angle error by 1% to get the risk proportion corresponding to the angle error, then multiply the proportion by the second weight coefficient, for example, 3 degrees multiplied by 1% gives a risk proportion of 3%, and then multiplied by 40% gives 1.2%; Finally, add the two converted results, 12% plus 1.2% gives 13.2%, which is the cooperative operation out-of-control risk coefficient, the higher the value, the higher the risk.

[0027] Step 303, the calculation of the special transport safety risk coefficient is divided into four parts: threshold judgment and parameter recording, recording the duration of exceedance, extracting the emergency response time, and calculating the coefficient based on the product relationship. From the 40-60% area amidships of the auxiliary function vessel, i.e., the location data of the dangerous goods monitoring unit, the real-time temperature and pressure of the dangerous goods are extracted. For example, the preset safe temperature threshold for a certain chemical is 30℃, the measured temperature is 35℃, the preset safe pressure threshold is 0.5MPa, and the measured pressure is 0.6MPa. When either the temperature or pressure parameter continuously exceeds the preset safe threshold... When the temperature remains at 35℃ for 5 consecutive minutes, calculate and record the exceedance value. The exceedance value is calculated by subtracting the preset safety threshold from the measured value. The temperature exceedance is 35℃ minus 30℃, resulting in 5℃. The pressure exceedance is 0.6MPa minus 0.5MPa, resulting in 0.1MPa. The larger of the two values ​​is taken as the primary parameter. The cumulative duration of this period is recorded from the moment the temperature (or pressure) exceeds the preset safety threshold for the first time until the current moment. For example, from the moment the temperature is first detected to 35℃ until... Currently, the cumulative duration is 5 minutes. Emergency response time is extracted from the location data of the emergency execution unit in the 5-15% area of ​​the bow of the auxiliary function vessel. This time is the measured delay from the moment the temperature (or pressure) exceeds the threshold triggering the warning signal (e.g., when the temperature reaches 35℃, the system automatically alarms) to the moment the emergency execution unit of the auxiliary function vessel initiates the corresponding emergency operation, such as activating the cooling device. For example, the measured delay from the alarm to the activation of the cooling device is 10 seconds. The exceedance amplitude value, exceedance duration, and emergency response time are standardized in units, i.e., the exceedance amplitude value, such as... The 5℃ value remains unchanged; the duration exceeding the limit needs to be converted to seconds. For example, 5 minutes equals 60 seconds, so 5 minutes multiplied by 60 seconds equals 300 seconds; the emergency response time, such as 10 seconds, remains unchanged. The standardized values ​​of the three are multiplied together, i.e., 5℃ multiplied by 300 seconds, then multiplied by 10 seconds, to obtain the product. The higher the product value, the higher the risk. For example, a product value in the range of 10,000-20,000 corresponds to medium risk; a product value above 20,000 corresponds to high risk. Based on this, a special transportation safety risk coefficient is generated.

[0028] By selectively extracting data from key areas and combining it with details such as environmental parameters and operational deviations, risks are quantified into specific coefficients, avoiding ambiguity in assessments and enabling intuitive judgment of risk points such as structural connections, collaborative operations, and special transportation. The three types of risk coefficients correspond to the most critical safety hazards of the combined fleet, namely connection failure, operational loss of control, and dangerous goods accidents, covering high-risk scenarios in the transportation process. The calculation logic of the risk coefficients is strongly correlated with actual navigation conditions, such as wave height and turning errors, and cargo status, such as temperature exceeding thresholds, improving the timeliness and effectiveness of fleet safety management.

[0029] In a preferred embodiment of the present application, the step 4 comprises: According to the range of the structural connection failure risk coefficient value, the head connection reinforcement instruction and the stern connection reinforcement instruction are generated; the cooperative operation out-of-control risk coefficient is decomposed into power compensation parameters and steering compensation parameters to generate power distribution optimization instructions and rudder angle correction instructions; and according to the special transportation safety risk coefficient level, the preset emergency resource scheduling scheme is matched to generate resource configuration instructions; The connection reinforcement instructions, the power distribution optimization instructions and the rudder angle correction instructions, and the resource configuration instructions are combined to output a full-segment dynamic risk early warning instruction set.

[0030] In the embodiments of the present application, the system presets three value ranges of the structure connection failure risk coefficient, the low risk is 0-30, the medium risk is 31-60, and the high risk is 61-100. Each range matches a corresponding reinforcement strategy. If the coefficient is in the low risk range, such as 25, a mild reinforcement instruction is generated. The instruction mainly promotes the hydraulic system of the ship head and stern connecting device to slightly increase the pressure by 10% of the original pressure, that is, the original pressure multiplied by 1.1, to slightly tighten the mechanical lock to enhance the connection stability. At the same time, the crew is prompted to check the connection state every 30 minutes. If the coefficient is in the medium risk range, such as 45, a moderate reinforcement instruction is generated. The hydraulic system pressure is increased by 30% of the original pressure, that is, the original pressure multiplied by 1.3. The mechanical lock is switched to the high-strength biting mode, and the vibration monitoring sensor of the connection part is started to feedback the reinforcement effect in real time. The crew needs to immediately go on duty and prepare emergency reinforcement tools. If the coefficient is in the high risk range, such as 70, an emergency reinforcement instruction is generated. The hydraulic system pressure is increased to the maximum safe value, that is, 90% of the design pressure, that is, the design pressure multiplied by 0.9. The mechanical lock is completely locked. At the same time, the auxiliary function ship is moved close to the connection part to enhance the structural strength through additional temporary support devices. The crew starts the connection failure emergency plan and suspends unnecessary navigation operations. The system will decompose the coordinated operation out-of-control risk coefficient into power compensation parameters and turning compensation parameters according to the preset proportion, wherein the power-related part accounts for 60%, and the turning-related part accounts for 40%, that is, the power compensation parameter is equal to the coordinated operation out-of-control risk coefficient multiplied by 60%, and the turning compensation parameter is equal to the coordinated operation out-of-control risk coefficient multiplied by 40%. According to the positive and negative values of the power compensation parameter, a positive value indicates power deficiency, and a negative value indicates power excess. The power output of the main propulsion ship to each barge is adjusted, for example, if the parameter is +15%, it means that 15% of additional power is needed, the instruction is to increase the power output of the main propulsion ship to the power transmission unit by 15%, that is, the original power output multiplied by 1.15, and the barge in the adverse wind and current direction is preferentially guaranteed. If the parameter is -10%, it means that the power is excessive by 10%, and the power output is reduced by 10%, that is, the original power output multiplied by 0.9. Avoiding power waste or hull overload; according to the value of the turning compensation parameter, in degrees, the rudder angle of the barge turning control unit is corrected, for example, if the parameter is +3°, it means that the actual turning angle is 3° smaller than the instruction, the instruction turning control unit increases the rudder angle by 3°, that is, the original rudder angle plus 3°, to ensure that the fleet turns according to the preset route; if the parameter is -2°, it means that the actual turning angle is 2° larger than the instruction, so the rudder angle is reduced by 2°, that is, the original rudder angle minus 2°, to avoid the deviation of the fleet caused by excessive turning. The system divides the special transportation safety risk coefficient into three levels, level one is low risk, level two is medium risk, and level three is high risk. Each level corresponds to a set of preset emergency resource scheduling scheme. If the coefficient is level one, such as risk level 1, match the basic resource configuration scheme, instruct the auxiliary function ship's emergency execution unit to prepare the conventional fire-fighting equipment such as fire extinguisher, fire hose and protective articles such as gas mask, and ensure that the emergency passage is unobstructed without the need for additional mobilization of external resources; if the coefficient is level two, such as risk level 2, match the enhanced resource configuration scheme, in addition to the basic equipment, instruct the emergency execution unit to start the special handling device for dangerous goods, such as explosion-proof pump and neutralizing agent storage tank; at the same time, notify the nearby port emergency rescue team to be on standby and prepare to arrive for support within 1 hour; the ventilation system of the dangerous goods barge is switched to the strong exhaust mode to reduce the risk of gas concentration; if the coefficient is level three, such as risk level 3, match the emergency resource configuration scheme, immediately mobilize all available emergency resources, including all emergency equipment of the auxiliary function ship, such as high-pressure water gun, gas detection unmanned aerial vehicle, fire-fighting ship and medical ship of the nearby port; instruct the emergency execution unit to start the isolation rescue mode, such as closing the direct passage between the dangerous goods barge and other ships; at the same time, send a distress signal to the nearby maritime management department and request temporary control of the route to create space for emergency treatment. The system sorts the above generated connection reinforcement instructions, power distribution optimization instructions, rudder angle correction instructions and resource configuration instructions according to the emergency degree, such as emergency reinforcement instructions are prior to power optimization instructions, and resource configuration instructions directly related to safety are executed first, and adds a time stamp to each instruction, such as execute in the 2nd hour of the voyage, complete before entering the XX sea area, and the execution subject, such as the main propulsion ship crew, the auxiliary function ship emergency team. Finally, a structured dynamic risk warning instruction set for the whole voyage is formed, which is issued to the operation terminal of each ship through the central control system to ensure that the instructions can be directly executed.

[0031] The instruction generation is directly related to the specific value and grade of the risk coefficient, different risk levels correspond to different intensity of response measures, such as light / emergency reinforcement, to avoid excessive operation or insufficient response, and to improve risk processing efficiency; Abstract risk coefficient is converted into specific operation parameters, such as hydraulic pressure lifting ratio, rudder angle correction degree, and specific execution steps, such as mobilizing emergency equipment and notifying crew to work, so that the crew can directly operate without secondary interpretation, thereby shortening the emergency response time; The pre-set scheme matches the risk level to avoid blind mobilization of emergency resources, such as not wasting high-priced equipment in low-risk situations and concentrating resources for rapid response in high-risk situations, thereby optimizing resource utilization efficiency and reducing emergency costs.

[0032] As shown in Figure 2 The embodiment of the application also provides a combined fleet safety risk assessment system based on data processing, comprising: A data acquisition module is used to acquire four types of data, i.e., ship state data, connecting device working condition data, navigation environment data and cargo safety parameters, through sensors on the main propulsion ship, the barge and the auxiliary function ship; A conversion module is used to transmit the four types of data through the data interaction channel of the connecting device between the ships, and after time and space alignment, the data is discretized into spatial distribution data of the key areas of the ships, to generate six sets of position data sets with three-dimensional space coordinate labels; A calculation module is used to perform regional feature analysis through a pre-designed calculation logic based on the six sets of position data sets with three-dimensional space coordinate labels, to generate a structure connection failure risk coefficient, a cooperative operation out-of-control risk coefficient and a special transportation safety risk coefficient; An instruction generation module is used to fuse the three types of risk coefficients with voyage planning data and sea state prediction data, to generate a full-segment dynamic risk assessment result and output a risk warning instruction set containing regional compensation parameters.

[0033] It should be noted that the system is a system corresponding to the above method, and all the implementation manners in the above method embodiment are applicable to this embodiment and can achieve the same technical effects.

[0034] The embodiment of the application also provides a computing device, comprising a processor and a memory storing a computer program, wherein the computer program is run by the processor to execute the method as described above. All the implementation manners in the above method embodiment are applicable to this embodiment and can achieve the same technical effects.

[0035] The embodiment of the application also provides a computer readable storage medium storing instructions, which, when run on a computer, cause the computer to execute the method as described above. All the implementation manners in the above method embodiment are applicable to this embodiment and can achieve the same technical effects.

[0036] The above is the preferred embodiment of the present application, it should be noted that for those skilled in the art, without departing from the principles described in the present application, can also be made several improvements and refinements, these improvements and refinements should also be considered the scope of protection of the present application.

Claims

1. A method for assessing the safety risks of a combined fleet based on data processing, characterized in that, The method includes: Step 1: Collect four types of data through sensors on the main propulsion vessel, barge, and auxiliary function vessel, including vessel status data, connection device operating status data, navigation environment data, and cargo safety parameters. Step 2: The four types of data are transmitted through the data interaction channel of the ship-to-ship connection device. After spatiotemporal alignment, they are discretized into spatial distribution data of key ship areas, generating six sets of location datasets with three-dimensional spatial coordinate labels. Step 3: Based on six sets of location datasets with three-dimensional spatial coordinate labels, perform regional feature analysis through preset calculation logic to generate structural connection failure risk coefficient, collaborative operation runaway risk coefficient, and special transportation safety risk coefficient. Step 4: Integrate the three types of risk coefficients with the voyage planning data and sea state prediction data to generate a dynamic risk assessment result for the entire voyage and output a risk warning instruction set that includes regional compensation parameters.

2. The data processing-based combined fleet safety risk assessment method according to claim 1, characterized in that, The operating data of the connection device includes mechanical locking stress value, hydraulic circuit pressure fluctuation value, and power transmission stability index.

3. The data processing-based combined fleet safety risk assessment method according to claim 1, characterized in that, Step 2 includes: Using the clock of the central control unit as a reference, the sensor data at six locations—the bow connection of the main propulsion vessel, the stern connection of the main propulsion vessel, the power transmission unit of the barge, the steering control unit of the barge, the dangerous goods monitoring unit of the auxiliary function vessel, and the emergency execution unit of the auxiliary function vessel—are synchronized to obtain synchronized data. The synchronized data is mapped to the ship's physical space coordinates. Specifically, the data of the bow connection of the main propulsion vessel is associated with the longitudinal region of the hull (0-15%), the data of the stern connection of the main propulsion vessel is associated with the longitudinal region of the hull (85-100%), the data of the barge power transmission unit is associated with the longitudinal region of the barge (25-35%), the data of the barge steering control unit is associated with the longitudinal region of the barge (75-85%), the data of the auxiliary function vessel dangerous goods monitoring unit is associated with the midship region (40-60%), and the data of the auxiliary function vessel emergency execution unit is associated with the bow region (5-15%). Output six sets of location datasets with three-dimensional spatial coordinate labels, where the coordinate labels include longitude, latitude, altitude, physical region, and timestamp information.

4. The data processing-based combined fleet safety risk assessment method according to claim 1, characterized in that, Step 3 includes: Based on six sets of location datasets with three-dimensional spatial coordinate labels, regional feature analysis was performed to generate three types of risk coefficients. The generation process of the three types of risk coefficients is as follows: Extract the location datasets of the 0-15% and 85-100% longitudinal regions of the hull, combine them with the wave height and wind speed parameters in the navigation environment data, and calculate the structural connection failure risk coefficient by weighted superposition of the real-time stress value of the mechanical latch and the wave height and wind speed parameters. Extract the location datasets of the 25-35% and 75-85% areas of the barge, calculate the deviation between the actual power distribution value recorded by the power transmission unit and the planned power value, and superimpose the maximum error value between the real-time steering angle and the command angle recorded by the steering control unit to generate a collaborative operation loss of control risk coefficient according to a preset ratio. Extract temperature and pressure monitoring data of dangerous goods in 40-60% of the midship area and emergency response time records in 5-15% of the bow area. When the temperature and pressure data exceed the preset safety threshold, generate a special transportation safety risk coefficient based on the correspondence between the magnitude of the exceedance and the emergency response time.

5. The data processing-based combined fleet safety risk assessment method according to claim 4, characterized in that, The location datasets of the 25-35% and 75-85% areas of the barge are extracted. The deviation between the actual power distribution values ​​recorded by the power transmission unit and the planned power values ​​is calculated. This deviation is then overlaid with the maximum error value between the real-time steering angle and the commanded angle recorded by the steering control unit. A coordinated operation loss-of-control risk coefficient is generated according to a preset ratio, including: Based on the location dataset of the 25-35% area of ​​the barge, the dynamic deviation between the actual power value allocated by the power transmission unit and the planned power value issued by the central control unit is calculated; based on the location dataset of the 75-85% area of ​​the barge, the maximum error value between the real-time steering angle of the steering control unit and the command angle of the central control unit during the coordinated operation is extracted. Using dynamic deviation as the first input factor and maximum error as the second input factor, a weighted calculation is performed using a preset first weighting coefficient and a second weighting coefficient to generate a collaborative operation loss of control risk coefficient representing the risk of loss of control of fleet power and steering coordination.

6. The data processing-based combined fleet safety risk assessment method according to claim 4, characterized in that, Extract temperature and pressure monitoring data of dangerous goods from 40-60% of the midship area and emergency response time records from 5-15% of the bow area. When the temperature and pressure data exceed a preset safety threshold, generate a special transportation safety risk coefficient based on the correlation between the magnitude of the threshold exceedance and the emergency response time, including: Threshold judgment is performed on the temperature and pressure monitoring data of the midship section 40-60% area. When any parameter continuously exceeds the preset safety threshold, the exceedance value and duration are recorded. Emergency response time records are extracted from the location data of the bow section 5-15% area. The emergency response time is the measured time delay from the triggering of the warning to the initiation of emergency operation by the auxiliary function ship. Based on the product relationship between the exceedance magnitude, exceedance duration, and emergency response time, a special transport safety risk coefficient representing the risk of uncontrolled transport of dangerous goods is generated.

7. The data processing-based combined fleet safety risk assessment method according to claim 1, characterized in that, Step 4 includes: Based on the range of structural connection failure risk coefficient values, generate bow connection reinforcement instructions and stern connection reinforcement instructions; decompose the risk coefficient of uncontrolled collaborative operation into power compensation parameters and steering compensation parameters, and generate power distribution optimization instructions and rudder angle correction instructions; based on the special transportation safety risk coefficient level, match the preset emergency resource scheduling plan to generate resource allocation instructions; By combining connection reinforcement commands, power distribution optimization commands, rudder angle correction commands, and resource allocation commands, a dynamic risk warning command set for the entire flight segment is output.

8. A data processing-based combined fleet safety risk assessment system, wherein the system implements the method as described in any one of claims 1 to 7, characterized in that, include: The data acquisition module is used to collect four types of data through sensors on the main propulsion vessel, barge, and auxiliary function vessel: ship status data, connection device operating status data, navigation environment data, and cargo safety parameters. The conversion module is used to transmit four types of data through the data interaction channel of the inter-ship connection device, and after spatiotemporal alignment, discretize them into spatial distribution data of key areas of the ship, generating six sets of location datasets with three-dimensional spatial coordinate labels. The calculation module is used to perform regional feature analysis based on six sets of location datasets with three-dimensional spatial coordinate labels, and generate structural connection failure risk coefficients, collaborative operation runaway risk coefficients, and special transportation safety risk coefficients through preset calculation logic. The instruction generation module is used to integrate the three types of risk coefficients with the voyage planning data and sea state prediction data to generate dynamic risk assessment results for the entire voyage and output a risk warning instruction set that includes regional compensation parameters.

9. A computing device, characterized in that, include: One or more processors; A storage device for storing one or more programs, which, when executed by one or more processors, cause the one or more processors to implement the method as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a program that, when executed by a processor, implements the method as described in any one of claims 1 to 7.

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