Ship safety monitoring platform based on cloud data and early warning processing method

Abstract

The invention discloses a ship safety monitoring platform based on cloud data and an early warning processing method, relates to the technical field of ship safety monitoring and early warning, and solves the technical problems that danger early warning analysis cannot be carried out according to ship navigation parameters, corresponding safety early warning measures are lacked, and safety influence is caused on whole ship navigation. The real-time parameters in the ship navigation process are acquired, the overall navigation state is analyzed based on the real-time parameters, the normal navigation condition and the abnormal navigation condition are independently analyzed, and when the normal condition is analyzed, the equipment parameters of the ship are monitored, so that the normal navigation condition is analyzed, and the ship navigation condition is monitored. According to the method, the navigation direction is adjusted in time, corresponding risk prediction is carried out on the basis of equipment parameters, the safety of overall navigation is improved, when abnormal conditions are analyzed, obstacles in the navigation direction are analyzed, corresponding navigation adjustment is carried out on the basis of the position parameters of the ship, the navigation direction is adjusted in time, and the safety of overall navigation is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of ship safety monitoring and early warning, and in particular to a ship safety monitoring platform and an early warning processing method based on cloud data. Background Art

[0002] The ship safety monitoring platform is a system that uses advanced technology to monitor and manage ships in real time, aiming to improve the safety and efficiency of ship operations.

[0003] According to Chinese patent publication number CN111409784A, a ship safety monitoring method based on a cloud data center is disclosed, wherein the cloud data center includes a monitoring platform, a ship data management platform, a ship positioning module and a ship communication module; the safety monitoring method includes the following steps: the operating personnel on the ship connect to the ship data management platform through the ship communication module, and upload the basic information of the ship to the ship data management platform; the management personnel assign a number to each ship connected to the ship data management platform on the ship data management platform, and the numbers of the ships are not repeated; the management personnel pre-set the safety range for each ship on the monitoring platform; the ship positioning module obtains the current position of the ship and sends it to the monitoring platform through the ship communication module; the monitoring platform determines whether the ship is within the safe driving range according to the pre-set current safety range of the ship.

[0004] The monitoring in the above patent is to monitor the safety of personnel, but some existing safety monitoring platforms lack safety warnings during the navigation of ships when monitoring the safety of ships, and cannot make corresponding danger warnings and analyses based on real-time ship navigation parameters, further affecting the overall navigation safety of ships. Summary of the invention

[0005] In view of the shortcomings of the prior art, the present invention provides a ship safety monitoring platform and an early warning processing method based on cloud data, which solves the problem that danger early warning analysis cannot be performed according to ship navigation parameters and there is a lack of corresponding safety early warning measures, which affects the safety of the overall ship navigation.

[0006] To achieve the above objectives, the present invention is implemented through the following technical solutions: A ship safety monitoring platform based on cloud data, comprising:

[0007] The data processing module is used to analyze the ship driving information transmitted by the ship information collection module, and analyze the transmitted driving information through the driving safety monitoring unit, judge the safety state of the ship driving, and generate safety state information, and the safety state information includes: driving safety results and driving unsafe results, and transmit the driving safety results to the normal driving monitoring unit, and transmit the driving unsafe results to the abnormal driving analysis unit;

[0008] The normal driving monitoring unit is used to analyze the obtained driving safety results, and continuously monitor the equipment parameters of the ship within a time period to determine the operating status of the corresponding equipment, and generate normal signals and abnormal signals. Then, the abnormal signals are analyzed based on historical data, and early warning analysis is performed on the ship. The early warning information is generated and transmitted to the monitoring information output unit;

[0009] The abnormal driving analysis unit is used to analyze the unsafe driving results obtained. It obtains the ship's position and analyzes the influence of the obstacle position in the area corresponding to the ship's position to generate an affecting signal and a non-affecting signal. At the same time, the affecting signal and the non-affecting signal are analyzed separately, and avoidance information is generated by adjusting the direction of the ship, and the avoidance information is transmitted to the monitoring information output unit.

[0010] As a further solution of the present invention: it also includes a ship information collection module, a data processing module and an intelligent display module, wherein the data processing module includes multiple functional units, specifically including: a driving safety monitoring unit, a normal driving monitoring unit, an abnormal driving analysis unit and a monitoring information output unit;

[0011] The ship information acquisition module is used to acquire the ship's driving information and transmit it to the data processing module;

[0012] The intelligent display module is used to display the obtained avoidance information, normal navigation signals and warning information to the corresponding operators through the intelligent display.

[0013] As a further solution of the present invention, the specific method in which the driving safety monitoring unit analyzes the transmitted driving information and determines the safety status of the ship's driving is:

[0014] Based on the ship's navigation parameters, the corresponding real-time navigation parameters are obtained, and the normal navigation parameters are obtained at the same time. Then the obtained normal navigation parameters are compared with the real-time navigation parameters. When the real-time navigation parameters are the same as the normal navigation parameters, a driving safety result is generated. Conversely, when the real-time navigation parameters are different from the normal navigation parameters, an unsafe driving result is generated.

[0015] As a further solution of the present invention: the specific manner in which the normal driving monitoring unit analyzes the obtained driving safety results is:

[0016] Obtain the equipment parameters of the ship, and compare the obtained ship equipment parameters with the normal working parameters. If the ship equipment parameters are different from the normal working parameters, it means that the corresponding equipment has an abnormal working condition, and a normal signal is generated. At the same time, the normal signal is transmitted to the monitoring information output unit. If the ship equipment parameters are the same as the normal working parameters, it means that the corresponding equipment is working normally, and an abnormal signal is generated, and the generated abnormal signal is analyzed.

[0017] As a further solution of the present invention: the specific manner in which the normal driving monitoring unit analyzes the abnormal signal is:

[0018] Obtain the corresponding abnormal ship equipment parameters, obtain the specific abnormal parameters, and obtain the normal working parameters, then calculate the difference between the abnormal parameters and the normal working parameters and record them as the abnormal difference, and obtain the historical data at the same time, and obtain the abnormal parameter data of the same type in the historical data, and then generate the risk level interval according to the obtained abnormal parameter data of the same type;

[0019] Match the abnormal parameters according to the risk level interval, generate risk level information, obtain corresponding associated parameters according to the abnormal parameters, and then obtain the risk level information corresponding to the associated parameters. If the risk level information corresponding to the associated parameters is the same as the risk level information corresponding to the abnormal parameters, the risk level information is used as the risk standard, and warning information is generated and transmitted to the monitoring information output unit;

[0020] If the risk level information corresponding to the associated parameters is different from the risk level information corresponding to the abnormal parameters, the associated parameter change value within the time period t is analyzed, and the associated parameter change value is matched with the corresponding risk level interval change value to obtain the associated risk level information. At the same time, the associated risk level information is used as a risk standard to generate early warning information, and the early warning information is transmitted to the monitoring information output unit.

[0021] As a further solution of the present invention: the specific manner in which the abnormal driving analysis unit analyzes the safe driving result is:

[0022] The ship position is obtained, and a safety zone with a radius of D is established with the ship position as the center. All obstacles in the safety zone are obtained and labeled as i, and i=1, 2, ..., j, where j represents the number of obstacles. The coordinates corresponding to obstacle i are obtained at the same time. Then, based on the ship's sailing direction, it is determined whether obstacle i is located in the sailing direction. If it exists in the sailing direction, the corresponding obstacle is marked as an obstacle to be analyzed. Otherwise, if it does not exist in the sailing direction, the corresponding obstacle is marked as an obstacle with no impact.

[0023] As a further solution of the present invention: the specific manner in which the abnormal driving analysis unit analyzes the obstacle to be analyzed is:

[0024] Obstacles to be analyzed are obtained, and a safe avoidance area with a radius of R is obtained with the position of the obstacle to be analyzed as the center of the circle. Based on the safe avoidance area and the safe area, corresponding tangent lines are generated, and the angle between the tangent lines and the navigation direction is obtained as the deflection angle. Then, corresponding avoidance information is generated based on 1.5 times the deflection angle, and the avoidance information is transmitted to the monitoring information output unit.

[0025] As a further solution of the present invention: the specific method in which the abnormal driving analysis unit analyzes the non-influencing obstacle is:

[0026] Obtain all non-impacting obstacles, calculate the straight-line distance between the non-impacting obstacles and the navigation direction, select the non-impacting obstacle corresponding to the smallest straight-line distance as the analysis object, and use the coordinates of the analysis object as the center of the circle to obtain the avoidance safety area with a radius of R1. At the same time, analyze the avoidance safety area and the safety area to determine whether the two intersect. If the two do not intersect, no processing is done and a normal navigation signal is generated. Otherwise, if the two intersect, the tangent line and deflection angle between the safety areas are obtained, and the corresponding avoidance information is generated based on 1.5 times the deflection angle, and the avoidance information is transmitted to the monitoring information output unit.

[0027] A ship safety early warning processing method based on cloud data, the method specifically comprises the following steps:

[0028] Step 1: Obtain the ship's driving information, and compare the ship's real-time navigation parameters based on normal navigation parameters to determine the ship's driving status and generate a safe driving result or an unsafe driving result;

[0029] Step 2: Analyze the driving safety results, continuously monitor the equipment parameters of the ship within the time period to determine the operating status of the corresponding equipment, and generate normal signals and abnormal signals. Then, analyze the abnormal signals based on historical data, conduct early warning analysis on the ship, and generate early warning information;

[0030] Step 3: Analyze the unsafe driving results obtained by acquiring the ship's position and analyzing the influence of the obstacle position in the area corresponding to the ship's position to generate an influence signal and a non-influence signal. At the same time, analyze the influence signal and the non-influence signal separately, and generate avoidance information by adjusting the ship's direction;

[0031] Step 4: Display the generated warning information and avoidance information to the corresponding operators.

[0032] The present invention provides a ship safety monitoring platform and early warning processing method based on cloud data. Compared with the prior art, it has the following beneficial effects:

[0033] The present invention acquires real-time parameters during the navigation of a ship, analyzes the overall navigation status based on the real-time parameters, and separately analyzes normal navigation conditions and abnormal navigation conditions. When analyzing normal conditions, the equipment parameters of the ship are monitored, and corresponding risk predictions are made based on the equipment parameters to discover potential problems of the ship and improve the overall navigation safety. Secondly, when analyzing abnormal conditions, obstacles in the navigation direction are analyzed and corresponding navigation adjustments are made based on the position parameters of the ship, so that the navigation direction is adjusted in time to improve the overall navigation safety. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] Figure 1 This is a schematic diagram of the security monitoring platform of the present invention;

[0035] Figure 2 This is a schematic diagram of ship avoidance according to the present invention;

[0036] Figure 3 This is a flow chart of the safety warning processing method of the present invention. DETAILED DESCRIPTION

[0037] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0038] For example, see Figure 1 and Figure 2 The present application provides a ship safety monitoring platform based on cloud data, which specifically includes a ship information acquisition module, a data processing module and an intelligent display module, and the above-mentioned units are unidirectionally electrically connected.

[0039] The data processing module includes multiple functional units, including: a driving safety monitoring unit, a normal driving monitoring unit, an abnormal driving analysis unit and a monitoring information output unit.

[0040] The ship information acquisition module is used to acquire the ship's driving information and transmit it to the data processing module. The ship's driving information includes the ship's position, the ship's driving direction, the ship's acceleration and the ship's angular velocity.

[0041] The data processing module is used to analyze the acquired ship driving information, and analyze the transmitted driving information through the driving safety monitoring unit, judge the safety status of the ship's driving, and generate safety status information, and the safety status information includes: driving safety results and driving unsafe results. The specific way to generate the safety status information is:

[0042] By receiving satellite signals, the position, speed and heading of the ship are accurately determined, and the specific acquisition method is to obtain them through multiple sets of sensors installed on the ship, and use sensors such as accelerometers and gyroscopes to measure the acceleration and angular velocity of the ship, so as to infer the position and attitude of the ship. For example, the speed change of the ship can be calculated according to the integral of the acceleration, and the current speed can be determined in combination with the initial speed. By integrating the angular velocity and referring to the initial attitude, the attitude information of the ship can be continuously updated, and the normal navigation parameters are obtained at the same time. The normal route parameters here represent the designated route parameters corresponding to the ship, and the designated route parameters are set by the operator. Then the obtained normal navigation parameters are compared with the real-time navigation parameters, and the real-time navigation parameters here represent the inferred position and attitude of the ship;

[0043] When the real-time navigation parameters are the same as the normal navigation parameters, it means that the ship's driving state is safe, and a driving safety result is generated. On the contrary, when the real-time navigation parameters are different from the normal navigation parameters, it means that the ship's driving state is abnormal, and an unsafe driving result is generated. The safe driving result is transmitted to the normal driving monitoring unit, and the unsafe driving result is transmitted to the abnormal driving analysis unit.

[0044] Normal driving monitoring unit, which is used to analyze the driving safety results obtained, and continuously monitor the equipment parameters of the ship within a time period to determine the operating status of the corresponding equipment, and generate normal signals and abnormal signals. Then, the abnormal signals are analyzed based on historical data, and the ship is warned and analyzed, and warning information is generated. At the same time, the warning information is transmitted to the monitoring information output unit, and the specific method of generating the warning information is:

[0045] Obtain the equipment parameters of the ship, where the equipment parameters include engine parameters, electrical system parameters and liquid level parameters. The engine parameters include speed, temperature, pressure, etc. The electrical system parameters include voltage, current, power and other parameters of the electrical system. The liquid level parameters include the liquid levels of ship fuel, fresh water, ballast water, etc., and compare the obtained ship equipment parameters with the normal working parameters. The normal working parameters here represent the corresponding working parameters of the corresponding equipment under normal working conditions. For example, the speed and temperature corresponding to the engine parameters. Under normal working conditions, the engine speed is 2000 rpm and the corresponding temperature is 40°C. If the ship equipment parameters are different from the normal working parameters, then It indicates that the corresponding equipment has an abnormal working condition, and generates a normal signal, and transmits the normal signal to the monitoring information output unit. If the ship equipment parameters are the same as the normal working parameters, it means that the corresponding equipment is working normally, and generates an abnormal signal, and analyzes the generated abnormal signal. Specifically, the parameters are compared here by calculating the difference between the two and judging the difference. For example, under normal circumstances, the corresponding difference interval is one tenth of the normal working parameters, which means that the speed difference is normal within 200, and if it exceeds 200, it indicates abnormal speed. For temperature, the difference is normal within 5°C, and the difference exceeds 5°C.

[0046] For example, when the ship is sailing, the system monitors the engine speed and temperature in real time. If the engine speed is detected to be 1800 rpm, which is lower than the normal operating speed of 2000 rpm, or the temperature is 45°C, which is higher than the normal operating temperature of 40°C, then the system will determine that the engine is operating abnormally, generate an abnormal signal and transmit it to the monitoring information output unit.

[0047] The generated abnormal signal is analyzed to obtain the corresponding abnormal ship equipment parameters, and the specific abnormal parameters are obtained at the same time. The specific abnormal parameters here represent the specific parameters in the corresponding equipment parameters of the same type. For example, the abnormal ship setting parameter is the engine parameter abnormality, and the corresponding speed abnormality in the engine parameter abnormality, then the motor speed abnormality is recorded as the abnormal parameter, and the normal working parameter is obtained. Then the difference between the abnormal parameter and the normal working parameter is calculated and recorded as the abnormal difference. At the same time, historical data is obtained, and the same type of abnormal parameter data in the historical data is obtained. The same type of abnormal parameters obtained here and the abnormal parameters belong to the same type of data. For example, if the abnormal parameter is an engine parameter, the corresponding abnormal parameter of the same type obtained is also an engine parameter. Then, a risk level interval is generated according to the obtained abnormal parameter data of the same type. Specifically, the corresponding risk level interval is generated according to the abnormal engine speed. When the speed is [1800-1900], it is a first-level risk, when the speed is [1901-1999], it is a second-level risk, and when the speed is [2100-2200], it is a third-level risk.

[0048] According to the risk level interval, the abnormal parameters are interval matched, and the risk level information is generated. At the same time, the corresponding associated parameters are obtained according to the abnormal parameters. The associated parameters here represent parameters that are proportional to the abnormal parameters. For example, when the engine speed increases, the corresponding engine temperature also increases. The engine speed and temperature are further recorded as associated parameters. Then, the risk level information corresponding to the associated parameters is obtained. If the risk level information corresponding to the associated parameters is the same as the risk level information corresponding to the abnormal parameters, the risk level information is used as the risk standard, and warning information is generated at the same time, and the warning information is transmitted to the monitoring information output unit. If the risk level information corresponding to the associated parameters is different from the risk level information corresponding to the abnormal parameters, the associated parameter change value within the time period t is analyzed, and the associated parameter change value is matched with the corresponding risk level interval change value to obtain the associated risk level information. At the same time, the associated risk level information is used as the risk standard to generate warning information, and the warning information is transmitted to the monitoring information output unit. The specific risk level interval will perform corresponding bundling analysis on the corresponding associated parameters, and generate the risk level interval of the associated parameters. Further, when matching the associated parameters, the associated parameters are matched with the corresponding associated parameter risk level interval to obtain the corresponding risk level.

[0049] The monitoring information output unit is used to transmit the acquired warning information to the intelligent display module.

[0050] Embodiment 2, as Embodiment 2 of the present invention, is implemented on the basis of Embodiment 1, and differs from Embodiment 1 in that.

[0051] The abnormal driving analysis unit is used to analyze the unsafe driving results obtained, obtain the ship position, and analyze the influence of the obstacle position in the area corresponding to the ship position to generate an influence signal and a non-influence signal, and analyze the influence signal and the non-influence signal respectively, and generate avoidance information by adjusting the direction of the ship, and transmit the avoidance information to the monitoring information output unit. The specific method of generating the avoidance information is:

[0052] The ship position is obtained, and a safety zone with a radius of D is established with the ship position as the center. The specific value of the radius D is set by the operator. All obstacles in the safety zone are obtained and labeled as i, and i=1, 2, ..., j, where j represents the number of obstacles. The coordinates corresponding to obstacle i are obtained at the same time. Then, based on the ship's sailing direction, it is determined whether obstacle i is located in the sailing direction. If it exists in the sailing direction, the corresponding obstacle is marked as an obstacle to be analyzed. Otherwise, if it does not exist in the sailing direction, the corresponding obstacle is marked as an obstacle without impact.

[0053] The specific method of analyzing and processing the obstacle to be analyzed is: obtain the obstacle to be analyzed, and at the same time, take the position of the obstacle to be analyzed as the center of the circle, obtain the avoidance safety area with a radius of R, and the specific value of the radius R is set by the operator, and generate the corresponding circle tangent based on the avoidance safety area and the safety area. The details are as shown in the attached Figure 2 As shown, the angle between the tangent line of the circle and the navigation direction is obtained as the deflection angle, and then the corresponding avoidance information is generated based on 1.5 times the deflection angle. At the same time, the avoidance information is transmitted to the monitoring information output unit. For example, if the angle between the tangent line of the circle and the navigation direction is 30 degrees, the deflection angle corresponding to the avoidance information is 1.5×30=45 degrees, so the deflection angle corresponding to the avoidance information is 45 degrees.

[0054] The specific method for analyzing and processing the non-impact obstacles is as follows: obtain all non-impact obstacles, calculate the straight-line distance between the non-impact obstacles and the navigation direction, and select the non-impact obstacle corresponding to the smallest straight-line distance as the analysis object. At the same time, take the coordinates of the analysis object as the center of the circle to obtain the avoidance safety area with a radius of R1, and analyze the avoidance safety area and the safety area to determine whether the two intersect. Here, it is determined whether there is a circle intersection or tangency between the safety area circle and the avoidance safety area circle. If the two do not intersect, they are not processed and a normal navigation signal is generated. Otherwise, if the two intersect, the tangent line and deflection angle between the safety areas are obtained, and the corresponding avoidance information is generated based on 1.5 times the deflection angle, and the avoidance information is transmitted to the monitoring information output unit.

[0055] Monitoring information output unit, which is used to transmit the acquired avoidance information and normal navigation signals to the intelligent display module.

[0056] An intelligent display module is used to display the obtained avoidance information, normal navigation signals and warning information to the corresponding operators through an intelligent display, where the intelligent display includes a touch screen display, a mobile tablet, etc.

[0057] Embodiment 3, as the embodiment 3 of the present invention, focuses on combining the implementation processes of embodiment 1 and embodiment 2 for implementation.

[0058] Example 4, please refer to Figure 3 , a ship safety early warning processing method based on cloud data, the method specifically comprises the following steps:

[0059] Step 1: Obtain ship driving information, and compare the real-time navigation parameters of the ship based on normal navigation parameters, determine the state of the ship's driving to generate a safe driving result and an unsafe driving result, and the specific state judgment method is the same as the analysis method of the data processing module in Example 1;

[0060] Step 2: Analyze the driving safety results, continuously monitor the equipment parameters of the ship within the time period to determine the operating status of the corresponding equipment, and generate normal signals and abnormal signals at the same time. Then, analyze the abnormal signals based on historical data, perform early warning analysis on the ship, and generate early warning information. The specific generation method is the same as the processing method of the normal driving monitoring unit in Example 1.

[0061] Step 3: Analyze the obtained unsafe driving results, obtain the ship position, and analyze the influence of the obstacle position in the area corresponding to the ship position to generate an influence signal and a non-influence signal, and analyze the influence signal and the non-influence signal respectively, and generate avoidance information by adjusting the ship direction. The specific processing method is the same as the processing method of the abnormal driving analysis unit in Example 2;

[0062] Step 4: Display the generated warning information and avoidance information to the corresponding operators.

[0063] Some of the data in the above formulas are dimensionless and numerically calculated. Meanwhile, the contents not described in detail in this specification belong to the prior art known to those skilled in the art.

[0064] The above embodiments are only used to illustrate the technical method of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical method of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical method of the present invention.

Claims

1. The ship safety monitoring platform based on cloud data is characterized by: include: The data processing module is used to analyze the ship driving information transmitted by the ship information collection module, and analyze the transmitted driving information through the driving safety monitoring unit, judge the safety state of the ship driving, and generate safety state information, and the safety state information includes: driving safety results and driving unsafe results, and transmit the driving safety results to the normal driving monitoring unit, and transmit the driving unsafe results to the abnormal driving analysis unit; The normal driving monitoring unit is used to analyze the obtained driving safety results, and continuously monitor the equipment parameters of the ship within a time period to determine the operating status of the corresponding equipment, and generate normal signals and abnormal signals. Then, the abnormal signals are analyzed based on historical data, and early warning analysis is performed on the ship. The early warning information is generated and transmitted to the monitoring information output unit; The abnormal driving analysis unit is used to analyze the unsafe driving results obtained. It obtains the ship's position and analyzes the influence of the obstacle position in the area corresponding to the ship's position to generate an affecting signal and a non-affecting signal. At the same time, the affecting signal and the non-affecting signal are analyzed separately, and avoidance information is generated by adjusting the direction of the ship, and the avoidance information is transmitted to the monitoring information output unit.

2. The cloud data-based ship safety monitoring platform according to claim 1, characterized in that: It also includes a ship information collection module, a data processing module and an intelligent display module, wherein the data processing module includes multiple functional units, specifically including: a driving safety monitoring unit, a normal driving monitoring unit, an abnormal driving analysis unit and a monitoring information output unit; The ship information acquisition module is used to acquire the ship's driving information and transmit it to the data processing module; The intelligent display module is used to display the obtained avoidance information, normal navigation signals and warning information to the corresponding operators through the intelligent display.

3. The cloud data-based ship safety monitoring platform according to claim 1, characterized in that: The specific method in which the driving safety monitoring unit analyzes the transmitted driving information and determines the safety status of the ship's driving is: Based on the ship's navigation parameters, the corresponding real-time navigation parameters are obtained, and the normal navigation parameters are obtained at the same time. Then the obtained normal navigation parameters are compared with the real-time navigation parameters. When the real-time navigation parameters are the same as the normal navigation parameters, a driving safety result is generated. Conversely, when the real-time navigation parameters are different from the normal navigation parameters, an unsafe driving result is generated.

4. The ship safety monitoring platform based on cloud data according to claim 1, characterized in that: The specific method in which the normal driving monitoring unit analyzes the obtained driving safety results is as follows: Obtain the equipment parameters of the ship, and compare the obtained ship equipment parameters with the normal working parameters. If the ship equipment parameters are different from the normal working parameters, it means that the corresponding equipment has an abnormal working condition, and a normal signal is generated. At the same time, the normal signal is transmitted to the monitoring information output unit. If the ship equipment parameters are the same as the normal working parameters, it means that the corresponding equipment is working normally, and an abnormal signal is generated, and the generated abnormal signal is analyzed.

5. The cloud data-based ship safety monitoring platform according to claim 4 is characterized in that: The specific method of analyzing the abnormal signal by the normal driving monitoring unit is as follows: Obtain the corresponding abnormal ship equipment parameters, obtain the specific abnormal parameters, and obtain the normal working parameters, then calculate the difference between the abnormal parameters and the normal working parameters and record them as the abnormal difference, and obtain the historical data at the same time, and obtain the abnormal parameter data of the same type in the historical data, and then generate the risk level interval according to the obtained abnormal parameter data of the same type; Match the abnormal parameters according to the risk level interval, generate risk level information, obtain corresponding associated parameters according to the abnormal parameters, and then obtain the risk level information corresponding to the associated parameters. If the risk level information corresponding to the associated parameters is the same as the risk level information corresponding to the abnormal parameters, the risk level information is used as the risk standard, and warning information is generated and transmitted to the monitoring information output unit; If the risk level information corresponding to the associated parameters is different from the risk level information corresponding to the abnormal parameters, the associated parameter change value within the time period t is analyzed, and the associated parameter change value is matched with the corresponding risk level interval change value to obtain the associated risk level information. At the same time, the associated risk level information is used as a risk standard to generate early warning information, and the early warning information is transmitted to the monitoring information output unit.

6. The ship safety monitoring platform based on cloud data according to claim 1, characterized in that: The specific method in which the abnormal driving analysis unit analyzes the safe driving result is as follows: The ship position is obtained, and a safety zone with a radius of D is established with the ship position as the center. All obstacles in the safety zone are obtained and labeled as i, and i=1, 2, ..., j, where j represents the number of obstacles. The coordinates corresponding to obstacle i are obtained at the same time. Then, based on the ship's sailing direction, it is determined whether obstacle i is located in the sailing direction. If it exists in the sailing direction, the corresponding obstacle is marked as an obstacle to be analyzed. Otherwise, if it does not exist in the sailing direction, the corresponding obstacle is marked as an obstacle with no impact.

7. The cloud data-based ship safety monitoring platform according to claim 6, characterized in that: The specific method in which the abnormal driving analysis unit analyzes the obstacle to be analyzed is as follows: Obstacles to be analyzed are obtained, and a safe avoidance area with a radius of R is obtained with the position of the obstacle to be analyzed as the center of the circle. Based on the safe avoidance area and the safe area, corresponding tangent lines are generated, and the angle between the tangent lines and the navigation direction is obtained as the deflection angle. Then, corresponding avoidance information is generated based on 1.5 times the deflection angle, and the avoidance information is transmitted to the monitoring information output unit.

8. The cloud data-based ship safety monitoring platform according to claim 6 is characterized in that the specific manner in which the abnormal driving analysis unit analyzes the non-impact obstacles is: Obtain all non-impacting obstacles, calculate the straight-line distance between the non-impacting obstacles and the navigation direction, select the non-impacting obstacle corresponding to the smallest straight-line distance as the analysis object, and use the coordinates of the analysis object as the center of the circle to obtain the avoidance safety area with a radius of R1. At the same time, analyze the avoidance safety area and the safety area to determine whether the two intersect. If the two do not intersect, no processing is done and a normal navigation signal is generated. Otherwise, if the two intersect, the tangent line and deflection angle between the safety areas are obtained, and the corresponding avoidance information is generated based on 1.5 times the deflection angle, and the avoidance information is transmitted to the monitoring information output unit.

9. A ship safety early warning processing method based on cloud data, used to execute the ship safety monitoring platform based on cloud data according to any one of claims 1 to 8, characterized in that the method specifically comprises the following steps: Step 1: Obtain the ship's driving information, and compare the ship's real-time navigation parameters based on normal navigation parameters to determine the ship's driving status and generate a safe driving result or an unsafe driving result; Step 2: Analyze the driving safety results, continuously monitor the equipment parameters of the ship within the time period to determine the operating status of the corresponding equipment, and generate normal signals and abnormal signals. Then, analyze the abnormal signals based on historical data, conduct early warning analysis on the ship, and generate early warning information; Step 3: Analyze the unsafe driving results obtained by acquiring the ship's position and analyzing the influence of the obstacle position in the area corresponding to the ship's position to generate an influence signal and a non-influence signal. At the same time, analyze the influence signal and the non-influence signal separately, and generate avoidance information by adjusting the ship's direction; Step 4: Display the generated warning information and avoidance information to the corresponding operators.

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