Roo-ro passenger ship equipment operation data monitoring and early warning system and method

Abstract

The invention discloses a roll-on-off passenger ship equipment operation data monitoring and early warning system and method, and relates to the technical field of ships, the roll-on-off passenger ship equipment operation data monitoring and early warning system comprises a real-time monitoring module, a data analysis and decision module and an emergency response management module, the real-time monitoring module is used for collecting various data of ballast water in real time so as to ensure that the state of the ballast water is accurately known, and the real-time monitoring module is used for monitoring the state of the ballast water; the data analysis and decision module is used for analyzing the collected data and providing decision support so as to timely adjust the state of ballast water, and the emergency response management module is used for providing emergency response measures and guaranteeing ship safety when monitoring that the state of the ballast water is abnormal. The real-time monitoring module comprises a data acquisition sub-module, a sensor self-checking sub-module and a data uploading sub-module, the data acquisition sub-module and the sensor self-checking sub-module are electrically connected with the data uploading sub-module, and the system has the characteristic of accurate monitoring.

Description

Technical Field

[0001] The present invention relates to the field of ship technology, and in particular to a ro-ro passenger ship equipment operation data monitoring and early warning system and method. Background Art

[0002] Ro-Ro passenger ferry is a ship that transports both passengers and cargo. In modern shipping, in order to improve operational efficiency and ensure safety, the monitoring of equipment operation data of Ro-Ro passenger ferry has become particularly important. Various sensors are used to collect equipment operating parameters in real time, and the collected data is analyzed to timely detect equipment anomalies, predict failures, and optimize operations.

[0003] During the transportation of cargo by ro-ro passenger ships, if the ballast water monitoring sensor fails, it may be impossible to monitor the ballast water volume in real time, so that timely adjustments cannot be made when needed, which may cause the ship to lose balance, even tilt or sink. Therefore, it is necessary to design an accurate monitoring and early warning system for the operation data of ro-ro passenger ship equipment. Summary of the invention

[0004] The object of the present invention is to provide a ro-ro passenger ship equipment operation data monitoring and early warning system and method to solve the problems raised in the above background technology.

[0005] In order to solve the above technical problems, the present invention provides the following technical solutions: a ro-ro passenger ship equipment operation data monitoring and early warning system, including a real-time monitoring module, a data analysis and decision-making module, and an emergency response management module. The real-time monitoring module is used to collect various data of ballast water in real time to ensure accurate understanding of the ballast water status. The data analysis and decision-making module is used to analyze the collected data and provide decision support so as to adjust the ballast water status in time. The emergency response management module is used to provide emergency response measures to ensure the safety of the ship when abnormal ballast water status is detected.

[0006] According to the above technical solution, the real-time monitoring module includes a data acquisition submodule, a sensor self-check submodule, and a data upload submodule. The data acquisition submodule and the sensor self-check submodule are electrically connected to the data upload submodule. The data acquisition submodule is used to collect the capacity, cabin pressure and temperature information of the ballast water in real time through the water level sensor, the pressure sensor and the temperature sensor. The sensor self-check submodule is used to regularly self-check the functions and accuracy of all monitoring sensors to ensure that they are in normal working state and that sensors with faults are discovered in time. The data upload submodule is used to upload the collected data to the central control unit and the remote monitoring platform to ensure the real-time and accessibility of the data.

[0007] The data analysis and decision-making module includes a data processing submodule, a status assessment submodule, and a decision suggestion submodule. The data processing submodule is electrically connected to the data upload submodule, and the status assessment submodule is electrically connected to the decision suggestion submodule. The data processing submodule is used to clean, filter and process the uploaded data to ensure the accuracy and effectiveness of the analysis. The status assessment submodule performs real-time assessment of the current ballast water status based on data analysis and gives risk warnings. The decision suggestion submodule is used to generate adjustment suggestions based on the assessment results to increase or decrease the amount of ballast water and provide them to the crew for reference through the user interface;

[0008] The emergency response management module includes an alarm system submodule, an emergency handling submodule, and a maintenance management submodule. The alarm system submodule is electrically connected to the decision suggestion submodule, and the emergency handling submodule is electrically connected to the maintenance management submodule. The alarm system submodule is used to trigger an alarm when a crisis state is detected, that is, the ballast water weight, the cabin pressure and the ballast water temperature are not within the normal range, and notify the crew to take necessary measures. The emergency handling submodule is used to provide emergency operation guidance, including specific steps for adding water and draining water, to help the crew take quick action. The maintenance management submodule is used to record the maintenance history and usage of the sensor, remind the crew when replacement or maintenance is needed, and manage the spare parts library.

[0009] The ro-ro passenger ship equipment operation data monitoring and early warning method comprises the following steps:

[0010] S1. Data acquisition: The data acquisition submodule continuously collects the volume, pressure and temperature information of ballast water through water level sensors, pressure sensors and temperature sensors. The real-time data is recorded as a raw data stream, which contains the parameters provided by various sensors.

[0011] S2, sensor self-check: At the same time, the sensor self-check submodule is started regularly to self-check the function and accuracy of all monitoring sensors. The results of the self-check will be fed back to the monitoring module to ensure the normal operation of the sensor. If a faulty sensor is found, the spare parts management mechanism will be activated;

[0012] S3, data upload: The monitored data is uploaded to the central control unit and remote monitoring platform through the data upload submodule to ensure the real-time and accessibility of the data. The real-time uploaded data stream is stored for subsequent analysis and decision-making;

[0013] S4. Data analysis and decision support: After the data is uploaded, the data processing submodule in the data analysis and decision module receives the uploaded data, cleans, filters and processes it to ensure the integrity and accuracy of the data. Subsequently, the status assessment submodule analyzes the processed data, assesses the current ballast water status and generates risk warnings. Based on the risk assessment, it generates corresponding adjustment suggestions, such as increasing or decreasing ballast water, and displays the suggestions to the crew through the user interface;

[0014] S5. Emergency response: When the system detects abnormal ballast water status, it immediately triggers an alarm to notify the crew and provide specific emergency operation instructions, including steps for adding or draining water. The maintenance management submodule records the maintenance history of all operations and sensors to facilitate subsequent management and decision-making. The crew quickly executes necessary emergency measures based on the alarm and instructions and records the incident.

[0015] According to the above technical solution, in S2, the specific method of sensor self-test is:

[0016] S2-1, set the self-check schedule, and determine the frequency and time period of the self-check through the system configuration file;

[0017] S2-2, at the beginning of the self-test, the submodule communicates with various sensors through signals to collect the current status of the sensors, including basic parameters such as operating voltage, output signal, and response time;

[0018] S2-3. Perform specific functional tests for each sensor;

[0019] S2-4. Compare the result of the functional test with the standard value, analyze the output of each sensor, determine whether it is within the normal working range, and determine whether the function of the sensor is abnormal based on the set threshold.

[0020] According to the above technical solution, in S2-3, for the water level sensor: simulate different water levels and check whether its output meets the expected value through given resistance or current input; for the pressure sensor, apply known pressure for calibration to ensure that the output matches the actual pressure; for the temperature sensor: test the output value in a known temperature environment to verify its accuracy.

[0021] According to the above technical solution, in S4, the specific method of evaluating the current ballast water status and generating risk warning is:

[0022] S4-1. Capacity assessment: Check the current volume of ballast water and its ratio to the total weight of the ship to determine the center of gravity and stability of the ship;

[0023] S4-2, status assessment: Analyze water level, pressure, and temperature sensor data to determine whether there are foreign objects or pollution in the water;

[0024] S4-3. Trend analysis: Compare with historical data to analyze the changing trend of current data and identify potential risks, such as rapid water level changes or abnormal temperatures.

[0025] S4-4. Use algorithmic models, such as machine learning models, to evaluate the weight of ballast water over a period of time to assess whether there is an imminent danger, such as tilt or imbalance.

[0026] According to the above technical solution, in S4-4, the specific method of evaluating the weight of ballast water in the previous period and adjusting the drainage flow rate is:

[0027] In the next unit time, count the weight of ballast water s in a water storage tank i , where i is the next unit time, i-1 is the previous unit time, i-2 is the previous two unit time, and the ballast water weight s of a water storage tank in the previous unit time i-1 For comparison, when s i ≤s i-1 And s i-1 ≥s i-2 When the next unit time drainage flow A i unchanged, and still equal in value to the drainage flow rate A of the previous unit time i-1 , when s i >s i-1 hour

[0028]

[0029] Among them, α is the influence coefficient of ballast water weight change trend, β is the influence coefficient of ballast water weight, which is selected according to actual experience. i <s i-1 <s i-2 When

[0030]

[0031] The ratio of α and β is relatively small in the first few unit times of ballast water discharge. As the cumulative ratio per unit time increases, the flow rate is unstable in the early stage of drainage, so more reference is made to the weight of the previous unit time. In the later stage of drainage, the discharge flow rate is stable, and the change trend of weight can better reflect whether the ballast water is discharged smoothly.

[0032] According to the above technical solution, in S5, after performing the emergency operation, the system should continue to monitor the status of the ballast water to ensure that the operation is effective and respond to any new status changes in a timely manner. The status feedback after the emergency operation should be updated to the system in a timely manner to ensure the integrity and accuracy of the data to optimize subsequent early warnings and decisions. According to different alarm levels and status severity, set the corresponding emergency response process. For low-risk status, only recording and monitoring are required; for high-risk status, immediate operation is required.

[0033] Compared with the prior art, the beneficial effects achieved by the present invention are: the present invention can realize efficient and comprehensive ballast water monitoring and management. The real-time monitoring module ensures the timeliness and accuracy of the data, the data analysis and decision support module provides scientific decision-making basis for the crew, and the emergency response and management module ensures effective response in abnormal situations. This system design can significantly improve the safety of ships and reduce the risk of accidents caused by improper ballast water management. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0035] Figure 1 It is a schematic diagram of the overall module structure of the present invention. DETAILED DESCRIPTION

[0036] 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.

[0037] See also Figure 1 The present invention provides a technical solution: a ro-ro passenger ship equipment operation data monitoring and early warning system, including a real-time monitoring module, a data analysis and decision module, and an emergency response management module. The real-time monitoring module is used to collect various data of ballast water in real time to ensure accurate understanding of the ballast water status. The data analysis and decision module is used to analyze the collected data and provide decision support so as to adjust the ballast water status in time. The emergency response management module is used to provide emergency response measures to ensure the safety of the ship when abnormal ballast water status is detected;

[0038] The real-time monitoring module includes a data acquisition submodule, a sensor self-check submodule, and a data upload submodule. The data acquisition submodule and the sensor self-check submodule are electrically connected to the data upload submodule. The data acquisition submodule is used to collect the capacity, cabin pressure and temperature information of the ballast water in real time through the water level sensor, the pressure sensor and the temperature sensor. The sensor self-check submodule is used to regularly self-check the functions and accuracy of all monitoring sensors to ensure that they are in normal working state and to promptly discover sensors with faults. The data upload submodule is used to upload the collected data to the central control unit and the remote monitoring platform to ensure the real-time and accessibility of the data.

[0039] The data analysis and decision-making module includes a data processing submodule, a status assessment submodule, and a decision suggestion submodule. The data processing submodule is electrically connected to the data upload submodule, and the status assessment submodule is electrically connected to the decision suggestion submodule. The data processing submodule is used to clean, filter and process the uploaded data to ensure the accuracy and effectiveness of the analysis. The status assessment submodule conducts real-time assessment of the current ballast water status based on data analysis and gives risk warnings. The decision suggestion submodule is used to generate adjustment suggestions based on the assessment results to increase or decrease the amount of ballast water and provide them to the crew for reference through the user interface;

[0040] The emergency response management module includes an alarm system submodule, an emergency disposal submodule, and a maintenance management submodule. The alarm system submodule is electrically connected to the decision suggestion submodule, and the emergency disposal submodule is electrically connected to the maintenance management submodule. The alarm system submodule is used to trigger an alarm when a crisis state is detected, i.e., the ballast water weight, cabin pressure, and ballast water temperature do not meet the normal range, and notify the crew to take necessary measures. The emergency disposal submodule is used to provide emergency operation guidance, including specific steps for adding water and draining water, to help the crew take quick action. The maintenance management submodule is used to record the maintenance history and usage of the sensor, remind the crew when replacement or maintenance is required, and manage the spare parts library;

[0041] The ro-ro passenger ship equipment operation data monitoring and early warning method comprises the following steps:

[0042] S1. Data acquisition: The data acquisition submodule continuously collects the volume, pressure and temperature information of ballast water through water level sensors, pressure sensors and temperature sensors. The real-time data is recorded as a raw data stream, which contains the parameters provided by various sensors.

[0043] S2, sensor self-check: At the same time, the sensor self-check submodule is started regularly to self-check the function and accuracy of all monitoring sensors. The results of the self-check will be fed back to the monitoring module to ensure the normal operation of the sensor. If a faulty sensor is found, the spare parts management mechanism will be activated;

[0044] S3, data upload: The monitored data is uploaded to the central control unit and remote monitoring platform through the data upload submodule to ensure the real-time and accessibility of the data. The real-time uploaded data stream is stored for subsequent analysis and decision-making;

[0045] S4. Data analysis and decision support: After the data is uploaded, the data processing submodule in the data analysis and decision module receives the uploaded data, cleans, filters and processes it to ensure the integrity and accuracy of the data. Subsequently, the status assessment submodule analyzes the processed data, assesses the current ballast water status and generates risk warnings. Based on the risk assessment, it generates corresponding adjustment suggestions, such as increasing or decreasing ballast water, and displays the suggestions to the crew through the user interface;

[0046] S5. Emergency response: When the system detects abnormal ballast water status, an alarm is triggered immediately to notify the crew. At this time, specific emergency operation instructions are provided, including steps for adding water or draining water. The maintenance management submodule records the maintenance history of all operations and sensors to facilitate subsequent management and decision-making. The crew quickly executes necessary emergency measures based on the alarm and instructions, and records the incident;

[0047] In S2, the specific method of sensor self-test is:

[0048] S2-1, set the self-check schedule, and determine the frequency and time period of the self-check through the system configuration file;

[0049] S2-2, at the beginning of the self-test, the submodule communicates with various sensors through signals to collect the current status of the sensors, including basic parameters such as operating voltage, output signal, and response time;

[0050] S2-3. Perform specific functional tests for each sensor;

[0051] S2-4, comparing the result of the functional test with the standard value, analyzing the output of each sensor, judging whether it is within the normal working range, and judging whether the function of the sensor is abnormal according to the set threshold value;

[0052] In S2-3, for the water level sensor: simulate different water levels and check whether its output meets the expected value through a given resistance or current input; for the pressure sensor, apply a known pressure for calibration to ensure that the output matches the actual pressure; for the temperature sensor: test the output value under a known temperature environment to verify its accuracy;

[0053] In S4, the specific method for evaluating the current ballast water status and generating risk warnings is:

[0054] S4-1. Capacity assessment: Check the current volume of ballast water and its ratio to the total weight of the ship to determine the center of gravity and stability of the ship;

[0055] S4-2, status assessment: Analyze water level, pressure, and temperature sensor data to determine whether there are foreign objects or pollution in the water;

[0056] S4-3. Trend analysis: Compare with historical data to analyze the changing trend of current data and identify potential risks, such as rapid water level changes or abnormal temperatures.

[0057] S4-4. Use algorithmic models, such as machine learning models, to evaluate the weight of ballast water over the previous period of time to assess whether there is an imminent danger, such as tilting or imbalance;

[0058] In S4-4, the specific method for evaluating the weight of ballast water in the previous period and adjusting the discharge flow is:

[0059] In the next unit time, count the weight of ballast water s in a water storage tank i , where i is the next unit time, i-1 is the previous unit time, i-2 is the previous two unit time, and the ballast water weight s of a water storage tank in the previous unit time i-1 For comparison, when s i ≤s i-1 And s i-1 ≥s i-2 When the next unit time drainage flow A i unchanged, and still equal in value to the drainage flow rate A of the previous unit time i-1 , when s i >s i-1 hour

[0060]

[0061] Among them, α is the influence coefficient of ballast water weight change trend, β is the influence coefficient of ballast water weight, which is selected according to actual experience. i <s i-1 <s i-2 When

[0062]

[0063] The ratio of α to β is relatively small in the first few unit times of ballast water discharge. As the cumulative ratio per unit time increases, the weight of the previous unit time is more referenced due to the unstable flow rate in the early stage of discharge. In the later stage of discharge, the discharge flow rate is stable, and the change trend of weight can better reflect whether the ballast water is discharged smoothly.

[0064] In S5, after performing the emergency operation, the system should continue to monitor the status of the ballast water to ensure that the operation is effective and respond to any new status changes in a timely manner. The status feedback after the emergency operation should be updated to the system in a timely manner to ensure the integrity and accuracy of the data to optimize subsequent early warnings and decisions. According to different alarm levels and status severity, set the corresponding emergency response process. For low-risk status, only recording and monitoring are required; for high-risk status, immediate operation is required.

[0065] Finally, it should be noted that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art can still modify the technical solutions described in the aforementioned embodiments or replace some of the technical features therein by equivalents. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. Ro-Ro passenger ship equipment operation data monitoring and early warning system, characterized by: It includes a real-time monitoring module, a data analysis and decision-making module, and an emergency response management module. The real-time monitoring module is used to collect various data of ballast water in real time to ensure accurate understanding of the ballast water status. The data analysis and decision-making module is used to analyze the collected data and provide decision support so as to adjust the ballast water status in time. The emergency response management module is used to provide emergency response measures to ensure the safety of the ship when abnormal ballast water status is monitored.

2. The ro-ro passenger ship equipment operation data monitoring and early warning system according to claim 1 is characterized by: The real-time monitoring module includes a data acquisition submodule, a sensor self-check submodule, and a data upload submodule. The data acquisition submodule and the sensor self-check submodule are electrically connected to the data upload submodule. The data acquisition submodule is used to collect the capacity, cabin pressure and temperature information of the ballast water in real time through a water level sensor, a pressure sensor and a temperature sensor. The sensor self-check submodule is used to regularly self-check the functions and accuracy of all monitoring sensors to ensure that they are in normal working state and to promptly discover sensors with faults. The data upload submodule is used to upload the collected data to the central control unit and the remote monitoring platform to ensure the real-time and accessibility of the data. The data analysis and decision-making module includes a data processing submodule, a status assessment submodule, and a decision suggestion submodule. The data processing submodule is electrically connected to the data upload submodule, and the status assessment submodule is electrically connected to the decision suggestion submodule. The data processing submodule is used to clean, filter and process the uploaded data to ensure the accuracy and effectiveness of the analysis. The status assessment submodule performs real-time assessment of the current ballast water status based on data analysis and gives risk warnings. The decision suggestion submodule is used to generate adjustment suggestions based on the assessment results to increase or decrease the amount of ballast water and provide them to the crew for reference through the user interface; The emergency response management module includes an alarm system submodule, an emergency handling submodule, and a maintenance management submodule. The alarm system submodule is electrically connected to the decision suggestion submodule, and the emergency handling submodule is electrically connected to the maintenance management submodule. The alarm system submodule is used to trigger an alarm when a crisis state is detected, that is, the ballast water weight, the cabin pressure and the ballast water temperature are not within the normal range, and notify the crew to take necessary measures. The emergency handling submodule is used to provide emergency operation guidance, including specific steps for adding water and draining water, to help the crew take quick action. The maintenance management submodule is used to record the maintenance history and usage of the sensor, remind the crew when replacement or maintenance is needed, and manage the spare parts library.

3. A method for monitoring and early warning of ro-ro passenger ship equipment operation data, characterized in that: The following steps are involved: S1. Data acquisition: The data acquisition submodule continuously collects the volume, pressure and temperature information of ballast water through water level sensors, pressure sensors and temperature sensors. The real-time data is recorded as a raw data stream, which contains the parameters provided by various sensors. S2, sensor self-check: At the same time, the sensor self-check submodule is started regularly to self-check the function and accuracy of all monitoring sensors. The results of the self-check will be fed back to the monitoring module to ensure the normal operation of the sensor. If a faulty sensor is found, the spare parts management mechanism will be activated; S3, data upload: The monitored data is uploaded to the central control unit and remote monitoring platform through the data upload submodule to ensure the real-time and accessibility of the data. The real-time uploaded data stream is stored for subsequent analysis and decision-making; S4. Data analysis and decision support: After the data is uploaded, the data processing submodule in the data analysis and decision module receives the uploaded data, cleans, filters and processes it to ensure the integrity and accuracy of the data. Subsequently, the status assessment submodule analyzes the processed data, assesses the current ballast water status and generates risk warnings. Based on the risk assessment, it generates corresponding adjustment suggestions, such as increasing or decreasing ballast water, and displays the suggestions to the crew through the user interface; S5. Emergency response: When the system detects abnormal ballast water status, it immediately triggers an alarm to notify the crew and provide specific emergency operation instructions, including steps for adding or draining water. The maintenance management submodule records the maintenance history of all operations and sensors to facilitate subsequent management and decision-making. The crew quickly executes necessary emergency measures based on the alarm and instructions and records the incident.

4. The method for monitoring and early warning of ro-ro passenger ship equipment operation data according to claim 3 is characterized in that: In S2, the specific method of sensor self-test is: S2-1, set the self-check schedule, and determine the frequency and time period of the self-check through the system configuration file; S2-2, at the beginning of the self-test, the submodule communicates with various sensors through signals to collect the current status of the sensors, including basic parameters such as operating voltage, output signal, and response time; S2-3. Perform specific functional tests for each sensor; S2-4. Compare the result of the functional test with the standard value, analyze the output of each sensor, determine whether it is within the normal working range, and determine whether the function of the sensor is abnormal based on the set threshold.

5. The method for monitoring and early warning of ro-ro passenger ship equipment operation data according to claim 4, characterized in that: In S2-3, for the water level sensor: simulate different water levels and check whether its output meets the expected value through given resistance or current input; for the pressure sensor, apply known pressure for calibration to ensure that the output matches the actual pressure; for the temperature sensor: test the output value in a known temperature environment to verify its accuracy.

6. The method for monitoring and early warning of ro-ro passenger ship equipment operation data according to claim 5, characterized in that: In S4, the specific method of evaluating the current ballast water status and generating risk warning is: S4-1. Capacity assessment: Check the current volume of ballast water and its ratio to the total weight of the ship to determine the center of gravity and stability of the ship; S4-2, status assessment: Analyze water level, pressure, and temperature sensor data to determine whether there are foreign objects or pollution in the water; S4-3. Trend analysis: Compare with historical data to analyze the changing trend of current data and identify potential risks, such as rapid water level changes or abnormal temperatures. S4-4. Use algorithmic models, such as machine learning models, to evaluate the weight of ballast water over a period of time to assess whether there is an imminent danger, such as tilt or imbalance.

7. The method for monitoring and early warning of ro-ro passenger ship equipment operation data according to claim 6, characterized in that: In S4-4, the specific method for evaluating the weight of ballast water in the previous period and adjusting the drainage flow rate is: In the next unit time, count the weight of ballast water s in a water storage tank i , where i is the next unit time, i-1 is the previous unit time, i-2 is the previous two unit time, and the ballast water weight s of a water storage tank in the previous unit time i-1 For comparison, when s i ≤s i-1 And s i-1 ≥s i-2 When the next unit time drainage flow A i unchanged, and still equal in value to the drainage flow rate A of the previous unit time i-1 , when s i >s i-1 hour Among them, α is the influence coefficient of ballast water weight change trend, β is the influence coefficient of ballast water weight, which is selected according to actual experience. i <s i-1 <s i-2 When The ratio of α and β is relatively small in the first few unit times of ballast water discharge. As the cumulative ratio per unit time increases, the flow rate is unstable in the early stage of drainage, so more reference is made to the weight of the previous unit time. In the later stage of drainage, the discharge flow rate is stable, and the change trend of weight can better reflect whether the ballast water is discharged smoothly.

8. The method for monitoring and early warning of ro-ro passenger ship equipment operation data according to claim 7, characterized in that: In S5, after performing the emergency operation, the system should continue to monitor the status of the ballast water to ensure that the operation is effective and reflect any new status changes in a timely manner. The status feedback after the emergency operation should be updated to the system in a timely manner to ensure the integrity and accuracy of the data to optimize subsequent early warnings and decisions. According to different alarm levels and status severity, set the corresponding emergency response process. For low-risk status, only recording and monitoring are required; for high-risk status, immediate operation is required.

Images