Ship emission carbon capture and fuel tank pressure interlock control system

Abstract

The present invention relates to the technical field of ship emission control, and discloses a ship emission carbon capture and fuel tank pressure interlock control system, the system comprising: a carbon capture device, a fuel tank pressure monitoring device, and an interlock control unit, the carbon capture device and the fuel tank pressure monitoring device are respectively communicatively connected to the interlock control unit, and the interlock control unit comprises a data acquisition unit, a pressure regulation unit, and an interlock logic processing unit. The carbon capture device is used to collect CO₂ emission data and fuel tank environmental parameters in the ship's exhaust gas, the fuel tank pressure monitoring device is used to receive adjustment instructions to adjust the pressure state, the data acquisition unit is used to determine abnormal compartments, etc., the pressure regulation unit is used to optimize the energy supply path to generate an interlock control scheme, and the interlock logic processing unit is used to control the execution of the baseline pressure mode and interlock intervention operations. The system realizes interlock control of carbon capture and fuel tank pressure, improving carbon capture efficiency and system stability.

Description

Technical Field

[0001] The present invention relates to the technical field of ship emission control, and in particular to a ship emission carbon capture and fuel tank pressure interlock control system. Background Art

[0002] As global attention to environmental protection and climate change continues to grow, the impact of pollutants emitted by ships, particularly carbon dioxide (CO2), on the atmospheric environment is receiving increasing attention. Stable fuel tank pressure is crucial during ship operation. Abnormal fluctuations in fuel tank pressure not only affect the supply and efficiency of fuel usage, but can also pose safety risks. For example, sudden pressure changes can cause fuel leaks and equipment damage, seriously threatening the safety of navigation. Furthermore, CO2 emissions from ship exhaust are a major contributor to the greenhouse effect. Efficiently capturing and treating CO2 emissions from ships has become a key challenge in the field of ship emission reduction technology.

[0003] Existing ship carbon capture technology has some shortcomings in practical applications. On the one hand, traditional carbon capture devices often find it difficult to collect CO2 emission data from ship exhaust and environmental parameters of fuel tanks in real time and accurately, resulting in low carbon capture efficiency. On the other hand, existing fuel tank pressure monitoring systems usually lack effective linkage with carbon capture devices, and are unable to take effective intervention measures in time when fuel tank pressure abnormalities occur, making it difficult to achieve precise regulation of fuel tank pressure. In the process of handling abnormal fuel tank pressure, how to quickly identify abnormal compartments and perform effective pressure regulation, as well as how to optimize the energy supply path to ensure the stable operation of the ship system, are also important challenges currently faced. Some existing pressure regulation methods often lack scientific algorithm support and precise logical control, resulting in poor pressure regulation effects and an inability to meet the operating requirements of ships under complex working conditions.

[0004] When the fuel tank pressure monitoring device detects an abnormal state, the existing emergency control mechanism usually responds slowly and is unable to formulate an effective interlocking control plan and perform interlocking intervention operations in a timely manner, which can easily lead to the expansion of the abnormal situation and increase the risk of ship operation.

[0005] In terms of judging carbon capture efficiency, traditional methods often lack scientific models and algorithm support, making it difficult to accurately judge the abnormal index of carbon capture efficiency, and unable to promptly detect failures in carbon capture devices and take corresponding measures, which affects the emission reduction effect of the entire system. Summary of the Invention

[0006] The object of the present invention is to provide a ship emission carbon capture and fuel tank pressure interlock control system to solve the problems raised in the above background technology.

[0007] To achieve the above objectives, the present invention provides the following technical solution: a ship emission carbon capture and fuel tank pressure interlock control system, the system comprising:

[0008] A carbon capture device, a fuel tank pressure monitoring device, and an interlock control unit, wherein the carbon capture device and the fuel tank pressure monitoring device are respectively communicatively connected to the interlock control unit, and the interlock control unit includes a data acquisition unit, a pressure regulation unit, and an interlock logic processing unit;

[0009] The carbon capture device is used to collect CO2 emission data from ship exhaust and fuel tank environmental parameters in real time;

[0010] The fuel tank pressure monitoring device is used to receive the adjustment instruction of the interlock control unit to adjust the fuel tank pressure state;

[0011] The data acquisition unit is used to record the pressure mutation period and parameter recovery period when the fuel tank pressure monitoring device is running, determine the abnormal tank section based on the pressure mutation period and parameter recovery period, control the carbon capture device to maintain a preset interlock threshold for abnormal pressure and record the change parameters, generate a pressure characteristic curve based on the change parameters, and perform pressure distribution mapping on the fuel tank structure diagram;

[0012] The pressure regulating unit is used to optimize the energy supply path of the fuel tank structure diagram that has completed the pressure distribution mapping and generate an interlocking control plan;

[0013] The interlocking logic processing unit includes a conventional control unit and an emergency control unit. The conventional control unit is used to control the fuel tank pressure monitoring device to execute the reference pressure mode when it is in a stable state; the emergency control unit is used to control the fuel tank pressure monitoring device to execute the interlocking intervention operation in the abnormal compartment according to the interlocking control scheme when the fuel tank pressure monitoring device detects an abnormal state.

[0014] Preferably, the carbon capture device includes a device housing and a multi-source collection device, a component analysis device, a state determination module and a transmission module arranged in the housing;

[0015] The multi-source acquisition device is used to synchronously acquire CO2 concentration data and temperature and humidity monitoring data;

[0016] The component analysis device is used to extract the periodic fluctuation characteristics of emission data;

[0017] The state determination module is used to calculate the correlation between the current cycle fluctuation characteristics and the historical standard mode based on the BP neural network, determine the carbon capture efficiency abnormality index, and trigger the interlock signal according to the calculation result;

[0018] The transmission module is used to upload monitoring data to the interlocking control unit.

[0019] Preferably, the fuel tank pressure monitoring device includes a monitoring box and a pressure sensing module, a parameter detection module, a command response module and a communication conversion module arranged in the box.

[0020] Preferably, the recording of the pressure mutation period and parameter recovery period during the operation of the fuel tank pressure monitoring device includes:

[0021] When the fuel tank pressure monitoring device detects a sudden change in pressure, it records the timestamp data of the time when the sudden change occurs, continuously monitors the parameter recovery critical point through the parameter detection module, and records the cycle number of the recovery time.

[0022] Preferably, determining the abnormal compartment according to the pressure mutation period and the parameter recovery period includes:

[0023] Generate mutation coordinates and recovery coordinates based on timestamp data and cycle number;

[0024] The mutation coordinates, recovery coordinates and the position of the carbon capture device are spatially correlated to form a closed area, which is marked as an abnormal compartment.

[0025] Preferably, the controlling of the carbon capture device to maintain a preset interlock threshold for abnormal pressure and recording the change parameters, generating a pressure characteristic curve according to the change parameters and performing pressure distribution mapping on the fuel tank structure diagram comprises the following steps:

[0026] Controlling the carbon capture device to adjust the output power of the abnormal compartment, and obtaining pressure parameters in real time through a parameter detection module;

[0027] A preset interlock threshold range is provided. If the pressure parameter exceeds the preset interlock threshold range, the carbon capture device is controlled to maintain operation at the preset interlock threshold;

[0028] Continuously record the pressure output value of the carbon capture device to form a set of changing parameters;

[0029] According to the set of changing parameters, BP neural network algorithm is used to generate the pressure dynamic characteristic curve;

[0030] Extracting a number of key feature points at equal time intervals from the pressure dynamic characteristic curve, wherein the number of the key feature points is proportional to the duration of the curve;

[0031] The pressure distribution mapping of the fuel tank structure diagram is annotated based on the extracted key feature points.

[0032] Preferably, the energy supply path optimization of the fuel tank structure diagram that has completed the pressure distribution mapping includes logically isolating the preset energy supply path overlapping with the high-pressure section in the fuel tank structure diagram after marking the pressure distribution mapping on the fuel tank structure diagram.

[0033] Preferably, when the fuel tank pressure monitoring device detects an abnormal state, controlling it to perform an interlocking intervention operation in the abnormal compartment according to the interlocking control scheme includes:

[0034] S1. Select the abnormal compartment access location with the shortest operation process based on the next energy supply node to be switched;

[0035] S2. Controlling the fuel tank pressure monitoring device to switch to the access position and perform parameter synchronization;

[0036] S3, controlling the fuel tank pressure monitoring device to cut into the abnormal compartment from the access position and perform state adjustment according to the energy supply path in the interlocking control scheme;

[0037] S4. Obtain the output index of the fuel tank pressure monitoring device in real time and dynamically correct the output index using the particle swarm optimization algorithm;

[0038] S5. After each continuous power supply operation is completed in the abnormal compartment, the fuel tank pressure monitoring device is controlled to suspend output and exit the abnormal compartment, and S1 is executed again.

[0039] Preferably, said S1 comprises the following steps:

[0040] The feasible access locations of each abnormal compartment are calculated using the A* algorithm, and a comprehensive evaluation is performed based on the operation process and spatial distance parameters;

[0041] Based on the comprehensive assessment results, select the abnormal compartment access location with the shortest operation process and the smallest spatial distance;

[0042] The comprehensive evaluation based on the operation process and spatial distance parameters includes:

[0043] A two-dimensional evaluation matrix containing the number of operation process steps and spatial distance values ​​was established;

[0044] After normalizing the two-dimensional evaluation matrix, the first principal component is extracted using the hierarchical analysis method as a comprehensive evaluation index;

[0045] The interlocking logic processing unit is used to select the abnormal compartment access position with the largest comprehensive evaluation index value.

[0046] Preferably, the correlation calculation between the current periodic fluctuation characteristics and the historical standard pattern based on the BP neural network includes:

[0047] Input the current cycle fluctuation characteristics and the historical standard pattern into the BP neural network model, wherein the number of nodes in the hidden layer of the model is 1.5 times the number of nodes in the input layer;

[0048] Adjust the model weights through the back-propagation algorithm and calculate the correlation coefficient value of the output layer as the correlation calculation result;

[0049] The determination of the carbon capture efficiency abnormality index includes comparing the correlation coefficient value with a preset threshold value, and if the correlation coefficient value is less than the preset threshold value, determining that the abnormality index is at a high risk level.

[0050] Compared with the prior art, the present invention has the following beneficial effects:

[0051] The multi-source acquisition device in the carbon capture device can synchronously obtain CO2 concentration data and temperature and humidity monitoring data. The component analysis device can extract the periodic fluctuation characteristics of the emission data. The state judgment module calculates the correlation between the current periodic fluctuation characteristics and the historical standard pattern based on the BP neural network, accurately judges the carbon capture efficiency abnormality index and triggers the interlocking signal. The transmission module uploads the monitoring data to the interlocking control unit, which enables the system to grasp the ship's exhaust emissions in real time and comprehensively, providing data support for efficient carbon capture and effectively improving carbon capture efficiency.

[0052] When the fuel tank pressure monitoring device detects a sudden change in pressure, it records the timestamp of the moment the change occurred. The parameter detection module continuously monitors the critical point of parameter recovery and records the cycle number of the recovery moment. Based on this data, the sudden change and recovery coordinates are generated. These coordinates are then spatially correlated with the position of the carbon capture device to form a closed area, accurately marking the abnormal compartment. This process enables the rapid and precise location of the abnormal compartment, laying the foundation for subsequent pressure regulation.

[0053] After identifying the abnormal compartment, the carbon capture device is controlled to maintain a preset interlock threshold for abnormal pressure and record the changing parameters. A BP neural network algorithm is used to generate a dynamic pressure characteristic curve, and the pressure distribution is mapped and annotated on the fuel tank structure diagram. This not only monitors the pressure changes in the abnormal compartment in real time, but also provides a clear picture of the pressure distribution within the fuel tank, providing a clear basis for optimizing the energy supply path.

[0054] The preset energy supply path that overlaps with the high-pressure section in the fuel tank structure diagram that completes the pressure distribution mapping is logically isolated, which realizes the optimization of the energy supply path, avoids the impact of the high-pressure section on the energy supply system, and improves the stability and reliability of the system.

[0055] The conventional control unit in the interlocking logic processing unit controls the fuel tank pressure monitoring device to execute the reference pressure mode when it is in a stable state. When an abnormal state is detected, the emergency control unit uses the A* algorithm to calculate the feasible access locations for each abnormal tank section. Based on a comprehensive evaluation of the operating process and spatial distance parameters, it selects the optimal access location. It then controls the fuel tank pressure monitoring device to perform interlocking intervention operations step by step, and uses the particle swarm optimization algorithm to dynamically correct the output indicators. This series of operations enables rapid response and precise handling of abnormal fuel tank pressure conditions, improves the system's emergency handling capabilities, and ensures the safe operation of the ship under various operating conditions.

[0056] In addition, through close collaboration and data sharing among various units, the entire system achieves interlocking linkage between carbon capture and fuel tank pressure control, which not only improves the carbon capture efficiency, but also ensures the stability of fuel tank pressure, reduces the risk of ship operation, and has significant economic and social benefits. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] Figure 1 This is a working principle diagram of the ship emission carbon capture and fuel tank pressure interlock control system according to the present invention;

[0058] Figure 2 A schematic diagram of how a carbon capture device works;

[0059] Figure 3 This is a flowchart of BP neural network correlation calculation;

[0060] Figure 4 Design diagram for abnormal compartment identification and pressure distribution mapping. DETAILED DESCRIPTION

[0061] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. 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 making creative efforts are within the scope of protection of the present invention.

[0062] See also Figures 1-4 The present invention relates to a ship emission carbon capture and fuel tank pressure interlock control system. The system includes: a carbon capture device, a fuel tank pressure monitoring device, and an interlock control unit. The carbon capture device and the fuel tank pressure monitoring device are respectively connected to the interlock control unit for communication. The interlock control unit includes a data acquisition unit, a pressure regulation unit, and an interlock logic processing unit. The specific implementation steps are as follows:

[0063] The carbon capture device is used to collect CO2 emission data and fuel tank environmental parameters in the ship's exhaust gas in real time; the fuel tank pressure monitoring device is used to receive adjustment instructions from the interlocking control unit to adjust the fuel tank pressure state; the data acquisition unit is used to record the pressure mutation period and parameter recovery period during the operation of the fuel tank pressure monitoring device, determine the abnormal compartment according to the pressure mutation period and parameter recovery period, control the carbon capture device to maintain the preset interlocking threshold for abnormal pressure and record the changing parameters, generate a pressure characteristic curve according to the changing parameters and perform pressure distribution mapping on the fuel tank structure diagram; the pressure regulation unit is used to optimize the energy supply path of the fuel tank structure diagram that has completed the pressure distribution mapping, and generate an interlocking control plan; the interlocking logic processing unit includes a conventional control unit and an emergency control unit. The conventional control unit is used to control the fuel tank pressure monitoring device to execute the reference pressure mode when it is in a stable state; the emergency control unit is used to control the fuel tank pressure monitoring device to execute interlocking intervention operations in the abnormal compartment according to the interlocking control plan when the abnormal state is detected.

[0064] Example 1: In this example, the carbon capture device consists of a housing, housed within which are a multi-source collection device, a component analysis device, a state determination module, and a transmission module. The housing is constructed of corrosion-resistant materials to withstand the harsh conditions of ship exhaust emissions, such as high temperature, high humidity, and corrosive gases. It provides reliable protection for the internal modules and ensures stable operation.

[0065] The multi-source acquisition device is used to simultaneously acquire CO2 concentration data and temperature and humidity monitoring data. The device incorporates multiple sensors of varying types. The CO2 concentration sensor utilizes non-dispersive infrared (NDIR) detection, accurately measuring CO2 concentrations in ship exhaust. The temperature and humidity sensor utilizes a high-precision composite sensor, enabling real-time monitoring of exhaust temperature and humidity parameters. These sensors are strategically positioned and integrated within the device housing to ensure sufficient contact with the exhaust, enabling simultaneous acquisition of multiple parameters. During the acquisition process, the multi-source acquisition device samples various parameters in real time at a fixed sampling frequency, which can be adjusted based on actual needs to ensure sufficient timeliness and accuracy of the acquired data. The collected data undergoes preliminary filtering to remove high-frequency noise and interference signals before being transmitted to the component analysis device.

[0066] The component analysis device is used to extract the periodic fluctuation characteristics of emission data. Using advanced signal processing algorithms, it analyzes CO2 concentration, temperature, and humidity data transmitted from multi-source acquisition devices. Data preprocessing, including normalization and detrending, is performed to eliminate the effects of baseline drift and trend terms. Spectral analysis methods, such as the Fast Fourier Transform (FFT), are then used to convert the time-domain data into the frequency domain, thereby identifying periodic components in the data. By analyzing the amplitude and phase of different frequency components, the primary periodic fluctuation characteristics of the emission data, such as the duration and amplitude of the fluctuation, are determined. Furthermore, the component analysis device performs statistical analysis on data from multiple cycles to obtain more representative periodic fluctuation characteristic parameters. These characteristic parameters serve as an important basis for subsequent status determination.

[0067] The state determination module uses a BP neural network to calculate the correlation between the current cyclical fluctuation characteristics and the historical standard pattern, determine the carbon capture efficiency anomaly index, and trigger an interlock signal based on the calculated results. The construction of the BP neural network model is the core of this module. The number of nodes in the model's input layer is determined by the number of extracted cyclical fluctuation characteristic parameters, and the number of hidden layer nodes is 1.5 times the number of input layer nodes. This setting ensures model fitting accuracy while avoiding overfitting. The output layer has 1 node, which outputs the correlation coefficient value. During the model training phase, the cyclical fluctuation characteristic parameters of the historical standard pattern are used as input. The model weights and thresholds are adjusted through the backpropagation algorithm to ensure that the model output accurately reflects the correlation between the input data and the historical standard pattern. When performing real-time state determination, the current cyclical fluctuation characteristic parameters are input into the trained BP neural network model, and the model calculates the correlation coefficient value of the output layer through forward propagation. This correlation coefficient value is then compared with a preset threshold. If the correlation coefficient value is less than the preset threshold, it means that the current periodic fluctuation characteristics are significantly different from the historical standard pattern, and the carbon capture efficiency abnormality index is judged to be at a high-risk level. At this time, the status judgment module will trigger an interlocking signal to notify the interlocking control unit to take corresponding measures.

[0068] The transmission module is used to upload monitoring data to the interlocking control unit. This module uses wireless communication methods, such as 4G or 5G communication technology, to ensure the real-time and reliability of data transmission. The transmission module packages and processes monitoring data such as the original data collected by the multi-source acquisition device, the periodic fluctuation characteristic parameters extracted by the component analysis device, and the judgment results of the state judgment module, encodes them according to a specific communication protocol format, and then sends them to the interlocking control unit through the wireless communication network. During the data transmission process, the transmission module will encrypt the data to prevent the data from being stolen or tampered with during the transmission process. At the same time, the transmission module also has a data retransmission mechanism. When a data transmission failure is detected, the data will be automatically resent to ensure that the interlocking control unit can receive complete and accurate monitoring data.

[0069] In actual applications, the carbon capture device achieves real-time collection, analysis, and transmission of CO2 emission data from ship exhaust and fuel tank environmental parameters through the coordinated work of the above modules. The multi-source acquisition device ensures the synchronization and accuracy of the data, the component analysis device extracts the periodic fluctuation characteristics of the data, the state judgment module uses the BP neural network model to conduct real-time evaluation of carbon capture efficiency, and the transmission module uploads the monitoring data to the interlock control unit in a timely manner, providing strong support for the stable operation of the entire ship's carbon capture and fuel tank pressure interlock control system. For example, when the ship operates under different operating conditions, the exhaust emissions will change. The carbon capture device can capture these changes in a timely manner and transmit the relevant information to the interlock control unit so that the interlock control unit can adjust the operating status of the carbon capture device and the fuel tank pressure monitoring device according to the actual situation.

[0070] Example 2: In this example, the fuel tank pressure monitoring device consists of a monitoring housing and, housed within it, a pressure sensing module, a parameter detection module, a command response module, and a communication conversion module. The monitoring housing is constructed of high-strength metal, offering excellent pressure resistance and protection, capable of withstanding pressure fluctuations within the fuel tank and external environmental impacts. The interior of the housing is sealed to prevent fuel leakage and the ingress of foreign matter, providing a safe and stable operating environment for all internal modules.

[0071] The pressure sensing module is used to monitor pressure changes within the fuel tank in real time. This module uses a high-precision piezoresistive pressure sensor whose measurement range covers the pressure range of the fuel tank during normal operation. It also has high measurement accuracy and sensitivity, and can accurately capture even small fluctuations in the fuel tank's pressure. The pressure sensor is installed at a location where the monitoring box connects to the fuel tank, ensuring that pressure changes within the fuel tank can be directly sensed. During operation, the pressure sensing module continuously collects pressure data within the fuel tank at a set sampling frequency. The sampling frequency can be adjusted according to the speed of pressure changes in the fuel tank. For faster pressure changes, the sampling frequency is increased to obtain more dense data points. For slower pressure changes, the sampling frequency is appropriately reduced to conserve system resources. The collected pressure data is first amplified and filtered to improve the signal-to-noise ratio before being transmitted to the parameter detection module.

[0072] The parameter detection module's main function is to record the timestamp of the moment a sudden pressure change is detected by the fuel tank pressure monitoring device. By continuously monitoring the critical point of parameter recovery, the module also records the cycle number associated with the recovery moment. When the pressure data transmitted by the pressure sensing module changes significantly, exceeding a preset pressure change threshold, the parameter detection module immediately triggers the pressure change detection mechanism. The module's internal clock system generates a precise timestamp, recording the exact moment of the sudden pressure change with millisecond accuracy, ensuring high accuracy. Simultaneously, the parameter detection module continuously monitors the pressure parameters, tracking pressure trends in real time. When the pressure gradually recovers after a series of fluctuations and reaches the preset critical point of parameter recovery, the parameter detection module identifies this as the parameter recovery moment and records the corresponding cycle number. Cycle numbers are assigned based on the fuel tank pressure monitoring device's operating cycle, with each cycle assigned a unique number. Recording cycle numbers facilitates tracing and analyzing pressure changes over time. During the recording of timestamp data and cycle numbers, the parameter detection module verifies and stores the data.

[0073] The command response module is used to receive adjustment commands issued by the interlocking control unit and perform corresponding operations based on the commands. This module receives command signals from the interlocking control unit in real time through a connection with the communication conversion module. The command signal contains specific adjustment requirements and operating parameters, such as the target value for pressure adjustment and the adjustment method. The command response module parses and verifies the received commands to ensure their legality and correctness. After confirming that the command is correct, the command response module controls the relevant components of the fuel tank pressure monitoring device to perform the corresponding operations according to the requirements of the command. For example, when the interlocking control unit issues a pressure adjustment command, the command response module controls the pressure adjustment mechanism to adjust the pressure in the fuel tank to the target value. During operation, the command response module monitors the execution of the operation in real time and feeds back the execution status to the interlocking control unit so that the interlocking control unit can monitor and adjust the operating status of the system in real time.

[0074] The communication conversion module is used to realize data communication conversion between the fuel tank pressure monitoring device and the interlocking control unit. This module supports multiple communication protocols and can realize efficient and stable data transmission with the interlocking control unit. During the data transmission process, the communication conversion module packages and processes information such as the pressure data collected by the pressure sensing module, the timestamp data and cycle number recorded by the parameter detection module, and the execution status of the command response module, and converts the data into a signal form suitable for transmission according to the predetermined communication protocol format, and then sends it to the interlocking control unit through the communication line. During the data reception process, the communication conversion module unpacks and converts the command signal received from the interlocking control unit, restores it to a command format that can be recognized and processed by the fuel tank pressure monitoring device, and transmits it to the command response module. The communication conversion module also has data caching and error checking functions, which can cache data during the communication process to avoid data loss, and at the same time verify the transmitted data through an error checking algorithm.

[0075] During actual operation, the various modules of the fuel tank pressure monitoring system collaborate to achieve real-time monitoring, data recording, and command execution of fuel tank pressure. The pressure sensing module continuously monitors fuel tank pressure, providing accurate pressure data to the parameter detection module. The parameter detection module records critical time and cycle information when pressure suddenly changes, providing a basis for subsequent identification of abnormal compartments and pressure analysis. The command response module strictly executes the instructions of the interlock control unit, ensuring that the fuel tank pressure can be adjusted according to system requirements. The communication conversion module ensures reliable data transmission between the fuel tank pressure monitoring system and the interlock control unit. For example, when the pressure in the fuel tank suddenly changes due to fuel consumption or replenishment, the pressure sensing module promptly detects the pressure change and transmits it to the parameter detection module. The parameter detection module records the timestamp of the sudden change and the cycle number of the recovery time. This data is then transmitted to the interlock control unit via the communication conversion module. The interlock control unit uses this data to identify the abnormal compartment and subsequently adjust the pressure. The command response module adjusts the fuel tank pressure according to the instructions of the interlock control unit, restoring normal operation of the system.

[0076] Example 3: In this example, the data acquisition unit involves multiple specific and interrelated operational steps in recording the pressure surge and parameter recovery periods during the operation of the fuel tank pressure monitoring device, as well as identifying abnormal compartments based on these periods. When the pressure sensing module in the fuel tank pressure monitoring device detects a sudden pressure surge within the fuel tank, the parameter detection module immediately initiates a timestamp recording mechanism. At this point, the module's internal high-precision clock system generates corresponding timestamp data, accurate to the millisecond level, accurately marking the exact moment of the pressure surge. Simultaneously, the parameter detection module continuously monitors the pressure parameters in real time and, using pre-set parameter recovery logic, tracks the pressure's recovery from a sudden state to normal. When the pressure parameters meet pre-set recovery threshold conditions, such as returning to a specific threshold within the normal fluctuation range and remaining stable, the parameter detection module records the cycle number at that time. These cycle numbers are arranged sequentially according to the fuel tank pressure monitoring device's operating cycle, with each cycle assigned a unique number to facilitate subsequent time-series management and traceability of pressure data from different stages.

[0077] After obtaining the timestamp data and cycle number, the data acquisition unit needs to convert these time dimension information into spatial position information to determine the specific location of the abnormal compartment. Specifically, the timestamp data will be converted into the corresponding mutation coordinates through the time-space mapping database inside the ship. The database pre-stores the coordinate mapping relationship of each compartment of the ship at different time points, taking into account factors such as displacement and posture changes during the navigation of the ship, to ensure that the timestamp can accurately correspond to the specific spatial position. The cycle number is combined with the monitoring range record of the fuel tank pressure monitoring device in each working cycle to generate the recovery coordinates. For example, each cycle number corresponds to the monitoring task of a specific area in the fuel tank, and the cycle number can be used to determine the specific spatial position point corresponding to the pressure recovery.

[0078] The data acquisition unit needs to perform spatial correlation processing on the mutation coordinates, recovery coordinates and the position of the carbon capture device. The installation position of the carbon capture device on the ship is fixed, and its coordinate information is stored in the basic database of the system. The data acquisition unit uses a spatial geometry algorithm to correlate the mutation coordinates and recovery coordinates with the position of the carbon capture device. Specifically, with the mutation coordinates and recovery coordinates as endpoints and the position of the carbon capture device as the reference point, a closed geometric area is constructed by calculating the spatial distance and angular relationship between the three points. The construction of this area follows a certain spatial logic, such as using the mutation point and recovery point as the boundary and the range that the carbon capture device can effectively cover as the expansion basis, to ensure that the closed area can truly reflect the range of the compartment affected by the pressure anomaly.

[0079] Once a closed area is formed, the data acquisition unit marks it as an abnormal compartment. This marking process involves real-time updates to the ship's fuel tank diagram. The system then annotates the abnormal compartment with a specific color or symbol on the 3D fuel tank diagram, allowing operators to intuitively identify the specific location of the pressure anomaly. Simultaneously, relevant information about the abnormal compartment, including coordinate range, formation time, and associated pressure parameters, is stored in the system's anomaly database.

[0080] Throughout the entire process, the data acquisition unit must ensure data accuracy and processing efficiency at every stage. For example, during the conversion between timestamps and coordinates, the ship's navigation parameters, including longitude, latitude, heading, and speed, must be calibrated in real time to avoid coordinate mapping errors caused by ship movement. During spatial correlation processing, the structural characteristics of the fuel tank's interior, such as the location of bulkheads and the distribution of pipes, must be considered to ensure that the demarcation of closed areas conforms to the actual structure of the fuel tank and to avoid misidentifying normal compartments as abnormal ones.

[0081] The data acquisition unit also features data verification and redundancy mechanisms. Recorded timestamps and cycle numbers undergo multiple checks, including temporal logic verification and cycle continuity verification, to ensure data reliability. During the spatial correlation process, if a closed area is constructed abnormally due to data errors, the system automatically triggers a retest process, recollecting pressure data and recalculating coordinates to correct the marking of the abnormal compartment.

[0082] In practical applications, when a sudden pressure change occurs in a certain area of ​​a ship's fuel tank due to fuel filling, consumption, or equipment operation, the data acquisition unit can respond quickly and accurately determine the location of the abnormal compartment through the above process. For example, when a sudden pressure increase occurs in a certain section of the fuel tank during refueling, the pressure sensing module detects the sudden change, and the parameter detection module records the timestamp and cycle number. The data acquisition unit converts this into coordinates and associates it with the location of the carbon capture device, forming a closed abnormal compartment marker. This provides a precise location basis for subsequent pressure control and interlocking intervention of the carbon capture device in this area, ensuring that the system can promptly and accurately handle abnormal fuel tank pressure conditions and ensure the safe operation of the ship.

[0083] Example 4: In this example, the data acquisition unit controls the carbon capture device to maintain a preset interlock threshold for abnormal pressure and records the changing parameters. Furthermore, the process of generating a pressure characteristic curve based on the changing parameters and mapping the pressure distribution on the fuel tank structure diagram requires detailed explanation based on specific scenarios. For example, consider a cargo ship experiencing abnormal pressure in the middle fuel tank during voyage. Once the data acquisition unit identifies the abnormal compartment through the fuel tank pressure monitoring device, it initiates the carbon capture device control process.

[0084] The data acquisition unit sends an output power adjustment instruction to the carbon capture device to control it to adjust the power according to the pressure status of the abnormal compartment. After receiving the instruction, the carbon capture device increases the power of the adsorption unit corresponding to the abnormal compartment to the preset adjustment range through the internal power adjustment module. During this process, the parameter detection module of the fuel tank pressure monitoring device continuously obtains the pressure parameters of the abnormal compartment in real time, including pressure value, pressure change rate and other data. For example, when the pressure value of the abnormal compartment suddenly rises from 0.8MPa during normal operation to 1.2MPa, the parameter detection module collects pressure data at a frequency of 10 times per second and transmits the data to the data acquisition unit in real time.

[0085] The data acquisition unit has a preset interlock threshold range, determined based on the fuel tank's design pressure parameters and safe operating standards, for example, between 0.7 MPa and 1.0 MPa. When the received pressure parameter exceeds this preset interlock threshold range, the data acquisition unit immediately issues a command to maintain threshold operation. For example, in the example above, when the pressure reaches 1.2 MPa, exceeding the upper limit of 1.0 MPa, the carbon capture device maintains the preset interlock threshold of 1.0 MPa. By increasing CO2 adsorption or adjusting the gas flow rate, the pressure in the abnormal compartment is prevented from rising further.

[0086] While the carbon capture unit maintains its pre-set interlock threshold, the data acquisition unit continuously records its pressure output values, forming a variable parameter set. This set includes parameters such as timestamp, real-time pressure value, and the carbon capture unit's operating power. For example, during the 30 minutes of abnormal compartment pressure control, the data acquisition unit records a pressure output value every 6 seconds, forming a variable parameter set containing 300 data points. It also records the carbon capture unit's power output status at that moment, such as 15kW, 20kW, etc.

[0087] The data acquisition unit uses a BP neural network algorithm to generate a dynamic pressure characteristic curve based on the set of variable parameters. The input layer of the BP neural network model is the pressure value and timestamp information in the variable parameter set. The number of hidden layer nodes is determined by 1.5 times the number of input layer nodes. The output layer is the predicted pressure change trend value. By learning the relationship between historical pressure data and the operating parameters of the carbon capture device, the model processes the current set of variable parameters to generate a dynamic characteristic curve that reflects the change of pressure over time. For example, in the above example, the curve will show the process of pressure gradually decreasing from 1.2MPa to 1.0MPa and maintaining stability under the control of the carbon capture device, as well as characteristics such as the rate of pressure change and the amplitude of fluctuation.

[0088] In the dynamic pressure characteristic curve, the data acquisition unit extracts a number of key feature points at equal time intervals. The number of key feature points is proportional to the curve duration. For example, if the curve duration is 30 minutes and a key feature point is extracted every 2 minutes, a total of 15 key feature points will be extracted. Each feature point contains information such as the pressure value and pressure change rate at that moment. These key feature points can summarize the main trends and characteristics of the dynamic pressure changes, reducing the amount of data while retaining important information.

[0089] Based on the extracted key feature points, the data acquisition unit maps and annotates the pressure distribution of the fuel tank structure diagram. The fuel tank structure diagram is a three-dimensional model stored in the system database, which contains information such as the specific location and structural dimensions of each compartment. The data acquisition unit maps the pressure information of each key feature point to the specific spatial position in the fuel tank structure diagram, and performs visual mapping through color gradients, numerical annotations, etc. For example, in the abnormal compartment area in the middle of the fuel tank, the area with a pressure value exceeding 1.0MPa is marked in red, and the area close to 1.0MPa is marked in yellow, so that the operator can intuitively see the pressure distribution in the fuel tank.

[0090] Throughout the entire process, the data acquisition unit must ensure the accuracy and real-time performance of each link. For example, when adjusting the output power of the carbon capture device, dynamic fine-tuning must be performed based on the actual pressure changes in the abnormal compartment to avoid excessive or insufficient power adjustment. When generating the dynamic characteristic curve of pressure, the BP neural network model must be regularly updated and trained with the latest historical data to adapt to the pressure change characteristics under different working conditions. When mapping and annotating the pressure distribution, the impact of structural components inside the fuel tank on the pressure distribution, such as bulkheads and pipes, must be considered to ensure that the mapping and annotation conform to the actual situation.

[0091] In practice, when uneven fuel consumption causes abnormal pressure in a particular section of a ship's fuel tank, the data acquisition unit, through the aforementioned process, can precisely control the carbon capture device to regulate the abnormal pressure and generate an intuitive pressure distribution map. For example, after a cargo ship has been sailing for 48 hours, the pressure in the forward area of ​​the fuel tank drops to 0.6 MPa due to excessive fuel consumption, falling below the preset interlock threshold of 0.7 MPa. The data acquisition unit controls the carbon capture device to reduce the adsorption power in this area while increasing the gas reinjection rate, gradually raising the pressure to 0.7 MPa and maintaining stability. During this process, the data acquisition unit records the changing parameters of the pressure from 0.6 MPa to 0.7 MPa, generates a dynamic pressure characteristic curve, and annotates the forward area with a pressure below 0.7 MPa in blue on the fuel tank structure diagram. Once the pressure recovers, the marking color returns to normal. In this way, precise regulation and visual management of the fuel tank pressure are achieved.

[0092] The data acquisition unit also features an exception handling mechanism. If a carbon capture device malfunctions or abnormal pressure parameter fluctuations occur during the control process, the system automatically triggers emergency procedures, such as switching to a backup carbon capture device or issuing an alarm signal, to ensure the reliability and safety of the entire system. Simultaneously, all recorded parameter changes and generated pressure characteristic curves are stored in the system database for subsequent data analysis and system optimization.

[0093] Example 5: In this example, when the fuel tank pressure monitoring device detects an abnormal condition, the interlock logic processing unit controls it to perform interlock intervention operations within the abnormal compartment according to the interlock control scheme. This can be explained in detail in conjunction with specific ship navigation scenarios. For example, consider a container ship experiencing abnormal pressure in the starboard mid-section of the fuel tank during ocean voyage. When the fuel tank pressure monitoring device detects that the pressure in this area remains consistently above the normal range and the data acquisition unit identifies the abnormal compartment, the interlock logic processing unit activates the emergency control unit and performs intervention operations according to the following steps.

[0094] First, execute step S1 and select the abnormal compartment access position with the shortest operation process according to the next energy supply node to be switched. Assume that the current energy supply node is pump group No. 1 on the port side of the fuel tank, and the next one to be switched to is pump group No. 3 on the starboard side. At this time, the abnormal compartment is the middle compartment on the starboard side. The interlocking logic processing unit calculates the feasible access position of the abnormal compartment through the A* algorithm. The algorithm takes into account the spatial layout, pipeline direction and other obstacle information in the fuel tank to generate multiple feasible paths. For example, three feasible access positions are calculated: position A is close to pump group No. 3, position B is in the middle of the abnormal compartment, and position C is close to the front end of the compartment.

[0095] Then, a comprehensive evaluation is performed based on the operation process and spatial distance parameters. A two-dimensional evaluation matrix containing the number of operation process steps and spatial distance values ​​is established. For example, the operation process of position A requires 5 valve switching steps and the spatial distance is 8 meters; position B requires 7 steps and the distance is 5 meters; position C requires 6 steps and the distance is 6 meters. The two-dimensional evaluation matrix is ​​normalized, and the number of steps and distance values ​​are converted into dimensionless values ​​between 0 and 1. The hierarchical analysis method is then used to extract the first principal component as the comprehensive evaluation index. For example, after calculation, the comprehensive evaluation index of position A is 0.75, position B is 0.68, and position C is 0.72. The interlocking logic processing unit selects position A with the largest comprehensive evaluation index value as the access position.

[0096] After selecting the access location, step S2 is executed to control the fuel tank pressure monitoring device to switch to location A and synchronize its parameters. After receiving the switching command, the command response module of the fuel tank pressure monitoring device controls the mobile mechanism to move along the preset path to location A. At the same time, the communication conversion module synchronizes parameters with the interlocking control unit, transmitting parameters such as the pressure reference value and the current measured pressure value at location A to the interlocking logic processing unit to ensure that the device status is consistent with the system data.

[0097] Then, step S3 is executed to control the fuel tank pressure monitoring device to cut into the abnormal compartment from position A and perform state adjustment according to the energy supply path in the interlocking control scheme. The interlocking control scheme has generated an energy supply path optimization plan for the abnormal compartment, such as closing the connecting valve between the abnormal compartment and the adjacent compartment and activating the backup energy supply pipeline. The command response module of the fuel tank pressure monitoring device controls the relevant valve actions according to the plan, adjusts the gas flow and pressure of the energy supply pipeline, and gradually restores the pressure of the abnormal compartment to normal. For example, by closing the connecting valve between the starboard middle compartment and the rear compartment and opening the front backup pipeline, the pressure is gradually adjusted from 1.3MPa to the normal range of 1.0MPa.

[0098] While the state adjustment is being executed, step S4 is executed simultaneously to obtain the output indicators of the fuel tank pressure monitoring device in real time and dynamically correct them using a particle swarm optimization algorithm. Output indicators include pressure regulation rate, valve opening, gas flow rate, etc. The parameter detection module of the fuel tank pressure monitoring device collects these indicators in real time and transmits them to the interlocking logic processing unit. The particle swarm optimization algorithm optimizes and calculates the collected indicators based on preset target parameters, such as a pressure regulation rate not exceeding 0.05 MPa / min, and generates correction instructions that are sent to the fuel tank pressure monitoring device. For example, when the pressure regulation rate is detected to have reached 0.08 MPa / min, the algorithm generates an instruction to reduce the valve opening to restore the regulation rate to the target range.

[0099] After the abnormal compartment completes a continuous power supply operation, step S5 is executed, controlling the fuel tank pressure monitoring device to suspend output and exit the abnormal compartment, and re-execution of step S1. For example, after the pressure in the starboard mid-section returns to normal, the fuel tank pressure monitoring device suspends power supply adjustment, and the mobile mechanism exits the abnormal compartment and returns to its initial position. At this time, the next power supply node to be switched may become pump group 4 on the starboard side. The interlocking logic processing unit re-executes step S1, selects the new access point, and continues the power supply switching operation.

[0100] Throughout the interlocking intervention process, the interlocking logic processing unit must ensure the coordination and accuracy of each step. For example, in step S1, the A* algorithm's obstacle information must be updated in real time. If a pipeline in the fuel tank is temporarily closed for maintenance, the system must promptly adjust the feasible path calculation to avoid selecting an unfeasible access location. In step S3, the switching of energy supply paths must be executed sequentially to avoid exacerbated pressure fluctuations caused by incorrect valve operation sequence.

[0101] In practice, when a ship navigates severe sea conditions, fuel sloshing within the fuel tanks can cause pressure anomalies in multiple compartments. The interlocking logic processing unit then prioritizes each abnormal compartment. For example, the forward starboard compartment, where pressure exceeds the safety threshold, is addressed first, followed by the port midship compartment, where pressure fluctuations are greater. For each abnormal compartment, interlocking intervention is performed according to steps S1 through S5.

[0102] The interlocking logic processing unit also features an emergency backup mechanism. If a device failure occurs during a specific step, such as a jam in the fuel tank pressure monitoring device's moving mechanism, the system automatically switches to the backup device to continue operations and issues a fault alarm, notifying the operator to initiate repairs. All operational data, including access point selection, parameter adjustment records, and fault handling logs, is stored in the system database.

[0103] Through the interlocking intervention process described above, the interlocking logic processing unit can efficiently and accurately control the fuel tank pressure monitoring device to perform intervention operations when abnormal fuel tank pressure occurs, ensuring that the fuel tank pressure remains stable within a safe range and ensuring the safe navigation of the ship. For example, when a container ship is crossing typhoon waters, the fuel tank pressure frequently becomes abnormal due to the ship's violent shaking. Through the real-time response and adjustment of the interlocking intervention mechanism, the fuel tank pressure is effectively maintained stable, avoiding equipment failure and safety hazards caused by pressure anomalies.

[0104] It should be noted that, in this document, relational terms such as first and second, etc., are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "comprises," "comprising," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that includes a list of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, method, article, or apparatus.

[0105] While embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions, and variations may be made to these embodiments without departing from the principles and spirit of the invention, and that the scope of the invention is defined by the appended claims and their equivalents.

Claims

1. A ship emission carbon capture and fuel tank pressure interlock control system, characterized in that: include: A carbon capture device, a fuel tank pressure monitoring device, and an interlock control unit, wherein the carbon capture device and the fuel tank pressure monitoring device are respectively communicatively connected to the interlock control unit, and the interlock control unit includes a data acquisition unit, a pressure regulation unit, and an interlock logic processing unit; The carbon capture device is used to collect CO2 emission data from ship exhaust and fuel tank environmental parameters in real time; The fuel tank pressure monitoring device is used to receive the adjustment instruction of the interlock control unit to adjust the fuel tank pressure state; The data acquisition unit is used to record the pressure mutation period and parameter recovery period when the fuel tank pressure monitoring device is running, determine the abnormal tank section based on the pressure mutation period and parameter recovery period, control the carbon capture device to maintain a preset interlock threshold for abnormal pressure and record the change parameters, generate a pressure characteristic curve based on the change parameters, and perform pressure distribution mapping on the fuel tank structure diagram; The pressure regulating unit is used to optimize the energy supply path of the fuel tank structure diagram that has completed the pressure distribution mapping and generate an interlocking control plan; The interlocking logic processing unit includes a conventional control unit and an emergency control unit. The conventional control unit is used to control the fuel tank pressure monitoring device to execute the reference pressure mode when it is in a stable state; the emergency control unit is used to control the fuel tank pressure monitoring device to execute the interlocking intervention operation in the abnormal compartment according to the interlocking control scheme when the fuel tank pressure monitoring device detects an abnormal state.

2. A ship emission carbon capture and fuel tank pressure interlock control system according to claim 1, characterized in that: The carbon capture device includes a device housing and a multi-source collection device, a component analysis device, a state determination module and a transmission module arranged in the housing; The multi-source acquisition device is used to synchronously acquire CO2 concentration data and temperature and humidity monitoring data; The component analysis device is used to extract the periodic fluctuation characteristics of emission data; The state determination module is used to calculate the correlation between the current cycle fluctuation characteristics and the historical standard mode based on the BP neural network, determine the carbon capture efficiency abnormality index, and trigger the interlock signal according to the calculation result; The transmission module is used to upload monitoring data to the interlocking control unit.

3. A ship emission carbon capture and fuel tank pressure interlock control system according to claim 1, characterized in that: The fuel tank pressure monitoring device includes a monitoring box and a pressure sensing module, a parameter detection module, a command response module and a communication conversion module arranged in the box.

4. A ship emission carbon capture and fuel tank pressure interlock control system according to claim 3, characterized in that: The recording of the pressure mutation period and parameter recovery period during the operation of the fuel tank pressure monitoring device includes: When the fuel tank pressure monitoring device detects a sudden change in pressure, it records the timestamp data of the time when the sudden change occurs, continuously monitors the parameter recovery critical point through the parameter detection module, and records the cycle number of the recovery time.

5. A ship emission carbon capture and fuel tank pressure interlock control system according to claim 4, characterized in that: Determining the abnormal compartment according to the pressure mutation period and the parameter recovery period includes: Generate mutation coordinates and recovery coordinates based on timestamp data and cycle number; The mutation coordinates, recovery coordinates and the position of the carbon capture device are spatially correlated to form a closed area, which is marked as an abnormal compartment.

6. A ship emission carbon capture and fuel tank pressure interlock control system according to claim 5, characterized in that: The controlling of the carbon capture device to maintain a preset interlock threshold for abnormal pressure and recording the change parameters, generating a pressure characteristic curve according to the change parameters and performing pressure distribution mapping on the fuel tank structure diagram comprises the following steps: Controlling the carbon capture device to adjust the output power of the abnormal compartment, and obtaining pressure parameters in real time through a parameter detection module; A preset interlock threshold range is provided. If the pressure parameter exceeds the preset interlock threshold range, the carbon capture device is controlled to maintain operation at the preset interlock threshold; Continuously record the pressure output value of the carbon capture device to form a set of changing parameters; According to the set of changing parameters, the BP neural network algorithm is used to generate the pressure dynamic characteristic curve; Extracting a number of key feature points at equal time intervals from the pressure dynamic characteristic curve, wherein the number of the key feature points is proportional to the duration of the curve; The pressure distribution mapping of the fuel tank structure diagram is annotated based on the extracted key feature points.

7. A ship emission carbon capture and fuel tank pressure interlock control system according to claim 6, characterized in that: The energy supply path optimization of the fuel tank structure diagram that has completed the pressure distribution mapping includes logically isolating the preset energy supply path overlapping with the high-pressure section in the fuel tank structure diagram after marking the pressure distribution mapping on the fuel tank structure diagram.

8. A ship emission carbon capture and fuel tank pressure interlock control system according to claim 1, characterized in that: When the fuel tank pressure monitoring device detects an abnormal state, controlling it to perform an interlock intervention operation in the abnormal compartment according to the interlock control scheme includes: S1. Select the abnormal compartment access location with the shortest operation process based on the next energy supply node to be switched; S2. Controlling the fuel tank pressure monitoring device to switch to the access position and perform parameter synchronization; S3, controlling the fuel tank pressure monitoring device to cut into the abnormal compartment from the access position and perform state adjustment according to the energy supply path in the interlocking control scheme; S4. Obtain the output index of the fuel tank pressure monitoring device in real time and dynamically correct the output index using the particle swarm optimization algorithm; S5. After each continuous power supply operation is completed in the abnormal compartment, the fuel tank pressure monitoring device is controlled to suspend output and exit the abnormal compartment, and S1 is executed again.

9. A ship emission carbon capture and fuel tank pressure interlock control system according to claim 8, characterized in that: Said S1 comprises the following steps: The feasible access locations of each abnormal compartment are calculated using the A* algorithm, and a comprehensive evaluation is performed based on the operation process and spatial distance parameters; Based on the comprehensive assessment results, select the abnormal compartment access location with the shortest operation process and the smallest spatial distance; The comprehensive evaluation based on the operation process and spatial distance parameters includes: A two-dimensional evaluation matrix containing the number of operation process steps and spatial distance values ​​was established; After normalizing the two-dimensional evaluation matrix, the first principal component is extracted using the hierarchical analysis method as a comprehensive evaluation index; The interlocking logic processing unit is used to select the abnormal compartment access position with the largest comprehensive evaluation index value.

10. A ship emission carbon capture and fuel tank pressure interlock control system according to claim 2, characterized in that: The calculation of the correlation between the current periodic fluctuation characteristics and the historical standard pattern based on the BP neural network includes: Input the current cycle fluctuation characteristics and the historical standard pattern into the BP neural network model, wherein the number of nodes in the hidden layer of the model is 1.5 times the number of nodes in the input layer; Adjust the model weights through the back-propagation algorithm and calculate the correlation coefficient value of the output layer as the correlation calculation result; The determination of the carbon capture efficiency abnormality index includes comparing the correlation coefficient value with a preset threshold value, and if the correlation coefficient value is less than the preset threshold value, determining that the abnormality index is at a high risk level.

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