Self-adaptive ship navigation terminal

Abstract

The invention relates to the technical field of ship navigation, and discloses a self-adaptive ship navigation terminal. A navigation environment sensing module of the terminal collects dynamic parameters of a ship navigation environment in real time through a multi-source sensor and sends the dynamic parameters to a self-adaptive control decision module and a remote monitoring platform; the adaptive control decision module obtains navigation deviation based on the real-time parameters and preset navigation parameters, calculates a control instruction through a fuzzy adaptive algorithm and sends the control instruction to the course adjustment execution module; the course adjustment execution module executes steering or navigational speed adjustment according to the control instruction and corrects a navigation track; the navigation state evaluation module monitors the adjusting process, generates a state signal and sends the state signal to the remote monitoring platform, and the remote monitoring platform gives out early warning when receiving the early warning signal. According to the terminal, a navigation strategy is dynamically adjusted by utilizing a fuzzy adaptive algorithm through multi-module cooperation, and the navigation adaptability and safety of a ship in a complex environment are improved in combination with real-time state evaluation and remote early warning.

Description

Technical Field

[0001] The present invention relates to the technical field of ship navigation, and in particular to an adaptive ship navigation terminal. Background Art

[0002] During a ship's voyage, the accuracy and adaptability of the navigation system are directly related to navigation efficiency and safety. With the development of the shipping industry, the navigation environment is becoming increasingly complex. From open waters to confined waters such as nearshore narrow channels and bridge areas, and from calm sea conditions to sudden disturbances such as wind, waves, and strong currents, higher requirements are placed on the dynamic response capabilities of the navigation system.

[0003] Traditional ship navigation relies heavily on manual operation or early automated navigation systems. Manual navigation requires crew members to rely on experience, combined with equipment such as nautical charts and radar, to determine navigational status. This is not only labor-intensive but also prone to deviations from the route due to fatigue and misjudgment during long voyages. While early automated navigation systems reduced manual intervention, they often employed fixed control logic, with algorithmic parameters pre-set at design time, making them incapable of adapting to changing environmental factors. For example, when a ship encounters a sudden strong wind, the sudden change in water speed and direction can subject the ship to additional lateral forces. Fixed-parameter control systems are unable to adjust the adjustment range in a timely manner, resulting in a gradual increase in navigational deviations.

[0004] Although some existing adaptive navigation systems have introduced environmental perception functions, they use a single sensor type and mostly rely solely on GPS positioning and radar obstacle detection, ignoring key environmental parameters such as water velocity, water temperature, and wave period. The lack of these parameters will lead to the system's one-sided judgment of the navigation environment. For example, in estuaries, changes in water velocity will significantly affect the ship's steering response, and relying solely on GPS data cannot accurately predict the ship's trajectory deviation trend. At the same time, the decision-making process of existing systems mostly uses conventional PID control algorithms. When dealing with nonlinear and time-varying navigation environments, this algorithm has difficulty in parameter adjustment and is prone to overshoot or adjustment lag. When a ship enters shallow water from deep water, the resistance to the hull changes. Conventional algorithms have difficulty quickly adapting to this dynamic characteristic, resulting in asynchronous speed adjustment and steering operations, further exacerbating trajectory deviations.

[0005] Existing navigation systems have weak status monitoring capabilities, mostly recording only the operating parameters of the equipment and lacking real-time assessment of the adjustment process. When mechanical wear or response delays occur in the heading adjustment execution module, the system is unable to detect them in time and does not issue an alarm until the deviation accumulates to a significant level, at which point the best opportunity for correction has been missed. Remote monitoring functions are also insufficient. Most systems can only receive and store navigation data and cannot be linked to status assessments. Shore-based managers find it difficult to grasp the abnormal status of the ship in a timely manner. In severe weather or complex waters, this lag may cause safety accidents such as collisions and groundings. These problems make it difficult for existing ship navigation technology to meet the needs of efficient and safe navigation when dealing with complex dynamic environments. There is an urgent need for an adaptive navigation terminal with comprehensive perception, dynamic decision-making, real-time adjustment and intelligent early warning capabilities. Summary of the Invention

[0006] The object of the present invention is to provide an adaptive ship navigation terminal to solve the problems raised in the above background technology.

[0007] To achieve the above object, the present invention provides an adaptive ship navigation terminal, the terminal comprising:

[0008] Navigation environment perception module, adaptive control decision module, heading adjustment execution module, navigation status assessment module and remote monitoring platform;

[0009] The navigation environment perception module collects the dynamic parameters of the ship's navigation environment in real time through multi-source sensors, and sends the real-time parameter values ​​of the ship's navigation environment to the adaptive control decision module and the remote monitoring platform. The remote monitoring platform displays the real-time parameter values ​​of the ship's navigation environment;

[0010] The adaptive control decision module obtains the navigation deviation based on the real-time parameter value of the ship's navigation environment and the preset navigation parameter value, calculates the control instruction of the heading adjustment execution module according to the navigation deviation through the fuzzy adaptive algorithm, and sends the control instruction to the heading adjustment execution module;

[0011] The heading adjustment execution module executes steering or speed adjustment operations according to the control instructions to correct the ship's navigation track; the navigation status evaluation module monitors the adjustment process of the heading adjustment execution module, judges the operating status of the heading adjustment execution module, and generates a normal status signal or a status warning signal accordingly, and sends the normal status signal or status warning signal to the remote monitoring platform. The remote monitoring platform issues an early warning when it receives the status warning signal.

[0012] Preferably, the specific analysis process of the navigation status evaluation module includes:

[0013] Through dynamic process hierarchical evaluation, the corresponding heading adjustment process is marked as an invalid adjustment process or a valid adjustment process. An evaluation period is set, and the ratio of the number of invalid adjustment processes to the total number of heading adjustment processes within the evaluation period is calculated to obtain the invalid adjustment ratio. If the invalid adjustment ratio exceeds the preset invalid ratio threshold, a status warning signal is generated;

[0014] If the invalid adjustment ratio does not exceed the preset invalid ratio threshold, the response speed value of the corresponding heading adjustment process is calculated by difference with the median of the preset response speed range and the absolute value is taken to obtain the response deviation value, and the ratio of the trajectory stability value of the corresponding adjustment process to the preset stability threshold is marked as the trajectory stability coefficient; the average response deviation is obtained by averaging the response deviation values ​​of all heading adjustment processes within the evaluation period, and the average stability coefficient is obtained by averaging the trajectory stability coefficients of all heading adjustment processes within the evaluation period;

[0015] The status evaluation value is obtained by numerically calculating the invalid adjustment ratio, the average response deviation and the average stability coefficient. If the status evaluation value exceeds the preset evaluation threshold, a status warning signal is generated. If the status evaluation value does not exceed the preset evaluation threshold, a status normal signal is generated.

[0016] Preferably, the specific analysis process of the dynamic process hierarchical evaluation is as follows:

[0017] The time when the heading adjustment execution module receives the control instruction is collected and marked as the starting time, and the time when the heading adjustment execution module completes the corresponding heading adjustment operation is collected and marked as the ending time, and the interval between the starting time and the ending time is marked as the adjustment time;

[0018] The ratio of the control command to the adjustment time is marked as the response speed value, and the trajectory stability value is obtained through trajectory smoothness analysis. If the response speed value is not within the preset response speed range or the trajectory stability value exceeds the preset stability threshold, the corresponding heading adjustment process is marked as an invalid adjustment process; if the response speed value is within the preset response speed range and the trajectory stability value does not exceed the preset stability threshold, the corresponding heading adjustment process is marked as a valid adjustment process.

[0019] Preferably, the specific analysis process of trajectory smoothness analysis is as follows:

[0020] A rectangular coordinate system is established with time as the horizontal axis and the actual track deviation as the vertical axis, and the track deviation curve of the ship during the corresponding heading adjustment process is obtained. The track deviation curve is placed in the rectangular coordinate system, and the starting point of the track deviation curve is located on the vertical axis;

[0021] Several sampling points are set on the track deviation curve, and the longitudinal distance between two adjacent groups of sampling points is marked as the deviation change. The variance of all deviation changes is calculated to obtain a fluctuation index, and the proportion of deviation changes that are not within the preset deviation change range is marked as the abnormal fluctuation proportion. The trajectory stability value of the corresponding heading adjustment process is obtained by numerically calculating the fluctuation index and the abnormal fluctuation proportion.

[0022] Preferably, the navigation status evaluation module is communicatively connected to the equipment abnormality diagnosis module, and the navigation status evaluation module sends a normal status signal to the equipment abnormality diagnosis module. When the equipment abnormality diagnosis module receives the normal status signal, it performs abnormality diagnosis analysis on the heading adjustment execution module, generates an equipment failure warning signal or an equipment normal signal through analysis, and sends the equipment failure warning signal or the equipment normal signal to the remote monitoring platform. When the remote monitoring platform receives the equipment failure warning signal, it issues a warning.

[0023] Preferably, the specific analysis process of abnormal diagnosis analysis is as follows:

[0024] During the operation of the heading control execution module, the operating temperature and mechanical vibration frequency of the heading control execution module are collected. If the operating temperature or the mechanical vibration frequency exceeds a corresponding preset threshold, it is determined that the heading control execution module is in an abnormal operating state.

[0025] Obtain the duration of the abnormal operation of the heading adjustment execution module during the evaluation period and calculate the ratio of the duration to the total operation duration of the heading adjustment execution module during the evaluation period to obtain the abnormal operation ratio, and mark the frequency of occurrence of a single duration of the abnormal operation of the heading adjustment execution module during the evaluation period exceeding the corresponding preset single duration threshold as an excessively long abnormal frequency, and mark the maximum value of the single duration of the abnormal operation of the heading adjustment execution module during the evaluation period as the maximum abnormal duration;

[0026] The equipment abnormality index is obtained by numerically calculating the abnormal operation ratio, the frequency of excessive abnormalities and the longest abnormal duration. If the equipment abnormality index exceeds the preset abnormality index threshold, an equipment failure warning signal is generated; if the equipment abnormality index does not exceed the preset abnormality index threshold, a equipment normal signal is generated.

[0027] Preferably, the remote monitoring platform is communicated with the equipment life prediction module. When a status warning signal or an equipment failure warning signal is generated, the equipment life prediction module will perform a life assessment on the heading adjustment execution module, determine through analysis whether to generate a replacement warning signal, and send the replacement warning signal to the remote monitoring platform. The remote monitoring platform will issue a warning when it receives the replacement warning signal.

[0028] Preferably, the specific analysis process of the equipment life prediction module is as follows:

[0029] The production date of the heading adjustment execution module is collected, and the time difference between the current date and the production date of the heading adjustment execution module is calculated to obtain the equipment usage time, and the total time the heading adjustment execution module is in operation during the historical operation stage is marked as the cumulative operation time;

[0030] And through analysis, the environmental loss time of the heading adjustment execution module is obtained, and the frequency of the maintenance interval time of the heading adjustment execution module exceeding the preset maintenance interval threshold in the historical operation stage is marked as the maintenance abnormality coefficient; the equipment life assessment value is obtained by numerically calculating the equipment usage time, cumulative operating time, environmental loss time and maintenance abnormality coefficient. If the equipment life assessment value exceeds the preset life threshold, a replacement warning signal is generated.

[0031] Preferably, the method for analyzing and obtaining the environmental loss duration is as follows:

[0032] The seawater salt spray concentration and ambient temperature of the environment in which the heading control execution module is located are collected, and the deviation of the seawater salt spray concentration from the set appropriate salt spray concentration standard value is marked as a salt spray deviation value, and the deviation of the ambient temperature from the set appropriate temperature standard value is marked as a temperature deviation value;

[0033] The humidity of the environment in which the heading adjustment execution module is located is collected and marked as the ambient humidity value. The environmental loss index is obtained by numerically calculating the salt spray deviation value, the temperature deviation value and the ambient humidity value. If the environmental loss index exceeds the preset loss index threshold, the heading adjustment execution module is judged to be in a high-loss state. The total duration of the heading adjustment execution module in the high-loss state during the historical operation stage is obtained and marked as the environmental loss duration.

[0034] Preferably, the remote monitoring platform is communicatively connected to the emergency response dispatch module, which receives the status warning signal sent by the navigation status evaluation module or the equipment failure warning signal sent by the equipment abnormality diagnosis module, and calls the preset emergency processing strategy according to the level of the warning signal; the emergency processing strategy includes automatically switching to the backup navigation mode, sending a distress signal to a nearby maritime rescue center, and generating an emergency obstacle avoidance path for the ship. The emergency response dispatch module sends the emergency obstacle avoidance path to the heading adjustment execution module to perform an emergency steering operation.

[0035] Compared with the prior art, the present invention has the following beneficial effects:

[0036] The adaptive ship navigation terminal proposed in this invention has achieved a qualitative improvement in environmental perception. The navigation environment perception module uses multi-source sensors to work together, and can simultaneously capture multiple dynamic parameters such as wind speed, wind direction, water flow speed, water flow direction, obstacle distance, water temperature, etc. Compared with traditional single sensor systems, the environmental information it obtains is more comprehensive and three-dimensional. This multi-dimensional data collection method enables the system to more accurately grasp the real-time environment of the ship. For example, when sailing in a bridge area, it can not only detect the position of the bridge piers through radar, but also use water flow sensors to perceive the degree of turbulence in the water flow in the bridge area, providing a richer basis for subsequent decision-making and avoiding judgment bias caused by missing information.

[0037] The fuzzy adaptive algorithm introduced in the adaptive control decision module breaks the limitations of traditional fixed parameter control. Rather than relying on a fixed, preset adjustment mode, the algorithm dynamically adjusts the calculation logic based on the deviation between real-time parameters and preset ones. When a ship encounters sudden environmental changes, such as a sudden surge in navigation deviation caused by a sudden strong wind, the fuzzy adaptive algorithm quickly converges on the deviation data and generates control instructions adapted to the current environment, ensuring the timeliness and accuracy of the adjustment instructions. This dynamic decision-making capability makes the system more adaptable to nonlinear and time-varying navigation environments, effectively avoiding the adjustment lag and overshoot problems caused by fixed parameters in traditional algorithms.

[0038] The heading adjustment execution module synchronizes steering and speed adjustments based on control commands, changing the traditional system's step-by-step approach to steering and speed adjustments. This synchronized operation allows for faster corrections to the vessel's trajectory, reducing the window for accumulated deviations. For example, when a vessel needs to circumvent a sudden obstacle, the system can simultaneously adjust the rudder angle and speed, enabling the vessel to circumvent the obstacle on an optimal trajectory, rather than steering first and then slowing down, or slowing down first and then steering, thereby reducing the risk of collision.

[0039] The introduction of the navigation status assessment module fills a gap in the existing system's adjustment process monitoring. Rather than simply recording equipment operating parameters statically, the module tracks the course adjustment execution module's adjustment process in real time. By analyzing dynamic indicators such as the rate of change of steering angle, the response time of speed adjustment, and the frequency of actuator movement, it accurately determines its operating status. When abnormal conditions such as adjustment delays or stuck actuators occur, the module promptly generates status warning signals. This real-time assessment capability enables the system to issue warnings at the incipient stage of a fault, rather than waiting until deviations escalate or equipment fails before issuing an alarm.

[0040] The linkage mechanism between the remote monitoring platform and various modules enhances remote navigation control capabilities. The platform not only receives and displays dynamic parameters collected by the navigation environment perception module in real time, allowing shore-based management personnel to keep abreast of the vessel's environment and navigation status, but also interfaces with the navigation status assessment module to issue warnings immediately upon receiving an early warning signal. This linkage mechanism enables shore-based personnel to promptly intervene in abnormal situations. For example, upon receiving an early warning signal from the heading adjustment execution module, they can remotely guide the crew to conduct maintenance or provide evasive measures based on real-time environmental parameters, thus avoiding delayed emergency response due to information transmission delays. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] Figure 1 This is a working principle diagram of the adaptive ship navigation terminal of the present invention;

[0042] Figure 2 Workflow diagram for hierarchical assessment of dynamic processes;

[0043] Figure 3 Workflow diagram for trajectory smoothness analysis;

[0044] Figure 4 Flowchart for abnormality diagnosis analysis. DETAILED DESCRIPTION

[0045] 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.

[0046] See also Figure 1 The present invention provides an adaptive ship navigation terminal, which includes: a navigation environment perception module, an adaptive control decision module, a heading adjustment execution module, a navigation status evaluation module and a remote monitoring platform. The specific implementation steps are as follows:

[0047] The navigation environment perception module collects dynamic parameters of the vessel's navigation environment in real time through multiple sensors, including but not limited to GPS positioning sensors, wind speed sensors, water velocity sensors, and obstacle detection radar. These dynamic parameters include the vessel's real-time position, speed, heading angle, distance to surrounding obstacles, wind speed, and water velocity and direction. Once collected, the navigation environment perception module synchronously transmits these real-time parameter values ​​to the adaptive control decision module and the remote monitoring platform. The remote monitoring platform visualizes these real-time parameter values ​​through devices such as display screens, allowing monitoring personnel to obtain a real-time overview of the vessel's navigation environment.

[0048] The adaptive control decision module pre-stores preset navigation parameter values, including the planned route, preset speed range, and preset heading angle. After receiving the real-time parameter values ​​from the navigation environment perception module, the adaptive control decision module compares these with the preset navigation parameter values ​​and calculates the navigation deviation, which includes position deviation, speed deviation, and heading deviation. The adaptive control decision module then uses a fuzzy adaptive algorithm to calculate these navigation deviations and generates control instructions for the heading control execution module. These control instructions specifically include the steering angle and speed adjustment value, and then send these control instructions to the heading control execution module.

[0049] After receiving the control command, the heading adjustment execution module controls the ship's steering gear to perform steering operations according to the steering angle in the command, and controls the ship's power system to perform speed adjustment operations according to the speed adjustment value in the command, thereby correcting the ship's navigation trajectory and making the ship sail as close to the preset route as possible.

[0050] The navigation status assessment module continuously monitors the course adjustment execution module's adjustment process, collecting various data in real time to determine the module's operational status. Based on the assessment results, it generates a normal status signal or a status warning signal, which is also sent to the remote monitoring platform. When the remote monitoring platform receives the status warning signal, it issues an alert through devices such as audio and visual alarms, alerting monitoring personnel to any abnormalities in the vessel's navigation system.

[0051] Example 1: See Figure 2 When the navigation state assessment module monitors the adjustment process of the heading adjustment execution module, it analyzes each heading adjustment process through a dynamic process hierarchical assessment, thereby marking it as an invalid adjustment process or a valid adjustment process. In the dynamic process hierarchical assessment, it is first necessary to determine the operation time nodes of the heading adjustment execution module. Specifically, the moment when the module receives the control instruction is collected as the starting moment, and the moment when the module completes the corresponding heading adjustment operation is collected as the ending moment. The interval between the two moments is the adjustment time.

[0052] After obtaining the adjustment time, the ratio of the control command to the adjustment time is calculated to obtain the response speed value, which reflects the speed of the heading adjustment execution module's response to the control command. Simultaneously, a trajectory smoothness analysis is performed to obtain the trajectory stability value, which is used to measure the smoothness of the ship's track during the adjustment process. The response speed value is then compared with the preset response speed range, and the trajectory stability value is compared with the preset stability threshold. If the response speed value is not within the preset response speed range, or the trajectory stability value exceeds the preset stability threshold, the heading adjustment process is marked as invalid. If the response speed value is within the preset response speed range and the trajectory stability value does not exceed the preset stability threshold, the heading adjustment process is marked as valid.

[0053] After marking a single heading adjustment process, the navigation status assessment module sets an assessment cycle. The duration of the assessment cycle can be set based on the actual needs of the ship's navigation, for example, a few hours or a day. The specific duration needs to be determined based on the complexity of the ship's navigation environment and the requirements of the navigation mission. During each assessment cycle, the total number of all heading adjustment processes within that period is counted, and the number of those marked as invalid is also counted. The ratio of the number of invalid adjustment processes to the total number is then calculated to obtain the invalid adjustment percentage.

[0054] When the proportion of invalid adjustments exceeds the preset invalid ratio threshold, the navigation status assessment module directly generates a status warning signal and sends it to the remote monitoring platform. If the proportion of invalid adjustments does not exceed the preset invalid ratio threshold, further analysis of the response speed and trajectory stability of the adjustment process is required. First, the median of the preset response speed range is determined. The difference between the response speed value of each valid adjustment process and this median is calculated and the absolute value is taken to obtain the response deviation value of each adjustment process. At the same time, the ratio of the trajectory stability value of each valid adjustment process to the preset stability threshold is calculated to obtain the trajectory stability coefficient of each adjustment process.

[0055] After obtaining the response deviation values ​​for all valid adjustment processes within the evaluation period, these response deviation values ​​are averaged to obtain the average response deviation, which reflects the overall deviation of the response speed within the period. Similarly, the trajectory stability coefficients of all valid adjustment processes within the evaluation period are averaged to obtain the average stability coefficient, which reflects the overall level of trajectory stability within the period.

[0056] The navigation status assessment module then performs a comprehensive numerical calculation of the invalid adjustment ratio, average response deviation, and average stability coefficient to obtain a status assessment value. During the calculation process, different weights are assigned to each indicator based on its importance, and the final status assessment value is obtained through weighted processing. If the status assessment value exceeds the preset assessment threshold, a status warning signal is generated; if the status assessment value does not exceed the preset assessment threshold, a status normal signal is generated. The generated status warning signal or status normal signal is sent to the remote monitoring platform. Upon receiving the status warning signal, the remote monitoring platform will issue an early warning through its own early warning mechanism to alert relevant personnel to possible abnormalities in the operating status of the heading adjustment execution module.

[0057] Throughout the entire process, all data collection, calculations, and signal generation are performed continuously to ensure that the navigation status assessment module can monitor the operation of the heading adjustment execution module in real time and promptly identify any potential problems. The setting of the assessment cycle can be adjusted according to the actual application scenario to adapt to the requirements for assessment frequency in different navigation environments. Parameters such as the preset invalid ratio threshold, preset response speed range, preset stability threshold, and preset assessment threshold are all pre-set based on a large amount of ship navigation data and the performance parameters of the heading adjustment execution module. These parameters can be appropriately adjusted based on factors such as the type of ship, the characteristics of the navigation area, and the model of the module to ensure the accuracy and applicability of the assessment results.

[0058] Example 2: See Figure 3 , trajectory smoothness analysis is used to obtain the trajectory stability value during the heading adjustment process, and the process begins with the establishment of a coordinate system. A plane rectangular coordinate system is constructed with time as the horizontal axis and the actual track deviation as the vertical axis, where the actual track deviation refers to the distance difference between the actual navigation trajectory of the ship during the adjustment process and the preset route. When obtaining the track deviation curve of the corresponding heading adjustment process, it is necessary to continuously collect the position information during the adjustment process through the positioning system on the ship, record the real-time position of the ship once every fixed time interval, and then compare these real-time positions with the preset route to calculate the actual track deviation corresponding to each time point, and then connect these deviation values ​​according to the time sequence to form a track deviation curve. When placing the curve into the established rectangular coordinate system, it is necessary to ensure that the starting point of the curve corresponds to the vertical axis, that is, the actual track deviation value at the starting moment is presented on the vertical axis, so as to clearly reflect the deviation state at the beginning of the adjustment.

[0059] When setting sampling points on the track deviation curve, the number and interval of sampling points must be determined based on the total duration of the adjustment process. If the adjustment process is short, the number of sampling points can be appropriately reduced, and the interval can be set to a few seconds; if the adjustment process is long, the number of sampling points can be increased, and the interval can be set to more than ten seconds to ensure that the sampling points can evenly cover the entire track deviation curve and accurately reflect the changing trend of the curve. The longitudinal distance between two adjacent groups of sampling points is the deviation change. This distance is obtained by calculating the numerical difference between the two sampling points on the vertical axis. A positive value indicates an increase in deviation, and a negative value indicates a decrease in deviation. However, in subsequent calculations, only the magnitude of the change is of interest.

[0060] The fluctuation index is derived by calculating the variance of all deviation changes. The variance calculation begins by finding the average of all deviation changes. The difference between each deviation change and the average is then calculated. These differences are squared and summed, and finally divided by the total number of deviation changes. The resulting fluctuation index reflects the degree of dispersion in the deviation changes. A larger fluctuation index indicates more unstable deviation changes and more pronounced track fluctuations.

[0061] Calculating the abnormal fluctuation percentage requires first defining a preset deviation change range. This range is determined based on the vessel's navigation stability requirements and the performance of the heading control module. Deviation changes outside this range are considered abnormal fluctuations. The number of abnormal fluctuations among all deviation changes is counted and then the ratio is calculated to the total number of deviation changes to determine the abnormal fluctuation percentage. A higher percentage indicates a higher frequency of large deviation changes during the control process, and therefore poorer track stability.

[0062] Generating a trajectory stability value requires combining the fluctuation index and the abnormal fluctuation ratio. In practice, the fluctuation index and abnormal fluctuation ratio are first integrated according to a specific ratio. This integration process does not require a specific formula; instead, the numerical values ​​of the two are weighed to produce a trajectory stability value that reflects the overall stability of the trajectory. This value is inversely proportional to the stability of the trajectory: a larger trajectory stability value indicates a less stable trajectory; a smaller trajectory stability value indicates a more stable trajectory during the adjustment process, meeting the expected stability requirements.

[0063] The entire trajectory smoothness analysis process is continuously applied to each heading adjustment process. Through detailed decomposition and multi-dimensional analysis of the track deviation curve, the trajectory stability of the adjustment process is comprehensively evaluated from the aspects of the amplitude, frequency, and overall trend of the deviation changes. This provides a key judgment basis for the subsequent dynamic process classification evaluation, ensuring a more accurate and comprehensive assessment of the operating status of the heading adjustment execution module. In actual application, parameters such as the sampling point interval and the preset deviation change range can be adjusted according to the navigation requirements and route characteristics of different ships to adapt to diverse navigation scenarios.

[0064] Example 3: See Figure 4 The navigation status assessment module maintains a continuous communication connection with the equipment abnormality diagnosis module. When the navigation status assessment module generates a normal status signal, it immediately transmits the signal to the equipment abnormality diagnosis module. After receiving the normal status signal, the equipment abnormality diagnosis module immediately initiates abnormality diagnosis and analysis of the heading control execution module to further confirm whether there are any potential abnormalities in its operating status.

[0065] During the abnormality diagnosis and analysis process, the equipment abnormality diagnosis module uses temperature sensors deployed in key locations on the heading control actuator module to collect the module's operating temperature in real time. These temperature sensors can utilize contact thermocouples to accurately capture temperature changes during module operation. Furthermore, a vibration sensor collects the module's mechanical vibration frequency during operation. The vibration sensor can utilize a piezoelectric sensor, effectively sensing vibration signals generated by the module's internal mechanical components. After collecting the operating temperature and mechanical vibration frequency, the module compares the operating temperature with a preset temperature threshold, determined based on the module's heat resistance and operating environment. The module also compares the mechanical vibration frequency with a preset vibration frequency threshold, which is based on the module's vibration spectrum during normal operation. If the operating temperature exceeds the preset temperature threshold or the mechanical vibration frequency exceeds the preset vibration frequency threshold, the heading control actuator module is deemed to be operating abnormally.

[0066] An evaluation cycle is set. The evaluation cycle can be set based on the continuity of the ship's navigation and the needs of equipment monitoring, for example, a 4-hour evaluation cycle. During each evaluation cycle, the total duration of the heading adjustment execution module in an abnormal operating state is recorded by a timing device. At the same time, the total operating time of the module during the evaluation cycle is counted. The total operating time is the cumulative time the module is in the working state, excluding downtime or sleep time. The total duration of the abnormal operating state is calculated by ratioing the total operating time to the total operating time to obtain the abnormal operation ratio, which intuitively reflects the proportion of time the module is in an abnormal state during the evaluation cycle.

[0067] During the evaluation period, for each abnormal operation state, its single duration is recorded and compared with the preset single duration threshold. The preset single duration threshold is set according to the tolerance of the module for short-term abnormalities, for example, it is set to 10 minutes. The number of occurrences in which the single duration exceeds the preset single duration threshold is counted and marked as the excessive abnormality frequency, which reflects the frequency of long-term abnormal operation of the module. At the same time, the maximum value is selected from all the single abnormal operation durations and marked as the longest abnormal duration. The longest abnormal duration reflects the most serious degree of single abnormal operation of the module.

[0068] The device anomaly index is generated by combining the values ​​of abnormal operation ratio, long abnormal frequency, and longest abnormal duration. It is calculated in the following way:

[0069]

[0070] in, Indicates the device abnormality index. Indicates the abnormal operation ratio, Indicates the frequency of extremely long exceptions, Indicates the longest abnormal duration. 、 、 They are the weight coefficients of abnormal operation ratio, long abnormal frequency and longest abnormal duration. The weight coefficients are set according to the degree of influence of each indicator on the equipment abnormality, and .

[0071] The device anomaly index is compared with a preset anomaly index threshold, determined based on extensive equipment operating data and analysis of failure cases. If the device anomaly index exceeds the threshold, a device failure warning signal is generated; if it does not, a device normal signal is generated. This generated device failure warning signal or device normal signal is transmitted via a communication module to the remote monitoring platform. The remote monitoring platform is equipped with an early warning device. Upon receiving the device failure warning signal, the device activates and issues a corresponding warning prompt, allowing relevant personnel to be notified and take appropriate countermeasures.

[0072] Throughout the entire abnormality diagnosis and analysis process, data collection, calculation, and signal generation are automatically performed by the module's internal microprocessor, ensuring real-time and accurate analysis. Preset thresholds and weighting factors can be adjusted based on the type of vessel, the environmental characteristics of the navigation area, and the age of the heading control module to meet the equipment monitoring needs in different scenarios.

[0073] Example 4: The remote monitoring platform maintains a communication connection with the equipment life prediction module. When the remote monitoring platform receives a status warning signal or an equipment failure warning signal, it will immediately trigger the equipment life prediction module to start working and perform a life assessment on the heading adjustment execution module.

[0074] The equipment life prediction module first retrieves the production date from the built-in storage unit of the heading adjustment execution module. The production date is the date when the module is completed and inspected. The time difference between the current date and the production date is calculated, and the result is the equipment usage time. This time is measured in days, months, or years, and intuitively reflects the module's existence from production to the present. At the same time, the equipment life prediction module accesses the ship's historical operation database, which records the start and end time of each operation of the heading adjustment execution module. By summarizing and counting these time records, the total time the module has been in operation during the historical operation phase is obtained, and it is marked as the cumulative operation time. The cumulative operation time focuses on the sum of the time the module is actually working, and does not include idle or inactive time.

[0075] The analysis and acquisition of environmental loss duration requires sensors deployed around the heading control actuator module. The salt spray sensor collects the module's surrounding seawater salt spray concentration in real time, the temperature sensor collects the ambient temperature, and the humidity sensor collects the ambient humidity and marks it as the ambient humidity value. The system has pre-set standard values ​​for suitable salt spray concentration and temperature. The standard value for suitable salt spray concentration is determined based on the salt spray corrosion resistance of the module's housing material, while the standard value for suitable temperature is set based on the normal operating temperature range of the module's electronic components. The difference between the collected seawater salt spray concentration and the standard value for suitable salt spray concentration is calculated, and the result is marked as the salt spray deviation value. The difference between the ambient temperature and the standard value for suitable temperature is calculated, and the result is marked as the temperature deviation value. The positive and negative signs of the salt spray deviation and temperature deviation values ​​reflect the direction of deviation between the actual environmental parameters and the standard values, and their absolute values ​​reflect the degree of deviation.

[0076] Based on the salt spray deviation value, temperature deviation value, and ambient humidity value, an environmental loss index is calculated through internal logical operations. This index comprehensively reflects the degree of module loss caused by environmental factors. If the environmental loss index exceeds the preset loss index threshold, which is set based on the environmental loss limit that the module can withstand in long-term use, the heading control execution module is determined to be in a high-loss state. By querying historical operation records, the total duration of the module in the high-loss state during the historical operation phase is calculated and marked as the environmental loss duration. The environmental loss duration is directly related to the degree of module aging or damage caused by harsh environments.

[0077] The system also records maintenance records for the heading control module during historical operation, including the time of each maintenance. A preset maintenance interval threshold is set based on the module's maintenance manual and operational experience, for example, three months. The number of times the maintenance interval exceeds the preset threshold is counted and marked as a maintenance anomaly coefficient. A higher maintenance anomaly coefficient indicates poor module maintenance timeliness, potentially accelerating equipment wear and tear.

[0078] An internal evaluation model is used to generate an equipment life assessment value based on the equipment usage time, cumulative operating time, environmental wear and tear time, and maintenance anomaly coefficient. This assessment value comprehensively considers the impact of time factors, usage intensity, environmental impact, and maintenance status on the equipment life. The equipment life assessment value is compared with a preset life threshold, which is determined based on the module's design service life and the average service life of similar equipment. If the equipment life assessment value exceeds the preset life threshold, a replacement warning signal is generated. The replacement warning signal is sent to the remote monitoring platform via a communication link. Upon receiving the replacement warning signal, the remote monitoring platform issues a warning through audible and visual alarms, prompting relevant personnel to consider replacing the heading adjustment execution module.

[0079] Example 5: The remote monitoring platform establishes a stable communication connection with the emergency response dispatch module. This connection is achieved through the ship's internal local area network or dedicated communication lines, ensuring real-time and reliable signal transmission. The emergency response dispatch module's storage unit pre-stores multiple emergency response strategies. These strategies are categorized according to the severity of the warning signal. These strategies are classified according to the severity of the problem reflected by the warning signal. For example, the warning signal can be divided into three levels: minor warning, moderate warning, and severe warning. Different levels correspond to different emergency response measures.

[0080] When the Emergency Response Dispatch Module receives a status warning signal from the Navigation Status Assessment Module or an equipment failure warning signal from the Equipment Anomaly Diagnosis Module, it first identifies the warning signal's level. This identification is accomplished by parsing the level identifier contained in the signal, which is pre-set by the sending module based on the severity of the problem. Based on the identified warning signal level, the Emergency Response Dispatch Module retrieves the corresponding pre-set emergency response strategy from its storage unit, ensuring that the measures taken are appropriate to the severity of the problem.

[0081] Automatically switching to backup navigation mode within the emergency response strategy involves the emergency response dispatch module sending a start command to the vessel's backup navigation system. This system is independent of the primary navigation system, possessing its own sensors and control unit, and is normally in standby mode. Upon receiving the start command, the backup system immediately activates and takes over navigation duties. Simultaneously, the heading control module in the primary navigation system suspends operations until the fault is resolved.

[0082] When sending a distress signal to a nearby maritime rescue center, the emergency response dispatch module first obtains the ship's real-time location information, including latitude and longitude coordinates, from the navigation environment perception module. It then collects basic information about the ship, such as its name, tonnage, route, cargo type (if any), and any current faults. This information is then integrated into a distress signal and transmitted via satellite or shortwave communication to the nearest maritime rescue center, ensuring the rescue center can quickly understand the ship's situation and needs.

[0083] When generating a vessel's emergency obstacle avoidance path, the emergency response dispatch module first receives real-time environmental data collected by the navigation environment perception module. This data includes information such as the location, size, speed and direction (if dynamic), water depth, and prohibited areas of surrounding obstacles. Combined with parameters such as the vessel's current position, speed, heading, and steering performance, the module's internal path planning logic processes this data to create a path that avoids all obstacles and meets navigation safety requirements. The generation of the emergency obstacle avoidance path takes into account the vessel's inertia and turning radius to ensure that the path is within the vessel's actual maneuverability.

[0084] The emergency response dispatch module converts the generated emergency obstacle avoidance path into specific control instructions, including steering angle, steering timing, and speed adjustment values. It then sends these instructions to the heading control execution module. Upon receiving these instructions, the heading control execution module immediately activates the ship's steering gear and power system to execute the corresponding operations, performing an emergency turn according to the emergency obstacle avoidance path, ensuring the ship avoids obstacles in the shortest possible time and ensuring safe navigation.

[0085] Throughout the emergency response process, the emergency response dispatch module continuously receives real-time data from the navigation environment perception module, monitoring the vessel's position and changes in the surrounding environment. If new risks are detected in the original emergency obstacle avoidance path, the module immediately replans the path and issues new control instructions until the vessel is out of danger. The remote monitoring platform records the entire emergency response process in real time, including the time the warning signal is received, the emergency measures taken, the implementation of these measures, and changes in the vessel's status, providing data support for subsequent fault analysis and navigation summary.

[0086] 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.

[0087] 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. An adaptive ship navigation terminal, characterized in that: It includes navigation environment perception module, adaptive control decision module, heading adjustment execution module, navigation status assessment module and remote monitoring platform; The navigation environment perception module collects the dynamic parameters of the ship's navigation environment in real time through multi-source sensors, and sends the real-time parameter values ​​of the ship's navigation environment to the adaptive control decision module and the remote monitoring platform. The remote monitoring platform displays the real-time parameter values ​​of the ship's navigation environment; The adaptive control decision module obtains the navigation deviation based on the real-time parameter value of the ship's navigation environment and the preset navigation parameter value, calculates the control instruction of the heading adjustment execution module according to the navigation deviation through the fuzzy adaptive algorithm, and sends the control instruction to the heading adjustment execution module; The heading adjustment execution module performs steering or speed adjustment operations according to the control instructions to correct the ship's navigation track; The navigation status evaluation module monitors the adjustment process of the heading adjustment execution module, determines the operating status of the heading adjustment execution module, and generates a normal status signal or a status warning signal based on this. The normal status signal or status warning signal is sent to the remote monitoring platform, and the remote monitoring platform issues a warning when it receives the status warning signal.

2. The adaptive ship navigation terminal according to claim 1, characterized in that: The specific analysis process of the navigation status assessment module includes: Through dynamic process hierarchical evaluation, the corresponding heading adjustment process is marked as an invalid adjustment process or a valid adjustment process. An evaluation period is set, and the ratio of the number of invalid adjustment processes to the total number of heading adjustment processes within the evaluation period is calculated to obtain the invalid adjustment ratio. If the invalid adjustment ratio exceeds the preset invalid ratio threshold, a status warning signal is generated; If the invalid adjustment ratio does not exceed the preset invalid ratio threshold, the response speed value of the corresponding heading adjustment process is calculated by difference with the median of the preset response speed range and the absolute value is taken to obtain the response deviation value, and the ratio of the trajectory stability value of the corresponding adjustment process to the preset stability threshold is marked as the trajectory stability coefficient; the average response deviation is obtained by averaging the response deviation values ​​of all heading adjustment processes within the evaluation period, and the average stability coefficient is obtained by averaging the trajectory stability coefficients of all heading adjustment processes within the evaluation period; The status evaluation value is obtained by numerically calculating the invalid adjustment ratio, the average response deviation and the average stability coefficient. If the status evaluation value exceeds the preset evaluation threshold, a status warning signal is generated. If the status evaluation value does not exceed the preset evaluation threshold, a status normal signal is generated.

3. The adaptive ship navigation terminal according to claim 2, characterized in that: The specific analysis process of dynamic process grading assessment is as follows: The time when the heading adjustment execution module receives the control instruction is collected and marked as the starting time, and the time when the heading adjustment execution module completes the corresponding heading adjustment operation is collected and marked as the ending time, and the interval between the starting time and the ending time is marked as the adjustment time; The ratio of the control command to the adjustment time is marked as the response speed value, and the trajectory stability value is obtained through trajectory smoothness analysis. If the response speed value is not within the preset response speed range or the trajectory stability value exceeds the preset stability threshold, the corresponding heading adjustment process is marked as an invalid adjustment process; If the response speed value is within the preset response speed range and the trajectory stability value does not exceed the preset stability threshold, the corresponding heading adjustment process is marked as a valid adjustment process.

4. The adaptive ship navigation terminal according to claim 3, characterized in that: The specific analysis process of trajectory smoothness analysis is as follows: A rectangular coordinate system is established with time as the horizontal axis and the actual track deviation as the vertical axis, and the track deviation curve of the ship during the corresponding heading adjustment process is obtained. The track deviation curve is placed in the rectangular coordinate system, and the starting point of the track deviation curve is located on the vertical axis; Several sampling points are set on the track deviation curve, and the longitudinal distance between two adjacent groups of sampling points is marked as the deviation change. The variance of all deviation changes is calculated to obtain a fluctuation index, and the proportion of deviation changes that are not within the preset deviation change range is marked as the abnormal fluctuation proportion. The trajectory stability value of the corresponding heading adjustment process is obtained by numerically calculating the fluctuation index and the abnormal fluctuation proportion.

5. The adaptive ship navigation terminal according to claim 1, characterized in that: The navigation status assessment module is communicatively connected to the equipment abnormality diagnosis module. The navigation status assessment module sends a normal status signal to the equipment abnormality diagnosis module. When the equipment abnormality diagnosis module receives the normal status signal, it performs abnormal diagnosis analysis on the heading adjustment execution module, generates an equipment failure warning signal or an equipment normal signal through analysis, and sends the equipment failure warning signal or the equipment normal signal to the remote monitoring platform. When the remote monitoring platform receives the equipment failure warning signal, it issues a warning.

6. The adaptive ship navigation terminal according to claim 5, characterized in that: The specific analysis process of abnormal diagnosis analysis is as follows: During the operation of the heading control execution module, the operating temperature and mechanical vibration frequency of the heading control execution module are collected. If the operating temperature or the mechanical vibration frequency exceeds a corresponding preset threshold, it is determined that the heading control execution module is in an abnormal operating state. Obtain the duration of the abnormal operation of the heading adjustment execution module during the evaluation period and calculate the ratio of the duration to the total operation duration of the heading adjustment execution module during the evaluation period to obtain the abnormal operation ratio, and mark the frequency of occurrence of a single duration of the abnormal operation of the heading adjustment execution module during the evaluation period exceeding the corresponding preset single duration threshold as an excessively long abnormal frequency, and mark the maximum value of the single duration of the abnormal operation of the heading adjustment execution module during the evaluation period as the maximum abnormal duration; The equipment abnormality index is obtained by numerically calculating the abnormal operation ratio, the frequency of excessive abnormality, and the longest abnormal duration. If the equipment abnormality index exceeds the preset abnormality index threshold, an equipment failure warning signal is generated; If the device abnormality index does not exceed the preset abnormality index threshold, a device normal signal is generated.

7. The adaptive ship navigation terminal according to claim 1, characterized in that: The remote monitoring platform is communicated with the equipment life prediction module. When a status warning signal or an equipment failure warning signal is generated, the equipment life prediction module will perform a life assessment on the heading adjustment execution module, and determine through analysis whether to generate a replacement warning signal. The replacement warning signal will be sent to the remote monitoring platform, and the remote monitoring platform will issue a warning when it receives the replacement warning signal.

8. The adaptive ship navigation terminal according to claim 7, characterized in that: The specific analysis process of the equipment life prediction module is as follows: The production date of the heading adjustment execution module is collected, and the time difference between the current date and the production date of the heading adjustment execution module is calculated to obtain the equipment usage time, and the total time the heading adjustment execution module is in operation during the historical operation stage is marked as the cumulative operation time; And through analysis, the environmental loss time of the heading adjustment execution module is obtained, and the frequency of the maintenance interval time of the heading adjustment execution module exceeding the preset maintenance interval threshold in the historical operation stage is marked as the maintenance abnormality coefficient; the equipment life assessment value is obtained by numerically calculating the equipment usage time, cumulative operating time, environmental loss time and maintenance abnormality coefficient. If the equipment life assessment value exceeds the preset life threshold, a replacement warning signal is generated.

9. The adaptive ship navigation terminal according to claim 8, characterized in that: The analysis and acquisition method of environmental loss duration is as follows: The seawater salt spray concentration and ambient temperature of the environment in which the heading control execution module is located are collected, and the deviation of the seawater salt spray concentration from the set appropriate salt spray concentration standard value is marked as a salt spray deviation value, and the deviation of the ambient temperature from the set appropriate temperature standard value is marked as a temperature deviation value; The humidity of the environment in which the heading adjustment execution module is located is collected and marked as the ambient humidity value. The environmental loss index is obtained by numerically calculating the salt spray deviation value, the temperature deviation value and the ambient humidity value. If the environmental loss index exceeds the preset loss index threshold, the heading adjustment execution module is judged to be in a high-loss state. The total duration of the heading adjustment execution module in the high-loss state during the historical operation stage is obtained and marked as the environmental loss duration.

10. The adaptive ship navigation terminal according to claim 1, characterized in that: The remote monitoring platform is communicated with the emergency response dispatch module, which receives the status warning signal sent by the navigation status assessment module or the equipment failure warning signal sent by the equipment abnormality diagnosis module, and calls the preset emergency processing strategy according to the level of the warning signal; the emergency processing strategy includes automatically switching to the backup navigation mode, sending a distress signal to the nearby maritime rescue center, and generating an emergency obstacle avoidance path for the ship. The emergency response dispatch module sends the emergency obstacle avoidance path to the heading adjustment execution module to perform emergency steering operations.

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