An adaptive ship navigation terminal

Abstract

This invention relates to the field of ship navigation technology and discloses an adaptive ship navigation terminal. The terminal's navigation environment perception module collects dynamic parameters of the ship's navigation environment in real time through multi-source sensors and sends them to an adaptive control decision module and a remote monitoring platform. The adaptive control decision module obtains the navigation deviation based on real-time parameters and preset navigation parameters, calculates control commands using a fuzzy adaptive algorithm, and sends them to the heading adjustment execution module. The heading adjustment execution module executes steering or speed adjustments according to the control commands to correct the navigation trajectory. The navigation status assessment module monitors the adjustment process, generates status signals, and sends them to the remote monitoring platform. The remote monitoring platform issues warnings when it receives warning signals. This terminal, through multi-module collaboration, dynamically adjusts the navigation strategy using a fuzzy adaptive algorithm, and combines real-time status assessment with remote warnings, improving the ship's navigation adaptability and safety in complex environments.

Description

Technical Field

[0001] This invention relates to the field of ship navigation technology, specifically to an adaptive ship navigation terminal. Background Technology

[0002] During ship navigation, 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 seas to narrow waterways and bridge areas, and from calm sea conditions to sudden disturbances such as wind, waves, and strong currents. This places higher demands on the dynamic response capabilities of the navigation system.

[0003] Traditional ship navigation relies heavily on manual operation or early automated navigation systems. During manual navigation, crew members must rely on experience combined with charts, radar, and other equipment to assess the navigational status. This is not only physically demanding but also prone to fatigue and misjudgment during long voyages, leading to deviations from the intended course. While early automated navigation systems reduced human intervention, they often employed fixed control logic with pre-set algorithm parameters, making them ill-suited to changing environmental factors. For example, when a ship encounters sudden strong winds, the abrupt changes in water speed and direction can subject the ship to additional lateral forces. Fixed-parameter control systems cannot adjust their adjustments in time, causing navigational deviations to gradually increase.

[0004] While some existing adaptive navigation systems incorporate environmental perception capabilities, they rely on limited sensor types, primarily GPS positioning and radar obstacle detection, neglecting crucial environmental parameters such as water flow velocity, water temperature, and wave period. This lack of parameters leads to incomplete judgments about the navigation environment. For example, in estuaries, changes in water flow velocity significantly impact a vessel's steering response; GPS data alone cannot accurately predict trajectory deviations. Furthermore, existing systems often employ conventional PID control algorithms in their decision-making processes. These algorithms face significant challenges in parameter tuning when dealing with nonlinear and time-varying navigation environments, easily exhibiting overshoot or lag. When a vessel transitions from deep to shallow water, the resistance experienced by the hull changes, and conventional algorithms struggle to adapt quickly to this dynamic characteristic, resulting in asynchronous speed adjustments and steering maneuvers, further exacerbating trajectory deviations.

[0005] Existing navigation systems suffer from weak status monitoring capabilities, often merely recording equipment operating parameters and lacking real-time evaluation of the adjustment process. When mechanical wear or response delays occur in the heading adjustment module, the system fails to detect them promptly, only issuing an alarm when the deviation accumulates to a significant level, by which time the optimal correction opportunity has been missed. Remote monitoring functions are also inadequate; most systems can only receive and store navigation data, unable to link with status assessments. Shore-based management personnel struggle to promptly grasp abnormal vessel conditions, and in severe weather or complex waters, this lag can lead to collisions, groundings, and other safety accidents. These problems make existing ship navigation technology insufficient to meet the demands for efficient and safe navigation in complex and dynamic environments, necessitating an adaptive navigation terminal with comprehensive perception, dynamic decision-making, real-time adjustment, and intelligent early warning capabilities. Summary of the Invention

[0006] The purpose of this invention is to provide an adaptive ship navigation terminal to solve the problems mentioned in the background art.

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

[0008] The system includes a navigation environment perception module, an adaptive control decision module, a heading adjustment execution module, a navigation status assessment module, and a remote monitoring platform.

[0009] The navigation environment perception module collects 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 values ​​of the ship's navigation environment and the preset navigation parameter values. Based on the navigation deviation, it calculates the control command of the heading adjustment execution module through a fuzzy adaptive algorithm and sends the control command to the heading adjustment execution module.

[0011] The heading adjustment execution module performs steering or speed adjustment operations according to control commands to correct the ship's navigation trajectory; the navigation status assessment 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. When the remote monitoring platform receives the status warning signal, it issues a warning.

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

[0013] The corresponding heading adjustment process is marked as an ineffective or effective adjustment process through dynamic process classification assessment. An assessment period is set, and the ratio of the number of ineffective adjustment processes to the total number of heading adjustment processes within the assessment period is calculated to obtain the ineffective adjustment ratio. If the ineffective adjustment ratio exceeds the preset ineffective ratio threshold, a status warning signal is generated.

[0014] If the proportion of invalid adjustments does not exceed the preset invalid proportion threshold, the difference between the response speed value of the corresponding heading adjustment process and the median of the preset response speed range is calculated and the absolute value is taken to obtain the response deviation value. 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 state assessment value is obtained by numerically calculating the proportion of ineffective regulation, the average response deviation, and the average stability coefficient. If the state assessment value exceeds the preset assessment threshold, a state warning signal is generated; if the state assessment value does not exceed the preset assessment threshold, a state normal signal is generated.

[0016] The preferred method for dynamic process hierarchical evaluation is as follows:

[0017] The time when the heading adjustment execution module receives the control command is collected and marked as the start time, and the time when the heading adjustment execution module completes the corresponding heading adjustment operation is collected and marked as the end time. The interval between the start time and the end time is marked as the adjustment time.

[0018] The ratio of control command to 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 an effective adjustment process.

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

[0020] A Cartesian coordinate system is established with time as the horizontal axis and actual track deviation as the vertical axis. The track deviation curve of the ship during the corresponding heading adjustment process is obtained. The track deviation curve is placed in the Cartesian 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. The longitudinal distance between two adjacent sets of sampling points is marked as the deviation change. The variance of all deviation changes is calculated to obtain the fluctuation index. 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 assessment module is connected to the device anomaly diagnosis module. The navigation status assessment module sends a normal status signal to the device anomaly diagnosis module. When the device anomaly diagnosis module receives the normal status signal, it performs anomaly diagnosis analysis on the heading adjustment execution module. Through analysis, it generates a device fault warning signal or a device normal signal and sends the device fault warning signal or device normal signal to the remote monitoring platform. When the remote monitoring platform receives the device fault warning signal, it issues a warning.

[0023] The preferred method for abnormal diagnostic analysis is as follows:

[0024] During the operation of the heading adjustment execution module, its operating temperature and mechanical vibration frequency are collected. If the operating temperature or mechanical vibration frequency exceeds the corresponding preset threshold, the heading adjustment execution module is judged to be in an abnormal operating state.

[0025] The abnormal operation rate is calculated by comparing the duration of the abnormal operation of the heading adjustment execution module within the evaluation period with the total operation time of the heading adjustment execution module within the evaluation period. The frequency of occurrences in which the single duration of the abnormal operation of the heading adjustment execution module exceeds the corresponding preset single duration threshold is marked as an excessively long abnormal frequency. The maximum value of the single duration of the abnormal operation of the heading adjustment execution module within the evaluation period is marked as the longest abnormal duration.

[0026] The equipment anomaly index is obtained by numerically calculating the percentage of abnormal operation, the frequency of excessively long anomalies, and the longest anomaly duration. If the equipment anomaly index exceeds the preset anomaly index threshold, an equipment fault warning signal is generated; if the equipment anomaly index does not exceed the preset anomaly index threshold, an equipment normal signal is generated.

[0027] Preferably, the remote monitoring platform communicates with the equipment life prediction module. When a status warning signal or equipment fault warning signal is generated, the equipment life prediction module performs a life assessment on the heading adjustment execution module. Through analysis, it determines whether a replacement warning signal should be generated and sends the replacement warning signal to the remote monitoring platform. When the remote monitoring platform receives the replacement warning signal, it issues a warning.

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

[0029] The manufacturing date of the heading adjustment execution module is collected, and the time difference between the current date and the manufacturing date of the heading adjustment execution module is calculated to obtain the equipment usage time. The total time that the heading adjustment execution module was in operation during the historical operation phase is marked as the cumulative running time.

[0030] The environmental wear duration of the heading adjustment execution module is obtained through analysis, and the frequency of maintenance intervals exceeding the preset maintenance interval threshold for the heading adjustment execution module during historical operation is marked as a maintenance anomaly coefficient. The equipment life assessment value is obtained by numerically calculating the equipment usage time, cumulative running time, environmental wear duration, and maintenance anomaly coefficient. If the equipment life assessment value exceeds the preset life threshold, a replacement warning signal is generated.

[0031] The preferred method for analyzing and obtaining the duration of environmental degradation is as follows:

[0032] The seawater salt spray concentration and ambient temperature of the environment where the heading adjustment execution module is located are collected. The deviation of the seawater salt spray concentration from the set suitable salt spray concentration standard value is marked as the salt spray deviation value, and the deviation of the ambient temperature from the set suitable temperature standard value is marked as the temperature deviation value.

[0033] The system collects the humidity of the environment in which the heading adjustment execution module is located and marks it as the ambient humidity value. It calculates the environmental loss index by numerically calculating the salt spray deviation value, temperature deviation value and ambient humidity value. If the environmental loss index exceeds the preset loss index threshold, it is determined that the heading adjustment execution module is in a high loss state. It obtains the total duration of the heading adjustment execution module in a high loss state during the historical operation phase and marks it as the environmental loss duration.

[0034] Preferably, the remote monitoring platform is connected to the emergency response dispatch module. The emergency response dispatch module receives status warning signals sent by the navigation status assessment module or equipment failure warning signals sent by the equipment anomaly diagnosis module, and calls preset emergency handling strategies according to the level of the warning signal. The emergency handling strategies include automatically switching to the backup navigation mode, sending a distress signal to the nearest 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 turning 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 achieves a qualitative improvement in environmental perception. The navigation environment perception module employs multi-source sensors working collaboratively, simultaneously capturing various dynamic parameters such as wind speed, wind direction, water flow speed, water flow direction, obstacle distance, and water temperature. Compared to traditional single-sensor systems, it acquires more comprehensive and three-dimensional environmental information. This multi-dimensional data acquisition method allows the system to more accurately grasp the real-time environment in which the ship is located. For example, when navigating in a bridge area, it can not only detect the location of bridge piers using radar but also perceive the turbulence of the water flow in the bridge area using water flow sensors, providing richer evidence for subsequent decision-making and avoiding judgment biases caused by missing information.

[0037] The fuzzy adaptive algorithm introduced in the adaptive control decision module breaks through the limitations of traditional fixed-parameter control. This algorithm dynamically adjusts the calculation logic based on the deviation between real-time parameters and preset parameters, rather than relying on a fixed preset adjustment mode. When the ship encounters sudden environmental changes, such as a sudden increase in navigation deviation due to strong winds, the fuzzy adaptive algorithm can quickly converge the deviation data and generate control commands adapted to the current environment, ensuring the timeliness and accuracy of the adjustment commands. This dynamic decision-making capability enables the system to exhibit stronger adaptability in the face of nonlinear and time-varying navigation environments, effectively avoiding the adjustment lag or overshoot problems caused by fixed parameters in traditional algorithms.

[0038] The heading adjustment module can simultaneously execute steering and speed adjustments based on control commands, changing the traditional system's step-by-step approach. This synchronous operation mode can more quickly correct the ship's trajectory and reduce the time window for deviation accumulation. For example, when a ship needs to avoid a suddenly appearing obstacle, the system can adjust the rudder angle and speed simultaneously, allowing the ship to bypass the obstacle with a better trajectory, rather than turning first and then decelerating, or decelerating first and then turning, thereby reducing the risk of collision.

[0039] The navigation status assessment module fills a gap in the existing system's monitoring of the adjustment process. This module does not merely statically record equipment operating parameters, but tracks the course adjustment process of the module in real time. By analyzing dynamic indicators such as the rate of change of steering angle, the response time of speed adjustments, and the frequency of action of actuators, it accurately judges the operational status. When abnormalities such as adjustment lag or actuator jamming occur, the module can promptly generate status warning signals. This real-time assessment capability allows the system to issue alerts at the initial stage of a fault, rather than waiting until the deviation expands or the equipment fails before issuing a warning.

[0040] The linkage mechanism between the remote monitoring platform and its various modules enhances the remote control capabilities of navigation. 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 monitor the vessel's environment and navigation status at any time, but also links with the navigation status assessment module to issue immediate warnings upon receiving alert signals. This linkage mechanism enables shore-based personnel to intervene promptly in handling abnormal situations. For example, upon receiving a warning signal from the course adjustment execution module, they can remotely guide the crew to conduct maintenance or provide avoidance suggestions based on real-time environmental parameters, preventing delayed emergency response due to information transmission lag. Attached Figure Description

[0041] Figure 1 This is a schematic diagram illustrating the working principle of the adaptive ship navigation terminal described in this invention.

[0042] Figure 2 A flowchart for the hierarchical evaluation of dynamic processes;

[0043] Figure 3 A flowchart illustrating the workflow for trajectory smoothness analysis;

[0044] Figure 4 This is a flowchart for abnormal diagnosis and analysis. Detailed Implementation

[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] Please see Figure 1 This invention provides an adaptive ship navigation terminal, comprising: 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 ship's navigation environment in real time through multi-source sensors, including but not limited to GPS positioning sensors, wind speed sensors, water current speed sensors, and obstacle detection radar. The collected dynamic parameters cover the ship's real-time position, speed, heading angle, distance to surrounding obstacles, wind speed, and water current speed and direction. After collection, the navigation environment perception module synchronously sends these real-time parameter values ​​to the adaptive control decision module and the remote monitoring platform. The remote monitoring platform visualizes the received real-time parameter values ​​through displays and other devices, enabling monitoring personnel to monitor the ship's navigation environment in real time.

[0048] The adaptive control decision module pre-stores preset navigation parameter values, including the planned route, preset speed range, and preset heading angle. Upon receiving real-time parameter values ​​from the navigation environment perception module, the adaptive control decision module compares these real-time values ​​with the preset navigation parameter values ​​to calculate the navigation deviation, which includes position deviation, speed deviation, and heading deviation. Subsequently, based on this navigation deviation, the adaptive control decision module uses a fuzzy adaptive algorithm to generate control commands for the heading adjustment execution module. These control commands specifically include turning angles and speed adjustment values, and are then sent to the heading adjustment 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 as possible to the preset route.

[0050] The navigation status assessment module continuously monitors the heading 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 either a normal status signal or a status warning signal, which is also sent to the remote monitoring platform. When the remote monitoring platform receives a status warning signal, it issues an alert via audible and visual alarms, prompting monitoring personnel to pay attention to any abnormalities in the ship's navigation system.

[0051] Example 1: See Figure 2 When the navigation status assessment module monitors the heading adjustment execution module's adjustment process, it analyzes each heading adjustment process through dynamic process hierarchical assessment, thereby marking it as an ineffective or effective adjustment process. In the dynamic process hierarchical assessment, the operation time nodes of the heading adjustment execution module must first be determined. Specifically, the moment the module receives the control command is collected as the start moment, and the moment the module completes the corresponding heading adjustment operation is collected as the end moment. The interval between these 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 how quickly the heading adjustment execution module responds to the control command. Simultaneously, a trajectory stability value is obtained through trajectory smoothness analysis, which measures the smoothness of the ship's trajectory during the adjustment process. Then, the response speed value is compared with a preset response speed range, and the trajectory stability value is compared with a preset stability threshold. If the response speed value is outside the preset response speed range, or the trajectory stability value exceeds the preset stability threshold, the heading adjustment process is marked as invalid; conversely, 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 period. The duration of the assessment period can be set according to the actual needs of the ship's navigation, such as several hours or a day. The specific duration needs to be determined based on the complexity of the navigation environment and the requirements of the navigation mission. Within each assessment period, the total number of all heading adjustments within that period is counted, along with the number of those marked as invalid adjustments. Then, the ratio of invalid adjustments to the total number is calculated to obtain the invalid adjustment percentage.

[0054] When the proportion of ineffective adjustments exceeds a preset ineffective proportion threshold, the navigation status assessment module directly generates a status warning signal and sends it to the remote monitoring platform. If the proportion of ineffective adjustments does not exceed the preset ineffective proportion threshold, further analysis of the response speed and trajectory stability of the adjustment process is required. First, determine the median of the preset response speed range, calculate the difference between the response speed value of each effective adjustment process and this median, and take the absolute value to obtain the response deviation value of each adjustment process; simultaneously, calculate the ratio of the trajectory stability value of each effective adjustment process to the preset stability threshold to obtain the trajectory stability coefficient of each adjustment process.

[0055] After obtaining the response deviation values ​​of all effective control processes within the evaluation period, the average response deviation is calculated by averaging these values. This value reflects the overall deviation of the response speed within that period. Similarly, the average stability coefficient is calculated by averaging the trajectory stability coefficients of all effective control processes within the evaluation period. This value reflects the overall level of trajectory stability within that period.

[0056] Next, the navigation status assessment module performs a comprehensive numerical calculation on the ineffective 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 according to their importance, and the final status assessment value is obtained after weighted processing. If the status assessment value exceeds a 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. When the remote monitoring platform receives the status warning signal, it will issue an alert through its own warning mechanism to notify relevant personnel that the operating status of the heading adjustment execution module may be abnormal.

[0057] Throughout the process, all data acquisition, calculation, and signal generation are performed continuously, ensuring 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 assessment cycle can be adjusted according to actual application scenarios to adapt to the assessment frequency requirements under different navigation environments. Parameters such as the preset invalid percentage 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 according to factors such as ship type, navigation area characteristics, and module model to ensure the accuracy and applicability of the assessment results.

[0058] Example 2: See Figure 3 Track smoothness analysis is used to obtain the track stability value during the course adjustment process, and the process begins with the establishment of a coordinate system. A Cartesian coordinate system is constructed with time as the horizontal axis and actual track deviation as the vertical axis, where actual track deviation refers to the distance difference between the ship's actual navigation trajectory and the preset route during the adjustment process. When obtaining the track deviation curve for the corresponding course adjustment process, the ship's positioning system continuously collects position information during the adjustment process, recording the ship's real-time position at fixed intervals. These real-time positions are then compared with the preset route to calculate the actual track deviation at each time point. These deviation values ​​are then connected in chronological order to form the track deviation curve. When placing this curve into the established Cartesian 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 beginning is presented on the vertical axis, thus clearly reflecting 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 need to be determined based on the total duration of the adjustment process. If the adjustment process is short, the number of sampling points can be reduced appropriately, and the interval can be set to a few seconds; if the adjustment process is long, the number of sampling points should be increased, and the interval can be set to tens of seconds to ensure that the sampling points can uniformly cover the entire track deviation curve and accurately reflect the changing trend of the curve. The longitudinal distance between two adjacent sets of sampling points is the amount of deviation change. This distance is obtained by calculating the 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, but in subsequent calculations, only the magnitude of the change is considered.

[0060] The volatility index is obtained based on the variance calculation of all deviation changes. In the variance calculation process, the average of all deviation changes is first calculated, then the difference between each deviation change and the average is calculated, these differences are squared and summed, and finally divided by the total number of deviation changes. The result is the volatility index. This index reflects the dispersion of deviation changes; the larger the volatility index, the more unstable the deviation changes and the more pronounced the track fluctuations.

[0061] The calculation of the percentage of abnormal fluctuations requires first setting a preset range for deviation changes. This range is determined based on the ship's navigation stability requirements and the performance of the heading adjustment execution module. Deviation changes exceeding this range are considered abnormal fluctuations. The number of abnormal fluctuations among all deviation changes is counted, and then the ratio of this number to the total number of deviation changes is calculated to obtain the percentage of abnormal fluctuations. A higher percentage indicates a higher frequency of large deviation changes during the adjustment process, and a worse track stability.

[0062] The generation of a trajectory stability value requires a combination of the volatility index and the proportion of abnormal volatility. In practice, the volatility index and the proportion of abnormal volatility are first integrated according to a certain ratio. No explicit formula is needed for this integration; instead, the values ​​of the two are weighed to obtain a trajectory stability value that comprehensively reflects the stability of the trajectory. This value is inversely proportional to the stability of the trajectory; that is, the larger the trajectory stability value, the worse the trajectory stability; the smaller the trajectory stability value, the smoother the trajectory 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 aspects such as the magnitude, frequency, and overall trend of deviation changes. This provides key judgment criteria for subsequent dynamic process classification evaluation, ensuring a more accurate and comprehensive assessment of the operational status of the heading adjustment execution module. In practical applications, 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 vessels 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 anomaly diagnosis module. When the navigation status assessment module generates a normal status signal, it immediately transmits the signal to the equipment anomaly diagnosis module. Upon receiving the normal status signal, the equipment anomaly diagnosis module immediately initiates anomaly diagnosis analysis of the heading adjustment execution module to further confirm whether there are any potential anomalies in its operating status.

[0065] During the anomaly diagnosis and analysis process, the equipment anomaly diagnosis module collects the module's operating temperature in real time using temperature sensors deployed at key locations on the heading adjustment actuator module. These temperature sensors, typically contact thermocouple sensors, ensure accurate capture of temperature changes during module operation. Simultaneously, vibration sensors collect the mechanical vibration frequency generated during module operation. Piezoelectric sensors can be used to effectively detect vibration signals generated by the operation of internal mechanical components. After collecting the operating temperature and mechanical vibration frequency, the operating temperature is compared to a preset temperature threshold, determined based on the heat resistance of the heading adjustment actuator module's material and operating environment requirements. The mechanical vibration frequency is also compared to a preset vibration frequency threshold, set based on the vibration spectrum characteristics during normal module operation. If the operating temperature exceeds the preset temperature threshold, or the mechanical vibration frequency exceeds the preset vibration frequency threshold, the heading adjustment actuator module is determined to be in an abnormal operating state.

[0066] An evaluation cycle is set, which can be determined based on the continuity of ship navigation and the needs of equipment monitoring, for example, a 4-hour evaluation cycle. Within each evaluation cycle, the total duration of the heading adjustment execution module in an abnormal operating state is recorded using a timing device. Simultaneously, the total operating time of the module within that evaluation cycle is calculated; the total operating time is the cumulative time the module is in working condition, excluding downtime or dormancy. The ratio of the total duration of abnormal operation to the total operating time is calculated to obtain the abnormal operation percentage, which directly reflects the proportion of time the module spends in an abnormal state within the evaluation cycle.

[0067] During the evaluation period, for each abnormal operating state, its duration is recorded and compared with a preset single-event duration threshold. This threshold is set based on the module's tolerance for short-term anomalies, for example, 10 minutes. The number of times a single event duration exceeds the preset threshold is counted and marked as the excessively long anomaly frequency. This frequency reflects the frequency of prolonged abnormal operation of the module. Simultaneously, the maximum value is selected from all single abnormal operating durations and marked as the longest anomaly duration. The longest anomaly duration reflects the most severe nature of a single abnormal operation of the module.

[0068] The equipment anomaly index is generated by combining the percentage of abnormal operations, the frequency of excessively long anomalies, and the longest anomaly duration. The specific calculation method is as follows:

[0069]

[0070] in, This indicates the equipment malfunction index. Indicates the percentage of abnormal operations. This indicates an abnormally high frequency. Indicates the longest duration of the anomaly. , , These are weighted coefficients for the percentage of abnormal operations, the frequency of excessively long abnormalities, and the longest duration of abnormalities. These weighted coefficients are set based on the degree of impact of each indicator on equipment abnormalities. .

[0071] The equipment anomaly index is compared with a preset anomaly index threshold, which is determined based on extensive equipment operation data and fault case analysis. If the equipment anomaly index exceeds the preset threshold, an equipment fault warning signal is generated; if the equipment anomaly index does not exceed the preset threshold, an equipment normal signal is generated. The generated equipment fault warning signal or equipment normal signal is sent to the remote monitoring platform via a communication module. The remote monitoring platform is equipped with an early warning device. When it receives an equipment fault warning signal, the early warning device is activated and issues a corresponding warning prompt so that relevant personnel can be informed in a timely manner and take appropriate measures.

[0072] Throughout the entire anomaly diagnosis and analysis process, data acquisition, calculation, and signal generation are all automatically completed by the module's internal microprocessor, ensuring real-time performance and accuracy. Various preset thresholds and weighting coefficients can be appropriately adjusted based on the ship type, the environmental characteristics of the navigation area, and the service life of the heading adjustment execution module to adapt to 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 equipment fault 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 manufacturing date from the heading adjustment execution module's built-in storage unit. The manufacturing date is the date the module was completed and passed inspection. The time difference between the current date and the manufacturing date is calculated, and the result is the equipment's usage time, expressed in days, months, or years, directly reflecting the module's existence from production to the present. Simultaneously, the equipment life prediction module accesses the ship's historical operation database, which records the start and end times of each operation of the heading adjustment execution module. By summarizing these time records, the total duration the module was in operation during the historical operation phase is obtained and marked as the cumulative runtime. The cumulative runtime focuses on the total time the module actually worked, excluding idle or inactive time.

[0075] The analysis and acquisition of environmental degradation duration are achieved through sensors deployed around the heading adjustment execution module. These sensors include a salt spray sensor that collects real-time seawater salt spray concentration data, a temperature sensor that collects ambient temperature data, and a humidity sensor that collects ambient humidity data and labels it as an ambient humidity value. The system has pre-set suitable salt spray concentration and temperature standards. The suitable salt spray concentration standard is determined based on the salt spray corrosion resistance of the module's casing material, while the suitable temperature standard 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 suitable salt spray concentration standard is calculated, and the result is labeled as the salt spray deviation value. Similarly, the difference between the ambient temperature and the suitable temperature standard is calculated, and the result is labeled as the temperature deviation value. The positive and negative signs of the salt spray and temperature deviation values ​​reflect the direction of deviation between the actual environmental parameters and the standard values, while their absolute values ​​reflect the degree of deviation.

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

[0077] The system also records maintenance records for the heading adjustment module during historical operation phases, including the time of each maintenance. The preset maintenance interval threshold is set based on the module's maintenance manual and operational experience, for example, set to 3 months. The system counts the number of times the maintenance interval exceeds the preset threshold and marks this number as a maintenance anomaly coefficient. A higher maintenance anomaly coefficient indicates poorer timeliness of module maintenance, potentially accelerating equipment wear and tear.

[0078] The system calculates equipment lifespan using an internal evaluation model by considering factors such as equipment usage time, cumulative runtime, environmental wear and tear, and maintenance anomaly coefficients. This assessment value comprehensively considers the impact of time, usage intensity, environmental influence, and maintenance conditions on equipment lifespan. The lifespan assessment value is then compared to a preset lifespan threshold, which is determined based on the module's design lifespan and the average lifespan of similar equipment. If the lifespan assessment value exceeds the preset threshold, a replacement warning signal is generated and transmitted to a remote monitoring platform via a communication link. Upon receiving the warning signal, the remote monitoring platform issues an alert through audible and visual alarms, prompting relevant personnel to consider replacing the heading adjustment execution module.

[0079] Example 5: A stable communication connection is established between the remote monitoring platform and the emergency response dispatch module. This connection is achieved through the ship's internal local area network or dedicated communication lines, ensuring the real-time performance and reliability of signal transmission. The emergency response dispatch module's storage unit pre-stores multiple emergency handling strategies. These strategies are categorized according to different levels of warning signals. The level classification is determined by the severity of the problem reflected by the warning signal; for example, it can be divided into three levels: minor warning, moderate warning, and severe warning. Different levels correspond to different emergency handling measures.

[0080] When the emergency response dispatch module receives a status warning signal from the navigation status assessment module or an equipment fault warning signal from the equipment anomaly diagnosis module, it first identifies the level of the warning signal. This identification is done by parsing the level identifier contained in the signal; the level identifier is pre-set by the module sending the signal based on the severity of the problem. Based on the identified warning signal level, the emergency response dispatch module retrieves the corresponding preset emergency handling strategy from its storage unit, ensuring that the measures taken match the severity of the problem.

[0081] The automatic switch to backup navigation mode in the emergency response strategy refers to the emergency response dispatch module sending a start command to the ship's backup navigation system. The backup navigation system is independent of the primary navigation system, possessing its own sensors and control units, and is normally in standby mode. Upon receiving the start command, the backup navigation system immediately activates, taking over the ship's navigation tasks. Simultaneously, the heading adjustment module in the primary navigation system suspends operation until the fault is resolved.

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

[0083] When generating an emergency obstacle avoidance path for a ship, the emergency response scheduling 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 of movement (if the obstacle is dynamic), water depth, and restricted navigation areas of surrounding obstacles. Combining this data with parameters such as the ship's current position, speed, heading, and turning performance, the module processes this data through internal path planning logic to plan a path that avoids all obstacles and meets navigation safety requirements. The generation of the emergency obstacle avoidance path must consider the ship's inertia and turning radius to ensure that the path remains within the ship's actual maneuverability.

[0084] The emergency response dispatch module converts the generated emergency obstacle avoidance path into specific control commands, including steering angle, steering timing, and speed adjustment values. These commands are then sent to the heading adjustment execution module. Upon receiving the control commands, the heading adjustment execution module immediately activates the ship's steering gear and propulsion system to perform the corresponding operations, making an emergency turn according to the emergency obstacle avoidance path. This ensures the ship can avoid obstacles in the shortest possible time and guarantees navigational safety.

[0085] Throughout the emergency response process, the emergency response dispatch module continuously receives real-time data from the navigation environment perception module, monitoring changes in the vessel's position and surrounding environment. If new risks are detected in the original emergency obstacle avoidance path, the module immediately replans the path and sends new control commands until the vessel is out of danger. The remote monitoring platform records the entire emergency response process in real time, including the time of receiving warning signals, the emergency measures taken, the implementation status of the 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" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus.

[0087] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. An adaptive ship navigation terminal, characterized in that, It includes a navigation environment perception module, an adaptive control decision module, a heading adjustment execution module, a navigation status assessment module, and a remote monitoring platform; The navigation environment perception module collects 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 values ​​of the ship's navigation environment and the preset navigation parameter values. Based on the navigation deviation, it calculates the control command of the heading adjustment execution module through a fuzzy adaptive algorithm and sends the control command to the heading adjustment execution module. The heading adjustment module executes steering or speed adjustment operations according to control commands to correct the ship's navigation trajectory; The navigation status assessment 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 accordingly. The normal status signal or status warning signal is then sent to the remote monitoring platform. When the remote monitoring platform receives the status warning signal, it issues a warning. The specific analysis process of the navigation status assessment module includes: The corresponding heading adjustment process is marked as an ineffective or effective adjustment process through dynamic process classification assessment. An assessment period is set, and the ratio of the number of ineffective adjustment processes to the total number of heading adjustment processes within the assessment period is calculated to obtain the ineffective adjustment ratio. If the ineffective adjustment ratio exceeds the preset ineffective ratio threshold, a status warning signal is generated. If the proportion of invalid adjustments does not exceed the preset invalid proportion threshold, the difference between the response speed value of the corresponding heading adjustment process and the median of the preset response speed range is calculated and the absolute value is taken to obtain the response deviation value. 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 state assessment value is obtained by numerically calculating the proportion of ineffective regulation, the average response deviation, and the average stability coefficient. If the state assessment value exceeds the preset assessment threshold, a state warning signal is generated; if the state assessment value does not exceed the preset assessment threshold, a state normal signal is generated.

2. The adaptive ship navigation terminal according to claim 1, characterized in that, The specific analysis process for dynamic process hierarchical evaluation is as follows: The time when the heading adjustment execution module receives the control command is collected and marked as the start time, and the time when the heading adjustment execution module completes the corresponding heading adjustment operation is collected and marked as the end time. The interval between the start time and the end time is marked as the adjustment time. The ratio of control command to 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 will be marked as a valid adjustment process.

3. An adaptive ship navigation terminal according to claim 2, characterized in that, The specific analysis process of trajectory smoothness analysis is as follows: A Cartesian coordinate system is established with time as the horizontal axis and actual track deviation as the vertical axis. The track deviation curve of the ship during the corresponding heading adjustment process is obtained. The track deviation curve is placed in the Cartesian 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. The longitudinal distance between two adjacent sets of sampling points is marked as the deviation change. The variance of all deviation changes is calculated to obtain the fluctuation index. 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.

4. An adaptive ship navigation terminal according to claim 1, characterized in that, The navigation status assessment module communicates with the equipment anomaly diagnosis module. The navigation status assessment module sends a normal status signal to the equipment anomaly diagnosis module. When the equipment anomaly diagnosis module receives the normal status signal, it performs anomaly diagnosis analysis on the heading adjustment execution module. Through analysis, it generates an equipment fault warning signal or an equipment normal signal and sends the equipment fault warning signal or equipment normal signal to the remote monitoring platform. When the remote monitoring platform receives the equipment fault warning signal, it issues an early warning.

5. An adaptive ship navigation terminal according to claim 4, characterized in that, The specific analysis process for abnormal diagnosis is as follows: During the operation of the heading adjustment execution module, its operating temperature and mechanical vibration frequency are collected. If the operating temperature or mechanical vibration frequency exceeds the corresponding preset threshold, the heading adjustment execution module is judged to be in an abnormal operating state. The abnormal operation rate is calculated by comparing the duration of the abnormal operation of the heading adjustment execution module within the evaluation period with the total operation time of the heading adjustment execution module within the evaluation period. The frequency of occurrences in which the single duration of the abnormal operation of the heading adjustment execution module exceeds the corresponding preset single duration threshold is marked as an excessively long abnormal frequency. The maximum value of the single duration of the abnormal operation of the heading adjustment execution module within the evaluation period is marked as the longest abnormal duration. The equipment anomaly index is obtained by numerically calculating the percentage of abnormal operation, the frequency of excessive anomalies, and the longest anomaly duration. If the equipment anomaly index exceeds the preset anomaly index threshold, an equipment fault warning signal is generated. If the equipment anomaly index does not exceed the preset anomaly index threshold, a normal equipment signal is generated.

6. An adaptive ship navigation terminal according to claim 1, characterized in that, The remote monitoring platform communicates with the equipment life prediction module. When a status warning signal or equipment fault warning signal is generated, the equipment life prediction module performs a life assessment on the heading adjustment execution module. Through analysis, it determines whether a replacement warning signal should be generated and sends the replacement warning signal to the remote monitoring platform. When the remote monitoring platform receives the replacement warning signal, it issues a warning.

7. An adaptive ship navigation terminal according to claim 6, characterized in that, The specific analysis process of the equipment life prediction module is as follows: The manufacturing date of the heading adjustment execution module is collected, and the time difference between the current date and the manufacturing date of the heading adjustment execution module is calculated to obtain the equipment usage time. The total time that the heading adjustment execution module was in operation during the historical operation phase is marked as the cumulative running time. The environmental wear duration of the heading adjustment execution module is obtained through analysis, and the frequency of maintenance intervals exceeding the preset maintenance interval threshold for the heading adjustment execution module during historical operation is marked as a maintenance anomaly coefficient. The equipment life assessment value is obtained by numerically calculating the equipment usage time, cumulative running time, environmental wear duration, and maintenance anomaly coefficient. If the equipment life assessment value exceeds the preset life threshold, a replacement warning signal is generated.

8. An adaptive ship navigation terminal according to claim 7, characterized in that, The specific methods for analyzing and obtaining environmental degradation duration are as follows: The seawater salt spray concentration and ambient temperature of the environment where the heading adjustment execution module is located are collected. The deviation of the seawater salt spray concentration from the set suitable salt spray concentration standard value is marked as the salt spray deviation value, and the deviation of the ambient temperature from the set suitable temperature standard value is marked as the temperature deviation value. The system collects the humidity of the environment in which the heading adjustment execution module is located and marks it as the ambient humidity value. It calculates the environmental loss index by numerically calculating the salt spray deviation value, temperature deviation value and ambient humidity value. If the environmental loss index exceeds the preset loss index threshold, it is determined that the heading adjustment execution module is in a high loss state. It obtains the total duration of the heading adjustment execution module in a high loss state during the historical operation phase and marks it as the environmental loss duration.

9. An adaptive ship navigation terminal according to claim 1, characterized in that, The remote monitoring platform is connected to the emergency response dispatch module. The emergency response dispatch module receives status warning signals sent by the navigation status assessment module or equipment failure warning signals sent by the equipment anomaly diagnosis module, and calls preset emergency handling strategies according to the level of the warning signal. The emergency handling strategies include automatically switching to the backup navigation mode, sending a distress signal to the nearest 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 turning operation.

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