Intelligent port marine environment real-time monitoring method and system

Abstract

The invention relates to the technical field of marine environment monitoring, and discloses an intelligent port marine environment real-time monitoring method and system. The method comprises the steps of periodically collecting environmental data of a specific position of a target sea area, obtaining predicted berthing time of all predicted berthing ships based on a berthing plan, extracting the latest predicted berthing time and comparing the latest predicted berthing time with the current time, judging whether the current ship is in a flat tide period or a fluctuation period based on a time difference value, and determining whether the ship is in the fluctuation period or not. If the environmental data meets a first preset condition, entering a flat tide period flow, otherwise, regenerating a mooring plan and returning to the step of obtaining the predicted mooring time, after the mooring action in the flat tide period is started, continuously monitoring whether the seawater flow velocity and the wave parameter value meet the mooring condition or not, and if not, regenerating the parking plan and returning to the step of acquiring the predicted parking time, and if yes, continuing the parking action until the target ship is parked, thereby improving the operation efficiency and safety of the port.

Description

Technical Field

[0001] The present application relates to the field of marine environment monitoring technology, and in particular to a method and system for real-time monitoring of the marine environment of an intelligent port. Background Art

[0002] With the booming development of global trade, ports, as important hubs for cargo transportation, have a significant impact on economic development through their operational efficiency and safety. The complexity and variability of the marine environment, such as the fluctuations in seawater velocity, waves, tide levels and other parameters, have brought many challenges to the berthing operations of ships in ports. Traditional manual monitoring methods are not only inefficient, but also difficult to obtain marine environmental data in real time and accurately, and cannot meet the needs of modern ports for efficient and safe operations. It is particularly urgent to develop a method that can monitor the marine environment of smart ports in real time, comprehensively and accurately.

[0003] Similar prior art includes a Chinese patent application with publication number CN118966798A, which discloses a method, terminal and storage medium for intelligent collection and analysis of marine environmental data, which conducts continuous real-time detection of each monitoring area of ​​the target ocean, collects environmental meteorological data and environmental pollution data of the current date; analyzes the collected meteorological and pollution data, calculates travel safety assessment coefficients and pollution degree assessment coefficients, determines areas that are not suitable for travel and areas of various pollution levels, and stores and feeds back the results; extracts historical travel safety assessment coefficients of each monitoring area from a database, analyzes suitable travel days for each monitoring area of ​​the target ocean, and displays them; extracts historical pollution degree assessment coefficients of each monitoring area, analyzes pollution change trends in each monitoring area, and displays and warns.

[0004] The above existing technologies are insufficient in the depth of data analysis and application, and cannot provide accurate, real-time, and dynamic decision-making basis for the complex operation scenarios of ports. In addition, they are relatively weak in the comprehensiveness and accuracy of marine disaster warnings. Their warning scope is mainly focused on pollution risks, and they cannot provide ports with all-round and multi-level disaster warning services. Therefore, it is an urgent problem to provide a real-time monitoring method and system for the marine environment of an intelligent port to improve the efficiency and safety of port operations and reduce the risk of marine disasters. Summary of the invention

[0005] The present application provides a method and system for real-time monitoring of the marine environment of a smart port, which are used to improve the efficiency and accuracy of real-time monitoring of the marine environment of a smart port.

[0006] In a first aspect, the present application provides a method for real-time monitoring of the marine environment of a smart port, the method comprising: Step 1: Collect environmental data at a specific location in the target sea area according to a preset period, wherein the environmental data includes seawater flow velocity and wave parameter values; Step 2: Obtain the estimated berthing time of all ships expected to berth in the target sea area, extract the most recent estimated berthing time and define it as the first time, and determine whether the time difference between the current time and the first time is less than or equal to a first preset value. If so, proceed to step 3; Step 3: Determine whether the current time is in the flat tide period or the rising and falling period. If it is the rising and falling period, proceed to step 4; if it is the flat tide period, proceed to step 5; Step 4: determine whether the environmental data meets the first preset condition. If so, proceed to step 5. If not, regenerate the parking plan and then return to step 2. Step 5: After the mooring action begins, monitor whether the seawater velocity and wave parameter values ​​meet the mooring conditions. If not, regenerate the mooring plan and then return to step 2. If so, continue the mooring action and repeat this step until the target ship completes the mooring, where the target ship is the ship corresponding to the first time.

[0007] In combination with the first aspect, in a first implementation of the first aspect of the present application, a first spatial position information sequence of a first measuring device at a specific position within a first preset time is obtained, the first spatial position information sequence is input into a first preset model, and a wave parameter value of a target sea area is obtained. The generation method of the first preset model is: Acquire a second spatial position information sequence and a wave parameter value sequence of the second measuring device within a second preset time, and simultaneously acquire a third spatial position information sequence of the first measuring device within the second preset time, wherein the second measuring device is physically connected to the first measuring device, and a distance between the two is less than or equal to a second preset value; Machine learning is performed on the second spatial position information sequence and the wave parameter value sequence to construct a second preset model from the spatial position information sequence to the wave parameters, and then the second preset model is trained based on the third spatial position information sequence and the wave parameter value sequence to generate a first preset model from the spatial position information sequence to the wave parameters.

[0008] In combination with the first aspect, in a second implementation of the first aspect of the present application, the wave parameters include wave height, wave speed and wave direction, and a first preset model is generated for each wave parameter.

[0009] In combination with the first aspect, in a third implementation of the first aspect of the present application, the environmental data includes tidal level change parameters, air flow parameters, tidal periodicity parameters, and river entry into the sea parameters. In step 4, determining whether the environmental data meets the first preset condition includes: Step 41, obtaining the tidal level change parameters of the target sea area within the third preset time, and judging whether the target sea area is in a specific tidal level state at the first time, if not, the first preset condition is met, and if so, entering step 42, the tidal level change parameters include the tidal level change amplitude; Step 42, judging whether the amplitude of the tidal level change is greater than or equal to a third preset value, if so, the first preset condition is not satisfied, if not, judging whether the target sea area is located in the low tide stage after the maximum tidal level or the low tide stage after the minimum tidal level at the first time, if so, the first preset condition is not satisfied, if not, proceeding to step 43; Step 43: Input the current tide level change parameters, air flow parameters, tidal periodicity parameters and river entry parameters into the third preset model, obtain the comprehensive seawater flow velocity of the target sea area at the first time, and extract the ship type of the target ship, obtain the flow velocity threshold based on the ship type, and judge whether the comprehensive seawater flow velocity is less than or equal to the flow velocity threshold. If so, the first preset condition is met.

[0010] In combination with the first aspect, in a fourth implementation of the first aspect of the present application, environmental information of multiple preset locations in the target sea area is collected, and before step 2, the following steps are included: Step 21, obtaining a first specific wave parameter value at any preset position, determining whether the first specific wave parameter value is within a first preset range, if so, determining that a significant marine disaster has occurred and sending a first warning message, then entering step 22, if not, determining whether the first specific wave parameter value is within a second preset range, if so, determining that a potential marine disaster has occurred and sending a second warning message, then entering step 22, if not, entering step 2; Step 22: obtaining a second preset position between any preset position and the port based on a preset rule, and predicting a predicted specific wave parameter value and a second time for the marine disaster to reach the second preset position; Step 23, obtain the second specific wave parameter value at the second preset position at the second time, and determine whether the second specific wave parameter value is greater than or equal to the set threshold value. If so, it is determined that a significant marine disaster has occurred and a first warning message is sent. If not, it is determined that no marine disaster will occur and the warning message is canceled, and then enter step 2, wherein the set threshold value is set based on the predicted specific wave parameter value.

[0011] In combination with the first aspect, in a fifth implementation of the first aspect of the present application, the warning information includes coordinate information of any preset location, a first specific wave parameter value, and a marine disaster type.

[0012] In combination with the first aspect, in a sixth implementation of the first aspect of the present application, a method for obtaining the predicted specific wave parameter value and the second time is: Acquire underwater three-dimensional image data of the target sea area and sea level data within a fourth preset time, determine a first underwater height at any preset position and a second underwater height at a second preset position based on the underwater three-dimensional image data and the sea level data, and determine a predicted specific wave parameter value based on the first specific wave parameter value, the first underwater height and the second underwater height; The third time when the first specific wave parameter value is monitored and the horizontal distance between any preset position and the second preset position are obtained, the estimated wave speed at any point between any preset position and the second preset position is calculated based on the underwater three-dimensional image data, the wave advancement time is calculated based on the horizontal distance and the estimated wave speed, and the sum of the third time and the wave advancement time is used as the second time.

[0013] In a second aspect, the present application provides a smart port marine environment real-time monitoring system, the system comprising: a data acquisition module, a time judgment module, a first judgment module, a second judgment module and an action monitoring module; A data acquisition module is used to collect environmental data of a specific location in the target sea area according to a preset period, wherein the environmental data includes seawater flow velocity and wave parameter values; A time judgment module is used to obtain the estimated berthing time of all ships expected to berth in the target sea area, extract the most recent estimated berthing time and define it as the first time, and judge whether the time difference between the current time and the first time is less than or equal to a first preset value. If so, enter the first judgment module; The first judgment module is used to judge whether the current time is in the flat tide period or the rising and falling period. If it is the rising and falling period, the second judgment module is entered; if it is the flat tide period, the action monitoring module is entered; The second judgment module is used to judge whether the environmental data meets the first preset condition. If so, the motion monitoring module is entered; if not, the parking plan is regenerated and then the time judgment module is returned; The action monitoring module is used to monitor whether the seawater flow rate and wave parameter values ​​meet the mooring conditions after the mooring action begins. If not, the mooring plan is regenerated and then returned to the time judgment module. If so, the mooring action is continued and continuous monitoring is performed until the target ship completes the mooring, wherein the target ship is the ship corresponding to the first time.

[0014] Compared with the prior art, the beneficial effects of the technical solution of the present application are at least as follows: 1. Continuously collect environmental data at specific locations in the target sea area according to the preset cycle, accurately determine whether the berthing conditions are met, and dynamically adjust the berthing plan in real time to ensure that ships berth in a safe environment, improve the refinement and intelligence of port operations, and effectively avoid berthing accidents caused by sudden environmental changes.

[0015] 2. Using machine learning technology, an accurate wave parameter prediction model is constructed based on the spatial position information sequence of the measuring equipment and the wave parameter value sequence. On the measuring equipment without parameter acquisition equipment, the wave parameters such as wave height, wave speed and wave direction are obtained in real time based on the changing characteristics of the spatial position information sequence of the measuring equipment, which has higher accuracy and can reduce equipment costs.

[0016] 3. When collecting environmental information, the environmental information of multiple preset locations in the target sea area is monitored in real time, significant marine disasters and potential marine disasters are judged, and warning information of different levels is sent. Based on underwater three-dimensional image data and sea level data, the wave parameter values ​​and time when marine disasters arrive at specific locations are accurately predicted, and further judgments on marine disasters are made, which can effectively improve port safety and reduce disaster losses. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0018] Figure 1 This is a schematic diagram of an embodiment of a method for real-time monitoring of marine environment in an intelligent port in an embodiment of the present application; Figure 2 This is a flowchart for determining whether environmental data meets the first preset condition in an embodiment of the present application; Figure 3 A schematic diagram of the preset position setting of the target sea area in an embodiment of the present application; Figure 4 This is a schematic diagram of an embodiment of a smart port marine environment real-time monitoring system in an embodiment of the present application. DETAILED DESCRIPTION

[0019] The embodiment of the present application provides a method and system for real-time monitoring of the marine environment of an intelligent port. The terms "first", "second", "third", "fourth", etc. (if any) in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments described here can be implemented in an order other than that illustrated or described here. In addition, the terms "including" or "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0020] For ease of understanding, the specific process of the embodiment of the present application is described below. Figure 1 , an embodiment of a method for real-time monitoring of the marine environment of an intelligent port in an embodiment of the present application includes: Step 1: Collect environmental data at a specific location in the target sea area according to a preset period, wherein the environmental data includes seawater flow velocity and wave parameter values.

[0021] The above preset period is set according to actual monitoring needs and the characteristics of marine environmental changes, such as a preset period of 5 minutes or 10 minutes, to ensure that the dynamic changes of the target sea area environmental data can be obtained in a timely manner.

[0022] The collected environmental data include seawater velocity, current wind direction, wave parameters, tide level, etc. Seawater velocity reflects the speed of seawater flow at a specific location, and wave parameter values ​​cover various characteristics of waves, such as wave height, wave speed, wave direction, wavelength, frequency, period, etc. Tide level is the height of seawater relative to the average sea level at a certain moment under the action of tide.

[0023] By periodically collecting environmental data, we can understand the changes in the marine environment of the target sea area in real time, which is crucial for the operation and management of the port.

[0024] Step 2: Obtain the estimated berthing time of all ships expected to berth in the target sea area, extract the most recent estimated berthing time and define it as the first time, and determine whether the time difference between the current time and the first time is less than or equal to a first preset value. If so, proceed to step 3.

[0025] The estimated berthing time of all ships that will enter the port for berthing in the target sea area is collected through the port's dispatching system and ship declaration information. From the many estimated berthing times, the nearest estimated berthing time is found to determine the berthing task that currently needs the most attention, and to determine the priority of monitoring and planning for subsequent steps. When the port is busy and many ships have berthing needs at the same time, this step ensures that monitoring resources can be allocated to the most urgent tasks first, thereby improving the pertinence and efficiency of monitoring work and improving the overall operational efficiency of the port.

[0026] The first preset value is a time threshold set based on port operation experience and safety requirements, such as 10 minutes, 30 minutes, etc., which is used to determine whether it is necessary to immediately conduct environmental assessment and planning for the upcoming berthing task. If the time difference between the current time and the first time is greater than the first preset value, it means that there is enough time to prepare, and the subsequent steps can be temporarily not executed, and judgment can be made when it is closer to the expected berthing time. This can avoid unnecessary environmental monitoring analysis and planning work too early and allocate resources reasonably.

[0027] Step 3: Determine whether the current time is in the slack tide period or the rising and falling period. If it is the rising and falling period, proceed to step 4; if it is the slack tide period, proceed to step 5.

[0028] Tidal changes in the marine environment have an important impact on ship mooring. During the rising and falling period, the seawater flow rate is large, the water level changes rapidly, and the mooring conditions are relatively complex, so more careful evaluation of environmental data is required; while during the flat tide period, the seawater is relatively stable and the mooring conditions are relatively good. By judging the current tidal state, the monitoring method can be adapted to different tidal environments, making subsequent environmental data monitoring more targeted, more effectively utilizing monitoring resources, and improving the accuracy and practicality of monitoring results.

[0029] Step 4: determine whether the environmental data meets the first preset condition. If so, proceed to step 5. If not, regenerate the parking plan and then return to step 2.

[0030] The marine environment is changing dynamically. By evaluating whether the environmental data meets the preset conditions, it is possible to effectively screen out environmental conditions that are not suitable for berthing, avoid ships from berthing in harsh marine environments, and thus reduce berthing risks and ensure the safety of ships and port facilities. When the environmental data does not meet the berthing conditions, the berthing plan is regenerated in a timely manner to provide ships with a more reasonable and safe berthing plan. Adjustments to the berthing plan may include adjusting the berthing position, changing the berthing time, and / or taking other auxiliary measures to adapt to the current changes in the marine environment. It can provide a scientific basis for berthing decisions, reduce the subjectivity and uncertainty of human judgment, make berthing decisions more scientific, reasonable and reliable, and improve the port's adaptability and risk resistance while improving the port's operational efficiency and safety.

[0031] Step 5: After the mooring action begins, monitor whether the seawater velocity and wave parameter values ​​meet the mooring conditions. If not, regenerate the mooring plan and then return to step 2. If so, continue the mooring action and repeat this step until the target ship completes the mooring, where the target ship is the ship corresponding to the first time.

[0032] Exemplarily, the wave parameter value is the wave height value, and different wave parameter thresholds are set for each type of ship, including small yachts, medium-sized cargo ships, large cargo ships, and guest ships, etc. The threshold corresponding to small yachts is 1.0m, the threshold corresponding to medium-sized cargo ships is 2.0m, the threshold corresponding to large cargo ships is 3.0m, and the threshold corresponding to passenger ships is 1.5m; the seawater flow rate threshold is 1m / s, and different seawater flow rate thresholds can also be set according to the type of ship. When the seawater flow rate and the wave parameter value meet the corresponding thresholds at the same time, the environmental data meets the mooring conditions.

[0033] After the berthing operation begins, the seawater velocity and wave parameter values ​​are continuously monitored, and abnormal changes in environmental conditions, such as sudden storm currents or large waves, can be discovered in a timely manner, so that corresponding measures can be taken to avoid continued berthing in an unsafe environment, reduce possible accidents and losses, and ensure the safety of the berthing process. This real-time monitoring mechanism can effectively respond to various complex changes in the marine environment, ensure the continuity and stability of port operations, provide dynamic safety guarantees for berthing operations, effectively reduce berthing risks, and improve the success rate and safety of berthing.

[0034] In a specific embodiment, a first spatial position information sequence of a first measuring device at a specific position within a first preset time is obtained, the first spatial position information sequence is input into a first preset model, and a wave parameter value of a target sea area is obtained. The generation method of the first preset model is: (1) obtaining a second spatial position information sequence and a wave parameter value sequence of a second measuring device within a second preset time, and simultaneously obtaining a third spatial position information sequence of a first measuring device within the second preset time, wherein the second measuring device is physically connected to the first measuring device, and a distance between the two is less than or equal to a second preset value.

[0035] (2) Performing machine learning on the second spatial position information sequence and the wave parameter value sequence to construct a second preset model from the spatial position information sequence to the wave parameters, and then training the second preset model based on the third spatial position information sequence and the wave parameter value sequence to generate a first preset model from the spatial position information sequence to the wave parameters.

[0036] In a specific embodiment, the wave parameters include wave height, wave speed and wave direction, and a first preset model is generated for each wave parameter.

[0037] The first preset time is set according to the characteristics of the ocean environment change, and is usually set to a value slightly larger than the wave period, such as 1.5 times the wave period, to ensure that the spatial position information sequence used to determine the wave parameter value can be obtained. The spatial position information is the positioning obtained by Beidou satellites, etc., including longitude, latitude and vertical distance relative to the sea level.

[0038] Specifically, the first measuring device is a measuring device that is anchored and set at a specific position in the target sea area, floats on the sea surface and moves up and down with the rise and fall of the sea surface, and can receive satellite signals and collect its own spatial position information in real time. The second measuring device is a spherical measuring device floating on the sea surface, which has the same stability in all directions, can evenly resist the force of wind and waves, can receive satellite signals, collect its own spatial position information in real time, and is equipped with a wave height meter and / or force measuring sensor, etc., and can provide high-precision wave height data and / or wave speed and direction data. The shapes of the first measuring device and the second measuring device may be the same or different.

[0039] The measurement results of different wave parameter measurement devices will be affected by the ocean conditions and their own motion characteristics (roll, pitch, heave, yaw, sway, surge, etc.). In order to improve the accuracy and uniformity of the measurement results, the monitoring data of the standard second measurement device is used to generate a second preset model, and the wave parameter value is inferred from the motion characteristics of the second measurement device. Then, the second preset model is adjusted using the monitoring data of the first measurement device to obtain the first preset model for measuring the wave parameter value suitable for the characteristics of the first measurement device. The second preset time for obtaining training data is set according to the actual application scenario to cover different tidal states and environmental conditions. After collecting enough training data, the operation of the second measurement device can be stopped. The distance between the second measurement device and the first measurement is relatively small. The two float in almost the same ocean conditions and are affected by almost the same ocean conditions such as waves. The first measurement device does not need to be equipped with a wave height meter and / or a force sensor, etc., and the wave parameter value at a specific position in the target sea area can be obtained only based on the spatial position information sequence. While improving the accuracy of the measurement results, the equipment cost can be reduced.

[0040] As time goes by, the performance of the first measurement device will change. The second preset model and the first preset model may be periodically trained according to preset rules to improve the periodicity of the measurement results.

[0041] See also Figure 2 In a specific embodiment, the environmental data includes tidal level change parameters, air flow parameters, tidal periodicity parameters and river discharge parameters. In step 4, determining whether the environmental data meets the first preset condition includes: Step 41, obtain the tidal level change parameters of the target sea area within the third preset time, and determine whether the target sea area is in a specific tidal level state at the first time. If not, the first preset condition is met. If so, enter step 42, and the tidal level change parameters include the tidal level change amplitude.

[0042] Step 42, determine whether the amplitude of the tide level change is greater than or equal to the third preset value. If so, the first preset condition is not met. If not, determine whether the target sea area is in the low tide stage after the maximum tide level or the low tide stage after the minimum tide level at the first time. If so, the first preset condition is not met. If not, proceed to step 43.

[0043] Step 43: Input the current tide level change parameters, air flow parameters, tidal periodicity parameters and river entry parameters into the third preset model, obtain the comprehensive seawater flow velocity of the target sea area at the first time, and extract the ship type of the target ship, obtain the flow velocity threshold based on the ship type, and judge whether the comprehensive seawater flow velocity is less than or equal to the flow velocity threshold. If so, the first preset condition is met.

[0044] Specifically, the tidal change parameters are obtained through tidal tables, tidal predictions and other means. The tidal change parameters include tidal change amplitude, tidal time (high tide time, low tide time), tidal level (high tide level, low tide level), tidal speed, tidal direction, tidal cycle and the like.

[0045] During the high tide stage, the sea level gradually rises, and the water depth of ports and docks increases, making it easier for ships with deeper draft to enter the port, reducing the risk of running aground. The tide usually points to the port or bay, which helps ships enter the port downstream, reducing navigation resistance and saving power. During the low tide stage, the sea level gradually decreases, and the water depth of ports and docks decreases, increasing the risk of ships running aground, especially for ships with deeper drafts. The tide usually points to the open sea, which may exert an outward pull on the moored ships, increasing the risk of ship displacement. Therefore, when the target sea area is in the high tide stage, it is judged that the first preset condition is met. When it is in the low tide stage, it is necessary to further judge whether the mooring action is allowed.

[0046] The tidal level variation refers to the maximum tidal level difference between high tide and low tide in a tidal cycle. The third preset value is used to determine whether the tidal level variation is within a tidal range threshold that may pose a threat to the safety of the ship. If the tidal level variation exceeds the third preset value, it is considered that the low tide stage is unsafe for the ship to anchor and the first preset condition is not met.

[0047] The low tide stage after the maximum tide level is the stage from high tide when the tide level is the highest to low tide when the tide level is the lowest. The sea level is highest at high tide and lowest at low tide. The water level drops rapidly and the tidal speed is fast in this stage, which will have a great impact on the anchoring of ships and the risk is high. In the low tide stage after the lowest tide level, the water level of the port and surrounding waters will continue to drop, especially for some shallow areas or ports with shallow water depths. The distance between the bottom of the ship and the seabed will get closer and closer. If the ship is anchored after the lowest tide level without fully considering the water level changes caused by the subsequent low tide, the ship may be stranded on the shoal or the bottom of the port, causing damage to the hull or even inability to navigate normally.

[0048] Specifically, air flow parameters include wind direction, wind speed, wind force level, wind direction change rate, wind pressure, wind shear, etc.; tidal periodic parameters include astronomical coefficients (coefficients of the influence of celestial bodies (such as the moon and the sun) on tides), the amplitude of the harmonic constant (parameter describing the amplitude of the periodic change of tides), angular frequency (parameter describing the speed of the periodic change of tides), the phase angle of the harmonic constant (parameter describing the phase of the periodic change of tides) and astronomical derivatives (parameter describing the influence of the position of celestial bodies on tides), etc. These parameters together describe the periodic changes of tides; river entry parameters include river flow, estuary width, estuary depth, etc. The river entry parameters are the river entry parameters of rivers entering the sea within a preset range from the port.

[0049] Air flow will directly cause the horizontal flow of seawater, and rivers entering the sea will affect local ocean currents. By inputting the tidal level change parameters, air flow parameters, tidal periodicity parameters and river entering the sea parameters into the third preset model, the horizontal flow speed of seawater calculated after considering multiple factors (such as air flow, rivers entering the sea, tides, etc.), that is, the comprehensive seawater flow rate, can be obtained. The comprehensive seawater flow rate of the target ship's expected berthing time is calculated based on multiple parameters to evaluate whether the berthing environment conditions at that time point are safe.

[0050] The technical solution of the present application can more comprehensively evaluate the marine environmental conditions of the target sea area, not only taking into account the seawater flow rate and wave parameters, but also covering factors such as tidal changes, air flow, meteorological conditions and rivers entering the sea. Through a step-by-step multi-dimensional judgment mechanism, the evaluation of environmental conditions is gradually refined to ensure that each key factor is fully considered, thereby improving the accuracy and reliability of the evaluation and reducing the risk of misjudgment of a single factor. At the same time, considering the different tolerance of different ships to seawater flow rates, a personalized berthing condition evaluation is provided for each ship, which improves the safety and adaptability of berthing and improves the practicality and effectiveness of the entire smart port marine environment real-time monitoring method.

[0051] In a specific embodiment, collecting environmental information of multiple preset locations in the target sea area includes before step 2: Step 21, obtain the first specific wave parameter value at any preset position, determine whether the first specific wave parameter value is within the first preset range, if so, determine that a significant marine disaster has occurred and send a first warning message, then enter step 22, if not, determine whether the first specific wave parameter value is within the second preset range, if so, determine that a potential marine disaster will occur and send a second warning message, then enter step 22, if not, enter step 2.

[0052] Step 22: Based on preset rules, a second preset position between any preset position and the port is obtained, and a predicted specific wave parameter value and a second time for the marine disaster to reach the second preset position are predicted.

[0053] Step 23, obtain the second specific wave parameter value at the second preset position at the second time, and determine whether the second specific wave parameter value is greater than or equal to the set threshold value. If so, it is determined that a significant marine disaster has occurred and a first warning message is sent. If not, it is determined that no marine disaster will occur and the warning message is canceled, and then enter step 2, wherein the set threshold value is set based on the predicted specific wave parameter value.

[0054] When an earthquake or volcanic eruption occurs in the ocean, it will cause submarine landslides, submarine collapse, tsunamis and other marine disasters. Among them, tsunami waves propagate outward from the source and may eventually reach coastal areas. When a tsunami propagates in the deep sea, the wave height is generally only a few meters or even lower, and its energy is relatively dispersed, so the impact on ships is small. When the tsunami approaches the coastline and the water depth gradually becomes shallower, the wave height will increase sharply, causing a huge water level drop and turbulent water flow, forming a huge destructive force. Ships are very likely to be involved, causing ships to break anchor and break cables, and then collide with other ships or port facilities, or even run aground, endangering the safety of ships and personnel. Once a tsunami is detected, the ship needs to be moved to safe waters in advance to provide a more stable shelter environment for ships and personnel. When an earthquake in the ocean triggers a tsunami, the tsunami will produce significant wave height changes on the sea surface. These wave height changes can be detected by wave height monitoring equipment, thereby indirectly monitoring the occurrence of an earthquake.

[0055] In order to more accurately distinguish different levels of tsunami threats and take corresponding early warning measures, different preset ranges are set. When the specific wave parameter value is within the first preset range, it indicates that the large-scale displacement of seawater caused by natural disasters such as earthquakes or volcanic eruptions has formed a type of sea wave with extremely high wave height and strong destructive power. When these waves reach coastal areas, the wave height usually increases significantly, which may cause serious disasters; when the specific wave parameter value is within the second preset range, it indicates that the wave height is relatively low in the deep sea area, but there is the potential for the wave height to increase significantly during the propagation process, and eventually reach tsunami-level waves in coastal areas. The preset range for judging marine disasters is determined based on wave height data, oceanographic models, and / or geological data in historical tsunami events. For example, in a certain sea area, historical tsunami data show that wave heights exceeding 0.5 meters usually attract attention, while wave heights exceeding 1.0 meters usually cause major disasters. Combined with oceanographic models and field measurement data, the first preset range can be set to [1.0, ) and the second preset range can be set to [0.5, 1.0). By setting a higher threshold, it can be ensured that an emergency alert is only issued when the wave height is indeed large enough, thereby improving the accuracy of the warning. At the same time, by setting a lower threshold, wave heights that may develop into tsunamis can be detected in advance, but an emergency alert will not be issued immediately, thereby reducing false alarms.

[0056] When an earthquake occurs in the sea, the waves caused by the tsunami spread out from the epicenter, such as Figure 3 As shown, mark 1 is the first preset position at the earthquake source, and mark 2 is the second preset position. A measuring device for monitoring wave parameters is set at each preset position, and the measuring device may be the same as or different from the first measuring device. The preset position where the abnormal wave height is measured is defined as the first preset position, and the preset position between the port and the first preset position and at a set distance from the first preset position is defined as the second preset position. It is only necessary to analyze the wave parameter values ​​of the preset positions close to the port side, and there is no need to analyze the wave parameter values ​​of the preset positions far from the port side.

[0057] Based on the wave parameter situation at the second preset position, the marine disaster is verified. When the second specific wave parameter value is greater than or equal to the set threshold, it is determined that a significant marine disaster will occur and the first warning information is sent; when the second specific wave parameter value is less than the set threshold, it is determined that no marine disaster will occur and the warning information is cancelled. Exemplarily, the threshold is set to K times the predicted specific wave parameter value, and the value of K is 0 to 1.

[0058] In order to more accurately distinguish different levels of tsunami threats and take corresponding early warning measures, monitoring and early warning through a graded early warning mechanism can improve the flexibility and accuracy of early warnings, reduce false alarms, ensure that appropriate response measures are taken in different situations, and improve the pertinence and effectiveness of early warnings. At the same time, based on the predicted wave parameter values, the actual wave parameter values ​​are verified, which can timely adjust the accuracy of early warning information, avoid false alarms or missed alarms, and improve the reliability and credibility of the early warning system.

[0059] In a specific embodiment, the warning information includes coordinate information of any preset location, a first specific wave parameter value, and a marine disaster type.

[0060] Specifically, the first warning information also includes reminding residents and relevant departments to immediately take emergency evacuation measures and initiate emergency response measures, such as evacuating residents and closing ports; the second warning information also includes reminding residents and relevant departments to pay attention to the possibility of a tsunami and initiate preliminary monitoring and preparation measures, such as strengthening monitoring and notifying relevant departments and residents.

[0061] In a specific embodiment, the method for predicting the specific wave parameter value and obtaining the second time is: (1) Acquire underwater three-dimensional image data of a target sea area and sea level data within a fourth preset time, determine a first underwater height at any preset position and a second underwater height at a second preset position based on the underwater three-dimensional image data and the sea level data, and determine a predicted specific wave parameter value based on the first specific wave parameter value, the first underwater height, and the second underwater height.

[0062] (2) Obtaining a third time when the first specific wave parameter value is monitored and a horizontal distance between any preset position and a second preset position, calculating an estimated wave speed at any point between any preset position and the second preset position based on the underwater three-dimensional image data, calculating a wave advancement time based on the horizontal distance and the estimated wave speed, and taking the sum of the third time and the wave advancement time as the second time.

[0063] The underwater height of any location in the sea is the vertical distance from the sea surface to the bottom of the ocean. The energy of the wave remains relatively constant during propagation. When the wave propagates from the deep sea to the shallow sea, the wave height changes with the underwater height, and its change is inversely proportional to the change of the underwater height. For example, the specific wave parameter value is predicted by empirical function calculation, where Hw is the predicted specific wave parameter value, H w1 D1 is the first underwater height, and D2 is the second underwater height.

[0064] The estimated wave velocity at any position in the sea is proportional to the square root of the underwater height at that position, and a first function for calculating the estimated wave velocity based on the underwater height is constructed in advance. The above horizontal distance is divided into N equal parts, and the underwater height of each equally divided point is obtained based on the underwater three-dimensional image data, and the estimated wave velocity of each equally divided point is further calculated. Then, according to the segment distance of any segment and the estimated wave velocity at the equally divided point of the segment close to the source side, the propagation time of any segment is calculated, and the propagation time of all segments is accumulated to obtain the wave advancement time, and finally the third time and the wave advancement time are added to obtain the second time.

[0065] Exemplarily, a preset model may also be trained in advance to obtain the predicted specific wave parameter value and the second time based on the underwater three-dimensional image data, the coordinate information of the first preset position, the first specific wave parameter value and the coordinate information of the second preset position.

[0066] Through technologies such as multi-beam sonar, single-beam sonar, lidar, satellite remote sensing and autonomous underwater robots, high-resolution underwater three-dimensional image data can be generated. Underwater three-dimensional image data can provide detailed information such as seabed topography, structure, texture and depth. Combining underwater three-dimensional image data with sea level data can more accurately predict the propagation path and parameter changes of waves, thereby improving the reliability and accuracy of early warning.

[0067] Preferably, when it is determined in step 23 that a significant marine disaster will occur, the specific wave parameter values ​​and time when the marine disaster will arrive at the port are predicted.

[0068] The above describes a method for real-time monitoring of the marine environment of an intelligent port in an embodiment of the present application. The following describes a system for real-time monitoring of the marine environment of an intelligent port in an embodiment of the present application. Figure 4 In an embodiment of the present application, an intelligent port marine environment real-time monitoring system comprises: a data acquisition module 10, a time judgment module 20, a first judgment module 30, a second judgment module 40 and an action monitoring module 50.

[0069] The data acquisition module 10 is used to collect environmental data of a specific location in the target sea area according to a preset period, wherein the environmental data includes seawater flow velocity and wave parameter values.

[0070] The time judgment module 20 is used to obtain the estimated berthing time of all ships expected to berth in the target sea area, extract the most recent estimated berthing time and define it as the first time, and judge whether the time difference between the current time and the first time is less than or equal to a first preset value. If so, enter the first judgment module 30.

[0071] The first judgment module 30 is used to judge whether the current time is in the flat tide period or the rising and falling period. If it is the rising and falling period, the second judgment module 40 is entered; if it is the flat tide period, the action monitoring module 50 is entered.

[0072] The second judgment module 40 is used to judge whether the environmental data meets the first preset condition. If so, the motion monitoring module 50 is entered. If not, the parking plan is regenerated and then the time judgment module 20 is returned.

[0073] The action monitoring module 50 is used to monitor whether the seawater flow rate and wave parameter values ​​meet the mooring conditions after the mooring action begins. If not, the mooring plan is regenerated, and then the time judgment module 20 is returned. If so, the mooring action is continued and the monitoring is continued until the target vessel completes the mooring, wherein the target vessel is the vessel corresponding to the first time.

[0074] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the above-described systems, systems and units can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0075] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application is essentially or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions to enable a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM), random access memory (RAM), disk or optical disk and other media that can store program codes.

[0076] As described above, the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A real-time monitoring method for the marine environment of an intelligent port, characterized in that: The method comprises: Step 1: Collect environmental data of a specific location in the target sea area according to a preset period, wherein the environmental data includes seawater flow velocity and wave parameter values; Step 2, obtaining the estimated berthing time of all ships expected to berth in the target sea area, extracting the most recent estimated berthing time and defining it as the first time, and determining whether the time difference between the current time and the first time is less than or equal to a first preset value, if so, proceeding to step 3; Step 3, determine whether the current time is in the slack tide period or the rising and falling period, if it is the rising and falling period, proceed to step 4, if it is the slack tide period, proceed to step 5; Step 4, determining whether the environmental data meets the first preset condition, if so, proceeding to step 5, if not, regenerating the parking plan, and then returning to step 2; Step 5: After the mooring action begins, monitor whether the seawater flow rate and the wave parameter value meet the mooring conditions. If not, regenerate the mooring plan and then return to step 2. If so, continue the mooring action and repeat this step until the target vessel completes the mooring, wherein the target vessel is the vessel corresponding to the first time.

2. A method for real-time monitoring of the marine environment of an intelligent port according to claim 1, characterized in that: A first spatial position information sequence of a first measuring device at the specific position within a first preset time is obtained, the first spatial position information sequence is input into a first preset model, and the wave parameter value of the target sea area is obtained. The generation method of the first preset model is: Acquire a second spatial position information sequence and a wave parameter value sequence of a second measuring device within a second preset time, and simultaneously acquire a third spatial position information sequence of the first measuring device within the second preset time, wherein the second measuring device is physically connected to the first measuring device, and a distance between the two is less than or equal to a second preset value; Machine learning is performed on the second spatial position information sequence and the wave parameter value sequence to construct a second preset model from the spatial position information sequence to wave parameters, and then the second preset model is trained based on the third spatial position information sequence and the wave parameter value sequence to generate the first preset model from the spatial position information sequence to wave parameters.

3. A method for real-time monitoring of the marine environment of an intelligent port according to claim 2, characterized in that: The wave parameters include wave height, wave speed and wave direction, and the first preset model is generated for each wave parameter.

4. A method for real-time monitoring of the marine environment of an intelligent port according to claim 1, characterized in that: The environmental data includes tidal level change parameters, air flow parameters, tidal periodicity parameters and river entry parameters. In step 4, determining whether the environmental data meets the first preset condition includes: Step 41, obtaining the tidal level change parameters of the target sea area within the third preset time, and judging whether the target sea area is in a specific tidal level state at the first time, if not, the first preset condition is met, and if so, entering step 42, the tidal level change parameters include the tidal level change amplitude; Step 42, judging whether the tidal level variation amplitude is greater than or equal to a third preset value, if so, the first preset condition is not satisfied, if not, judging whether the target sea area is in the low tide stage after the maximum tidal level or the low tide stage after the minimum tidal level at the first time, if so, the first preset condition is not satisfied, if not, proceeding to step 43; Step 43: Input the tidal level change parameter, the air flow parameter, the tidal periodicity parameter and the river into the sea parameter at the current time into a third preset model, obtain the comprehensive seawater flow velocity of the target sea area at the first time, and extract the ship type of the target ship, obtain a flow velocity threshold based on the ship type, and determine whether the comprehensive seawater flow velocity is less than or equal to the flow velocity threshold. If so, the first preset condition is met.

5. The method for real-time monitoring of the marine environment of an intelligent port according to claim 1, characterized in that: Collecting environmental information of multiple preset locations in the target sea area, before step 2 includes: Step 21, obtaining a first specific wave parameter value at any preset position, determining whether the first specific wave parameter value is within a first preset range, if so, determining that a significant marine disaster has occurred and sending a first warning message, then entering step 22, if not, determining whether the first specific wave parameter value is within a second preset range, if so, determining that a potential marine disaster has occurred and sending a second warning message, then entering step 22, if not, entering step 2; Step 22: obtaining a second preset position between any of the preset positions and the port based on preset rules, and predicting a predicted specific wave parameter value and a second time for the marine disaster to reach the second preset position; Step 23, obtaining the second specific wave parameter value at the second preset position at the second time, and determining whether the second specific wave parameter value is greater than or equal to a set threshold value. If so, determining that a significant marine disaster has occurred and sending the first warning information. If not, determining that no marine disaster will occur and canceling the warning information, and then entering step 2, wherein the set threshold value is set based on the predicted specific wave parameter value.

6. A method for real-time monitoring of the marine environment of an intelligent port according to claim 5, characterized in that: The warning information includes coordinate information of any of the preset locations, the first specific wave parameter value and the type of marine disaster.

7. A method for real-time monitoring of the marine environment of an intelligent port according to claim 5, characterized in that: The method for obtaining the predicted specific wave parameter value and the second time is: Acquire underwater three-dimensional image data of the target sea area and sea level data within a fourth preset time, determine a first underwater height at any of the preset positions and a second underwater height at the second preset position based on the underwater three-dimensional image data and the sea level data, and determine the predicted specific wave parameter value based on the first specific wave parameter value, the first underwater height, and the second underwater height; Obtain a third time when the first specific wave parameter value is monitored, and a horizontal distance between any of the preset positions and the second preset position, calculate an estimated wave speed at any point between any of the preset positions and the second preset position based on the underwater three-dimensional image data, calculate a wave advancement time based on the horizontal distance and the estimated wave speed, and use the sum of the third time and the wave advancement time as the second time.

8. A real-time monitoring system for the marine environment of an intelligent port, characterized in that: The system comprises: a data acquisition module, a time judgment module, a first judgment module, a second judgment module and an action monitoring module; The data acquisition module is used to collect environmental data of a specific location in the target sea area according to a preset period, wherein the environmental data includes seawater flow velocity and wave parameter values; The time judgment module is used to obtain the estimated berthing time of all ships expected to berth in the target sea area, extract the most recent estimated berthing time and define it as the first time, and judge whether the time difference between the current time and the first time is less than or equal to a first preset value, and if so, enter the first judgment module; The first judgment module is used to judge whether the current time is in the flat tide period or the rising and falling period, if it is the rising and falling period, then enter the second judgment module, if it is the flat tide period, then enter the action monitoring module; The second judgment module is used to judge whether the environmental data meets the first preset condition, and if so, enter the action monitoring module, and if not, regenerate the parking plan and then return to the time judgment module; The action monitoring module is used to monitor whether the seawater flow rate and the wave parameter value meet the mooring conditions after the mooring action begins. If not, the mooring plan is regenerated, and then the time judgment module is returned. If so, the mooring action is continued and the monitoring is continued until the target vessel completes the mooring, wherein the target vessel is the vessel corresponding to the first time.

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