Large-scale structure long-distance towing guarantee monitoring method and system

Abstract

The invention relates to the technical field of towing guarantee monitoring, in particular to a large-scale structure long-distance towing guarantee monitoring method and system, and the method comprises the steps: carrying out the real-time monitoring and collection of towing state data according to the towing guarantee monitoring demands, and obtaining the real-time data of the towing state; a monitoring terminal is constructed to receive the collected towing state real-time data and transmit the data to a towing monitoring data cloud platform; real-time rolling weather forecast data on a towing route is calculated by adopting a method for calculating weather data at any position of the open sea based on real-time fixed grid point weather forecast data, and floating body dynamics calculation methods such as a time-frequency domain combined calculation method and the like are adopted; and calculating motion state forecast data and towing resistance of the towed large-scale structure on the towing route in real time, and performing towing feasibility analysis and decision according to a calculation result and towing state real-time data. According to the invention, comprehensive collection of real-time data of the towing state is combined with rolling weather forecast and towing feasibility analysis, so that the efficiency and accuracy of towing monitoring and decision making are improved.

Description

Technical Field

[0001] This invention relates to the field of towing support monitoring technology, specifically to a method and system for long-distance towing support monitoring of large structures. Background Technology

[0002] As offshore wind power expands into deeper waters, the towing distances for large offshore wind power structures, such as stationary and floating wind turbines, are significantly longer than those for near-shore wind power projects. With the increased towing time and more complex sea conditions along towing routes, the risks associated with towing are drastically increasing. Therefore, ensuring safe towing at sea and improving the ability to identify towing risks in advance will gradually become the focus of future research on offshore wind power construction technology in my country.

[0003] Safety measures for long-distance towing of large offshore wind power structures generally include simulated towing motion and the development of comprehensive towing plans. Since the 1960s, scholars have continuously studied the maneuverability and navigation performance factors of towing. With the development of computing and simulation capabilities, numerical simulation and modeling techniques for the towing motion performance of large structures have gained a solid foundation. Towing plans, based on the China Classification Society's "Guidelines for Marine Towing," also have clear requirements regarding route setting, tugboat environmental condition design, verification of towing intensity and stability of the towed object, and towing operation layout. However, marine environmental conditions along the towing route change rapidly during towing. Therefore, simply relying on calculations such as towing stability analysis based on limited conditions to guide marine towing is clearly insufficient to ensure towing safety and guide towing decisions under emergency conditions.

[0004] Furthermore, the monitoring of the towed cargo's condition and the identification of towing risks largely rely on the crew's observations and comparisons, resulting in insufficient monitoring capabilities, low monitoring frequency, and weak statistical and analytical capabilities for monitoring data. In addition, due to the limited means of communication in the open sea, poor communication capabilities, limited reception of environmental forecast information, and poor communication between land and sea personnel, emergency response and handling of sudden situations rely heavily on the experience and capabilities of the towing captain, leading to problems such as untimely emergency response or unreasonable emergency measures, which affect the implementation of towing plans and cannot effectively guarantee towing safety.

[0005] Therefore, there is an urgent need for a monitoring and support method that can collect towing status data in real time, achieve efficient land-sea monitoring and communication, and accurately analyze the feasibility of towing. This method can automatically collect real-time data on the location, dynamics, status, weather, and environment of structures during towing, as well as on-site monitoring images. It can monitor the route trajectory, structure status, and changes in weather and environment in real time. It can utilize big data to collect information such as weather forecasts and the dynamics of surrounding vessels, and build a cloud platform to realize the transmission and processing of various data, images, and information. It can achieve towing status early warning through independently developed algorithms to assist in the formulation of towing support decisions. It can deploy monitoring terminals to achieve land-sea management collaboration, effectively ensuring the safety of long-distance towing of large offshore wind power structures. Summary of the Invention

[0006] To address the aforementioned technical shortcomings, this invention provides a method and system for monitoring and supporting the long-distance towing of large structures, thereby resolving the problems of insufficient accuracy in monitoring and analyzing the towing status and inefficient communication and cooperation between land and sea in existing towing support and monitoring methods.

[0007] This invention is achieved through the following technical solution: A method for monitoring and supporting long-distance towing of large structures is provided, the method comprising the following steps: Step S10: Based on the towing support monitoring requirements, monitor and collect towing status data in real time to obtain real-time towing status data; Step S20: Build a monitoring terminal to receive the collected real-time data on the towing status and transmit it to the towing monitoring data cloud platform; Step S30: Calculate real-time rolling weather forecast data along the towing route using a method based on real-time fixed grid weather forecast data for any location in the open sea. Use floating body dynamics calculation methods such as time-frequency domain joint calculation to calculate the motion state data and towing resistance of the towed large structure along the towing route in real time. Conduct towing feasibility analysis and decision-making based on the calculation results.

[0008] Preferably, step S10, which involves real-time monitoring and collection of towing status data to obtain real-time towing status data, includes: Constructing a towing status data acquisition device: Integrating hardware devices such as satellite positioning equipment, electromagnetic compass, motion reference unit (MRU), anemometer, and high-definition camera to obtain a towing status data acquisition device. Among them, the satellite positioning equipment is used to acquire the position information of the towed large structure in real time, the electromagnetic compass is used to provide the towing heading data, the motion reference unit (MRU) is used to collect the motion attitude data of the structure, including the motion states such as roll, pitch, and heave, the anemometer is used to collect real-time wind speed and wind direction information, and the high-definition camera is used to capture real-time images and videos of the towing site. The data acquisition and control program is designed to utilize an advanced synchronous control algorithm to enable collaborative operation of the towing status data acquisition devices. This program provides unified management and control of all hardware devices, ensuring synchronous data acquisition and stable transmission. By setting the sampling frequency and time synchronization mechanism for each device, data is acquired according to a predetermined sequence and time interval, thus achieving automated data acquisition. After preliminary preprocessing, the acquired data is packaged and stored in a unified data format for subsequent transmission and processing. The real-time towing status data includes the towed object's position, heading, motion attitude, ambient wind speed and direction, and on-site images and videos, providing foundational data for subsequent monitoring and analysis. The data acquisition hardware has a 120-hour battery life, meeting the long-term data acquisition needs during long-distance towing. After data acquisition, appropriate communication technology is used to achieve data transmission up to 180 kilometers from the shore, ensuring timely data transmission to the monitoring terminal during long-distance towing.

[0009] Preferably, the step S20, which involves constructing a monitoring terminal to receive and transmit the collected real-time towing status data to the towing monitoring data cloud platform, includes: The monitoring terminals include offshore and land-based monitoring terminals. The offshore monitoring terminals are deployed on the command tugboat, while the land-based monitoring terminals are deployed in the land-based command center. The offshore terminals access satellite signals and use high-gain satellite antennas and dedicated satellite communication units, enabling stable satellite communication within 180 kilometers offshore. This ensures that data transmission and communication with the outside world are not limited by distance and allows for real-time communication with the towing monitoring cloud platform. During towing, the offshore monitoring terminals receive data from the towing status data acquisition equipment in real time and transmit it to the towing monitoring data cloud platform. At the same time, the offshore terminals can also receive command and decision information from the land-based terminals deployed in the land-based command center, enabling real-time interaction between the site and the land-based command center. Constructing a towing monitoring data cloud platform: This platform utilizes a distributed cloud computing architecture to access and transmit real-time towing status data, offshore monitoring terminal data, and onshore monitoring terminal data, and stores them. It supports various data interfaces for data access, capable of receiving various data from step S10, including location, heading, motion status, wind speed and direction, and on-site images. Encrypted transmission protocols are used during data transmission to ensure data security and integrity. Data storage employs a distributed database, enabling efficient storage of massive amounts of towing data. The towing monitoring data cloud platform uses WebGIS as its user interface, leveraging geographic information system technology to visually display the towed object's preset route, real-time location and historical trajectory, status data, environmental forecasts, and surrounding vessel information in map form. Users can use the WebGIS interface to view whether the towed object's location deviates from the preset route, understand its historical motion trajectory, obtain current motion status parameters, and view environmental forecast information, including wind speed, wind direction, and wave height for the future, as well as the location and navigation information of surrounding vessels, to comprehensively understand the towing situation. Land-sea collaborative monitoring and communication: Offshore and land-based monitoring terminals synchronize data through the towing monitoring data cloud platform to monitor important towing data in real time. The offshore monitoring terminal uploads the collected towing data to the towing monitoring data cloud platform in real time, while the land-based monitoring terminal obtains this data from the cloud platform in real time and transmits it to the land command center to understand the status of the towing site in real time. At the same time, the offshore and land-based monitoring terminals can communicate in real time through the towing monitoring data cloud platform, supporting multiple communication methods such as text, images, and video. The interaction between the monitoring terminals and the cloud platform not only realizes data sharing and display but also provides data support and an interactive platform for real-time feasibility analysis and rolling forecasts of towing, making the entire monitoring system an organic whole. In addition, the towing monitoring data cloud platform has a historical data query function for towing status. Users can query historical data based on conditions such as time or data type, providing data support for the analysis and summary of the towing process.

[0010] Preferably, the step S30, which involves calculating real-time rolling weather forecast data along the towing route using a method based on real-time fixed-grid weather forecast data for any location in the open sea, includes: Meteorological forecast data acquisition: Acquire real-time fixed grid meteorological forecast data within a set area, including parameters such as air pressure, temperature, wind speed, wind direction, and wave height. Based on the towing plan route, delineate a strip-shaped calculation area centered on the route and 50-100 kilometers wide, extract meteorological parameters from all fixed grid points within this area, and form an initial meteorological dataset. Meteorological data preprocessing: timestamps of different meteorological parameters are aligned. When time deviation exists, linear interpolation is used to calibrate the time dimension. Spatial integrity of grid data is checked. Missing or outliers are marked. Subsequently, grid data from different sources are uniformly converted to the WGS84 geographic coordinate system and stored in NetCDF or HDF5 format for easy use in subsequent interpolation calculations. Interpolation calculation of meteorological data at any location in the open sea: Real-time meteorological data at any location in the open sea is calculated based on meteorological data of surrounding fixed grid points using spatial interpolation methods; Real-time rolling weather forecast data generation: Based on the interpolation results at the current moment, combined with the extrapolation algorithm of the numerical weather prediction model, rolling forecasts of meteorological parameters for the next 12-72 hours are obtained, with a time step of 1-3 hours. The interpolation and forecast results are converted into JSON or GeoJSON format and overlaid on a WebGIS map to display the spatial distribution of parameters such as wind speed and ocean waves in the form of color gradient maps or vector arrows. At the same time, a text-formatted forecast report is generated, which includes extreme value warnings of meteorological elements for each key navigation segment. The real-time rolling weather forecast data is synchronized to the towing monitoring data cloud platform through the API interface and stored by timestamp and spatial coordinate index for subsequent towing feasibility analysis. It also supports real-time querying by offshore monitoring terminals and onshore monitoring terminals.

[0011] Preferably, step S30, which employs floating body dynamics calculation methods such as time-frequency domain joint calculation, to calculate in real time the predicted motion state data and towing resistance of the towed large structure along the towing route, includes: Constructing a frequency domain dynamic model of the towed structure: Based on the three-dimensional shape, weight, center of gravity position, and tow cable connection point of the towed object, a mechanical model of it in waves is established using specialized software. The model focuses on describing the interaction characteristics between the underwater part and the fluid. Based on the geometric dimensions and physical parameters of the towed large structure, such as length, width, height, and underwater profile, and physical parameters such as weight, center of gravity position, and tow cable connection point, the model simulates the effect of waves of different frequencies on the structure and calculates its response characteristics such as the sway amplitude and force magnitude in the frequency domain. For example, a 1-second period wave causes a roll of 5°, and a 3-second period wave causes a roll of 8°, forming a frequency-response relationship database. Calculate the motion state and towing resistance of the structure: Convert real-time meteorological data into a load distribution spectrum in the frequency domain, convert wave energy into a dynamic force spectrum of the structure according to frequency distribution, combine the frequency domain dynamic model with the load distribution spectrum, and convert it into the motion trajectory of the structure over time through a convolution algorithm, outputting parameters such as real-time roll angle, heave speed, and towing resistance.

[0012] Preferably, step S30, which involves performing towing feasibility analysis and decision-making based on the calculation results, includes setting a safety threshold for the towed object's movement; extracting core parameters such as peak roll angle, heave rate, and towing resistance from the calculation results; comparing these parameters with the set safety threshold; automatically triggering a graded warning when the set safety threshold is reached or exceeded, indicating that towing poses a risk and requires corresponding adjustments; calculating the remaining time to reach the destination based on the current speed, remaining range, and real-time environmental influences, providing data support for the tugboat to adjust its course or request resupply; synchronizing information such as movement status, risk warnings, and remaining time to the offshore monitoring terminal and the onshore monitoring terminal in real time; and supporting both monitoring terminals to obtain data and make decisions through the towing monitoring data cloud platform. Simultaneously, based on real-time data updates, the feasibility of towing is dynamically assessed to ensure the accuracy and timeliness of the assessment results, providing a comprehensive and reliable reference for towing decisions.

[0013] Furthermore, to achieve the above objectives, the present invention also proposes a long-distance towing support and monitoring system for large structures, wherein the long-distance towing support and monitoring system for large structures includes: Real-time data acquisition module for towing status: Used to monitor and acquire towing status data in real time according to the towing support monitoring requirements; Towing monitoring terminal construction module: used to build a monitoring terminal to receive real-time data on towing status and transmit it to the towing monitoring data cloud platform; The real-time feasibility analysis and decision-making module for towing is used to calculate real-time rolling weather forecast data along the towing route using a method based on real-time fixed grid weather forecast data for any location in the open sea. It employs floating body dynamics calculation methods such as time-frequency domain joint calculation to calculate the motion state data and towing resistance of the towed large structure along the towing route in real time, and performs towing feasibility analysis and decision-making based on the calculation results.

[0014] Furthermore, to achieve the above objectives, the present invention also proposes a long-distance towing support and monitoring device for large structures. The device includes: a memory, a processor, and a program for long-distance towing support and monitoring of large structures stored in the memory and executable on the processor. The program for long-distance towing support and monitoring of large structures comprises the steps for implementing the long-distance towing support and monitoring method for large structures as described above.

[0015] In addition, to achieve the above objectives, the present invention also provides a computer program product, which includes programs such as long-distance towing support and monitoring for large structures. When the long-distance towing support and monitoring for large structures is executed by a processor, the program implements a long-distance towing support and monitoring method for large structures as described above.

[0016] The advantages and effects of this invention are: This invention proposes a method and system for monitoring and supporting long-distance towing of large structures. The invention achieves comprehensive and real-time acquisition of towing status data through a real-time data acquisition module; it enables efficient monitoring and communication between land and sea through a monitoring terminal and a towing monitoring data cloud platform, allowing the command center to grasp the towing situation on-site in real time and make decisions; and it achieves accurate analysis and rolling forecasts of towing feasibility through real-time feasibility analysis and real-time rolling weather forecast data, assisting in towing decision-making and improving the safety and reliability of long-distance towing of large structures. Attached Figure Description

[0017] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 This is a flowchart of a long-distance towing support and monitoring method for large structures according to the present invention.

[0019] Figure 2 This is a schematic diagram of a long-distance towing support and monitoring system for large structures according to the present invention.

[0020] Figure 3 This is a schematic block diagram of a large-scale structure for long-distance towing support and monitoring electronic equipment according to the present invention. Detailed Implementation

[0021] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0022] like Figure 1 As shown, in one embodiment of the present invention, a method for monitoring and supporting long-distance towing of large structures includes the following steps: Step S10: Based on the towing support monitoring requirements, monitor and collect towing status data in real time to obtain real-time towing status data.

[0023] Specifically, step S10, which involves real-time monitoring and collection of towing status data to obtain real-time towing status data, includes the following steps: Constructing a towing status data acquisition device: Integrating hardware devices such as satellite positioning equipment, electromagnetic compass, motion reference unit (MRU), anemometer, and high-definition camera to obtain a towing status data acquisition device. Among them, the satellite positioning equipment is used to acquire the position information of the towed large structure in real time, the electromagnetic compass is used to provide the towing heading data, the motion reference unit (MRU) is used to collect the motion attitude data of the structure, including the motion states such as roll, pitch, and heave, the anemometer is used to collect real-time wind speed and wind direction information, and the high-definition camera is used to capture real-time images and videos of the towing site. The data acquisition control program is designed to employ an advanced synchronous control algorithm to enable collaborative operation of the towing status data acquisition devices. This program provides unified management and control of all hardware devices, ensuring synchronous data acquisition and stable transmission. By setting the sampling frequency and time synchronization mechanism for each device, the program ensures that each device acquires data according to a predetermined sequence and time interval. For example, the control program periodically triggers the satellite positioning device to acquire position data, synchronously triggers the electromagnetic compass and motion reference unit (MRU) to acquire heading and motion status data, receives real-time wind speed and direction data from the anemometer, and controls the high-definition camera to capture images at a certain frequency. The system enables automated data acquisition. After preliminary preprocessing of various data types, the collected data is packaged and stored in a unified data format for subsequent transmission and processing. The real-time data collected on the towing status includes the position, heading, motion attitude of the towed object, environmental wind speed and direction, as well as on-site images and videos, providing basic data for subsequent monitoring and analysis. The data acquisition hardware has a 120-hour battery life, which can meet the long-term data acquisition needs during long-distance towing. After data acquisition, appropriate communication technology is used to achieve data transmission up to 180 kilometers away from the shore, ensuring that data can be transmitted to the monitoring terminal in a timely manner during long-distance towing.

[0024] Step S20: Build a monitoring terminal to receive the collected real-time data on the towing status and transmit it to the towing monitoring data cloud platform.

[0025] Specifically, step S20, which involves building a monitoring terminal to receive the collected real-time data on the towing status and transmit it to the towing monitoring data cloud platform, includes: The monitoring terminals include offshore and land-based monitoring terminals. The offshore monitoring terminals are deployed on the command tugboat, while the land-based monitoring terminals are deployed in the land-based command center. The offshore terminals access satellite signals and use high-gain satellite antennas and dedicated satellite communication units, enabling stable satellite communication within 180 kilometers offshore. This ensures that data transmission and communication with the outside world are not limited by distance and allows for real-time communication with the towing monitoring cloud platform. During towing, the offshore monitoring terminals receive data from the towing status data acquisition equipment in real time and transmit it to the towing monitoring data cloud platform. At the same time, the offshore terminals can also receive command and decision information from the land-based terminals deployed in the land-based command center, enabling real-time interaction between the site and the land-based command center. Constructing a towing monitoring data cloud platform: This platform utilizes a distributed cloud computing architecture to access and transmit real-time towing status data, offshore monitoring terminal data, and onshore monitoring terminal data, and stores them. It supports various data interfaces for data access, capable of receiving various data from step S10, including location, heading, motion status, wind speed and direction, and on-site images. Encrypted transmission protocols are used during data transmission to ensure data security and integrity. Data storage employs a distributed database, enabling efficient storage of massive amounts of towing data. The towing monitoring data cloud platform uses WebGIS as its user interface, leveraging geographic information system technology to visually display the towed object's preset route, real-time location and historical trajectory, status data, environmental forecasts, and surrounding vessel information in map form. Users can view real-time information through the WebGIS interface, checking if the towed object deviates from the preset route, understanding its historical trajectory, obtaining current motion parameters such as roll angle, pitch angle, and heave rate, and viewing environmental forecast information including wind speed, wind direction, and wave height for the future, as well as the location and navigation information of surrounding vessels, to comprehensively understand the towing situation. Land-sea collaborative monitoring and communication: Offshore and land-based monitoring terminals synchronize data through access to the towing monitoring data cloud platform to monitor important towing data in real time. The offshore monitoring terminal uploads the collected towing data to the towing monitoring data cloud platform in real time, while the land-based monitoring terminal obtains this data from the cloud platform in real time and transmits it to the land-based command center to understand the status of the towing operation in real time. Simultaneously, the offshore and land-based monitoring terminals can communicate in real time through the towing monitoring data cloud platform, supporting various communication methods such as text, images, and video. For example, personnel on the tugboat can take photos or videos of the scene using the offshore terminal and upload them. On the cloud platform, personnel at the land command center can view and analyze data through land-based terminals. They can also send text commands or voice messages to the crew on the tugboat, enabling real-time communication of on-site status and command decisions, thus assisting in towing decisions. The interaction between the monitoring terminal and the cloud platform not only enables data sharing and display but also provides data support and an interactive platform for real-time feasibility analysis and rolling forecasts of towing, making the entire monitoring system an organic whole. In addition, the towing monitoring data cloud platform has a historical data query function for towing status. Users can query historical data based on conditions such as time or data type, providing data support for the analysis and summary of the towing process.

[0026] Step S30: Calculate real-time rolling weather forecast data along the towing route using a method based on real-time fixed grid weather forecast data for any location in the open sea. Use floating body dynamics calculation methods such as time-frequency domain joint calculation to calculate the motion state data and towing resistance of the towed large structure along the towing route in real time. Conduct towing feasibility analysis and decision-making based on the calculation results.

[0027] Specifically, step S30, which uses the method of calculating meteorological data at any location in the open sea based on real-time fixed grid meteorological forecast data, includes the following steps: Meteorological forecast data acquisition: Acquire real-time fixed-grid meteorological forecast data within a designated area, including parameters such as air pressure, temperature, wind speed, wind direction, and wave height. Based on the towing plan route, delineate a strip-shaped calculation area centered on the route and 50-100 kilometers wide, extract meteorological parameters from all fixed grid points within this area, and form an initial meteorological dataset. For example, access the real-time grid data interface of global or predetermined numerical weather prediction models, such as the European Centre for Medium-Range Weather Forecasts (ECMWF) and the National Center for Environmental Prediction (NCEP) GFS model, to acquire standard grid meteorological data with resolutions of 0.1° and -1°. Data types include parameters such as pressure field, temperature field, wind speed field, wind direction field, wave height, period, and direction, with a data update frequency of 1-6 hours / time. Meteorological data preprocessing: Timestamps of different meteorological parameters, such as wind speed and ocean waves, are aligned to ensure consistent data collection times. When time deviations exist, linear interpolation is used for time dimension calibration. Spatial integrity of grid data is checked, and missing or outlier values ​​are marked, such as wind speed exceeding historical extremes. Subsequently, neighborhood mean filling or model prediction correction are used. Grid data from different sources are uniformly converted to the WGS84 geographic coordinate system and stored in NetCDF or HDF5 format for easy use in subsequent interpolation calculations. Meteorological data interpolation calculation at any location in the open sea: Real-time meteorological data at this location is calculated based on meteorological data from surrounding fixed grid points using spatial interpolation methods, such as Kriging interpolation or inverse distance weighted interpolation. Real-time rolling weather forecast data generation: Based on the interpolation results at the current moment, combined with the extrapolation algorithm of the numerical weather prediction model, such as the Runge-Kutta method, rolling forecasts of meteorological parameters for the next 12-72 hours are obtained, with a time step set to 1-3 hours. For example, for wind speed parameters, by solving the simplified form of the atmospheric motion equation, the wind speed vector change of each target point at future moments is predicted. The interpolation and forecast results are converted into JSON or GeoJSON format and overlaid on the WebGIS map to display the spatial distribution of parameters such as wind speed and waves in the form of color gradient maps or vector arrows. At the same time, a text-formatted forecast report is generated, which includes extreme value warnings of meteorological elements for each key navigation segment, such as maximum wind speed and maximum wave height, to obtain real-time rolling weather forecast data. The real-time rolling weather forecast data is synchronized to the towing monitoring data cloud platform through the API interface and stored by timestamp and spatial coordinate index for subsequent towing feasibility analysis. It also supports real-time querying by offshore monitoring terminals and onshore monitoring terminals.

[0028] Specifically, step S30, which employs floating body dynamics calculation methods such as time-frequency domain joint calculation, to calculate in real time the predicted motion state data and towing resistance of the towed large structure along the towing route, includes: Constructing a frequency domain dynamic model of the towed structure: Based on parameters such as the three-dimensional shape, weight, center of gravity position, and tow cable connection points of the towed object, such as offshore platforms and ship sections, a mechanical model of the structure in waves is established using specialized software. The model focuses on describing the interaction characteristics between the underwater part and the fluid. Based on the geometric dimensions and physical parameters of the towed large structure, such as length, width, height, and underwater profile, and physical parameters such as weight, center of gravity position, and tow cable connection points, the model simulates the effect of waves of different frequencies on the structure and calculates its response characteristics such as the sway amplitude and force magnitude in the frequency domain. For example, a 1-second period wave causes a roll of 5°, and a 3-second period wave causes a roll of 8°, forming a frequency-response relationship database. Calculate the motion state of the structure and towing resistance: Convert real-time meteorological data into a load distribution spectrum in the frequency domain, such as wave height, period, and water flow velocity. Convert wave energy into a dynamic force spectrum of the structure according to frequency distribution. Combine the frequency domain dynamic model with the load distribution spectrum and convert it into the motion trajectory of the structure over time through a convolution algorithm. Output parameters such as real-time roll angle, heave rate, and towing resistance. For example, if the roll angle fluctuates between 8° and 12° in the next hour, the towing resistance is 500 tons.

[0029] Specifically, step S30, which involves conducting a towing feasibility analysis and decision-making based on the calculation results, includes setting a safety threshold for the towed object's movement; extracting core parameters such as peak roll angle, heave rate, and towing resistance from the calculation results; comparing these parameters with the set safety threshold; and automatically triggering tiered warnings when the set safety threshold is reached or exceeded, indicating a risk to towing and requiring corresponding adjustments. For example, a yellow warning indicates a roll exceeding 15°, a yellow warning indicates speed adjustment, and a red warning suggests suspending towing. The remaining time to reach the destination is calculated based on the current speed, remaining distance, and real-time environmental influences, such as slowing down against headwinds. This provides data support for the tugboat to adjust its course or request resupply. The motion status, risk warnings, and remaining time are synchronized in real-time to the offshore monitoring terminal and the onshore monitoring terminal. Both monitoring terminals can obtain data and make decisions through the towing monitoring data cloud platform, such as changing the route, adjusting speed, or suspending towing. Simultaneously, the feasibility of towing is dynamically assessed based on real-time data updates, ensuring the accuracy and timeliness of the assessment results and providing a comprehensive and reliable reference for towing decisions.

[0030] In addition, such as Figure 2 As shown, in one embodiment of the present invention, a long-distance towing support and monitoring system for large structures is proposed, the long-distance towing support and monitoring system for large structures comprising: Real-time data acquisition module for towing status: Used to monitor and acquire towing status data in real time according to the towing support monitoring requirements; Towing monitoring terminal construction module: used to build a monitoring terminal to receive real-time data on towing status and transmit it to the towing monitoring data cloud platform; The real-time feasibility analysis and decision-making module for towing is used to calculate real-time rolling weather forecast data along the towing route using a method based on real-time fixed grid weather forecast data for any location in the open sea. It employs floating body dynamics calculation methods such as time-frequency domain joint calculation to calculate the motion state data and towing resistance of the towed large structure along the towing route in real time, and performs towing feasibility analysis and decision-making based on the calculation results.

[0031] Furthermore, in the aforementioned long-distance towing support and monitoring system for large structures, the towing data acquisition system can collect real-time data on the movement and attitude of the towed structure, and has the function of transmitting data with a continuous voyage of 120 hours and a distance of 180 kilometers from the shore. The collected towing data can be queried in real time by logging into the Sanhang Offshore Wind Power Cloud Service Platform. The towing monitoring data cloud platform can provide a 3-hour forecast of the towing feasibility for the next 72 hours, and can also realize typhoon path warning and display of anchorages along the route, and dynamically predict the towing time.

[0032] This application provides a long-distance towing support and monitoring system for large structures, employing a method described in the above embodiments. This system addresses the technical problems of incomplete and untimely data collection, inaccurate towing status monitoring and analysis, and low efficiency in land-sea communication and coordination found in existing towing support and monitoring methods. Compared to existing technologies, the beneficial effects of the long-distance towing support and monitoring system for large structures provided in this application are the same as those of the method described in the above embodiments. Furthermore, other technical features of the long-distance towing support and monitoring system for large structures are the same as those disclosed in the methods of the above embodiments, and will not be elaborated upon here.

[0033] This application provides a long-distance towing support and monitoring device for large structures. The long-distance towing support and monitoring device for large structures includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to execute the long-distance towing support and monitoring method for large structures in the above embodiment 1.

[0034] like Figure 3 As shown in the illustration, in one embodiment of the present invention, a structural schematic diagram of a long-distance towing support and monitoring device for large structures suitable for implementing the embodiments of this application is presented. The long-distance towing support and monitoring device for large structures in the embodiments of this application may include, but is not limited to, mobile terminals such as mobile phones, laptops, digital broadcast receivers, PDAs (Personal Digital Assistants), PADs (Portable Application Descriptions), PMPs (Portable Media Players), etc., as well as fixed terminals such as digital TVs, desktop computers, etc. Figure 3 The large-structure long-distance towing support and monitoring device shown is merely an example and should not impose any limitations on the functionality and scope of use of the embodiments of this application.

[0035] Figure 3 The large-structure long-distance towing support and monitoring device shown may include a processor 1001 (e.g., a central processing unit, graphics processor, etc.), which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 1002 or a program loaded from a storage device 1003 into a machine-readable storage medium (RAM) 1004. The RAM 1004 also stores various programs and data required for the operation of the large-structure long-distance towing support and monitoring device. The processor 1001, ROM 1002, and RAM 1004 are interconnected via a bus 1005. An input / output (I / O) interface 1006 is also connected to the bus. Typically, the following systems can be connected to I / O interface 1006: input devices 1007 including, for example, touchscreens, touchpads, keyboards, mice, image sensors, microphones, accelerometers, gyroscopes, etc.; output devices 1008 including, for example, liquid crystal displays (LCDs), speakers, vibrators, etc.; storage devices 1003 including, for example, magnetic tapes, hard disks, etc.; and a communication unit 1009. Communication unit 1009 allows a large structure long-distance towing support monitoring device to exchange data with other devices wirelessly or via wired communication. Although a large structure long-distance towing support monitoring device with various systems is shown in the figure, it should be understood that it is not required to implement or possess all the systems shown. More or fewer systems may be implemented alternatively.

[0036] Specifically, according to the embodiments disclosed in this application, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments disclosed in this application include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via a communication unit, or installed from storage device 1003, or installed from ROM 1002. When the computer program is executed by processor 1001, it performs the functions defined in the methods of the embodiments disclosed in this application.

[0037] This application provides a long-distance towing support and monitoring device for large structures, employing a long-distance towing support and monitoring method for large structures as described in the above embodiments. This addresses the technical problems of incomplete and untimely data collection, inaccurate towing status monitoring and analysis, and low efficiency in land-sea communication and coordination in existing towing support and monitoring methods. Compared with the prior art, the beneficial effects of the long-distance towing support and monitoring device for large structures provided in this application are the same as those of the long-distance towing support and monitoring method for large structures provided in the above embodiments. Furthermore, other technical features of this long-distance towing support and monitoring device for large structures are the same as those disclosed in the previous embodiment method, and will not be repeated here.

[0038] The various parts disclosed in this application can be implemented using hardware, software, firmware, or a combination thereof. In the description of the above embodiments, specific features, structures, materials, or characteristics can be combined in any suitable manner in one or more embodiments or examples.

[0039] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the steps of the above-described method for monitoring and supporting long-distance towing of large structures.

[0040] The computer program product provided in this application can solve the technical problems of incomplete and untimely data collection, insufficient accuracy in towing status monitoring and analysis, and low efficiency in communication and coordination between land and sea in existing towing support and monitoring methods. Compared with the prior art, the beneficial effects of the computer program product provided in this application are the same as those of the long-distance towing support and monitoring method for large structures provided in the above embodiments, and will not be repeated here.

[0041] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, this invention also intends to include these modifications and variations.

Claims

1. A method for monitoring and supporting long-distance towing of large structures, characterized in that, The method includes the following steps: Step S10: Based on the towing support monitoring requirements, monitor and collect towing status data in real time to obtain real-time towing status data; Step S20: Build a monitoring terminal to receive the collected real-time data on the towing status and transmit it to the towing monitoring data cloud platform; Step S30: Calculate real-time rolling weather forecast data along the towing route using a method based on real-time fixed grid weather forecast data for any location in the open sea. Use a time-frequency domain joint calculation method to calculate the motion state data and towing resistance of the towed large structure along the towing route in real time. Conduct towing feasibility analysis and decision-making based on the calculation results.

2. The method for long-distance towing support and monitoring of large structures according to claim 1, characterized in that, The step S10, which involves real-time monitoring and collection of towing status data, includes the following steps: Constructing a towing status data acquisition device: Integrating satellite positioning equipment, electromagnetic compass, motion reference unit (MRU), anemometer, and camera into a towing status data acquisition device. The satellite positioning equipment is used to acquire the position information of the towed large structure in real time, the electromagnetic compass is used to provide towing heading data, the motion reference unit (MRU) is used to collect the motion attitude data of the structure, the anemometer is used to collect real-time wind speed and wind direction information, and the camera is used to capture real-time images and videos of the towing site. Design of data acquisition control program: The data acquisition control program adopts a synchronous control algorithm to manage and control various hardware devices in a unified manner. By setting the sampling frequency and time synchronization mechanism of each device, each device acquires data in a predetermined order and time interval. After preliminary preprocessing of the acquired data, it is packaged and stored in a unified data format.

3. The method for long-distance towing support and monitoring of large structures according to claim 1, characterized in that, The step S20, which involves constructing a monitoring terminal to receive and transmit the collected real-time towing status data to the towing monitoring data cloud platform, includes: The monitoring terminals include offshore and land-based monitoring terminals. The offshore monitoring terminals are deployed on the command tugboat, while the land-based monitoring terminals are deployed in the land-based command center. The offshore terminals access satellite signals and use satellite antennas and dedicated satellite communication units to achieve stable satellite communication within 180 kilometers offshore. They communicate in real time with the towing monitoring cloud platform. During towing, the offshore monitoring terminals receive data from the towing status data acquisition equipment in real time and transmit it to the towing monitoring data cloud platform. At the same time, the offshore monitoring terminals receive command and decision information from the land-based monitoring terminals deployed in the land-based command center. Constructing a towing monitoring data cloud platform: The towing monitoring data cloud platform adopts a distributed cloud computing architecture for real-time access and transmission of towing status data, offshore monitoring terminal data, and land monitoring terminal data, and stores them. In data access, it supports various data interfaces to receive various types of data from the towing status data acquisition equipment in step S10. During data transmission, an encrypted transmission protocol is used, and data storage adopts a distributed database. The towing monitoring data cloud platform uses WebGIS as the user interface and utilizes geographic information system technology to display the preset route, real-time location and historical trajectory, status data, environmental forecasts, and surrounding vessel information of the towed object in the form of a map. Users can view whether the position of the towed object deviates from the preset route in real time through the WebGIS interface, understand its historical movement trajectory, obtain the current movement status parameters, and view environmental forecast information, including wind speed, wind direction, and wave height for a period of time in the future, as well as the position and navigation information of surrounding vessels. Land-sea collaborative monitoring and communication: Offshore and land-based monitoring terminals synchronize data by accessing the towing monitoring data cloud platform to monitor towing data in real time. The offshore monitoring terminal uploads the collected towing data to the towing monitoring data cloud platform in real time, while the land-based monitoring terminal obtains this data from the cloud platform in real time and transmits it to the land command center to obtain the real-time status of the towing site. At the same time, the offshore and land-based monitoring terminals communicate in real time through the towing monitoring data cloud platform, supporting text, image, and video communication methods. In addition, the towing monitoring data cloud platform has a historical data query function for towing status, allowing users to query historical data by time or data type.

4. The method for long-distance towing support and monitoring of large structures according to claim 1, characterized in that, The step S30, which uses a method based on real-time fixed-grid meteorological forecast data to calculate meteorological data at any location in the open sea, to calculate real-time rolling meteorological forecast data along the towing route, includes: Meteorological forecast data acquisition: Acquire real-time fixed grid meteorological forecast data within a set area, including air pressure, temperature, wind speed, wind direction and wave height parameters. Based on the towing plan route, delineate a strip calculation area centered on the route and 50-100 kilometers wide, extract meteorological parameters of all fixed grid points within this area, and form an initial meteorological dataset. Meteorological data preprocessing: timestamps of different meteorological parameters are aligned. When time deviation exists, linear interpolation is used to calibrate the time dimension. The spatial integrity of grid data is checked. Missing or outliers are marked. Subsequently, grid data from different sources are uniformly converted to the WGS84 geographic coordinate system and stored in NetCDF or HDF5 format through neighborhood mean filling or model prediction correction. Interpolation calculation of meteorological data at any location in the open sea: Real-time meteorological data at any location in the open sea is calculated based on meteorological data of surrounding fixed grid points using spatial interpolation methods; Real-time rolling weather forecast data generation: Based on the interpolation results at the current moment, combined with the extrapolation algorithm of the numerical weather prediction model, rolling forecasts of meteorological parameters for the next 12-72 hours are obtained, with a time step of 1-3 hours. The interpolation and forecast results are converted into JSON or GeoJSON format and overlaid on a WebGIS map to display the spatial distribution of wind speed and wave parameters in the form of color gradient maps or vector arrows. At the same time, a text-formatted forecast report is generated, which includes extreme value warnings of meteorological elements for each key navigation segment. Real-time rolling weather forecast data is obtained and synchronized to the towing monitoring data cloud platform through an API interface. The data is stored by timestamp and spatial coordinate index for subsequent towing feasibility analysis and supports real-time querying by offshore monitoring terminals and onshore monitoring terminals.

5. A method for long-distance towing support and monitoring of large structures according to claim 1, characterized in that, The step S30, which employs a joint time-frequency domain calculation method to calculate in real-time motion state prediction data and towing resistance of the towed large structure along the towing route, includes the following steps: Constructing a frequency domain dynamic model of the towed structure: Based on the three-dimensional shape, weight, center of gravity position and tow cable connection point of the towed object, a mechanical model of the towed large structure in waves is established. Based on the geometric dimensions and physical parameters of the towed large structure, the effect of waves of different frequencies on the structure is simulated, and its response characteristics of sway amplitude and force magnitude in the frequency domain are calculated to form a frequency-response relationship database. Calculate the motion state and towing resistance of the structure: Convert real-time meteorological data into a load distribution map in the frequency domain, combine the mechanical model with the load distribution map, and convert it into the motion trajectory of the structure over time through a convolution algorithm, outputting real-time roll angle, heave speed and towing resistance parameters.

6. The method for long-distance towing support and monitoring of large structures according to claim 1, characterized in that, The towing feasibility analysis and decision-making process in step S30 includes setting a safety threshold for the towed object's movement, extracting peak roll angle, heave rate, and towing resistance parameters from the calculation results, comparing them with the set safety threshold, automatically triggering a graded warning when the set safety threshold is reached or exceeded, calculating the remaining time to reach the destination by combining the current speed, remaining range, and real-time environmental influences, providing data support for the tugboat to adjust its course or request resupply, synchronizing the movement status, risk warnings, and remaining time to the offshore monitoring terminal and the land-based monitoring terminal in real time, and supporting the two monitoring terminals to obtain data and make decisions through the towing monitoring data cloud platform. At the same time, the feasibility of towing is dynamically evaluated based on the updates of real-time data.

7. A long-distance towing support and monitoring system for large structures, characterized in that, The system executes the long-distance towing support and monitoring method for large structures as described in claim 1, comprising: Real-time data acquisition module for towing status: Used to monitor and acquire towing status data in real time according to the towing support monitoring requirements; Towing monitoring terminal construction module: used to build a monitoring terminal to receive real-time data on towing status and transmit it to the towing monitoring data cloud platform; The real-time feasibility analysis and decision-making module for towing is used to calculate real-time rolling weather forecast data along the towing route using a method based on real-time fixed grid weather forecast data for any location in the open sea. It employs a time-frequency domain joint calculation method to calculate the motion state data and towing resistance of the towed large structure along the towing route in real time, and performs towing feasibility analysis and decision-making based on the calculation results.

8. A long-distance towing support and monitoring device for large structures, characterized in that, include: The system includes a memory, a processor, and a large structure long-distance towing support monitoring program stored in the memory and executable on the processor. When the large structure long-distance towing support monitoring program is executed by the processor, it implements a large structure long-distance towing support monitoring method as described in any one of claims 1 to 6.

9. A computer program product, characterized in that, The computer program product includes a long-distance towing support and monitoring program for large structures, which, when executed by a processor, implements a long-distance towing support and monitoring method for large structures as described in any one of claims 1 to 6.

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