Anchor chain force calculation method, system and equipment for deep sea floating type draught fan and medium

Abstract

The invention relates to a method, a system and equipment for calculating the anchor chain force of a deep sea floating fan and a medium. The method comprises the following steps: acquiring motion data of a target platform; processing the obtained motion data, inputting the processed motion data into a pre-constructed anchor chain force calculation model, and calculating to obtain anchor chain force data at the current time; alarm information is generated according to the anchor chain force data at the current time and a preset threshold value, and multi-level early warning is carried out; and platform motion data, anchor chain force data and early warning information are transmitted to a remote monitoring system or a data center for remote monitoring and analysis. The method can be widely applied to the field of ocean engineering.

Description

Technical Field

[0001] The present invention belongs to the field of marine engineering and relates to a method, system, equipment and medium for calculating the anchor chain force of a deep-sea floating wind turbine. Background Art

[0002] Wind power has gained widespread popularity due to its clean, renewable nature, short infrastructure construction cycles, flexible installation scale, and low operating and maintenance costs. However, due to the limited land area available for wind turbine installation on land and continental shelves, truly promoting sustainable energy development ultimately requires focusing on offshore deepwaters and even the deep sea. Compared to fixed wind turbines on the continental shelf, floating wind turbines can bypass the limitations of sea depth and effectively utilize wind energy at greater depths.

[0003] Because floating wind turbine platforms float on the sea surface, they are significantly affected by the marine environment. To ensure the normal operation of semi-submersible platforms, a mooring system is required to secure the turbines in place. Therefore, the stability and safety of the mooring system must be guaranteed. However, after prolonged service in harsh sea conditions and under the influence of multiple external forces, the mooring system is prone to fatigue damage, which in turn affects the safety and reliability of the semi-submersible platform. To determine the fatigue status of the mooring system, it is necessary to monitor the forces acting on the mooring cables and anchor chains. By comparing the changes in anchor chain forces with the design parameters, the service life of the anchor chains can be determined. However, deploying anchor chain force measurement equipment is complex and costly. Summary of the Invention

[0004] In response to the problem that the above-mentioned mooring system is prone to fatigue damage, the purpose of the present invention is to provide a method, system, equipment and medium for calculating the anchor chain force for deep-sea floating wind turbines. The method can calculate the anchor chain force based on the movement of the platform without direct contact, so as to ensure the safety and stability of the platform.

[0005] To achieve the above object, the present invention adopts the following technical solutions: In a first aspect, the present invention provides a method for calculating anchor chain forces for deep-sea floating wind turbines, comprising the following steps: Obtain motion data of the target platform; After processing the acquired motion data, the data is input into the pre-built anchor chain force estimation model to calculate the anchor chain force data at the current time; Generate alarm information based on the current anchor chain force data and preset thresholds to provide multi-level warnings; The platform motion data, anchor chain force data and warning information are transmitted to the remote monitoring system or data center for remote monitoring and analysis.

[0006] Furthermore, obtaining the motion data of the target platform includes: Deploy observation equipment at preset locations on the target platform; Use observation equipment to measure the motion data of the target platform; Wireless communication technology is used to transmit measurement data to the ground control center or monitoring platform in real time, while performing local backup.

[0007] Furthermore, the observation equipment includes an MRU and a GPS device; the MRU is used to measure the acceleration and angular velocity of the platform; and the GPS device is used to provide XYZ coordinates and velocity information of the floating platform.

[0008] Furthermore, the obtained motion data is processed and input into a pre-built anchor chain force calculation model to calculate the anchor chain force data at the current time, including: The preset method is used to fuse the measurement data of MRU and GPS to obtain the precise motion status of the platform; The model is calibrated using known environmental parameters and the initial state of the platform to remove the influence of the initial state on the platform motion and ensure the accuracy of the back-calculation results; The platform's motion state data is input into the anchor chain force calculation model to obtain the anchor chain force data at the current time.

[0009] Furthermore, the construction of the anchor chain force calculation model includes: Obtain the basic parameters of the target platform according to the design report of the target platform; According to the design drawing of the target platform, a simulation model of the platform is established in orcaflex; Take several sea conditions and use orcaflex to calculate the corresponding platform motion state and anchor chain force, and establish a platform motion state-anchor chain force database; The training data set is divided based on the data of the platform motion state-anchor chain force database, and the constructed neural network model is trained to obtain the anchor chain force estimation model.

[0010] Furthermore, the generation of alarm information based on the anchor chain force data at the current time and the preset threshold value to perform multi-level early warning includes: Tension overload warning: Determines whether the anchor chain force exceeds the preset safety threshold. If so, an alarm is immediately triggered to indicate possible equipment damage or platform stability issues. Movement out-of-limit warning: Determines whether the platform's movement exceeds the safety range. If so, a warning is triggered.

[0011] In a second aspect, the present invention provides an anchor chain force estimation system for deep-sea floating wind turbines, comprising: A data measurement unit, used to obtain motion data of the target platform; A calculation unit is used to process the measured motion data and input it into a pre-built anchor chain force calculation model to calculate the anchor chain force data at the current time; The early warning unit is used to generate alarm information based on the current anchor chain force data and preset thresholds, and perform multi-level early warning; The data transmission unit is used to transmit platform motion data, anchor chain force data and warning information to the remote monitoring system or data center for remote monitoring and analysis.

[0012] Furthermore, the data transmission unit realizes communication through the Beidou short message system respectively set up on the platform and the land base station.

[0013] In a third aspect, the present invention provides a computer-readable storage medium storing one or more programs, wherein the one or more programs include instructions that, when executed by a computing device, cause the computing device to perform any method.

[0014] In a fourth aspect, the present invention provides a computing device comprising: one or more processors and a memory, wherein the memory stores one or more programs and is configured to be executed by the one or more processors, and the one or more programs include instructions for executing any method.

[0015] The present invention has the following advantages due to the adoption of the above technical solution: 1. The present invention saves the cost of sensor deployment caused by the direct method of measuring anchor chain force and avoids the subsequent maintenance work.

[0016] 2. The present invention is based on the simulation modeling of ocarflex, which is easier to implement than methods such as model testing and has a convenient and quick effect.

[0017] 3. Compared with other calculation methods, the present invention adopts a neural network model, which can locally restore the physical characteristics of the platform, obtain more accurate calculation results, and calculate the anchor chain force for any conventional working conditions.

[0018] Therefore, the present invention can be widely applied in the field of marine engineering. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Various other advantages and benefits will become apparent to those skilled in the art upon reading the detailed description of the preferred embodiment below. The accompanying drawings are for illustration purposes only and are not to be considered as limiting the present invention. Throughout the drawings, the same reference numerals are used to denote the same components. In the drawings: Figure 1This is a flow chart of a method for calculating anchor chain force for deep-sea floating wind turbines provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0020] To make the objectives, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions of the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the described embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field are within the scope of protection of the present invention.

[0021] It should be noted that the terms used herein are only for describing specific embodiments and are not intended to limit the exemplary embodiments according to the present invention. As used herein, unless the context clearly indicates otherwise, the singular form is intended to include the plural form. In addition, it should be understood that when the terms "comprise" and / or "include" are used in this specification, they indicate the presence of features, steps, operations, devices, components and / or combinations thereof.

[0022] In some embodiments of the present invention, a method for calculating anchor chain forces for deep-sea floating wind turbines is provided, comprising: obtaining motion data of a target platform; processing the measured motion data and inputting it into a pre-built anchor chain force calculation model to calculate anchor chain force data at the current time; generating alarm information based on the anchor chain force data at the current time and preset thresholds, providing multi-level early warning; and transmitting the platform motion data, anchor chain force data, and alarm information to a remote monitoring system or data center for remote monitoring and analysis. The present invention utilizes a neural network model to partially restore the physical characteristics of the physical platform, resulting in more accurate calculation results and capable of calculating anchor chain forces for any conventional operating conditions.

[0023] Correspondingly, in other embodiments of the present invention, a system, device and medium for calculating the anchor chain force of a deep-sea floating wind turbine are provided.

[0024] Example 1 like Figure 1 As shown, the present invention provides a method for calculating the anchor chain force for deep-sea floating wind turbines, which is generally applicable to offshore platforms or similar environments. The purpose is to infer the platform's motion by the force changes of the anchor chain to ensure the stability, positioning, and safety of the platform. Specifically, the method includes the following steps: 1) Obtain motion data of the target platform; 2) After processing the acquired motion data, the data is input into the pre-built anchor chain force estimation model to calculate the anchor chain force data at the current time; 3) Generate alarm information based on the current anchor chain force data and preset thresholds, and provide multi-level warnings; 4) Transmit platform motion data, anchor chain force data, and warning information to a remote monitoring system or data center for remote monitoring and analysis.

[0025] Furthermore, the above step 1) includes the following steps: 1.1) Deploy observation equipment at the preset location of the target platform; 1.2) Use observation equipment to measure the motion data of the target platform; 1.3) Use wireless communication technologies (such as satellite communication, Wi-Fi, LTE, etc.) to transmit measurement data to the ground control center or monitoring platform in real time, and perform local backup at the same time.

[0026] Furthermore, in step 1.1) above, the observation equipment primarily includes an MRU (Motion Reference Unit) and a GPS device. The MRU is used to measure the platform's acceleration, angular velocity, and other parameters, typically including a gyroscope and accelerometer. The GPS device provides information such as the floating platform's X, Y, and Z coordinates and velocity. Specifically, the MRU and GPS devices must continuously collect platform motion data, and the MRU sensors must employ high-frequency sampling to accurately reflect changes in the platform's motion.

[0027] Furthermore, the above step 2) includes the following steps: 2.1) Using a pre-set method to fuse the measurement data from the MRU and GPS, the precise motion state of the platform is obtained; 2.2) Calibrate the model using known environmental parameters and the platform's initial state to remove the influence of the platform's initial state on its motion and ensure the accuracy of the inverse calculation results; 2.3) Input the platform's motion state data into the anchor chain force calculation model to obtain the anchor chain force data at the current time.

[0028] Furthermore, in the above step 2.1), this embodiment uses a Kalman filter algorithm to fuse the GPS position data and the inertial data of the MRU.

[0029] Furthermore, in the above step 2.3), the method for constructing the anchor chain force calculation model includes the following steps: 2.3.1) Based on the design report of the target platform, obtain the basic parameters of the target platform, including weight, center of gravity, waterline height, platform length, etc. 2.3.2) Based on the design drawings of the target platform, build a simulation model of the platform in OrcaFlex; 2.3.3) Take several sea conditions and use OrcaFlex to calculate the corresponding platform motion state and anchor chain force, and establish a platform motion state-anchor chain force database; 2.3.4) Divide the training data set based on the platform motion state-anchor chain force database, train the constructed neural network model, and obtain the anchor chain force estimation model.

[0030] Specifically, the method includes the following steps: ① Divide the data of the platform motion state-anchor chain force database into training set, verification set and test set according to the preset ratio.

[0031] In this embodiment, 70% is the training set, 15% is the validation set, and 15% is the test set.

[0032] ② Use the training set to train the pre-built neural network model, and use the validation set and test set to verify and test the trained neural network model.

[0033] In this embodiment, the neural network model adopts a convolutional neural network (CNN) + RNN mode. CNN is used to extract local features in the data (for example, the relationship between the acceleration and velocity of the platform, etc.), and then the extracted features are passed to the RNN for time series modeling.

[0034] ③ The neural network model that meets the preset requirements is used as the anchor chain force calculation model.

[0035] Furthermore, in the above step 3), an alarm message is generated based on the anchor chain force data at the current time and the preset threshold value, and a multi-level warning is performed, including: Tension overload warning: Determines whether the anchor chain force exceeds the preset safety threshold. If so, an alarm is immediately triggered to indicate possible equipment damage or platform stability issues. Movement out-of-limit warning: Determine whether the platform's movement exceeds the safety range (such as tilt angle, offset distance, etc.). If exceeded, a warning is triggered.

[0036] Example 2 The above-mentioned embodiment 1 provides a method for calculating anchor chain forces for deep-sea floating wind turbines. Correspondingly, this embodiment provides a system for calculating anchor chain forces for deep-sea floating wind turbines. The system provided in this embodiment can implement the anchor chain force calculation method for deep-sea floating wind turbines in embodiment 1. The system can be implemented through software, hardware, or a combination of software and hardware. For example, the system can include integrated or separate functional modules or functional units to perform the corresponding steps in each method of embodiment 1. Because the system of this embodiment is basically similar to the method embodiment, the description of the process of this embodiment is relatively simple. For relevant details, please refer to the partial description of embodiment 1. The embodiment of the system provided in this embodiment is merely illustrative.

[0037] The anchor chain force calculation system for deep-sea floating wind turbines provided in this embodiment includes: A data measurement unit, used to obtain motion data of the target platform; A calculation unit is used to process the measured motion data and input it into a pre-built anchor chain force calculation model to calculate the anchor chain force data at the current time; The early warning unit is used to generate alarm information based on the current anchor chain force data and preset thresholds, and perform multi-level early warning; The data transmission unit is used to transmit platform motion data, anchor chain force data and warning information to the remote monitoring system or data center for remote monitoring and analysis.

[0038] Furthermore, the early warning unit includes: The tension overload warning module is used to determine whether the anchor chain force exceeds the preset safety threshold. If so, an alarm is immediately issued to indicate possible equipment damage or platform stability issues; The motion over-limit warning module is used to determine whether the platform's motion exceeds the safety range (such as tilt angle, offset distance, etc.). If so, an alarm is triggered; The warning information output module is used to transmit warning information in various ways, such as displaying it on the operation terminal or sending it to the remote monitoring center via wireless communication.

[0039] Furthermore, the data transmission unit has the following key functions: Wireless data transmission: Use wireless communication technologies (such as satellite communication, Wi-Fi, LTE, etc.) to transmit measured data to the ground control center or monitoring platform in real time.

[0040] Data storage and backup: Data during transmission should be backed up to prevent data loss or transmission failure. It can also be stored regularly on a local storage device (such as an SD card or hard drive).

[0041] Extreme weather alarm: In extreme weather conditions, UPS power supply can also be used to realize functions and transmit data.

[0042] The data transmission unit uses the BeiDou short message system for communication. A BeiDou terminal device is deployed for each platform and land-based base station. The platform-side equipment features a weatherproof design to ensure stable operation even in typhoon conditions. The BeiDou short message system seamlessly integrates with the main system.

[0043] Example 3 This embodiment provides a processing device corresponding to the anchor chain force calculation method for deep-sea floating wind turbines provided in this embodiment 1. The processing device can be a processing device for a client, such as a mobile phone, laptop computer, tablet computer, desktop computer, etc., to execute the method of embodiment 1.

[0044] The processing device includes a processor, a memory, a communication interface, and a bus. The processor, memory, and communication interface are connected via the bus to facilitate communication between them. The memory stores a computer program executable by the processor. When the processor executes the computer program, it executes the anchor chain force estimation method for deep-sea floating wind turbines provided in Example 1.

[0045] Preferably, the memory may be a high-speed random access memory (RAM), and may also include a non-volatile memory, such as at least one disk memory.

[0046] Preferably, the processor may be a central processing unit (CPU), a digital signal processor (DSP), or other general-purpose processors of various types, which are not limited here.

[0047] Example 4 The anchor chain force calculation method for deep-sea floating wind turbines of this embodiment 1 can be specifically implemented as a computer program product. The computer program product may include a computer-readable storage medium carrying computer-readable program instructions for executing the anchor chain force calculation method for deep-sea floating wind turbines described in this embodiment 1.

[0048] Computer readable storage media can be tangible devices that hold and store instructions used by instruction execution devices. Computer readable storage media can be, for example, but not limited to, electronic storage devices, magnetic storage devices, optical storage devices, electromagnetic storage devices, semiconductor storage devices, or any combination thereof.

[0049] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Thus, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code. The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowcharts and / or block diagrams, as well as combinations of processes and / or blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowcharts and / or block diagrams. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks. These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes. These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0050] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents. Any modification or equivalent replacement that does not depart from the spirit and scope of the present invention should be covered by the scope of protection of the claims of the present invention.

Claims

1. A method for calculating anchor chain force for deep-sea floating wind turbines, characterized in that: The following steps are involved: Obtain motion data of the target platform; After processing the acquired motion data, the data is input into the pre-built anchor chain force estimation model to calculate the anchor chain force data at the current time; Generate alarm information based on the current anchor chain force data and preset thresholds to provide multi-level warnings; The platform motion data, anchor chain force data and warning information are transmitted to the remote monitoring system or data center for remote monitoring and analysis.

2. The method for calculating anchor chain force for deep-sea floating wind turbines according to claim 1, characterized in that: The obtaining of motion data of the target platform includes: Deploy observation equipment at preset locations on the target platform; Use observation equipment to measure the motion data of the target platform; Wireless communication technology is used to transmit measurement data to the ground control center or monitoring platform in real time, while performing local backup.

3. The method for calculating anchor chain force for deep-sea floating wind turbines according to claim 2, characterized in that: The observation equipment includes an MRU and a GPS device; the MRU is used to measure the acceleration and angular velocity of the platform; the GPS device is used to provide XYZ coordinates and speed information of the floating platform.

4. The method for calculating anchor chain force for deep-sea floating wind turbines according to claim 3, characterized in that: The obtained motion data is processed and input into a pre-built anchor chain force estimation model to calculate the anchor chain force data at the current time, including: The preset method is used to fuse the measurement data of MRU and GPS to obtain the precise motion status of the platform; The model is calibrated using known environmental parameters and the initial state of the platform to remove the influence of the initial state on the platform motion and ensure the accuracy of the back-calculation results; The platform's motion state data is input into the anchor chain force calculation model to obtain the anchor chain force data at the current time.

5. The method for calculating anchor chain force for deep-sea floating wind turbines according to claim 1, characterized in that: The construction of the anchor chain force calculation model includes: Obtain the basic parameters of the target platform according to the design report of the target platform; According to the design drawing of the target platform, a simulation model of the platform is established in orcaflex; Take several sea conditions and use orcaflex to calculate the corresponding platform motion state and anchor chain force, and establish a platform motion state-anchor chain force database; The training data set is divided based on the data of the platform motion state-anchor chain force database, and the constructed neural network model is trained to obtain the anchor chain force estimation model.

6. The method for calculating anchor chain force for deep-sea floating wind turbines according to claim 1, characterized in that: The method of generating alarm information based on the anchor chain force data at the current time and the preset threshold value and performing multi-level early warning includes: Tension overload warning: Determines whether the anchor chain force exceeds the preset safety threshold. If so, an alarm is immediately triggered to indicate possible equipment damage or platform stability issues. Movement out-of-limit warning: Determines whether the platform's movement exceeds the safety range. If so, a warning is triggered.

7. An anchor chain force estimation system for deep sea floating wind turbines, characterized in that: include: A data measurement unit, used to obtain motion data of the target platform; A calculation unit is used to process the measured motion data and input it into a pre-built anchor chain force calculation model to calculate the anchor chain force data at the current time; The early warning unit is used to generate alarm information based on the current anchor chain force data and preset thresholds, and perform multi-level early warning; The data transmission unit is used to transmit platform motion data, anchor chain force data and warning information to the remote monitoring system or data center for remote monitoring and analysis.

8. The anchor chain force estimation system for deep sea floating wind turbines according to claim 7, characterized in that: The data transmission unit realizes communication through the Beidou short message system respectively arranged on the platform and the land base station.

9. A computer-readable storage medium storing one or more programs, characterized in that: The one or more programs include instructions that, when executed by a computing device, cause the computing device to perform any one of the methods of claims 1 to 6 .

10. A computing device, characterized in that include: One or more processors and a memory, wherein the memory stores one or more programs and is configured to be executed by the one or more processors, wherein the one or more programs include instructions for executing any one of the methods according to claims 1 to 6.

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