System, method and apparatus for scour monitoring and early warning identification of offshore wind power foundation

Abstract

Disclosed in the present application are a system, method and apparatus for scour monitoring and early warning identification of an offshore wind power foundation. In a data processing and training module, feature matching and a preset recurrent neural network algorithm are used to train a collected preset scour early warning level data set and a collected historical scour measurement data set, so as to obtain a target recurrent neural network model; and when a scour disaster has occurred, in a monitoring and early warning identification module, the target recurrent neural network model can be directly used to monitor and identify a current scour situation and obtain a scour early warning level. Therefore, by implementing the present application, an influence mechanism of a horizontal cyclic load of a pile body on pile foundation scour is taken into full consideration, so that a scour situation of an offshore wind turbine foundation can be known in a more timely, accurate and reliable manner; and different scour levels can be quickly, accurately and reliably identified, and losses caused by scour can be effectively prevented on the basis of identification results, thereby providing technical support for the operation safety and maintenance of a wind turbine.

Description

Offshore wind power foundation scour monitoring and early warning identification system, method and device Technical Field

[0001] The present application relates to the technical field of offshore wind power intelligent monitoring, and specifically to an offshore wind power foundation scour monitoring and early warning identification system, method and device. Background Art

[0002] With the increasing application of single pile foundations for offshore wind turbines, the scouring of soil around single pile foundations has received increasing attention and research. To date, relevant research on scouring of single pile foundations has failed to fully consider the impact of pile-soil interaction on the scouring of soil around single pile foundations of offshore wind turbines under wave-current coupling and horizontal cyclic loads, and has been unable to conduct real-time online monitoring of scouring conditions and intelligent fault warning.

[0003] Summary of the Invention

[0004] In view of this, the embodiments of the present application provide a system, method and device for monitoring and early warning identification of offshore wind power foundation scour to solve the technical problem in the existing technology that it is impossible to perform real-time online monitoring of offshore wind power foundation scour and intelligent fault early warning.

[0005] The technical solutions proposed in this application are as follows:

[0006] In a first aspect, an embodiment of the present application provides an offshore wind power foundation scour monitoring and early warning identification system, which includes: a data acquisition module for obtaining a preset scour warning level data set and a historical scour measurement data set corresponding to the offshore wind power foundation, and sending the preset scour warning level data set and the historical scour measurement data set to a data processing and training module; the data processing and training module for establishing a target recurrent neural network model based on the preset scour warning level data set and the historical scour measurement data set through feature matching and a preset recurrent neural network algorithm, and sending the target recurrent neural network model to a monitoring and early warning identification module; the monitoring and early warning identification module for monitoring and identifying the scour conditions corresponding to the offshore wind power foundation based on the target recurrent neural network model when a scour disaster occurs, and obtaining a scour warning level.

[0007] In combination with the first aspect, in a possible implementation of the first aspect, based on the preset scour warning level dataset and the historical scour measurement dataset, a target recurrent neural network model is established through feature matching and a preset recurrent neural network algorithm, including: based on the historical scour measurement data, at least one scour measurement average value is obtained through a preset calculation method; based on each of the scour measurement average values ​​and the preset scour warning level dataset, a correspondence between each of the scour measurement average values ​​and each scour warning level in the preset scour warning level dataset is obtained through feature matching; based on the correspondence and the historical scour measurement dataset, the target recurrent neural network model is established through a preset recurrent neural network algorithm.

[0008] In combination with the first aspect, in another possible implementation of the first aspect, the data acquisition module is also used to obtain at least one scour measurement data sent by each scour sensor in the target monitoring area when a scour disaster occurs, and each of the scour sensors is pre-buried in the severely scoured soil layer around the offshore wind power foundation in the target monitoring area.

[0009] In combination with the first aspect, in another possible implementation of the first aspect, when a scour disaster occurs, the scour measurement data sent by each scour sensor in the target monitoring area is obtained, including: when a scour disaster occurs, each of the scour sensors in the target area uses an end-to-end wireless transmission sensor signal model to send each of the scour measurement data to the data acquisition module.

[0010] In combination with the first aspect, in another possible implementation of the first aspect, the monitoring and early warning identification module includes: a first monitoring and early warning identification submodule, including a data processing submodule, for receiving each of the scour measurement data sent by the data acquisition module, and processing each of the scour measurement data based on a preset processing method to obtain at least one target scour measurement data, and sending each of the target scour measurement data to a second monitoring and early warning identification submodule; the second monitoring and early warning identification submodule is used to obtain the scour warning level based on each of the target scour measurement data through identification by the target recurrent neural network model.

[0011] In combination with the first aspect, in another possible implementation of the first aspect, the data acquisition module is also used to obtain the wave parameter set and water flow velocity data information set sent by the scour sensor in the target monitoring area when a scour disaster occurs, and determine the evolution relationship between the water flow velocity and wave characteristics in the target monitoring area based on the wave parameter set and the water flow velocity data information set.

[0012] In a second aspect, an embodiment of the present application provides a method for monitoring and early warning identification of offshore wind power foundation scour, which is used in the offshore wind power foundation scour monitoring and early warning identification system as described in the first aspect of the embodiment of the present application. The offshore wind power foundation scour monitoring and early warning identification method includes: when a scour disaster occurs, based on each scour sensor in the target monitoring area, at least one scour measurement data is obtained through an end-to-end wireless transmission sensor signal model, and each of the scour sensors is pre-buried in the severely scoured soil layer around the offshore wind power foundation in the target monitoring area; based on each of the scour measurement data, at least one target scour measurement data is obtained through a preset processing method; based on each of the target scour measurement data, a scour warning level is obtained through target recurrent neural network model identification, and the target recurrent neural network model is obtained by training a preset scour warning level data set and a historical scour measurement data set corresponding to the offshore wind power foundation using feature matching and a preset recurrent neural network algorithm.

[0013] In a third aspect, an embodiment of the present application provides an offshore wind power foundation scour monitoring and early warning identification device, which is used in the offshore wind power foundation scour monitoring and early warning identification system as described in the first aspect of the embodiment of the present application. The offshore wind power foundation scour monitoring and early warning identification device includes: an acquisition module, which is used to obtain at least one scour measurement data based on each scour sensor in the target monitoring area when a scour disaster occurs, through an end-to-end wireless transmission sensor signal model, and each of the scour sensors is pre-buried in the severely scoured soil layer around the offshore wind power foundation in the target monitoring area; a processing module, which is used to obtain at least one target scour measurement data based on each of the scour measurement data through a preset processing method; and an early warning identification module, which is used to obtain a scour warning level based on each of the target scour measurement data through a target recurrent neural network model identification, and the target recurrent neural network model is obtained by training a preset scour warning level data set and a historical scour measurement data set corresponding to the offshore wind power foundation using feature matching and a preset recurrent neural network algorithm.

[0014] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores computer instructions, and the computer instructions are used to enable the computer to execute the offshore wind power foundation scour monitoring and early warning identification method as described in the second aspect of the embodiment of the present application.

[0015] In a fifth aspect, an embodiment of the present application provides an electronic device, comprising: a memory and a processor, wherein the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the computer instructions to execute the offshore wind power foundation scour monitoring and early warning identification method as described in the second aspect of the embodiment of the present application.

[0016] The technical solution provided by this application has the following effects:

[0017] The offshore wind power foundation scour monitoring and early warning identification system provided in the embodiment of the present application obtains a preset scour early warning level data set and a historical scour measurement data set corresponding to the offshore wind power foundation in the data acquisition module; uses feature matching and a preset recurrent neural network algorithm to train the preset scour early warning level data set and the historical scour measurement data set in the data processing and training module to obtain a target recurrent neural network model; when a scour disaster occurs, the target recurrent neural network model can be directly used in the monitoring and early warning identification module to monitor and identify the current scour situation and obtain the scour early warning level. Therefore, by implementing this application, the influence mechanism of the pile body's horizontal cyclic load on pile foundation scour is fully considered, and the scour situation of the offshore wind turbine foundation can be understood more timely, accurately and reliably; different scour levels can be quickly, accurately and reliably identified, and according to the identification results, the losses caused by scour can be effectively prevented, providing technical support for wind turbine operation safety and maintenance.

[0018] The offshore wind turbine foundation scour monitoring and early warning identification method provided in the embodiment of the present application uses the offshore wind turbine foundation scour monitoring and early warning identification system described in the embodiment of the present application for identification, which can understand the scour situation of the offshore wind turbine foundation in a more timely, accurate and reliable manner, further scientifically optimize the existing offshore wind turbine single pile foundation scour and protection design method, effectively reduce the development and maintenance costs of offshore wind turbine foundations, and improve the safety of offshore wind turbine foundations. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the specific implementation methods of the present application or the technical solutions in the prior art, the following is a brief introduction to the drawings required for use in the specific implementation methods or the description of the prior art. Obviously, the drawings described below are some implementation methods of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0020] FIG1 is a structural block diagram of an offshore wind power foundation scour monitoring and early warning identification system provided according to an embodiment of the present application;

[0021] FIG2 is a schematic diagram of scouring of a single pile foundation under horizontal cyclic load according to an embodiment of the present application;

[0022] FIG3 is a schematic diagram of a wind power foundation scour sensor provided according to an embodiment of the present application;

[0023] FIG4 is a schematic diagram of the structure of an intelligent monitoring and early warning management platform for offshore wind power scour provided according to an embodiment of the present application;

[0024] FIG5 is a flowchart of the intelligent monitoring and early warning system for the flushing process according to an embodiment of the present application;

[0025] FIG6 is a schematic diagram illustrating the principle of a wind turbine foundation scour intelligence and monitoring system according to an embodiment of the present application;

[0026] FIG7 is a flow chart of a method for monitoring and early warning identification of offshore wind power foundation scour according to an embodiment of the present application;

[0027] FIG8 is a general flow chart of an intelligent early warning identification algorithm for monitoring scour of offshore wind power foundations according to an embodiment of the present application;

[0028] FIG9 is a structural block diagram of an offshore wind power foundation scour monitoring and early warning identification device provided according to an embodiment of the present application;

[0029] FIG10 is a schematic diagram of the structure of a computer-readable storage medium provided according to an embodiment of the present application;

[0030] FIG11 is a schematic structural diagram of an electronic device provided according to an embodiment of the present application. DETAILED DESCRIPTION

[0031] To make the purpose, technical solutions, and advantages of the embodiments of the present application more clear, the technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without making creative efforts shall fall within the scope of protection of this application.

[0032] It should be noted that the terms "first", "second", etc. 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 sequential order. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in a sequence other than those illustrated or described herein. In addition, the terms "including" and "having" and any of their variations 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.

[0033] An embodiment of the present application provides an offshore wind power foundation scour monitoring and early warning identification system. As shown in FIG1 , the offshore wind power foundation scour monitoring and early warning identification system 1 includes: a data acquisition module 11 , a data processing and training module 12 , and a monitoring and early warning identification module 13 .

[0034] The data processing and training module 12 is connected to the data acquisition module 11 and the monitoring and early warning identification module 13 respectively.

[0035] It should be understood that the system may also include other devices and equipment.

[0036] The monitoring and early warning identification module 13 includes a first monitoring and early warning identification submodule 131 and a second monitoring and early warning identification submodule 132 ; the first monitoring and early warning identification submodule 131 includes a data processing submodule 1311 .

[0037] The first monitoring and early warning identification submodule 131 is a real-time monitoring module; the second monitoring and early warning identification submodule 132 is a wireless remote monitoring module.

[0038] Furthermore, the function of each device in the above system is described.

[0039] Specifically, the data acquisition module 11 is used to obtain a preset scour warning level dataset and a historical scour measurement dataset corresponding to the offshore wind power foundation, and the preset scour warning level dataset and the historical scour measurement dataset are sent to the data processing and training module 12 .

[0040] After the data processing and training module 14 receives the preset scour warning level data set and the historical scour measurement data set, it first calculates at least one scour measurement average value based on the historical scour measurement data set; secondly, based on each scour measurement average value, the corresponding scour warning level is determined in the preset scour warning level data set, that is, the correspondence between each scour measurement average value and each scour warning level can be obtained; finally, based on the correspondence and the historical scour measurement data set, after training with a preset recurrent neural network algorithm (RNN neural network algorithm), the target recurrent neural network model can be obtained, and the target recurrent neural network model is sent to the monitoring and warning identification module 13.

[0041] Specifically, a good algorithm model, namely the target recurrent neural network model, is determined by continuously training the algorithm model and finding the optimal parameters in different sensor signal modeling stages.

[0042] When a scour disaster occurs, the monitoring and early warning identification module 13 can directly use the received target recurrent neural network model to monitor and identify the scour situation corresponding to the offshore wind power foundation to obtain a scour early warning level.

[0043] First, when a scour disaster occurs, the data acquisition module 11 obtains at least one scour measurement data sent by each scour sensor in the target monitoring area, uses the data processing sub-module 1311 to process each scour measurement data to obtain at least one target scour measurement data, and sends each target scour measurement data to the second monitoring and early warning identification sub-module 131.

[0044] Among them, the scour sensors are pre-buried in the soil layer with severe scour around the offshore wind power foundation in the target monitoring area. The scour sensors at different depths of the soil layer correspond to different scour warning levels, as shown in Figure 2.

[0045] When a scouring disaster occurs, the scouring sensors located at different depths of the soil layer will be washed out by the water flow and transmit the measurement data related to the scouring process to the data acquisition module 11, as shown in FIG3 .

[0046] Among them, the flushing sensor transmits data through an end-to-end wireless transmission sensor signal model. Through this end-to-end wireless transmission sensor signal model, the goal of increasing the distance between feature classes and reducing the distance within classes can be achieved. It can quickly prepare the discriminability of a reliable recognition model, and has a small number of parameters, making it more suitable for deployment on embedded hardware.

[0047] Secondly, after receiving the target scour measurement data, the second monitoring and warning identification submodule 132 inputs the target scour measurement data into the target recurrent neural network model (RNN model) for warning identification, and can obtain the corresponding scour warning level.

[0048] Optionally, the data acquisition module 11 is also used to obtain the wave parameter set and water flow velocity data information set sent by the scour sensor in the target monitoring area when a scour disaster occurs, and determine the evolution relationship between the water flow velocity and wave characteristics in the target monitoring area based on the wave parameter set and water flow velocity data information set. Optionally, a corresponding evolution process diagram can be formed based on the evolution relationship, and synchronous observation of the scour process and water flow characteristics can be achieved based on the evolution process diagram.

[0049] The offshore wind power foundation scour monitoring and early warning identification system provided in the embodiment of the present application obtains a preset scour early warning level data set and a historical scour measurement data set corresponding to the offshore wind power foundation in the data acquisition module; uses feature matching and a preset recurrent neural network algorithm to train the preset scour early warning level data set and the historical scour measurement data set in the data processing and training module to obtain a target recurrent neural network model; when a scour disaster occurs, the target recurrent neural network model can be directly used in the monitoring and early warning identification module to monitor and identify the current scour situation and obtain the scour early warning level. Therefore, by implementing this application, the influence mechanism of the pile body's horizontal cyclic load on pile foundation scour is fully considered, and the scour situation of the offshore wind turbine foundation can be understood more timely, accurately and reliably; different scour levels can be quickly, accurately and reliably identified, and according to the identification results, the losses caused by scour can be effectively prevented, providing technical support for wind turbine operation safety and maintenance.

[0050] In one example, a remote intelligent monitoring and fault warning system for scour on offshore wind turbine foundations is provided. The system includes a scour sensor module for measuring scour depth, wave current, and water velocity; a base station real-time monitoring module for receiving, filtering, and processing scour sensor feedback data; a wireless remote monitoring module for monitoring the hydraulic scour process and issuing warnings, and an intelligent warning recognition model. Schematic diagrams of the specific implementation principle are shown in Figures 4 and 5.

[0051] Specifically, scour sensors are pre-buried in the soil layers around pile foundations, which are prone to scour. When a scour disaster occurs, scour sensors located at different depths in the soil layer are dislodged by the water flow and transmit measurement data related to the scour process. The base station's real-time monitoring module filters and processes this data before transmitting it to the remote monitoring center. After the intelligent warning recognition algorithm identifies the signals transmitted by different sensors, different scour warning levels are generated, as shown in Figure 6.

[0052] In another example, a wind turbine foundation scour monitoring and early warning system is provided. Its hardware includes a Beidou GPS ATGM336H, an E32-TTL-100 wireless serial port, and an STC15F2K single-chip microcomputer. It also includes the SS-DTU68G signal receiver required for the base station's real-time monitoring module. The software is compiled in Python, and the compiled code program displays data such as sensor number, latitude and longitude, date, and water flow velocity. This accurately and concisely displays the required data on the client, achieving real-time monitoring.

[0053] The present embodiment provides a method for monitoring and early warning identification of offshore wind power foundation scour, which is used in the offshore wind power foundation scour monitoring and early warning identification system 1 described in the embodiment of the present application. As shown in FIG7 , the method includes the following steps:

[0054] Step 201: When a scour disaster occurs, at least one scour measurement data is obtained based on each scour sensor in the target monitoring area through an end-to-end wireless transmission sensor signal model.

[0055] Each of the scour sensors is pre-buried in a soil layer with severe scour around the offshore wind power foundation in the target monitoring area.

[0056] The specific implementation process refers to the functional description and definition of the data acquisition module 11 in the offshore wind power foundation scour monitoring and early warning identification system 1 in the above embodiment, which will not be repeated here.

[0057] Step 202: Based on each of the scour measurement data, at least one target scour measurement data is obtained through a preset processing method.

[0058] The specific implementation process refers to the description of the connection relationship between the data acquisition module 11 and the monitoring and early warning identification module 13 in the offshore wind power foundation scour monitoring and early warning identification system 1 in the above embodiment, as well as the functional description of the first monitoring and early warning identification submodule 131 in the monitoring and early warning identification module 13, which will not be repeated here.

[0059] Step 203: Based on each target scour measurement data, the scour warning level is obtained through target recurrent neural network model identification.

[0060] The target recurrent neural network model is trained using feature matching and a preset recurrent neural network algorithm on a preset scour warning level dataset and a historical scour measurement dataset corresponding to the offshore wind turbine foundation. The specific training process is described in the functional description of the data processing and training module 12 in the offshore wind turbine foundation scour monitoring and warning identification system 1 in the above embodiment and will not be repeated here.

[0061] The specific early warning identification process refers to the connection relationship description and function description of the first monitoring and early warning identification submodule 131 and the second monitoring and early warning identification submodule 132 in the offshore wind power foundation scour monitoring and early warning identification system 1 in the above embodiment, and will not be repeated here.

[0062] The offshore wind turbine foundation scour monitoring and early warning identification method provided in the embodiment of the present application uses the offshore wind turbine foundation scour monitoring and early warning identification system described in the embodiment of the present application for identification, which can understand the scour situation of the offshore wind turbine foundation in a more timely, accurate and reliable manner, further scientifically optimize the existing offshore wind turbine single pile foundation scour and protection design method, effectively reduce the development and maintenance costs of offshore wind turbine foundations, and improve the safety of offshore wind turbine foundations.

[0063] In one example, a general flow chart of an intelligent early warning identification algorithm for offshore wind power foundation scour monitoring is provided, as shown in FIG8 .

[0064] In another example, a method for rapid identification of offshore wind power foundation scour monitoring and early warning is provided, which is characterized by comprising the following steps:

[0065] S1: Setting a plurality of scour sensor collection points, wherein the sensor collection points are used to collect sensor scour information under the action of wave and current loads, and the sensor information includes the magnitude of the sensor transmission signal;

[0066] S2: The average value of information transmitted by multiple sensors is x, and the warning level corresponding to x is y;

[0067] S3: Perform sample statistics: Take N samples, one of which has a scour warning level y n Corresponding to the average value x of the information transmitted by a sensor n , where n represents a non-zero natural number;

[0068] S4: Use the information collection and processing module to collect sensor information,

[0069] And denoise the N sample sensor information to obtain N groups of qualified sensor information;

[0070] S5: Send N groups of gridded sensor information to the RNN neural network model for training;

[0071] S6: Obtain the corresponding relationship between the average value x of the emission information of M sensors and the scour warning level y;

[0072] S7: Determine the scour warning level based on the corresponding relationship.

[0073] The present application also provides an offshore wind power foundation scour monitoring and early warning identification device, which is used in the offshore wind power foundation scour monitoring and early warning identification system 1 described in the present application embodiment. As shown in FIG9 , the device includes:

[0074] The acquisition module 301 is used to obtain at least one scour measurement data based on each scour sensor in the target monitoring area through an end-to-end wireless transmission sensor signal model when a scour disaster occurs. Each of the scour sensors is pre-buried in the soil layer with severe scour around the offshore wind power foundation in the target monitoring area; for details, please refer to the relevant description of step 201 in the above method embodiment.

[0075] The processing module 302 is configured to obtain at least one target scour measurement data based on each scour measurement data through a preset processing method; for details, please refer to the description of step 202 in the above method embodiment.

[0076] The warning identification module 303 is used to obtain the scour warning level based on each of the target scour measurement data through target recurrent neural network model identification. The target recurrent neural network model is obtained by training the preset scour warning level data set and the historical scour measurement data set corresponding to the offshore wind power foundation using feature matching and a preset recurrent neural network algorithm; for details, please refer to the relevant description of step 203 in the above method embodiment.

[0077] The offshore wind turbine foundation scour monitoring and early warning identification device provided in the embodiment of the present application uses the offshore wind turbine foundation scour monitoring and early warning identification system described in the embodiment of the present application for identification, which can understand the scour situation of the offshore wind turbine foundation in a more timely, accurate and reliable manner, further scientifically optimize the existing offshore wind turbine single pile foundation scour and protection design method, effectively reduce the development and maintenance costs of offshore wind turbine foundations, and improve the safety of offshore wind turbine foundations.

[0078] For a detailed description of the functions of the offshore wind power foundation scour monitoring and early warning identification device provided in the embodiments of the present application, please refer to the description of the offshore wind power foundation scour monitoring and early warning identification method in the above embodiments.

[0079] The present application also provides a storage medium, as shown in FIG10 , on which a computer program 401 is stored. When the instructions are executed by a processor, the computer program 401 implements the steps of the offshore wind power foundation scour monitoring and early warning identification method in the above embodiment. The storage medium may be a magnetic disk, an optical disk, a read-only memory (ROM), a random access memory (RAM), a flash memory, a hard disk drive (HDD), or a solid-state drive (SSD); the storage medium may also include a combination of the above types of memory.

[0080] Those skilled in the art will appreciate that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the relevant hardware through a computer program. The program can be stored in a computer-readable storage medium. When the program is executed, it can include the processes of the embodiments of the above-mentioned methods. The storage medium can be a magnetic disk, an optical disk, a read-only memory (ROM), a random access memory (RAM), a flash memory, a hard disk drive (HDD), or a solid-state drive (SSD). The storage medium can also include a combination of the above-mentioned types of memory.

[0081] An embodiment of the present application also provides an electronic device, as shown in FIG11 , which may include a processor 51 and a memory 52 , wherein the processor 51 and the memory 52 may be connected via a bus or other means, with FIG11 taking the bus connection as an example.

[0082] The processor 51 may be a central processing unit (CPU). The processor 51 may also be other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, or a combination of the above chips.

[0083] Memory 52, as a non-transitory computer-readable storage medium, can be used to store non-transitory software programs, non-transitory computer executable programs, and modules, such as the corresponding program instructions / modules in the embodiments of the present application. Processor 51 executes the non-transitory software programs, instructions, and modules stored in memory 52 to perform various processor functions and data processing, thereby implementing the offshore wind turbine foundation scour monitoring and early warning identification method in the above-mentioned method embodiment.

[0084] The memory 52 may include a program storage area and a data storage area, wherein the program storage area may store applications required for operating the device and at least one function; the data storage area may store data created by the processor 51, etc. In addition, the memory 52 may include a high-speed random access memory, and may also include a non-volatile memory, such as at least one disk storage device, a flash memory device, or other non-volatile solid-state storage device. In some embodiments, the memory 52 may optionally include a memory remotely located relative to the processor 51, and these remote memories may be connected to the processor 51 via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0085] The one or more modules are stored in the memory 52 , and when executed by the processor 51 , perform the offshore wind power foundation scour monitoring and early warning identification method in the embodiments shown in FIG. 7-8 .

[0086] The specific details of the above electronic device can be understood by referring to the corresponding descriptions and effects in the embodiments shown in Figures 7 to 8, and will not be repeated here.

[0087] Although the embodiments of the present application have been described with reference to the accompanying drawings, those skilled in the art may make various modifications and variations without departing from the spirit and scope of the present application, and such modifications and variations shall fall within the scope defined by the appended claims.

Claims

1. An offshore wind power foundation scour monitoring and early warning identification system, characterized in that: The system comprises: A data acquisition module, used to obtain a preset scour warning level data set and a historical scour measurement data set corresponding to the offshore wind power foundation, and send the preset scour warning level data set and the historical scour measurement data set to a data processing and training module; The data processing and training module is used to establish a target recurrent neural network model based on the preset scour warning level data set and the historical scour measurement data set through feature matching and a preset recurrent neural network algorithm, and send the target recurrent neural network model to the monitoring and warning identification module; The monitoring and early warning identification module is used to monitor and identify the scour conditions corresponding to the offshore wind power foundation based on the target recurrent neural network model when a scour disaster occurs, and obtain a scour early warning level.

2. The system according to claim 1, characterized in that Based on the preset scour warning level data set and the historical scour measurement data set, a target recurrent neural network model is established through feature matching and a preset recurrent neural network algorithm, including: Based on the historical scour measurement data, at least one scour measurement average value is obtained through a preset calculation method; Based on each of the scour measurement average values ​​and the preset scour warning level data set, a corresponding relationship between each of the scour measurement average values ​​and each scour warning level in the preset scour warning level data set is obtained through feature matching; Based on the corresponding relationship and the historical scour measurement data set, the target recurrent neural network model is established through a preset recurrent neural network algorithm.

3. The system according to claim 1, characterized in that The data acquisition module is also used to obtain at least one scour measurement data sent by each scour sensor in the target monitoring area when a scour disaster occurs, and each scour sensor is pre-buried in the soil layer with severe scour around the offshore wind power foundation in the target monitoring area.

4. The system according to claim 3, characterized in that When a scour disaster occurs, obtain the scour measurement data sent by each scour sensor in the target monitoring area, including: When a scour disaster occurs, each scour sensor in the target area sends each scour measurement data to the data acquisition module using an end-to-end wireless transmission sensor signal model.

5. The system according to claim 4, characterized in that The monitoring and early warning identification module includes: The first monitoring and early warning identification submodule includes a data processing submodule, which is used to receive each of the scour measurement data sent by the data acquisition module, and process each of the scour measurement data based on a preset processing method to obtain at least one target scour measurement data, and send each of the target scour measurement data to the second monitoring and early warning identification submodule; The second monitoring and early warning identification submodule is used to obtain the scour warning level based on each target scour measurement data through identification by the target recurrent neural network model.

6. The system according to claim 1, characterized in that The data acquisition module is also used to obtain the wave parameter set and water flow velocity data information set sent by the scour sensor in the target monitoring area when a scour disaster occurs, and determine the evolution relationship between the water flow velocity and wave characteristics in the target monitoring area based on the wave parameter set and the water flow velocity data information set.

7. A method for monitoring and early warning identification of offshore wind power foundation scour, used in the offshore wind power foundation scour monitoring and early warning identification system as claimed in any one of claims 1 to 6; characterized in that: The method comprises: When a scour disaster occurs, at least one scour measurement data is obtained based on each scour sensor in the target monitoring area through an end-to-end wireless transmission sensor signal model, and each of the scour sensors is pre-buried in a soil layer with severe scour around the offshore wind power foundation in the target monitoring area; Based on each of the scour measurement data, at least one target scour measurement data is obtained through a preset processing method; Based on each of the target scour measurement data, the scour warning level is obtained through identification by a target recurrent neural network model, and the target recurrent neural network model is obtained by training a preset scour warning level data set and a historical scour measurement data set corresponding to the offshore wind power foundation using feature matching and a preset recurrent neural network algorithm.

8. An offshore wind power foundation scour monitoring and early warning identification device, used in the offshore wind power foundation scour monitoring and early warning identification system as claimed in any one of claims 1 to 6; characterized in that: The device comprises: The acquisition module is used to obtain at least one scour measurement data based on each scour sensor in the target monitoring area through an end-to-end wireless transmission sensor signal model when a scour disaster occurs. The scour sensors are pre-buried in the soil layer with severe scour around the offshore wind power foundation in the target monitoring area; A processing module, configured to obtain at least one target scour measurement data based on each of the scour measurement data by a preset processing method; The warning identification module is used to obtain the scour warning level based on each of the target scour measurement data through target recurrent neural network model identification. The target recurrent neural network model is obtained by training a preset scour warning level data set and a historical scour measurement data set corresponding to the offshore wind power foundation using feature matching and a preset recurrent neural network algorithm.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable the computer to execute the offshore wind power foundation scour monitoring and early warning identification method as described in claim 7.

10. An electronic device, characterized in that: include: A memory and a processor, wherein the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the offshore wind power foundation scour monitoring and early warning identification method as described in claim 7 by executing the computer instructions.

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