Offshore wind turbine generator support structure fault mode characterization method and system
By combining multibeam echo sounding, side-scan sonar, and 3D image sonar, data on the support structure of offshore wind turbines is acquired and fused to identify potential fault modes. This solves the problems of inaccurate identification and high cost in existing technologies, and achieves high-precision fault detection.
Patent Information
- Application Number
- CN202410611534.1
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-05-16
- Publication Date
- 2025-11-18
AI Technical Summary
Existing technologies suffer from problems such as inaccurate identification, high cost, and difficulties in installation and maintenance when identifying failure modes of offshore wind turbine support structures.
A combination of multibeam echo sounder, side-scan sonar, and 3D image sonar is used to acquire seabed topographic data, seabed geomorphological images, and high-resolution sonar images of the supporting structure surface. Potential fault modes are identified through data fusion and anomaly detection.
It improves the accuracy and reliability of fault identification, provides high-precision underwater basic data, and provides strong support for the operation and maintenance management of offshore wind farms.
Smart Images
Figure CN120969064A_ABST
Abstract
Description
TECHNICAL FIELD
[0001] The application belongs to the technical field of support structure failure mode identification, and particularly relates to a support structure failure mode characterization method and system for offshore wind turbines. BACKGROUND
[0002] The support structure of an offshore wind turbine is a key component that ensures the stable operation of the wind turbine, and its failure modes and existing technologies are worth attention. The failure modes of the support structure of an offshore wind turbine may involve various factors, such as material fatigue, corrosion, improper installation, insufficient maintenance, etc., which may lead to structural failure or performance degradation.
[0003] Characterization of the failure modes of the support structure of an offshore wind turbine refers to identifying and describing the types, causes and effects of possible failures of the support structure during operation through a series of technical means. In the prior art, the characterization of the failure modes of the support structure of an offshore wind turbine mainly relies on the following methods:
[0004] Vibration monitoring technology: by monitoring the vibration signals of the support structure, analyzing its frequency, amplitude and other characteristics, to determine whether the structure has abnormalities. This method can timely detect faults such as looseness and cracks in the structure, but is sometimes difficult to accurately identify the type of failure due to environmental noise and signal processing technology limitations.
[0005] Non-destructive testing technology: using ultrasonic, X-ray, magnetic powder and other non-destructive testing methods to detect internal defects of the support structure. This method can directly show the internal damage of the structure, but the detection process may be limited by the shape, size and material of the structure, and the operation is complex and costly.
[0006] Strain monitoring technology: by installing strain sensors at key positions of the support structure, real-time monitoring of the strain changes of the structure to determine the stress state of the structure. This method can reflect the performance changes of the structure under load, but the installation and maintenance of the sensors may be difficult. SUMMARY
[0007] The purpose of the present application is to provide a support structure failure mode characterization method and system for offshore wind turbines to solve the problems of inaccurate identification, high cost, and difficult installation and maintenance.
[0008] To achieve the above-mentioned purpose, the present application adopts the following technical solutions:
[0009] In a first aspect, the present application provides a support structure failure mode characterization method for offshore wind turbines, comprising:
[0010] obtaining seabed topographic data, seabed topographic images, and high-resolution sonar images of the surface of the support structure at the seabed;
[0011] The seabed topography data, seabed geomorphology images, and high-resolution sonar images of the support structure surface are fused;
[0012] Potential failure modes in the support structure are identified by performing anomaly detection on the fused data;
[0013] A failure distribution map and a damage degree map are drawn according to the identified failure modes.
[0014] Optionally, the seabed topography data, seabed geomorphology images, and high-resolution sonar images of the support structure surface at the seabed support structure are acquired:
[0015] The seabed topography data are acquired by using a multi-beam echo sounder to perform high-precision depth sounding on the seabed under the support structure; the seabed geomorphology images are acquired by using a side-scan sonar to scan the seabed around the support structure; and the high-resolution sonar images of the support structure surface are acquired by using an imaging sonar to perform close-range imaging on the support structure.
[0016] Optionally, the seabed topography data, seabed geomorphology images, and high-resolution sonar images of the support structure surface are fused:
[0017] The image data are preprocessed by performing noise removal, contrast enhancement, and histogram equalization steps;
[0018] Different images are aligned by a registration algorithm according to feature points, edges, or region information of the images through a transformation matrix;
[0019] The registered images are decomposed in multiple scales or transformed by wavelets, so that the images are decomposed into sub-images of different frequencies or scales;
[0020] Fusion feature information is extracted from the transformed images, the fusion feature information is fused according to a weighted average method, the fused feature information is converted back to an image space, and a new image is reconstructed.
[0021] Optionally, the fusion feature information extracted from the transformed images includes brightness, contrast, texture, and edges of the images.
[0022] Optionally, different images are aligned by a registration algorithm according to feature points, edges, or region information of the images through a transformation matrix:
[0023] Based on the matched feature points, edges, or region information, a transformation model is selected, the transformation model describes a mapping relationship from a to-be-registered image to a reference image, a global mapping model or a local mapping model is selected according to a geometric distortion condition between the images, the global mapping model performs global parameter estimation by using all control point information, and the local mapping model performs local parameter estimation by using local features of the images;
[0024] Based on the estimated transformation model, a transformation matrix is calculated, and the to-be-registered image is subjected to coordinate transformation using the calculated transformation matrix so as to align with the reference image.
[0025] Optionally, potential failure modes in the support structure are identified through abnormality detection on the fused data.
[0026] Through wide-angle emission and directional reception of acoustic waves by the acoustic wave emission and reception transducer array, a strip-shaped high-density water depth data is formed in the vertical plane perpendicular to the heading, a three-dimensional terrain and topography of the seabed in a strip of a set width along the route is drawn, and according to the seabed terrain change around the underwater fixed structure of the offshore wind turbine support structure, the seabed terrain change under the support structure is analyzed to determine whether the support structure is unstable or damaged due to the terrain change; an echo signal image is obtained by using the acoustic wave reflection principle, the seabed terrain and topography are analyzed according to the echo signal image, the distribution of the seabed fixed structure is determined, the contact between the support structure and the seabed is observed, and an abnormal contact area is identified; the image sonar map is used to observe the damage situation of cracks and corrosion on the surface of the support structure; and the damage degree and failure mode of the support structure are determined in combination with the morphology and distribution characteristics of the damage.
[0027] Optionally, the image sonar emits an acoustic pulse through the sonar head, forms a scanning sector each time, obtains spatial data of 256 measurement points, and realizes 360° range scanning through rotation of the gimbal in the vertical and horizontal directions; the three-dimensional image sonar obtains the time t and echo intensity value of acoustic wave propagation through acoustic wave backscattering, and calculates the distance observation value L according to the time and sound speed value; the gimbal control system obtains the transverse angle observation value and longitudinal angle observation value of each beam in real time by controlling the rotation of the sonar head.
[0028] In a second aspect, the present application provides a support structure failure mode characterization system for offshore wind turbines, comprising:
[0029] A data acquisition module is configured to acquire seabed terrain data, seabed topography images, and high-resolution sonar images of the surface of the support structure.
[0030] A fusion processing module is configured to fuse the seabed terrain data, seabed topography images, and high-resolution sonar images of the surface of the support structure.
[0031] A failure mode identification module is configured to identify potential failure modes in the support structure through abnormality detection on the fused data.
[0032] An output module is configured to draw a failure distribution map and a damage degree map according to the identified failure modes.
[0033] In a third aspect, the present application provides a computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the offshore wind turbine support structure failure mode characterization method when executing the computer program.
[0034] In a fourth aspect, the present application provides a computer-readable storage medium storing a computer program, wherein the processor implements the steps of the offshore wind turbine support structure failure mode characterization method when executing the computer program.
[0035] Compared with the prior art, the present application has the following technical effects:
[0036] The present application is a comprehensive application of the combined multi-beam sounding system, side-scan sonar and three-dimensional image sonar in the scour detection of offshore wind farm underwater fixed structures. The combination of the three can effectively complement each other and obtain more detailed and accurate water depth data and underwater fixed structure images, providing reliable basic data support for the operation and maintenance of offshore wind farms and the establishment of a full life cycle management system.
[0037] The multi-beam sounding system of the present application is a high-precision, high-resolution and high-efficiency underwater topography measurement technology. The system performs wide-angle emission and directional reception of sound waves through the sound wave emission and reception transducer array, forms a strip-shaped high-density water depth data in the vertical plane perpendicular to the heading, and thus can draw the three-dimensional topography and geomorphology of the seabed within a certain width of the strip along the route, and analyze the scour condition of the offshore wind turbine underwater fixed structure according to the seabed topography change around the structure. The side-scan sonar is an active sonar that emits sound waves from the transducer installed in the tow fish (towed type), obtains echo signal images using the sound wave reflection principle, and analyzes the seabed topography and geomorphology and determines the distribution of seabed fixed structures according to the echo signal images.
[0038] The combination of multi-beam sounding technology, side-scan sonar technology and image sonar technology can effectively identify the failure mode of offshore wind turbine support structures. This method combines the advantages of different technologies, improves the accuracy and reliability of failure identification, and provides strong support for the operation and management of wind farms. BRIEF DESCRIPTION OF DRAWINGS
[0039] Figure 1 The flowchart of the present application.
[0040] Figure 2 The system structure diagram of the present application.
[0041] Figure 3 The multi-beam sounding schematic diagram.
[0042] Figure 4Fig. 1 is a schematic diagram of an image sonar coordinate system.
[0043] Figure 5 Fig. 10 is a multi-beam three-dimensional surveying map of a 10# unit.
[0044] Figure 6 Fig. 11 is a multi-beam contour map of a 10# unit.
[0045] Figure 7 Fig. 12 is a three-dimensional sonar surveying map of a submarine cable. DETAILED DESCRIPTION
[0046] The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are some of the embodiments of the present application, rather than all the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative work fall within the scope of protection of the present application.
[0047] In the description of the present application, it should be understood that the terms "comprise" and "include" indicate the presence of described features, integers, steps, operations, elements, and / or components, but do not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and / or sets thereof.
[0048] It should also be understood that the terms used in the specification of the present application are only for the purpose of describing specific embodiments and are not intended to limit the present application. As used in the specification and the appended claims of the present application, the singular forms "a", "an" and "the" are intended to include the plural forms unless the context clearly indicates otherwise.
[0049] It should be further understood that the term "and / or" used in the specification and the appended claims of the present application means any combination of one or more of the associated listed items and all possible combinations thereof, and includes these combinations, for example, A and / or B can represent three cases of A alone, A and B together, and B alone. In addition, the character " / " in the present application generally represents an "or" relationship between the front and rear associated objects.
[0050] It should be understood that although the terms first, second, third, etc. may be used in the embodiments of the present application to describe the preset ranges, etc., these preset ranges should not be limited to these terms. These terms are only used to distinguish the preset ranges from each other. For example, the first preset range can also be referred to as the second preset range, and similarly, the second preset range can also be referred to as the first preset range without departing from the scope of the embodiments of the present application.
[0051] Depending on the context, the word "if" as used herein can be interpreted to mean "when" or "while" or "in response to determining" or "in response to detecting." Similarly, the phrase "if it is determined" or "if [a stated condition or event] is detected" can be interpreted to mean "upon determining" or "in response to determining" or "upon detecting [the stated condition or event]" or "in response to detecting [the stated condition or event]."
[0052] Various structural diagrams according to the embodiments of the present application are shown in the accompanying drawings. These diagrams are not drawn to scale, in which certain details are exaggerated for clarity and others omitted. The shapes and relative sizes of the various regions, layers, and their relative positions are shown for exemplary purposes only and can vary in actual implementation due to manufacturing tolerances or technical limitations, and can be designed differently in actual implementation by those skilled in the art according to actual needs with different shapes, sizes, and relative positions.
[0053] Embodiment 1, please refer to Figure 1 The present application provides a method for characterizing failure modes of offshore wind turbine support structures, comprising:
[0054] S1, obtaining seabed topographic data, seabed geomorphology images, and high-resolution sonar images of the support structure surface at the seabed support structure;
[0055] S2, fusing the seabed topographic data, seabed geomorphology images, and high-resolution sonar images of the support structure surface;
[0056] S3, identifying potential failure modes in the support structure by performing anomaly detection on the fused data;
[0057] S4, drawing a failure distribution map and a damage degree map according to the identified failure modes.
[0058] The use of sonar equipment such as multi-beam sounding system, side scan sonar and three-dimensional image sonar to detect the scouring condition of the underwater fixed structure of offshore wind farm is the main means to evaluate the life cycle of the underwater structure. The multi-beam sounding system can obtain high-precision water depth data and points in the target area, and generate three-dimensional images reflecting the seabed topographic features, but it cannot reflect the detailed features of the seabed. The side scan sonar can obtain high-resolution two-dimensional plane images of the target area, but the position information and water depth data are less accurate. The three-dimensional image sonar system can generate point cloud data of underwater targets, obtain clear images of underwater topography, structures and targets, and obtain the depth of the submarine cable of each offshore wind turbine and offshore booster station through scanning the pile foundation of offshore wind turbines and offshore booster stations. Based on the above three detection technologies, a detection method combining multi-beam sounding system, side scan sonar and three-dimensional image sonar is proposed, which is applied in the detection of scouring and submarine cable depth of underwater fixed structure in a certain offshore wind farm in Jiangsu. The purpose is to understand the changes of scouring and submarine cable depth of underwater fixed structure in offshore wind farm through regular and comprehensive high-precision data collection and analysis, and to provide important basic data support for the construction and improvement of the whole life cycle management system of offshore wind farm.
[0059] Please refer to Figure 3 , the multi-beam sounding system is a high-precision, high-resolution and high-efficiency underwater topographic measurement technology. The system uses sound wave emission and receiving transducer array to emit sound wave in wide angle and receive in direction, forming a strip of high-density water depth data in the vertical plane perpendicular to the heading, so as to draw the three-dimensional topography and geomorphology of the seabed in a certain width of the strip along the route, and analyze the scouring condition of the underwater fixed structure around the offshore wind turbine according to the seabed topographic changes. The SONIC2024 broadband ultrahigh resolution multi-beam sounder of R2SONIC company in the United States is used, with a working frequency of 200-400 kHz, a real-time online selectable frequency, a coverage width of 10°-160° real-time online adjustable, a 0.5°x1° ultranarrow beam, an ultrahigh resolution of 1.25 cm, and a maximum sounding range of 500 m.
[0060] Please refer to Figure 4 , the side scan sonar is an active sonar, which emits sound waves from the transducer installed in the tow fish (towed type), and obtains echo signal images by using sound wave reflection principle. The seabed topography and geomorphology are analyzed to determine the distribution of seabed fixed structure. The EdgeTech4125 side scan sonar system of EdgeTech company in the United States is used, with a low frequency of 100 kHz and a high frequency of 400 kHz, working at the same time, a beam inclination angle of 5°-20° downward, real-time online adjustable, a maximum range of 500 m / 100 kHz on one side, and 150 m / 400 kHz on one side.
[0061] The image sonar belongs to a multi-beam sonar, and can emit 256 beams with a beam angle of 1°*1°. The sonar head forms a scanning sector by emitting a sound pulse each time, and spatial data of 256 measuring points can be obtained. By rotating the gimbal in the vertical direction and the horizontal direction, a 360° range scan can be achieved. There is an overlap between the beams, the angle of the scanning sector is 45°, and the reflection of the central sound wave of each beam is the strongest. The three-dimensional image sonar obtains the time t of sound wave propagation and the echo intensity value through sound wave backscattering, and calculates the distance observation value L according to the time and the sound speed value. The gimbal control system obtains the transverse angle observation value and the longitudinal angle observation value of each beam in real time by controlling the rotation of the sonar head. Generally, the coordinate system of the instrument itself is used, the X-axis is in the horizontal scanning plane, the y-axis is perpendicular to the X-axis in the horizontal scanning plane, and the Z-axis is perpendicular to the horizontal scanning plane.
[0062] In an embodiment, the application provides a method for characterizing the failure mode of a support structure of an offshore wind turbine, comprising the following steps:
[0063] S1, obtaining seabed topographic data, seabed geomorphology images, and high-resolution sonar images of the surface of the support structure at the seabed support structure;
[0064] A multi-beam depth sounder is used to perform high-precision depth sounding on the seabed under the support structure to obtain seabed topographic data. A side scan sonar is used to scan the seabed around the support structure to obtain seabed geomorphology images. An image sonar is used to perform close-range imaging of the support structure to obtain high-resolution sonar images of the surface of the support structure.
[0065] S2, fusing the seabed topographic data, seabed geomorphology images, and high-resolution sonar images of the surface of the support structure:
[0066] The image data is preprocessed by noise removal, contrast enhancement, and histogram equalization steps;
[0067] Different images are aligned through a transformation matrix according to feature points, edges, or region information of the images through a registration algorithm;
[0068] The registered images are decomposed into sub-images of different frequencies or scales through multi-scale decomposition or wavelet transformation;
[0069] In the transformed images, the fusion feature information is extracted, these feature information is fused according to the weighted average method, and the fused feature information is converted back to the image space to reconstruct a new image.
[0070] Different images are aligned through a transformation matrix according to feature points, edges, or region information of the images through a registration algorithm;
[0071] Based on the matching feature points, edges or region information, a transformation model is selected, which describes the mapping relationship from the image to be registered to the reference image, and a global mapping model or a local mapping model is selected according to the geometric distortion between images; the global mapping model uses all control point information for global parameter estimation, and the local mapping model uses local features of the image for local parameter estimation respectively;
[0072] Based on the estimated transformation model, a transformation matrix is calculated, and the calculated transformation matrix is used for coordinate transformation of the image to be registered, so as to align it with the reference image.
[0073] S3, by detecting the fused data, the potential failure mode in the support structure is identified;
[0074] Through the wide-angle emission and directional reception of the acoustic wave by the acoustic wave emission and reception transducer array, a strip-shaped high-density water depth data is formed in the vertical plane perpendicular to the heading, the three-dimensional terrain and topography of the seabed in the strip with a set width along the route are drawn, and the change of the seabed terrain under the support structure is analyzed according to the seabed terrain change around the underwater fixed structure of the offshore wind turbine, so as to determine whether the support structure is unstable or damaged due to the terrain change; the echo signal image is obtained by using the acoustic reflection principle, the seabed terrain and topography are analyzed according to the echo signal image, the distribution of the seabed fixed structure is determined, the contact condition between the support structure and the seabed is observed, and the abnormal contact area is identified; the image sonar map is used to observe the damage condition of the cracks and corrosion on the surface of the support structure; the damage degree and failure mode of the support structure are determined by combining the shape and distribution characteristics of the damage.
[0075] Example 3:
[0076] Taking a 10# unit in a certain offshore wind farm as an example, the application of the scanning system is given, and the multi-beam measurement of the 10# unit is shown in Figure 5 and Figure 6 .
[0077] The second monitoring date of the 10# wind turbine during operation was March 24, 2020. Within a radius of 17m from the center position (including the pile foundation), the local scour pit was relatively developed, and the scour phenomenon was relatively obvious. The seabed elevation range was-18.7m to-12.2m, the average elevation was-16.4m, the maximum scour pit depth around the wind turbine foundation was about 12.33m, and the total amount of scour and deposition was 8999.9 cubic meters; within a radius of 25m from the center position (including the pile foundation), the local scour pit was relatively developed, and the scour phenomenon was relatively obvious. The seabed elevation range was-18.9m to-12.2m, the average elevation was-15.9m, the maximum scour pit depth around the wind turbine foundation was about 12.53m, and the total amount of scour and deposition was 18304.9 cubic meters.
[0078] The scouring phenomenon is mainly local scouring after the pile forming of the fan foundation, and the scouring phenomenon is greatly affected by the overall scouring; within a radius of 17m to 50m of the center of the machine position, the sea bed topography fluctuates greatly, and the elevation changes obviously; the sea bed elevation ranges from -18.9m to -10.5m, and the average elevation is -13.1m; the maximum scouring depth is about 12.53m. The total scouring and silting amount is 46486.2 cubic meters. The scouring form of the topography in the monitoring range is elliptical, and the main erosion direction is southwest-northeast. The scouring depth and the scouring and silting amount calculation reference elevation (using the design mud surface elevation) is -6.37m.
[0079] The change of the scouring characteristics of the sea bed around the pile over time can be seen. From May 2019 to March 2020, the sea bed around the pile had an overall upward trend (from -14.85m to -12.30m), but was still lower than the design sea bed elevation (-6.37m). The deepest part around the pile had a downward trend (from -18.93m to -18.85m). Due to the rapid overall rise of the sea bed, the absolute pit depth within a range of 17m around the pile changed from 6.53m to 6.84m, and had a tendency to intensify. The comparison of the unit scouring conditions is shown in the following table.
[0080]
[0081]
[0082] The three-dimensional sonar scanning of the submarine cable is shown in Figure 7 .
[0083] As can be seen from Figure 7 , the J-shaped pipe horn mouth is 6.42m above the mud surface, the horizontal distance between the mud inlet end of the 10# to 9# submarine cable and the horn mouth is 7.56m, and the horizontal distance between the mud inlet end of the 10# to 11# submarine cable and the horn mouth is 19.05m. The 10# to 9# submarine cable suspension section is in a south-north direction as a whole, and the submarine cable direction is consistent with the direction of the J-shaped pipe horn mouth. The 10# to 11# submarine cable is in a south-north direction as a whole, and the submarine cable direction is consistent with the direction of the J-shaped pipe horn mouth.
[0084] There are problems of damage and disconnection of the bending limiter at the connection end of the 10# to 9# and 10# to 11# submarine cables. Figure 6 The double-frequency sonar scanning diagram of the 10# unit submarine cable connection end is given, from which it can be seen that the 10# to 9# and 10# to 11# submarine cable connection end positions are normal, but there are problems of disconnection of the bending limiter.
[0085] Please refer to Figure 2 , in another embodiment of the present application, a kind of offshore wind turbine support structure fault mode characterization system can be used to realize the offshore wind turbine support structure fault mode characterization method described above, specifically, the system comprises:
[0086] a data acquisition module configured to acquire seabed topography data, seabed topographic images, and high-resolution sonar images of the support structure surface at the seabed support structure;
[0087] a fusion processing module configured to perform fusion processing on the seabed topography data, the seabed topographic images, and the high-resolution sonar images of the support structure surface;
[0088] a fault mode identification module configured to identify potential fault modes in the support structure by performing anomaly detection on the fused data;
[0089] an output module configured to draw a fault distribution map and a damage degree map according to the identified fault modes.
[0090] The division of the modules in the embodiments of the present application is illustrative, and is merely a logical function division. In actual implementation, another division manner can be used. In addition, each function module in each embodiment of the present application can be integrated in one processor, or can be physically separated, or two or more modules can be integrated in one module. The integrated module can be realized in the form of hardware or in the form of a software function module.
[0091] In still another embodiment of the present application, a computer device is provided, which includes a processor and a memory. The memory is configured to store a computer program, and the computer program includes program instructions. The processor is configured to execute the program instructions stored in the computer storage medium. The processor can be a central processing unit (CPU), and can 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 gates or transistor logic devices, discrete hardware components, etc. The processor is the computing core and control core of the terminal, and is suitable for implementing one or more instructions, and is specifically suitable for loading and executing one or more instructions in the computer storage medium to implement a corresponding method flow or a corresponding function. The processor in the embodiments of the present application can be used for the operation of the offshore wind turbine support structure fault mode characterization method.
[0092] In still another embodiment, the present application provides a storage medium, specifically a computer readable storage medium (Memory), which is a memory device in a computer system, for storing programs and data. It should be understood that the computer readable storage medium here can include both built-in storage medium in the computer system, and also can include the extended storage medium supported by the computer system. The computer readable storage medium provides a storage space, which stores an operating system of the terminal. In addition, one or more instructions adapted to be loaded and executed by the processor are also stored in the storage space, and these instructions can be one or more computer programs (including program codes). It should be noted that the computer readable storage medium here can be a high-speed RAM memory, or a non-volatile memory such as at least one disk memory. The one or more instructions stored in the computer readable storage medium can be loaded and executed by the processor to implement the corresponding steps of the offshore wind turbine support structure fault mode characterization method in the above embodiment.
[0093] Those skilled in the art should understand that the embodiments of the present application can be provided as a method, a system, or a computer program product. Therefore, the present application can take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can take the form of a computer program product implemented on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROMs, optical storage devices, etc.) containing computer-usable program code.
[0094] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each flow and / or block in the flowcharts and / or block diagrams, and the combination of flows 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 apparatus to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing apparatus generate a means for implementing the functions specified in the flowcharts and / or block diagrams. Figure 1 one or more flows and / or blocks Figure 1 an apparatus that carries out the functions specified in one or more flows and / or blocks.
[0095] These computer program instructions can also be stored in a computer readable memory that can direct the computer or other programmable data processing apparatus to work in a specific manner, so that the instructions stored in the computer readable memory produce a product including instruction means, which implements the functions specified in the flowcharts and / or block diagrams. Figure 1 one or more flows and / or blocksFigure 1 the function specified in the one or more blocks.
[0096] These computer program instructions can also be loaded into computer or other programmable data processing devices, so that a series of operation steps are performed on the computer or other programmable data processing devices to generate computer-implemented processes, thus the instructions executed on the computer or other programmable data processing devices provide a process for implementing the flow Figure 1 the flow or flows and / or blocks Figure 1 the steps of the function specified in the one or more blocks.
[0097] Finally, it should be noted that: the above examples are only used to illustrate the technical solutions of the present application, but not to limit it, although the above embodiments of the present application have been described in detail, those skilled in the art should understand: the specific embodiments of the present application can be modified or replaced by the same, without departing from the spirit and scope of the present application, any modification or equivalent replacement, which should be covered in the protection scope of the claims of the present application.
Claims
1. A method for characterizing the failure modes of offshore wind turbine support structures, characterized in that, include: Acquire seabed topographic data, seabed geomorphological images, and high-resolution sonar images of the support structure surface at the seabed support structure location; The seabed topography data, seabed geomorphological images, and high-resolution sonar images of the supporting structure surface are fused together. By performing anomaly detection on the fused data, potential failure modes in the support structure can be identified. Based on the identified fault modes, draw fault distribution maps and damage severity maps.
2. The method for characterizing the failure modes of an offshore wind turbine support structure according to claim 1, characterized in that, Acquire seabed topographic data, seabed geomorphological images, and high-resolution sonar images of the support structure surface at the seabed support structure location: A multibeam echo sounder was used to perform high-precision depth sounding on the seabed below the support structure to obtain seabed topographic data; a side-scan sonar was used to scan the seabed around the support structure to obtain seabed topographic images; and an imaging sonar was used to perform close-range imaging of the support structure to obtain high-resolution sonar images of the support structure surface.
3. The method for characterizing the failure modes of an offshore wind turbine support structure according to claim 1, characterized in that, The seabed topography data, seabed geomorphological images, and high-resolution sonar images of the supporting structure surface are fused together. The image data is preprocessed by noise removal, contrast enhancement, and histogram equalization. The registration algorithm aligns different images using a transformation matrix based on the image's feature points, edges, or region information. The registered image is decomposed into sub-images of different frequencies or scales by performing multi-scale decomposition or wavelet transform. In the transformed image, the fusion feature information is extracted, and these feature information is fused according to the weighted average method. The fused feature information is then converted back to the image space to reconstruct a new image.
4. The method for characterizing the failure modes of an offshore wind turbine support structure according to claim 3, characterized in that, The fused feature information, including brightness, contrast, texture, and edges, is extracted from the transformed image.
5. The method for characterizing the failure modes of an offshore wind turbine support structure according to claim 3, characterized in that, Registration algorithms align different images using a transformation matrix based on feature points, edges, or region information. Based on the matched feature points, edges, or region information, a transformation model is selected. This transformation model describes the mapping relationship from the image to be registered to the reference image. Depending on the geometric distortion between the images, a global mapping model or a local mapping model is selected. The global mapping model uses all control point information to estimate global parameters, while the local mapping model uses local features of the image to estimate local parameters. Based on the estimated transformation model, the transformation matrix is calculated, and the calculated transformation matrix is used to perform coordinate transformation on the image to be registered so that it is aligned with the reference image.
6. The method for characterizing the failure modes of an offshore wind turbine support structure according to claim 1, characterized in that, By performing anomaly detection on the fused data, potential failure modes in the supporting structure were identified: Wide-angle acoustic transmission and directional reception are achieved through an array of acoustic transducers, generating high-density water depth data in a vertical plane perpendicular to the course of the wind turbine. This data is used to map the three-dimensional topography and geomorphology of the seabed within a defined width along the route. Furthermore, changes in the seabed topography around the underwater fixed structures of the offshore wind turbine are analyzed to determine if any instability or damage to the support structure is caused by these topographical changes. Echo signal images are acquired using the principle of acoustic reflection, and the distribution of the fixed structures is determined based on these images. The contact between the support structure and the seabed is observed, and abnormal contact areas are identified. Image sonar images are used to observe cracks and corrosion damage on the surface of the support structure. Finally, the degree of damage and failure mode of the support structure are determined by analyzing the morphology and distribution characteristics of the damage.
7. The method for characterizing the failure modes of an offshore wind turbine support structure according to claim 6, characterized in that, Image sonar emits sound pulses from the sonar head, forming a scanning sector with each emission, obtaining spatial data of 256 measurement points. By rotating the pan-tilt unit in the vertical and horizontal directions, a 360° range scan is achieved. The three-dimensional image sonar obtains the sound wave propagation time t and echo intensity value through sound wave backscattering, and calculates the distance observation value L based on the time and sound speed values. The pan-tilt control system obtains the lateral angle observation value and longitudinal angle observation value of each beam in real time by controlling the rotation of the sonar head.
8. A fault mode characterization system for offshore wind turbine support structures, characterized in that, include: The data acquisition module is used to acquire seabed topographic data, seabed geomorphological images, and high-resolution sonar images of the surface of the support structure at the seabed support structure. The fusion processing module is used to fuse seabed topographic data, seabed geomorphological images, and high-resolution sonar images of the supporting structure surface. The fault mode identification module is used to identify potential fault modes in the support structure by performing anomaly detection on the fused data. The output module is used to draw fault distribution maps and damage severity maps based on the identified fault modes.
9. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the method for characterizing the failure modes of an offshore wind turbine support structure as described in any one of claims 1 to 7.
10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the steps of the method for characterizing the failure modes of an offshore wind turbine support structure as described in any one of claims 1 to 7.