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WO2025223627A1 - Automatisation de réparation d'un composant d'éolienne - Google Patents

Automatisation de réparation d'un composant d'éolienne

Info

Publication number
WO2025223627A1
WO2025223627A1 PCT/DK2025/050046 DK2025050046W WO2025223627A1 WO 2025223627 A1 WO2025223627 A1 WO 2025223627A1 DK 2025050046 W DK2025050046 W DK 2025050046W WO 2025223627 A1 WO2025223627 A1 WO 2025223627A1
Authority
WO
WIPO (PCT)
Prior art keywords
repair
wind turbine
anomaly
turbine component
output
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
PCT/DK2025/050046
Other languages
English (en)
Inventor
Arran WOOD
Christian Lindgaard Munk LAURSEN
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Vestas Wind Systems AS
Original Assignee
Vestas Wind Systems AS
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Vestas Wind Systems AS filed Critical Vestas Wind Systems AS
Publication of WO2025223627A1 publication Critical patent/WO2025223627A1/fr
Pending legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Classifications

    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B29—WORKING OF PLASTICS; WORKING OF SUBSTANCES IN A PLASTIC STATE IN GENERAL
    • B29C—SHAPING OR JOINING OF PLASTICS; SHAPING OF MATERIAL IN A PLASTIC STATE, NOT OTHERWISE PROVIDED FOR; AFTER-TREATMENT OF THE SHAPED PRODUCTS, e.g. REPAIRING
    • B29C73/00—Repairing of articles made from plastics or substances in a plastic state, e.g. of articles shaped or produced by using techniques covered by this subclass or subclass B29D
    • B29C73/24—Apparatus or accessories not otherwise provided for
    • B29C73/26—Apparatus or accessories not otherwise provided for for mechanical pretreatment
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F03—MACHINES OR ENGINES FOR LIQUIDS; WIND, SPRING, OR WEIGHT MOTORS; PRODUCING MECHANICAL POWER OR A REACTIVE PROPULSIVE THRUST, NOT OTHERWISE PROVIDED FOR
    • F03D—WIND MOTORS
    • F03D17/00—Monitoring or testing of wind motors, e.g. diagnostics
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F03—MACHINES OR ENGINES FOR LIQUIDS; WIND, SPRING, OR WEIGHT MOTORS; PRODUCING MECHANICAL POWER OR A REACTIVE PROPULSIVE THRUST, NOT OTHERWISE PROVIDED FOR
    • F03D—WIND MOTORS
    • F03D80/00—Details, components or accessories not provided for in groups F03D1/00 - F03D17/00
    • F03D80/50—Maintenance or repair
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F30/00—Computer-aided design [CAD]
    • G06F30/20—Design optimisation, verification or simulation
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B29—WORKING OF PLASTICS; WORKING OF SUBSTANCES IN A PLASTIC STATE IN GENERAL
    • B29L—INDEXING SCHEME ASSOCIATED WITH SUBCLASS B29C, RELATING TO PARTICULAR ARTICLES
    • B29L2031/00—Other particular articles
    • B29L2031/08—Blades for rotors, stators, fans, turbines or the like, e.g. screw propellers
    • B29L2031/082—Blades, e.g. for helicopters
    • B29L2031/085—Wind turbine blades

Definitions

  • the present invention relates to the field of wind turbine components, especially wind turbine blades. Especially, the invention provides a method and a system for wind turbine component repair which allows for an automated or semi-automated repair process.
  • wind turbine blades for MW wind turbines are composite fibre blades made of multiple layers of fibre mats or plies manufactured in a complex process involving many activities for applying the fibre mats and resin on a mould to form the final blade. Anomalies such as wrinkles, voids with lack of resin filling and other errors are known in the process of layup of the fibre mats and resin application. Further, in case of minor damages of a blade, e.g. during transport or handling, there is a need to repair such blades with the purpose of restoring their original mechanical strength to ensure safe function when installed in a wind turbine.
  • the blades Due to the large size of the blades, e.g. with a length of more than 50 m, or more than 100 m, it is a complex task for an operator to detect an anomaly, to decide how to repair the anomaly, and to finally perform the repair including removing material around the anomaly and replacing the removed material with new material.
  • the repair task is complicated since it is expected that the wind turbine blade after a repair can comply with the intended mechanical properties of a healthy wind turbine blade to ensure safe operation of a wind turbine after installation of a repaired blade. Therefore, a repair of a complex anomaly or damage of a blade extending down several layers to a significant depth of the blade cannot be reliably performed from a simple manual visual inspection of the anomaly or damage. Still further, a repair of a large wind turbine blade is time consuming, and it is a further requirement that the repair time can be reduced.
  • the invention provides a method for repairing an anomaly on a wind turbine component, such as a wind turbine blade or a component for a wind turbine blade, wherein the wind turbine component comprises a layered structure with a plurality of layers of fibre material,
  • repair zone is defined by lateral dimensions and a depth of material, such as a distance from a surface of the wind turbine component or a number of layers, to be removed from the wind turbine component, and
  • a repair output comprising at least an output indicative of the repair zone and an output indicative of properties of one or more fibre materials to be used in a repair to be performed on the wind turbine component based on data in the Computer Aided-Design model.
  • Such method has been found to be a highly efficient tool to ensure a rapid and still safe repair of wind turbine blades, also large blades, either in a blade manufacturing setup where an anomaly may be detected during or immediately after manufacturing, or in a special blade repair setup, e.g. in a workshop setup for repair of damaged wind turbine blades.
  • the anomaly can be such as a wrinkle in a fibre mat layer at a certain depth, a void or space between fibre mat layers with lack of resin filling, or in principle any damage on a part of the wind turbine blade.
  • the linking to the CAD model allows intended mechanical properties of the wind turbine component to be restored after a repair has been performed. Based on the CAD model, it can be ensured that sufficient material is removed and that the correct materials are used in the layup for repair after material has been removed.
  • the invention is based on the insight that the repair process can benefit from a link to a digital representation of a wind turbine blade which exists in a CAD program including all structural details about the blade, such as types and positions of all fibre mats of all layers in the blade structure.
  • the CAD model can be used e.g. in determining a list of materials (Bill of Materials), e.g. which types and dimensions of fibre mats, are required to be provided for the repair, and the CAD model may further be used to generate a repair output which causes robots to automatically provide and cut fibre mats in dimension required for the repair work. It may further be preferred to determine how much material to remove around the anomaly based on the CAD program, so as to allow for the repair to result in restored mechanical properties of the blade.
  • materials Bill of Materials
  • the CAD model can be used e.g. in determining a list of materials (Bill of Materials), e.g. which types and dimensions of fibre mats, are required to be provided for the repair, and the CAD model may further be used to generate a repair output which causes robots to automatically provide and cut fibre mats in dimension required for the repair work. It may further be preferred to determine how much material to remove around the anomaly based on the CAD program, so as to allow for the repair to result in restored mechanical properties
  • the method can be used for providing a fully automated repair using robots both for removing of material and for application of new material or in a semiautomatic setting where some steps are performed manually while other steps are performed by means of robots.
  • robots with a grinding tool may be used for removing of material while application of new material is at least partly a manual process.
  • the repair output may comprise an output to allow control of a laser light projector or other visual position indicator to directly indicate the repair zone on the blade, or to do so via Virtual Reality means, or to do so on a display with a visual indication of the blade. In this way, a rapid manual material removal process is facilitated.
  • the repair process involves removing of material in a repair zone around the detected anomaly and down to a certain depth, e.g. a process comprising grinding manually or by means of a robot with a griding or milling tool.
  • Detection of anomalies can be performed in various ways, e.g. manual visual detection by an operator, or by means of a measurement or analysis tool, e.g. involving a camera and image processing and/or ultrasonic equipment or the like. It has been found that it is possible to position cameras at an elevated position relative to the manufacturing area, so that they do not interfere with the manufacturing operations and still capture images with enough details to allow for example detection of wrinkles in the layup process. The images can be analysed to provide an automatic detection of anomalies in the ongoing manufacturing or on a damaged blade positioned in a workshop for repair. In other implementations, the operator may use a mobile device to take a photo of an anomaly along with a position indication which is then sent to a computer system which links the anomaly position to the CAD model.
  • the Determination of the repair zone on the wind turbine component based on the Computer Aided-Design model may involve use of the mapped position and/or extension of the detected anomaly together with Computer Aided-Design model.
  • the position and/or depth of the anomaly may be used to determine lateral dimensions of the repair zone for different repair layers (fibre materials to be used in a repair).
  • a repair output for a manual, semiautomatic or fully automatic repair operation in response to a detected anomaly.
  • the same means as mentioned for assisting manual removing of material can be provided for application of new material to rebuild the layers of the blade, i.e. visual means to guide an operator to correctly orient and position new fibre mats.
  • the guiding preferably includes information to guide the operator to ensure that the correct type of fibre mats are used and that their fibre oriented correctly.
  • a computer with access to the CAD model of the blade is connected to an automated anomaly detecting means, to a controllable material removing robot, and to a controllable robot serving to layup new fibre mats determined by the computer, based on the CAD model of the blade.
  • the CAD model may be used to provide a list (Bill of Material) of materials to be provided and to control robot systems to transport the materials, and e.g. prepare fibre mats in the intended dimensions, so that the repairing robot can access the materials when needed in the repair process.
  • the method may comprise the step of entering the position of the anomaly to the computer system with access to a predetermined Computer Aided-Design model of the wind turbine component, such as by means of an automated, semiautomated or manual entering procedure.
  • the method comprises determining the position of the anomaly with respect to a reference point on the wind turbine component, e.g. a visual mark or another identifiable mark on a known location of the wind turbine component. In this way, it is possible to refer the position of the anomaly to coordinates in the CAD model of the wind turbine component and thereby determine the absolute position of the anomaly.
  • a reference point on the wind turbine component e.g. a visual mark or another identifiable mark on a known location of the wind turbine component.
  • the method comprises determining a geometric extension of the anomaly comprising at least a depth, such as a distance from a surface of the wind turbine component or a number of layers of fibre material.
  • a geometric extension of the anomaly comprising at least a depth, such as a distance from a surface of the wind turbine component or a number of layers of fibre material.
  • this may include a span-wise coordinate, a chord-wise coordinate and a depth coordinate or another 3D coordinate representation of the position of the anomaly that can be mapped to the CAD model of the wind turbine component.
  • the position of the anomaly may be determined by means of a camera or a laser tracker or an ultrasonic probe system, or a combination of two or more of the mentioned means, configured to transmit data accordingly to the computer system computer system with access to the Computer Aided-Design model.
  • Other ways of determining the position may be manual visual inspection and entering position data to the computer system, e.g. via a mobile device.
  • the repair output comprises information about fibre mats to be used in the repair, based on the CAD model.
  • said information preferably comprises information about each fibre mat to be used in the repair, wherein the information about each fibre mat comprises one or more of: lateral dimensions, fibre type or material, fibre orientation, and areal weight, based on the CAD model.
  • the repair output may comprise a complete Bill of Materials to be used for the repair. Such information can be used to provide a rapid process of providing the correct materials, e.g. types or fibre mats with the correct dimensions and with the correct orientation of fibres etc. for the repair.
  • the method may comprise applying the information about fibre mats to be used in the repair to an automated manufacturing process for manufacturing fibre mats to be used for the repair.
  • the method comprises generating a repair output serving to guide a person in performing a manual repair in the repair zone.
  • a repair output serving to guide a person in performing a manual repair in the repair zone.
  • this may be in the form of written, spoken instructions guiding the person through the steps to be followed to perform the repair, so as to ensure the correct fibre mats and the correct fibre orientations are used for each layer of the repair.
  • the method comprises generating a control output for controlling a robot to remove material in the repair zone.
  • a robot may comprise a manipulator with a grinding or milling tool to remove material, e.g. involving a scanner or a camera to guide the control of the robot to remove the material of the repair zone. In this way, a time-consuming manual work with removing material can be avoided.
  • the method comprises generating an output for visualizing the repair zone. Especially, this may comprise generating an output to a laser light projector for controlling the laser light projector to visualize the repair zone on the surface of the wind turbine component. Especially, the method may comprise visualizing the repair zone to guide a person in performing a manual removing of material in the repair zone. Especially, the repair output may comprise an output serving to visualize the repair zone to guide a person in performing the repair by manual layup of fibre mats.
  • the repair output may comprise an output to a mobile device with information serving to guide a person in performing the repair, however the repair output may additionally or alternatively comprise a control output for controlling a robot to perform at least a part of the repair, such as to perform the complete repair.
  • the robot may be configured to operate a material removal machine, such as a grinding machine, wherein controlling the robot comprises controlling the robot to remove material until material has been removed down to a certain depth.
  • a material removal machine such as a grinding machine
  • controlling the robot comprises controlling the robot to remove material until material has been removed down to a certain depth.
  • the robot may be configured with an accurate linear digital scale configured to measure how deep a grinding machine, which is handled by the robot, works its way down in the layered structure. When a certain depth is reached the grinding process is stopped.
  • the desired depth may be fixed, set manually or obtained based on the position of the of the anomaly.
  • the anomaly may especially be one of: a wrinkle in a fiber layup of the layered structure, an aeration or a dry spot in one or more layers of the layered structure.
  • the anomaly may in principle be any error or imperfection caused by a damage or caused by an error in the manufacturing process of the wind turbine component.
  • the wind turbine component is preferably a composite wind turbine blade or a component for a composite wind turbine blade.
  • the invention is advantageous for saving time in repair of large wind turbine blades, since part of the complete repair process can be automated or at least partly automated.
  • the process or grinding in a composite material causes dust of resin and fibre particles which requires personal protection gear, air suction etc. This can be reduced in an automated material removing process.
  • the method comprises performing steps of an iterative feedback loop involving a plurality of loops of: removing material, providing an image or scan of the area where material has been removed, checking if the anomaly has been removed based on the image or scan, and deciding accordingly whether to stop removing material or to continue to remove material.
  • the iterative feedback loop may involve manually removing material, automatically providing an image or scan, automatically checking if the anomaly has been removed based on the image or scan, and automatically deciding accordingly whether to send information to stop removing material or to send information to continue removing material. In this way, a person performing the material removing, e.g. grinding, can be guided during the process.
  • the iterative feedback loop may involve automatically generating a control output for controlling a machine to iteratively remove material, such as a grinding machine, until it is automatically decided that the anomaly is removed based on processing the images or scans by means of a detection algorithm.
  • a fully automated iterative feedback loop can be provided which allows a fully automated repair process.
  • the iterative feedback loop may comprise processing said plurality of images or scans according to a machine learning or Artificial Intelligence algorithm. In this way, the machine learning or Al algorithm can learn over time to decide about whether to continue removing material or to stop the material removing process based on incoming images or scans.
  • the iterative feedback loop involves automatically generating a control output for controlling a machine to iteratively remove material until material has been removed down to a certain depth based on processing the images or scans by means of a detection algorithm.
  • the feedback loop may internally check the obtained depth measured by the linear scale as described above so that the material removal process is continued until the desired depth has been obtained.
  • any one of the mentioned iterative feedback loop embodiments may involve mapping the image or scan to the CAD model and in this way it is possible to finally determine the repair output.
  • said image or scan may be provided by a laser tracker, a 2D or 3D camera, or a probe or the like.
  • the mapping of the image or scan to the CAD model may provide a method for determining the the repair zone, e.g. for determining the lateral dimensions and/or the depth of material, to be removed from the wind turbine component.
  • layers of fibre material may be removed in a stepwise manner, e.g. layer by layer, until the images or scan shows that the anomaly is no longer visible.
  • the lateral dimensions and/or the depth of material is determined according to the iterative feedback loop so that the lateral dimensions and/or the depth of material to be removed from the wind turbine component is determined iteratively dependent on the result of each step of removing material.
  • the repair zone may be predetermined based on results of nondestructive test methods such as ultrasonic or x-ray imaging or the repair zone may be determined based on results of an iterative material removal process.
  • the method may comprise an initial step of identifying the anomaly, e.g. by visual inspection by a person, or by means of a camera or scanning system serving to automatically identify an anomaly of the wind turbine component.
  • the layered structure of the wind turbine component may be formed by layers, e.g. mats or plies, made of glass or carbon fibres or made of a mix of glass and carbon fibres, or a mix of other types of fibres.
  • the invention provides a repair system arranged for repairing an anomaly on a wind turbine component, wherein the wind turbine component comprises a layered structure with a plurality of layers of fibre material, the system comprising a computer system programmed to:
  • a repair output comprising at least an output indicative of the repair zone and an output indicative of properties of one or more fibre materials to be used in a repair to be performed on the wind turbine component based on data in the Computer Aided-Design model.
  • the computer system comprises a user interface comprising a display, such as a display on a portable device such as a tablet or a smart phone or a smart watch, and wherein an anomaly type and a localization on the wind turbine blade part of a detected anomaly is communicated by a symbolic and/or text overlay on a captured photo of the wind turbine blade part.
  • the display may include a large display visible by the operator from many positions.
  • the user interface comprises a projection system, such as a 3D laser projector, arranged to provide a visual indication of a detected anomaly on the determined location directly on a surface of the wind turbine blade part.
  • a projection system such as a 3D laser projector
  • This type of anomaly indication can be a fast way of indicating an anomaly on a large object.
  • FIG. 1 illustrates a block diagram of a system embodiment
  • FIG. 2 illustrates a block diagram of another system embodiment
  • FIG. 3 illustrates steps of a method embodiment.
  • the figures illustrate specific ways of implementing the present invention and are not to be construed as being limiting to other possible embodiments falling within the scope of the attached claim set.
  • FIG. 1 illustrates a sketch of a part of a wind turbine blade BL made of multiple layers of fibre mats in a composite structure comprising resin.
  • the blade BL has an anomaly or an error in the form of a wrinkle in the fibre mat layout.
  • the anomaly may be visually detected by an operator or it may be automatically detected by means of a camera CM placed at an elevated position above the blade BL.
  • the detection can also be based on utilizing a laser tracker, by utilizing a calibrated laser setup, which is used for laser projection in the layup process.
  • a position P_XYZ of the anomaly may be provided as input to a computer with a processor system PS executing a control algorithm C_A and which has access to a software based Computer Aided Design model CDM of the blade BL, i.e. a full digital representation of structural details of all components of the blade, especially for each layer information about position of all fibre mats, their dimensions, fibre types and fibre orientation.
  • a processor system PS executing a control algorithm C_A and which has access to a software based Computer Aided Design model CDM of the blade BL, i.e. a full digital representation of structural details of all components of the blade, especially for each layer information about position of all fibre mats, their dimensions, fibre types and fibre orientation.
  • CDM Computer Aided Design model
  • the depth of the anomaly may be determined by means of an ultrasonic scanner automatically or manually operated.
  • an X-ray scanner may provide data for the depth of the anomaly.
  • it may also be determined by a 3D camera CM or entered to the computer system after manual inspection.
  • the depth may be represented directly a distance from the surface of the blade, or as the number of layers involved in the anomaly, counted from the surface layer.
  • the above-mentioned systems for determining the depth of the anomaly may also provide lateral dimensions of the anomaly, e.g. dimensions of the anomaly extending in spanwise and chordwise directions or other suitable coordinates.
  • the geometric extension of the anomaly comprising depth and/or lateral dimensions of the anomaly may be determined by such material scanning systems.
  • a point cloud scanner operated by a robot for probing the blade BL and thereby detect the anomaly as well as its position P_XYZ.
  • the point cloud representation of the blade BL can then be correlated with the CAD model CDM.
  • a laser scanner can be used to determine the anomaly position P_XYZ.
  • the blade BL may have a visual or otherwise readable mark M which indicates the identity of the blade BL to thereby access the relevant CAD model CDM.
  • the mark M may serve as a position reference point on the blade BL, so that the position P_XYZ of the anomaly can be determined relative to the blade BL and CAD model CDM.
  • the position P_XYZ of the anomaly can be determined by means of suitable image processing.
  • the anomaly position P_XYZ preferably involves an indication of a 3D space, i.e. a space in X, Y and Z coordinates, indicating the full extension of the anomaly.
  • the control algorithm C_A processes the position P_XYZ data and maps the coordinates of the anomaly on the CAD model CDM. Based on the data in the CAD model CDM for the position P_XYZ and extension of the anomaly, the control algorithm C_A can determine a repair zone RZ defined by lateral dimensions and a depth where material should be removed from the blade BL in order to ensure that the intended mechanical properties of the blade BL can be restored after a repair has been performed.
  • a repair zone RZ defined by lateral dimensions and a depth where material should be removed from the blade BL in order to ensure that the intended mechanical properties of the blade BL can be restored after a repair has been performed.
  • the CDM model preferably contains a specification database as input to the C_A for calculating the repair zone, based on the layup present in the CDM.
  • the specification would be nominal overlap dimensions, dependent on each fibre layer content and fibre direction.
  • a repair output RPO is generated from the computer system.
  • the repair output RPO comprises a representation of the repair zone RZ, i.e. the material to be removed, so as to allow manual or automated removing of the material in the repair zone RZ.
  • the repair output RPO comprises an output indicative of properties of one or more fibre materials to be used in the repair to be performed on the blade BL, based on data in the Computer Aided-Design model CDM. This can be in the form of a data file, information on a display to a user, or in the form of a control signal to allow automated manufacturing and/or retrieval of the materials to be used for the repair.
  • FIG. 2 illustrates a block diagram of another system embodiment, with a more specific example of how a repair output from the computer system can be used.
  • the computer system has a processor system PS running a control algorithm C_A and with access to the CAD model CDM with all relevant data of the wind turbine component, e.g. the blade BL of FIG. 1.
  • the anomaly position P_XYZ is entered as input.
  • the computer system In response to the anomaly position input P_XYZ, the computer system generates a repair output in the form of a control signal for controlling a material removing robot MR_RT, e.g. a 6-DOF arm, with a milling or grinding tool which is controlled to remove all material in the repair zone.
  • a material removing robot MR_RT e.g. a 6-DOF arm
  • a milling or grinding tool which is controlled to remove all material in the repair zone.
  • the computer system generates a complete bill of material B_O_M with a specification of all materials necessary for the repair, based on the data in the CAD model CDM.
  • the output B_O_M allows information of an operator to provide the necessary materials, and/or providing the output B_O_M as a control signal to an automated manufacturing process for manufacturing fibre mats MF_FM according to the material list B_O_M. This may e.g. involve controlling a cutting table to cut fibre mats in the dimensions required.
  • the computer system generates a control signal to control a laser projector LSP which generates visible light on the wind turbine component surface which indicates the position of the fibre mat to be laid up in the repair zone, so as to guide an operator to geometrically correctly lay up the fibre mats.
  • a display e.g. on a mobile device, may guide the operator to select the fibre mat.
  • a camera can be used to monitor the repair process and thus serve as feedback to the computer system in the guiding process.
  • FIG. 3 illustrates steps of an embodiment of the method for repairing an anomaly on a wind turbine blade which is formed by a layered structure with a plurality of layers of fibre mats or plies.
  • First step is determining D_PS a position of an anomaly on the blade with respect to span-wise and chord-wise coordinates, as well as with respect to depth, or the position may involve determining a 3D indication of the extension of the anomaly, e.g. wrinkles or voids or spaces with insufficient resin filling.
  • Next step is entering E_PS of the position of the anomaly to a computer system with access to a predetermined CAD model of the blade.
  • the CAD model contains data representing properties of elements of each of the layers of fibre material and the position of the elements relative to the blade.
  • the elements preferably comprises plies or mats of glass or carbon fibre material and core material such a balsa woold or foam material.
  • mapping M_CAD the position of the anomaly to the CAD model, thus identifying in the extension of the anomaly in the CAD model, thereby allowing e.g. identification of which fibre mats are involved in the anomaly.
  • determining D_RZ a repair zone on the wind turbine component in response to the CAD model namely the repair zone comprising an indication of lateral dimensions and a depth of a space where material is to be removed from the blade.
  • the lateral dimensions may be determined so that they depend on the depth or the layer number of material to be removed. For example, the lateral dimensions may decrease stepwise in direction of the depth to ensure that the repair layers or repair elements (fibre materials to be used in a repair) will extend beyond edges of lower repair layers.
  • the link to the CAD model is important, since for example different materials and layup directions can lead to varying overlaps per direction. This can be resolved based on the content of the CAD model.
  • G_RPO a repair output with an output indicating the repair zone, e.g. controlling a laser projector to visually indicate the repair zone to facilitate manual removing of material.
  • a complete Bill of Material can be output to facilitate and speed up the task of providing the required materials, e.g. correctly dimensioned fibre mats etc. to allow the repair.
  • the computer system may control an automated manufacturing facility to at least partly prepare the correct fibre mats in the correct dimensions for the repair.
  • the invention provides a method and a system for repairing an anomaly on a wind turbine component, such as blade, built of a structure with a plurality of layers of fibre material.
  • determining (D_PS) a position or a full 3D extension of an anomaly on the component
  • E_PS the position or 3D extension of the anomaly
  • mapping (M_CAD) the position or 3D extension of the anomaly to the CAD model to determine (D_RZ) a repair zone on the component based on the CAD model.
  • the repair zone is defined by lateral dimensions and a depth of material to be removed, e.g. by milling or grinding, from the component to allow intended mechanical properties of the wind turbine component to be restored after a repair has been performed.
  • G_RPO a repair output with an output indicative of the repair zone, e.g. a visual indication by means of a laser projector, and an output indicative of properties of one or more fibre materials to be used in the repair, e.g. involving a complete Bill of Materials to be used, based on data in the CAD model.

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  • Computer Hardware Design (AREA)

Abstract

L'invention concerne un procédé et un système de réparation d'une anomalie sur un composant d'éolienne, tel qu'une pale, constitué d'une structure avec une pluralité de couches de matériau fibreux. Tout d'abord, la détermination (D_PS) d'une position ou d'une extension 3D complète d'une anomalie sur le composant, ensuite l'entrée (E_PS) de la position ou de l'extension 3D de l'anomalie dans un système informatique avec accès à un modèle CAO prédéterminé du composant avec des données représentant des propriétés d'éléments de chacune des couches du matériau fibreux et la position des éléments par rapport au composant. Ensuite, le mappage (M_CAD) de la position ou de l'extension 3D de l'anomalie au modèle de CAO pour déterminer (D_RZ) une zone de réparation sur le composant sur la base du modèle de CAO. La zone de réparation est définie par des dimensions latérales et une profondeur de matériau à retirer, par exemple par fraisage ou meulage, à partir du composant pour permettre à des propriétés mécaniques prévues du composant d'éolienne d'être restaurées après qu'une réparation a été effectuée. Enfin, la génération (G_RPO) d'une sortie de réparation avec une sortie indiquant la zone de réparation, par exemple une indication visuelle au moyen d'un projecteur laser, et d'une sortie indiquant les propriétés d'un ou de plusieurs matériaux fibreux à utiliser dans la réparation, par exemple impliquant une liste détaillée de matériaux à utiliser, sur la base de données dans le modèle CAO. Une telle liaison d'une anomalie au modèle CAO du composant permet un procédé de réparation plus rapide impliquant des étapes automatisées ou semi-automatisées.
PCT/DK2025/050046 2024-04-23 2025-04-09 Automatisation de réparation d'un composant d'éolienne Pending WO2025223627A1 (fr)

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DKPA202430192 2024-04-23
DKPA202430192 2024-04-23

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WO2025223627A1 true WO2025223627A1 (fr) 2025-10-30

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Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US11280319B2 (en) * 2018-04-05 2022-03-22 Siemens Gamesa Renewable Energy A/S Method for on-site repairing of a wind turbine component
US20220134691A1 (en) * 2020-10-30 2022-05-05 The Boeing Company Systems and Methods for Actualizing Simulated Scarfs and Patches for Repair of Composite Laminates
EP4261408A1 (fr) * 2022-04-12 2023-10-18 Siemens Gamesa Renewable Energy A/S Procédé de support technique d'un processus d'inspection manuelle d'un composant d'éolienne
US11865647B2 (en) * 2020-03-13 2024-01-09 The Boeing Company Utilization of CNC machining in composite part rework

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US11280319B2 (en) * 2018-04-05 2022-03-22 Siemens Gamesa Renewable Energy A/S Method for on-site repairing of a wind turbine component
US11865647B2 (en) * 2020-03-13 2024-01-09 The Boeing Company Utilization of CNC machining in composite part rework
US20220134691A1 (en) * 2020-10-30 2022-05-05 The Boeing Company Systems and Methods for Actualizing Simulated Scarfs and Patches for Repair of Composite Laminates
EP4261408A1 (fr) * 2022-04-12 2023-10-18 Siemens Gamesa Renewable Energy A/S Procédé de support technique d'un processus d'inspection manuelle d'un composant d'éolienne

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