Wind turbine blade cutting trajectory optimization method, device and system

Abstract

The present invention provides a method, device, and system for optimizing the cutting trajectory of a wind turbine blade. The method comprises: obtaining a first contour model and a second contour model of the blade to be cut; calculating a first cutting trajectory of a cutting device in a device coordinate system based on the first contour model and the second contour model; and determining a second cutting trajectory of the cutting device on the blade to be cut based on the first cutting trajectory and density grayscale information corresponding to the first cutting trajectory. The method, device, and system for optimizing the cutting trajectory of a wind turbine blade provided by the present invention are based on fusing the first contour model in the blade coordinate system and the second contour model in the device coordinate system into the same framework, performing path optimization using the determined first cutting trajectory and density grayscale information fed back by a first scanning device, and obtaining a second cutting trajectory for the automated cutting device. The method can plan and optimize corresponding cutting trajectories based on different wind turbine blades, thereby improving cutting efficiency and accuracy.

Description

Technical Field

[0001] The present invention relates to the technical field of wind turbine blade recycling and processing, and in particular to a method, device and system for optimizing the cutting trajectory of a wind turbine blade. Background Art

[0002] With the rapid development of the wind power industry, the number of wind turbine blades forced to be scrapped after reaching their service life has also increased. Wind turbine blades are primarily made of materials such as glass fiber or carbon fiber, epoxy resin, and balsa wood. However, blade materials vary, with different parts using different materials. The difficulty of cutting different materials and their ultimate use also vary.

[0003] Currently, the disposal options for scrapped blades include physical crushing, physical and chemical methods, and incineration. Due to the large size of blades, it is inconvenient to transport them during processing, so they generally need to be broken down into small pieces before proceeding to the next step of processing.

[0004] However, existing blade cutting methods typically involve manually hammering the blade, using the principle of "sound detection" (different densities and structures produce different sounds) to identify weaker locations, or subjectively judging weaker locations based on experience, before marking and sawing. This method relies too much on manual cutting trajectories, resulting in inefficient cutting operations and prone to misjudgment of strength at the junction of different materials, leading to lower cutting accuracy. Summary of the Invention

[0005] The present invention provides a method, device and system for optimizing the cutting trajectory of a wind turbine blade, which are used to solve the defects of the prior art of relying on manual setting of the cutting trajectory, resulting in relatively low cutting efficiency and cutting accuracy.

[0006] The present invention provides a method for optimizing the cutting trajectory of a wind turbine blade, comprising:

[0007] Acquire a first contour model and a second contour model of the blade to be cut;

[0008] Calculating a first cutting trajectory of a cutting device in a device coordinate system based on the first contour model and the second contour model;

[0009] determining a second cutting trajectory of the cutting device on the blade to be cut based on the first cutting trajectory and density grayscale information corresponding to the first cutting trajectory;

[0010] In which, the density grayscale information is obtained by scanning the blade to be cut along the first cutting trajectory using a first scanning device; the first contour model includes the point cloud information of the blade to be cut in the blade coordinate system; the second contour model includes the point cloud information of the blade to be cut in the cutting device coordinate system.

[0011] According to a cutting trajectory optimization method for a wind turbine blade provided by the present invention, the method determines a second cutting trajectory of the cutting device on the blade to be cut based on the first cutting trajectory and the density grayscale information corresponding to the first cutting trajectory, including: for each path point in the first cutting trajectory, performing: determining a set of junction points corresponding to the path point in the blade to be cut based on the density grayscale information of the path point; if the path point is in the corresponding set of junction points, using the path point as a target path point; if the path point is not in the corresponding set of junction points, selecting a coordinate point with the smallest distance to the path point from the corresponding set of junction points as the target path point;

[0012] Based on the target path point, the second cutting trajectory is generated.

[0013] According to a method for optimizing a cutting trajectory of a wind turbine blade provided by the present invention, calculating a first cutting trajectory of a cutting device in a device coordinate system based on the first contour model and the second contour model includes:

[0014] Performing feature point matching on the first contour model and the second contour model to determine a cutting starting point;

[0015] The first cutting trajectory is calculated based on the cutting starting point and cutting parameters.

[0016] According to a cutting trajectory optimization method for a wind turbine blade provided by the present invention, before obtaining the first contour model and the second contour model of the blade to be cut, the method further includes:

[0017] Get blade identification information;

[0018] Using the blade identification information, matching the first contour model corresponding to the blade identification information from a blade model library;

[0019] The blade model library is pre-built based on design drawings of various wind turbine blades.

[0020] According to a cutting trajectory optimization method for wind turbine blades provided by the present invention, after obtaining the cutting trajectory of the cutting device on the blade to be cut, the method further includes: controlling the cutting device to cut the blade to be cut according to the second cutting trajectory.

[0021] According to a cutting trajectory optimization method for wind turbine blades provided by the present invention, the cutting parameters include: at least one of: product size data after cutting, material distribution characteristic data, minimum sawing length and yield rate.

[0022] The present invention also provides a cutting trajectory optimization device for wind turbine blades, comprising:

[0023] A contour acquisition module, used to acquire a first contour model and a second contour model of the blade to be cut;

[0024] an initial trajectory acquisition module, configured to calculate a first cutting trajectory of the cutting device in a device coordinate system based on the first contour model and the second contour model;

[0025] a trajectory optimization module, configured to determine a second cutting trajectory of the cutting device on the blade to be cut based on the first cutting trajectory and density grayscale information corresponding to the first cutting trajectory;

[0026] In which, the density grayscale information is obtained by scanning the blade to be cut along the first cutting trajectory using a first scanning device; the first contour model includes the point cloud information of the blade to be cut in the blade coordinate system; the second contour model includes the point cloud information of the blade to be cut in the cutting device coordinate system.

[0027] The present invention also provides a cutting trajectory optimization system for wind turbine blades, comprising a first scanning device, a second scanning device, and a cutting device, and further comprising: the cutting trajectory optimization device for wind turbine blades as described above;

[0028] The second scanning device is used to scan the blade to be cut to obtain a second contour model.

[0029] The present invention also provides an electronic device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the cutting trajectory optimization method for a wind turbine blade as described above is implemented.

[0030] The present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the cutting trajectory optimization method for a wind turbine blade as described above is implemented.

[0031] The wind turbine blade cutting trajectory optimization method, device, and system provided by the present invention integrate a first contour model in the blade coordinate system and a second contour model in the equipment coordinate system into a single framework. The system then optimizes the path using the determined first cutting trajectory and density grayscale information fed back by a first scanning device to obtain a second cutting trajectory for the automated cutting equipment. This system can plan and optimize cutting trajectories for different wind turbine blades, improving cutting efficiency and precision, thereby enhancing the adaptability of the automated cutting equipment and reducing its cost. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] In order to more clearly illustrate the technical solutions in the present invention or the prior art, a brief introduction is given below to the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0033] Figure 1 It is a schematic flow chart of the cutting trajectory optimization method of wind turbine blades provided by the present invention;

[0034] Figure 2 It is a structural schematic diagram of the cutting trajectory optimization device for wind turbine blades provided by the present invention;

[0035] Figure 3 It is a structural schematic diagram of the cutting trajectory optimization system for wind turbine blades provided by the present invention;

[0036] Figure 4 It is a structural schematic diagram of the electronic device provided by the present invention. DETAILED DESCRIPTION

[0037] To make the objectives, technical solutions, and advantages of the present invention more clear, the technical solutions of the present invention will be clearly and completely described below in conjunction with the accompanying drawings. Obviously, the embodiments described are only some of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts shall fall within the scope of protection of the present invention.

[0038] The terms "first," "second," and the like in this application are used to distinguish similar objects, and are not used to describe a particular order or precedence. It should be understood that the terms used in this manner are interchangeable where appropriate, so that the embodiments of this application can be implemented in orders other than those illustrated or described herein. Furthermore, the objects distinguished by "first," "second," and the like generally refer to a class of objects and do not limit the number of objects. For example, the first object may be one or more.

[0039] It should be understood that the terms used in this specification are only for the purpose of describing specific embodiments and are not intended to limit the present invention. As used in the present invention, unless the context clearly indicates otherwise, the singular forms "a", "an" and "the" are intended to include the plural forms.

[0040] The terms “include” and “comprising” indicate the presence of described features, integers, steps, operations, elements and / or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or groups thereof.

[0041] Figure 1 FIG. 1 is a flow chart of the method for optimizing the cutting trajectory of wind turbine blades provided by the present invention. Figure 1 As shown, the cutting trajectory optimization method for wind turbine blades provided by the embodiment of the present invention includes: step 101, obtaining a first contour model and a second contour model of the blade to be cut.

[0042] The first contour model includes point cloud information of the blade to be cut in the blade coordinate system; the second contour model includes point cloud information of the blade to be cut in the device coordinate system.

[0043] It should be noted that the execution subject of the cutting trajectory optimization method for wind turbine blades provided by the embodiment of the present invention is the electronic device on which the cutting trajectory optimization device for wind turbine blades relies for operation.

[0044] The above-mentioned electronic devices can be implemented in various forms, for example: the electronic devices described in the embodiments of the present application may include mobile terminals such as mobile phones, smart phones, laptops, digital broadcast receivers, PDAs (personal digital assistants), PADs (tablet computers), PMPs (portable multimedia players), navigation devices, smart bracelets, smart watches, digital cameras, etc., as well as fixed terminals such as digital TVs, desktop computers, etc. Below, it is assumed that the electronic device is a mobile terminal. However, it will be understood by those skilled in the art that, in addition to components specifically for mobile purposes, the construction according to the embodiments of the present application can also be applied to fixed-type terminals.

[0045] The application scenario of the cutting trajectory optimization method for wind turbine blades provided by an embodiment of the present invention is that when the user determines the blades to be cut and related cutting requirements according to actual task requirements, the corresponding cutting trajectory can be automatically fitted. According to the cutting trajectory, parts of different materials can be independently separated to realize the recycling of scrapped wind turbine blades.

[0046] It should be noted that blades to be cut refer to wind turbine blades that have reached their service life, need to be replaced, are damaged, or are unqualified and need to be scrapped.

[0047] Specifically, in step 101, the cutting trajectory optimization device for wind turbine blades can obtain a first contour model based on a design drawing of the blade to be cut, and receive a second contour model obtained in real time by a three-dimensional scanning device scanning the blade to be cut.

[0048] The first contour model is a model that converts the dimensional information indicated in the design drawing of the blade to be cut into three-dimensional coordinates of each coordinate point within the blade coordinate system relative to the origin of the blade coordinate system in the blade coordinate system, thereby constructing a corresponding point cloud model. The embodiment of the present invention does not specifically limit the setting of the blade coordinate system.

[0049] For example, the blade coordinate system can be established by calculating the center of mass of the blade to be cut based on its design drawing, and using this center of mass as the origin of the blade coordinate system. In the cross section where the origin is located, the horizontal direction to the right is the positive X-axis direction, and the vertical direction downward is the positive Y-axis direction. In the vertical cross section where the origin is located, the vertical direction upward is the positive Z-axis direction.

[0050] Exemplarily, the process of establishing the blade coordinate system may also be to extract an edge feature point according to the design drawing of the blade to be cut, and establish a corresponding three-dimensional coordinate system with the point as the origin of the coordinate system.

[0051] The second contour model refers to the three-dimensional coordinates directly captured between the three-dimensional scanning device and the blade to be cut, as scanned by the three-dimensional scanning device in the device coordinate system, to construct a corresponding point cloud model. The embodiment of the present invention does not specifically limit the setting of the device coordinate system.

[0052] Exemplarily, the process of establishing the device coordinate system can be as follows: the scanning starting point of the three-dimensional scanning device is used as the origin of the coordinate system, the forward moving direction of the three-dimensional scanning device is the positive direction of the X-axis, the vertical direction of the three-dimensional scanning device pointing to the blade to be cut is the negative direction of the Z-axis, and the Y-axis is determined by the Cartesian right-hand coordinate system rule.

[0053] Optionally, the three-dimensional scanning device and the cutting device are arranged adjacent to each other and share a device coordinate system.

[0054] Step 102: Calculate a first cutting trajectory of the cutting device in the device coordinate system based on the first contour model and the second contour model.

[0055] Specifically, in step 102, the cutting trajectory optimization device for wind turbine blades matches the highly correlated feature points in the first contour model and the second contour model, and then uses a path planning algorithm to obtain a first cutting trajectory of the cutting device on the blade to be cut.

[0056] The first cutting trajectory refers to the initially planned cutting trajectory.

[0057] Among them, the path planning algorithm includes but is not limited to the packing algorithm, simulated annealing algorithm, artificial potential field method, fuzzy logic algorithm, taboo search algorithm, ant colony algorithm, neural network algorithm, particle swarm algorithm, genetic algorithm and other methods, and the embodiment of the present invention does not make specific limitations on this.

[0058] Step 103: Determine a second cutting trajectory of the cutting device on the blade to be cut based on the first cutting trajectory and density grayscale information corresponding to the first cutting trajectory.

[0059] The density grayscale information is obtained by scanning the blade to be cut along a first cutting trajectory using a first scanning device.

[0060] It should be noted that before step 103, the first scanning device sequentially aligns with each path point in the first cutting path and scans the grayscale image of the material density inside the blade in the area near the path point. The grayscale information in the scanned area is compared with the grayscale distortion threshold built into the first scanning device. The material density of different areas of the blade varies greatly, and the grayscale distinction is more significant. Therefore, the comparison results are divided into two types:

[0061] If there is grayscale information greater than or equal to the grayscale distortion threshold in the scanning area, it is determined that the scanning area is composed of two different materials, and the grayscale information greater than or equal to the grayscale distortion threshold can represent the junction of the two different material areas.

[0062] If the grayscale information in the scanning area is all less than the grayscale distortion threshold, it is determined that the material in the scanning area is uniform.

[0063] The embodiment of the present invention does not specifically limit the first scanning device. Exemplarily, the first scanning device may be a reflective X-ray scanning device.

[0064] Reflective X-ray scanning equipment places the ray source and detector on the same side, performs statistical analysis on the rays reflected from the target object obtained by the detector, obtains an image of the blade, and displays defects inside or on the surface of the blade in the form of grayscale texture on the image.

[0065] The radiation source of a reflective X-ray scanner emits low-energy X-rays toward the blade being inspected. Upon striking an object, the majority of the radiation passes through, while a portion is absorbed by the object through the photoelectric effect. The remaining small portion is reflected and then absorbed by a detector located near the radiation source. Internal structural defects can cause changes in the material's response to heat, sound, light, electricity, and magnetism. These changes can be used to detect anomalies and defects within the material or structure. Therefore, in wind turbine blades composed of regions of varying material, the number of scattered photons detected varies depending on the density of the material. The higher the number of photons, the brighter the image automatically, allowing the grayscale value to distinguish between different materials.

[0066] Specifically, in step 103, the cutting trajectory optimization device of the wind turbine blade determines the position of the junction of different materials in the blade to be cut based on the density grayscale information fed back by the first scanning device during the scanning process, and then matches and optimizes it with the first cutting trajectory obtained in step 102 to obtain a second cutting trajectory.

[0067] The second cutting trajectory refers to the cutting trajectory finally determined according to the first cutting trajectory.

[0068] This embodiment of the present invention integrates a first contour model in the blade coordinate system and a second contour model in the device coordinate system into a single framework. This model then optimizes the path using the determined first cutting trajectory and density grayscale information fed back by the first scanning device to obtain a second cutting trajectory for the automated cutting device. This allows for planning and optimizing cutting trajectories tailored to specific wind turbine blade types, improving cutting efficiency and precision, thereby enhancing the adaptability of the automated cutting equipment and reducing its cost.

[0069] On the basis of any of the above embodiments, based on the first cutting trajectory and the density grayscale information corresponding to the first cutting trajectory, the second cutting trajectory of the cutting device on the blade to be cut is determined, including: for each path point in the first cutting trajectory, the following are executed: based on the density grayscale information of the path point, the set of connection points corresponding to the path point in the blade to be cut is determined; when the path point is in the corresponding set of connection points, the path point is used as the target path point; when the path point is not in the corresponding set of connection points, the coordinate point with the smallest distance to the path point is selected from the corresponding set of connection points as the target path point.

[0070] Specifically, in step 103, while the first scanning device is scanning along the first cutting trajectory, in the scanning area near each path point, grayscale values ​​greater than or equal to the grayscale distortion threshold are filtered out from the density grayscale information of the current path point, and the coordinate points corresponding to all grayscale values ​​that meet the above conditions are integrated into a set of junction points to represent the existence of junctions of different materials in the current scanning area.

[0071] Different path points in the first cutting trajectory correspond to different sets of connection points.

[0072] Then, any path point under the first cutting trajectory is compared with the set of combined points corresponding to the current path point passed by the scan, and the comparison results are divided into two types: comparison failure and comparison success.

[0073] Among them, successful comparison means that the current path point is in the corresponding combination point set, which means that the path point is at the junction of different materials. There is no need to optimize the path point. It can be directly integrated into the second cutting trajectory as the target path point, and the next path point can be processed in the same process until all the path points in the first cutting trajectory are processed in sequence according to the above process.

[0074] Comparison failure means that the current path point is not in the corresponding junction point set, that is, the path point is not at the junction of different materials. The path point needs to be brought as close to the junction as possible. The coordinates of the path point can be used as the target value, and a coordinate point that is infinitely close to the target value (that is, the target path point) can be extracted from the junction point set. The target path point can be used as the updated value of the path point to optimize the first cutting trajectory into the second cutting trajectory using the updated path point.

[0075] Based on the target path point, the second cutting trajectory is generated.

[0076] Specifically, each path point in the first cutting trajectory is converted into a corresponding target path point in turn and then integrated into a second cutting trajectory, so that the optimized second cutting trajectory contains more material junctions, thereby enabling different material areas to be cut to the most complete degree.

[0077] This embodiment of the present invention determines the set of junction points corresponding to the locations of the junctions between different materials in the blade to be cut based on the density grayscale information corresponding to the first cutting trajectory. This set of junction points is then used to determine the optimization of the first cutting trajectory to obtain a second cutting trajectory. This optimization of the cutting trajectory improves cutting efficiency and accuracy, thereby increasing the yield rate and reducing the cost of automated cutting equipment.

[0078] On the basis of any of the above embodiments, the first cutting trajectory of the cutting device in the device coordinate system is calculated based on the first contour model and the second contour model, including: matching feature points of the first contour model and the second contour model to determine the cutting starting point.

[0079] Specifically, in step 102, the cutting trajectory optimization device of the wind turbine blade adopts a correlation matching algorithm to match the feature points with high correlation in the first contour model and the second contour model, and fuses the complete original blade contour and the scanned contour into the equipment coordinate system framework. The initial coordinate value of the cutting equipment relative to the blade to be cut is extracted from the actual contour information as the starting point of cutting.

[0080] The cutting starting point is used to instruct the cutting equipment to drive the robotic arm to move to this point and wait for the execution of the cutting task.

[0081] The correlation matching algorithm includes, but is not limited to, Grey Relation Analysis (GRA), Least Squares Method, Pearson correlation coefficient calculation, Spearman correlation coefficient calculation, and the like, which are not specifically limited in the embodiment of the present invention.

[0082] It can be understood that the basis for extracting the cutting starting point from the actual contour information includes but is not limited to selecting typical shape feature points or contour lines such as the tip contour, edge contour, root and blade junction, and the embodiment of the present invention does not make specific limitations on this.

[0083] It is understandable that the feature points that do not match between the two contour models can also be marked as defects in the blade. If the defect marking point is a typical shape feature point, the defect marking point can also be used as the cutting starting point.

[0084] Based on the cutting starting point and the cutting parameters, a first cutting trajectory is calculated.

[0085] Specifically, it should be noted that, before step 102 , the cutting trajectory optimization device for wind turbine blades may receive cutting parameters input by the user according to the cutting task, so that the cut product meets the requirements of the cutting task.

[0086] Specifically, the cutting trajectory optimization device for wind turbine blades performs fuzzy comprehensive evaluation based on pre-input cutting parameters as constraints, and uses a path planning algorithm in combination with a determined cutting starting point to obtain the first cutting trajectory of the cutting equipment on the blade to be cut.

[0087] In this embodiment of the present invention, a first contour model in the blade coordinate system and a second contour model in the equipment coordinate system are integrated into a single framework. By determining the cutting starting point and cutting parameters, a first cutting trajectory for the automated cutting equipment is obtained. This allows for the design of a specific first cutting trajectory for each wind turbine blade, improving cutting efficiency and, in turn, enhancing the adaptability of the automated cutting equipment while reducing its cost.

[0088] On the basis of any of the above embodiments, before obtaining the first contour model and the second contour model of the blade to be cut, the method further includes: receiving input blade identification information.

[0089] Specifically, before step 101 , the cutting trajectory optimization device for wind turbine blades receives blade identification information input by a user to uniquely determine properties such as performance, specifications, and dimensions of the blade to be cut.

[0090] The embodiment of the present invention does not specifically limit the blade identification information.

[0091] Optionally, the blade identification information may be a blade model, for example, blade models of different series provided by various manufacturers.

[0092] Optionally, the blade identification information may also be an identification code that corresponds one-to-one with the blade model. For example, the user may classify and code wind turbine blades from various manufacturers in a unified manner according to established principles, and associate the identification code with the blade model.

[0093] The blade identification information is used to match a first contour model corresponding to the blade identification information from a blade model library.

[0094] Among them, the blade model library is pre-built based on the design drawings of various wind turbine blades.

[0095] It should be noted that before step 101, the user can import the design drawings of scrapped wind turbine blades of different models into the electronic device for modeling to form a blade model library, and perform real-time maintenance and update of the blade model library.

[0096] The embodiment of the present invention does not specifically limit the blade model library. For example, the model of the scrapped wind turbine blade is used as the index field, and the original contour model built according to the drawing is stored under the corresponding index field.

[0097] Specifically, the cutting trajectory optimization device for wind turbine blades performs a query and search on the blade model library according to the received blade identification information, and the query results include two types, namely query success and query failure.

[0098] Among them, a successful query means that the blade identification information can match the index field of the blade model library, that is, the blade model library has the original contour model corresponding to this model of blade. The original contour model is then used as the first contour model and fed back to the cutting trajectory optimization device of the wind turbine blade.

[0099] A query failure occurs when the blade identification information doesn't match the index field in the blade model library. This indicates that the blade model library doesn't contain the original contour model for that blade type. A warning message is then fed back to the user, for example, with the text "No original contour model found for this model. Please enter new query information!" Once an original contour model matching the new blade identification information is found, the model is fed back to the wind turbine blade cutting trajectory optimization device.

[0100] Based on the blade identification information, the present invention retrieves the corresponding first contour model from the blade model library. This provides a strong reference for obtaining the actual contour, avoiding the confusion between the defective parts of the scrapped blade and the original design joints caused by scanning with a 3D scanning device alone, thereby improving cutting efficiency and accuracy.

[0101] On the basis of any of the above embodiments, after obtaining the cutting trajectory of the cutting device on the blade to be cut, the method further includes: controlling the cutting device to cut the blade to be cut according to the second cutting trajectory.

[0102] Specifically, after step 103 , the cutting trajectory optimization device for wind turbine blades may encapsulate the second cutting trajectory obtained in step 103 into a control instruction and send the control instruction to the cutting device.

[0103] The cutting device receives and responds to the control instruction, drives the robotic arm carrying the cutting knife to move to the cutting starting point, and after adjusting the relevant mechanism parameters, controls the robotic arm to move along the second cutting trajectory encapsulated in the control instruction. During its movement, the cutting knife performs the corresponding cutting operation.

[0104] It is understood that the wind turbine blade cutting trajectory optimization device can encapsulate the second cutting trajectory obtained in step 103 into a control instruction and send it to the positioning device. The positioning device then performs marking or line laser positioning on the surface of the blade to be cut according to the second cutting trajectory indicated in the control instruction, thereby guiding the operator to perform the cutting operation according to the line on the surface.

[0105] The embodiment of the present invention controls the cutting equipment to perform cutting operations on the surface of the blade to be cut according to the second cutting trajectory, thereby optimizing the cutting trajectories of different wind turbine blades, maximizing the number of junctions passed by the cutting trajectory, improving the cutting efficiency and yield rate, and realizing the automation and intelligence of blade recovery cutting.

[0106] Based on any of the above embodiments, the cutting parameters include: at least one of: product size data after cutting, material distribution characteristic data, minimum sawing length and material yield rate.

[0107] Specifically, in step 102, the cutting parameters received by the wind turbine blade cutting trajectory optimization device are determined according to actual cutting task requirements, and the cutting parameters are used as constraints for fuzzy comprehensive evaluation. The present invention does not impose any specific limitations on this.

[0108] Optionally, the cutting parameters may be dimensional data of the product after cutting, so as to describe the cutting task.

[0109] For example, the size data of the product after cutting may be a post-processing size, so that the product after cutting can meet the transportation size, processing size, etc. of a recycling plant.

[0110] Optionally, the cutting parameters may be material distribution characteristic data to describe the material properties of the blade to be cut.

[0111] For example, the material distribution characteristic data can be information about the materials used in the area defined by at least two coordinates in the machine coordinate system. This information is used to indicate the materials used in different areas of the blade to be cut, thereby controlling the cutting settings and executing the cutting operation in the corresponding areas using the appropriate machine parameters.

[0112] For example, the material distribution characteristic data may be coordinate point information pre-determined based on the material joint location. This information can be used as a preset trajectory point, so that the final first cutting trajectory includes the above trajectory point, thereby achieving the purpose of cutting two areas of different materials.

[0113] Optionally, the cutting parameter may be a minimum sawing length to form a corresponding fuzzy constraint condition, so as to minimize the cutting loss of the blade to be cut.

[0114] Optionally, the cutting parameter may be a material yield rate, so as to form a corresponding fuzzy constraint condition so that the material of the cut product that does not meet the product processing requirements is minimized.

[0115] The embodiment of the present invention will participate in the fuzzy planning of the cutting trajectory through the product size data and / or material distribution characteristic data contained in the cutting parameters, which can improve the cutting efficiency while also improving the blade cutting yield, thereby realizing the automation and intelligence of blade recovery cutting.

[0116] Figure 2 Schematic diagram of the cutting trajectory optimization device for wind turbine blades provided by the present invention. Figure 2 As shown, the cutting trajectory optimization device for wind turbine blades provided by the embodiment of the present invention includes: a contour acquisition module 210, an initial trajectory acquisition module 220 and a trajectory optimization module 230, wherein:

[0117] The contour acquisition module 210 is configured to acquire a first contour model and a second contour model of the blade to be cut.

[0118] The initial trajectory acquisition module 220 is configured to calculate a first cutting trajectory of the cutting device in the device coordinate system based on the first contour model and the second contour model.

[0119] The trajectory optimization module 230 is configured to determine a second cutting trajectory of the cutting device on the blade to be cut based on the first cutting trajectory and density grayscale information corresponding to the first cutting trajectory.

[0120] Among them, the density grayscale information is obtained by scanning the blade to be cut along the first cutting trajectory using a first scanning device; the first contour model includes point cloud information of the blade to be cut in the blade coordinate system; the second contour model includes point cloud information of the blade to be cut in the cutting device coordinate system.

[0121] Specifically, the contour acquisition module 210 , the initial trajectory acquisition module 220 , and the trajectory optimization module 230 are electrically connected in sequence.

[0122] The contour acquisition module 210 may acquire a first contour model according to a design drawing of the blade to be cut, and receive a second contour model acquired in real time by a three-dimensional scanning device scanning the blade to be cut.

[0123] After matching the highly correlated feature points in the first contour model and the second contour model, the initial trajectory acquisition module 220 uses a path planning algorithm to acquire a first cutting trajectory of the cutting device on the blade to be cut.

[0124] The trajectory optimization module 230 determines the location of the junction of different materials in the blade to be cut based on the density grayscale information fed back by the first scanning device during the scanning process, and then matches and optimizes it with the first cutting trajectory obtained by the initial trajectory acquisition module 220 to obtain a second cutting trajectory.

[0125] Optionally, the trajectory optimization module 230 includes an optimization unit and a trajectory generation unit, wherein:

[0126] The optimization unit is used to perform the following operations for each path point in the first cutting trajectory: determining a set of connection points corresponding to the path point in the blade to be cut based on the density grayscale information of the path point; when the path point is in the corresponding set of connection points, using the path point as a target path point; when the path point is not in the corresponding set of connection points, selecting a coordinate point with the smallest distance to the path point from the corresponding set of connection points as a target path point.

[0127] The trajectory generating unit is configured to generate the second cutting trajectory based on the target path point. Optionally, the initial trajectory acquiring module 220 includes a starting point determining unit and an initial trajectory acquiring unit, wherein:

[0128] The starting point determination unit is used to perform feature point matching on the first contour model and the second contour model to determine the cutting starting point.

[0129] The initial trajectory acquisition unit is used to calculate a first cutting trajectory based on a cutting starting point and cutting parameters.

[0130] Optionally, the cutting trajectory optimization device for wind turbine blades further includes a receiving identification unit and a model query unit, wherein:

[0131] The identification receiving unit is used to receive input blade identification information.

[0132] The model query unit is used to use the blade identification information to match a first contour model corresponding to the blade identification information from a blade model library.

[0133] Among them, the blade model library is pre-built based on the design drawings of various wind turbine blades.

[0134] Optionally, the cutting trajectory optimization device for wind turbine blades further includes a control module, wherein:

[0135] The control module is used to control the cutting device to cut the blade to be cut according to the second cutting trajectory.

[0136] Optionally, the cutting parameters include at least one of: product size data after cutting, material distribution characteristic data, minimum sawing length and material yield rate.

[0137] The cutting trajectory optimization device for wind turbine blades provided in an embodiment of the present invention is used to execute the cutting trajectory optimization method for wind turbine blades mentioned above in the present invention. Its implementation method is consistent with the implementation method of the cutting trajectory optimization method for wind turbine blades provided by the present invention, and can achieve the same beneficial effects, which will not be repeated here.

[0138] This embodiment of the present invention integrates a first contour model in the blade coordinate system and a second contour model in the device coordinate system into a single framework. This model then optimizes the path using the determined first cutting trajectory and density grayscale information fed back by the first scanning device to obtain a second cutting trajectory for the automated cutting device. This allows for planning and optimizing cutting trajectories tailored to specific wind turbine blade types, improving cutting efficiency and precision, thereby enhancing the adaptability of the automated cutting equipment and reducing its cost.

[0139] Figure 3 Schematic diagram of the cutting trajectory optimization system for wind turbine blades provided by the present invention. Figure 3 As shown, the cutting trajectory optimization system for wind turbine blades provided by the embodiment of the present invention includes a first scanning device 310, a second scanning device 320 and a cutting device 330, and also includes a cutting trajectory optimization device 340 for wind turbine blades.

[0140] Specifically, the cutting trajectory optimization system for wind turbine blades is composed of a first scanning device 310 , a second scanning device 320 , a cutting device 330 , and a cutting trajectory optimization device 340 for wind turbine blades.

[0141] Among them, the cutting trajectory optimization device 340 of the wind turbine blade can be integrated into the control development board of the wind turbine blade cutting equipment 330 as a chip or microprocessor, or it can rely on the operation of a remote terminal, and realize the planning of the cutting path through communication connections with the first scanning device 310, the second scanning device 320 and the cutting device 330 respectively.

[0142] Preferably, the cutting trajectory optimization device 340 for wind turbine blades respectively transmits signals with the first scanning device 310 , the second scanning device 320 and the cutting device 330 using wireless communication technology.

[0143] Among them, wireless communication technology includes but is not limited to WIFI wireless cellular signals (2G, 3G, 4G, 5G), Bluetooth, Zigbee and other methods, which are not specifically limited in the embodiments of the present invention.

[0144] The second scanning device 320 is used to scan the blade to be cut to obtain a second contour model.

[0145] Specifically, the second scanning device 320 can scan the blade to be cut in the device coordinate system, and directly collect the relative three-dimensional coordinates between the second scanning device 320 and the blade to be cut to construct the corresponding second contour model.

[0146] The embodiment of the present invention does not specifically limit the selection of the second scanning device 320. For example, the second scanning device 320 may be a three-dimensional scanning device.

[0147] Preferably, the first scanning device 310 and the second scanning device 320 can be arranged on the same horizontal plane of the robot arm in an adjacent manner to the cutting blade in the cutting device 320 so as to share the same device coordinate system.

[0148] This embodiment of the present invention integrates a first contour model in the blade coordinate system and a second contour model in the device coordinate system into a single framework. This model then optimizes the path using the determined first cutting trajectory and density grayscale information fed back by the first scanning device to obtain a second cutting trajectory for the automated cutting device. This allows for planning and optimizing cutting trajectories tailored to specific wind turbine blade types, improving cutting efficiency and precision, thereby enhancing the adaptability of the automated cutting equipment and reducing its cost.

[0149] Figure 4 An example of a physical structure diagram of an electronic device is shown below. Figure 4As shown, the electronic device may include: a processor 410, a communication interface 420, a memory 430, and a communication bus 440, wherein the processor 410, the communication interface 420, and the memory 430 communicate with each other via the communication bus 440. The processor 410 may call the logic instructions in the memory 430 to execute a cutting trajectory optimization method for a wind turbine blade, the method comprising: obtaining a first contour model and a second contour model of the blade to be cut; calculating a first cutting trajectory of a cutting device in a device coordinate system based on the first contour model and the second contour model; determining a second cutting trajectory of the cutting device on the blade to be cut based on the first cutting trajectory and density grayscale information corresponding to the first cutting trajectory; wherein the density grayscale information is obtained by scanning the blade to be cut along the first cutting trajectory using a first scanning device; the first contour model includes point cloud information of the blade to be cut in the blade coordinate system; and the second contour model includes point cloud information of the blade to be cut in the cutting device coordinate system.

[0150] In addition, the logic instructions in the above-mentioned memory 430 can be implemented in the form of a software functional unit and can be stored in a computer-readable storage medium when sold or used as an independent product. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0151] On the other hand, the present invention also provides a computer program product, which includes a computer program, which can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute the cutting trajectory optimization method for wind turbine blades provided by the above methods, the method including: obtaining a first contour model and a second contour model of the blade to be cut; based on the first contour model and the second contour model, calculating the first cutting trajectory of the cutting device in the device coordinate system; based on the first cutting trajectory and the density grayscale information corresponding to the first cutting trajectory, determining the second cutting trajectory of the cutting device on the blade to be cut; wherein the density grayscale information is obtained by scanning the blade to be cut along the first cutting trajectory using a first scanning device; the first contour model includes point cloud information of the blade to be cut in the blade coordinate system; the second contour model includes point cloud information of the blade to be cut in the cutting device coordinate system.

[0152] On the other hand, the present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, is implemented to execute the cutting trajectory optimization method for wind turbine blades provided by the above-mentioned methods, the method comprising: obtaining a first contour model and a second contour model of the blade to be cut; calculating a first cutting trajectory of the cutting device in the device coordinate system based on the first contour model and the second contour model; determining a second cutting trajectory of the cutting device on the blade to be cut based on the first cutting trajectory and the density grayscale information corresponding to the first cutting trajectory; wherein the density grayscale information is obtained by scanning the blade to be cut along the first cutting trajectory using a first scanning device; the first contour model includes point cloud information of the blade to be cut in the blade coordinate system; the second contour model includes point cloud information of the blade to be cut in the cutting device coordinate system.

[0153] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, i.e., they may be located in one location or distributed across multiple network units. Some or all of the modules may be selected based on actual needs to achieve the objectives of the present embodiment. Persons of ordinary skill in the art will be able to understand and implement the present invention without inventive effort.

[0154] Through the description of the above embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus a necessary general hardware platform, or of course, by hardware. Based on this understanding, the essence of the above technical solution or the part that contributes to the existing technology can be embodied in the form of a software product. The computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a magnetic disk, an optical disk, etc., and includes a number of instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or certain parts of the embodiments.

[0155] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present invention.

Claims

1. A method for optimizing the cutting trajectory of a wind turbine blade, characterized in that: include: Acquire a first contour model and a second contour model of the blade to be cut; Calculating a first cutting trajectory of a cutting device in a device coordinate system based on the first contour model and the second contour model; determining a second cutting trajectory of the cutting device on the blade to be cut based on the first cutting trajectory and density grayscale information corresponding to the first cutting trajectory; The density grayscale information is obtained by scanning the blade to be cut along the first cutting trajectory using a first scanning device; the first contour model includes point cloud information of the blade to be cut in the blade coordinate system; and the second contour model includes point cloud information of the blade to be cut in the cutting device coordinate system. The determining, based on the first cutting trajectory and the density grayscale information corresponding to the first cutting trajectory, a second cutting trajectory of the cutting device on the blade to be cut includes: For each path point in the first cutting trajectory, the following steps are performed: determining a set of junction points corresponding to the path point in the blade to be cut based on density grayscale information of the path point; if the path point is in the corresponding set of junction points, using the path point as a target path point; if the path point is not in the corresponding set of junction points, selecting a coordinate point with the smallest distance to the path point from the corresponding set of junction points as the target path point; Based on the target path point, the second cutting trajectory is generated.

2. The cutting trajectory optimization method for wind turbine blades according to claim 1, characterized in that: The calculating, based on the first contour model and the second contour model, a first cutting trajectory of the cutting device in the device coordinate system includes: Performing feature point matching on the first contour model and the second contour model to determine a cutting starting point; The first cutting trajectory is calculated based on the cutting starting point and cutting parameters.

3. The cutting trajectory optimization method for wind turbine blades according to claim 1, characterized in that: Before obtaining the first contour model and the second contour model of the blade to be cut, the method further includes: Get blade identification information; Using the blade identification information, matching the first contour model corresponding to the blade identification information from a blade model library; The blade model library is pre-built based on design drawings of various wind turbine blades.

4. The cutting trajectory optimization method for wind turbine blades according to claim 1, characterized in that: After obtaining the cutting trajectory of the cutting device on the blade to be cut, the method further includes: controlling the cutting device to cut the blade to be cut according to the second cutting trajectory.

5. The cutting trajectory optimization method for wind turbine blades according to claim 2, characterized in that: The cutting parameters include at least one of: product size data after cutting, material distribution characteristic data, minimum sawing length and material yield rate.

6. A cutting trajectory optimization device for wind turbine blades, characterized in that: include: A contour acquisition module, used to acquire a first contour model and a second contour model of the blade to be cut; an initial trajectory acquisition module, configured to calculate a first cutting trajectory of the cutting device in a device coordinate system based on the first contour model and the second contour model; a trajectory optimization module, configured to determine a second cutting trajectory of the cutting device on the blade to be cut based on the first cutting trajectory and density grayscale information corresponding to the first cutting trajectory; The density grayscale information is obtained by scanning the blade to be cut along the first cutting trajectory using a first scanning device; the first contour model includes point cloud information of the blade to be cut in the blade coordinate system; and the second contour model includes point cloud information of the blade to be cut in the cutting device coordinate system. The determining, based on the first cutting trajectory and the density grayscale information corresponding to the first cutting trajectory, a second cutting trajectory of the cutting device on the blade to be cut includes: For each path point in the first cutting trajectory, the following steps are performed: determining a set of junction points corresponding to the path point in the blade to be cut based on density grayscale information of the path point; if the path point is in the corresponding set of junction points, using the path point as a target path point; if the path point is not in the corresponding set of junction points, selecting a coordinate point with the smallest distance to the path point from the corresponding set of junction points as the target path point; Based on the target path point, the second cutting trajectory is generated.

7. A cutting trajectory optimization system for wind turbine blades, characterized in that: It comprises a first scanning device, a second scanning device and a cutting device, and is characterized in that it further comprises: the cutting trajectory optimization device for wind turbine blades according to claim 6; The second scanning device is used to scan the blade to be cut to obtain a second contour model.

8. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the program, the cutting trajectory optimization method for a wind turbine blade according to any one of claims 1 to 5 is implemented.

9. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the cutting trajectory optimization method for a wind turbine blade according to any one of claims 1 to 5 is implemented.

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