A method and system for field cutting of decommissioned blades based on a cutting robot

Abstract

The application provides a retired blade field cutting method and system based on a cutting robot, wherein the method comprises the following steps: obtaining three-dimensional scanning data of the retired blade and constructing a blade model by using the three-dimensional scanning data; positioning the retired blade to determine the relative position of the cutting robot and the retired blade; comprehensively analyzing the blade model and the relative position of the cutting robot and the retired blade to determine a cutting path; and controlling the cutting robot to cut based on the cutting path. The retired blade field cutting method and system based on the cutting robot model the retired blade, analyze the model, control the cutting robot to cut according to the analyzed cutting path, and consider the requirements of the factory during the analysis, so that the cutting is fast, efficient and accurate.

Description

Technical Field

[0001] This invention relates to the field of decommissioned blade cutting technology, and in particular to a method and system for decommissioned blade cutting based on a cutting robot. Background Technology

[0002] With the increasing prominence of global climate change and environmental issues, wind power, as a clean and renewable energy source, has received more and more attention. Due to environmental factors such as wind, rain erosion, and sun exposure, wind turbine blades are forced to be decommissioned after a certain period of use. In addition, due to technological advancements leading to the expansion of individual wind turbine units, more and more wind turbine blades are facing the problem of disposal and reuse after decommissioning.

[0003] Methods for treating retired wind turbine blades include incineration, pyrolysis, pyrolysis, directional depolymerization, crushing, and cutting for reuse. Incineration has low calorific value, incomplete combustion, and is prone to coking and the generation of harmful gases. Pyrolysis and pyrolysis are energy-intensive, produce many impurities, and are difficult to purify. Directional depolymerization technology is still immature, costly, and produces difficult-to-treat and purify wastewater, resulting in low added value. Crushing typically involves crushing the blades for incineration or using them as additives in building materials such as cement and asphalt, which is not economically efficient. Cutting for reuse requires sophisticated tools and specialized equipment, and a stable downstream market. Overall, chemical treatment methods such as incineration, pyrolysis, and directional depolymerization still face many technical challenges and lack the conditions for value-added utilization. Physical processing methods such as crushing and cutting are more feasible and produce less secondary pollution.

[0004] However, the blades are large, and the unloading site is complex, making it impossible to transport them to the factory for unified cutting or shredding. Therefore, they need to be disassembled in the field before being transported to the factory for unified cutting. Currently, field cutting mainly relies on manual labor, which is inefficient. The main reason for the low cutting efficiency is the limited physical strength of humans. During the cutting process, it is necessary to constantly climb up and down the blades with a chainsaw, and maintain stability while holding the chainsaw for a long time, which requires extremely high physical strength and long rest periods. Therefore, there is a considerable amount of non-cutting time in manual operations. Overall, manual cutting is inefficient.

[0005] To address the issue of low manual efficiency, a blade cutting tool can be used. This tool can be an excavator whose actuator is replaced with an electric saw, using a rock saw blade. The main workflow is as follows: after the decommissioned blade is disassembled and placed on the ground, the excavator cutter travels to the blade and makes a transverse cut at the predetermined position. Water is sprayed onto the saw blade for cooling throughout the cutting process. After the first section is cut (completely severed), the cutter travels to the second cutting point and continues cutting, and so on, until the blade is cut into pieces as planned, at which point the cutting work is complete. However, the main problem with the cut plates is that they cannot be directly processed in a factory and require secondary cutting. Summary of the Invention

[0006] One of the objectives of this invention is to provide a method and system for field cutting of decommissioned blades based on a cutting robot. The decommissioned blade is modeled, the model is analyzed, and the cutting robot is controlled to cut according to the analyzed cutting path. The needs of the factory are taken into account during the analysis, so as to achieve fast, efficient and accurate cutting.

[0007] This invention provides a method for field cutting of decommissioned blades based on a cutting robot, comprising:

[0008] Acquire 3D scan data of decommissioned blades and construct blade models using the 3D scan data;

[0009] The decommissioned blades are located to determine the relative position of the cutting robot and the decommissioned blades;

[0010] By comprehensively analyzing the blade model and the relative positions of the cutting robot and the decommissioned blade, the cutting path is determined;

[0011] The cutting robot performs cutting based on the cutting path control.

[0012] Preferably, the 3D scanning data is obtained by scanning the decommissioned blades using a laser galvanometer stereo industrial camera.

[0013] Preferably, the positioning of the decommissioned blades is achieved by coordinate mapping based on the positioning data of the cutting robot and the corresponding 3D scanning data.

[0014] Preferably, the steps for determining the cutting path are as follows:

[0015] Analyze the blade model to identify at least one divisible region;

[0016] Based on pre-configured demand targets, the segmentation units within each divisible region are determined;

[0017] Based on the edge lines of each divisible region and the edge lines of each segmentation unit, a segmentation meridian diagram on the blade model is obtained.

[0018] Based on the closed curves in the segmented meridian diagram, a cutting path is generated.

[0019] Preferably, the steps for determining the divisible region are as follows:

[0020] Obtain production and usage data for the blades;

[0021] Based on production and usage data, the various locations in the blade model are evaluated;

[0022] The area comprised of the locations that passed the evaluation is considered a divisible region.

[0023] The present invention also provides a field cutting system for decommissioned blades based on a cutting robot, comprising: a scanning and construction module, a positioning module, a path analysis module, and a control module; wherein, the scanning and construction module acquires three-dimensional scanning data of the decommissioned blade and constructs a blade model using the three-dimensional scanning data; the positioning module positions the decommissioned blade and determines the relative position of the cutting robot and the decommissioned blade; the path analysis module comprehensively analyzes the blade model and the relative position of the cutting robot and the decommissioned blade to determine the cutting path; and the control module controls the cutting robot to perform cutting based on the cutting path.

[0024] Preferably, the 3D scanning data is obtained by scanning the decommissioned blades using a laser galvanometer stereo industrial camera.

[0025] Preferably, the positioning of the decommissioned blades is achieved by coordinate mapping based on the positioning data of the cutting robot and the corresponding 3D scanning data.

[0026] Preferably, the steps for determining the cutting path are as follows:

[0027] Analyze the blade model to identify at least one divisible region;

[0028] Based on pre-configured demand targets, the segmentation units within each divisible region are determined;

[0029] Based on the edge lines of each divisible region and the edge lines of each segmentation unit, a segmentation meridian diagram on the blade model is obtained.

[0030] Based on the closed curves in the segmented meridian diagram, a cutting path is generated.

[0031] Preferably, the steps for determining the divisible region are as follows:

[0032] Obtain production and usage data for the blades;

[0033] Based on production and usage data, the various locations in the blade model are evaluated;

[0034] The area comprised of the locations that passed the evaluation is considered a divisible region.

[0035] Other features and advantages of the invention will be set forth in the following description, and will be apparent in part from the description, or may be learned by practicing the invention. The objects and other advantages of the invention may be realized and obtained by means of the structures particularly pointed out in the written description and the accompanying drawings.

[0036] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Attached Figure Description

[0037] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used in conjunction with embodiments of the invention to explain the invention and do not constitute a limitation thereof. In the drawings:

[0038] Figure 1 This is a schematic diagram of a field cutting method for decommissioned blades based on a cutting robot, as described in an embodiment of the present invention.

[0039] Figure 2 This is a schematic diagram of the cutting robot in an embodiment of the present invention;

[0040] Figure 3 This is a schematic diagram of a field cutting system for decommissioned blades based on a cutting robot, as described in an embodiment of the present invention. Detailed Implementation

[0041] The preferred embodiments of the present invention will be described below with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are for illustration and explanation only and are not intended to limit the present invention.

[0042] Example 1

[0043] This invention provides a method for field cutting of decommissioned blades based on a cutting robot, such as... Figure 1 As shown, it includes:

[0044] Step 1: Obtain 3D scanning data of the decommissioned blades and construct a blade model using the 3D scanning data;

[0045] 3D scanning data is obtained by scanning decommissioned blades using a laser galvanometer stereo industrial camera. The simplest approach is to have on-site personnel use the laser galvanometer stereo industrial camera to perform a 3D scan of the blades. The laser galvanometer stereo industrial camera then transmits the 3D scan data to the system. During scanning, a positioning device (RF positioning, GPS positioning, BeiDou positioning, etc.) is first deployed. Alternatively, the laser galvanometer stereo industrial camera can have a built-in positioning module to facilitate analysis and processing of the 3D scan data based on the positioning data. The key is that the 3D scan data is point cloud data obtained by sending scanning lasers from the camera to the decommissioned blades. To build a comprehensive and accurate model, personnel need to move the laser galvanometer stereo industrial camera to scan from multiple angles. Connecting the scan data from each angle requires positioning data, which is essential for constructing an accurate blade model.

[0046] Step 2: Locate the decommissioned blades and determine the relative position of the cutting robot and the decommissioned blades;

[0047] The positioning of the decommissioned blades is achieved by mapping the positioning data of the cutting robot and the coordinates corresponding to the 3D scanning data. The coordinate mapping corresponding to the 3D scanning data is essentially the positioning data that corresponds to the connection between the blade model and the scanning data taken from various directions. The positioning data of the blade model can be derived from this mapping. In this way, given the positioning data of the cutting robot and the positioning data corresponding to the blade model, the relative positional relationship between the two can be determined.

[0048] Step 3: Analyze the relative positions of the blade model, the cutting robot, and the decommissioned blade to determine the cutting path;

[0049] In step three, the comprehensive analysis of the relative positions of the blade model, the cutting robot, and the decommissioned blade yields a cutting path consisting of two parts: the first part analyzes the blade model to obtain the trajectory for cutting the blade; the second part analyzes the relative positions to determine the movement of the cutting robot to cut the trajectory. The results from both parts are combined to obtain the complete cutting path. Therefore, the steps for determining the cutting path are as follows:

[0050] Analyze the blade model to identify at least one divisible region; a divisible region is one in which there is material that needs to be recycled and the material is free from any damage; damaged material needs to be removed during this segmentation.

[0051] Based on pre-configured demand targets, the segmentation units within each segmentable region are determined. Each segmentation unit is a unit formed after segmentation and corresponds to the demand target. The demand target is a unit that can be directly used in the factory without further segmentation. The demand target is pre-configured in the system as a series of small local models corresponding to the blade model. First, the segmentable region is processed to obtain a filling template, and the small models are filled and compared to determine the segmentation units that can be accommodated in each segmentable region.

[0052] Based on the edge lines of each divisible region and the edge lines of each segmentation unit, a segmentation network diagram is obtained on the blade model; each network of the segmentation network diagram is a line with a preset width (the width is determined according to the thickness of the cutting blade) with the edge line as the side boundary.

[0053] A cutting path is generated based on the closed curves in the segmented meridian diagram. This process includes: determining the closest closed curve as the starting working curve and its starting point based on the relative position between the cutting robot and the decommissioned blade; then determining the nearest other curve as the next working curve based on the distance between the starting working point and other curves; and so on, sequentially constructing a list of working curves and configuring the starting point of each curve; using the current position of the cutting robot as the first point; and then constructing the cutting path using the first point, the starting points of each working curve, and the working curves themselves.

[0054] The steps for determining the separable region are as follows: First, acquire the production and usage data of the blade. Second, evaluate each location in the blade model based on the production and usage data. Third, define the regions formed by the evaluated locations as the separable regions. Evaluation can be performed using a pre-configured evaluation library. Features are extracted from the production and usage data, and evaluation results corresponding to the extracted features are retrieved from the evaluation library. The evaluation library is pre-built, and each evaluation result in the library is associated with a specific feature parameter. Feature parameters include: parameters indicating whether cracks have occurred, parameters indicating whether repairs have been performed, and parameters indicating the performance (tensile strength, stress resistance, etc.) at that location. It is important to note that performance changes over time. Therefore, for more accurate evaluation, time parameters can be associated with each evaluation result in the evaluation library, and then the time parameters can be used to retrieve more accurate evaluation results, ensuring the accuracy of the separable region determination.

[0055] Step 4: Control the cutting robot to perform cutting based on the cutting path.

[0056] like Figure 2As shown in the figure, the cutting robot includes: a six-axis robotic arm 11, a cutting system 12, a tracked vehicle 13, a dust removal system 14, and a battery pack (located at the bottom of the chassis). Its main function is to cut blades. The main role of the six-axis robotic arm 11 is to drive the cutting integrated mechanism and perform cutting operations at any position and at any angle in three-dimensional space. The six-axis robotic arm 11 is already a relatively mature industrial product in the market and exists as a component in this patent, so there is no need for excessive elaboration. The cutting system 12 is a device equipped with multiple sensors, a motor, and a saw blade, which is connected to the wrist of the robotic arm (i.e., the end of the robotic arm). It mainly has two functions: First, it is equipped with a vision camera, a laser sensor, and a six-axis force sensor to achieve linkage during the cutting process. The six-axis force sensor monitors the force feedback from the cutting head in real time, the laser sensor feeds back the cutting depth in real time, and the vision camera guides the robotic arm for path tracking cutting; Second, the motor drives the saw blade to achieve the cutting function. The tracked vehicle mainly has three functions: First, it serves as a platform for carrying the robotic arm, the dust removal system, and the electrical cabinet; Second, it can perform basic walking, including moving forward, backward, turning left, and turning right; Third, there is a hydraulic support rod at each of the four corners of the tracked vehicle, which will extend during operation to lift the tracked vehicle and provide a horizontal and stable working platform for the robotic arm. The dust removal system includes a small dust collector, which is carried on the tracked vehicle and is used to suck away the dust generated during cutting to achieve pollution-free operation. The battery pack is placed at the bottom of the tracked vehicle and is used to supply power to the tracked vehicle, the robotic arm, the dust removal system, and the cutting system.

[0057] A specific application scenario of the present invention: After the blade is removed from the wind turbine and parked on the ground, on-site personnel use a laser scanning galvanometer stereo industrial camera to perform three-dimensional scanning on the blade, and use the point cloud data to reverse engineer the digital model. Subsequently, the blade is scanned and positioned to obtain the relative coordinates between the robot and the blade. The upper computer calculates the optimal cutting path based on the established digital model (here, "optimal" refers to the method with the highest cutting efficiency and the highest material yield). Subsequently, the vision sensor positions the cutting robotic arm, the robotic arm moves to the cutting position, the on-vehicle dust removal system is started, and the cutting system starts cutting (according to the path generated by the upper computer for cutting). During the cutting process, the laser sensor and the six-axis force sensor perform real-time feedback, and the cutting depth and speed are optimized through algorithms. After the cutting is completed, the dust removal system is turned off, and the cut main beam blanks and the like are loaded onto a vehicle and transported to the factory for hierarchical processing and utilization. The processing residues are crushed by a primary crusher and then loaded onto a vehicle and transported to the factory for composite material preparation. In addition, multiple cutting robots can also work together.

[0058] When multiple cutting robots assist in joint operation, how to achieve effective operation without mutual interference is the guarantee for improving the overall efficiency; in one embodiment, the method for cutting retired blades in the wild based on the cutting robot further includes:

[0059] Mark each working curve in the blade model, mark the virtual guide rail for the cutting robot on the outer periphery of the blade model, and determine the working point corresponding to each working area on the guide rail; wherein, the virtual guide rail is a closed line on the outer periphery of the blade model at a preset distance from the outer edge of the blade model; the working point is the point on the virtual guide rail that is the shortest distance from the central axis of the working curve.

[0060] Based on the number of cutting robots working simultaneously, determine the grouping rules; the main focus is on determining the number of groups in the grouping rules; that is, dividing all the work curves into groups equal to the number of groups.

[0061] Based on the grouping rules, the working curves are grouped to determine multiple analysis groups. The specific grouping method is as follows: Based on the number of groups according to the grouping rules, the angle difference threshold between the working point corresponding to the starting working curve of each group and the center point of the model is determined; one working curve is randomly selected as the starting working curve of one group, and then the starting industrial curves of the other two groups are determined based on the angle difference (specifically, the industrial curves with the angle difference closest to the determined angle difference threshold can be selected); then, the working curves corresponding to the working points are placed into the corresponding groups by sliding in the same direction on the virtual guide rail. Through the above operation, a group is obtained, which is a set of analysis groups; repeat the above operation, select different working curves as working curves for one group, and then re-slide and sample to obtain another set of analysis groups. In this way, all possible analysis groups can be obtained.

[0062] The working time of each group in the analysis group is estimated. The estimation method is as follows: the cutting robot is associated with the group based on the distance between the working point of the initial working curve in each group and the cutting robot; a time prediction axis is constructed for each group, and time prediction is performed. First, the time it takes for the cutting robot to move to the working point of the initial working curve of the assigned group is used as the initial prediction. Then, the working time of each working curve in the group is determined according to the pre-configured working rate. The transition time between each working time is determined by the pre-configured connection speed (the speed at which the cutting robot moves from one working curve to another after cutting from another working curve). Then, the transition time is added between the working times of the two working curves, thus forming the working time corresponding to each group.

[0063] The process of associating cutting robots with groups includes: randomly assigning cutting robots to groups, determining the assignment scheme that minimizes the time required for all cutting robots to move to the starting work point of the assigned group's work curve, and associating cutting robots with groups in the correspondence between cutting robots and groups.

[0064] The analysis group with the smallest difference in estimated working time among its subgroups is used as the final allocation basis. These subgroups are then assigned to individual cutting robots, achieving optimal work allocation and improving machine utilization and work efficiency.

[0065] This invention also provides a field cutting system for decommissioned blades based on a cutting robot, such as... Figure 3 As shown, it includes: a scanning construction module 1, a positioning module 2, a path analysis module 3, and a control module 4; wherein, the scanning construction module 1 acquires the three-dimensional scanning data of the decommissioned blade and uses the three-dimensional scanning data to construct the blade model; the positioning module 2 positions the decommissioned blade and determines the relative position of the cutting robot and the decommissioned blade; the path analysis module 3 comprehensively analyzes the blade model and the relative position of the cutting robot and the decommissioned blade to determine the cutting path; the control module 4 controls the cutting robot to perform cutting based on the cutting path.

[0066] The 3D scanning data was obtained by scanning the decommissioned blades using a laser galvanometer stereo industrial camera.

[0067] The positioning of the decommissioned blades is achieved by mapping the coordinates corresponding to the positioning data of the cutting robot and the 3D scanning data.

[0068] The steps for determining the cutting path are as follows:

[0069] Analyze the blade model to identify at least one divisible region;

[0070] Based on pre-configured demand targets, the segmentation units within each divisible region are determined;

[0071] Based on the edge lines of each divisible region and the edge lines of each segmentation unit, a segmentation meridian diagram on the blade model is obtained.

[0072] Based on the closed curves in the segmented meridian diagram, a cutting path is generated.

[0073] The steps for determining the divisible region are as follows:

[0074] Obtain production and usage data for the blades;

[0075] Based on production and usage data, the various locations in the blade model are evaluated;

[0076] The area comprised of the locations that passed the evaluation is considered a divisible region.

[0077] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, this invention also intends to include these modifications and variations.

Claims

1. A method for field cutting of decommissioned blades based on a cutting robot, characterized in that, The method comprises the following steps: acquiring three-dimensional scanning data of the retired blade and constructing a blade model based on the three-dimensional scanning data; positioning the retired blade to determine the relative position of the cutting robot and the retired blade; comprehensively analyzing the blade model and the relative position of the cutting robot and the retired blade to determine a cutting path; controlling the cutting robot to cut based on the cutting path; wherein the determination of the cutting path comprises the following steps: analyzing the blade model to determine at least one dividable region; determining a division unit in each dividable region based on a pre-configured demand target; obtaining a division meridian graph on the blade model based on the edge line of each dividable region and the edge line of each division unit; generating a cutting path according to the closed curve in the division meridian graph; wherein the division unit is a unit formed after division; the division unit corresponds to the demand target; the demand target is a unit that can be directly used by the factory without further division; the demand target is pre-configured in the system as a small model corresponding to a local part of the blade model; firstly, a fill-in template is obtained by processing the dividable region, and the small model is filled in and compared to determine the division unit that can be accommodated in each dividable region; wherein the determination of the dividable region comprises the following steps: acquiring production data and use data of the blade; evaluating each position in the blade model based on the production data and the use data; regarding a region composed of positions that pass the evaluation as a dividable region; wherein the evaluation is performed by using a pre-configured evaluation library; the evaluation is performed by extracting features from the production data and the use data, and the evaluation result associated with the feature parameters is retrieved from the evaluation library according to the extracted feature parameters; wherein the evaluation library is pre-constructed, and each evaluation result in the library is associated with a feature parameter; the feature parameters include a parameter indicating whether a crack occurs, a parameter indicating whether a repair is performed, and a parameter indicating the performance of the position; each evaluation result in the evaluation library is associated with a time parameter, and the evaluation result is retrieved by using the time parameter.

2. The decommissioned blade field cutting method based on a cutting robot according to claim 1, wherein, The three-dimensional scanning data is obtained by scanning the retired blade by a laser galvanometer stereo industrial camera.

3. The decommissioned blade field cutting method based on a cutting robot according to claim 1, wherein, The positioning of the retired blade is achieved based on the coordinate mapping of the positioning data of the cutting robot and the three-dimensional scanning data.

4. A decommissioned blade field cutting system based on a cutting robot, characterized by The method comprises the following steps: a scanning and constructing module, a positioning module, a path analysis module, and a control module; wherein the scanning and constructing module acquires three-dimensional scanning data of the retired blade and constructs a blade model based on the three-dimensional scanning data; the positioning module positions the retired blade to determine the relative position of the cutting robot and the retired blade; the path analysis module comprehensively analyzes the blade model and the relative position of the cutting robot and the retired blade to determine a cutting path; and the control module controls the cutting robot to cut based on the cutting path; wherein the determination of the cutting path comprises the following steps: analyzing the blade model to determine at least one dividable region; determining a division unit in each dividable region based on a pre-configured demand target; obtaining a division meridian graph on the blade model based on the edge line of each dividable region and the edge line of each division unit; generating a cutting path according to the closed curve in the division meridian graph; The segmentation unit is a unit formed after segmentation; the segmentation unit corresponds to a demand target; the demand target is a unit that can be directly used by the factory without secondary segmentation; the demand target is a small model corresponding to a blade model and is configured in the system in advance; the fill-in template is obtained by processing the segmentable region, and the small model is filled in and compared to determine the segmentable unit that can be accommodated in each segmentable region; The determination of the segmentable region is as follows: Obtain production data and use data of the blade; Evaluate each position in the blade model based on the production data and the use data; The region composed of the positions that pass the evaluation is the segmentable region; The evaluation is performed by using a pre-configured evaluation library; the feature parameters are extracted from the production data and the use data, and the evaluation results associated with the feature parameters are retrieved from the evaluation library according to the extracted feature parameters; the evaluation library is constructed in advance, and each evaluation result in the library is associated with a feature parameter; the feature parameters include a parameter indicating whether a crack occurs, a parameter indicating whether a repair is performed, and a parameter indicating the performance of the position; each evaluation result in the evaluation library is associated with a time parameter, and the evaluation result is searched by using the time parameter.

5. The decommissioned blade field cutting system based on a cutting robot of claim 4, wherein, The three-dimensional scanning data is obtained by scanning the retired blade by using a laser galvanometer stereoscopic industrial camera.

6. The decommissioned blade field cutting system based on a cutting robot of claim 4, wherein, The positioning of the retired blade is achieved by mapping the coordinates corresponding to the positioning data of the cutting robot and the three-dimensional scanning data.

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