Retired leaf field cutting method and system based on cutting robot

Abstract

The invention provides an out-of-service leaf field cutting method and system based on a cutting robot. The method comprises the steps that three-dimensional scanning data of an out-of-service leaf is obtained, and a leaf model is constructed through the three-dimensional scanning data; the decommissioned blade is positioned, and the relative position of the cutting robot and the decommissioned blade is determined; comprehensively analyzing the blade model and the relative position of the cutting robot and the retired blade, and determining a cutting path; and controlling the cutting robot to cut based on the cutting path. According to the out-of-service leaf field cutting method and system based on the cutting robot, modeling is conducted on the out-of-service leaf, the model is analyzed, the cutting robot is controlled to conduct cutting according to the analyzed cutting path, the requirements of factories are considered during analysis, and rapid, efficient and accurate cutting is achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of field cutting of retired blades, and particularly to a method and system for field cutting of retired blades based on a cutting robot. Background Art

[0002] With the increasing prominence of global climate change and environmental protection issues, wind power, as a clean and renewable energy source, has received more and more attention. Due to the influence of environmental factors such as wind, rain erosion, and sunlight exposure, the blades of wind power generators are compulsorily retired after a certain period of use, and due to the expansion of single wind turbines caused by technological progress, more and more wind power blades are facing the problems of post-retirement treatment and reuse.

[0003] For the treatment methods of retired wind power blades, there are ways such as incineration, pyrolysis, cracking, directional depolymerization, pulverization, and reuse after cutting and breaking. The incineration method has a low calorific value, incomplete combustion, is prone to coking and generating harmful gases; the pyrolysis and cracking methods have high energy consumption, many impurities in the products, and are not easy to purify; the directional depolymerization technology is not yet mature, has a high cost, is difficult to treat waste liquid, is difficult to purify, and has a low added value of the products; the pulverization method generally pulverizes wind power blades and then incinerates them or uses them as fillers for building cement, asphalt and other materials, and the economic benefits are not high; the cutting and reuse method has high requirements for tools and special equipment, and a stable downstream market is required. Generally speaking, there are still many technical difficulties that are difficult to break through in chemical treatment methods such as incineration, pyrolysis, and directional depolymerization, and the conditions for value-added utilization are not yet available; the physical processing methods of pulverization and cutting have a relatively high feasibility and less secondary pollution.

[0004] However, the blades are large in size, and the site environment is complex after unloading, and they cannot be transported to the factory for unified cutting or pulverization. Therefore, they need to be disassembled in the field and then transported to the factory for unified cutting. At present, field cutting mainly relies on manual on-site cutting, which has low efficiency. The main reason for the low cutting efficiency is that the physical strength of people is limited. During the cutting process, it is necessary to hold an electric saw and constantly climb up and down on the blade. During the cutting process, it is necessary to hold the electric saw steadily for a long time, which requires extremely high physical strength and a long rest time. Therefore, there is a relatively long non-cutting time in manual operation. Generally speaking, the manual cutting efficiency is relatively low.

[0005] To solve the problem of low manual efficiency, a blade cutting tool can be used for cutting. The blade cutting tool can replace the actuator of an excavator with an electric saw, and the saw blade uses a rock saw. The main working process is as follows: When the retired blade is disassembled and placed on the ground, the excavator cutting machine drives to the side of the blade and cuts transversely according to the established position. The saw blade will be sprayed with water for cooling throughout the cutting process. After the first cut is completed (i.e., completely cut off), the cutting machine drives to the second cutting point and continues to cut, and so on. When the blade is cut into pieces according to the plan, the cutting work ends. However, the main problem with the cut plates is that they cannot be directly processed by the factory and require secondary cutting. Summary of the Invention

[0006] One of the objectives of the present invention is to provide a method and system for field cutting of retired blades based on a cutting robot, which models the retired blades, analyzes the model, and controls the cutting robot to perform cutting according to the analyzed cutting path. The requirements of the factory are considered during the analysis to achieve fast, efficient, and accurate cutting.

[0007] A method for field cutting of retired blades based on a cutting robot provided by an embodiment of the present invention includes:

[0008] Obtaining three-dimensional scan data of the retired blade and constructing a blade model using the three-dimensional scan data;

[0009] Positioning the retired blade to determine the relative position between the cutting robot and the retired blade;

[0010] Comprehensively analyzing the blade model and the relative position between the cutting robot and the retired blade to determine the cutting path;

[0011] Controlling the cutting robot to perform cutting based on the cutting path.

[0012] Preferably, the three-dimensional scan data is obtained by scanning the retired blade with a laser scanning galvanometer stereo industrial camera.

[0013] Preferably, positioning the retired blade is achieved based on the positioning data of the cutting robot and the coordinate mapping corresponding to the three-dimensional scan data.

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

[0015] Analyzing the blade model to determine at least one dividable area;

[0016] Based on the pre-configured requirement objectives, determining the segmentation units within each dividable area;

[0017] Based on the edge lines of each dividable area and the edge lines of each segmentation unit, obtaining a segmentation meridian map on the blade model;

[0018] Generating a cutting path according to the closed curves in the segmentation meridian map.

[0019] Preferably, the steps for determining the dividable area are as follows:

[0020] Obtaining the production data and usage data of the blade;

[0021] Based on the production data and usage data, evaluating each position in the blade model;

[0022] Taking the area composed of the positions passing the evaluation as the dividable area.

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

[0024] Preferably, the three-dimensional scanning data is obtained by scanning the retired blades with a laser galvanometer stereo industrial camera.

[0025] Preferably, the positioning of the retired blades is realized based on the positioning data of the cutting robot and the coordinate mapping corresponding to the three-dimensional scanning data.

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

[0027] Analyze the blade model to determine at least one dividable region;

[0028] Based on the pre-configured requirement objectives, determine the segmentation units within each dividable region;

[0029] Based on the edge lines of each dividable region and the edge lines of each segmentation unit, obtain a segmentation meridian map on the blade model;

[0030] Generate a cutting path according to the closed curves in the segmentation meridian map.

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

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

[0033] Based on the production data and usage data, evaluate each position in the blade model;

[0034] Take the region composed of the positions passing the evaluation as the dividable region.

[0035] Other features and advantages of the present invention will be described in the subsequent specification, and part of them will be obvious from the specification or understood by implementing the present invention. The objectives and other advantages of the present invention can be achieved and obtained through the structures specifically pointed out in the written specification and the drawings.

[0036] The technical solution of the present invention will be further described in detail below through the drawings and embodiments. Description of the Drawings

[0037] The accompanying drawings are used to provide a further understanding of the present invention and form a part of the specification. They are used together with the embodiments of the present invention to explain the present invention, but do not constitute a limitation to the present invention. In the accompanying drawings:

[0038] Figure 1 It is a schematic diagram of a method for field cutting of retired blades based on a cutting robot in an embodiment of the present invention;

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

[0040] Figure 3 It is a schematic diagram of a system for field cutting of retired blades based on a cutting robot in an embodiment of the present invention. Detailed implementation manners

[0041] The preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention.

[0042] Embodiment 1

[0043] The embodiment of the present invention provides a method for field cutting of retired blades based on a cutting robot, as Figure 1 shown, including:

[0044] Step 1: Obtain the three-dimensional scan data of the retired blade and construct a blade model using the three-dimensional scan data;

[0045] The three-dimensional scan data is obtained by scanning the retired blade with a laser scanning galvanometer stereo industrial camera. The simplest way is to have on-site personnel use a laser scanning galvanometer stereo industrial camera to perform three-dimensional scanning of the blade in the field; the laser scanning galvanometer stereo industrial camera transmits the three-dimensional scan data to the system end; when scanning, a positioning device (any one of radio frequency positioning, GPS positioning, Beidou positioning, etc.) is first arranged. Of course, a positioning module can also be built into the laser scanning galvanometer stereo industrial camera to facilitate the analysis and processing of the three-dimensional scan data of the laser scanning galvanometer stereo industrial camera according to the positioning data; mainly because the three-dimensional scan data is point cloud data obtained by sending scanning laser from the camera end to the retired blade. In order to establish a comprehensive and accurate model, the staff needs to move the laser scanning galvanometer stereo industrial camera to perform scans in multiple directions, and positioning data is required to connect the scan data in each direction, so as to construct an accurate blade model;

[0046] Step 2: Locate the retired blade to determine the relative position between the cutting robot and the retired blade;

[0047] The positioning of the retired blade is achieved based on the positioning data of the cutting robot and the coordinate mapping corresponding to the three-dimensional scanning data; the coordinate mapping corresponding to the three-dimensional scanning data is essentially the positioning data that establishes the connection between the scanning data taken from various directions when constructing the blade model. The positioning data of the blade model can be deduced from this mapping. Thus, given the positioning data of the cutting robot and the positioning data corresponding to the blade model, the relative position relationship between the two can be determined.

[0048] Step 3: Comprehensively analyze the relative positions of the blade model, the cutting robot, and the retired blade to determine the cutting path.

[0049] The comprehensive analysis of the relative positions of the blade model, the cutting robot, and the retired blade in Step 3 to obtain the cutting path is divided into two parts: The first part is to analyze the blade model to obtain the trajectory for cutting the blade, and the second part is to analyze the relative position to determine the moving part of the cutting robot's movement for cutting the trajectory. The results of the two 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 determine at least one dividable area; a dividable area is an area where there is material to be recycled and the material is not damaged at all. Damaged material needs to be cut off during this division.

[0051] Based on the pre-configured requirement targets, determine the division units within each dividable area; among them, a division unit is each individual unit formed after division; it corresponds to the requirement target; the requirement target is a unit that can be directly used in the factory without further secondary division; the requirement targets are pre-configured in the system as small models corresponding to the local parts of the blade model. First, process the dividable area to obtain a filling template, and compare the filling of the small models to determine the division units that can be accommodated within each dividable area.

[0052] Based on the edge lines of each dividable area and the edge lines of each division unit, obtain the division meridian map on the blade model; each network in the division network map 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] Generate a cutting path based on the closed curve in the segmented meridian diagram. Among them, generating a cutting path based on the closed curve in the segmented meridian diagram includes: when generating the cutting path, determine the closest closed curve as the starting working curve and determine the starting working point on the starting working curve according to the relative position between the cutting robot and the retired blade; then determine the other curve with the closest distance as the next working curve according to the distance between the starting working point and other curves; construct a working curve list in this order and configure the starting points of each working curve; take the current position of the cutting robot as the first point; then construct a cutting path with the first point, the starting points of each working curve and the working curves.

[0054] Among them, the steps to determine the dividable area are as follows: obtain the production data and usage data of the blade; based on the production data and usage data, evaluate each position in the blade model; take the area composed of the positions that pass the evaluation as the dividable area. The evaluation can be carried out using a pre-configured evaluation library; by extracting features from the production data and usage data, retrieve the evaluation results corresponding to the feature parameters from the evaluation library according to the extracted feature parameters; among them, the evaluation library is pre-constructed, and the evaluation results in the library are in one-to-one correspondence with the feature parameters; the feature parameters include: parameters indicating whether cracks have occurred, parameters indicating whether repairs have been carried out, and parameters indicating the performance (tensile strength, stress resistance, etc.) of this position. It should be noted that the performance will change over time. Therefore, for more accurate evaluation, time parameters can be associated with each evaluation result in the evaluation library, and then more accurate evaluation results can be retrieved through the time parameters to ensure the accuracy of determining the dividable area;

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

[0056] Such as 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, which can perform cutting operations at any position and 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 to elaborate too much. 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 (also 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, which are linked 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 trace 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 to lift the tracked vehicle during operation, providing 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, achieving 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 reverse establish a digital model using the point cloud data. Subsequently, the blade is scanned and positioned to obtain the relative coordinates of the robot and the blade. The upper computer calculates the optimal cutting path based on the established digital model (here, the optimal means the way 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 provide 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 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] For the collaborative operation assisted by multiple cutting robots, 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 a cutting robot further includes:

[0059] Mark each working curve on the blade model, mark the virtual guide rail for the operation of the cutting robot on the outer periphery of the blade model, and determine the working points 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 with the shortest distance from the central axis point of the working curve.

[0060] Determine the grouping rule according to the number of cutting robots that cooperate simultaneously; mainly determine the number of groups in the grouping rule; that is, divide all the working curves into groups equal to the number of groups.

[0061] Group the working curves according to the grouping rule to determine multiple analysis groups; the specific grouping method is as follows: according to the number of groups in the grouping rule, determine the angle difference threshold between the working point corresponding to the starting working curve of each group and the center point of the model; randomly select a working curve as the starting working curve of a group, and then determine the starting industrial curves of the other two groups according to the angle difference (specifically, the industrial curve with the angle difference closest to the determined angle difference threshold can be selected); then perform a sliding sampling in the same direction on the virtual guide rail to group and sample, and place the working curves corresponding to the working points into the corresponding groups. Through the above operations, a group of groupings is obtained as a group of analysis groups; repeat the above operations, select different working curves as the working curves of a group and then re-perform the sliding sampling grouping to obtain another group of analysis groups, so that all possible analysis groups can be obtained.

[0062] Estimate the working time for each group in the analysis group; the method of estimating time is as follows: according to the distance between the working point of the starting working curve in each group and the cutting robot, associate the cutting robot with the group; construct a time prediction axis for each group for time prediction. First, use the time when the cutting robot moves to the working point of the starting working curve of the assigned group as the starting prediction, and then determine the working time of each working curve in the group in sequence according to the pre-configured working rate; determine the transition time between each working time according to the pre-configured connection speed (the moving speed of the cutting robot from the completion of cutting one working curve to moving to another working curve); then add the transition time between the working times of two working curves, so as to form the working time corresponding to each group.

[0063] Among them, associating the cutting robot with the group includes: performing random allocation and associating the cutting robot with the group in the cutting robot-group correspondence of the allocation scheme with the minimum time for all cutting robots to move to the working point of the starting working curve of the assigned group.

[0064] The analysis group with the smallest difference in the estimated working time of each subgroup in the analysis group is used as the final allocation basis. Each subgroup in the analysis group finally determined as the allocation basis is allocated to each cutting robot to achieve the best work allocation, improving the machine utilization rate and work efficiency.

[0065] The present invention also provides a retired blade field cutting system based on a cutting robot, as Figure 3 shown, including: a scanning and building module 1, a positioning module 2, a path analysis module 3 and a control module 4; wherein, the scanning and building module 1 acquires three-dimensional scanning data of the retired blade and constructs a blade model using the three-dimensional scanning data; the positioning module 2 positions the retired blade to determine the relative position between the cutting robot and the retired blade; the path analysis module 3 comprehensively analyzes the blade model and the relative position between the cutting robot and the retired blade to determine a cutting path; the control module 4 controls the cutting robot to perform cutting based on the cutting path.

[0066] Among them, the three-dimensional scanning data is obtained by scanning the retired blade with a laser galvanometer stereo industrial camera.

[0067] Among them, positioning the retired blade is achieved based on the positioning data of the cutting robot and the coordinate mapping corresponding to the three-dimensional scanning data.

[0068] Among them, the steps for determining the cutting path are as follows:

[0069] Analyze the blade model to determine at least one dividable area;

[0070] Based on the pre-configured requirement target, determine the segmentation units within each dividable area;

[0071] Based on the edge lines of each dividable area and the edge lines of each segmentation unit, obtain a segmentation meridian map on the blade model;

[0072] Generate a cutting path according to the closed curves in the segmentation meridian map.

[0073] Among them, the steps for determining the dividable area are as follows:

[0074] Obtain the production data and usage data of the blade;

[0075] Based on the production data and usage data, evaluate each position in the blade model;

[0076] The area composed of the positions that pass the evaluation is used as the dividable area.

[0077] Obviously, those skilled in the art can make various modifications and variations to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalent technologies, the present invention is also intended to include these modifications and variations.

Claims

1. A method for field cutting of retired blades based on a cutting robot, characterized in that, Including: Obtaining three-dimensional scanning data of a decommissioned blade and constructing a blade model using the three-dimensional scanning data; Positioning the decommissioned blade to determine the relative position between the cutting robot and the decommissioned blade; Comprehensively analyzing the blade model and the relative position between the cutting robot and the decommissioned blade to determine the cutting path; Controlling the cutting robot to perform cutting based on the cutting path.

2. The field cutting method for retired blades based on a cutting robot as claimed in claim 1, wherein The three-dimensional scanning data is obtained by scanning the decommissioned blade with a laser galvanometer stereo industrial camera.

3. The field cutting method for retired blades based on a cutting robot according to claim 1, characterized in that Positioning the decommissioned blade is achieved based on the positioning data of the cutting robot and the coordinate mapping corresponding to the three-dimensional scanning data.

4. The field cutting method for retired blades based on a cutting robot according to claim 1, characterized in that The steps for determining the cutting path are as follows: Analyzing the blade model to determine at least one dividable area; Determining the segmentation units within each dividable area based on pre-configured requirement objectives; Obtaining a segmentation meridian map on the blade model based on the edge lines of each dividable area and the edge lines of each segmentation unit; Generating the cutting path according to the closed curves in the segmentation meridian map.

5. The method for field cutting of retired blades based on a cutting robot according to claim 4, wherein The steps for determining the dividable area are as follows: Obtaining the production data and usage data of the blade; Evaluating each position in the blade model based on the production data and usage data; Taking the area composed of the positions that pass the evaluation as the dividable area.

6. A field cutting system for retired blades based on a cutting robot, characterized in that Including: A scanning and construction module, a positioning module, a path analysis module, and a control module; among them, the scanning and construction module obtains three-dimensional scanning data of a decommissioned blade and constructs a blade model using the three-dimensional scanning data; the positioning module positions the decommissioned blade to determine the relative position between the cutting robot and the decommissioned blade; The path analysis module comprehensively analyzes the blade model and the relative position between the cutting robot and the decommissioned blade to determine the cutting path; the control module controls the cutting robot to perform cutting based on the cutting path.

7. The field cutting system for retired blades based on a cutting robot according to claim 6, wherein The three-dimensional scanning data is obtained by scanning the decommissioned blade with a laser galvanometer stereo industrial camera.

8. The field cutting system for retired blades based on a cutting robot according to claim 6, wherein, Positioning the decommissioned blade is achieved based on the positioning data of the cutting robot and the coordinate mapping corresponding to the three-dimensional scanning data.

9. The field cutting system for retired blades based on a cutting robot according to claim 6, characterized in that, The steps for determining the cutting path are as follows: Analyzing the blade model to determine at least one dividable area; Determining the segmentation units within each dividable area based on pre-configured requirement objectives; Obtaining a segmentation meridian map on the blade model based on the edge lines of each dividable area and the edge lines of each segmentation unit; Generating the cutting path according to the closed curves in the segmentation meridian map.

10. The field cutting system for retired blades based on a cutting robot as claimed in claim 9, characterized in that, The steps for determining the dividable area are as follows: Obtaining the production data and usage data of the blade; Evaluating each position in the blade model based on the production data and usage data; Taking the area composed of the positions that pass the evaluation as the dividable area.

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