Ultra-large component electric arc additive system and method with surface detection and repair functions

Abstract

The invention relates to an ultra-large component electric arc additive system with surface detection and repair functions and a method. The system comprises a laser three-dimensional contour scanning system, a system control unit and an additive manufacturing and remelting repairing platform. The laser three-dimensional contour scanning system is used for compiling a robot detection path and simulating a track, and issuing an instruction to carry out laser contour three-dimensional scanning on the additive component after no error is reported; the system control unit is internally provided with an additive structural part original model, technological parameters of electric arc additive are controlled according to the additive structural part original model, data preprocessing and defect recognition are conducted on scanning data obtained by the laser three-dimensional contour scanning system, and positions and parameters of additive manufacturing and remelting repairing are controlled according to a defect recognition result. According to the method, the problems of insufficient surface precision, incomplete fusion defects and deformation of formed parts during arc additive manufacturing of large components are solved, so that the precision of additive forming is guaranteed, metallurgical defects are eliminated, and the additive quality is improved.

Description

Technical Field

[0001] The present invention belongs to the field of metal additive manufacturing, and in particular relates to an arc additive manufacturing system and method for a super-large component with surface detection and repair functions. Background Art

[0002] Weapons and major national projects have put forward higher requirements on product performance, cost and production cycle. However, traditional casting and forging processes are difficult to complete the complete manufacturing of large and complex structural parts. Large structural parts produced by traditional methods have low life and high cost. The metal manufacturing industry urgently needs to adopt new overall preparation technology to meet the core competitiveness requirements of future high-end equipment in the direction of large-scale, high reliability and long service life.

[0003] In recent years, electric arc additive manufacturing (WAAM) has attracted widespread attention at home and abroad due to its high efficiency and low cost. This technology uses electric arc as a heat source to melt wire material to achieve layer-by-layer deposition of metal components. It has the characteristics of short manufacturing process and high efficiency, and is particularly suitable for the manufacture of large and complex components.

[0004] During the arc additive manufacturing process, metal materials are heated to high temperatures and cooled rapidly, which may cause thermal stress accumulation and deformation inside and on the surface of the component, thereby affecting the geometric accuracy and dimensional stability of the workpiece. When manufacturing large metal workpieces, defects such as uneven composition or lack of fusion may occur due to factors such as differences in the quality of the original metal materials and improper setting of process parameters. In addition, the surface of the metal workpiece after arc additive manufacturing may have high roughness, granular structure or other defects, requiring surface treatment or subsequent processing operations to improve the surface quality.

[0005] In order to solve the problems of low surface accuracy, unfused defects and deformation of formed parts in the process of arc additive manufacturing of ultra-large components, there is an urgent need for detection and control methods to monitor the forming quality of ultra-large additive workpieces in real time. At present, the traditional arc additive laser scanning detection method usually adopts point-to-point laser 3D scanning, but for ultra-large workpieces, the scanning time is long, the measurement cost is high, and the point cloud data density will be affected, which may lead to insufficient detailed information. Summary of the invention

[0006] The purpose of the present invention is to provide an arc additive system and method for ultra-large components with surface detection and repair functions, in order to control the problems of low forming surface accuracy, easy generation of unfused defects and large deformation of formed structural parts in the process of arc additive manufacturing of meter-scale ultra-large components.

[0007] The technical solution to achieve the purpose of the present invention is: an arc additive system for ultra-large components with surface inspection and repair functions, including a laser three-dimensional profile scanning system, a system control unit, an additive manufacturing and remelting repair platform;

[0008] The laser 3D contour scanning system compiles the robot detection path and simulates the trajectory. If no error is reported, it will issue a command to perform laser contour 3D scanning on the additive component.

[0009] The system control unit is equipped with an original model of the additive structural part, and controls the process parameters of the arc additive according to the original model of the additive structural part. It also performs data preprocessing and defect identification on the scanning data obtained by the laser 3D profile scanning system, and controls the position and parameters of the additive manufacturing and remelting repair according to the defect identification results.

[0010] The robotic additive manufacturing and remelting repair platform enables additive manufacturing of ultra-large components.

[0011] Furthermore, the additive manufacturing and remelting repair platform includes: a power source, a robotic arm equipped with a plasma-melting electrode composite welding gun, a wire feeder, a shielding gas delivery device and a base for placing the super-large components to be additively manufactured.

[0012] Further, the laser three-dimensional profile scanning system includes a gantry, two sets of mechanical arms equipped with scanners, two trackers, two oppositely arranged ground rails, baffles, marking points arranged between the ground rails and the bases on the corresponding sides, and a ruler placement rod;

[0013] The gantry is arranged on the periphery of the base, and its cross-section is a rectangle matching the shape of the base; the baffle can be stored in the middle of the super-large component to be added. During scanning, the baffle descends to divide the area to be scanned into two separated areas. Each area is equipped with a group of robot arms equipped with scanners and a tracker. The tracker is slidably arranged on the ground rail, and the robot arm equipped with the scanner is arranged on the gantry and can realize three-dimensional movement.

[0014] Furthermore, the tracker is arranged on a ground rail through an embedded steel ball slide rail, and the tracker tracks and locates the fixed position of the scanner in real time through an optical tracker.

[0015] Furthermore, the placement direction of the scale is parallel to the test direction, 0.15L away from the additive structure, where L is the length of the additive structure, and the scale height is 400±50mm, that is, the distance between adjacent scales is d, where 1.0m≤d≤1.5m;

[0016] Marking points include reflective marking points S ij ,, coding mark point S i There are n reflective marking points on the ruler, j is the reflective marking point number, 1≤j≤n, i is the ruler code, i=1,2,3…; Coded marking point S i It is a dot-coded mark point i which is a scale code. It is a point set with coding information and can be recognized by the software, i=1,2,3….

[0017] A method for adding materials based on the above system comprises the following steps:

[0018] Step (1): Use a scanner to calibrate the ruler and the coded marking points S of the ruler around the additive base. i And reflective marking point S ij Perform tracking scans, collect and save the spatial coordinates G of all the marker points obtained by the scan ij (x,y,z)i=1,2,3…,1≤j≤n;

[0019] Step (2): importing the original structural component model into the system control unit, the system control unit adjusts the path and speed of the arc additive according to the original structural component model, and controls the robot arm to drive the welding gun to complete the N-layer additive task, N = 1, 2, 3...;

[0020] Step (3): Compile the robot detection path and simulate the trajectory. If there is no error, issue a command to start the device. The system control unit controls the expansion of the baffle. The laser profile scanning device runs in an automatic state and performs the scanning task according to the preset scanning path. Scanner A and scanner B are respectively equipped with tracker A and scanner B to scan the corresponding side areas, and the space array coordinates G of the marking point are used. ij (x, y, z) as the reference, calculate the three-dimensional coordinates M of each information point on the surface of the object n (x, y, z), n is the information point number, so as to obtain the three-dimensional scanning data of the surface;

[0021] Step (4): the original structural component model is transmitted to the system control unit, and the scanned data is pre-processed by noise reduction and smoothing; the pre-processed scanned data is imported into the system control unit for three-dimensional model reconstruction, and then compared with the original structural component model, and the processed data is subjected to defect identification through an iterative image processing algorithm, and thresholds or discrimination criteria are set, and areas exceeding these thresholds or not meeting the criteria are judged as defects, and the defects are rated, located and marked by calculating the geometric center boundary and feature points of the defective area;

[0022] Step (5): The system control unit can adjust the position and parameters of the additive manufacturing and remelting repair platform according to the defect level and position located and marked in step (4), and drive the plasma-melting electrode composite welding gun to perform remelting, repair and surface heat treatment tasks;

[0023] Step (6): After the remelting, repairing and surface heat treatment tasks are completed, the system control unit issues a command and activates the start button to perform a three-dimensional contour scan of the additive workpiece along the original set scanning path. After the scanning is completed, the point cloud is saved and the data is processed;

[0024] Step (7): Repeat steps (4) to (6) until the overall deformation of the additive workpiece is less than 2 mm and the surface accuracy is within the range of ±0.5 mm;

[0025] Step (8): Repeat steps (2)-(7) to complete the full-field contour measurement and repair, remelting and heat treatment tasks of the arc-added large component to obtain the arc-added component.

[0026] Furthermore, in step (3), when the scanning length is ≤ the maximum range DMAX of the device, a single scanner cooperates with the tracker to complete the laser contour three-dimensional scanning task;

[0027] When the maximum range of the device DMAX ≤ scanning length ≤ the maximum range of the device 2DMAX, it is necessary to use marking points and ruler placement rods to perform global photographic scanning measurement.

[0028] Furthermore, in step (3), "using the coordinates of the space array of the marking point G ij (x, y, z) as the reference, calculate the three-dimensional coordinates M of each information point on the surface of the object n (x, y, z), n is the information point number, so as to obtain the three-dimensional scanning data of the surface" specifically:

[0029] M 1 , M, ···, M N is a real point on the surface contour of the additive workpiece. The ideal plane is obtained by fitting the real points by the least squares method. The fitting plane is expressed by the following formula:

[0030] Ax+By+Cz+D=0

[0031] Where A, B, C and D are plane fitting coefficients;

[0032] The deviation between each surface appearance point and the fitting plane is formulated as:

[0033]

[0034] The workpiece surface roughness is defined as:

[0035]

[0036] The threshold of surface roughness R was set to 0.5 mm in the iterative image processing algorithm;

[0037] Laser profile 3D scanning converts the points on the laser bar in the image coordinate system into the world coordinate system, and obtains the 3D coordinates for comparison with the original 3D model data; the correlation formula between the image coordinate system and the world coordinate system is:

[0038]

[0039] In the formula, (u0 ,v 0 ) represents a point in the image coordinate system, (X w , Y w , Z w ) represents a point in the world coordinate system; the scale factor is s, and R and T represent the rotation matrix and translation vector respectively, (u 0 、v 0 ) is the principal point coordinate, α and β are the scale factors of the image u-axis and v-axis respectively, and γ represents the inclination between the two axes; based on camera calibration and laser plane fitting, the points of the surface contour in the image are reconstructed at Z w Under the assumption that =0, the model is simplified as follows:

[0040]

[0041] where r 1 and r 2 is the column vector of the rotation matrix R, R = [r 1 、r 2 、r 3 ];

[0042] Assume the correlation between the camera coordinate systems Z w =0, then the world coordinate system is:

[0043]

[0044] Combining formulas (4) and (5), the points on the laser bar in the camera coordinate system can be reconstructed, and then the points in the image coordinate system obtained by laser scanning can be converted to the world coordinate system.

[0045] Furthermore, in step (4), "identifying defects on the processed data by iterative image processing algorithm, setting thresholds or discrimination criteria, determining areas exceeding these thresholds or not meeting the criteria as defects, and rating, locating and marking defects by calculating the geometric center boundary and feature points of the defective area" is specifically:

[0046] When it is identified that the absolute value of the surface roughness of an area in the reconstructed three-dimensional model is greater than a threshold value of 0.5 mm, the area is marked as a rough interface Ya, a=1, 2, 3, ...;

[0047] When it is identified that there is a region where surface texture details of the reconstructed three-dimensional model are missing, the region is marked as an unfused region Rb, b=1, 2, 3, ...;

[0048] When it is identified that there is a region of the reconstructed three-dimensional model that is deformed by more than 2 mm, the region is marked as a region with large deformation Bk (k=1, 2, 3, . . . ).

[0049] An ultra-large arc additive component is prepared by the above method.

[0050] Compared with the prior art, the present invention has the following significant advantages:

[0051] (1) By precisely controlling the position and angle of the laser beam and combining it with a high-resolution camera for data collection, detailed and accurate surface morphology information can be obtained, and a large number of data points can be quickly acquired, which is particularly important for large additive structures. Compared with traditional manual measurement or trigger scanning methods, tracking 3D laser scanning can complete data collection tasks more efficiently. Large additive structures often have complex geometric shapes and curved surface features, and tracking 3D laser scanning technology has strong adaptability and can measure complex curved surfaces and accurately capture various detailed shapes. The tracking system can track the position and posture of the laser scanner on the surface of the component in real time, helping operators to accurately locate the scanning area, automatically generate complete scanning data, and reduce human errors and operation time. The raw data is processed by subsequent data processing software to extract the geometric features, dimensional parameters and other information of the additive workpiece for visualization, comparison and analysis. These advantages make it an ideal choice for accurate measurement and quality control of ultra-large additive structures.

[0052] (2) Provide an automated surface inspection solution for ultra-large arc additive manufacturing, using a dual gantry laser 3D measurement system, applying intelligent optical tracking measurement technology, high-quality optical equipment, and high-precision scanners to overcome the limitations of traditional marker point scanning technology; the system can achieve ultra-high-precision dynamic 3D measurement of additive workpieces without the need for point sticking, support robot offline programming and simulation, and achieve manual teaching-free operation; with the independently developed algorithm and control system, the robot can be linked with the external axis to meet the overall automated online inspection needs for meter-level ultra-large additive components, and is suitable for dimensional measurement, additive and subtractive materials, reverse engineering, and other aspects, providing quality assurance for the fully automated additive process; for some blind spots in the field of vision, handheld point scanning and tracking 3D ball scanning point cloud data splicing are used to achieve complete scanning functions for ultra-large additive components; the inspection data can be evaluated for size, and the overall data can be used for subsequent processing, providing quality assurance for the automated additive process.

[0053] (3) Automated 3D scanning technology can obtain 3D data of the contours of ultra-large arc additive workpieces with high precision and speed; compared with traditional manual inspection methods, automated scanning provides more accurate, comprehensive and objective data, which helps to evaluate product quality; with the feedback system, it can quickly obtain a large amount of data, conduct in-depth analysis and mining, identify potential quality problems, monitor changes and defects in workpieces during arc manufacturing, and realize real-time processing and analysis, quickly discover and solve problems, improve quality inspection efficiency, save human resources and time costs, improve production efficiency and quality, improve process parameters, optimize production processes, and continuously improve; data-driven decision-making can improve process stability and consistency. Arc additive and remelting repair involve arcs and high-temperature environments, which pose safety risks; the application of automated 3D scanning systems can effectively reduce the chances of personnel coming into contact with high-risk environments and improve safety levels.

[0054] (4) After the data point cloud is saved, it is transmitted to the system control unit for 3D model reconstruction and comparison with the original additive model. The processed data is identified by an iterative image processing algorithm and compared with the original structural model in the system control unit. After rating the relevant feature points, the detection data set is output. The 3D data processing unit is used to rate, locate and mark the defects by calculating the geometric center boundary or other feature points of the defect area. The system control unit can automatically adjust the position and parameters of the additive manufacturing and remelting repair device according to the above-mentioned located and marked defect positions, and drive the plasma-melting electrode composite welding gun to perform remelting, repair and surface heat treatment tasks; through the alternating operation of laser 3D scanning and surface remelting repair equipment, until the component has no obvious defects and the surface accuracy is ±0.5mm, it is expected to control the problems of low forming surface accuracy, easy generation of unfused defects and large deformation of formed parts in the process of arc additive manufacturing of meter-level super-large components. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] Figure 1 It is a schematic diagram of the method flow of the present invention.

[0056] Figure 2 It is an arc additive manufacturing platform.

[0057] Figure 3 It is an arc additive remelting repair platform.

[0058] Figure 4 It is a schematic diagram of the on-site layout of the system diagram of the present invention.

[0059] Figure 5 It is an enlarged schematic diagram of the on-site layout of the poles and trackers with marking points of the present invention.

[0060] Notes on the attached drawings:

[0061] 1-wire feeder, 2-additive power supply, 3-teach pendant, 4-control cabinet, 5-shielding gas delivery device, 6-base, 7-substrate, 8-plasma-melting electrode composite welding gun, 9-workpiece, 10-computer workstation, 11-industrial robot arm A, 12-scanner A, 13-tracker A, 14-industrial robot arm B, 15-scanner B, 16-tracker B, 17-gantry A, 18-ground rail A, 19-additive remelting repair robot C, 20-additive remelting repair robot D, 21-gantry B, 22-ground rail B, 23-baffle, 24-marking point and ruler placement rod. DETAILED DESCRIPTION

[0062] The present invention is further described in detail below in conjunction with the accompanying drawings.

[0063] The present invention is an equipment and method for surface detection and repair of large arc additive components. It includes a fully automated laser contour scanning system, a system control unit, and a robotic additive manufacturing and remelting repair platform; for every N layers of additive, a fully automated laser contour scanning system is used to perform contour scanning on the additive component, and the data is imported into the system control unit for three-dimensional reconstruction after preprocessing. The defects are rated, located, and marked by comparing the iterative image processing algorithm with the original model of the component imported into the system control unit. The control unit controls the arc remelting device to perform repairs based on the above information. The laser three-dimensional scanning and remelting repair equipment are operated alternately until the component has no obvious defects and the surface accuracy is ±0.5mm, in order to control the problems of low forming surface accuracy, easy generation of unfused defects, and large deformation of formed parts in the process of arc additive manufacturing of ultra-large components. The present invention is used to ensure the accuracy of additive forming, eliminate metallurgical defects, and improve the quality of additives. (See Figure 1 ).

[0064] like Figures 2 to 4 As shown, an equipment for surface inspection and repair of large arc additive components includes a laser profile scanning system, a system control unit, a robot additive manufacturing and remelting repair platform.

[0065] The scanning simulation unit of the laser 3D contour scanning system compiles the robot detection path and simulates the trajectory. If no error is reported, it will issue instructions to perform laser contour 3D scanning on the additive component.

[0066] The scanned data is preprocessed, including noise reduction, smoothing and other operations, to improve data quality. These preprocessing steps help eliminate interference factors in the scanned data and highlight defect features.

[0067] The system control unit is responsible for the operation and data processing of the entire device. In the additive stage, the control unit adjusts the arc additive path and speed and other process parameters according to the size and shape of the original structural part model; in the three-dimensional data processing stage, the control unit processes and analyzes the scan data according to the preset algorithm; in the remelting repair stage, the control unit adjusts the parameters of the arc remelting device according to the type and size of the defect to achieve the best repair effect.

[0068] The robot additive manufacturing and remelting repair platform includes: a wire feeder 1, an additive power supply 2, a teaching pendant 3, a control cabinet 4, a protective gas device 5, a base 6, a base plate 7, a plasma-melting electrode composite welding gun 8, etc. (see Figure 2 and Figure 3 ).

[0069] The control cabinet controls the wire feeder 4, the additive remelting repair robot C19 and the additive remelting repair robot D20, the shielding gas device 5 and the plasma-melting electrode composite welding gun 8, etc.

[0070] The teaching pendant 3 is a remote controller used to memorize and store the mechanical motion behavior of the additive remelting repair robot, which can realize the human-machine interaction function; the complete 3D model of the additive component is imported, and the system control unit controls the software to plan the optimal path for additive and generate the corresponding slice file, which is then imported to generate the additive program. The plasma-melting electrode composite welding gun 8 is installed under the robot C19 and the robot D 20 to form an additive remelting repair robot. The robot additive manufacturing and remelting repair platform is used for additive and remelting repair of workpieces (see Figure 3 );

[0071] The fully automated laser 3D profile scanning system includes: a six-axis industrial robot arm and scanner, a tracker, a ground rail, a baffle, a marking point and a ruler placement rod (see Figure 4 ).

[0072] The main crossbeam of the gantry structure is equipped with electrical control cabinets, drive motors and other equipment, and also carries the vertical beam and industrial robot arm. The vertical beam, i.e., the Z-axis motion system, is connected to the crossbeam through a guide rail slider, and the vertical beam is connected to the robot arm through a flange. A clamping tool is added to the end of the industrial robot arm A11 and the industrial robot arm B14, and the laser contour scanner A12 and scanner B15 are integrated into the robot system respectively, and the robot is used to simulate the operator to perform visual inspection operations. The embedded steel balls under the tracker A13 and the tracker B16 are respectively installed on the ground rail A18 and the ground rail B 22 through the steel ball slide rail. The baffle 23 is fixed on the gantry beam. It can be retracted and unfolded through the reel controlled by the system control unit. It is in a retracted state during additive work, and when the laser contour is measured in three dimensions, the baffle is unfolded to divide the additive workpiece into two sides, which serves as a shielding device when the point cloud data of the two scanners are spliced ​​to prevent the two from interfering with each other; at this time, the marking point and the ruler placement rod 24 are placed on both sides of the additive workpiece, and the placement direction of the ruler should be parallel to the test direction, 0.15L (L is the length of the additive structure), and the ruler placement cannot be deformed. The ruler length is 400mm, and the applicable accuracy range is 2.5-3.5 times of itself, that is, the distance between adjacent rulers is d (1.0m≤d≤1.5m), and the number of rulers can be set according to the size of the additive structure (see Figure 5 ).

[0073] When the scanning length ≤ the maximum range of the device D MAX When the laser profile is scanned, a single scanner and a tracker can complete the task of 3D laser scanning.

[0074] When the device has a maximum range of D MAX ≤Scan length≤Maximum range of the device 2D MAX When measuring, it is necessary to use marking points and rulers to perform global photographic scanning measurement.

[0075] The marking points include reflective marking points and coded marking points. The reflective marking points refer to the measuring points at both ends of the pasted ruler. The coded marking points used by the system are dot-shaped coded marking points, which refer to a set of points with certain arrangement rules and coded information, which can be recognized by the software and display their numbers.

[0076] The technical solution to achieve the purpose of the present invention is: a method for adding materials using equipment for surface inspection and repair of large components using arc additive, comprising the following steps:

[0077] Step (1): Use a scanner to calibrate the ruler and the coded marking points S of the ruler around the additive platform. i And reflective marking point S ij Perform tracking scans, collect and save the spatial coordinates G of all the marker points obtained by the scan ij(x,y,z)(i=1,2,3…,1≤j≤18);

[0078] Step (2): importing the original structural component model into the system control unit, the system control unit adjusts the process parameters such as the path and speed of the arc additive according to the size and shape of the original structural component model, and controls the industrial robot arm to drive the welding gun to complete the N-layer additive task, N = 1, 2, 3...;

[0079] Step (3): In the scanning simulation unit, the robot detection path is compiled and the trajectory is simulated. If there is no error, the command is issued to start the device. The system control unit controls the expansion of the baffle. The laser profile scanning device runs in an automatic state and performs the scanning task according to the preset scanning path. The scanners A and B are respectively equipped with trackers A and B to scan their respective areas, and the space array coordinates G of the marking point are used. ij (x, y, z) as the reference, and calculate the three-dimensional coordinates M of each information point on the surface of the object according to the geometric relationship between the laser emitter and the tracker n (x, y, z) (n is the information point number) to obtain the three-dimensional scanning data of the surface.

[0080] Step (4): The original model of the additive structure is transmitted to the system control unit, and the three-dimensional data obtained by laser contour scanning is saved and transmitted to the three-dimensional data processing unit, and the scanned data is pre-processed by noise reduction and smoothing. The pre-processed scanned data is imported into the system control unit for three-dimensional model reconstruction, and then compared with the original model of the structure. The processed data is subjected to defect identification through an iterative image processing algorithm. Certain thresholds or discrimination criteria are set in the algorithm, and areas that exceed these thresholds or do not meet the criteria are judged as defects or areas with large deformation. After the above areas are identified, the three-dimensional data processing unit can be used to calculate the geometric center boundary or other feature points of the defect area to rate, locate and mark the defects.

[0081] Step (5): The system control unit can automatically adjust the position and parameters of the additive manufacturing and remelting repair device according to the defect position located and marked as above, and drive the plasma-melting electrode composite welding gun to perform remelting, repair and surface heat treatment tasks.

[0082] Step (6): After the remelting, repair and surface heat treatment tasks are completed, the system control unit issues a command and activates the start button to perform a three-dimensional contour scan of the additive workpiece along the original set scanning path. After the scanning is completed, the point cloud is saved and the data is processed.

[0083] Step (7): Repeat steps (4) to (6) until the additive workpiece is well formed, the overall deformation is less than 2 mm, and the surface accuracy is within the range of ±0.5 mm;

[0084] Step (8): Repeat steps (2)-(7) to complete the full-field contour measurement and repair, remelting and heat treatment tasks of the arc additive large component to ensure that the arc additive component with good quality is finally obtained.

[0085] In step (1) and step (3), the marking points S around the component are automatically scanned. ij Scan and save, which is necessary for the subsequent two scanners to scan their respective areas. Because the two share the same marker point, the spatial position of the point cloud imaging is in the same coordinate system. If the inside of the component needs to be scanned, a handheld 3D scanner is used, and point-by-point scanning is used to solve the problem of blind spots in the field of vision. The splicing of the internal point cloud and the external point cloud depends on the above common marker points.

[0086] In step (4), defects are identified on the processed data through an iterative image processing algorithm and compared with the original structural model in the system control unit. The defects are rated, located and marked by calculating the geometric center boundary or other feature points of the defect area using a three-dimensional data processing unit.

[0087] When the absolute value of the surface roughness of the reconstructed 3D model is greater than the threshold value of 0.5 mm, the area is marked as a rough interface Y. a (a=1, 2, 3…).

[0088] When it is identified that the reconstructed 3D model has a region where surface texture details are missing, the region is marked as an unfused region R. b (b=1, 2, 3...).

[0089] When it is identified that there is a region of the reconstructed 3D model with deformation exceeding 2 mm, the region is marked as a region with large deformation B. k (k=1, 2, 3...).

[0090] A large arc additive component is prepared by the above method.

[0091] In order to further verify the effect, multiple groups of comparative experiments were carried out, and the parameters in each experimental example were kept consistent. The following example is used to illustrate: The embodiment specifically includes the following steps:

[0092] The experiment used an arc additive manufacturing platform composed of a welding robot produced by ABB of Switzerland and a CMT5000Advanced welding power arc produced by Fonis of Austria. The study used 14Ni3Cr3Mo1MnTiAl ultra-high-strength steel wire with a diameter of 1.6mm. Before the experiment, the single-pass welding forming process was studied, and it was found that when the shielding gas was 99% Ar, the shielding gas flow was 18L / min, the welding current was 160A, the welding voltage was 18V, the welding speed was 4mm / s, and the wire feeding speed was 6.7m / min, the additive process was stable and the weld was beautiful. Based on the above process parameters, a reciprocating additive path was used to control the interlayer temperature at 150°C to prepare metal components with a size of 6000mm*4000mm*180mm on a 316L stainless steel substrate.

[0093] Step (1): Use a scanner to calibrate the ruler and the coded marking points S of the ruler around the additive platform. i And reflective marking point S ij Perform tracking scans, collect and save the spatial coordinates G of all the marker points obtained by the scan ij (x,y,z)(i=1,2,3...,1≤j≤18).

[0094] Step (2): The original structural component model is imported into the system control unit. The system control unit adjusts the process parameters such as the path and speed of the arc additive according to the size and shape of the original structural component model, and controls the industrial robot arm to drive the welding gun to complete the N-layer additive task, N = 1, 2, 3...

[0095] Step (3): In the scanning simulation unit, the robot detection path is compiled and the trajectory is simulated. If there is no error, the command is issued to start the device. The system control unit controls the expansion of the baffle. The laser profile scanning device runs in an automatic state and performs the scanning task according to the preset scanning path. The scanners A and B are respectively equipped with trackers A and B to scan their respective areas, and the space array coordinates G of the marking point are used. ij (x, y, z) as the reference, and calculate the three-dimensional spatial coordinates M of each information point on the surface of the object according to the geometric relationship between the laser emitter and the tracker n (x, y, z) (n is the information point number) to obtain the three-dimensional scanning data of the surface.

[0096] Step (4): The original model of the additive structure is transmitted to the system control unit, and the three-dimensional data obtained by laser contour scanning is saved and transmitted to the three-dimensional data processing unit, and the scanned data is pre-processed by noise reduction and smoothing. The pre-processed scanned data is imported into the system control unit for three-dimensional model reconstruction, and then compared with the original model of the structure. The processed data is subjected to defect identification through an iterative image processing algorithm. Certain thresholds or discrimination criteria are set in the algorithm, and areas that exceed these thresholds or do not meet the criteria are judged as defects or areas with large deformation. After the above areas are identified, the three-dimensional data processing unit can be used to calculate the geometric center boundary or other feature points of the defect area to rate, locate and mark the defects.

[0097] Step (5): The system control unit can automatically adjust the position and parameters of the additive manufacturing and remelting repair device according to the defect position located and marked as above, and drive the plasma-melting electrode composite welding gun to perform remelting, repair and surface heat treatment tasks.

[0098] Step (6): After the remelting, repair and surface heat treatment tasks are completed, the system control unit issues a command and activates the start button to perform a three-dimensional contour scan of the additive workpiece along the original set scanning path. After the scanning is completed, the point cloud is saved and the data is processed.

[0099] Step (7): Repeat steps (4)-(6) until the additive workpiece is well formed, the overall deformation is less than 2 mm, and the surface accuracy is within the range of ±0.5 mm.

[0100] Step (8): Repeat steps (2)-(7) to complete the full-field contour measurement and repair, remelting and heat treatment tasks of the arc additive large component to ensure that the arc additive component with good quality is finally obtained.

Claims

1. An arc additive system for ultra-large components with surface inspection and repair functions, characterized in that: Includes laser 3D profile scanning system, system control unit, additive manufacturing and remelting repair platform; The laser 3D contour scanning system compiles the robot detection path and simulates the trajectory. If no error is reported, it will issue a command to perform laser contour 3D scanning on the additive component. The system control unit is equipped with an original model of the additive structural part, and controls the process parameters of the arc additive according to the original model of the additive structural part. It also performs data preprocessing and defect identification on the scanning data obtained by the laser 3D profile scanning system, and controls the position and parameters of the additive manufacturing and remelting repair according to the defect identification results. The robotic additive manufacturing and remelting repair platform enables additive manufacturing of ultra-large components.

2. The arc additive system for ultra-large components according to claim 1, characterized in that: The additive manufacturing and remelting repair platform includes: a power source, a robotic arm equipped with a plasma-melting electrode composite welding gun, a wire feeder, a shielding gas delivery device and a base for placing super-large components to be added.

3. The arc additive system for ultra-large components according to claim 2, characterized in that: The laser 3D profile scanning system includes a gantry, two sets of robotic arms equipped with scanners, two trackers, two oppositely arranged ground rails, baffles, marking points and scale placement rods arranged between the ground rails and the bases on the corresponding sides; The gantry is arranged on the periphery of the base, and its cross-section is a rectangle matching the shape of the base; the baffle can be stored in the middle of the super-large component to be added. During scanning, the baffle descends to divide the area to be scanned into two separated areas. Each area is equipped with a group of robot arms equipped with scanners and a tracker. The tracker is slidably arranged on the ground rail, and the robot arm equipped with the scanner is arranged on the gantry and can realize three-dimensional movement.

4. The arc additive system for ultra-large components according to claim 3, characterized in that: The tracker is set on the ground rail through an embedded steel ball slide rail. The tracker tracks and locates the scanner's fixed point in real time through an optical tracker.

5. The arc additive system for ultra-large components according to claim 4, characterized in that: The ruler is placed in parallel with the test direction, 0.15L away from the additive structure, where L is the length of the additive structure, and the ruler height is 400±50mm, that is, the distance between adjacent rulers is d, where 1.0m≤d≤1.5m; Marking points include reflective marking points S ij ,, coding mark point S i There are n reflective marking points on the ruler, j is the reflective marking point number, 1≤j≤n, i is the ruler code, i=1,2,3…; Coded marking point S i It is a dot-coded mark point i which is a scale code. It is a point set with coding information and can be recognized by the software, i=1,2,3….

6. A method for adding materials based on the system of claim 5, characterized in that: The steps include: Step (1): Use a scanner to calibrate the ruler and the coded marking points S of the ruler around the additive base. i And reflective marking point S ij Perform tracking scans, collect and save the spatial coordinates G of all the marker points obtained by the scan ij (x,y,z)i=1,2,3…,1≤j≤n; Step (2): importing the original structural component model into the system control unit, the system control unit adjusts the path and speed of arc additive according to the original structural component model, and controls the robot arm to drive the welding gun to complete N-layer additive tasks, N = 1, 2, 3...; Step (3): Compile the robot detection path and simulate the trajectory. If there is no error, issue a command to start the device. The system control unit controls the expansion of the baffle. The laser profile scanning device runs in an automatic state and performs the scanning task according to the preset scanning path. Scanner A and scanner B are respectively equipped with tracker A and scanner B to scan the corresponding side areas, and the space array coordinates G of the marking point are used. ij (x, y, z) as the reference, calculate the three-dimensional coordinates M of each information point on the surface of the object n (x, y, z), n is the information point number, so as to obtain the three-dimensional scanning data of the surface; Step (4): the original structural component model is transmitted to the system control unit, and the scanned data is pre-processed by noise reduction and smoothing; the pre-processed scanned data is imported into the system control unit for three-dimensional model reconstruction, and then compared with the original structural component model, and the processed data is subjected to defect identification through an iterative image processing algorithm, and thresholds or discrimination criteria are set, and areas exceeding these thresholds or not meeting the criteria are judged as defects, and the defects are rated, located and marked by calculating the geometric center boundary and feature points of the defective area; Step (5): The system control unit can adjust the position and parameters of the additive manufacturing and remelting repair platform according to the defect level and position located and marked in step (4), and drive the plasma-melting electrode composite welding gun to perform remelting, repair and surface heat treatment tasks; Step (6): After the remelting, repairing and surface heat treatment tasks are completed, the system control unit issues a command and activates the start button to perform a three-dimensional contour scan of the additive workpiece along the original set scanning path. After the scanning is completed, the point cloud is saved and the data is processed; Step (7): Repeat steps (4) to (6) until the overall deformation of the additive workpiece is less than 2 mm and the surface accuracy is within the range of ±0.5 mm; Step (8): Repeat steps (2)-(7) to complete the full-field contour measurement and repair, remelting and heat treatment tasks of the arc-added large component to obtain the arc-added component.

7. The method according to claim 6, characterized in that In step (3), when the scanning length is less than or equal to the maximum range DMAX of the device, a single scanner cooperates with a tracker to complete the laser contour three-dimensional scanning task; When the maximum range of the device DMAX ≤ scanning length ≤ the maximum range of the device 2DMAX, it is necessary to use marking points and ruler placement rods to perform global photographic scanning measurement.

8. The method according to claim 7, characterized in that In step (3), the coordinates of the space array of the marking point G ij (x, y, z) as the reference, calculate the three-dimensional coordinates M of each information point on the surface of the object n (x, y, z), n is the information point number, so as to obtain the three-dimensional scanning data of the surface" specifically: M1,M、···、M N is a real point on the surface contour of the additive workpiece. The ideal plane is obtained by fitting the real points by the least squares method. The fitting plane is expressed by the following formula: Ax+By+Cz+D=0 Where A, B, C and D are plane fitting coefficients; The deviation between each surface appearance point and the fitting plane is formulated as: The workpiece surface roughness is defined as: The threshold of surface roughness R was set to 0.5 mm in the iterative image processing algorithm; Laser profile 3D scanning converts the points on the laser bar in the image coordinate system into the world coordinate system, and obtains the 3D coordinates for comparison with the original 3D model data; the correlation formula between the image coordinate system and the world coordinate system is: Where (u0, v0) represents a point in the image coordinate system, (X w , Y w , Z w ) represents a point in the world coordinate system; The scale factor is s, while R and T represent the rotation matrix and translation vector respectively, (u0, v0) are the coordinates of the principal point, α and β are the scale factors of the image u-axis and v-axis respectively, and γ represents the inclination between the two axes; Based on camera calibration and laser plane fitting, the points of the surface contour in the image are reconstructed in Z w Under the assumption that =0, the model is simplified as follows: Where r1 and r2 are column vectors of the rotation matrix R, R = [r1, r2, r3]; Assume the correlation between the camera coordinate systems Z w =0, then the world coordinate system is: Combining formulas (4) and (5), the points on the laser bar in the camera coordinate system can be reconstructed, and then the points in the image coordinate system obtained by laser scanning can be converted to the world coordinate system.

9. The method according to claim 8, characterized in that In step (4), "defect identification is performed on the processed data by iterative image processing algorithm, thresholds or discrimination criteria are set, areas exceeding these thresholds or not meeting the criteria are judged as defects, and defects are rated, located and marked by calculating the geometric center boundary and feature points of the defective area" is specifically: When it is identified that the absolute value of the surface roughness of an area in the reconstructed three-dimensional model is greater than a threshold value of 0.5 mm, the area is marked as a rough interface Ya, a=1, 2, 3, ...; When it is identified that there is a region where surface texture details of the reconstructed three-dimensional model are missing, the region is marked as an unfused region Rb, b=1, 2, 3, ...; When it is identified that there is a region of the reconstructed three-dimensional model that is deformed by more than 2 mm, the region is marked as a region with large deformation Bk (k=1, 2, 3, . . . ).

10. An ultra-large arc additive component, characterized in that: The method is prepared by any one of claims 6 to 9.

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