A 3D printing composite machine tool and its dynamic control method

Abstract

The present invention relates to the technical field of 3D printing machine tools, and it relates to a 3D printing composite machine tool and a dynamic control method thereof, comprising a bed, an X-axis moving component, a Z-axis moving component, a Y-axis moving component, a 3D printing head, a swing component, a rotating component, a feeding component, and a processing head. By importing 3D model data, a printing processing path is generated, the 3D printer is started, and parts are printed layer by layer according to a preset path. The original 3D model data and data collected by a camera are compared and analyzed, and then the part processing data is output. The control center converts the data into dynamic parameters of the machine tool, generates a topological path, and transmits the compensation parameters to the control center. The spatial position of the machine tool tool is adjusted in real time through a PID control unit. The present invention ensures the high quality of the processing process through dynamic monitoring and real-time error compensation, integrates real-time monitoring and feedback mechanisms, can detect and correct deviations in time during the processing process, and improves the reliability of the finished product.

Description

Technical Field

[0001] The present invention relates to the technical field of 3D printing machine tools, and more specifically, to a 3D printing composite machine tool and a dynamic control method thereof. Background Art

[0002] Traditional manufacturing methods, such as CNC machining, primarily utilize subtractive processes, removing material from a raw material to create the desired shape. However, with technological advancements, 3D printing has gradually become a valuable addition to the manufacturing industry. 3D printing utilizes an additive process, building parts by layering material. This technology offers advantages such as high design freedom, the ability to merge parts, lightweight construction, rapid prototyping, and reduced programming time.

[0003] In recent years, the integration of 3D printing technology and CNC machine tool technology has become a mainstream trend in the manufacturing industry. By combining additive manufacturing technology with CNC technology, near-net-shape parts can be achieved, while machining can ensure machining accuracy and surface quality.

[0004] For example, the 3D printing and milling compound machine tool disclosed in announcement number CN105196063A has both 3D printing and milling functions. During the 3D printing process, the parts being printed can be precisely milled through the indexing of the CNC rotary table, making it easy to obtain 3D printed parts with high surface quality (including internal and external surfaces).

[0005] For example, announcement number CN106964993B discloses a composite 3D printing equipment and method for CMT and multi-axis CNC machine tools. Through a platform with two rotational degrees of freedom and the X, Y, and Z axis movement freedom of the forming drive mechanism, processing at any position in space can be achieved. By rotating the forming platform, the optimal angle between the workpiece and the welding gun or milling cutter can be adjusted to maximize the processing quality, while also minimizing or avoiding the presence of support structures.

[0006] The above two known existing technologies can perform refined post-processing on 3D printed products by setting them up on a machine tool. During use, the accuracy of 3D printing comes from the three-dimensional model file and its various parameters, especially after the 3D print head outputs the product. Although existing 3D printing and milling composite machine tools can perform milling during the 3D printing process, errors are still difficult to avoid in actual operation, especially in the processing of complex geometric shapes. Due to the lack of real-time monitoring and feedback mechanisms, deviations cannot be corrected in time during the processing process, resulting in unstable quality of the finished product.

[0007] Based on the above, there is currently a need for a set of machine tools and processing methods that can accurately and finely process the products after the 3D printing head outputs them. Summary of the Invention

[0008] In view of the shortcomings of the existing technology, the purpose of the present invention is to provide a reasonable and simple 3D printing composite machine tool and a dynamic control method thereof that can improve processing accuracy.

[0009] To achieve the above object, the present invention provides the following technical solutions:

[0010] A 3D printing composite machine tool comprises a bed, an X-axis moving component, a Z-axis moving component, a Y-axis moving component, a 3D printing head, a swing component, a rotating component, a feeding component, and a processing head.

[0011] The 3D printing head is movably connected to the outer wall of the processing machine body, and a guide rail and a cylinder that controls the sliding movement of the 3D printing head on the guide rail are installed on the outer wall of the processing machine body. A tool is detachably installed at the output end of the processing machine head.

[0012] The Z-axis moving assembly controls the movement of the processing head in the Z-axis direction, the X-axis moving assembly controls the movement of the processing head in the X-axis direction, and the Y-axis moving assembly controls the movement of the processing head in the Y-axis direction;

[0013] The X-axis moving assembly, Z-axis moving assembly, and Y-axis moving assembly all include servo motors, guide rails, and slides. The slides are placed on the guide rails so that the servo motors drive the slides to move on the guide rails.

[0014] The swing assembly includes a motor 1, a base and a swing table. The swing table and the base are rotatably connected. The output end of the motor 1 is connected to the swing table to control the swing table to rotate around the X-axis.

[0015] The rotating assembly includes a rotating table and a second motor placed in the swing table. The rotating table and the swing table are connected in rotation. The output end of the second motor is connected to the turntable to control the turntable to rotate around the Z axis.

[0016] A processing station for the print head to output products is formed on the top surface of the rotating table.

[0017] The feeding assembly includes a material box, a feeding pump, and a feeding pipe. The material box outputs the material through the 3D printing head to the processing station via the feeding pump and the feeding pipe.

[0018] A method for dynamically controlling a 3D printing composite machine tool comprises the following steps:

[0019] S1. Design and import 3D model data, generate printing processing paths, and calibrate the machine tool to ensure printing and processing accuracy;

[0020] S2. Set the printing parameters, start the 3D printer, print the parts layer by layer according to the preset path, and monitor the printing process in real time through sensors and cameras;

[0021] S3, compare and analyze the original 3D model data and the data collected by the camera and output the part processing data.

[0022] Based on the part processing data, the control center converts it into the dynamic parameters of the machine tool, generates a topological path based on the dynamic parameters, and calibrates the tool;

[0023] S4. Establish a compensation parameter model, transmit the compensation parameters to the control center, and adjust the spatial position of the machine tool tool in real time according to the compensation parameters through the PID control unit.

[0024] The present invention is further configured as follows: Step S4 specifically includes the following steps:

[0025] S41, starting the machine tool, setting a predetermined first gear speed according to the control center, controlling the tool to move according to the topological path to obtain a first running trajectory, and generating a first trajectory measurement map;

[0026] S42, according to the predetermined second gear speed set by the control center, controlling the tool to move according to the topological path to obtain a second running trajectory, and generating a second trajectory measurement graph;

[0027] S43, according to the predetermined third gear speed set by the control center, controlling the tool to move according to the topological path to obtain a third running trajectory, and generating a third trajectory measurement map;

[0028] S44, comparing the first trajectory measurement graph, the second trajectory measurement graph, and the third trajectory measurement graph with the topological path respectively to determine a path error interval;

[0029] S45. After inputting the obtained error interval value into the compensation parameter model for calculation, the controlled compensation parameter is output, and then the dynamics of the tool is controlled by the PID control unit.

[0030] The present invention is further configured as follows: the error compensation parameter model is:

[0031]

[0032]

[0033]

[0034] 、 、 Respectively represent the compensation coefficients in the X-axis, Y-axis and Z-axis directions, 、 They represent the tool errors in the X-axis, Y-axis and Z-axis directions at time t respectively.

[0035] The present invention is further configured as follows: the topology path generating step in step S3:

[0036] S31, Data Collection: Collect the contour data of 3D printed products through the camera,

[0037] S32, fitting point selection: calculate the contour curvature and select the point where the curvature change is greater than a certain threshold as the fitting point to facilitate tool processing;

[0038] S33, preliminary path planning: use the matching points to generate preliminary tool processing paths, using path planning Algorithms to connect these points,

[0039] S34, Path Optimization: Perform local optimization based on the preliminary path, refine the path through the gradient descent algorithm, reduce the curvature change, and make the tool follow the contour more accurately;

[0040] Use B-spline curves to smooth the path and reduce tool vibration and adjustment.

[0041] The present invention is further configured such that when it is determined in step S44 that the path error interval exceeds the originally set threshold, the process returns to step S32 and reselects the fitting point.

[0042] The present invention is further configured as follows: the specific steps of determining the path error interval in step S44 are:

[0043] S441, recording and synchronizing the first trajectory measurement graph, the second trajectory measurement graph, and the third trajectory measurement graph according to a unified time standard and format;

[0044] S442, calculating the difference between the actual path and the planned path for each collection point, and calculating basic statistics of the error data: including mean, standard deviation, and variance;

[0045] S443. Determine the error range based on the statistical analysis results of the error data.

[0046] Compared with the shortcomings of the prior art, the beneficial effects of the present invention are:

[0047] Through dynamic monitoring and real-time error compensation, processing accuracy is effectively improved, ensuring high quality of printing and processing. The integrated real-time monitoring and feedback mechanism can detect and correct deviations in time during the processing, improving the consistency and reliability of the finished product.

[0048] Adaptive control is achieved, which can adjust control parameters in real time according to processing conditions and adapt to different working conditions and environmental changes. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] Figure 1It is a structural schematic diagram of the present invention;

[0050] Figure 2 It is a process flow chart of the present invention. DETAILED DESCRIPTION

[0051] Reference Figures 1 to 2 The embodiments of the present invention are further described.

[0052] This embodiment specifically includes: a bed 1, an X-axis moving component 2, a Z-axis moving component 3, a Y-axis moving component 4, a 3D printing head 5, a swing component 6, a rotating component 7, a feeding component 8, a processing head 9 and a control center.

[0053] The 3D printing head is movably connected to the outer wall of the processing machine body, and a guide rail and a cylinder that controls the sliding movement of the 3D printing head on the guide rail are installed on the outer wall of the processing machine body. A tool is detachably installed at the output end of the processing machine head.

[0054] The Z-axis motion assembly controls the movement of the processing head in the Z-axis direction, the X-axis motion assembly controls the movement of the processing head in the X-axis direction, and the Y-axis motion assembly controls the movement of the swing assembly in the Y-axis direction. Each of the X-axis, Z-axis, and Y-axis motion assemblies includes a servo motor, a guide rail, and a slide. The slide is positioned on the guide rail, allowing the servo motor to drive the slide along the guide rail. The swing assembly includes a first motor, a base, and a swing table. The swing table is rotatably connected to the base. The output of the first motor is connected to the swing table to control its rotation about the X-axis. The rotation assembly includes a turntable and a second motor positioned within the turntable. The turntable is rotatably connected to the turntable. The output of the second motor is connected to the turntable to control its rotation about the Z-axis. A processing station for the printhead to output products is formed on the top surface of the turntable. MEMS sensors are installed within the swing table and the turntable to monitor their rotation angle and speed and provide data feedback to the control center. The control center includes a data processing module, a data acquisition module, and a database.

[0055] The data acquisition module collects dynamic data in real time through sensors and visual acquisition (such as high-definition cameras). The collected data includes the position of the tool on the 3D printing head, the real-time status of the processing path, and the rotation angle and speed.

[0056] The data is collected into the central processing unit, which performs data analysis through its data processing module. The analysis content includes real-time error calculation, path optimization, error compensation parameter calculation, etc. Finally, the data is transmitted to the database through the cloud for storage for long-term monitoring and quality traceability.

[0057] The feeding assembly includes a material box, a feeding pump, and a feeding pipe. The material box outputs the material through the 3D printing head to the processing station via the feeding pump and the feeding pipe.

[0058] A method for dynamically controlling a 3D printing composite machine tool comprises the following steps:

[0059] Step 1: Design and calibration:

[0060] Design and import 3D model data, generate printing processing paths, and calibrate machine tools to ensure printing and processing accuracy.

[0061] Step 2: Printing and real-time monitoring:

[0062] Set the printing parameters, start the 3D printer, print the parts layer by layer according to the preset path, and monitor the printing process in real time through sensors and cameras.

[0063] Step 3: Data analysis and topology path generation:

[0064] The original 3D model data and the data collected by the camera are compared and analyzed, and then the part processing data is output.

[0065] Based on the part processing data, the control center converts it into the dynamic parameters of the machine tool, generates a topological path based on the dynamic parameters, and calibrates the tool.

[0066] The topology path generation steps are:

[0067] Data acquisition: The camera collects the contour data of the 3D printed product to obtain accurate point cloud data and 3D coordinate points; the MEMS sensor feedback is used to measure the rotation angle of the swing table and the rotating table during the 3D printing process. and rotation speed ,

[0068] Fitting point selection: Calculate the contour curvature and select the point where the curvature change is greater than a certain threshold as the fitting point to facilitate tool processing;

[0069] For a curve in 3D space, the curvature is calculated as:

[0070]

[0071] in, is the parametric equation of the curve, and are its first and second order derivative vectors respectively.

[0072] Based on the calculated curvature value, select the curvature change greater than a certain threshold The point of fit is:

[0073]

[0074] in, Represents a point on the contour.

[0075] Preliminary path planning: Generate preliminary tool processing paths using the contact points; as well as the rotation angle and speed of the swing table and rotary table.

[0076] Using path planning Algorithms to connect these points,

[0077] Path optimization: Based on the preliminary path, local optimization is performed, and the path is refined through the gradient descent algorithm to reduce the curvature change and enable the tool to track the contour more accurately;

[0078] Optimize the objective function The gradient descent update formula is:

[0079]

[0080] in, is the position vector of the current path point, is the learning rate, is the objective function About Waypoints gradient;

[0081] Objective function It can be defined as the total curvature or total length of the path, specifically:

[0082]

[0083] Yes, it is the first The curvature of each point, is the distance between adjacent path points, is the weight.

[0084] Use B-spline curves to smooth the path and reduce tool vibration and adjustment.

[0085] B-spline is a commonly used method for smoothing paths, which generates smooth paths by adjusting control points.

[0086] The formula for the B-spline curve is:

[0087]

[0088] in, is a point on the curve, is the control point, It is basis functions, is the control point, is the order of the B-spline.

[0089] B-spline basis functions The recursive calculation formula is:

[0090]

[0091] Step 4: Trajectory measurement and error calculation:

[0092] Start the machine tool, control the tool to move along the predetermined topological path according to the first gear speed v1 set by the control center, and record the actual path points , generate the first running trajectory measurement map .

[0093] Set the second gear speed v2, control the tool to move along the predetermined topological path, and record the actual path points , generate the second running trajectory measurement map .

[0094] Set the third gear speed v3 to control the tool to move along the predetermined topological path and record the actual path points , generate the third running trajectory measurement map .

[0095] The first trajectory measurement map , Second trajectory measurement diagram and the third trajectory measurement map Record and synchronize according to a unified time standard and format. Assuming the time standard is t, each trajectory measurement graph can be expressed as:

[0096]

[0097]

[0098]

[0099] The rotation angle of each swing stage and rotary stage should be included in each trajectory measurement diagram and rotation speed ,

[0100]

[0101] Calculate the error at each acquisition point:

[0102] The planned route points are , the actual path point is Calculate the error of each acquisition point ,

[0103]

[0104] The components of the error are calculated as follows:

[0105]

[0106] Calculate the error between the actual angle and the predetermined angle in real time:

[0107]

[0108]

[0109]

[0110] Statistics calculation of error data:

[0111] Calculate basic statistics of error: including mean , standard deviation and variance.

[0112]

[0113]

[0114]

[0115] in, It is error samples, is the sample size.

[0116] The error range is determined based on the statistical analysis results of the error data and the topological path comparison.

[0117] Error margin:

[0118]

[0119] in, is the Z value corresponding to the confidence level

[0120] If the determined path error interval exceeds the originally set threshold, return to the meeting point selection stage and adjust the path planning.

[0121] Step 5: Error compensation and adjustment:

[0122] The error interval value (average value) obtained in the fourth step , standard deviation ) Input the compensation parameter model and use the compensation parameter model to calculate the compensation parameters in each direction according to the error interval value.

[0123] The error compensation parameter model is:

[0124]

[0125]

[0126]

[0127] 、 、 Respectively represent the compensation coefficients in the X-axis, Y-axis and Z-axis directions, 、 They represent the tool errors in the X-axis, Y-axis and Z-axis directions at time t respectively.

[0128] The PID controller adjusts the position of the tool based on the input error and compensation parameters. The standard formula for the PID controller is:

[0129]

[0130] in, is the control output, is the error, are the proportional, integral, and derivative gains respectively.

[0131] According to the compensation parameters Calculate the input error of the PID controller:

[0132]

[0133]

[0134]

[0135] Calculate the control output in the X, Y, and Z axis directions respectively:

[0136]

[0137]

[0138]

[0139] According to the output of the PID controller, the position of the machine tool tool is adjusted in real time so that it moves accurately along the predetermined path. The tool adjustment amounts are:

[0140]

[0141]

[0142]

[0143] Finally, sensors and cameras monitor the tool's position and trajectory in real time, capturing actual operational data. A feedback mechanism compares the actual position with the desired position, updating the error data. If new errors are detected, the error calculation and compensation steps are repeated to further optimize the tool path.

[0144] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Common changes and substitutions made by those skilled in the art within the scope of the technical solution of the present invention should be included in the protection scope of the present invention.

Claims

1. A 3D printing composite machine tool, comprising a bed, an X-axis moving assembly, a Z-axis moving assembly, a Y-axis moving assembly, a 3D printing head, a swing assembly, a rotating assembly, a feeding assembly, and a processing head, characterized in that: The 3D printing head is movably connected to the outer wall of the processing head. The Z-axis moving assembly controls the movement of the processing head in the Z-axis direction, the X-axis moving assembly controls the movement of the processing head in the X-axis direction, and the Y-axis moving assembly controls the movement of the processing head in the Y-axis direction; The X-axis moving assembly, Z-axis moving assembly, and Y-axis moving assembly all include servo motors, guide rails, and slides. The slides are placed on the guide rails so that the servo motors drive the slides to move on the guide rails. The swing assembly includes a motor 1, a base and a swing table. The swing table and the base are rotatably connected. The output end of the motor 1 is connected to the swing table to control the swing table to rotate around the X-axis. The rotating assembly includes a rotating table and a second motor placed in the swing table. The rotating table and the swing table are connected in rotation. The output end of the second motor is connected to the turntable to control the turntable to rotate around the Z axis. A processing station for the print head to output products is formed on the top surface of the rotating table. The feeding assembly includes a material box, a feeding pump, and a feeding pipe. The material box outputs the material through the 3D printing head and the feeding pipe through the feeding pump to the processing station; The dynamic control method for a 3D printing composite machine tool includes the following steps: S1. Design and import 3D model data, generate printing processing paths, and calibrate the machine tool to ensure printing and processing accuracy; S2. Set the printing parameters, start the 3D printer, print the parts layer by layer according to the preset path, and monitor the printing process in real time through sensors and cameras; S3, compare and analyze the original 3D model data and the data collected by the camera and output the part processing data. Based on the part processing data, the control center converts it into the dynamic parameters of the machine tool, generates a topological path based on the dynamic parameters, and calibrates the tool; The topology path generation step in step S3: S31. Data acquisition: Collect the contour data of the 3D printed product through the camera; obtain accurate point cloud data and 3D coordinate points; and use the MEMS sensor to feedback the rotation angle of the swing table and the rotating table during the 3D printing process. and rotation speed , S32, fitting point selection: Calculate the contour curvature and select the point where the curvature change is greater than a certain threshold as the fitting point to facilitate tool processing; for curves in 3D space, the curvature calculation formula is: ， in, is the parametric equation of the curve, and are the first and second order derivative vectors, respectively, Based on the calculated curvature value, select the curvature change greater than a certain threshold The point of fit is: , in, Represents a point on the contour; S33, preliminary path planning: using the contact points to generate a preliminary tool processing path, and using the path planning A* algorithm to connect these contact points; S34, Path Optimization: Perform local optimization based on the preliminary path, refine the path through the gradient descent algorithm, reduce the curvature change, and make the tool track the contour more accurately; optimize the objective function The gradient descent update formula is: ， in, is the position vector of the current path point, is the learning rate, is the objective function About Waypoints gradient; Objective function It can be defined as the total curvature or total length of the path, specifically: ， Yes, it is the first The curvature of each point, is the distance between adjacent path points, is the weight, Use B-spline curves to smooth the path and reduce tool vibration and adjustment; S4. Establish a compensation parameter model, transmit the compensation parameters to the control center, and adjust the spatial position of the machine tool tool in real time according to the compensation parameters through the PID control unit; The step S4 specifically includes the following steps: S41. Start the machine tool, set the predetermined first gear speed according to the control center, control the tool to move according to the topological path to obtain the first running trajectory, and record the actual path points , generate the first trajectory measurement map ; S42: According to the predetermined second gear speed set by the control center, the tool is controlled to move according to the topological path to obtain a second running trajectory, and the actual path points are recorded. , generate the second trajectory measurement map ; S43, according to the control center setting the predetermined third gear speed, control the tool to move according to the topological path to obtain the third running trajectory, and record the actual path point , generate the third trajectory measurement map ; S44, measuring the first trajectory , Second trajectory measurement diagram and the third trajectory measurement map Compare with the topological path respectively to determine the path error range; Specific steps for determining the path error interval in step S44: S441, the first trajectory measurement map , Second trajectory measurement diagram and the third trajectory measurement map Record and synchronize according to a unified time standard and format. Assuming the time standard is t, each trajectory measurement graph can be expressed as: ； ； ， The rotation angle of each swing stage and rotary stage should be included in each trajectory measurement diagram and rotation speed , ， S442. Calculate the difference between the actual path and the planned path for each collection point: The planned route points are , the actual path point is , calculate the error of each acquisition point , ； The components of the error are calculated as follows: ， Calculate the actual angle in real time With the predetermined angle The error between: ； ； ， Calculate basic statistics for error data: including mean , standard deviation and variance : ； ； ， in, It is error samples, is the sample size, S443. Determine the error interval based on the statistical analysis results of the error data. Error margin: ， in, is the Z value corresponding to the confidence level, If the determined path error interval exceeds the originally set threshold, the process returns to step S32, returns to the contact point selection phase, and adjusts the path planning; S45, inputting the obtained error interval value into the error compensation parameter model for calculation, outputting the control compensation parameter, and then controlling the dynamics of the tool through the PID control unit; The error compensation parameter model is: ； ； ， 、 、 Respectively represent the compensation coefficients in the X-axis, Y-axis and Z-axis directions, 、 They represent the tool errors in the X-axis, Y-axis and Z-axis directions at time t, respectively. According to the output of the PID controller, the position of the machine tool tool is adjusted in real time so that it moves accurately along the predetermined path.

Images