Coaxiality error correction system and method based on laser reference and real-time feedback

Abstract

The coaxiality error correction system and method based on laser reference and real-time feedback relate to the field of close coaxial system part machining and optical reference calibration, and solve the problems that the existing coaxiality correction depends on off-line detection of a three-coordinate measuring instrument for secondary clamping correction, causes process connection error accumulation, and the correction accuracy is influenced by subjective judgment of human experience dependence, etc.. The closed-loop technical path of signal acquisition-algorithm solving-instruction generation-execution feedback is constructed, the limitation of traditional off-line detection is broken through, the integrated process of "measurement-solution-compensation" is realized, and the secondary clamping error is reduced. The present application is also suitable for the field of online dynamic correction of micron-level precision shaft system machining, optical instrument calibration and aerospace high-precision assembly parts.

Description

Technical Field

[0001] This invention relates to the field of precision shaft parts machining and optical reference calibration technology, specifically to a coaxiality error correction system and method based on laser reference and real-time feedback. Background Technology

[0002] Currently, many coaxiality correction techniques rely on offline inspection using equipment such as coordinate measuring machines (CMMs). First, after inspection, the workpiece needs to be re-clamped onto the machining equipment for correction. This separate operation mode lacks direct continuity between the inspection and machining processes. This means that the workpiece's position and orientation may change during offline inspection and reclamping, leading to deviations between the inspection data and the actual machining state. These deviations accumulate and ultimately affect the accuracy of coaxiality correction. Offline inspection and secondary clamping increase process complexity and time costs, reducing production efficiency.

[0003] Secondly, in existing technologies, the accuracy of coaxiality calibration often relies on the operator's experience and subjective judgment. Operators need to determine the direction and magnitude of correction based on the inspection results and their own experience. This leads to differences in the experience and judgment abilities of different operators, resulting in fluctuations in calibration accuracy. Even the same operator may make different judgments at different times or under different conditions, introducing uncontrollable systematic errors. Because it relies on human experience, it is difficult to standardize the calibration process and to replicate and promote it across different equipment or operators.

[0004] Finally, traditional coaxiality correction methods lack real-time feedback capabilities, making it impossible to monitor and adjust errors in real time during machining. Once machining begins, it's impossible to dynamically compensate for errors that have already occurred. This results in the inability to eliminate dynamic errors during machining: During machining, dynamic errors arise due to various factors such as machine tool thermal deformation, tool wear, and workpiece deformation. Traditional methods cannot detect and eliminate these errors in real time, leading to a decrease in machining accuracy. For complex workpieces or high-precision machining tasks, traditional methods struggle to meet dynamically changing requirements and cannot guarantee the stability and consistency of the machining process. Summary of the Invention

[0005] This invention addresses the problems in existing technologies regarding coaxiality correction, such as reliance on offline inspection by a coordinate measuring machine followed by secondary clamping and correction, leading to accumulated errors in process connections, subjective judgment-based correction accuracy dependent on human experience, and the lack of real-time feedback capabilities, which prevents the elimination of dynamic errors during the machining process.

[0006] To solve the above-mentioned technical problems, the present invention is achieved through the following technical solution:

[0007] The present invention proposes the following technical solutions:

[0008] Option 1: A coaxiality error correction system based on laser reference and real-time feedback, the system comprising a laser reference construction module, a dynamic compensation execution module, and a collaborative control module;

[0009] The laser reference construction module includes a reference block, a photosensitive position sensor, a laser, and an optical measurement unit;

[0010] The dynamic compensation execution module includes an air-floating chuck, a tool assembly, and a two-dimensional nano-displacement platform, wherein the two-dimensional nano-displacement platform includes a first two-dimensional nano-movement platform, a second two-dimensional nano-movement platform, and a third two-dimensional nano-movement platform.

[0011] The collaborative control module includes an FPGA-based central control module, which integrates a least-squares fitting algorithm and a PID closed-loop control and error calculation unit, and a spindle motor;

[0012] A laser is set on the first two-dimensional nano-mobile platform. A reference block is fixed at the focal plane of the laser. The reference block and the workpiece to be repaired are respectively clamped in the reference block fixture and the air-floating chuck. The tool assembly is set on one side of the workpiece to be repaired. The optical measurement unit is set on the third two-dimensional nano-mobile platform.

[0013] A reference block is set on the second two-dimensional nano-mobile platform and fixed by a reference block clamp. A photosensitive position sensor is set on the spindle box. The photosensitive position sensor collects the laser beam emitted by the laser and simultaneously starts the optical measurement unit to collect the outer contour boundary data of the workpiece to be repaired. The workpiece to be repaired is rotated by the spindle motor in the spindle box. The minimum boundary position is made to coincide with the minimum deviation of the reference block by the error calculation unit and the central control module. The boundary and the deviation are compared concentrically to complete the coaxiality error correction.

[0014] Furthermore, in a preferred embodiment, the tool assembly is further provided with a rotary motor for driving the tool assembly to perform cutting, thereby achieving convergence of coaxiality error.

[0015] Furthermore, a preferred embodiment is provided in which the first two-dimensional nanomobile platform, the second two-dimensional nanomobile platform, and the third two-dimensional nanomobile platform are arranged horizontally in sequence.

[0016] Option 2: A coaxiality error correction method based on laser reference and real-time feedback, wherein the method is implemented based on the system described in Option 1, and the method includes the following steps:

[0017] S1. A photosensitive position sensor acquires the displacement signal of the laser beam emitted by the laser on a two-dimensional nanometer displacement platform in real time, and calculates the coordinates of discrete sampling points and the coordinates of the dynamic rotation center. Based on the synchronously started optical measurement unit, the outer contour boundary data of the workpiece to be repaired is acquired to fit the center trajectory and generate an initial eccentricity matrix. The FPGA-based central control module generates a tool compensation vector based on the real-time eccentricity ΔEt. ;

[0018] S2. The workpiece to be repaired is rotated by the spindle motor in the spindle box. The minimum boundary position is made to coincide with the minimum deviation of the reference block by the error calculation unit and the central control module. The boundary and the deviation are compared concentrically, and the difference between the boundary and the deviation is calculated. The difference between the boundary and the center deviation is also calculated.

[0019] S3. Based on the initial boundary data and deviation values, determine the tool assembly trajectory, and generate the tool compensation vector according to the real-time feedback boundary data. The rotating motor drives the tool assembly to perform cutting, and the coaxiality error convergence is achieved through multi-iteration closed-loop control.

[0020] Furthermore, a preferred embodiment is provided, wherein the method for calculating the coordinates of discrete sampling points in S1 is as follows:

[0021]

[0022] In the formula, For discrete sampling point coordinates, n This represents the number of sampling points.

[0023] Furthermore, a preferred embodiment is provided in which the tool compensation vector is generated in S2. The method is as follows:

[0024]

[0025] In the formula, , This is the dynamic gain coefficient.

[0026] Furthermore, in a preferred embodiment, the rotation motor 15 driving the tool assembly 7 to perform cutting in S3 needs to satisfy the following:

[0027]

[0028] In the formula, The material removal coefficient is... This is the eccentricity direction angle.

[0029] Furthermore, a preferred embodiment is provided, wherein the convergence condition of the iterative closed-loop control in S3 is: .

[0030] Option 4: A computer device, including a memory and a processor, wherein the memory stores a computer program, and when the processor runs the computer program stored in the memory, the processor executes the method described in Option 2.

[0031] Option 4: A computer-readable storage medium for storing a computer program that executes the method described in Option 2.

[0032] The advantages of this invention are:

[0033] This invention discloses a coaxiality error correction system and method based on laser reference and real-time feedback. It employs a coaxiality correction method to achieve precise correction through a collaborative working mechanism between a laser reference coordinate system and a dynamic compensation system. A closed-loop technical path of "signal acquisition - algorithm calculation - instruction generation - execution feedback" is constructed, overcoming the limitations of traditional offline detection and realizing an integrated "measurement-calculation-compensation" process, reducing secondary clamping errors.

[0034] This invention is also applicable to the fields of micron-level precision shaft machining, optical instrument calibration, and online dynamic correction of high-precision aerospace assemblies. Attached Figure Description

[0035] Figure 1 This is a schematic diagram of the coaxiality error correction system based on laser reference and real-time feedback described in this invention.

[0036] Figure 2 This is an enlarged view of the end portion of the rotary motor-driven tool assembly described in this invention.

[0037] The components include: laser 1, reference block 2, reference block fixture 3, photosensitive position sensor 4, air-bearing chuck 5, workpiece to be repaired 6, tool assembly 7, optical measurement unit 8, first two-dimensional nano-moving platform 9, spindle box 10, second two-dimensional nano-moving platform 11, third two-dimensional nano-moving platform 12, slide rail 14, and rotary motor 15. Detailed Implementation

[0038] To make the objectives, technical solutions and advantages of the embodiments of this application clearer, it is obvious that the described embodiments are only a part of the embodiments of this application, and not all of them.

[0039] Implementation Method 1: This implementation method provides a coaxiality error correction system based on a laser reference and real-time feedback. The system includes a laser reference construction module, a dynamic compensation execution module, and a collaborative control module.

[0040] The laser reference construction module includes a reference block 2, a photosensitive position sensor 4, a laser 1, and an optical measurement unit 8;

[0041] The dynamic compensation execution module includes an air-floating chuck 5, a tool assembly 7, and a two-dimensional nano-displacement platform. The two-dimensional nano-displacement platform includes a first two-dimensional nano-movement platform 9, a second two-dimensional nano-movement platform 11, and a third two-dimensional nano-movement platform 12.

[0042] The collaborative control module includes an FPGA-based central control module, which integrates a least-squares fitting algorithm and a PID closed-loop control and error calculation unit, and a spindle motor;

[0043] A laser 1 is installed on the first two-dimensional nano-mobile platform 9. A reference block 2 is fixed at the focal plane of the laser 1. The reference block 2 and the workpiece 6 to be repaired are respectively clamped in the reference block fixture 3 and the air-floating chuck 5. The tool assembly 7 is installed on one side of the workpiece 6 to be repaired. The optical measurement unit 8 is installed on the third two-dimensional nano-mobile platform 12.

[0044] A reference block 2 is set on the second two-dimensional nano-mobile platform 11 and fixed by the reference block clamp 3; a photosensitive position sensor 4 is set on the spindle box 10. The photosensitive position sensor 4 collects the laser beam emitted by the laser and simultaneously starts the optical measurement unit 8 to collect the outer contour boundary data of the workpiece 6 to be repaired. The spindle motor in the spindle box 10 rotates the workpiece 6 to be repaired. The error settlement unit and the central control module make its minimum boundary position coincide with the minimum deviation of the reference block 2. The boundary and the deviation are compared concentrically to complete the coaxiality error correction.

[0045] Implementation Method 2: This implementation method further defines the coaxiality error correction system based on laser reference and real-time feedback described in Implementation Method 1. The tool assembly 7 is also equipped with a rotary motor 15, which is used to drive the tool assembly 7 to perform cutting and realize coaxiality error convergence.

[0046] Implementation Method 3: This implementation method further defines the coaxiality error correction system based on laser reference and real-time feedback described in Implementation Method 1. The first two-dimensional nano-mobile platform 9, the second two-dimensional nano-mobile platform 11, and the third two-dimensional nano-mobile platform 12 are arranged horizontally in sequence.

[0047] Implementation Method 4: This implementation method proposes a coaxiality error correction method based on a laser reference and real-time feedback. The method is implemented using the system described in any one of Implementation Methods 1 to 3, and includes the following steps:

[0048] S1. The photosensitive position sensor 4 collects the displacement signal of the laser beam emitted by the laser on the two-dimensional nano-displacement platform in real time, and calculates the coordinates of discrete sampling points and the coordinates of the dynamic rotation center. Based on the synchronous start of the optical measurement unit 8, the outer contour boundary data of the workpiece 6 to be repaired is collected to fit the center trajectory and generate the initial eccentricity matrix. The FPGA-based central control module generates the tool compensation vector according to the real-time eccentricity ΔEt. ;

[0049] S2. The spindle motor inside the spindle box 10 rotates the workpiece 6 to be repaired, and the error calculation unit and the central control module make its minimum boundary position coincide with the minimum deviation of the reference block 2; the boundary and the deviation are compared concentrically, the difference between the boundary and the deviation is calculated, and the difference between the boundary and the center deviation is calculated.

[0050] S3. Based on the initial boundary data and deviation values, determine the tool assembly 7 trajectory, and generate the tool compensation vector according to the real-time feedback boundary data. The rotating motor 15 drives the tool assembly 7 to perform cutting, and the coaxiality error convergence is achieved through multi-iteration closed-loop control.

[0051] Implementation Method 5: This implementation method further defines the coaxiality error correction method based on laser reference and real-time feedback described in Implementation Method 4. The method for calculating the coordinates of discrete sampling points in S1 is as follows:

[0052]

[0053] In the formula, For discrete sampling point coordinates, n This represents the number of sampling points.

[0054] Implementation Method Six: This implementation method further defines the coaxiality error correction method based on laser reference and real-time feedback described in Implementation Method Four. In S2, a tool compensation vector is generated. The method is as follows:

[0055]

[0056] In the formula, , This is the dynamic gain coefficient.

[0057] Implementation Method Seven: This implementation method further defines the coaxiality error correction method based on laser reference and real-time feedback described in Implementation Method Four. In S3, the rotation motor 15 driving the tool assembly 7 for cutting needs to meet the following requirements:

[0058]

[0059] In the formula, The material removal coefficient is... This is the eccentricity direction angle.

[0060] Implementation Method Eight: This implementation method further defines the coaxiality error correction method based on laser reference and real-time feedback described in Implementation Method Four. The convergence condition for the iterative closed-loop control in S3 is: .

[0061] Implementation Method Nine: This implementation method provides a computer device, including a memory and a processor. The memory stores a computer program. When the processor runs the computer program stored in the memory, the processor executes the method described in Implementation Method Four.

[0062] Implementation Method 10: This implementation method provides a computer device, including a memory and a processor. The memory stores a computer program. When the processor runs the computer program stored in the memory, the processor executes the method described in Implementation Method 4.

[0063] Implementation Method Eleven: To further explain Implementation Methods One through Ten above, this implementation method describes a coaxiality error correction system and method based on a laser reference and real-time feedback. It achieves precise correction by constructing a collaborative working mechanism between the laser reference coordinate system and the dynamic compensation system. A closed-loop technical path of "signal acquisition - algorithm calculation - instruction generation - execution feedback" is constructed, overcoming the limitations of traditional offline detection and realizing an integrated "measurement-calculation-compensation" process, reducing secondary clamping errors.

[0064] It mainly includes the following steps:

[0065] 1. Establishment of the reference coordinate system

[0066] First, clamp the reference block 2 and the workpiece 6 to be repaired onto the reference block fixture 3 and the high-precision air-floating chuck 5, respectively. Install the workpiece 6 and reference block 2, and adjust the high-precision two-dimensional moving platform to ensure the centers of the optical tube, optical measurement unit 8, reference block 2, photosensitive position sensor 4, and workpiece 6 are aligned. Additionally, a reference component is fixed at the focal plane of the laser 1. Clamp the reference block 2 and the workpiece 6 onto the air-floating chuck 5, and achieve spatial registration of the optical axis and workpiece axis using the two-dimensional displacement platform. Start the reference component to rotate at a uniform speed. The photosensitive position sensor 4 array captures the displacement signal of the laser beam in the XY plane in real time, and uses the formula... In the formula For discrete sampling point coordinates, n The number of sampling points. Calculation of dynamic rotation center coordinates: Synchronously acquire the outer contour boundary data of the original part to be repaired (6), fit the center trajectory using the base algorithm, generate the initial eccentricity matrix, and the central control system generates a compensation vector based on the real-time eccentricity ΔEt. ;

[0067] The central control module generates a compensation vector based on the solid eccentricity ΔEt. , In the formula, , This is the dynamic gain coefficient.

[0068] The servo system drives the tool assembly 7 to perform depth of cut compensation and cutting amount. satisfy:

[0069]

[0070] In the formula, The material removal coefficient is... This is the eccentricity direction angle.

[0071] Through iterative closed-loop control, the convergence condition is: This achieves an exponential decrease in coaxiality error.

[0072] An optical positioning reference is established using a laser transmission film with a centrally located microporous structure as a reference block. Reference block 2 rotates continuously at a uniform speed. A photosensitive position sensor 4 captures the displacement signal of the laser beam in the XY plane. The coordinates of the dynamic rotation center of the reference component are calculated using a least-squares fitting algorithm. This requires the collaboration of a central control system and an error settlement unit. The optical measurement unit 8 is simultaneously activated to continuously acquire the outer contour boundary data of the component to be repaired 6. The center coordinates are obtained using a least-squares fitting algorithm. The central control system and the error settlement unit generate compensation commands based on the initial boundary data and real-time deviation, driving the three-jaw air-floating chuck 5 to perform micron-level radial compensation, thus converging the spatial deviation between the dynamic rotation center of the component to be repaired 6 and the reference axis. The spindle motor inside the spindle box 10 rotates the component to be repaired 6, and the error settlement unit and central control system ensure that its minimum boundary position coincides with the minimum deviation of the reference component. The boundary and deviation are compared concentrically. The difference between the boundary and the deviation, and the difference between the boundary and the center deviation, are calculated.

[0073] 2. Repair and maintenance phase:

[0074] Based on the initial boundary data and deviation values, the tool path is determined. According to the real-time feedback boundary data, the system generates a tool compensation feed vector, and the servo system drives the tool to perform cutting, thereby achieving convergence of coaxiality error.

[0075] During the cutting correction stage, the system constructs a tool feed vector model based on real-time acquired eccentricity and a reference component. An algorithm calculates the tool pose compensation, driving the cutting assembly to synchronously adjust the spatial pose of the cutting tool. During continuous workpiece rotation, a cutting depth compensation curve is generated in real-time based on the boundary curve produced by the optical detection component, controlling the servo control system to achieve feed compensation. Through multi-iteration closed-loop control, coaxiality error is attenuated, ultimately achieving machining accuracy with very small residual eccentricity. The cutting assembly, paired with a high-precision servo drive system, controls the tool assembly feed, allowing for both rotation and translation.

[0076] Those skilled in the art will understand that the above description is merely a preferred embodiment of the present invention, and the features described in the various embodiments and / or technical solutions of this disclosure can be combined or combined in various ways, even if such combinations or combinations are not explicitly described in this disclosure. This is not intended to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

[0077] Although preferred embodiments of the present invention have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended technical solutions are intended to be interpreted as including both the preferred embodiments and all changes and modifications falling within the scope of the present invention. Clearly, those skilled in the art can make various modifications and variations to the present invention without departing from its spirit and scope. Thus, if these modifications and variations of the present invention fall within the scope of the present invention and its equivalents, the present invention also intends to include these modifications and variations.

Claims

1. A coaxiality error correction system based on laser reference and real-time feedback, characterized in that, The system includes a laser reference construction module, a dynamic compensation execution module, and a collaborative control module; The laser reference construction module includes a reference block (2), a photosensitive position sensor (4), a laser (1), and an optical measurement unit (8). The dynamic compensation execution module includes an air-floating chuck (5), a tool assembly (7), and a two-dimensional nano-displacement platform. The two-dimensional nano-displacement platform includes a first two-dimensional nano-movement platform (9), a second two-dimensional nano-movement platform (11), and a third two-dimensional nano-movement platform (12). The collaborative control module includes an FPGA-based central control module, which integrates a least-squares fitting algorithm and a PID closed-loop control and error calculation unit, and a spindle motor; A laser (1) is installed on the first two-dimensional nano-mobile platform (9). A reference block (2) is fixed at the focal plane of the laser (1). The reference block (2) and the workpiece to be repaired (6) are respectively clamped in the reference block fixture (3) and the air-floating chuck (5). The tool assembly (7) is set on one side of the workpiece to be repaired (6). The optical measurement unit (8) is set on the third two-dimensional nano-mobile platform (12). A reference block (2) is set on the second two-dimensional nano-mobile platform (11), and the reference block (2) is fixed by the reference block clamp (3); a photosensitive position sensor (4) is set on the spindle box (10). The photosensitive position sensor (4) collects the laser beam emitted by the laser and simultaneously starts the optical measurement unit (8) to collect the outer contour boundary data of the original part (6) to be repaired. The original part (6) to be repaired is rotated by the spindle motor in the spindle box (10). The minimum boundary position of the original part (6) is made to coincide with the minimum deviation of the reference block (2) by the error settlement unit and the central control module. The boundary and the deviation are compared concentrically to complete the coaxiality error correction.

2. The coaxiality error correction system based on laser reference and real-time feedback according to claim 1, characterized in that, The tool assembly (7) is also equipped with a rotary motor (15) for driving the tool assembly (7) to perform cutting and achieve convergence of coaxiality error.

3. The coaxiality error correction system based on laser reference and real-time feedback according to claim 1, characterized in that, The first two-dimensional nanomobile platform (9), the second two-dimensional nanomobile platform (11), and the third two-dimensional nanomobile platform (12) are arranged horizontally in sequence.

4. A coaxiality error correction method based on laser reference and real-time feedback, characterized in that, The method is implemented based on the system described in any one of claims 1-3, and the method includes the following steps: S1, the photosensitive position sensor (4) collects the displacement signal of the laser beam emitted by the laser on the two-dimensional nano-displacement platform in real time, and calculates the coordinates of discrete sampling points and the coordinates of the dynamic rotation center. Based on the synchronous start of the optical measurement unit (8), the outer contour boundary data of the workpiece (6) to be repaired is collected to fit the center trajectory and generate the initial eccentricity matrix. The central control module based on FPGA generates the tool compensation vector according to the real-time eccentricity ΔEt. ; S2. Rotate the workpiece (6) to be repaired by the spindle motor in the spindle box (10), and make its minimum boundary position coincide with the minimum deviation of the reference block (2) by the error settlement unit and the central control module; compare the boundary and the deviation in a concentric manner, calculate the difference between the boundary and the deviation, and calculate the difference between the boundary and the center deviation. S3. Based on the initial boundary data and the value of the deviation, determine the trajectory of the tool assembly (7), and generate the tool compensation vector according to the real-time feedback boundary data. The rotating motor (15) drives the tool assembly (7) to perform cutting. Through multi-iteration closed-loop control, the coaxiality error convergence is achieved.

5. The coaxiality error correction method based on laser reference and real-time feedback according to claim 4, characterized in that, The method for calculating the coordinates of discrete sampling points in S1 is as follows: In the formula, For discrete sampling point coordinates, n This represents the number of sampling points.

6. The coaxiality error correction method based on laser reference and real-time feedback according to claim 4, characterized in that, Generate tool compensation vector in S2 The method is as follows: In the formula, , This is the dynamic gain coefficient.

7. The coaxiality error correction method based on laser reference and real-time feedback according to claim 4, characterized in that, The rotary motor (15) in S3 drives the tool assembly (7) to perform cutting, which requires the following: In the formula, The material removal coefficient is... This is the eccentricity direction angle.

8. The coaxiality error correction method based on laser reference and real-time feedback according to claim 4, characterized in that, The convergence condition for the iterative closed-loop control in S3 is: .

9. A computer device, including a memory and a processor, characterized in that, The memory stores a computer program, and when the processor runs the computer program stored in the memory, the processor performs the method described in claim 4.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements the steps of the method of claim 4.

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