Chip mounter based on adjustable prism and assembling method
By collecting imaging error data in the pick-and-place machine and optimizing the positioning bolt positions of the prism assembly, the problem of prism assembly drift under vibration and long-term operation was solved, achieving high-precision and stable optical path alignment, and improving production continuity and placement accuracy.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-12-30
- Publication Date
- 2026-04-07
AI Technical Summary
The prism assembly of existing pick-and-place machines is prone to drift under vibration and long-term operation, which leads to a decrease in imaging overlap and affects placement accuracy and production continuity.
A patch machine based on an adjustable prism is used to collect imaging error datasets through a vision imaging system. The positioning bolt positions of the prism assembly are optimized by the control system to achieve precise alignment of the optical path and stable imaging.
This achieves long-term stable high-precision optical path alignment of the prism assembly after a single assembly, reducing maintenance frequency and improving mounting accuracy and production continuity.
Smart Images
Figure CN121815654A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of chip mounting technology, and in particular to a chip mounter and assembly method based on an adjustable prism. Background Technology Pick-and-place machines are core equipment in the field of surface mount technology, widely used for the automated placement of miniature, high-precision components such as integrated circuits, consumer electronics, and communication modules. As component sizes continue to shrink and placement accuracy requirements increase, the visual positioning system of pick-and-place machines needs to achieve sub-pixel-level alignment. This process typically relies on an optical prism assembly to combine two imaging beams from the chip and the placement head, which are then captured and compared by the same camera. Therefore, the optical path stability of the prism assembly directly determines the accuracy of visual alignment and the placement yield.
[0002] In existing technologies, the prism assembly of pick-and-place machines often employs an adjustable mechanical support structure. For example, multiple adjusting bolts are installed on the support plate, which are manually tightened by the operator during assembly to fine-tune the angle and position of the prism until the image overlaps and meets the initial requirements. However, this mechanical adjustment method, relying on manual on-site adjustments, has a major drawback: poor long-term operational stability. Under the influence of vibrations, temperature changes, or stress relaxation caused by continuous equipment operation, the preload of the adjusting bolts can easily change slightly, leading to drift in the prism support point and consequently causing optical path deviation and a decrease in image overlap. This defect necessitates frequent machine shutdowns for recalibration during use, increasing maintenance costs and severely impacting production continuity and the consistency of final placement accuracy.
[0003] Therefore, it is necessary to improve the existing technology to solve the technical problem that traditional adjustment structures are prone to drift under vibration and long-term operation, resulting in decreased imaging overlap and unstable mounting accuracy. Summary of the Invention
[0004] The purpose of this invention is to provide a chip mounter and assembly method based on an adjustable prism, thereby solving the above-mentioned technical problems.
[0005] To achieve this objective, the present invention adopts the following technical solution: A pick-and-place machine based on an adjustable prism, comprising: The platform is defined with point A for carrying the chip; A swing arm assembly is hinged to one side of the platform via a swing arm rotation point, and point B is defined at the end of the swing arm. A visual imaging system, including an image-capturing component; A prism assembly is disposed in the optical path of the pick-and-place machine system, and its position is such that the images of point A and point B intersect and are transmitted to the image-capturing assembly; A control system is used to control the operation of the placement machine and process the images acquired by the vision imaging system to obtain an imaging error dataset; Based on the imaging error dataset, the control system performs optimization analysis on the spatial positions of the positioning bolts of the prism assembly to obtain optimized bolt positions, and adjusts the assembly position of the prism assembly according to the optimized bolt positions.
[0006] Optionally, a first optical path is formed at point A on the optical path, and a second optical path is formed at point B. The prism assembly is disposed at an optical path node, which is the intersection of the first optical path and the second optical path.
[0007] Optionally, the prism assembly includes an adjustment component and a beam splitter prism, wherein the adjustment component includes a fixing plate and a first adjustment plate; The fixed plate is provided with a first V-shaped groove, and a first shaft is placed in the first V-shaped groove. The first adjusting plate is rotatably connected to the fixed plate through the first shaft. The first adjusting plate is connected to the second adjusting plate by connecting bolts, and the end of the second adjusting plate is provided with a clamping assembly for clamping the beam splitter.
[0008] Optionally, the adjustment assembly further includes multiple sets of positioning bolts, which are arranged on both sides of the first shaft along preset points; At least two sets of positioning bolts are arranged asymmetrically on both sides of the first shaft.
[0009] Optionally, the positioning bolts are provided in two sets, namely the first positioning bolt and the second positioning bolt, which are arranged asymmetrically on both sides of the first shaft.
[0010] Optionally, the platform includes a support platform for carrying and positioning the chip, the support platform being located at point A.
[0011] Optionally, the swing arm assembly includes a drive device connected to the control system for driving the swing arm to rotate around the swing arm rotation point, thereby causing point B to move.
[0012] The present invention also provides a mounting method for a pick-and-place machine, applicable to the pick-and-place machine based on an adjustable prism as described above, the mounting method comprising the following steps: Install the prism assembly at the optical path node of the pick-and-place machine; The placement machine is operated to collect imaging data at points A and B on the optical path through the imaging acquisition system, and the imaging error dataset is obtained by analysis. Based on the imaging error dataset, the spatial positions of the positioning bolts of the prism assembly are optimized and analyzed to obtain optimized bolt positions. Based on the optimized bolt positions, adjust and fix the actual installation positions of the positioning bolts in the prism assembly.
[0013] Optionally, based on the imaging error dataset, the spatial positions of the positioning bolts of the prism assembly are optimized to obtain optimized bolt positions, specifically including: The three-dimensional model of the prism assembly is parameterized and imported into the constructed mechanical-optical integrated model. At the same time, the imaging error dataset is used as the model input, and the installation coordinates (x1, y1) and (x2, y2) of the first and second positioning bolts on the first adjustment plate are defined as optimization variables. In the mechanical-optical integrated model, the initial spatial position and coordinate change constraint range of the optimization variables are set based on the physical structure of the first adjustment plate, and the convergence threshold of the optimization algorithm is configured with minimizing the imaging error function E as the optimization objective. The mechanical-optical integrated model is driven to perform iterative calculations. In each iteration, the model simulates and calculates the prism attitude and corresponding imaging error E under the action of external force P based on the current bolt spatial positions (x1, y1) and (x2, y2), and generates the next set of optimized bolt spatial positions based on the optimization algorithm. When the calculation result of the imaging error function E satisfies the convergence threshold, the iteration is terminated, and the corresponding bolt spatial points (x1, y1) and (x2, y2) are output as the optimal bolt points for manufacturing.
[0014] Optionally, the process of constructing the aforementioned mechanical-optical integrated model is as follows: An optical model is established, which is used to characterize the functional relationship between the beam splitter attitude and the imaging overlap of points A and B, namely the imaging error function E=f(Δx, Δy, Δα). A mechanical model is established to characterize the functional relationship between the external force and the deformation displacement of the prism at the support point, i.e., Δx=g(P, xi, yi); By coupling the optical model and the mechanical model, using the spatial position (xi, yi) of the positioning bolt as the optimization variable and minimizing the imaging error function E as the optimization objective, a mechanical-optical integrated model is constructed.
[0015] Compared with existing technologies, this invention has the following advantages: During chip mounting, the platform first carries the chip and defines point A, while the swing arm assembly drives point B to move; the vision imaging system synchronously acquires images of points A and B through the prism assembly and transmits them to the image acquisition assembly; the control system processes the acquired images and analyzes them to generate an imaging error dataset; based on this dataset, the control system optimizes the spatial positions of the positioning bolts in the prism assembly, obtains optimized bolt positions, and adjusts the actual assembly position of the prism assembly accordingly, thereby achieving precise alignment and stable imaging of the optical path; this solution achieves high-precision optical path alignment of the prism assembly with one-time assembly and long-term stability through data-driven bolt position optimization and assembly adjustment. Attached Figure Description
[0016] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0017] The structures, proportions, sizes, etc., shown in the accompanying drawings of this specification are only for the purpose of assisting those skilled in the art in understanding and reading the content disclosed in the specification, and are not intended to limit the conditions under which the present invention can be implemented. Therefore, they have no substantial technical significance. Any modifications to the structure, changes in the proportions, or adjustments to the size, without affecting the effects and objectives that the present invention can produce, should still fall within the scope of the technical content disclosed in the present invention.
[0018] Figure 1 This is a side view of the placement machine system in Embodiment 1; Figure 2 This is a front view schematic diagram of the placement machine system in Embodiment 1; Figure 3 This is a schematic diagram of the prism assembly in Embodiment 1; Figure 4 This is a schematic diagram of the positioning bolt layout structure of the prism assembly in Embodiment 1; Figure 5 This is a schematic diagram of the system layout of the pick-and-place machine system in Example 1.
[0019] Reference numerals in the attached figures: prism assembly 10, beam splitter prism 11, fixing plate 12, first adjusting plate 13, first V-groove 121, first shaft 14, second adjusting plate 16, clamping assembly 17, platform 20, visual imaging system 30, swing arm assembly 40, swing arm rotation point 41. Detailed Implementation
[0020] To make the objectives, features, and advantages of this invention more apparent and understandable, the technical solutions of the embodiments of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the embodiments described below are only some embodiments of this invention, and not all embodiments. Based on the embodiments of this invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this invention.
[0021] In the description of this invention, it should be understood that the terms "upper," "lower," "top," "bottom," "inner," and "outer," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings, and are only for the convenience of describing the invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of the invention. It should be noted that when a component is considered to be "connected" to another component, it can be directly connected to the other component or there may be a component positioned centrally in the connection.
[0022] The technical solution of the present invention will be further described below with reference to the accompanying drawings and specific embodiments.
[0023] Example 1 Combination Figures 1 to 5 As shown, the present invention also provides a patching machine based on an adjustable prism, including a platform 20, a swing arm assembly 40, a vision imaging system 30, a prism assembly 10, and a control system. Platform 20 is defined with point A for carrying the chip; platform 20 includes a support platform for carrying and positioning the chip, the support platform being located at point A.
[0024] The swing arm assembly 40 is hinged to one side of the platform 20 via the swing arm rotation point 41, and point B is defined at the end of the swing arm. The swing arm assembly 40 includes a drive device, which is connected to the control system and is used to drive the swing arm to rotate around the swing arm rotation point 41 so as to drive point B to move.
[0025] The visual imaging system 30 includes an image acquisition component; the prism component 10 is disposed in the optical path of the pick-and-place machine system, and its position is such that the images of point A and point B intersect and are transmitted to the image acquisition component; the control system is used to control the operation of the pick-and-place machine and process the images acquired by the visual imaging system 30 to obtain an imaging error dataset.
[0026] Based on the imaging error dataset, the control system performs optimization analysis on the spatial positions of the positioning bolts of the prism assembly 10 to obtain optimized bolt positions, and adjusts the assembly position of the prism assembly 10 according to the optimized bolt positions.
[0027] The prism assembly 10 transmits the beams from the first optical path (point A) and the second optical path (point B) to the image acquisition component (such as the same CCD) of the vision imaging system 30 after splitting / combining, so that the images of points A and B on the imaging plane can overlap or be placed side by side for computer vision algorithms to perform comparative analysis. When the two images achieve the expected overlap, the system determines that the swing arm and the chip are in the correct alignment relationship; otherwise, it adjusts the position of the swing arm or the posture of the mounting head through feedback from the control system until the alignment requirements are met.
[0028] The working principle of this invention is as follows: During chip mounting, the platform 20 first carries the chip and defines point A, while the swing arm assembly 40 drives point B to move; the vision imaging system 30 synchronously acquires images of points A and B through the prism assembly 10 and transmits them to the image acquisition assembly; the control system processes the acquired images and analyzes them to generate an imaging error dataset; based on this dataset, the control system optimizes the spatial position of the positioning bolts in the prism assembly 10, obtains the optimized bolt positions, and adjusts the actual assembly position of the prism assembly 10 accordingly, thereby achieving precise alignment and stable imaging of the optical path; this solution achieves high-precision optical path alignment of the prism assembly 10 with one-time assembly and long-term stability through data-driven bolt position optimization and assembly adjustment.
[0029] In this embodiment, it should be noted that a first optical path is formed at point A on the optical path, and a second optical path is formed at point B; wherein, the prism assembly 10 is disposed at the optical path node, and the optical path node is the intersection of the first optical path and the second optical path.
[0030] It should be noted that the beam splitter prism 11, located at the intersection point, guides the images from two different reference points, chip point A on platform 20 and device point B on swing arm, to the same imaging component to form a superimposed image, which serves as the basis for determining the mounting positioning. Therefore, the control of the geometric accuracy of the optical path nodes and the prism attitude directly determines the imaging superposition and positioning accuracy.
[0031] This embodiment emphasizes that during the on-site acquisition phase, the intersection point should be used as the coordinate reference to record the imaging deviation, and the resulting A / B imaging error should be used as the direct input of the mechanical-optical coupling model to ensure that the subsequent bolt position optimization closely corresponds to the geometric requirements of the actual optical path, thereby achieving the goal of eliminating the positioning deviation caused by imaging error.
[0032] In this embodiment, the prism assembly 10 specifically includes an adjustment assembly and a beam splitter 11. The adjustment assembly includes a fixed plate 12 and a first adjustment plate 13. The fixed plate 12 is provided with a first V-groove 121, and a first shaft 14 is placed inside the first V-groove 121. The first adjustment plate 13 is rotatably connected to the fixed plate 12 through the first shaft 14. The first adjustment plate 13 is connected to a second adjustment plate 16 through connecting bolts. The end of the second adjustment plate 16 is provided with a clamping assembly 17 for clamping the beam splitter 11.
[0033] The working principle of this prism assembly 10 is as follows: During operation, the beam splitter prism 11 separates and / or combines the beams from the first and second optical paths according to a predetermined incident / exit angle, so that the two paths form an overlapping image on the same camera sensor; the first shaft 14 provides assembly and initial adjustment freedom, while the connecting bolts (fixed points optimized according to the design method of Embodiment 1 and subjected to fixed depth / curing treatment) support the adjustment plate and optical elements at a fixed spatial position during operation, thereby passively maintaining the stability of the prism attitude when subjected to assembly stress, vibration or thermal deformation, reducing the possibility of manual fine adjustment during operation, and ensuring the long-term stability of imaging overlap and positioning accuracy.
[0034] In this embodiment, it is further explained that, in combination with Figure 3 As shown, the adjustment assembly also includes multiple sets of positioning bolts 18, which are arranged along preset points on both sides of the first shaft 14; at least two sets of positioning bolts 18 are arranged asymmetrically on both sides of the first shaft 14.
[0035] This structure retains the convenience of installation, alignment, and initial attitude adjustment at the shaft hinge (for example, minor adjustments can be made around the first shaft 14 during assembly or replacement for quick positioning), while also distributing the support stiffness and constraints during operation to multiple locations by arranging multiple sets of fixing points on both sides of the shaft, thereby reducing stress concentration at a single point.
[0036] As a preferred embodiment, the positioning bolts 18 are provided in two sets, namely the first positioning bolt and the second positioning bolt, which are arranged asymmetrically on both sides of the first shaft 14.
[0037] It should be noted that this asymmetric arrangement is not arbitrarily designed, but rather determined through optimization algorithms based on collected A / B imaging error data and a constructed mechanical-optical coupling model. The asymmetric arrangement can be used to intentionally offset the support stiffness and stress transmission path, thereby achieving passive compensation for imaging deviations when assembly deviations, static / dynamic moments of the swing arm, or uneven local stress exist. Compared to a symmetrical arrangement, the data-driven optimized asymmetric point positions can more effectively offset systematic errors (such as deviations caused by geometric asymmetry of the pick-and-place machine swing arm or assembly reference deviations), and reduce dependence on the stability of bolt preload during operation, ultimately achieving a high-stability, adjustment-free prism positioning structure composed of fixed-depth bolts.
[0038] Example 2: The present invention also provides a mounting method for a pick-and-place machine, applicable to a pick-and-place machine based on an adjustable prism as described in Embodiment 1. The mounting method includes the following steps: S1, install the prism assembly 10 onto the optical path node of the pick-and-place machine; S2, run the placement machine, collect imaging data of points A and B on the optical path through the imaging acquisition system, and analyze the imaging error dataset; S3. Based on the imaging error dataset, the spatial positions of the positioning bolts of the prism assembly 10 are optimized and analyzed to obtain the optimized bolt positions. S4. Based on the optimized bolt positions, adjust and fix the actual installation positions of the positioning bolts in the prism assembly 10.
[0039] This installation method effectively overcomes the problems of relying on multiple trial and error adjustments and poor consistency in traditional assembly by actually collecting optical path imaging error data and driving the optimization and fixation of bolt positions. It significantly improves the assembly accuracy and repeatability of prism assembly 10. After assembly, prism assembly 10 is not easily affected by vibration and stress changes during long-term operation because the bolt positions are optimized and reliably fixed. This ensures the continuous stability and alignment accuracy of the pick-and-place machine vision system and reduces the frequency of subsequent maintenance and calibration. This method achieves high precision and long-term stability of prism assembly 10 by driving bolt position optimization and fixation with imaging error data in one step.
[0040] In this embodiment, step S3 specifically includes: S31, the three-dimensional model of the prism assembly 10 is parameterized and imported into the constructed mechanical-optical integrated model. At the same time, the imaging error dataset is used as the model input, and the installation coordinates (x1, y1) and (x2, y2) of the first positioning bolt and the second positioning bolt on the first adjustment plate 13 are defined as optimization variables. In this step, the three-dimensional geometric model of the standard prism assembly 10 obtained according to the design drawings (including the detailed dimensions and topology of the fixing block, the first adjusting plate 13, the first shaft 14, the second adjusting plate 16, and the clamping assembly 17) is parametrically processed and imported into the established mechanical-optical integrated model as the simulation subject; at the same time, the imaging error dataset generated in step S1 is used as the calibration input or perturbation sample set of the model. For the positioning bolts to be optimized, in this embodiment, the installation coordinates of the first positioning bolt and the second positioning bolt on the first adjusting plate 13 are represented as (x1, y1) and (x2, y2) respectively, and these two coordinates are used as optimization variables to clarify their geometric meaning in the model (e.g., the offset relative to the reference line and the datum plane of the first shaft 14) so that they correspond one-to-one in the simulation and subsequent manufacturing drawings.
[0041] S32, in the mechanical-optical integrated model, the initial spatial position and coordinate change constraint range based on the physical structure of the first adjustment plate 13 are set for the optimization variables, and the convergence threshold of the optimization algorithm is configured with minimizing the imaging error function E as the optimization objective.
[0042] Meanwhile, the optimization objective is clearly defined as minimizing the imaging error function E under the representative perturbation set (which can be weighted RMS, maximum value, or a combination of both), and a convergence threshold is configured in the optimizer (e.g., the relative rate of change of the objective function is less than a preset ε, or the objective improvement is lower than the threshold and the variable step size is satisfied for several consecutive iterations) to ensure the convergence of the numerical solution.
[0043] S33, the driving mechanics-optics integrated model performs iterative calculations. In each iteration, the model simulates and calculates the prism attitude and corresponding imaging error E under the action of external force P based on the current bolt spatial positions (x1, y1) and (x2, y2), and generates the next set of optimized bolt spatial positions based on the optimization algorithm.
[0044] The mechanical-optical integrated model is invoked to simulate and evaluate the bolt points (x1, y1) and (x2, y2) of the current iteration: the mechanical sub-model calculates the micro-displacement and rotation of the prism under the action of a representative external force P (or perturbation sample), and the optical sub-model maps the displacement / rotation to the imaging offset on the CCD and calculates the imaging error E; the optimization algorithm (which can use a combination of global search method and local refinement or surrogate model acceleration strategy) generates the next set of candidate points based on the current E value and sends them to the next round of simulation.
[0045] Each iteration simultaneously records the history of the objective function, the degree of constraint violation, the sensitivity information of each variable, and the simulation residuals. When necessary, surrogate models (response surface, Gaussian process, etc.) are used to replace the high-cost FEM-optical coupling simulation to accelerate the global search, and the results of the surrogate models are periodically verified with high-fidelity simulations to prevent distortion.
[0046] S34. When the calculation result of the imaging error function E meets the convergence threshold, the iteration is terminated, and the corresponding bolt spatial points (x1, y1) and (x2, y2) are output as the optimal bolt points for manufacturing.
[0047] When the imaging error function E satisfies the pre-set convergence criterion during the iteration process (e.g., the relative improvement of the objective function is less than ε for several consecutive iterations and all engineering constraints are satisfied), or when the maximum number of iterations is reached and a stable optimal value is obtained in multiple restarts, the calculation is terminated; the corresponding bolt spatial points (x1, y1) and (x2, y2) at this time are output as the optimal points in the engineering, and a performance report of the design under representative disturbances (including mean, RMS, extreme values, stress distribution and sensitivity analysis results) and manufacturing tolerance suggestions are generated at the same time.
[0048] In this embodiment, the process of constructing the mechanical-optical integrated model is as follows: An optical model is established to characterize the functional relationship between the orientation of the beam splitter 11 and the imaging overlap of points A and B, namely the imaging error function E=f(Δx, Δy, Δα); Δx and Δy represent the translation components of the prism center, and Δα represents the small rotation angle of the prism (both are increments relative to the assembly reference).
[0049] Optical models can be constructed using two methods: for high-precision applications, ray tracing or geometric optics simulation can be used to calculate the optical path and map the minute displacements / rotations of the prism to image point offsets on the CCD; for rapid engineering evaluation, a mapping matrix Mo can be established based on small-angle approximation linearization, such that Δr = Mo[Δx, Δy, Δα], and an explicit expression for E can be derived from this. The parameters of the optical model (such as equivalent focal length, prism refractive surface position and angle, optical center position, etc.) are calibrated using acquired and calibrated imaging data and a calibration matrix.
[0050] A mechanical model is established to characterize the functional relationship between the external force and the deformation displacement of the prism at the support point, i.e., Δx=g(P, xi, yi).
[0051] In this embodiment, the mechanical model is used to describe the deformation and rigid body response relationship of the prism assembly 10 at each positioning support point under the action of external force, prestress and assembly constraints, and is formalized as the displacement function Δx=g(P, {xi, yi}) (similarly, there are corresponding functions for Δy and Δα).
[0052] The mechanical model can be established using finite element analysis (FEM) to create the overall and local elastic responses of the component. Inputs include the material's elastic modulus, Poisson's ratio, a three-dimensional geometric model, bolt / constraint boundary conditions, and a representative set of external loads P (obtained statistically from the multi-condition data acquisition results of S1, such as swing arm torque, vibration spectrum, and temperature gradient). Outputs are the translational and rotational responses of the prism reference point. To improve engineering efficiency, this embodiment can also use a simplified elastic support model or a multibody elastic model as an approximation. Subsequent optimization iterations are accelerated by fitting the FEM results to a response surface / surrogate model (such as polynomial regression or Gaussian process). Simultaneously, necessary terms such as manufacturing tolerances and contact nonlinearities are introduced into the model to ensure the feasibility and reliability of the predictions.
[0053] By coupling the optical model and the mechanical model, using the spatial position (xi, yi) of the positioning bolt as the optimization variable and minimizing the imaging error function E as the optimization objective, a mechanical-optical integrated model is constructed.
[0054] In this embodiment, the steps of establishing the optical model and establishing the mechanical model are coupled to form a complete mechanical-optical integrated mapping E({xi, yi}, P) = f(g(P, {xi, yi})). An optimization problem is constructed using the spatial location (xi, yi) of the positioning bolt as the design variable. The objective is to minimize the imaging error (e.g., minimize the weighted RMS error or minimize the worst-case error) under a representative set of perturbations, i.e., to solve for Emin. For computationally intensive coupled simulations, a surrogate model can be introduced for accelerated evaluation and robustness analysis (e.g., Monte Carlo sampling or robust optimization). Finally, a set of optimal positioning bolt locations and their tolerance ranges that satisfy the constraints and have the lowest imaging error under the perturbation set are output.
[0055] The above-described embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.
Claims
1. A pick-and-place machine based on an adjustable prism, characterized in that, include: The platform is defined with point A for carrying the chip; A swing arm assembly is hinged to one side of the platform via a swing arm rotation point, and point B is defined at the end of the swing arm. A visual imaging system, including an image-capturing component; A prism assembly is disposed in the optical path of the pick-and-place machine system, and its position is such that the images of point A and point B intersect and are transmitted to the image-capturing assembly; A control system is used to control the operation of the placement machine and process the images acquired by the vision imaging system to obtain an imaging error dataset; Based on the imaging error dataset, the control system performs optimization analysis on the spatial positions of the positioning bolts of the prism assembly to obtain optimized bolt positions, and adjusts the assembly position of the prism assembly according to the optimized bolt positions.
2. The patching machine based on an adjustable prism according to claim 1, characterized in that, Point A on the optical path forms a first optical path, and point B forms a second optical path. The prism assembly is disposed at an optical path node, which is the intersection of the first optical path and the second optical path.
3. The patching machine based on an adjustable prism according to claim 1, characterized in that, The prism assembly includes an adjustment component and a beam-splitting prism, and the adjustment component includes a fixed plate and a first adjustment plate; The fixed plate is provided with a first V-shaped groove, and a first shaft is placed in the first V-shaped groove. The first adjusting plate is rotatably connected to the fixed plate through the first shaft. The first adjusting plate is connected to the second adjusting plate by connecting bolts, and the end of the second adjusting plate is provided with a clamping assembly for clamping the beam splitter.
4. The patching machine based on an adjustable prism according to claim 3, characterized in that, The adjustment assembly also includes multiple sets of positioning bolts, which are arranged on both sides of the first shaft along preset points; At least two sets of positioning bolts are arranged asymmetrically on both sides of the first shaft.
5. The pick-and-place machine based on an adjustable prism according to claim 4, characterized in that, The positioning bolts are provided in two sets, namely the first positioning bolt and the second positioning bolt, which are arranged asymmetrically on both sides of the first shaft.
6. The pick-and-place machine based on an adjustable prism according to claim 1, characterized in that, The platform includes a support platform for carrying and positioning the chip, and the support platform is located at point A.
7. The pick-and-place machine based on an adjustable prism according to claim 1, characterized in that, The swing arm assembly includes a drive device connected to the control system, which drives the swing arm to rotate around the swing arm rotation point, thereby causing point B to move.
8. A method for mounting a chip mounter, characterized in that, The mounting method, applicable to a pick-and-place machine based on an adjustable prism as described in any one of claims 1 to 7, comprises the following steps: Install the prism assembly at the optical path node of the pick-and-place machine; The placement machine is operated to collect imaging data at points A and B on the optical path through the imaging acquisition system, and the imaging error dataset is obtained by analysis. Based on the imaging error dataset, the spatial positions of the positioning bolts of the prism assembly are optimized and analyzed to obtain optimized bolt positions. Based on the optimized bolt positions, adjust and fix the actual installation positions of the positioning bolts in the prism assembly.
9. The installation method of the pick-and-place machine according to claim 8, characterized in that, Based on the imaging error dataset, the spatial positions of the positioning bolts of the prism assembly are optimized through analysis to obtain optimized bolt positions, specifically including: The three-dimensional model of the prism assembly is parameterized and imported into the constructed mechanical-optical integrated model. At the same time, the imaging error dataset is used as the model input, and the installation coordinates (x1, y1) and (x2, y2) of the first and second positioning bolts on the first adjustment plate are defined as optimization variables. In the mechanical-optical integrated model, the initial spatial position and coordinate change constraint range of the optimization variables are set based on the physical structure of the first adjustment plate, and the convergence threshold of the optimization algorithm is configured with minimizing the imaging error function E as the optimization objective. The mechanical-optical integrated model is driven to perform iterative calculations. In each iteration, the model simulates and calculates the prism attitude and corresponding imaging error E under the action of external force P based on the current bolt spatial positions (x1, y1) and (x2, y2), and generates the next set of optimized bolt spatial positions based on the optimization algorithm. When the calculation result of the imaging error function E satisfies the convergence threshold, the iteration is terminated, and the corresponding bolt spatial points (x1, y1) and (x2, y2) are output as the optimal bolt points for manufacturing.
10. The installation method of the pick-and-place machine according to claim 9, characterized in that, The process of constructing the aforementioned mechanical-optical integrated model is as follows: An optical model is established, which is used to characterize the functional relationship between the beam splitter attitude and the imaging overlap of points A and B, namely the imaging error function E=f(Δx, Δy, Δα). A mechanical model is established to characterize the functional relationship between the external force and the deformation displacement of the prism at the support point, i.e., Δx=g(P, xi, yi); By coupling the optical model and the mechanical model, using the spatial position (xi, yi) of the positioning bolt as the optimization variable and minimizing the imaging error function E as the optimization objective, a mechanical-optical integrated model is constructed.