A connector manufacturing method with high-precision servo pick-and-place and riveting collaborative control

Abstract

This invention discloses a connector manufacturing method with high-precision servo-controlled material feeding and riveting coordination, belonging to the field of connector automated manufacturing technology. The method includes: system initialization and process package loading; a servo-controlled material feeding unit performing coarse positioning and conveying; a vision system acquiring images and calculating three-dimensional position deviations; a motion controller executing a look-ahead coordination algorithm to dynamically calculate the material feeding axis start-up timing based on the riveting head return state, achieving dual-axis spatiotemporal synchronization; superimposing the three-dimensional deviations onto the riveting head trajectory to achieve visually guided precise positioning; real-time acquisition of force-displacement data during riveting, comparison with a standard curve, alarming and eliminating abnormalities, automatically fine-tuning riveting parameters and feeding the trend forward to the coordination algorithm when systematic drift is detected; and recording key data after riveting completion. This invention achieves deep coordination between material feeding and riveting, significantly improving the precision, efficiency, and process adaptability of connector manufacturing, providing a data foundation for intelligent manufacturing.

Description

Technical Field

[0001] This invention relates to the field of connector automated manufacturing technology, and in particular to a connector manufacturing method with high-precision servo material feeding and riveting coordinated control. Background Technology

[0002] In the manufacturing process of high-end connectors, the stripping and crimping of terminals or plastic shells are two core and interrelated processes. Existing technologies typically employ these processes in relatively independent units.

[0003] For example, the servo-driven pressing equipment disclosed in CN223028976U only focuses on improving the precision of the riveting unit itself, while the material feeding unit still uses a traditional drive method. This results in low material feeding positioning accuracy and high randomness, and the accumulated deviation under high-speed production directly affects the riveting concentricity and product consistency. Second, the riveting assembly described in CN114552328A uses a passive correction structure with radial buffering and axial floating. When there are fluctuations in incoming materials, mold wear, or equipment temperature drift, it lacks the ability to actively adjust based on real-time feedback, resulting in poor process robustness and long changeover and adjustment times. For example, the servo-driven riveting system disclosed in CN120516385A uses a serial control logic of "positioning first, then compensation, then riveting". The material feeding and riveting actions are executed separately by independent control systems, resulting in waiting time between processes and preventing seamless connection, which limits further improvement in production cycle time. For example, the multi-servo system pre-simulation collaborative control method proposed in CN107203191A remains at the level of general motion control algorithms, without proposing specific hardware architectures and process closed-loop strategies for the specific process scenario of "material feeding-riveting," and lacks the ability to self-optimize process parameters based on process force perception. Similarly, the fully automatic crimping method disclosed in CN120955437A focuses on production management and material flow automation; the material feeding and riveting units remain information silos, and the pressure curve is only used for post-event detection and alarm, with the data not being fully utilized for process optimization and predictive maintenance.

[0004] In summary, existing technologies generally suffer from problems such as poor product consistency, low production efficiency, weak process adaptability, and insufficient intelligence due to inaccurate material feeding and positioning, and isolated riveting and feeding actions. Therefore, there is an urgent need for a manufacturing method that can treat material feeding and riveting as a whole, achieve high-precision, high-efficiency, and highly robust connections through dynamic collaboration of dual servo axes, real-time vision guidance, and force-displacement adaptive compensation. Summary of the Invention

[0005] To address the technical problems existing in the prior art, this invention provides a connector manufacturing method with high-precision servo material feeding and riveting coordinated control, comprising the following steps: S101. System initialization and process package loading: According to the model of the connector to be produced, the corresponding process package is called from the database. The process package includes at least motion parameters, visual parameters, force-displacement curve parameters, and coordination parameters. S102, the servo feeding unit performs coarse positioning conveying. The motion controller controls the servo feeding unit to convey the connector material to the coarse positioning area of ​​the riveting station according to the motion parameters in the process package, so that the material is within the field of view of the vision system. S103. The vision system acquires images and calculates position deviations. The vision system acquires material images located in the coarse positioning area, obtains the actual position coordinates of material feature points through image processing, compares them with the theoretical position coordinates in the process package, generates three-dimensional position deviation data including X-axis deviation, Y-axis deviation and angle deviation, and sends the deviation data to the motion controller. S104. The motion controller executes a look-ahead collaborative algorithm. The motion controller monitors the return motion of the riveting head in the servo riveting unit in real time. It calculates the remaining time required for the riveting head to reach the predetermined junction point based on the current position and current speed of the riveting head. At the same time, it calculates the shortest time required for the feeding shaft to start from a stationary state and deliver the material to the junction point based on the kinematic characteristics of the servo feeding unit. By adjusting the start time of the servo feeding unit, the two times are made equal, thereby achieving spatiotemporal synchronization of the feeding and riveting motion axes at the junction point. S105, Correction and precise positioning of the riveting head trajectory: The motion controller superimposes the three-dimensional position deviation data onto the theoretical pressing trajectory of the riveting head to generate a corrected spatial trajectory, and controls the servo riveting unit to descend along the corrected trajectory, so that the riveting head and the part of the material to be riveted are aligned at the micron level. S106. Servo riveting and force displacement real-time monitoring: During the downward pressing process of the riveting head, pressure and displacement data are collected in real time and fitted into a force displacement curve. This force displacement curve is compared with the standard process window curve in the process package. If the characteristic value of the real-time curve exceeds the preset fault tolerance zone, the machine is immediately stopped, an alarm is triggered, and the current product is removed. If the real-time curve experiences systematic drift but does not exceed the fault tolerance zone, the riveting parameters are automatically fine-tuned, and the drift trend is quantified into a time correction factor as a feedforward signal to adjust the material feeding start timing of subsequent cycles. S107. Complete riveting and data recording. After riveting is completed, the three-dimensional position deviation data, force-displacement curve characteristic values ​​and product identification information of this production are associated and stored in the database for quality traceability and process optimization.

[0006] As a preferred embodiment of this application, in step S101, the process package includes at least: acceleration, speed, and path point parameters for controlling the motion of the servo feeding unit and the servo riveting unit; feature point template images, search areas, and theoretical coordinates for visual guidance; standard force-displacement curves and their tolerance bands for quality criteria; and the coordinates of the junction points and the allowable range of synchronization errors for collaborative control.

[0007] As a preferred embodiment of this application, in step S103, the vision system obtains the pixel coordinates of the feature points through a template matching algorithm, and then converts the pixel coordinates into physical coordinates using pre-calibrated camera parameters and a hand-eye calibration matrix, thereby generating the three-dimensional position deviation data.

[0008] As a preferred embodiment of this application, in step S104, the motion controller recalculates the remaining time based on the real-time position and speed of the riveting head in each control cycle, and fine-tunes the speed curve of the feeding shaft by combining feedforward and feedback to ensure the synchronization accuracy of the two shafts at the junction point under disturbance conditions.

[0009] As a preferred embodiment of this application, in step S106, the comparison includes morphological comparison and feature value comparison; the morphological comparison uses a dynamic time warping algorithm or a curve integral difference algorithm to evaluate the curve similarity; the feature value comparison includes at least peak pressure comparison and total displacement comparison.

[0010] As a preferred embodiment of this application, in step S106, the systematic drift includes an overall upward shift of the pressure curve due to mold wear or a change in the slope of the curve due to changes in the hardness of material batches; when a mold wear trend is detected, the riveting termination displacement setting value is automatically increased; when a material hardness change trend is detected, the trend is quantified as a time correction factor to adjust the material feeding start timing.

[0011] As a preferred embodiment of this application, in step S107, the stored data also includes the version number of the currently used process package and equipment operating status parameters, the equipment operating status parameters including at least temperature and vibration data.

[0012] As a preferred embodiment of this application, the method involves a single multi-axis motion controller communicating with a servo feeding unit, a servo riveting unit, a vision system, and a data storage unit via a real-time industrial Ethernet bus to achieve closed-loop collaborative control throughout the entire process.

[0013] Compared with the prior art, the beneficial effects of the present invention are as follows: 1) Micron-level active positioning is achieved, ensuring ultimate product consistency. Through a dual positioning mechanism of "servo coarse positioning + visual fine correction", the alignment accuracy between the riveting head and the part of the material to be pressed is controlled within ±5 microns, fundamentally solving the product consistency problem caused by inaccurate material positioning.

[0014] 2) Dual-axis spatiotemporal collaboration is achieved, significantly improving production efficiency. Through a forward-looking collaborative algorithm, the material conveying and riveting head return are precisely overlapped at the junction point, completely eliminating waiting time between processes. Compared with the serial solution, the production cycle time is increased by 15%-30%.

[0015] 3) It achieves adaptive compensation for the process, enhancing system robustness. Based on the real-time monitoring and adaptive compensation mechanism of the force-displacement curve, it not only automatically fine-tunes the riveting parameters to cope with changes such as mold wear and material fluctuations, but also feeds the drift trend forward to the collaborative algorithm, realizing a leap from passive response to active prevention and solving the problem that passive solutions cannot adapt to changes in process conditions.

[0016] 4) A full-process digital foundation has been established, enhancing the level of intelligence. Process package management enables rapid production changeover, and the full recording of production data provides support for quality traceability and process optimization. It also enables mold life prediction, solving the problems of data silos and insufficient intelligence. It provides quantifiable, traceable, and optimizable process data for connector manufacturing, laying a solid foundation for moving towards a higher level of intelligent manufacturing. Attached Figure Description

[0017] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with the invention and, together with the description, serve to explain the principles of the invention.

[0018] 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, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 This is a general flowchart of the connector manufacturing method with high-precision servo material feeding and riveting coordinated control provided in the embodiments of the present invention.

[0020] Figure 2 This is a flowchart of system initialization and process package loading provided in an embodiment of the present invention.

[0021] Figure 3 This is a schematic diagram of the coarse positioning and conveying of the servo feeding unit provided in an embodiment of the present invention.

[0022] Figure 4This is a schematic diagram illustrating the principle of vision system positioning and deviation calculation provided in an embodiment of the present invention.

[0023] Figure 5 This is a schematic diagram of the spatiotemporal synchronization principle of the look-ahead collaborative algorithm provided in this embodiment of the invention.

[0024] Figure 6 This is a schematic diagram of the riveting head trajectory correction and precise positioning provided in an embodiment of the present invention.

[0025] Figure 7 This is a schematic diagram of the principle of real-time force-displacement monitoring and adaptive compensation provided in the embodiments of the present invention.

[0026] Figure 8 This is an architecture diagram of a connector manufacturing system with high-precision servo material feeding and riveting coordinated control provided in an embodiment of the present invention. Detailed Implementation

[0027] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0028] It should be noted that all directional indications (such as up, down, left, right, front, back, etc.) in the embodiments of the present invention are only used to explain the relative positional relationship and movement of each component in a certain specific posture (as shown in the figure). If the specific posture changes, the directional indication will also change accordingly.

[0029] Furthermore, the use of terms such as "first" and "second" in this invention is for descriptive purposes only and should not be construed as indicating or implying their relative importance or implicitly specifying the number of technical features indicated. Therefore, features defined with "first" and "second" may explicitly or implicitly include at least one of those features. Additionally, the technical solutions of the various embodiments can be combined with each other, but only on the basis of being achievable by those skilled in the art. When the combination of technical solutions is contradictory or impossible to implement, such a combination of technical solutions should be considered non-existent and not within the scope of protection claimed by this invention.

[0030] Example 1 This invention provides a connector manufacturing method with high-precision servo-controlled material feeding and riveting. This method integrates the servo material feeding unit and the servo riveting unit into an intelligent collaborative manufacturing unit through a unified motion controller, utilizing visual feedback and real-time force-displacement monitoring to achieve high-precision, high-efficiency, and highly adaptive connector production. Figure 1-7As shown, the specific steps include: S101, System Initialization and Process Package Loading Before production begins, operators input the specific model number of the connector to be produced via a human-machine interface. The system then retrieves the corresponding process package from the local database or the manufacturing execution system based on this model number. The process package is a predefined data set containing all the key parameters required for manufacturing that model of product. The process package is constructed based on extensive process testing and statistical analysis of historical production data for that connector model, and its content covers four aspects: motion control, vision positioning, quality criteria, and collaborative control. The first aspect of the data is motion parameters, which determine the basic motion characteristics of the servo feeding unit and the servo riveting unit. For the feeding unit, motion parameters include acceleration, deceleration, maximum speed, and the coordinates of the critical path points from the material picking position to the coarse positioning position. For the riveting unit, motion parameters include pressing speed, return speed, pressure limit, and holding time. The second aspect of the data is visual parameters, which guide the vision system to complete material positioning. Visual parameters include template images of the feature points of the material to be detected, the range of the visual search area, the similarity threshold of the template matching algorithm, and the theoretical position coordinates of the feature points under ideal conditions. The third aspect of the data is force-displacement curve parameters, which define the quality criteria of the riveting process. These parameters can be mathematical expressions of standard process window curves or sets of discrete points, and also include allowable deviation tolerance data, such as upper and lower limits of peak pressure, upper and lower limits of total displacement, and similarity thresholds of curve shape. The fourth aspect of the data is coordination parameters, which directly serve the spatiotemporal synchronization of the feeding and riveting axes. The coordination parameters include the lead time coefficient for starting the material feeding shaft, the spatial coordinates of the handover point, and the allowable range of synchronization error.

[0031] After the process package is loaded, the motion controller parses it and configures the relevant parameters into the drivers of the servo feeding unit, the servo riveting unit, and the vision processing unit. Simultaneously, the motion controller controls each actuator to complete the homing operation. The homing process is achieved by finding the origin switches and encoder zero-position signals of each axis, ensuring that each axis has an absolute position reference at each startup. The motion controller also checks the status of each sensor through a self-test program, including limit switches, grating signals, and zero-point drift of pressure sensors, ensuring the entire system is in a standby state. This initialization process lays the data and state foundation for subsequent high-precision collaborative manufacturing.

[0032] S102, Servo feeding unit performs coarse positioning conveying After system initialization, the production command is triggered, and the motion controller sends motion commands to the servo driver of the servo feeding unit. The servo feeding unit uses a high-rigidity linear module as the actuator, the core of which is a high-performance AC servo motor combined with a high-resolution absolute encoder. Based on the motion parameters set in the process package, the motion controller plans an optimal trajectory from the material picking position to the coarse positioning station, and controls the servo motor to execute precisely using a three-loop control system of position loop, speed loop, and current loop.

[0033] During the conveying process, the servo feeding unit carries a tray or special fixture containing connector materials. The tray is fixed to the moving platform of the feeding unit by positioning pins and a quick-clamping mechanism, ensuring no relative displacement occurs during high-speed acceleration and deceleration. When the material is conveyed to the coarse positioning area near the riveting station, the motion controller controls the servo feeding unit to stop smoothly according to a preset deceleration curve. At this time, due to factors such as mechanical transmission clearance, inertia, and load fluctuations, there is a certain deviation between the actual stopping position of the material and its ideal position, typically within ±0.1 mm to ±0.5 mm. Although this accuracy is not sufficient for direct riveting, it is sufficient to ensure that the material is within the effective field of view of the subsequent vision system. At this point, the coarse positioning conveying step is completed, and the motion controller sends a trigger pulse to the vision system via a digital output signal to initiate the next step of precise positioning. The delay between the rising edge of this trigger pulse and the moment the material stops stably is strictly controlled at the microsecond level to ensure that the vision system acquires images at the optimal time.

[0034] S103. The vision system acquires images and calculates positional deviations. The vision system begins operation immediately upon receiving a trigger pulse. It consists of two high-resolution macro industrial cameras with matching high-performance lenses, an adjustable-brightness LED light source, and an independent image processing unit. The dual-camera layout aims to improve positioning accuracy through stereo vision or multi-view imaging, especially for materials with complex three-dimensional structures. The cameras are fixedly mounted on the frame, with their optical axes perpendicular to the plane of the material, covering the entire coarse positioning area. The light source is controlled by appropriate illumination angles and stroboscopic adjustment to ensure that feature points on the material surface are clearly imaged. Figure 4 As shown, the specific implementation is as follows: First, the motion controller triggers the camera to acquire signals. Two cameras simultaneously capture digital images of the current material and transmit the image data to the image processing unit via a high-speed interface. The image processing unit runs a pre-defined vision algorithm, the core of which is template matching. The image processing unit first preprocesses the image, including grayscale conversion, Gaussian filtering for noise reduction, and contrast enhancement, to improve image quality. Then, the image processing unit constructs an image pyramid, performing a fast, coarse search at the low-resolution layer to identify candidate regions; followed by a fine search at the high-resolution layer to find the position with the highest similarity to the feature point templates pre-stored in the process package. The template matching algorithm uses normalized cross-correlation as a similarity metric, which is insensitive to changes in illumination. Through sub-pixel interpolation and a quadratic surface fitting method, the image processing unit can improve the feature point localization accuracy to within 0.1 pixels, thereby accurately calculating the pixel coordinates of the feature points in the image coordinate system and obtaining the rotation angle of the material by calculating the geometric relationship of the feature point array.

[0035] Subsequently, using the camera intrinsic parameters and hand-eye calibration matrix obtained beforehand through calibration, the image processing unit converts the pixel coordinates into actual coordinates in the physical coordinate system. Camera calibration employs the Zhang Zhengyou calibration method, using a high-precision checkerboard calibration board to acquire multiple images and calculate the camera's intrinsic parameter matrix and distortion coefficients. Hand-eye calibration involves controlling the material handling unit to move the calibration board to multiple known positions while simultaneously capturing images, and using classical hand-eye calibration to solve the transformation relationship between the camera coordinate system and the material handling unit coordinate system. This transformation process eliminates the effects of lens distortion, camera mounting angle, and perspective projection.

[0036] After obtaining the actual coordinates, the image processing unit compares them with the theoretical coordinates in the process package to generate a three-dimensional position deviation. The X-direction deviation equals the actual X-coordinate minus the theoretical X-coordinate, the Y-direction deviation equals the actual Y-coordinate minus the theoretical Y-coordinate, and the angle deviation equals the actual angle minus the theoretical angle. This deviation data is immediately sent to the motion controller via real-time industrial Ethernet as the basis for subsequent trajectory correction. The entire image acquisition and deviation calculation process is extremely short, and this time overlaps with the mechanical motion time, thus not significantly affecting the production cycle.

[0037] S104, The motion controller executes the look-ahead cooperative algorithm. The motion controller is the decision-making core of the entire collaborative manufacturing process. It receives real-time information from multiple sources, including the servo riveting unit, the servo material handling unit, and the vision system, and dynamically adjusts the motion commands of each axis through a built-in look-ahead collaborative algorithm. The core objective of this algorithm is to achieve precise temporal and spatial overlap between the material handling and riveting axes, thereby completely eliminating idle time caused by process waiting in traditional manufacturing methods. Figure 5 As shown, the specific implementation is as follows: The motion controller continuously monitors the operating status of the servo riveting unit. After the riveting operation of the previous cycle is completed, the riveting head begins its upward return stroke. The motion controller obtains the current position and speed of the riveting head in real time by reading the encoder feedback from the servo motor of the riveting head. At the same time, the process package has predefined the junction point between material feeding and riveting. The junction point is usually located at a certain height above the riveting station, a spatial point where the material and the riveting head can safely meet without interference. The coordinates of this point are determined during equipment design based on the geometry of the riveting head and the highest point of the material, and have been verified in practice to ensure safety.

[0038] The motion controller calculates the remaining time required for the riveting head to reach the junction point from its current position using predictive control methods, based on the real-time motion parameters of the riveting head. Under the assumption of ideal uniform motion, the remaining time equals the difference between the junction point position and the current position divided by the current velocity. However, the actual algorithm considers acceleration and velocity planning, employing a more accurate integral or predictive model. Simultaneously, based on the kinematic characteristics of the servo feeding unit (known maximum acceleration, deceleration, and maximum velocity), the motion controller calculates the shortest time required for the feeding shaft to start from its current stationary state and smoothly deliver the material from its current position to the junction point. The goal of the motion controller is to adjust the start time of the feeding shaft so that the shortest time required for the feeding shaft to deliver the material to the junction point is precisely equal to the remaining time required for the riveting head to reach the junction point. In other words, when the riveting head passes a specific position, the motion controller sends a start command to the servo feeding unit, ensuring that when the riveting head arrives at the junction point, the feeding shaft also delivers the material to the same spatial point. This process transforms two originally sequential actions into parallel actions, achieving spatiotemporal overlap.

[0039] Because of various minute disturbances (such as friction fluctuations and load changes) in actual motion, the motion controller recalculates the aforementioned time difference in each control cycle and fine-tunes the speed curve of the feeding shaft through a combination of feedforward and feedback to ensure precise synchronization during handover. This dynamic adjustment mechanism greatly enhances the robustness of the system.

[0040] S105, Riveting head trajectory correction and precise positioning After the feeding shaft delivers the material to the handover point, the riveting head continues its downward movement. However, the downward trajectory of the riveting head at this point is not simply a vertical movement, but is dynamically corrected based on the deviation data generated by the S103 vision system. For example... Figure 6 As shown, the specific implementation is as follows: The motion controller superimposes the three-dimensional deviation onto the theoretical pressing trajectory of the riveting head, generating a corrected spatial trajectory. In practice, the motion controller converts the deviation into position compensation commands attached to each motion axis of the servo riveting unit. If the riveting head only has a vertical degree of freedom, and horizontal position adjustment requires moving the entire riveting unit, the motion controller coordinates the simultaneous movement of the X and Y axis motion platforms and the Z axis of the riveting unit. If the riveting head itself has multiple degrees of freedom, its posture is directly adjusted. This process is equivalent to using the vision system as the "eye" and the riveting head as the "hand," achieving vision-guided servo control.

[0041] In the final stage of the riveting head's descent, just before it contacts the material, the visual deviation has been precisely compensated for, achieving micron-level alignment between the riveting head and the part of the material to be riveted (e.g., the crimping part on a terminal and the hole on a plastic shell). At this point, the error between the actual and theoretical positions of the riveting head is controlled within ±5 microns, creating the necessary conditions for high-quality riveting.

[0042] S106, Servo riveting and real-time force-displacement monitoring The riveting head continues its downward movement, entering the crimping stage. The servo riveting unit uses a servo electric cylinder as the actuator, which integrates high-precision pressure and displacement sensors, or directly utilizes a servo motor encoder for displacement detection. These two sensors continuously acquire pressure and displacement data at an extremely high synchronous sampling rate, forming a raw data stream. For example... Figure 7 As shown, the specific implementation is as follows: Data is immediately sent to the motion controller for processing after acquisition. First, the motion controller fits the acquired discrete data points into a continuous force-displacement curve in real time, with displacement on the x-axis and pressure on the y-axis. Second, the motion controller performs a multi-dimensional comparison between the real-time curve and the pre-stored standard process window curve in the process package. This comparison includes two aspects: morphological comparison and eigenvalue comparison. Morphological comparison uses a dynamic time warping algorithm or calculates the integral difference of the curve within a certain interval to assess the overall similarity of the curves. Eigenvalue comparison extracts key features of the real-time curve, such as peak pressure, total displacement, and the location of curve inflection points, and compares them with the allowable range in the standard window.

[0043] Based on the comparison results, the motion controller makes two types of responses. The first response is anomaly handling. If any characteristic value of the real-time curve exceeds the set tolerance band—for example, a peak pressure exceeding the upper limit indicates that the material may be too hard or that foreign objects are present, or a total displacement less than the lower limit indicates that it may not be properly pressed—the motion controller immediately issues a stop command and simultaneously controls the alarm device to alert the operator with sound and light. The motion controller records the product's serial number and its abnormal data, and controls subsequent actuators to automatically remove it from the production line, preventing defective products from flowing into the next stage.

[0044] The second response is adaptive compensation. If the real-time curve does not exceed the tolerance zone, but the motion controller detects a systematic drift of the curve relative to the standard window—for example, multiple consecutive products exhibiting the same slight deviation, such as slightly higher peak pressure or slightly larger displacement—the motion controller will activate the adaptive compensation mechanism. This mechanism utilizes a built-in parameter identification mechanism to analyze the trend and magnitude of the drift, and then automatically fine-tunes the process parameters. A typical compensation scenario is mold wear: as the number of times the mold is used increases, the pressure required to achieve the same riveting depth gradually increases, resulting in an overall upward shift in the pressure curve. Upon recognizing this trend, the motion controller automatically increases the riveting termination displacement setting by a small increment to ensure the final crimping state is consistent with the standard part. Another compensation scenario is batch hardness variation in materials: if a new batch of material is slightly harder, causing the pressure curve to rise faster, the motion controller will not only adjust the termination displacement but also send this trend as a feedforward signal to the look-ahead collaborative algorithm module to adjust the timing of subsequent material handover. Specifically, the motion controller quantifies the drift trend into a time correction factor, which is added to the calculation of the shortest time required for S104 to reach the handover point. This allows for preventative adjustments to the start-up timing of the feeding shaft in the next cycle, achieving a leap from passive response to proactive prevention.

[0045] Throughout the entire riveting process, the acquisition, comparison, anomaly response, and adaptive compensation of force-displacement data are all completed within milliseconds, without affecting the normal production cycle.

[0046] S107. Complete riveting and data recording. Once the riveting head reaches the adaptively adjusted termination position, the system sets a short holding time to ensure sufficient plastic deformation of the crimped area. After the holding time ends, the motion controller controls the riveting head to quickly rise back to the initial position according to the return speed command set in the process package, preparing for the next work cycle. At the same time, the servo feeding unit removes the riveted material from the station and feeds the next material to be processed into the coarse positioning area.

[0047] As the riveting head returns to its original position, the motion controller uploads all key production data to the data storage and processing unit. This data includes: the 3D deviation generated by the S103 vision system; the complete force-displacement curve recorded by the S106 system and its key characteristic values, such as peak pressure and total displacement; the product's unique serial number or production timestamp; the currently used process package version number; and equipment operating status parameters, such as temperature and vibration. All data is organized into structured records and stored in a local database or cloud server.

[0048] This accumulated data provides immense value for subsequent work. Quality engineers can quickly trace the production process of a specific batch of products by querying the database and analyze the causes of defects. Process engineers can utilize historical data to optimize process package parameters, making the production process more stable and efficient. Equipment maintenance personnel can also predict the remaining life of molds by analyzing the long-term trends of force-displacement curves, enabling predictive maintenance and avoiding unplanned downtime.

[0049] The above seven steps are repeated cyclically, constituting the complete connector manufacturing process. The entire process achieves deep collaboration between the two core processes of material selection and riveting, and through visual feedback and force-displacement closed-loop control, it achieves the manufacturing goals of high precision, high efficiency, and high adaptability.

[0050] Example 2 This invention also provides a connector manufacturing system with high-precision servo-controlled material feeding and riveting coordination. The various units of this system are interconnected via a high-speed fieldbus, forming a unified, high-real-time control network to jointly achieve the coordinated control process. For example... Figure 8 As shown, it specifically includes: Rack and foundation The frame serves as the system's supporting foundation, constructed from high-strength cast iron or welded steel. It undergoes aging treatment to eliminate internal stress, ensuring excellent dimensional stability during long-term use. Precision linear guides and ball screws are mounted on the frame surface, providing high-rigidity motion guidance for the servo feeding and riveting units. An enclosed electrical cabinet houses servo drives, power modules, motion controllers, industrial switches, and other electrical components. This cabinet features excellent heat dissipation and electromagnetic shielding to ensure reliable operation of the electronic equipment in complex industrial environments. Furthermore, mounting reference surfaces for each unit are arranged on the frame to guarantee spatial positioning accuracy between the motion axes.

[0051] Servo feeding unit The servo feeding unit is mounted on the lower worktable of the frame and is responsible for conveying materials. Its hardware consists of a high-performance AC servo motor, a transmission mechanism, a material carrier, and limit sensors. The servo motor is equipped with a high-resolution absolute encoder, enabling precise position and speed control. The transmission mechanism can be either a linear module or a direct-drive rotary mechanism, depending on the application: the linear module uses a combination of precision ball screws and linear guides, suitable for linear reciprocating conveying; the direct-drive rotary mechanism uses a DD motor with zero backlash, suitable for rotary multi-station worktables. The material carrier is designed with precise positioning pins and a quick-clamping mechanism to ensure no displacement of materials during high-speed conveying. The carrier also has calibration reference points for vision system calibration. The limit sensors include photoelectric limit switches at both ends of the travel and a high-precision origin switch for zeroing and overtravel protection.

[0052] Servo riveting unit The servo riveting unit is mounted on the upper crossbeam of the frame, positioned opposite the servo feeding unit, and is responsible for performing the riveting action. Its hardware components include an integrated servo electric cylinder, a high-precision pressure sensor, a displacement detection element, a quickly replaceable riveting head, and a precision guiding mechanism. The servo electric cylinder integrates the servo motor, ball screw, and cylinder body into one unit, offering advantages such as high thrust, fast response, and high positioning accuracy. The pressure sensor uses a strain gauge or piezoelectric structure, installed between the piston rod end of the electric cylinder and the riveting head. The measuring range is selected according to product requirements, with an accuracy better than 0.1% of full scale. Displacement detection directly utilizes the servo motor's built-in encoder, converting linear displacement through the ball screw lead, achieving a resolution of 0.1 micrometers; and full closed-loop control is achieved through a grating ruler. The riveting head is designed with a quickly replaceable structure based on the connector model, its end shape precisely matching the part to be riveted, and an internal guiding structure can be installed. The guiding mechanism uses precision guide posts and sleeves to eliminate the influence of lateral forces on riveting accuracy.

[0053] Visual unit The vision unit is used to achieve high-precision positioning of materials. Its hardware consists of a high-resolution industrial camera, a high-performance lens, an adjustable LED light source, and an image processing unit. The camera uses a CMOS or CCD sensor with at least five megapixels and a global shutter to capture fast-moving materials without motion blur. The lens is selected based on the working distance and field of view, using either a telecentric lens or a standard CCTV lens to ensure low-distortion imaging. The light source can be configured as a ring light, backlight, or coaxial light, with brightness and flicker controlled by PWM. The image processing unit can be an embedded processor built into the camera or a standalone industrial computer, running image processing algorithms. All cameras and light sources are fixed to the frame using precision mounting brackets, positioned diagonally or directly above the riveting station, covering the entire coarse positioning area without interfering with the movement of the material feeding and riveting mechanisms.

[0054] motion controller The motion controller is the core of the system, responsible for the execution of all algorithms and the coordination of instructions. Its hardware platform adopts a PC-based software motion controller or a high-performance dedicated motion controller, which has multi-axis synchronous control capabilities, supports real-time industrial Ethernet protocols such as EtherCAT, and exchanges data at high speed with servo drives, I / O modules, sensors, etc. via bus.

[0055] The motion controller integrates multiple core software modules: The multi-axis interpolator is responsible for the precise trajectory planning and interpolation calculation of the servo feeding axis and the servo riveting axis. It supports linear interpolation, circular interpolation and spline curve interpolation to ensure smooth motion.

[0056] The forward-looking collaborative algorithm module receives real-time feedback on the current position and speed of the riveting head, combines it with the coordinates of the junction point in the process package, dynamically calculates the optimal start time for the material feeding shaft, and generates corresponding motion commands; at the same time, it fine-tunes the speed curve in real time according to the disturbance to ensure that the two axes are precisely synchronized at the junction point.

[0057] The vision servo module receives deviation data sent by the vision unit and converts it into a dynamic correction amount for the riveting shaft trajectory, thereby realizing a vision-based position closed loop.

[0058] The force-displacement monitoring module acquires data from pressure and displacement sensors at high frequency, generates force-displacement curves in real time, and compares them with standard curves. It runs an adaptive compensation algorithm to automatically adjust riveting parameters based on curve drift trends and quantifies the drift trends as time correction factors for use by the forward-looking collaborative algorithm.

[0059] The process package management module is responsible for storing, retrieving, and parsing process packages. During production changeovers, it quickly distributes the parameters of the new process package to each execution module.

[0060] The motion controller also provides an Ethernet interface for communication with the data storage unit and MES system, as well as USB and serial interfaces for local debugging.

[0061] Data storage and processing unit The data storage and processing unit consists of an industrial-grade industrial control computer server, running a relational database system and data visualization software. The unit connects to the motion controller via Ethernet to receive and store production data in real time.

[0062] The main functions of the data storage and processing unit include: process package database management, which centrally stores process package parameters for all connector models, supporting import, export, editing, and version control; production data recording, which receives visual deviations, force-displacement curve characteristic values, production timestamps, equipment status, etc. for each product, and organizes them into the database by batch and time; and quality traceability and analysis, which provides a query interface that allows users to retrieve historical data by product batch, time period, or serial number, and displays the distribution and trends of key process parameters through charts, providing a basis for quality analysis and process optimization.

[0063] Auxiliary Unit The auxiliary unit includes a human-machine interface, alarm and safety devices, and a material handling mechanism. The human-machine interface uses an industrial touchscreen, installed in an easily accessible location on the rack, to display system status, process parameters, and real-time alarm information, allowing operators to set parameters, perform manual operations, and issue production commands. Alarm and safety devices include a three-color alarm light, safety light curtains, an emergency stop button, and safety door locks to ensure the safety of personnel and equipment. The material handling mechanism is responsible for automatically conveying materials to be processed to the carrier of the servo-driven material feeding unit and removing finished products to the next workstation or material bin.

[0064] Through the organic integration of the above-mentioned units, a complete collaborative control platform is constructed. The servo material feeding unit and the servo riveting unit, under the scheduling of a unified motion controller, achieve spatiotemporal synchronization using a look-ahead collaborative algorithm. The vision unit provides high-precision position deviation measurement, guiding the riveting head to precise alignment. The force-displacement monitoring module not only ensures crimping quality in real time but also feeds forward process drift to the collaborative control through adaptive compensation, forming a closed-loop process. The data storage and processing unit provides data support for quality traceability and process optimization. The entire system achieves high-precision collaboration between material feeding and riveting, significantly improving the efficiency, consistency, and intelligence level of connector manufacturing.

[0065] Example 3 The present invention also provides an electronic device, including: a processor, a transmitting device, an input device, an output device, and a memory. The processor may be implemented using a general-purpose CPU (Central Processing Unit), a microprocessor, an application-specific integrated circuit, or one or more integrated circuits, and is used to execute relevant programs to implement the technical solutions provided in the embodiments of this application. The memory may be implemented using a read-only memory (ROM), a static storage device, a dynamic storage device, or a random access memory (RAM), and is used to store computer program code. The computer program code includes computer instructions. When the processor executes the computer instructions, the electronic device executes a method as described in any of the above possible implementation methods.

[0066] Example 4 The present invention also provides a computer-readable storage medium storing a computer program, the computer program including program instructions, which, when executed by a processor of an electronic device, cause the processor to perform a method as described in any of the above possible implementations.

[0067] In the description of this specification, the references to terms such as "an embodiment," "example," "specific example," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the present invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0068] The above description is merely a specific embodiment of the present invention, enabling those skilled in the art to understand or implement the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the present invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features claimed herein.

Claims

1. A connector manufacturing method with high-precision servo-controlled material feeding and riveting, characterized in that, Includes the following steps: S101. System initialization and process package loading: According to the model of the connector to be produced, the corresponding process package is called from the database. The process package includes at least motion parameters, visual parameters, force-displacement curve parameters and coordination parameters. S102, the servo feeding unit performs coarse positioning conveying. The motion controller controls the servo feeding unit to convey the connector material to the coarse positioning area of ​​the riveting station according to the motion parameters in the process package, so that the material is within the field of view of the vision system. S103. The vision system acquires images and calculates position deviations. The vision system acquires material images located in the coarse positioning area, obtains the actual position coordinates of material feature points through image processing, compares them with the theoretical position coordinates in the process package, generates three-dimensional position deviation data including X-axis deviation, Y-axis deviation and angle deviation, and sends the three-dimensional position deviation data to the motion controller. S104. The motion controller executes a look-ahead collaborative algorithm. The motion controller monitors the return motion of the riveting head in the servo riveting unit in real time. It calculates the remaining time required for the riveting head to reach the predetermined junction point based on the current position and current speed of the riveting head. At the same time, it calculates the shortest time required for the feeding shaft to start from a stationary state and deliver the material to the junction point based on the kinematic characteristics of the servo feeding unit. By adjusting the start time of the servo feeding unit, the two times are made equal, thereby achieving spatiotemporal synchronization of the feeding and riveting motion axes at the junction point. S105, Correction and precise positioning of the riveting head trajectory: The motion controller superimposes the three-dimensional position deviation data onto the theoretical pressing trajectory of the riveting head to generate a corrected spatial trajectory, and controls the servo riveting unit to descend along the corrected trajectory, so that the riveting head and the part of the material to be riveted are aligned at the micron level. S106. Servo riveting and force displacement real-time monitoring: During the downward pressing process of the riveting head, pressure and displacement data are collected in real time and fitted into a force displacement curve. This force displacement curve is compared with the standard process window curve in the process package. If the characteristic value of the real-time curve exceeds the preset fault tolerance zone, the machine is immediately stopped, an alarm is triggered, and the current product is removed. If the real-time curve experiences systematic drift but does not exceed the fault tolerance zone, the riveting parameters are automatically fine-tuned, and the drift trend is quantified into a time correction factor as a feedforward signal to adjust the material feeding start timing of subsequent cycles. S107. Complete riveting and data recording. After riveting is completed, store the three-dimensional position deviation data, force-displacement curve characteristic values ​​and product identification information related to this production in the database for quality traceability and process optimization.

2. The method according to claim 1, characterized in that, In step S101, the motion parameters include at least: acceleration, speed, and path point parameters for controlling the motion of the servo feeding unit and the servo riveting unit; The visual parameters include at least the feature point template image for visual guidance, the search region, and the theoretical coordinates.

3. The method according to claim 2, characterized in that, In step S101, the force-displacement curve parameters include at least the standard force-displacement curve and its tolerance band used for quality criteria. The coordination parameters include at least the coordinates of the handover point used for coordination control and the allowable range of synchronization error.

4. The method according to claim 3, characterized in that, In step S103, the vision system obtains the pixel coordinates of feature points through a template matching algorithm, and then converts the pixel coordinates into physical coordinates using pre-calibrated camera parameters and hand-eye calibration matrix, thereby generating the three-dimensional position deviation data.

5. The method according to claim 4, characterized in that, In step S104, the motion controller recalculates the remaining time based on the real-time position and speed of the riveting head in each control cycle, and fine-tunes the speed curve of the feeding shaft by combining feedforward and feedback to ensure the synchronization accuracy of the two axes at the junction point under disturbance conditions.

6. The method according to claim 5, characterized in that, In step S106, the comparison includes morphological comparison and feature value comparison; the morphological comparison uses a dynamic time warping algorithm or a curve integral difference algorithm to evaluate the curve similarity; the feature value comparison includes at least peak pressure comparison and total displacement comparison.

7. The method according to claim 6, characterized in that, In step S106, the systematic drift includes an overall upward shift of the pressure curve due to mold wear or a change in the slope of the curve due to changes in the hardness of material batches.

8. The method according to claim 7, characterized in that, Step S106 further includes: when a wear trend of the mold is detected, automatically increasing the riveting termination displacement setting value; when a change trend of material hardness is detected, quantifying the trend as a time correction factor to adjust the material feeding start timing.

9. The method according to claim 8, characterized in that, In step S107, the stored data also includes the version number of the currently used process package and equipment operating status parameters, which include at least temperature and vibration data.

10. The method according to claim 9, characterized in that, The method involves a single multi-axis motion controller communicating with a servo feeding unit, a servo riveting unit, a vision system, and a data storage unit via a real-time industrial Ethernet bus to achieve closed-loop collaborative control throughout the entire process.

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