A control system of a hot air expansion intelligent production line for metal pipe parts

Abstract

A control system of a metal pipe component hot air expansion intelligent production line, the production line comprises a heating special machine and a general control system, the heating special machine comprises a vision system, an infrared temperature measurement probe, a multi-axis servo sliding table carrying the infrared temperature measurement probe, and a heating device; the general control system is configured to, during the heating of the workpiece by the heating special machine, perform the following operations: obtaining a real-time profile image of the workpiece based on the vision system; identifying the actual thermal deformation state of the workpiece caused by heating through image analysis; dynamically adjusting the position of the infrared temperature measurement probe through the multi-axis servo sliding table according to the actual thermal deformation state, so that the temperature measurement area of the infrared temperature measurement probe is always locked on the preset target area of the workpiece surface; based on the temperature data collected by the infrared temperature measurement probe after the position is adjusted, the output power of the heating device is closed-loop adjusted, and the problem of heating out of control caused by temperature measurement failure is solved.

Description

Technical Field

[0001] This article relates to intelligent manufacturing technology, specifically a control system for an intelligent production line for thermal expansion of metal tubular components. Background Technology

[0002] Semi-automated production lines have been adopted for the production of hot-expansion metal tubular components. These lines physically connect multiple automated machines with handling robots, achieving basic automation from billet loading to finished product unloading, thus reducing direct human intervention to some extent. However, in actual operation, these semi-automated production lines still require optimization. Summary of the Invention

[0003] This application provides a control system for an intelligent production line for thermal expansion of metal tubular components. The production line includes a dedicated heating machine and a central control system. The dedicated heating machine includes a vision system, an infrared temperature probe, a multi-axis servo slide that carries the infrared temperature probe, and a heating device. The central control system is configured to perform the following operations during the heating process of the workpiece by the heating machine: The vision system acquires a real-time contour image of the workpiece. Image analysis is used to identify the actual thermal deformation state of the workpiece caused by heating; Based on the actual thermal deformation state, the position of the infrared temperature probe is dynamically adjusted by the multi-axis servo slide, so that the temperature measurement area of ​​the infrared temperature probe is always locked on the preset target area on the workpiece surface. Based on the temperature data collected by the infrared temperature probe after its position is adjusted from the preset target area, the output power of the heating device is adjusted in a closed loop.

[0004] This application embodiment utilizes a vision system to acquire real-time contour images of a workpiece under heating conditions, and quantitatively extracts thermal deformation information of the workpiece through image analysis. This thermal deformation information is used as input to servo control, driving a multi-axis servo slide carrying an infrared temperature probe to follow the movement, compensating for the positional deviation of the temperature measurement point caused by workpiece deformation, ensuring that the temperature measurement spot remains locked within the effective temperature measurement area of ​​the workpiece even after deformation. Based on this, the actual temperature data collected from the locked area is used as closed-loop feedback to adjust the output power of the heating device, eliminating positional errors in the temperature measurement process and fundamentally solving the heating runaway problem caused by temperature measurement failure.

[0005] Other features and advantages of this application will be set forth in the following description, and will be apparent in part from the description, or may be learned by practicing the application. Other advantages of this application can be realized and obtained by means of the embodiments described in the description and the accompanying drawings. Attached Figure Description

[0006] The accompanying drawings are used to provide an understanding of the technical solutions of this application and constitute a part of the specification. They are used together with the embodiments of this application to explain the technical solutions of this application and do not constitute a limitation on the technical solutions of this application.

[0007] Figure 1 A schematic diagram of the plan layout of an intelligent production line for thermal expansion of metal tubular components provided in an embodiment of this application; Figure 2 This is a flowchart illustrating the processing method of the overall control system provided in this application embodiment during the heating process of the workpiece by the heating machine. Detailed Implementation

[0008] This application describes several embodiments, but these descriptions are exemplary and not limiting, and it will be apparent to those skilled in the art that many more embodiments and implementations are possible within the scope of the embodiments described herein. Although many possible combinations of features are shown in the drawings and discussed in the detailed description, many other combinations of the disclosed features are also possible. Unless specifically limited, any feature or element of any embodiment may be used in combination with, or may replace, any feature or element of any other embodiment.

[0009] This application includes and contemplates combinations of features and elements known to those skilled in the art. The embodiments, features, and elements disclosed in this application can also be combined with any conventional features or elements to form unique inventive solutions. Any feature or element of any embodiment can also be combined with features or elements from other inventive solutions to form another unique inventive solution. Therefore, it should be understood that any feature shown and / or discussed in this application can be implemented individually or in any suitable combination. Therefore, the embodiments are not limited except by the limitations imposed by the appended claims and their equivalents. Furthermore, various modifications and changes can be made within the scope of the appended claims.

[0010] Furthermore, in describing representative embodiments, the specification may have presented methods and / or processes as a specific sequence of steps. However, the method or process should not be limited to the specific order of steps described herein, to the extent that it does not depend on such a specific order. As will be understood by those skilled in the art, other sequences of steps are also possible. Therefore, the specific order of steps set forth in the specification should not be construed as a limitation of the claims. Moreover, the claims concerning the method and / or process should not be limited to the steps performed in the written order, and those skilled in the art will readily understand that these orders can be varied and still remain within the spirit and scope of the embodiments of this application.

[0011] Figure 1 This is a schematic plan view of the intelligent production line for thermal expansion of metal tubular components provided in an embodiment of this application. Figure 1 As shown, this thermal expansion intelligent production line is physically protected by a closed-off safety fence, within which is a fully automated, unmanned operating area. Safety doors are installed at corresponding locations within the fence, allowing authorized personnel to enter for maintenance or handling of any malfunctions.

[0012] The main equipment deployed on the production line includes: a central control cabinet and human-machine interface (HMI), depalletizing bins, a preforming press, a heating machine, a final forming press (i.e., a hot air expansion machine), a palletizing bin, a gripping mechanism storage platform, and four six-axis industrial robots. The four six-axis industrial robots are configured sequentially according to the process flow direction as a loading robot, a first transfer robot, a second transfer robot, and an unloading robot. Each robot is equipped with a corresponding robot control cabinet and can be configured with gripping mechanisms of different functions. When not in use, each gripping mechanism is stored on the gripping mechanism storage platform. The production line has AGV loading and unloading stations at the depalletizing and palletizing ends, respectively, for automatic material supply and finished product output.

[0013] The following is a description of some of the equipment: 1. Central Control System: The central control system adopts a centralized CPU and bus communication control architecture. The core controller of the central control system can be a high-performance industrial PLC or industrial PC, serving as the communication master station. It establishes data interconnection with the controllers of various devices on the production line via industrial Ethernet or fieldbus, enabling unified command scheduling and status monitoring of various dedicated machines and industrial robots. The central control system is equipped with a human-machine interface, which can be an industrial touchscreen or a host computer monitoring display, to display the real-time operating status of each device on the production line, current process parameters, production progress, and energy consumption information. It also provides operation entry points for product changeover, parameter setting, and alarm query.

[0014] In terms of safety protection, the central control system integrates a safety PLC module, and the production line is equipped with safety devices such as safety door locks, safety light curtains, emergency stop buttons, and safety relays. Each safety device is connected to the input channel of the safety PLC module. The central control system continuously monitors the status of the safety area through the safety PLC module, and when a safety device is detected to be triggered, it can promptly issue an audible and visual alarm signal or execute a shutdown protection.

[0015] 2. Industrial robots: Each industrial robot communicates with the central control system via a standard industrial Ethernet interface, receiving action commands from the system and reporting its current operating status. Each robot's end flange is equipped with a quick-change disc (tool changer), enabling rapid and automatic replacement of different gripping mechanisms. These gripping mechanisms include, but are not limited to, single-jaw, double-jaw, and palletizing grippers, with different gripping methods and forces configured according to process requirements (gripping raw tubes, transferring pre-formed workpieces, transferring high-temperature workpieces, and palletizing finished products). When not in use, each gripping mechanism is stored on a gripping mechanism storage platform. The platform has multiple fixed stations, each corresponding to a different gripping mechanism model, facilitating automatic robot positioning and gripper replacement.

[0016] In addition, the loading station and transfer station are equipped with transfer positioning platforms, which are equipped with precision positioning mechanisms and workpiece in-situ detection sensors. The in-situ detection sensors can be photoelectric switches or proximity switches, used to confirm whether the workpiece has been placed in place, and feed the detection signal back to the central control system as one of the condition signals to trigger the robot to start grasping in the next process.

[0017] 3. Heating machine: The heating machine adopts a fully enclosed structure with separate water and electricity systems. The cooling water circuit and electrical wiring inside the heating unit are physically isolated, with cooling water pipe joints and cable joints routed in separate, isolated channels to prevent electrical short circuits due to pipe leaks. The worktable of the heating machine uses a composite structure of bakelite and mica boards. The bakelite serves as the base layer, providing mechanical strength and insulation, while the mica board is laid on top of the bakelite, corresponding to the area in contact with the workpiece, providing high-temperature resistance and insulation. Through this structural design, the heating machine can effectively protect the internal electrical components and the safety of operators under long-term high-temperature operating conditions.

[0018] 4. Hot air expansion machine: The hot air expansion press, also known as the final forming press, is primarily a servo hydraulic press. The hydraulic power system of this servo hydraulic press uses a servo pump assembly, which consists of a servo driver, a servo motor, and an internally meshing high-pressure gear pump. A pressure sensor is installed in the upper chamber of the main cylinder to monitor the hydraulic pressure within the cylinder in real time during mold closing and pressurization. A displacement sensor is installed at the slide block to monitor the slide block's position during the mold closing process. The control device of the hot air expansion press uses a combination of a PLC (Programmable Logic Controller) and an industrial computer. The PLC is responsible for logic control and the sequential operation of each valve group, while the industrial computer is responsible for storing and displaying process parameters and interacting with the central control system.

[0019] During the hot gas expansion molding process, the control system calculates the target speed required by the servo motor using a PID control algorithm based on pressure feedback signals, position feedback signals, and preset pressure, position, and speed setpoint signals. This, in turn, controls the output flow of the high-pressure gear pump, achieving closed-loop control of the mold closing pressure, slide speed, and position. The servo motor operates differently at different stages: during the rapid descent of the slide and when the slide is stationary at its upper limit for loading and unloading, the servo motor speed is zero, and the pump has no output. During the pressurization and return phases of the slide, the servo motor speed is determined by the set working speed and required pressure. During the pressure holding phase, the servo motor speed only needs to compensate for internal leakage in the pump and minor leakage in the hydraulic system, maintaining the pressure holding pressure at extremely low speed. Through this servo control scheme, the hot gas expansion machine achieves precise control of the mold closing pressure while exhibiting significant energy-saving and consumption-reducing effects.

[0020] The following describes the functions and collaborative relationships of the main equipment in this production line, following the typical workflow from raw materials to finished products.

[0021] Before starting the production line, the operator places a standard depalletized bin filled with blank tubes at the depalletizing station. AGVs can also automatically transfer fully loaded bins from the warehouse to the AGV loading station for docking. After startup, the central control system controls the loading robot to pick up blank tubes one by one from the depalletized bins, completing the automatic depalletizing and loading process.

[0022] The loading robot places the blank tube into the mold of the preforming press. The preforming press is a servo hydraulic press that performs preliminary forming of the tube blank according to a preset pressure-displacement curve. After forming, the ejection mechanism inside the mold automatically ejects the workpiece to a preset height, awaiting the next robot to grasp it. The loading robot is equipped with a dedicated end effector, which can flexibly grasp tube blanks of different specifications. The end effector integrates a force sensor to monitor the magnitude and trend of the clamping force in real time during the grasping process. When the force sensor detects an abnormal clamping force (such as insufficient clamping force leading to slippage, or excessive clamping force leading to workpiece deformation), the loading robot pauses its loading action and sends an abnormal signal to the central control system, which then issues an alarm.

[0023] The first transfer robot removes the pre-formed workpiece, transports it, and places it into the heating station of the dedicated heating machine. The dedicated heating machine is a medium-frequency induction heating device used to quickly and accurately heat the workpiece to the temperature range required for hot gas expansion molding. During the heating process, the machine's temperature monitoring system continuously monitors the workpiece temperature to ensure heating quality. After reaching the preset temperature and completing the heat preservation process, the workpiece is in a high-temperature state awaiting molding.

[0024] The second transfer robot then removes the high-temperature workpiece from the heating machine, quickly transfers it, and places it into the mold of the final forming press. The final forming press is a hot gas expansion machine, which introduces high-pressure gas into the tube blank after the mold closes to complete the final expansion forming.

[0025] After molding is completed, the final molding press opens the mold. The unloading robot takes the molded workpiece out of the press and, in conjunction with the vision system, stacks the workpieces one by one and layer by layer into the stacking bin, completing the automatic unloading and stacking.

[0026] Once the palletizing bins are full of finished products, the central control system can dispatch AGVs to the AGV unloading station to automatically transfer the full-load bins to the finished product storage area or shipping area, and simultaneously replenish empty bins to the palletizing station, completing the automatic closed loop of production line logistics.

[0027] Throughout the production process, the central control system serves as the control hub of the production line, responsible for the unified coordination, scheduling, status monitoring, and safety interlock management of all the aforementioned equipment. Operators only need to perform necessary monitoring and parameter settings through the human-machine interface of the central control cabinet, without having to enter the safety fence to participate in direct production operations, thus achieving fully unmanned intelligent production.

[0028] This application provides a control system for an intelligent production line for thermal expansion of metal tubular components. The production line includes a dedicated heating machine and a central control system.

[0029] The heating machine is used to heat workpieces and includes a vision system, an infrared temperature probe, a multi-axis servo slide supporting the infrared temperature probe, and a heating device. The vision system acquires real-time contour images of the workpiece; the infrared temperature probe, mounted on the multi-axis servo slide, can move within a certain spatial range for non-contact temperature measurement of the workpiece surface; the multi-axis servo slide, under the control of the central control system, drives the infrared temperature probe to achieve multi-degree-of-freedom position adjustment; and the heating device heats the workpiece.

[0030] In existing hot gas expansion production lines for metal tubular components, the heating process typically employs medium-frequency induction heating combined with infrared thermography for temperature monitoring. During actual production, the tubular blank undergoes morphological changes such as axial elongation, radial bending, or localized warping due to thermal expansion and the release of internal material stress. Since the infrared thermography probe is usually fixedly installed at a preset position in the heating station, its projection position is calibrated to a specific surface area of ​​the workpiece in its initial state during installation and commissioning. However, once the workpiece undergoes morphological changes during heating, the original temperature measurement area on the workpiece surface will spatially shift with the deformation, while the position and orientation of the infrared thermography probe remain unchanged. This causes the temperature measurement spot to deviate from the workpiece surface and instead project onto an ineffective area of ​​the workpiece, the heating electrode, or the background structure of the station. Consequently, the temperature data collected by the infrared thermography probe is no longer the true temperature of the workpiece surface, but rather the temperature of the background area or the edge of the workpiece, resulting in distorted or completely invalid temperature data.

[0031] If the temperature measurement fails, and the control system receives a false signal that is lower than the actual workpiece temperature, it will continue to output heating power, causing the workpiece to overheat or melt. If the control system receives a false signal that is higher than the actual workpiece temperature, it will reduce or cut off the heating power in advance, resulting in insufficient heating of the workpiece, which will not reach the temperature range required for the hot gas expansion molding process.

[0032] The root cause of the above problems is that the position of the infrared temperature probe in the existing solution is fixed, or can only be switched according to a few pre-set fixed positions, and does not have the ability to perform dynamic position compensation based on the nonlinear thermal deformation of the workpiece that occurs in real time during the heating process.

[0033] In view of this, this embodiment provides a dynamic tracking and closed-loop temperature control mechanism for temperature measurement points based on visual feedback, which aims to solve the technical problem of temperature measurement point offset caused by workpiece thermal deformation, which in turn leads to temperature measurement failure and heating runaway.

[0034] See Figure 2 The central control system is configured to execute steps 201 to 204 during the heating process of the workpiece by the heating machine: Step 201: Obtain the real-time contour image of the workpiece based on the vision system.

[0035] The purpose of this step is to continuously and in real-time acquire the workpiece's appearance and shape information during the heating process, providing the raw data foundation for subsequent thermal deformation identification. Specifically, the vision system can be installed at an appropriate position above or to the side of the heating station. After heating begins, it takes pictures of the workpiece at a certain frequency to acquire two-dimensional or three-dimensional images reflecting the current outline of the workpiece, and transmits the image data to the central control system for processing.

[0036] In one example implementation, the vision system captures images of the workpiece within the heating station at a predetermined sampling period (e.g., one frame every 500 milliseconds) to obtain grayscale or depth maps of the workpiece. The vision system then transmits each captured image frame to the image processing module of the central control system via GigE Vision or a USB interface.

[0037] This step, by introducing a vision system, enables online, non-contact, and quantitative perception of the overall shape of the workpiece, obtaining image data to determine whether the workpiece has undergone thermal deformation and the degree of deformation, providing information for subsequent dynamic adjustments.

[0038] Step 202: Identify the actual thermal deformation state of the workpiece caused by heating through image analysis.

[0039] The purpose of this step is to process and analyze the real-time contour image acquired in step 201, extracting the workpiece's thermal deformation information as the basis for decision-making regarding the movement of the temperature probe. Specifically, the central control system can compare the current workpiece contour acquired during the heating process with a pre-stored initial contour or reference position. By calculating parameters such as the displacement and direction of specific points or regions on the contour, the actual thermal deformation state of the workpiece can be determined, such as bending in a certain direction, axial expansion or contraction, or local warping.

[0040] In one example implementation, the central control system pre-stores an initial contour template of the workpiece before heating begins. During the heating process, the central control system registers and compares each frame of the real-time image with the initial contour template, calculating the offset between the pixel coordinates of preset feature points on the workpiece contour (e.g., the center point of the tube end, the outer edge contour point of the tube) in the current image and the pixel coordinates of those feature points in the initial template. This offset is converted using camera calibration parameters to obtain the actual displacement of the workpiece in physical space, which is used as the thermal deformation state data of the workpiece.

[0041] This step uses image analysis to enable the system to determine the current deformation state of the workpiece, thus providing quantitative control input for the next step of servo servo tracking.

[0042] Step 203: Based on the actual thermal deformation state, dynamically adjust the position of the infrared temperature probe using a multi-axis servo slide to ensure that the temperature measurement area of ​​the infrared temperature probe is always locked on the preset target area on the workpiece surface.

[0043] The purpose of this step is to compensate for the deformation displacement of the workpiece in real time through a mechanical actuator, based on the thermal deformation state identified in step 202, to ensure that the temperature measuring spot of the temperature probe always falls on the effective temperature measuring position. Specifically, the central control system calculates the direction and distance that the infrared temperature measuring probe needs to move based on parameters such as the direction and amplitude of the workpiece's thermal deformation, and sends corresponding control commands to the multi-axis servo slide. The multi-axis servo slide drives the infrared temperature measuring probe to translate or rotate along one or more axes according to the commands, so that its temperature measuring spot moves synchronously with the displacement of the preset target area, always "locked" on the effective temperature measuring position on the workpiece surface.

[0044] In one example implementation, the central control system converts the spatial displacement of the target area calculated in step 202 into motion control commands for each axis of the multi-axis servo slide. For example, when downward bending of the workpiece is detected, causing the preset target area to shift downward by δ millimeters, the central control system sends a position command to the vertical axis driver of the servo slide to descend by δ millimeters. The servo motor drives the slide to synchronously shift the infrared temperature probe downward by δ millimeters, so that the temperature measurement spot is re-aligned with the preset target area on the workpiece surface after the displacement. When the workpiece undergoes continuous, non-linear deformation during heating, the above-mentioned control loop of "calculating displacement - generating command - driving follow-up" is repeatedly executed at a frequency matching the sampling period of the vision system, so that the temperature measurement spot remains locked in the preset target area throughout the entire heating process of the workpiece.

[0045] This step adjusts the position of the temperature probe based on the actual thermal deformation state of the workpiece; furthermore, the adjustment method is continuous tracking, rather than discrete position switching. Through this approach, this step resolves the issue of temperature probe spot deviation caused by workpiece thermal deformation, ensuring that the infrared temperature probe consistently acquires temperature signals from the effective area of ​​the workpiece surface throughout the entire heating process, providing a reliable feedback signal source for subsequent closed-loop power adjustment.

[0046] Step 204: Based on the temperature data collected by the infrared temperature probe of the adjusted position on the preset target area, the output power of the heating device is adjusted in a closed loop.

[0047] The purpose of this step is to utilize the real and continuous temperature feedback signal obtained in step 203 to perform precise closed-loop control of the heating process. Specifically, the central control system receives real-time temperature data collected by the infrared temperature probe from the preset target area, compares it with the preset target temperature or target temperature curve, calculates the required heating power correction based on the comparison result, and dynamically adjusts the output power of the heating device accordingly to maintain the actual temperature of the workpiece within the set range.

[0048] In one example implementation, the central control system receives the temperature signal output from the infrared temperature probe in real time, compares it with a preset target temperature value or the expected value at the corresponding moment on a preset temperature-time curve, and calculates the temperature deviation. The central control system uses this temperature deviation as the input to the PID controller to calculate the required heating power correction, and sends the corrected power command to the intermediate frequency power controller of the heating device to adjust its output power. When the temperature deviation is positive (actual temperature is higher than the target temperature), the output power is reduced; when the temperature deviation is negative (actual temperature is lower than the target temperature), the output power is increased.

[0049] In this step, since the temperature feedback signal is based on the actual temperature data of the preset target area ensured in step 203, the temperature feedback signal always accurately reflects the actual surface temperature of the workpiece. The adjustment direction and control quantity of the PID controller are calculated based on the actual temperature deviation, thereby avoiding erroneous control decisions caused by erroneous feedback signals and ensuring that the workpiece heating temperature is always maintained within the range required by the process.

[0050] Through the configuration of the above control system, this embodiment utilizes a vision system to acquire the contour image of the workpiece in the heating state in real time, and quantitatively extracts the thermal deformation information of the workpiece through image analysis. Using this thermal deformation information as the input of servo control, the multi-axis servo slide carrying the infrared temperature probe is driven to follow up, compensating for the position deviation of the temperature measurement point caused by the workpiece deformation, so that the temperature measurement spot remains locked in the effective temperature measurement area of ​​the workpiece after the workpiece deforms. On this basis, the real temperature data collected in the locked area is used as the closed-loop feedback quantity to adjust the output power of the heating device, eliminating the position error of the temperature measurement link and fundamentally solving the heating runaway problem caused by temperature measurement failure.

[0051] In one specific embodiment, a further explanation is given for step 202, "identifying the actual thermal deformation state of the workpiece due to heating through image analysis".

[0052] In step 202, the central control system needs to identify the actual thermal deformation state of the workpiece due to heating from the real-time contour image of the workpiece acquired by the vision system. However, under heating conditions, the image quality of the workpiece surface may deteriorate due to factors such as oxidation, luminescence, and smoke, and the thermal deformation of the workpiece is usually small and gradual, with the initial displacement possibly only on the order of millimeters. If only a general image comparison method is used, the deformation recognition result may be insufficient due to image noise interference or inaccurate feature extraction, which in turn affects the accuracy of subsequent temperature probe position adjustment. In addition, even if a vision system is used to assist temperature measurement in the prior art, it is mostly a one-time position calibration before heating, and does not perform real-time, quantitative deformation recognition for the continuous deformation of the workpiece during the heating process.

[0053] Therefore, in step 202 of this embodiment, a real-time thermal deformation recognition method combining semantic segmentation and motion estimation is adopted to improve the accuracy and robustness of deformation recognition.

[0054] The specific implementation of this embodiment includes: (a) Locking of reference feature points before heating starts Before heating begins, the central control system acquires an initial image of the workpiece at room temperature via a vision system. A semantic segmentation algorithm is then applied to this initial image, separating the workpiece region from non-workpiece regions such as the background, fixtures, and electrodes at the pixel level. Within the segmented workpiece region, locations with significant geometric or textural features are extracted as reference feature points, such as corner points at the end of the tube blank or extreme curvature points of the outer edge contour. These reference feature points are stored as reference coordinates for a preset target region, serving as the basis for subsequent deformation calculations.

[0055] In one example implementation, the semantic segmentation algorithm can employ a deep learning-based U-Net or DeepLab network, pre-trained using labeled images of billets of different specifications. Reference feature points can be extracted using the Shi-Tomasi corner detection algorithm or the SIFT feature point detection algorithm, and the extraction results are stored in the memory of the overall control system in the form of pixel coordinates.

[0056] (ii) Real-time calculation of thermal deformation vector during the heating process During the heating process, the vision system continuously acquires real-time contour images of the workpiece at a preset sampling period. The central control system performs the following processing on each frame of the real-time image: First, the displacement of each reference feature point on the workpiece contour from its initial position to its current position is calculated using either the frame difference method or optical flow method. In one example implementation, the Lucas-Kanade sparse optical flow algorithm is employed. Centered on the reference feature point, the algorithm searches for the best-matching corresponding region in the real-time image and calculates the pixel-level displacement of each reference feature point. This displacement is then converted using the camera calibration matrix to obtain the three-dimensional displacement vector of the reference feature point in physical space.

[0057] Specifically, a reference feature point P can be extracted from the end of the tube blank. Its pixel coordinates in the initial image are (u0, v0), and its pixel coordinates in the current real-time image are (u1, v1). The difference between the two (Δu, Δv) is the pixel displacement of that point. Using the intrinsic and extrinsic parameter matrices obtained through camera calibration, this pixel displacement is converted into a displacement (ΔX, ΔY, ΔZ) in the physical space coordinate system. This displacement vector characterizes the direction and magnitude of the thermal deformation of the workpiece at that reference feature point.

[0058] (iii) Using thermal deformation vector to drive servo slide follow-up The central control system determines the new positions of each reference feature point in physical space based on the calculated thermal deformation vector. The displacement vector of the reference feature point corresponding to the preset target area (i.e., the area where the temperature measuring spot should be locked) is used as the control input and converted into motion commands for each axis of the multi-axis servo slide. The slide drives the infrared temperature measuring probe to follow the movement, so that the temperature measuring spot is locked at the position of the reference feature point after the displacement.

[0059] In this embodiment, a semantic segmentation algorithm is used to accurately separate the workpiece area from the complex background, ensuring that the extraction of reference feature points is not affected by non-workpiece areas such as the background and fixtures, thus improving the accuracy of feature extraction. During the heating process, the thermal deformation of the workpiece is continuously and quantitatively calculated in real time using frame difference or optical flow methods, rather than just calibrating once before heating. This allows for capturing the continuous deformation process of the workpiece throughout the entire heating process. The thermal deformation information is quantified and output in vector form, rather than just making a qualitative judgment of "whether deformation has occurred." This provides specific displacement control parameters for the subsequent precise follow-up of the servo slide, ensuring the continuity and authenticity of the temperature data and providing a reliable feedback signal guarantee for the final closed-loop adjustment of the heating power.

[0060] In one specific embodiment, a further explanation is given for step 204, "based on the temperature data collected by the infrared temperature probe after the position is adjusted from the preset target area, the output power of the heating device is adjusted in a closed loop."

[0061] In step 204, the central control system needs to perform closed-loop adjustment of the heating device's output power based on the temperature data collected by the infrared temperature probe. However, the medium-frequency induction heating process has significant nonlinear characteristics: the temperature rise rate of the workpiece depends not only on the current heating power but also on the combined influence of multiple factors such as the workpiece material, geometric dimensions, cumulative heating time, and environmental heat dissipation conditions. Furthermore, different batches of tube blanks exhibit variations within tolerance ranges in material composition and initial diameter. While these variations are not significant in single-piece processing, they can affect heating consistency in continuous mass production.

[0062] More importantly, when the output power of the medium frequency power supply is high and the workpiece temperature rises rapidly and approaches the preset target temperature threshold, due to the thermal inertia of the heating system, even if the control system immediately stops the power output when it detects that the temperature has reached the threshold, the workpiece will continue to heat up due to the heat it has already absorbed, resulting in a "temperature overshoot" phenomenon. Temperature overshoot is significantly harmful to the hot gas expansion molding process. Excessively high temperatures may cause coarsening of the workpiece grains, accelerated surface oxidation, or even localized melting, directly affecting product quality.

[0063] The root cause of the above problems is that, on the one hand, existing closed-loop temperature control systems usually only use temperature deviation as a single feedback quantity, without considering other interference factors affecting the temperature rise process. This results in the same temperature deviation potentially corresponding to different power correction requirements under different workpieces or different heating stages. On the other hand, when approaching the target temperature, there is a lack of predictive adjustment strategies for thermal inertia, and the conventional PID control method is still used, with the response lagging behind the temperature rise change.

[0064] Therefore, in step 204 of this embodiment, a two-stage adjustment mechanism combining a multivariable temperature control model and a slow-rise heating strategy is introduced to improve the accuracy and stability of heating temperature control.

[0065] The core of this embodiment lies in the composite control method employing a multivariable model feedforward regulation and a gradual increase strategy at the end. The multivariable temperature control model dynamically and predictively corrects the heating power throughout the heating process, taking into account various disturbances such as the workpiece material, initial diameter, and cumulative heating time, thus addressing the insufficient adaptability of single-variable feedback control in nonlinear systems. The gradual increase heating strategy forcibly reduces the rate of increase of heating power at specific stages approaching the target temperature threshold, suppressing temperature overshoot caused by thermal inertia and resolving the issue of lag in the final response of conventional PID control. These two methods are functionally independent but sequentially interconnected, working together to achieve precise temperature control throughout the entire heating process.

[0066] The specific implementation of this embodiment includes: (I) Generation of power control commands based on a multivariable temperature control model Throughout the heating process, the central control system generates power control commands for the heating device based on a pre-set multivariable temperature control model. The inputs of this multivariable temperature control model include multiple parameters that affect the workpiece temperature rise process, including at least: the real-time temperature collected by the infrared temperature probe from the preset target area, the material information of the workpiece, the initial diameter of the workpiece, and the cumulative heating time.

[0067] In one example implementation, the multivariable temperature control model can be constructed as follows: For tube blanks of different materials and specifications, a temperature rise characteristic database is established through process experiments or simulations. This database records the corresponding relationship between workpiece temperature and time under different initial diameters, different heating powers, and different ambient temperatures. In actual production, the central control system retrieves the corresponding temperature rise characteristic data based on the current workpiece material information and initial diameter size. Combining this with the current cumulative heating time and real-time temperature feedback, it calculates the power correction amount required to reach the preset target temperature. This correction amount is then superimposed with the preset base power to form the final control command, which is sent to the intermediate frequency power controller of the heating device.

[0068] In another example implementation, the multivariable temperature control model can adopt a system identification model based on a neural network. It takes parameters such as material code, initial diameter, cumulative heating time, and current temperature as inputs and the target power value as output. It is trained in advance using historical production data and outputs power control commands online based on real-time input parameters during actual operation.

[0069] (ii) Switching to a gradual heating strategy near the temperature threshold When the real-time temperature approaches the preset target temperature threshold, the central control system automatically switches to a gradual heating strategy. The "approaching the preset target temperature threshold" can be defined as the current temperature reaching a preset percentage (e.g., 90%) of the target temperature threshold or the difference between the current temperature and the target temperature being less than a preset temperature difference (e.g., within 50°C of the target temperature).

[0070] In one example implementation, the gradual heating strategy is implemented as follows: the central control system gradually reduces the output power of the heating device according to a predetermined decay curve. For example, at each preset temperature increase (e.g., 10°C), the output power is linearly reduced by a preset percentage (e.g., 5% of the rated power), so that the temperature rise curve of the workpiece tends to flatten as it approaches the target temperature, thus overcoming the influence of thermal inertia. Once the target temperature is reached, the system switches to a heat preservation power mode, supplementing only the minimum power required to dissipate heat loss.

[0071] In another example implementation, the gradual heating strategy can employ model predictive control: the central control system predicts the temperature value that will be reached within a preset time period if the power output is not changed, based on the current temperature rise rate and the system's thermal inertia parameters; if the predicted value exceeds the target temperature threshold, the output power is reduced in advance so that the final temperature converges to the target value, rather than passively responding after overshoot is detected.

[0072] In this embodiment, a multivariate temperature control model is introduced, incorporating multiple parameters such as workpiece material information, initial diameter, and cumulative heating time into the control input. This allows power adjustment to not only rely on real-time temperature feedback but also predict the impact of different workpiece characteristics on the temperature rise process, thereby maintaining heating consistency across different batches and specifications of workpieces. The multivariate temperature control model provides a multi-factor, predictive decision-making basis for power adjustment throughout the heating process, improving the temperature control system's adaptability to material differences and operating condition changes. Furthermore, when approaching the target temperature threshold, it automatically switches to a slow-rise heating strategy, proactively reducing the power rise rate to overcome system thermal inertia, rather than performing remedial adjustments after temperature overshoot. By providing a preventative mechanism to overcome thermal inertia at the heating end, it effectively prevents temperature overshoot. The synergistic effect of these two mechanisms not only ensures that the temperature rise process of different batches and specifications of workpieces is controllable and traceable during heating but also eliminates product quality fluctuations caused by inconsistent incoming materials at the source, improving product consistency and yield.

[0073] In one specific embodiment, a solution is proposed to address the technical defects of the hot air expansion machine in the production line.

[0074] In existing hot gas expansion production lines for metal tubular components, the hot gas expansion forming process involves placing a heated tubular blank into a mold and then introducing high-pressure gas into the blank to cause it to expand and adhere to the mold, thus completing the final forming. In this process, the establishment of the forming pressure is crucial to product quality: if the pressure builds up too slowly, the workpiece may not expand in time after the mold closes, resulting in insufficient adhesion; if there are leaks or blockages in the pipeline, the pressure may not reach the preset value or may fluctuate abnormally, affecting the consistency of the forming quality.

[0075] In existing technologies, monitoring molding air pressure generally employs a comparison between instantaneous values ​​and thresholds. The control system reads the current value from the air pressure sensor in real time, triggering an alarm when this value exceeds the set safety upper limit or falls below the safety lower limit. However, this method only responds after the air pressure has significantly deviated from the preset value, constituting a reactive alarm. For slowly developing micro-leaks or progressive pipeline blockages, the instantaneous air pressure value may remain within the threshold range for a considerable period, but the timing characteristics of the air pressure build-up process, such as the rate of increase, fluctuation frequency, or steady-state stability, may already show abnormalities. Relying on instantaneous value comparisons fails to capture these early characteristics, leading to a continued deterioration of the problem until it ultimately results in defective products or mold damage.

[0076] The root cause of the above problems is that the existing solutions only detect the instantaneous amplitude of air pressure, without analyzing the temporal characteristics of air pressure changes, and therefore lack the ability to use dynamic information during the air pressure establishment process for early warning.

[0077] In view of this, this embodiment is equipped with a detection device in the hot gas expansion machine, and the molding diagnosis operation based on time-series feature analysis is performed by the central control system, which aims to solve the technical problem that the existing technology cannot detect small slow leaks or pipeline blockage precursors in advance.

[0078] The core of this embodiment lies in proposing a well-defined diagnostic mechanism based on temporal feature extraction, achieving a leap from post-event alarms to pre-event warnings. Specific implementation methods include: The hot gas expansion machine includes a detection device installed in the hot gas expansion forming gas path to collect real-time time-series data on the gas pressure or flow rate inside the workpiece. In one example implementation, the detection device can be a high-frequency response pressure transmitter or mass flow meter with a sampling frequency of not less than 100Hz to accurately capture the rapid changes in gas pressure during the build-up process. The detection device transmits the collected time-series data to the central control system in real time via an analog interface or fieldbus.

[0079] Accordingly, the central control system performs the following steps: Step 301: The detection device is used to collect real-time time-series data of the gas pressure or flow rate inside the workpiece; The slope of the pressure rise characterizes the rate at which the air pressure climbs from its initial value to its target value. In one example implementation, during the pressure rise phase, the central control system performs linear fitting on the collected data every preset time window (e.g., 100 milliseconds) to calculate the slope of the pressure change over time within that window. When the slope of the pressure rise remains below a preset reference slope threshold, it indicates that the pressure build-up is slow, which may indicate partial blockage in the pipeline or insufficient air supply pressure.

[0080] Fluctuation frequency characterizes the high-frequency vibrations of gas pressure during rising or steady-state phases. In one example implementation, the central control system performs a Fast Fourier Transform on the acquired time-domain data to obtain its spectral distribution. When the fluctuation frequency or amplitude differs significantly from a preset reference spectrum, it indicates that there may be abnormal disturbances or leaks in the gas path causing pressure oscillations.

[0081] Steady-state retention characterizes the ability of air pressure to remain stable after reaching a target value. In one example implementation, after the air pressure enters a steady-state phase, the central control system calculates the standard deviation of the pressure data over a preset time period. When the standard deviation exceeds a preset steady-state deviation threshold, it indicates that the air pressure cannot be maintained stably, and there may be a minor leak.

[0082] Step 302: When a deviation is detected between the feature and the preset process curve feature, and the deviation exceeds a preset threshold, it is diagnosed as a risk of minor slow leakage or pipeline blockage.

[0083] The central control system compares the extracted features with the preset process curve features. The preset process curve features are ideal characteristic parameters of the pressure build-up process obtained through experiments under standard process conditions, including the reference rise slope range, reference spectrum characteristics, and allowable steady-state deviation threshold.

[0084] When the deviation between any of the above characteristics and the corresponding preset characteristics exceeds a preset threshold, the central control system diagnoses a risk of minor slow leakage or pipeline blockage. For example, when the rising slope is less than 80% of the preset slope and the fluctuation frequency exceeds the normal frequency range, a risk of pipeline blockage is diagnosed; when the standard deviation of the steady-state retention exceeds 1.5 times the preset threshold, a risk of minor slow leakage is diagnosed.

[0085] Step 303: Based on the diagnosis, when the risk occurs, trigger an early warning and execute a safety control strategy such as pressurization, suspension of heating, or shutdown.

[0086] Based on the diagnosis, when the risk occurs, the central control system triggers an early warning and executes safety control strategies in advance. These safety control strategies include: pressure replenishment (when insufficient pressure is diagnosed due to a minor leak, the air supply is increased to maintain molding pressure), heating suspension (when abnormal air pressure build-up is diagnosed, heating of the next workpiece is suspended until the problem is resolved), and shutdown (when a serious leak or blockage is diagnosed, molding is immediately stopped and gas is released to protect the mold from damage).

[0087] Furthermore, once the real-time temperature collected by the infrared temperature sensor reaches the preset target temperature, the central control system switches the heating device to heat preservation mode. In heat preservation mode, the output power of the heating device is reduced to the minimum compensation power required to maintain the workpiece temperature, only replenishing the heat lost by the workpiece to the environment, thus keeping the workpiece temperature stably maintained within the target temperature range for the set time. After the heat preservation period ends, the central control system sends a material handling command to the transfer robot, initiating the transfer of the workpiece to the hot air expansion machine.

[0088] The technical improvement in this embodiment is as follows: First, instead of analyzing the air pressure value at a single moment, we analyze the characteristics of air pressure / flow rate changes over time, including the slope reflecting the rate of increase, the frequency reflecting stability, and the steady state reflecting the pressure holding capacity. This expands the diagnostic criteria from the amplitude at a single moment to the dynamic characteristics of the entire process.

[0089] Second, the diagnostic results are not a simple binary judgment of "normal / exceeding limits", but rather identify the type and degree of risk (minor slow leaks or pipeline blockage), so that subsequent safety control strategies are targeted, and measures such as pressurization, suspension of heating or shutdown are matched with the diagnostic results.

[0090] Third, the diagnosis is made earlier, triggering an alarm when the air pressure deviation is still in the "signs" stage, rather than after a significant leak or complete blockage has occurred. This buys time for remedial measures and significantly reduces the defect rate and the risk of mold damage.

[0091] In this embodiment, the central control system can accurately detect early signs of minor slow leaks or pipeline blockages based on the temporal characteristics of air pressure / flow rate. It triggers warnings and executes targeted safety control strategies before the problem worsens, enabling the hot air expansion molding process to have self-diagnostic capabilities. This not only reduces the defect rate and mold damage risk caused by air path abnormalities but also provides complete temporal data records for the molding process, supporting post-process quality traceability and optimization.

[0092] In one specific embodiment, further description of the material transfer system is provided.

[0093] In existing hot gas expansion production lines for metal tubular components, the transfer of raw material tube blanks from the warehouse to the loading station on the production line usually relies on manual forklift handling or general AGVs for material box transfer. After the material box arrives at the loading station, a destacking robot picks up the blank tubes one by one from the material box for loading.

[0094] However, the following problems exist in practice: the docking accuracy of general-purpose AGVs is typically at the centimeter level (e.g., ±10mm to ±30mm), while depalletizing robots require higher repeatability (usually within ±1mm) when grasping the billets in the bins. Due to random errors in the AGV's docking position, the actual position of the bin varies each time it is placed at the loading station, requiring the depalletizing robot to recalibrate its vision positioning or perform teaching adjustments each time to accurately grasp the workpieces in the bin. This additional positioning calibration step increases the cycle time of the loading process and reduces the continuous operating efficiency of the production line. Furthermore, if the workpieces in the bin are slightly displaced due to transportation bumps, the depalletizing robot may fail to grasp the workpiece or collide with it.

[0095] The root cause of the above problems is that in the existing solution, the AGV's carrying platform and the material box have only a simple planar carrying relationship. There is a lack of mechanical cooperation structure between the two that can guarantee the accuracy of repeated positioning, which results in cumulative errors in the position of the material box relative to the AGV and the loading station.

[0096] Therefore, in this embodiment, a precise mechanical positioning and matching structure is designed between the AGV's carrying platform and the standardized material box in the AGV material transfer system. This aims to eliminate the cumulative positioning error during the material transfer process and provide a stable and reliable material reference for the depalletizing robot's grasping.

[0097] The core of this embodiment lies in proposing a precise positioning scheme for AGV tote boxes based on pin-and-hole mating. The technical principle of this scheme is as follows: a matrix-arranged array of positioning pins is set on the AGV's carrying platform, and matrix-arranged positioning holes corresponding one-to-one with the positioning pins are opened on the bottom of standardized tote boxes. When the tote box is placed on the AGV carrying platform, the positioning pins engage with the positioning holes to achieve precise mechanical positioning of the tote box relative to the AGV, eliminating random errors caused by manual operation or AGV docking accuracy. Simultaneously, the AGV scheduling management system is interconnected with the central control system, ensuring that the tote box transfer timing matches the production line's rhythm. Therefore, this scheme, through a single mechanical mating structure, guarantees the precise position of the tote box during material transfer, providing a stable grasping reference for the subsequent depalletizing robot without the need for secondary positioning.

[0098] The specific implementation of this embodiment includes: (a) Positioning pin array on the AGV carrying platform The AGV material handling system includes at least one autonomous laser-guided AGV. The AGV's carrying platform is a horizontally positioned structure, on which multiple positioning pins are fixedly mounted in a matrix arrangement. In one example implementation, the positioning pins may be made of hardened alloy steel, with chamfered or tapered guide surfaces at the top to guide and center the positioning holes when the material box is placed. The distribution spacing and position of the positioning pins can be standardized according to the specifications of the material box, for example, arranged symmetrically at the four corners or evenly distributed along the edge of the carrying platform, to ensure that the material box is positioned and constrained in all directions after placement.

[0099] (ii) Matrix positioning holes at the bottom of the standardized material bin The standardized material bin is a standard container for holding blank tubes, and its bottom has a matrix of positioning holes corresponding one-to-one with the positioning pin array. In one example implementation, wear-resistant bushings can be embedded in the positioning holes to reduce the impact of wear on positioning accuracy during long-term use. The diameter of the positioning hole and the outer diameter of the positioning pin are in clearance fit or transition fit, and the fit clearance can be selected according to the required positioning accuracy, for example, using an H7 / g6 grade fit to ensure millimeter-level positioning accuracy.

[0100] (iii) Precise positioning is achieved through the use of pins and holes. When the tote box is transported to the depalletizing and loading station by the AGV, or placed on the AGV's carrying platform by a forklift / crane, the tote box automatically falls into position under gravity through the engagement of the positioning pin array with the pins of the matrix positioning holes. The guiding surface of the positioning pins guides the tote box to the accurate predetermined position. This achieves precise positioning of the tote box relative to the AGV's carrying platform. The positioning accuracy depends on the engagement accuracy of the pins rather than the stopping accuracy of the AGV, thus eliminating cumulative errors caused by transportation and transfer, and ensuring that the workpiece coordinates within the tote box remain consistent each time the depalletizing robot grasps it.

[0101] (iv) Collaboration between the AGV scheduling and management system and the central control system The AGV material transfer system also includes an AGV scheduling and management system, AGV docking stations, and an automatic bin identification and status tracking system. The AGV scheduling and management system is interconnected with the central control system via industrial Ethernet or other fieldbuses. During production line operation, when the central control system detects that the bins in the depalletizing and loading unit are empty, or the bins in the unloading and palletizing unit are full, it sends a scheduling command to the AGV scheduling and management system. The AGV scheduling and management system dispatches an idle AGV to automatically travel to the corresponding AGV docking station. The automatic bin identification and status tracking system (e.g., an RFID reader or barcode scanner installed at the docking station) verifies the bin number and material information. After confirmation, the positioning mechanism is unlocked, and the AGV accurately docks and carries the corresponding bin, transferring it along a preset path to the designated area, thus achieving an automatic closed-loop material transfer.

[0102] The improvement in this embodiment is as follows: First, a precision mechanical mating structure consisting of a positioning pin array and a matrix of positioning holes is added between the AGV carrying platform and the hopper, which improves the positioning accuracy of the hopper relative to the AGV from relying on the AGV navigation accuracy (usually at the centimeter level) to relying on the machining accuracy (at the millimeter level), thus eliminating the cumulative error of transfer.

[0103] Secondly, this precision positioning structure is mechanically passive, which can achieve positioning without electrical control or sensor feedback. It has a simple structure, high reliability, and does not increase the control complexity of the production line.

[0104] Third, the AGV scheduling and management system is deeply interconnected with the central control system, so that the triggering time of the material box transfer is linked with the actual production consumption of the production line, avoiding the inefficient mode of traditional solutions that require manual judgment of the replenishment time or blind transfer of AGVs according to fixed cycles.

[0105] Through the aforementioned improvements, this embodiment of the AGV material handling system ensures precise positioning of the material bins during the material handling process via the mechanical cooperation of the positioning pin array and matrix positioning holes. This provides a stable and consistent material receiving benchmark for the depalletizing robot, eliminating the need for secondary positioning calibration before each loading and shortening the cycle time of the loading process. Simultaneously, the data interconnection between the AGV scheduling and the central control system enables automatic linkage between material replenishment and production line consumption, ensuring the stability of the logistics supply for continuous production line operation.

[0106] In one specific embodiment, further description of the preforming hydraulic press is given.

[0107] In existing hot gas expansion production lines for metal tubular components, the preforming process involves placing the blank tube into the mold of a preforming hydraulic press for initial pressing and shaping, providing the shape basis for subsequent heating and hot gas expansion. After forming, the workpiece is embedded in the mold cavity and needs to be removed from the mold before it can be transferred to the next process.

[0108] In existing technologies, workpieces are typically removed from the mold in the following ways: manually prying or removing the workpiece from the mold using tools, or having a robot directly clamp the workpiece from the mold. Manual removal is inefficient, labor-intensive, and poses safety hazards due to human hands entering the press area. While direct robotic clamping reduces human intervention, the robot's end effector needs to extend into the mold cavity, requiring high precision in the movement path and timing of the clamping action. Furthermore, the removal process is affected by the mold's opening and closing state and the uncertain position of the workpiece within the mold cavity.

[0109] Furthermore, whether the workpiece is manually picked up or directly gripped by a robot, at the moment it leaves the mold, due to the thrust of the hydraulic press ejector rod and the inertia of the workpiece, the workpiece may bounce, slip, or collide with the mold, causing scratches or deformation on the workpiece surface. The root cause of these problems is that the end of the ejection action in the existing solution lacks buffer protection, and the ejection action and the gripping action are sequential and waiting, without timing coordination design, resulting in a long process interval.

[0110] In view of this, this embodiment adds a pneumatic ejection device with an end-buffer mechanism to the automated mold system of the preforming hydraulic press, and connects the control system of the preforming hydraulic press to the main control system to achieve the timing coordination of the ejection action and the grasping action of the transfer robot, aiming to solve the problems of damage risk and excessive process interval time during the workpiece demolding process.

[0111] The core of this embodiment lies in proposing an automatic workpiece ejection scheme based on buffer protection and timing coordination. The technical principle of this scheme is as follows: after molding is completed, a pneumatic ejection device smoothly lifts the workpiece from the mold cavity to a preset gripping height; a buffer mechanism is set at the end of the ejection stroke to absorb the inertial kinetic energy of the workpiece and prevent the workpiece from bouncing or colliding with the mold due to sudden stopping; at the same time, the control system of the preforming hydraulic press communicates in real time with the main control system, so that the timing of the ejection action is coordinated with the gripping action of the transfer robot. When the workpiece is ejected into place or slightly ahead of time, the transfer robot starts the gripping action, reducing the idle waiting time between the two.

[0112] The specific implementation of this embodiment includes: (a) Pneumatic ejection device The automated mold system includes a pneumatic ejection device. In one example implementation, the pneumatic ejection device consists of a cylinder, a push rod, and an ejection plate. The cylinder is mounted below or to the side of the mold, and its piston rod is connected to the push rod, which passes through the mold base plate and extends to the bottom of the cavity. After pressing and molding, the mold opens, and the central control system sends a control signal to the pneumatic ejection device. Air enters the cylinder, pushing the push rod upward, which in turn drives the ejection plate to eject the workpiece upward from the cavity, causing the workpiece to detach from the mold cavity and rise to a preset gripping height. This preset gripping height can be set according to the effective working range of the end effector of the transfer robot to ensure that the workpiece is lifted to a spatial position where the robot can easily and accurately grip it.

[0113] (ii) Buffer mechanism The pneumatic ejector is equipped with a buffer mechanism at the end of its ejection stroke. In one example implementation, the buffer mechanism can be a hydraulic damper or an elastic buffer pad, installed at the end of the cylinder's stroke or on the contact surface between the ejector plate and the workpiece. When the ejector lifts the workpiece to near the end of its stroke, the buffer mechanism applies a gradually increasing damping force to the ejection motion, causing the ejection speed to decrease smoothly, and the workpiece to stop slowly as it approaches the gripping height. Therefore, the workpiece will not detach from the ejector plate due to inertia or bounce due to the sudden stop of the ejection motion, avoiding uncontrolled falling or secondary collisions with the mold that could cause damage.

[0114] In another example implementation, the buffer mechanism can also be implemented through pneumatic control. That is, when the cylinder is close to the end of its stroke, the exhaust speed of the cylinder is reduced by a throttle valve or an exhaust buffer valve, so that the piston's movement speed naturally decreases, thereby achieving a buffering effect.

[0115] (iii) Timing coordination between the ejection action and the robot's grasping action The control system of the preforming hydraulic press communicates with the main control system via industrial Ethernet or fieldbus. When the preforming process is nearing completion, the main control system, based on the mold opening status and feedback signals from the preforming hydraulic press control system, sends a pre-grabbing command to the transfer robot, causing the transfer robot to move in advance to the vicinity of the preforming hydraulic press's discharge position. When the pneumatic ejector begins ejecting the workpiece, the preforming hydraulic press control system feeds back the ejection progress to the main control system in real time. Based on the moment the ejection reaches the preset height, the main control system sends a grabbing start command to the transfer robot, causing the robot's grippers to close and grab the workpiece simultaneously with or slightly ahead of the ejection position. This optimizes the traditional sequential sequence of "ejection complete → waiting → robot start" into a parallel and collaborative sequence of "ejection process → robot pre-positioning → grabbing upon ejection position," reducing idle waiting time between processes.

[0116] The improvement in this embodiment is as follows: First, a buffer mechanism is set at the end of the ejection stroke of the pneumatic ejection device. Whether a hydraulic buffer or a pneumatic buffer is used, it can effectively absorb the inertial impact at the end of the ejection, so that the workpiece stops smoothly at the preset gripping height, preventing workpiece damage caused by bouncing or collision, and ensuring the surface quality and dimensional accuracy of the workpiece during the demolding process.

[0117] Secondly, by communicating in real time between the preforming hydraulic press control system and the main control system, the timing of the ejection action and the grasping action of the transfer robot are designed in a coordinated manner. Ejection and grasping are no longer executed independently, but form an organically linked action sequence. The transfer robot can be pre-positioned and started in time, reducing the idle waiting time between processes.

[0118] Third, the servo pump unit directly adjusts the output flow and pressure of the hydraulic pump by controlling the speed of the servo motor, reducing the throttling losses of the hydraulic valve and offering advantages such as fast response speed, high control precision, and energy saving. Through this pressure-displacement closed-loop control, the preforming hydraulic press can achieve precise matching of pressure, speed, and position during the pressing process, ensuring the dimensional consistency and forming quality of the preformed workpiece.

[0119] Through the above improvements, the automated mold system of the preforming hydraulic press achieves automatic demolding of the workpiece through a pneumatic ejection device, protects the workpiece from damage through a buffer mechanism, and achieves timing coordination of ejection and gripping through communication with the central control system. This completely eliminates manual intervention in the preforming demolding process, reduces the risk of damage to the workpiece during demolding, and effectively reduces the interval time between the preforming process and the transfer and handling process, thereby improving the overall cycle stability of the production line.

[0120] In one specific embodiment, further description of the unloading and stacking unit is provided.

[0121] In existing hot air expansion production lines for metal tubular components, after hot air expansion molding is completed, the workpiece is removed from the final forming press by a cutting robot and stacked into a material box. This cutting and stacking process faces the following challenges: First, the workpiece, after being hot-expanded and just removed from the mold, is at a high temperature (usually above several hundred degrees Celsius). If the unloading robot directly removes the workpiece from the press and performs high-precision stacking, the workpiece is still in a high-temperature state and its dimensions are not yet fully stable. Furthermore, the prolonged contact time between the robot's grippers and the high-temperature workpiece may affect the gripper's lifespan. At the same time, the workpiece needs to be removed as soon as possible after the press opens the mold to shorten the press's occupancy time and ensure the production line's cycle time.

[0122] Secondly, in traditional solutions, unloading robots are usually equipped with only a single-function gripping mechanism. If the same gripper is used to both quickly pick up parts from the press and perform high-precision palletizing tasks, it is difficult to meet the dual requirements of speed and accuracy: picking up parts requires the gripper to move quickly and have a large clamping force; palletizing requires the gripper to have high positioning accuracy and minimal damage to the workpiece surface.

[0123] Third, traditional manual palletizing or simple stacking methods have low palletizing accuracy and poor stacking neatness, requiring secondary manual sorting, which affects the overall efficiency of the production line and the appearance quality of the finished product.

[0124] The root cause of the above problems is that the gripping mechanism of the unloading robot in the existing solution has a single function and lacks a buffer between unloading and palletizing. This forces the robot to simultaneously perform the two contradictory tasks of fast picking and precise placement under high temperature and high-speed working conditions.

[0125] In view of this, this embodiment is equipped with a material unloading robot with dual grippers and a dedicated palletizing end effector in the material unloading and palletizing unit, and a workpiece buffer rack with a precision positioning and clamping mechanism is set between the press and the palletizing station. The aim is to solve the contradiction between fast retrieval of high-temperature workpieces and high-precision palletizing through a composite operation sequence of "fast retrieval - buffering - gripper changing - precision placement", thereby improving the efficiency and accuracy of material unloading and palletizing.

[0126] The core of this embodiment lies in proposing a material unloading and palletizing scheme based on temporary storage in a buffer rack and automatic end-effector switching. The technical principle of this scheme is to decompose the material unloading and palletizing process into two independent stages: "rapid part retrieval" and "precise palletizing," connected by a workpiece buffer rack with precision positioning and clamping mechanisms. In the first stage, the unloading robot uses dual grippers to quickly retrieve workpieces from the press in one go and temporarily place them on the buffer rack, releasing press resources in the shortest possible time. In the second stage, the unloading robot automatically switches to a dedicated palletizing end effector, picking up workpieces one by one from the buffer rack that have undergone preliminary cooling and shaping under precision positioning, and performing high-precision palletizing under the guidance of a vision system. Thus, this scheme, through process decomposition and tool switching, allows rapid part retrieval and precise palletizing to each be completed by the most suitable gripping mechanism, eliminating the performance compromise between high cycle time and high precision for a single gripper.

[0127] The specific implementation of this embodiment includes: (a) Dual-claw rapid component removal The unloading robot is equipped with a gripping mechanism. In one example implementation, the gripping mechanism is a dual-jaw gripping mechanism, which can employ two symmetrically arranged pneumatic or electric grippers. The gripping surfaces of the grippers can be adapted to the shape of the workpiece (e.g., V-grooves, arc-shaped gripping surfaces) to ensure stable gripping of high-temperature workpieces. After the final forming press opens the mold, the unloading robot uses the dual-jaw gripping mechanism to enter the press, simultaneously or sequentially gripping two formed workpieces and quickly removing them from the press area to release press resources in the shortest possible time and shorten the time occupied by the press in a single cycle.

[0128] (ii) Cache rack temporary storage and precise positioning The workpiece buffer rack is equipped with a precision positioning mechanism and a clamping mechanism. In one example implementation, the precision positioning mechanism can be a V-shaped positioning block or a contoured positioning groove, the contour of which is adapted to the cross-sectional shape of the workpiece being unloaded. When the workpiece is placed, it automatically slides into the positioning position, achieving precise positioning of the workpiece on the buffer rack. The clamping mechanism can be a pneumatic or spring-return clamping arm, used to fix the workpiece in the positioning position after it is placed, preventing the workpiece from shifting or tilting during cooling and shrinkage, and providing a definite positional reference for the subsequent precise gripping by the palletizing end effector.

[0129] After the unloading robot removes the workpiece from the press, it places it on the workpiece buffer rack. The workpiece undergoes initial cooling on the buffer rack, which reduces its temperature and stabilizes its dimensions. At the same time, the spatial orientation of the workpiece is accurately defined and fixed by the precision positioning mechanism and the clamping mechanism.

[0130] The workpiece buffer rack is positioned between the final forming press and the palletizing station, serving as a buffer link between "high-temperature rapid unloading" and "precision palletizing." After the unloading robot temporarily places the formed, high-temperature workpiece on the buffer rack during the dual-gripper part-picking stage, it can return to the press area to await the part-picking task of the next forming cycle, without waiting for the palletizing operation to complete. After the workpiece undergoes preliminary cooling and positioning on the buffer rack, the unloading robot switches to a dedicated palletizing end effector to sequentially pick up the precisely positioned and clamped workpieces from the buffer rack and perform the precision palletizing operation. Thus, the unloading and palletizing unit separates part-picking and palletizing into two sub-processes that can be executed in parallel, reducing the sequential dependency between them.

[0131] (iii) Automatically replace the dedicated palletizing end effector and perform visually guided palletizing. After placing the workpiece on the buffer rack, the unloading robot automatically proceeds to the gripping mechanism storage platform. The central control system controls the quick-change tray to automatically unload the dual-gripper gripping mechanism and load the palletizing end effector. In one example implementation, the palletizing end effector can be a single-gripper or suction cup type end effector with a flexible contact surface (such as a high-temperature resistant rubber pad) to reduce damage to the workpiece surface.

[0132] After the replacement is completed, the unloading robot picks up the workpieces, which are now in a precisely positioned state, from the workpiece buffer rack. Guided by the vision positioning system, the workpieces are precisely stacked one by one, layer by layer, into the material box according to a preset stacking pattern. In one example implementation, the vision system can be an industrial camera mounted above the palletizing station or a vision sensor integrated into the robot's end effector, scanning the current spatial state of the material box and the actual position and orientation information of the workpieces, and calculating and adjusting the palletizing path in real time.

[0133] The improvement in this embodiment is as follows: First, by employing a division of labor between rapid part retrieval with dual grippers and precise palletizing with a dedicated palletizing end effector, part retrieval and palletizing are each performed by the most suitable gripping tool, resolving the contradiction between speed and accuracy that a single gripper cannot simultaneously achieve. The dual grippers enable the simultaneous and rapid retrieval of multiple parts, minimizing press downtime; the dedicated palletizing end effector is optimally designed for palletizing tasks, improving palletizing accuracy and protecting the workpiece surface.

[0134] Secondly, by setting up a workpiece buffer rack with precision positioning and clamping mechanisms between the press and the palletizing station, a "physical and temporal buffer" is provided for high-temperature workpieces. The workpieces undergo preliminary cooling and shaping on the buffer rack, and are precisely positioned and fixed, providing a definite positional reference for the subsequent precise gripping by the palletizing end effector, thus avoiding the problem of accumulated palletizing position deviations caused by the thermal deformation of the workpieces.

[0135] Third, by automatically changing the gripping mechanism through the robot, the switching between tools with different functions can be completed automatically without human intervention, saving the cost of manual replacement or additional workstation configuration.

[0136] This embodiment, through the aforementioned improvements, effectively resolves the contradiction between rapid retrieval of high-temperature workpieces and high-precision palletizing by using a dual-gripper unit to quickly remove parts and release press resources, a workpiece buffer rack to temporarily store parts for precise positioning and initial cooling, and a vision-guided sequence of operations for precise palletizing after automatic replacement of the dedicated palletizing end effector. This solution significantly improves palletizing accuracy and stacking neatness, eliminates the need for manual secondary sorting, and greatly enhances palletizing efficiency. Simultaneously, it shortens the press's single-cycle occupancy time, positively contributing to the overall production line cycle time.

[0137] Optionally, the unloading robot is also configured to perform visual verification and automatic sorting operations of the stacking status as an optional enhancement to the above unloading and palletizing process.

[0138] During the aforementioned material unloading and palletizing process, the unloading robot, guided by the vision positioning system, places the workpieces one by one and layer by layer into the material box according to the preset stacking pattern. However, in the actual stacking process, the following abnormalities may still occur: after stacking, the actual stacking position of the workpiece may deviate from the preset position due to its own weight or slight slippage of the contact surface; or slight positional deviations of the previous layer of workpieces may accumulate layer by layer, causing the upper layer of workpieces to become unstable, tilt, or even slip. If the above abnormal stacking is not detected and corrected in time, subsequent stacking will continue, which may result in the entire stack of workpieces being misaligned, causing workpiece collisions, compression deformation, or overturning during subsequent AGV transfer, affecting the appearance quality of the finished product and the delivery qualification rate.

[0139] Therefore, this embodiment further configures visual verification and automatic sorting functions in the material unloading and palletizing unit, aiming to realize online real-time detection and immediate correction of palletizing quality.

[0140] Specifically, a closed-loop control mechanism for palletizing quality, namely "layer-by-layer verification and immediate reorganization," is proposed. The technical principle of this mechanism is as follows: after each layer of workpieces is stacked, a visual positioning system is used to perform real-time image acquisition and comparative analysis of the current layer's stacking status. When a deviation exceeding the allowable range is detected between the actual stacking position and the preset position, without waiting for manual intervention, the unloading robot immediately reorganizes the layer, correcting the posture and position of the abnormal workpieces to ensure that the stacking quality of the current layer meets the preset standards before moving to the next layer.

[0141] Specific implementation methods include: (a) Visual verification after each layer is stacked In one example implementation, after the unloading robot has completed stacking all workpieces in the current layer within the material bin, it pauses the stacking operation and issues a verification command. The vision positioning system captures an image of the current layer, obtaining a top-view or side-view image reflecting the actual position and orientation of all workpieces in that layer. The central control system registers and compares the acquired image with a preset standard stacking template, calculating the deviation and direction between the actual placement position and the preset position of each workpiece.

[0142] In another example implementation, visual verification can be performed item by item. That is, after each workpiece is placed, the vision system performs a quick verification of the placement status of that workpiece to detect anomalies earlier.

[0143] (II) Detection and Judgment of Abnormal Stacking The central control system presets allowable stacking deviation thresholds (e.g., positional deviation not exceeding ±2mm, angular deviation not exceeding ±3°). When the deviation of any detected workpiece exceeds the above threshold, or when there is an obvious abnormality in the gap between adjacent workpieces (e.g., too small a gap may cause interference, or too large a gap may affect space utilization), the central control system determines that there is abnormal stacking in the current layer.

[0144] (iii) Automatically trigger the reorganization operation When an abnormal stacking is detected, the central control system issues a reordering command to the unloading robot. Based on the deviation information of each workpiece obtained from visual verification, the unloading robot picks up and re-stacks the workpieces with out-of-tolerance positions one by one. The reordering can be done by adjusting only individual abnormal workpieces, or by rearranging all workpieces in the current layer, prioritizing the overall stacking quality of the current layer. After reordering, the vision system verifies the layer again. Only after confirming it is acceptable can the unloading robot continue stacking the next layer of workpieces.

[0145] The improvement of this embodiment is as follows: First, the timing of quality inspection is moved from "post-event sampling" to "instant review of each layer," so that abnormalities can be detected early in the stacking process, avoiding the accumulation and spread of abnormal states between layers.

[0146] Secondly, the review and sorting are performed automatically by robots without human intervention, which is consistent with the concept of fully unmanned operation of the production line.

[0147] Third, the verification results can be used as part of the quality data and linked to the batch traceability system to provide a basis for subsequent process optimization and quality analysis.

[0148] Through the aforementioned improvements, this embodiment further enables real-time closed-loop monitoring of the stacking quality of each layer, building upon the foundation of visually guided precision stacking. When abnormal stacking occurs, the system can promptly identify and automatically correct it before moving to the next layer, ensuring the stacking quality and stability of the entire stack of workpieces. This avoids the additional time spent on post-stack dismantling and reorganization, thus guaranteeing the pass rate of finished products leaving the warehouse.

[0149] In one specific embodiment, the production line also includes industrial robots that correspond one-to-one with the equipment in the production line; the central control system is also configured to perform collaborative scheduling operations, and further explanation of this collaborative scheduling function is given.

[0150] In existing hot air expansion production lines for metal tubular components, each automated piece of equipment (such as loading robots, transfer robots, unloading robots, preforming hydraulic presses, heating machines, and hot air expansion machines) is typically managed by its own independent controller. The coordination between these devices relies on simple I / O signals or preset fixed timing triggers. The drawback of this approach is that the operating rhythm of each device is fixed during the design phase, and during operation, it can only be triggered serially according to a preset sequence.

[0151] In actual production, due to factors such as differences in workpiece specifications, fluctuations in heating time, and time variations caused by robot transport path adjustments for obstacle avoidance or grasping, the actual time consumed by each machine in a single operation is not constant. When the operation time of an upstream machine fluctuates slightly, the downstream machine still starts at the preset fixed time, resulting in two unfavorable situations: if the upstream is delayed, the downstream machine is idle and waiting, wasting production line capacity; if the upstream finishes ahead of schedule, workpieces accumulate at the process connection point, resulting in wasted cycle time. In addition, the transport paths between robots may have overlapping or interference areas. Without unified scheduling, multiple robots may compete for the same space area simultaneously, requiring additional waiting or avoidance logic to resolve, further increasing the non-value-adding time of the production line.

[0152] The root cause of the above problems is that the action sequence of each device in the existing solution is a pre-fixed, open-loop control mode that executes independently. There is a lack of a central scheduling mechanism that can acquire the status of each device in real time, dynamically calculate the global optimal action sequence, and coordinate the execution sequence of each device.

[0153] Therefore, this embodiment configures industrial robots that correspond one-to-one with each piece of equipment in the production line, and the overall control system performs collaborative scheduling operations. The aim is to eliminate redundant waiting time caused by poor equipment coordination through global dynamic optimization, thereby maximizing the overall cycle time of the production line.

[0154] The core of this embodiment lies in proposing a global dynamic collaborative scheduling mechanism based on the real-time status of multiple devices. The technical principle of this mechanism is as follows: the central control system, acting as the central scheduling unit of the production line, collects real-time information on the current operating status and pending production tasks of each device (including industrial robots, preforming hydraulic presses, heating machines, hot air expansion machines, and material unloading and palletizing units); using the single-step time of each discrete process and the transfer path of each industrial robot as constraints, a global scheduling model encompassing the action sequence of all devices is constructed; an optimization algorithm dynamically calculates the action sequence and timing that minimizes the overall process interval time, and the scheduling results are sent to each device in real-time as control commands. Thus, the action sequence of each device is no longer independent and fixed, but is uniformly coordinated and continuously optimized by the central control system based on the dynamic changes in the global status.

[0155] Specific implementation methods include: (a) Configuration of industrial robots The production line also includes industrial robots that correspond one-to-one with the equipment in the production line. In one example implementation, the production line is configured with a loading robot, a first transfer robot, a second transfer robot, and an unloading robot in sequence according to the process flow direction. Each robot serves the depalletizing and loading unit, the transfer from the preforming hydraulic press to the heating machine, the transfer from the heating machine to the hot air expansion machine, and the transfer from the hot air expansion machine to the unloading and palletizing unit, respectively. The controller of each industrial robot is connected to the central control system via an industrial Ethernet or fieldbus, reporting its current operating status (such as position, speed, stage of execution, remaining execution time, etc.) to the central control system in real time, and receiving action commands issued by the central control system.

[0156] (ii) Real-time status data acquisition of equipment The central control system continuously collects real-time status information of each device through the production line communication network at a preset polling cycle, including at least: the current position, current task stage, and estimated remaining execution time of each industrial robot; the mold closing / opening status, pressure holding stage, and estimated completion time of the preforming hydraulic press; the heating stage (heating / heat holding / completion) and current temperature of the heating machine; the mold closing / expansion / pressure holding / opening status and estimated completion time of the hot air expansion machine; and the stacking progress and remaining space in the material bin of the unloading and palletizing unit.

[0157] (III) Determination of the time consumption of each discrete process step In one example implementation, the single-step time of each discrete process can be obtained as follows: During the production line debugging phase, trial production runs are conducted for each product model. The average time and fluctuation range of each piece of equipment in each process stage are measured and recorded, forming a process time database which is stored in the central control system. During formal production, the central control system retrieves the corresponding process time data from the database based on the currently processed product model as the benchmark parameter for scheduling calculations. The central control system can also periodically update the reference values ​​in the database based on the process time statistics collected during actual operation to adapt to time changes caused by equipment aging or process parameter adjustments.

[0158] (iv) Establishment of robot transport path constraints The central control system pre-stores the workspace model and geometric information of the transfer paths for each industrial robot. In one example implementation, the standard transfer path for each robot is defined by a starting point (material pick-up position), an ending point (material unloading position), and a set of intermediate path points. Based on the current task allocation for each robot, the central control system determines the transfer path that each robot will execute and calculates the spatial occupancy time and interval for each path. When the transfer paths of multiple robots intersect or overlap spatially, the central control system uses this spatial interference relationship as a constraint for scheduling calculations, ensuring that no two robots simultaneously occupy the same interference area within the same time period.

[0159] (v) Dynamic scheduling calculation and action sequence optimization In one example implementation, the overall control system aims to minimize the total time (makespan) of a complete production cycle on the production line. It constructs a scheduling optimization problem with constraints such as the sequence of operations performed by each device, single-step time constraints, robot transfer time constraints, and spatial interference constraints. The system then uses algorithms such as genetic algorithms, particle swarm optimization algorithms, or simulated annealing algorithms to solve the problem, dynamically calculating the start time and execution order of each device's actions that minimize the overall waiting time.

[0160] In another example implementation, when the production line is small and the number of devices is limited, the central control system can adopt a rule-based scheduling strategy, such as the "earliest start time priority" principle: when a device completes the current process, the central control system immediately checks the current status of its downstream devices. If the downstream devices are idle and the transfer path is uninterrupted, it immediately issues a start command to the subsequent devices; if the downstream devices are still processing the previous workpiece, it calculates the expected idle time and, in conjunction with the transfer time, reverses the optimal start time of the current device, so that when the workpiece arrives at the downstream device, the downstream device has just completed the previous task, achieving seamless connection.

[0161] The central control system converts the optimized start time and sequence of actions into control commands that can be executed by each device, and sends them to the controllers of each industrial robot and the control systems of each special machine through the communication network. Each device then executes the corresponding actions according to the scheduling commands.

[0162] The improvement in this embodiment is as follows: First, a global information collection mechanism based on the real-time status of all equipment on the production line was established, enabling the central control system to grasp the current operating stage and remaining time of each piece of equipment in real time, rather than relying solely on a preset fixed timing table for triggering and judgment.

[0163] Second, using the single-step time of each discrete process and the transfer path of each industrial robot as dual constraints, the action sequence and timing of each device are dynamically calculated and optimized. The coordination between devices is no longer a fixed sequential trigger, but a dynamic optimization based on the actual operating state, so that the time when the upstream device completes the process and the time when the downstream device starts are closely connected.

[0164] Third, to address the potential spatial interference issues in multi-robot transport paths, path interference is incorporated as a constraint into the scheduling calculation, thus avoiding collision risks at the action sequence optimization level without requiring additional online avoidance negotiations between robots.

[0165] In this embodiment, the central control system, based on the real-time status of each device and the actual process time, uses a dynamic scheduling algorithm to coordinate the action sequences and timing of each industrial robot and special-purpose machine, effectively eliminating redundant waiting time between processes caused by poor coordination between devices. The overall production cycle of the production line is no longer limited by the fixed speed of the slowest single machine or idle time caused by multiple machines waiting, but continuously approaches the theoretical optimal value through global dynamic optimization, improving the overall capacity and equipment utilization rate of the production line. At the same time, when the production line experiences changes in the time of each device due to product changes, equipment maintenance, or fluctuations in incoming materials, the central control system can automatically adapt to the new constraints in the next scheduling calculation without manual intervention to adjust timing parameters, ensuring the flexibility of the production line operation.

[0166] In one specific embodiment, the central control system is further configured to perform at least one of a one-click model change operation, a full-process data traceability operation, and a safety interlock operation.

[0167] I. One-click model change operation The one-click product change operation function is as follows: when the production line needs to switch from the current product model to another product model, the operator only needs to select the target product model on the human-machine interface of the central control system, and the central control system will automatically complete the switching and distribution of all process parameters without the need for manual parameter setting for each piece of equipment.

[0168] In one example implementation, the process parameter database of the central control system pre-stores a complete set of digital process parameter packages corresponding to each product model. The parameter packages include, but are not limited to: the heating temperature-time curve and holding time corresponding to the heating machine, the air pressure-time curve and holding time corresponding to the hot air expansion machine, the pressure-displacement curve corresponding to the preforming hydraulic press, the running path and speed settings of each industrial robot, and the stacking type and stacking parameters of the unloading and palletizing unit, etc.

[0169] After the operator selects the target product model via the human-machine interface, the central control system receives the selection command and automatically retrieves the corresponding complete set of process parameters from the process parameter database. The central control system then sends the heating temperature curve and holding time from the parameter package to the controller of the heating machine, the air pressure curve and holding time to the controller of the hot air expansion machine, the pressure-displacement curve to the controller of the pre-forming hydraulic press, the robot path and speed settings to the controllers of each industrial robot, and the stacking parameters to the unloading and palletizing unit. Each device automatically updates its parameters and reports its ready status upon receiving the new parameters. Simultaneously, if the end effector model corresponding to the target product model differs from the currently used end effector model, the central control system controls the industrial robot to automatically proceed to the gripper storage platform to replace the end effector.

[0170] In another example implementation, the process parameter database can be deployed on an industrial PC or data server in the central control system, supporting remote updates and backups via an external network.

[0171] II. Full-process data traceability operation The function of the full-process data traceability operation is to establish a data record chain containing key process parameters and equipment status for each tube blank from the start of processing to the output of finished product, and to support the traceability query of the production process data of any finished product.

[0172] In one example implementation, when the destacking and loading unit completes the destacking of a blank tube and the blank begins to enter the preforming process, the central control system generates a unique identifier for it. The identifier can be generated by combining a timestamp and the equipment number, or by using an incremental serial number, to ensure that each blank is unique throughout its entire production line lifecycle.

[0173] In the subsequent production process, the central control system associates and stores the identification code with all process data collected in real time at each stage of the tube blank. This process data includes at least: the actual temperature-time curve obtained by the infrared temperature probe in the heating machine from the preset target area; the gas pressure / flow time-series curve and diagnostic results recorded by the hot gas expansion machine during the forming diagnostic operation; the actual pressure-displacement curve of the preforming hydraulic press; the action timestamps and operating status of each industrial robot; and the quality result indicating whether the product is qualified. The aforementioned associated and stored data records are stored in the process data server connected to the central control system.

[0174] In one example implementation, the operator can input the identification code of the product to be traced or the production time period through the human-machine interface of the central control system. The central control system retrieves and graphically displays the corresponding full-process data from the database, supporting process review and quality problem localization.

[0175] In another example implementation, the identification code can be attached to the finished product or material box in the form of a QR code or RFID tag. Subsequent quality inspection or customer acceptance can read the identification code by scanning it and query it in conjunction with the whole process data stored in the production line data server.

[0176] In addition, the central control system collects and statistically analyzes data such as equipment operating status, output, and energy consumption on the production line. In one example implementation, the central control system can automatically generate production statistical reports on a shift, daily, weekly, or monthly basis. These reports include output statistics for each product model, cumulative operating time and energy consumption statistics for each piece of equipment, and quality pass rate analysis for each batch of products. Reports can be viewed locally via a human-machine interface or exported to the upper-level manufacturing execution system via a network interface, providing data support for production management and process optimization.

[0177] III. Safety Interlock Operation The function of the safety interlock operation is to monitor the dangerous area within the safety fence of the production line in real time, and to immediately control the relevant moving equipment to stop and alarm when any safety device is detected to be triggered, so as to ensure the safety of personnel.

[0178] In one example implementation, the production line is equipped with a safety hardware loop consisting of safety door locks, safety light curtains, and emergency stop buttons. Safety door locks are installed on each entrance door of the line's safety perimeter fence. When any safety door is opened, the electrical contacts of the door lock disconnect, interrupting the safety hardware loop. Safety light curtains are installed at the entrances to the robot's working area or the press's operating area. When the light beam is blocked, the light curtain outputs a signal that interrupts the safety hardware loop. Emergency stop buttons are distributed on the main control cabinet panel and in key locations around the production line. Pressing any of these emergency stop buttons also interrupts the safety hardware loop.

[0179] The central control system integrates a safety PLC module, whose input terminals are electrically connected to the aforementioned safety hardware circuits. The safety PLC module continuously collects status signals from each safety hardware circuit at preset intervals. When a collected status signal indicates an interruption in any safety hardware circuit, the safety PLC module immediately executes preset safety control logic: sending an emergency stop command to the industrial robot in the corresponding area to stop the drive output of all motion axes; sending unloading or shutdown commands to the hydraulic systems of the preforming hydraulic press and the hot air expansion machine; sending a stop heating command to the intermediate frequency power supply of the heating machine; simultaneously, the central control system displays the fault location and type through a human-machine interface and issues an alarm signal via an audible and visual alarm.

[0180] The main control system prohibits the production line from restarting until the safety hardware circuit is restored to normal and the operator confirms the reset on the human-machine interface, in order to prevent maintenance or inspection personnel from accidentally starting the equipment before they have completely left the danger zone.

[0181] In summary, this solution provides a fully automated, precise, intelligent closed-loop, and highly efficient intelligent production line control system for the thermal expansion of metal tubular components. The system addresses temperature measurement failure during heating through visual feedback and servo-driven dynamic tracking of temperature measurement points; it provides early warning and self-diagnosis of the expansion process through temporal feature analysis; it prevents temperature overshoot through a multivariate temperature control model and a gradual heating strategy; it compresses process intervals through a two-layer temporal collaborative design at the process and production line levels; it enables rapid and flexible changeover through centralized parameter management and one-click deployment; and it constructs a complete production data traceability chain through full-process identification code association and centralized storage of process data. The system achieves unmanned automated operation within the safety fence of the entire production line, comprehensively overcoming the bottlenecks of existing semi-automated production lines in terms of process stability, production cycle time, changeover flexibility, and quality traceability.

[0182] It will be understood by those skilled in the art that all or some of the steps, systems, or apparatuses disclosed above, and their functional modules / units, can be implemented as software, firmware, hardware, or suitable combinations thereof. In hardware implementations, the division between functional modules / units mentioned above does not necessarily correspond to the division of physical components; for example, a physical component may have multiple functions, or a function or step may be performed collaboratively by several physical components. Some or all components may be implemented as software executed by a processor, such as a digital signal processor or microprocessor, or as hardware, or as an integrated circuit, such as an application-specific integrated circuit (ASIC). Such software may be distributed on a computer-readable medium, which may include computer storage media (or non-transitory media) and communication media (or transient media). As is known to those skilled in the art, the term "computer storage medium" includes volatile and non-volatile, removable and non-removable media implemented in any method or technology for storing information (such as computer-readable instructions, data structures, program modules, or other data). Computer storage media include, but are not limited to, RAM, ROM, EEPROM, flash memory or other memory technologies, CD-ROM, digital versatile disc (DVD) or other optical disc storage, magnetic cartridges, magnetic tape, disk storage or other magnetic storage devices, or any other medium that can be used to store desired information and can be accessed by a computer. Furthermore, it is well known to those skilled in the art that communication media typically contain computer-readable instructions, data structures, program modules, or other data in modulated data signals such as carrier waves or other transmission mechanisms, and may include any information delivery medium.

Claims

1. A control system for an intelligent production line for the thermal expansion of metal tubular components, the production line comprising a dedicated heating machine and a central control system, characterized in that, The heating machine includes a vision system, an infrared temperature probe, a multi-axis servo slide that carries the infrared temperature probe, and a heating device. The central control system is configured to perform the following operations during the heating process of the workpiece by the heating machine: The vision system acquires a real-time contour image of the workpiece. Image analysis is used to identify the actual thermal deformation state of the workpiece caused by heating; Based on the actual thermal deformation state, the position of the infrared temperature probe is dynamically adjusted by the multi-axis servo slide, so that the temperature measurement area of ​​the infrared temperature probe is always locked on the preset target area on the workpiece surface. Based on the temperature data collected by the infrared temperature probe after its position is adjusted from the preset target area, the output power of the heating device is adjusted in a closed loop.

2. The control system according to claim 1, characterized in that: The overall control system identifies the actual thermal deformation state of the workpiece due to heating through image analysis, including: before heating is started, locking the reference feature points on the workpiece surface as the preset target area through the vision system; during the heating process, calculating the thermal deformation vector of the workpiece contour relative to the reference feature points in real time. The overall control system dynamically adjusts the position of the infrared temperature measuring probe through the multi-axis servo slide, including: driving the multi-axis servo slide to move the infrared temperature measuring probe according to the calculated thermal deformation vector, so that the temperature measuring spot of the infrared temperature measuring probe always follows and locks onto the reference feature point after the displacement.

3. The control system according to claim 1, characterized in that, The central control system performs closed-loop regulation of the output power of the heating device, including: Control commands are generated based on a multivariable temperature control model. The input of the multivariable temperature control model includes at least one of the following: the real-time temperature of the preset target area collected by the infrared temperature probe, the material information of the workpiece, the initial diameter of the workpiece, and the cumulative heating time. When the real-time temperature approaches the preset target temperature threshold, the system automatically switches to a gradual heating strategy to prevent temperature overshoot.

4. The control system according to claim 1, characterized in that, The production line also includes a hot air expansion machine; wherein the hot air expansion machine includes a detection device. The overall control system is also configured to perform the following operations during the hot gas expansion molding process after the heating step is completed: The detection device collects real-time time-series data of the gas pressure or flow rate inside the workpiece. Obtain at least one of the following features from the time series data: rising slope, fluctuation frequency, and steady-state retention. When a deviation is detected between the detected feature and the preset process curve feature, and the deviation exceeds a preset threshold, it is diagnosed as a risk of minor slow leakage or pipeline blockage. Based on the diagnosis, when the risk occurs, an early warning is triggered and a safety control strategy is implemented, such as pressurization, suspension of heating, or shutdown.

5. The control system according to claim 1, characterized in that, The production line also includes an AGV material transfer system, which includes AGV carts and standardized material bins. The AGV's carrying platform is equipped with multiple positioning pins, which are arranged in a matrix, and each positioning pin has a guide surface on its top. The bottom of the standardized material box is provided with multiple positioning holes, and the positions of the multiple positioning holes correspond one-to-one with the positions of the multiple positioning pins. When the standardized bin is placed on the AGV's carrying platform, each positioning pin is inserted into its corresponding positioning hole. Through the guiding effect of the tapered guide surface and the engagement of the positioning pin with the positioning hole, the standardized bin is automatically guided to the preset precise position. The AGV material transfer system also includes an automatic bin identification and status tracking system, which is used to verify the bin number and material information at the AGV docking station, and unlock the standardized bin after confirming that there are no errors, allowing the standardized bin to be transferred.

6. The control system according to claim 1, characterized in that, The production line also includes a preforming hydraulic press, which includes an automated mold system, the automated mold system comprising: A pneumatic ejection device is used to automatically lift the workpiece to a preset gripping height after molding is completed; A buffer mechanism is provided at the end of the ejection stroke of the pneumatic ejection device to prevent the workpiece from bouncing or being damaged due to inertia when it is ejected into place. The control system of the preforming hydraulic press is connected to the main control system so that the ejection action of the pneumatic ejection device and the gripping action of the external transfer robot are coordinated in time, thereby reducing the process interval time.

7. The control system according to claim 1, characterized in that, The production line also includes a material unloading and palletizing unit, which includes an unloading robot, a workpiece buffer rack, and a vision positioning system. The unloading robot is equipped with a gripping mechanism and a dedicated palletizing end effector, and is configured to perform the following sequence of operations: The gripping mechanism is used to remove the formed workpiece from the hot air expansion machine and place it in the workpiece buffer rack. After automatically switching to the dedicated palletizing end effector, the workpiece is picked up from the workpiece buffer rack and, guided by the vision positioning system, is placed into the material box according to the preset palletizing pattern. The workpiece buffer rack is equipped with a precision positioning mechanism and a clamping mechanism, which are used to position and clamp the workpiece before it is stacked.

8. The control system according to claim 7, characterized in that, The unloading robot is also configured to: After each layer of workpieces is stacked, the stacking status is checked using the vision positioning system. When abnormal stacking is detected, a reorganization operation is automatically triggered.

9. The control system according to any one of claims 1 to 7, characterized in that, The production line also includes industrial robots that correspond one-to-one with the equipment in the production line; the central control system is also configured to perform collaborative scheduling operations. Based on the real-time status of each piece of equipment in the production line and the production tasks to be executed, the single-step time of each discrete process and the transfer path of the corresponding industrial robot are used as constraints to dynamically calculate and optimize the action sequence and timing of the industrial robot and each piece of equipment, so as to minimize the redundant waiting time between processes.

10. The control system according to any one of claims 1 to 7, characterized in that, The central control system is also configured to perform at least one of the following: one-click model change operation, full-process data traceability operation, and safety interlock operation; wherein: The one-click model change operation involves: receiving a selection instruction for the target product model; responding to the instruction, automatically retrieving a complete set of digital process parameter packages corresponding to the target product model from the process parameter database; and sending the configuration information in the parameter package to the corresponding equipment in the production line with one click to adapt to the target product model. The full-process data traceability operation involves generating a unique identification code for each tube blank at the start of processing; during subsequent production, the identification code is associated with and stored in conjunction with all real-time collected process data, which includes at least: the actual temperature curve collected by the infrared temperature probe on the preset target area, the gas pressure / flow time sequence curve and key process parameters in the forming diagnosis step; The safety interlock operation is as follows: the safety PLC module integrated in the main control system continuously collects the status signals of the safety hardware circuits; when the collected status signals indicate that any of the safety hardware circuits is interrupted, all moving equipment in the relevant area is controlled to enter a preset safety stop state and an alarm signal is issued, wherein the safety hardware circuits include safety doors, light curtains and emergency stop buttons.

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