Intelligent assembling method for integrated built-in top plate

Abstract

The invention relates to the technical field of in-built roofs, and provides an intelligent assembly method for an integrated in-built roof, which comprises the following steps: an assembly line planning step: re-planning an assembly line layout, building an integrated middle roof assembly line, and realizing the connection among all procedures through continuous procedure integration and worktable optimized layout; an automatic transfer step: configuring an automatic turnover machine and a full-electric self-walking AGV lifting vehicle, through the arrangement of structures such as the automatic turnover machine and the full-electric self-walking AGV lifting vehicle, enabling the automatic turnover machine to drive a worm and gear mechanism through a servo motor to realize stable turnover of components, and enabling the AGV lifting vehicle to perform autonomous path planning and accurate positioning by means of a laser navigation system; under cooperative scheduling of the manufacturing execution system, manual intervention and material waiting time are greatly reduced, the overall installation efficiency is remarkably improved, and through the technical scheme, the problems of low installation efficiency and low product quality in the prior art are solved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of built-in ceiling, in particular, to an integrated built-in ceiling intelligent assembly method. BACKGROUND

[0002] The built-in ceiling, commonly referred to as "ceiling", refers to the integrated decoration and functional components installed on the top of the internal cabin of a vehicle (such as a rail transit vehicle, a bus), a building (such as a high-speed rail station, a subway station) or a ship. It is not only a visual ceiling of the internal space, but also a modularized and standardized component integrating multiple functional systems.

[0003] In the field of rail transit vehicle manufacturing, the built-in ceiling, as the largest visible component in the passenger compartment, directly affects the visual effect, riding comfort and safety of the vehicle. The traditional installation method of the built-in ceiling of the rail transit vehicle mainly relies on the "manual leading and sequential operation" mode, and its specific process and characteristics are as follows: The existing technology usually adopts fixed station assembly. First, a plurality of operators move large built-in ceiling components (such as skeletons, interior panels, pre-integrated air ducts, and lamp strips) to the assembly station by using a trolley or a manual hydraulic vehicle. Then, the operators manually position and center according to the drawings and tooling molds by visual observation and using conventional measuring tools (such as a tape measure and a level). In the connection process, hand-held tools such as pneumatic or electric screwdrivers and rivet guns are commonly used, and the tightening degree of the bolts and the riveting quality are controlled by the experience of the operators. The entire assembly process is linearly expanded, and each process is relatively independent. The material flow is transported between different stations by the intermittent transportation of the manually driven forklift or flatbed truck.

[0004] However, this traditional manual assembly method has many inherent defects and cannot meet the high requirements of modern rail transit for production efficiency and product quality. SUMMARY

[0005] The present application provides an integrated built-in ceiling intelligent assembly method, which solves the problems of low installation efficiency and low product quality in the related art.

[0006] The technical scheme of the present application is as follows: an integrated built-in ceiling intelligent assembly method, comprising the following steps: S1, assembly line planning step: re-planning the assembly line layout to create an integrated middle ceiling assembly line, and realizing the connection between processes through continuous process integration and workbench optimization layout; S2, automatic transfer step: configure an automatic turnover machine and a full-electric self-propelled AGV lifting vehicle, the automatic turnover machine realizes stable turnover of the middle top plate component through motor driving, the full-electric self-propelled AGV lifting vehicle realizes accurate positioning and path planning through a laser navigation system, and the automatic turnover machine and the full-electric self-propelled AGV lifting vehicle realize automatic transfer and turnover operation of the component through collaborative scheduling of a manufacturing execution system; S3, position calibration step: real-time monitoring and calibration of the spatial position of the middle top plate component in X / Y / Z directions are realized through a laser tracker, real-time position information is calculated by emitting a laser beam to a component reflection target and measuring the reflection angle and distance, when the position deviation is detected to be out of the preset allowable range, the deviation information is fed back to the manufacturing execution system, and assembly parameter adjustment or correction instructions are sent to the execution equipment by the manufacturing execution system; S4, robot assembly step: a six-axis industrial robot is adopted to perform automatic thread connection process and riveting process, a vacuum chuck and a mechanical gripper are configured on the robot end effector to adapt to the grasping requirements of flexible components and rigid components, the connection position is determined through a vision positioning system during the thread connection process, and a torque device is controlled to tighten the bolt, the riveting position is determined through the vision positioning system during the riveting process, and the riveting operation is completed by controlling the riveting gun; S15, collaborative positioning step: a vision positioning system, a 3D vision system and a laser profiler are deployed to realize multi-sensor collaborative positioning, the vision positioning system preliminarily determines the component position and spatial attitude, the 3D vision system realizes accurate identification of feature points through three-dimensional reconstruction and feature extraction, and the laser profiler realizes accurate identification of feature points through surface profile scanning and outputs positioning coordinates, guiding the robot to complete precision assembly; S6, whole-process management and control step: a manufacturing execution system is integrated to realize digital management and control of the whole assembly process, the system integrates a device state monitoring module, an assembly progress tracking module, a quality data acquisition module and a fault early warning processing module, realizes comprehensive monitoring and intelligent scheduling of the assembly process through real-time data interaction, and supports dynamic adjustment and optimization of production plans with an upper management system.

[0007] As a preferred scheme of the present application, in the assembly line planning step, the re-planning of the assembly line specifically includes integrating the dispersed pre-assembly process, final assembly process and detection process into a continuous production line, reducing the material carrying distance between processes by optimizing the relative position layout of workbenches, and establishing an assembly rhythm of the assembly line to improve the overall assembly efficiency.

[0008] As a preferred embodiment of the present invention, in the automated transfer step, the automatic tilting machine and the all-electric self-propelled AGV lifting vehicle achieve task coordination and scheduling through the manufacturing execution system. When the production line workbench detects the need for component supply through sensors, the manufacturing execution system sends a transfer instruction to the designated all-electric self-propelled AGV lifting vehicle. The automatic tilting machine performs a tilting operation at a specific angle according to the current assembly process requirements. The two work together to complete the directional conveying and posture adjustment of materials.

[0009] As a preferred embodiment of the present invention, in the position calibration step, the laser tracker calibration process calculates the real-time spatial coordinates of the component by accurately measuring the reflection angle and round-trip time of the laser beam. When the system detects that the position deviation exceeds the preset threshold, the manufacturing execution system automatically adjusts the operating parameters of the relevant assembly equipment or directly sends position correction commands to the six-axis industrial robot or AGV lifting vehicle to form a closed-loop control loop.

[0010] As a preferred embodiment of the present invention, in the robot assembly step, when the six-axis industrial robot performs the threaded connection process, it identifies the mating position of the bolt and nut through a vision positioning system, uses an intelligent wrench to perform the tightening operation, and monitors and feeds back the torque data to the manufacturing execution system in real time; when performing the riveting process, after the riveting gun completes the riveting operation, it automatically uploads the riveting force parameters and riveting duration parameters to the quality database of the manufacturing execution system.

[0011] As a preferred embodiment of the present invention, in the collaborative positioning step, the collaborative mechanism of the visual positioning system, the 3D vision system, and the laser profilometer is specifically manifested as follows: the visual positioning system first performs two-dimensional image acquisition and preliminary positioning of the component to obtain the position and rotational attitude of the component in the plane; the 3D vision system performs three-dimensional point cloud reconstruction and feature geometry extraction based on structured light projection or stereo vision principles; the laser profilometer scans the surface of the component to obtain high-precision contour information through laser triangulation; the data from the three sensors are fused and processed in the central processing unit to jointly output precise positioning coordinates in a unified coordinate system, guiding the robot to complete the assembly operation with sub-millimeter precision.

[0012] As a preferred embodiment of the present invention, in the full-process control steps, the equipment status monitoring function integrated into the manufacturing execution system collects the operating status data of the automatic turnover machine, AGV lifting vehicle, six-axis industrial robot, and laser tracker in real time through industrial Ethernet; the assembly progress tracking function realizes real-time control of production progress by setting RFID readers or visual recognition tags at each process node; the quality data acquisition function comprehensively covers bolt tightening torque curves, riveting process parameters, and position calibration records; and the fault early warning and processing function realizes an early warning and automatic processing mechanism for abnormal equipment conditions based on historical data and machine learning algorithms.

[0013] As a preferred embodiment of the present invention, the assembly method adopts a modular design concept, decomposing the top plate into multiple functionally independent assembly modules. The modules are quickly interchanged through standardized interfaces, significantly reducing the replacement time of a single module and greatly improving the overall assembly efficiency. This method is particularly suitable for the assembly of interior top plates of rail transit vehicles.

[0014] As a preferred embodiment of the present invention, in the robot assembly step and the collaborative positioning step, the vision positioning system also undertakes the function of online inspection of assembly quality. It uses image recognition algorithms to detect assembly defects such as missing bolts, incorrect labeling, and missing sealing strips in real time, and uploads the inspection results to the manufacturing execution system in real time to ensure the reliability of assembly quality and realize full-process quality control and data traceability from parts to finished products.

[0015] The working principle and beneficial effects of this invention are as follows: 1. This invention, through the setup of an automatic tilting machine and a fully electric self-propelled AGV lifting vehicle, achieves smooth component tilting by using a servo motor to drive a worm gear mechanism. The AGV lifting vehicle relies on a laser navigation system for autonomous path planning and precise positioning. Under the coordinated scheduling of the manufacturing execution system, the two significantly reduce manual intervention and material waiting time, thereby significantly improving the overall installation efficiency.

[0016] 2. This invention utilizes a six-axis industrial robot and a multi-sensor collaborative positioning system. The six-axis robot, driven by an AC servo drive system, performs high-precision threaded connections and riveting. The multi-sensor system achieves feature point fusion positioning and online quality inspection through visual positioning, 3D reconstruction, and laser contour scanning, ensuring that assembly gaps, connection torque, and riveting parameters are controllable throughout the process, effectively improving product consistency and reliability. Attached Figure Description

[0017] The present invention will now be described in further detail with reference to the accompanying drawings and specific embodiments.

[0018] Figure 1 This is a flowchart illustrating the overall assembly process of the present invention. Figure 2 This is a flowchart illustrating the production line planning and automated transfer process of this invention. Figure 3 This is a flowchart of the position calibration and robot assembly process of the present invention; Figure 4 This is a flowchart of the multi-sensor collaborative positioning system of the present invention; Figure 5 This is a flowchart of the MES full-process digital management and control process of the present invention; Figure 6 This is a flowchart illustrating the modular assembly process of the present invention. Figure 7This is a flowchart illustrating the quality traceability process of this invention. Detailed Implementation

[0019] The technical solutions of the present invention will be clearly and completely described below with reference to the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0020] Example 1 like Figures 1-7 As shown in this embodiment, an integrated intelligent assembly method for interior roof panels is characterized by the following steps: S1. Assembly line planning steps: Re-plan the assembly line layout, create an integrated mid-to-top assembly line, and achieve the connection between each process through continuous process integration and workbench optimization layout; S2. Automated transfer steps: Configure an automatic tilting machine and a fully electric self-propelled AGV lifting vehicle. The automatic tilting machine achieves smooth tilting of the top plate component through motor drive. The fully electric self-propelled AGV lifting vehicle adopts a laser navigation system to achieve precise positioning and path planning. The automatic tilting machine and the fully electric self-propelled AGV lifting vehicle are coordinated and scheduled through the manufacturing execution system to complete the automatic transfer and tilting operation of the component. S3. Position calibration step: Use a laser tracker to monitor and calibrate the spatial position of the top plate component in the X / Y / Z directions in real time. Calculate the real-time position information by emitting a laser beam to the component's reflective target and measuring the reflection angle and distance. When the detected position deviation exceeds the preset allowable range, the deviation information is fed back to the manufacturing execution system, which then adjusts the assembly parameters or sends a correction command to the execution equipment. S4. Robot Assembly Steps: A six-axis industrial robot is used to perform automatic thread connection and riveting processes. The robot's end effector is equipped with a vacuum suction cup and a mechanical gripper to meet the gripping requirements of flexible and rigid parts. During the thread connection process, the connection position is determined by the vision positioning system and the torque device is controlled to tighten the bolts. During the riveting process, the riveting position is determined by the vision positioning system and the riveting gun is controlled to complete the riveting operation. S15, Collaborative Positioning Steps: Deploy a visual positioning system, a 3D vision system, and a laser profilometer to achieve multi-sensor collaborative positioning. The visual positioning system initially determines the position and spatial orientation of the component. The 3D vision system, through three-dimensional reconstruction and feature extraction, and the laser profilometer, through surface contour scanning, jointly achieve accurate identification of feature points and output positioning coordinates to guide the robot to complete precision assembly. S6. Full-process control steps: The integrated manufacturing execution system realizes digital control of the entire assembly process. The system integrates equipment status monitoring module, assembly progress tracking module, quality data acquisition module and fault early warning and processing module. Through real-time data interaction, it realizes comprehensive monitoring and intelligent scheduling of the assembly process, and supports dynamic adjustment and optimization of production plans with the upper management system.

[0021] Specifically, this invention provides a specific implementation method for an integrated intelligent assembly method for interior roof panels. In the assembly line planning step, the traditional assembly line is first redesigned to create an integrated roof panel assembly line. This is achieved by systematically integrating previously scattered processes and optimizing the spatial layout of workbenches, enabling seamless connections between processes. In the automated transfer step, an automatic tilting machine and a fully electric self-propelled AGV (Automated Guided Vehicle) are configured. The automatic tilting machine uses a servo motor-driven reducer transmission, achieving smooth tilting of the roof panel components via a synchronous belt or rack and pinion mechanism. The fully electric self-propelled AGV uses a differential steering wheel drive system, combined with a laser navigation system, to achieve autonomous path planning and precise positioning. The navigation system calculates position by receiving laser beams emitted from a laser scanner and calculating the reflection angle. The two sets of equipment are coordinated and scheduled through a manufacturing execution system to achieve automatic material transfer and tilting operations. In the position calibration step, utilizing the precision measurement capabilities of a laser tracker, a laser beam is emitted towards a reflective target mounted on the component, and the return angle and propagation time of the reflected light are precisely measured. The real-time position coordinates of the component in three-dimensional space are calculated using the triangulation principle. When a positional deviation exceeds the preset range, the system immediately feeds the deviation information back to the manufacturing execution system. In the robotic assembly step, a six-axis industrial robot is used as the execution body. Its six rotary joints employ an AC servo motor coupled with a precision reducer transmission scheme to achieve precise movement in any spatial orientation. The robot's end effector is equipped with a vacuum suction cup and an adaptive mechanical gripper, which reliably grasp flexible and rigid components through a vacuum generator and a pneumatic transmission system, respectively. In the collaborative positioning step, a multi-sensor collaborative positioning system is deployed. The visual positioning system uses an industrial camera to acquire two-dimensional images for initial positioning, the 3D vision system reconstructs three-dimensional point clouds based on structured light projection, and the laser profilometer performs high-precision contour scanning using laser triangulation. Data from the three sensors are fused and processed in the central processing unit. In the end-to-end control step, the manufacturing execution system acts as the control hub, establishing real-time data communication with each device via industrial Ethernet to achieve digital control of the entire assembly process.

[0022] In this embodiment, the assembly line planning step specifically includes integrating the dispersed pre-assembly process, final assembly process and inspection process into a continuous production line, reducing the material handling distance between processes by optimizing the relative position layout of workbenches, and establishing a flow-line assembly rhythm to improve overall assembly efficiency.

[0023] Specifically, in the process of redesigning the assembly line layout, the traditional discrete production model was first reformed. Pre-assembly, final assembly, and inspection processes, previously scattered across multiple areas, were systematically integrated according to technological logic to establish a continuous flow production line. The pre-assembly process primarily handles the pre-assembly of small and medium-sized components, the final assembly process handles the integration and assembly of major structural components, and the inspection process is responsible for quality verification. This process integration eliminates material waiting and multiple transfers inherent in the traditional model. Regarding workbench layout optimization, digital factory simulation technology is used to accurately calculate and optimize the relative positions of workbenches, arranging workstations with technological logical connections adjacent to each other. This allows materials to flow directly between processes via an automated conveyor system. The workbenches adopt a modular design, equipped with pneumatic quick-release clamps and standardized tooling interfaces, adapting to the assembly needs of products of different specifications. The reduction in material handling distance is achieved by optimizing material delivery paths. Based on process integration and layout optimization, a flow-line assembly model based on cycle time control is established. By accurately calculating the standard operating time of each process and setting a reasonable production cycle time, the continuous and stable flow of materials between processes is ensured, thereby significantly improving overall assembly efficiency.

[0024] In this embodiment, during the automated transfer step, the automatic tilting machine and the all-electric self-propelled AGV lifting vehicle achieve task coordination and scheduling through the manufacturing execution system. When the production line workbench detects the need for component supply through sensors, the manufacturing execution system sends a transfer instruction to the designated all-electric self-propelled AGV lifting vehicle. The automatic tilting machine performs a tilting operation at a specific angle according to the current assembly process requirements. The two work together to complete the directional conveying and posture adjustment of materials.

[0025] Specifically, the automatic tilting machine adopts a gantry structure design. Its tilting mechanism is driven by a servo motor, and motion transmission and torque amplification are achieved through a worm gear reducer. The self-locking function of the worm gear mechanism ensures the safety and reliability of the tilting process. The tilting angle is controlled by the encoder of the servo motor, which can achieve positioning at any angle. The fully electric self-propelled AGV lifting vehicle adopts a Mecanum wheel omnidirectional moving chassis or differential steering wheel drive. The wheels are driven by a servo motor in conjunction with a precision reducer to achieve forward, backward, translation and rotation movement. The laser navigation system uses reflectors placed around the workshop. The laser scanner on the AGV body scans these reflectors to calculate its own position and achieve positioning. The manufacturing execution system acts as the scheduling hub. By monitoring the status of the production line in real time, when the workbench detects that a part needs to be supplied through photoelectric sensors or RFID readers, the system immediately generates a transfer task. The scheduling algorithm sends transfer instructions to the most suitable all-electric self-propelled AGV lifting vehicle based on the AGV's current position, power status, and task priority. At the same time, the system sends a flipping angle instruction to the automatic flipping machine based on the current assembly process requirements. After the AGV transports the parts to the flipping station, the flipping machine automatically performs a flipping operation at a specific angle. The two work together in precise timing to complete the directional conveying and attitude adjustment of materials, achieving full automation of the process.

[0026] In this embodiment, during the position calibration step, the laser tracker calibration process calculates the real-time spatial coordinates of the component by accurately measuring the reflection angle and round-trip time of the laser beam. When the system detects that the position deviation exceeds the preset threshold, the manufacturing execution system automatically adjusts the operating parameters of the relevant assembly equipment or directly sends position correction commands to the six-axis industrial robot or AGV lifting vehicle, forming a closed-loop control loop.

[0027] Specifically, the laser tracker, as a high-precision spatial measurement device, is a laser interferometric ranging system mounted on a dual-axis precision turntable. It emits a laser beam towards a reflective target attached to the top plate component. After reaching the target, the laser beam returns along its original path. The tracker calculates the precise distance by measuring the phase change or time of flight of the laser. Simultaneously, it measures the horizontal and vertical rotation angles using a precision encoder. Through spherical coordinate transformation, combined with the distance and angle values, it calculates the real-time coordinates of the component in three-dimensional space. The entire measurement process is performed continuously at an extremely high frequency to ensure the real-time nature of the position data. When the system detects a position deviation exceeding a preset threshold through coordinate comparison, the manufacturing execution system immediately initiates a correction program. Based on the magnitude and direction of the deviation, the system automatically calculates the parameter values ​​that need adjustment. These parameters may include the robot's trajectory offset and the compensation value of the positioning mechanism. The adjustment command is sent to the relevant assembly equipment via a real-time industrial Ethernet. After receiving the correction command, the six-axis industrial robot dynamically adjusts its motion trajectory through its control system. The AGV (Automated Guided Vehicle) then performs fine-tuning of its position according to the command, ensuring that the assembly accuracy remains within the allowable range.

[0028] In this embodiment, during the robot assembly step, when the six-axis industrial robot performs the threaded connection process, it identifies the mating position of the bolt and nut through a vision positioning system, uses an intelligent wrench to perform the tightening operation, and monitors and feeds back the torque data to the manufacturing execution system in real time; when performing the riveting process, after the riveting gun completes the riveting operation, it automatically uploads the riveting force parameters and riveting duration parameters to the quality database of the manufacturing execution system.

[0029] Specifically, the six-axis industrial robot adopts a serial articulated structure, with each joint driven by an AC servo motor. High torque output is achieved through a reducer. The robot's motion control system uses forward and inverse kinematics calculations to achieve precise positioning of the end effector in three-dimensional space. When performing threaded connection, the robot first moves to a pre-installed position, and then a vision positioning system installed at the end effector performs precise positioning. This involves acquiring images through an industrial camera and using edge detection and pattern recognition algorithms to identify the mating position of the bolt and nut. After positioning, the robot's end effector is fitted with a smart wrench, driven by a servo motor and integrating a torque sensor and angle encoder. During tightening, it monitors torque and angle data in real time and feeds this data back to the manufacturing execution system (MES) via a fieldbus. When performing riveting, the robot's end effector is fitted with a riveting gun, driven by a pneumatic or servo-electric motor. Precise control of the riveting force and duration ensures riveting quality. The riveting gun integrates pressure and displacement sensors. After completing the riveting operation, it automatically uploads process data such as riveting force and duration parameters to the MES's quality database. The entire process achieves digital acquisition and recording of process parameters.

[0030] In this embodiment, the collaborative mechanism of the visual positioning system, 3D vision system, and laser profilometer in the collaborative positioning step is specifically manifested as follows: the visual positioning system first performs two-dimensional image acquisition and preliminary positioning of the component to obtain the component's position and rotational attitude in the plane; the 3D vision system performs three-dimensional point cloud reconstruction and feature geometry extraction based on structured light projection or stereo vision principles; the laser profilometer scans the surface of the component to obtain high-precision contour information through laser triangulation; the data from the three sensors are fused and processed in the central processing unit to jointly output precise positioning coordinates in a unified coordinate system, guiding the robot to complete the assembly operation with sub-millimeter precision.

[0031] Specifically, the visual positioning system, as the primary positioning unit, uses a high-resolution industrial camera to acquire two-dimensional images of the component. Image processing algorithms extract the component's contour features and marker points, and perspective transformation is used to calculate the component's position and rotational attitude in the plane, providing initial coordinates for subsequent precise positioning. The 3D vision system operates based on structured light projection, projecting specific light spot patterns or grating stripes onto the component surface. The camera captures the patterns deformed by the surface contour, and phase measurement and triangulation are used to reconstruct the three-dimensional point cloud data of the component surface. The system extracts key geometric features such as planes, edges, and holes from the point cloud data. The laser profilometer uses laser triangulation, scanning the component surface with a laser line. The camera receives the deformed laser line at a certain angle, and high-precision contour profile data is obtained through triangulation. The data from the three sensors are fused by a central processing unit. First, time synchronization and coordinate system unification are performed. Then, a data registration algorithm maps data from different sources to the same coordinate system. Complementary filtering or Kalman filtering algorithms eliminate errors from individual sensors, ultimately outputting precise positioning coordinates in a unified coordinate system. This fused coordinate data is used to guide the robot to complete assembly operations with sub-millimeter precision, ensuring assembly quality.

[0032] In this embodiment, during the full-process control steps, the equipment status monitoring function integrated into the manufacturing execution system collects real-time operating status data of automatic turnover machines, AGV lifting vehicles, six-axis industrial robots, and laser trackers via industrial Ethernet; the assembly progress tracking function achieves real-time control of production progress by setting RFID readers or visual recognition tags at each process node; the quality data acquisition function comprehensively covers bolt tightening torque curves, riveting process parameters, and position calibration records; and the fault early warning and processing function realizes an early warning and automatic processing mechanism for abnormal equipment conditions based on historical data and machine learning algorithms.

[0033] Specifically, the Manufacturing Execution System (MES) establishes a network connection with all devices via Industrial Ethernet. The equipment status monitoring function collects real-time operating parameters such as motor current, speed, and temperature of the automatic tilting machine via OPC and UA protocols; battery power, navigation status, and motion parameters of the AGV lifting vehicle; joint torque, servo status, and fault codes of the six-axis industrial robot; and measurement status and environmental compensation parameters of the laser tracker. The assembly progress tracking function uses RFID readers or visual recognition tags at each process node. When a workpiece with an RFID tag passes through a process node, the reader automatically collects workpiece information, and the visual recognition system automatically records the process progress by reading the QR code or barcode on the workpiece. The quality data acquisition function comprehensively covers torque-angle curve characteristic parameters during bolt tightening, pressure-time curve parameters during riveting, and deviation records and correction history during position calibration. The fault early warning and processing function establishes an equipment health status model based on historical operating data. It analyzes the deviation between real-time data and the historical model using machine learning algorithms, issuing early warnings when abnormal trends appear and initiating corresponding automatic processing mechanisms according to preset rules, such as equipment self-calibration, production cycle adjustment, or maintenance reminders.

[0034] In this embodiment, the assembly method adopts a modular design concept, decomposing the top plate into multiple functionally independent assembly modules. The standardized interface enables rapid replacement between modules, significantly reducing the replacement time of a single module and greatly improving the overall assembly efficiency. This method is particularly suitable for the assembly of interior top plates of rail transit vehicles.

[0035] Specifically, the complete roof panel system is decomposed into multiple functionally independent assembly modules. Each module has clearly defined functional boundaries and standard mechanical and electrical interfaces. For mechanical interfaces, locating pins and quick-locking mechanisms are used to achieve precise docking and reliable connection between modules, ensuring consistency in repetitive assembly. For electrical interfaces, waterproof connectors and standard cables are used to achieve electrical connections between modules. The modular design makes the replacement of individual modules simple and quick; operators only need to disconnect a few mechanical connectors and electrical connectors to complete the module replacement. The standardized interface design ensures interchangeability between different modules, reducing adjustment and adaptation time during assembly. The independence and interchangeability of modules allow the production line to quickly adapt to the roof panel assembly requirements of different vehicle models. Only the corresponding functional modules need to be replaced to achieve rapid production line switching. This modular design concept is particularly suitable for the assembly of interior roof panels in rail transit vehicles, as rail transit vehicles typically require customized configurations based on different line requirements and customer specifications. The modular design provides the necessary flexibility and adaptability.

[0036] In this embodiment, during the robot assembly and collaborative positioning steps, the vision positioning system also undertakes the function of online assembly quality detection. It uses image recognition algorithms to detect assembly defects such as missing bolts, incorrectly affixed labels, and missing sealing strips in real time, and uploads the detection results to the manufacturing execution system in real time to ensure the reliability of assembly quality and realize full-process quality control and data traceability from parts to finished products.

[0037] Specifically, in the robot assembly and collaborative positioning steps, the vision positioning system, in addition to its positioning function, also undertakes online inspection of assembly quality. It acquires images of assembled components using high-resolution industrial cameras and employs deep learning algorithms for defect identification. For bolt omission detection, the algorithm analyzes image features of the bolt installation area to identify missing bolts. For mislabeled defects, the system verifies the correctness of the label content using optical character recognition technology and checks the accuracy of the label's placement and orientation using image matching algorithms. For missing sealing strips, the system analyzes the texture features and edge contours of the sealing strip installation area to determine if the sealing strip is completely installed. During the inspection process, the system uses multi-angle imaging and 3D reconstruction technology to ensure comprehensive inspection and avoid omissions due to perspective issues. All inspection results are uploaded to the manufacturing execution system in real time. The system automatically judges the product quality status based on the inspection results, automatically marks non-conforming products and triggers alarms. Inspection data is bound to product serial numbers for storage, establishing a complete product quality file. This enables end-to-end quality control and data traceability from parts to finished products, providing data support for quality improvement.

[0038] The above are merely preferred embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. An integrated intelligent assembly method for interior roof panels, characterized in that, Includes the following steps: S1. Assembly line planning steps: Re-plan the assembly line layout, create an integrated mid-to-top assembly line, and achieve the connection between each process through continuous process integration and workbench optimization layout; S2. Automated transfer steps: Configure an automatic tilting machine and a fully electric self-propelled AGV lifting vehicle. The automatic tilting machine achieves smooth tilting of the top plate component through motor drive. The fully electric self-propelled AGV lifting vehicle adopts a laser navigation system to achieve precise positioning and path planning. The automatic tilting machine and the fully electric self-propelled AGV lifting vehicle are coordinated and scheduled through the manufacturing execution system to complete the automatic transfer and tilting operation of the component. S3. Position calibration step: The laser tracker is used to monitor and calibrate the spatial position of the top plate component in the X / Y / Z directions in real time. The laser beam is emitted to the component's reflection target and the reflection angle and distance are measured to calculate the real-time position information. When the position deviation is detected to exceed the preset allowable range, the deviation information is fed back to the manufacturing execution system, which then adjusts the assembly parameters or sends a correction command to the execution equipment. S4. Robot Assembly Steps: A six-axis industrial robot is used to perform automatic thread connection and riveting processes. The robot's end effector is equipped with a vacuum suction cup and a mechanical gripper to meet the gripping requirements of flexible and rigid parts. During the thread connection process, the connection position is determined by the vision positioning system and the torque device is controlled to tighten the bolts. During the riveting process, the riveting position is determined by the vision positioning system and the riveting gun is controlled to complete the riveting operation. S15, Collaborative Positioning Steps: Deploy a visual positioning system, a 3D vision system, and a laser profilometer to achieve multi-sensor collaborative positioning. The visual positioning system initially determines the position and spatial orientation of the component. The 3D vision system, through three-dimensional reconstruction and feature extraction, and the laser profilometer, through surface contour scanning, jointly achieve accurate identification of feature points and output positioning coordinates to guide the robot to complete precision assembly. S6. Full-process control steps: The integrated manufacturing execution system realizes digital control of the entire assembly process. The system integrates equipment status monitoring module, assembly progress tracking module, quality data acquisition module and fault early warning and processing module. Through real-time data interaction, it realizes comprehensive monitoring and intelligent scheduling of the assembly process, and supports dynamic adjustment and optimization of production plans with the upper management system.

2. The integrated intelligent assembly method for interior roof panels according to claim 1, characterized in that, In the assembly line planning step, the replanning of the assembly line specifically includes integrating the scattered pre-assembly process, final assembly process and inspection process into a continuous production line, reducing the material handling distance between processes by optimizing the relative position layout of workbenches, and establishing a flow-line assembly cycle to improve overall assembly efficiency.

3. The integrated interior roof panel intelligent assembly method according to claim 1, characterized in that, In the automated transfer step, the automatic tilting machine and the all-electric self-propelled AGV lifting vehicle achieve task coordination and scheduling through the manufacturing execution system. When the production line workbench detects that a part needs to be supplied through the sensor, the manufacturing execution system sends a transfer instruction to the designated all-electric self-propelled AGV lifting vehicle. The automatic tilting machine performs a tilting operation at a specific angle according to the current assembly process requirements. The two work together to complete the directional conveying and posture adjustment of the material.

4. The integrated intelligent assembly method for interior roof panels according to claim 1, characterized in that, In the position calibration step, the laser tracker calibration process calculates the real-time spatial coordinates of the component by accurately measuring the reflection angle and round-trip time of the laser beam. When the system detects that the position deviation exceeds the preset threshold, the manufacturing execution system automatically adjusts the operating parameters of the relevant assembly equipment or directly sends position correction commands to the six-axis industrial robot or AGV lifting vehicle, forming a closed-loop control loop.

5. The integrated intelligent assembly method for interior roof panels according to claim 1, characterized in that, In the robot assembly process, when the six-axis industrial robot performs the threaded connection process, it identifies the mating position of the bolt and nut through the vision positioning system, uses an intelligent wrench to perform the tightening operation, and monitors and feeds back the torque data to the manufacturing execution system in real time; when performing the riveting process, after the riveting gun completes the riveting operation, it automatically uploads the riveting force parameters and riveting duration parameters to the quality database of the manufacturing execution system.

6. The integrated intelligent assembly method for interior roof panels according to claim 1, characterized in that, In the collaborative positioning step, the collaborative mechanism of the visual positioning system, the 3D vision system, and the laser profilometer is specifically manifested as follows: the visual positioning system first performs two-dimensional image acquisition and preliminary positioning of the component to obtain the component's position and rotational attitude in the plane; the 3D vision system performs three-dimensional point cloud reconstruction and feature geometry extraction based on structured light projection or stereo vision principles; the laser profilometer scans the surface of the component to obtain high-precision contour information through laser triangulation; the data from the three sensors are fused and processed in the central processing unit to jointly output precise positioning coordinates in a unified coordinate system, guiding the robot to complete the assembly operation with sub-millimeter precision.

7. The integrated intelligent assembly method for interior roof panels according to claim 1, characterized in that, In the aforementioned full-process control steps, the equipment status monitoring function integrated into the manufacturing execution system collects real-time operating status data of automatic turnover machines, AGV lifting vehicles, six-axis industrial robots, and laser trackers via industrial Ethernet; the assembly progress tracking function achieves real-time control of production progress by setting RFID readers or visual recognition tags at each process node; the quality data acquisition function comprehensively covers bolt tightening torque curves, riveting process parameters, and position calibration records; and the fault early warning and handling function realizes an early warning and automatic handling mechanism for abnormal equipment conditions based on historical data and machine learning algorithms.

8. The integrated intelligent assembly method for interior roof panels according to claim 1, characterized in that, The assembly method adopts a modular design concept, decomposing the top plate into multiple functionally independent assembly modules. Through standardized interfaces, rapid replacement between modules is achieved, significantly reducing the replacement time of a single module and greatly improving the overall assembly efficiency. This method is particularly suitable for the assembly of interior top plates of rail transit vehicles.

9. The integrated intelligent assembly method for interior roof panels according to claim 1, characterized in that, In the robot assembly and collaborative positioning steps, the vision positioning system also undertakes the function of online assembly quality inspection. It uses image recognition algorithms to detect assembly defects such as missing bolts, incorrect labeling, and missing sealing strips in real time, and uploads the inspection results to the manufacturing execution system in real time to ensure the reliability of assembly quality and realize full-process quality control and data traceability from parts to finished products.

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