A control method suitable for a multi-process mechanized auxiliary device of a workshop production line

Abstract

The application discloses a control method suitable for a multi-process mechanized auxiliary device of a workshop production line, and belongs to the technical field of intelligent manufacturing workshop multi-dimensional physical matching and dynamic control. The method comprises the following steps: collecting state parameters of the auxiliary device and workpieces to obtain a global physical state data set; performing dynamic abnormal state monitoring on the global physical state data set, performing compensation data calculation on the abnormal state, and performing abnormal state compensation based on the compensation data; generating a multi-module dynamic compensation instruction for the auxiliary device to perform flexible compensation; dynamically reconstructing process switching, workpiece cutting and mixed production processes of the auxiliary device to complete mechanized flexible assembly; performing rigid-flexible cooperation, physical mechanics matching and dynamic impact absorption capacity adjustment on the auxiliary device to complete multi-dimensional dynamic matching at the mechanical level; and performing execution effect feedback and self-adaptive evolution update on the auxiliary device to complete control of the auxiliary device. The application strengthens the physical adaptability of the production line level assembly process.

Description

Technical Field

[0001] This invention belongs to the field of multi-dimensional physical matching and dynamic control technology in intelligent manufacturing workshops, specifically relating to a control method for multi-process mechanized auxiliary devices in workshop production lines. Background Technology

[0002] With the rapid development of intelligent manufacturing and multi-variety, variable-batch production, workshop production lines face multiple challenges, including mixed-process production, complex cycle time fluctuations, and differences in workpiece assembly shape tolerances. Existing mechanized auxiliary devices are mostly based on fixed fixtures, single-degree-of-freedom support platforms, and linear material buffer rollers. These rigid or semi-rigid mechanical structures are ill-suited to adapting to complex multi-task switching and workpiece matching requirements, easily leading to problems such as assembly clamping force mismatch, unstable support, and material buffer stacking conflicts. Especially in high-cycle mixed-process production and multi-task parallel assembly, traditional rigid fixtures and single-point support configurations lack dynamic adjustment capabilities, making it difficult to adapt to changes in workpiece shape or assembly sequence in a timely manner. This results in increased process mismatch rates, significantly impacting assembly efficiency and product quality.

[0003] While some workshops have deployed sensor arrays and local monitoring systems, most are limited to monitoring single-point clamping force or attitude angles, lacking an overall adaptive flexible matching strategy based on multi-dimensional state perception. Existing mechanized auxiliary devices typically lack modular, quick-change structures and multi-dimensional flexible buffering capabilities, making it impossible to form a mechanized flexible adaptive network under multi-process dynamic matching. Furthermore, instantaneous cycle time impacts and workpiece position drift during assembly, without real-time multi-dimensional state feedback and physical compensation capabilities, can easily cause cycle time instability, material flow blockages, and even workpiece assembly defects, affecting the efficient and safe operation of the production line.

[0004] Therefore, there is an urgent need for a mechanized physical control system that integrates multi-dimensional modular fixtures, retractable flexible support arms, and multi-channel logistics buffer rollers. This system should possess real-time perception of multi-source physical states, adaptive flexible adjustment, and human-machine collaborative support functions, forming a highly flexible physical assembly support network under dynamic matching of multiple tasks and processes. This novel system can significantly improve the flexible physical adaptability and dynamic safety assurance level of multi-process workstations under complex process dynamic matching and high-cycle mixed-line production, supporting the high-quality and high-efficiency development of intelligent manufacturing production lines. Summary of the Invention

[0005] This invention aims to address the problems of insufficient rigidity adaptation, delayed response during process switching, and material buffer conflicts in traditional auxiliary devices. It proposes a control method for multi-process mechanized auxiliary devices in workshop production lines, integrating multi-dimensional modular adjustable clamping units, retractable flexible support arms, and multi-channel material buffer rollers. By real-time acquisition of multi-source physical state data such as clamping force, support arm posture angle, material buffer speed, and workpiece alignment error, a multi-process dynamically matched mechanized flexible control network is formed. This method is suitable for highly efficient and rapid adaptation and multi-degree-of-freedom dynamic safety assurance in complex operating scenarios such as parallel multi-task assembly processes, dynamic fluctuation matching of cycle time, and flexible production lines with mixed product types, significantly enhancing the physical adaptability and safety stability of production line-level assembly processes.

[0006] To achieve the above objectives, the present invention provides the following solution: a control method for a multi-process mechanized auxiliary device suitable for workshop production lines, the auxiliary device comprising: an auxiliary clamp, a flexible support posture arm, and a logistics buffer channel roller, the control method comprising the following steps:

[0007] S1. Collect the state parameters of the auxiliary fixture, the flexible support posture arm, the logistics buffer channel roller and the workpiece, and preprocess the state parameters to obtain a global physical state dataset.

[0008] S2. Perform dynamic abnormal state monitoring on the global physical state dataset, calculate compensation data for the abnormal state, and perform abnormal state compensation based on the compensation data.

[0009] S3. Generate multi-module dynamic compensation instructions for the auxiliary device, and perform flexible compensation on the auxiliary device based on the multi-module dynamic compensation instructions;

[0010] S4. Dynamically reconstruct the process switching, workpiece cutting, and mixed-line production process of the auxiliary device to complete mechanized flexible assembly.

[0011] S5. Adjust the auxiliary device by performing rigid-flexible cooperation, physical-mechanical matching and dynamic impact absorption capacity to complete multi-dimensional dynamic matching at the mechanical level.

[0012] S6. Perform performance feedback and adaptive evolution updates on the auxiliary device to complete the control of the auxiliary device.

[0013] More preferably, the state parameters include: clamping force, end gripper position drift information, three-dimensional attitude vector, roller speed, roller cycle offset coefficient, and workstation disturbance vector;

[0014] The methods for representing the state parameters include:

[0015]

[0016] In the formula, Represents the state parameter; F c Indicates clamping force; δ grip Indicates the position drift information of the end gripper; θ r Represents a three-dimensional attitude vector; v buf Indicates the drum speed; χ buf Indicates the drum cycle offset coefficient;

[0017] Using the aforementioned workstation disturbance vector, we obtain:

[0018]

[0019] In the formula, T represents the extended multimodal sensing vector; var Represents the workstation disturbance vector;

[0020] The extended multimodal sensing vector is subjected to tensor mapping and global renormalization using the nonlinear fusion operator Φ(·) to obtain a multidimensional physical state vector:

[0021]

[0022] The global physical state dataset includes a multidimensional physical state vector and workpiece mating residual error;

[0023] The residual error in the workpiece fit includes:

[0024] ε align =|ptarget-pactual|,

[0025] In the formula, ε align This represents the residual error in workpiece fit; ptarget represents the target pose of the workpiece; pactual represents the actual assembly pose.

[0026] More preferably, the clamping force and the position drift information of the end gripper are coupled and dynamically monitored. When the clamping force fluctuation exceeds the upper and lower tolerance range, the auxiliary fixture performs adaptive compensation.

[0027] F c =f CNN (e align ,Δq,θ assist ),

[0028] In the formula, f CNN () represents a multi-layer convolutional neural network; e align The contact force distribution and friction changes during workpiece assembly are represented; Δq represents the six-degree-of-freedom deviation vector of the workpiece attitude monitored in real time; θ assistThis indicates the attitude assistance response of the support arm to assembly conditions;

[0029] The flexible support posture arm determines whether posture deviation needs to be corrected based on a dynamic rate of change, which includes:

[0030]

[0031] In the formula, Δt represents the change over time;

[0032] Methods for angle correction include:

[0033]

[0034] In the formula, θ0 is the assembly reference angle, α is the flexible matching coefficient, ω is the cycle disturbance frequency, and t is the current sampling time; S dyn Indicates the dynamic cycle time disturbance of the process; C space Indicates assembly space constraints; K arm This indicates the stiffness characteristics of the support arm mechanism;

[0035] The logistics buffer roller module adaptively adjusts based on the transient impedance characteristics of the roller:

[0036]

[0037] In the formula, v ref For the reference speed of the roller; φ load ζ represents the current phase difference of the cache queue. sync σ represents the beat synchronization coefficient; buf ρ represents the roller's flexible inertia compensation factor. dyn This indicates the drum load packing density.

[0038] More preferably, S5 includes:

[0039] In the auxiliary clamp, the physical matching degree of the clamping action is jointly affected by the clamping force and the end effector position drift information. The calculation method for the clamping force adjustment includes:

[0040]

[0041] In the formula, ΔF c Indicates the amount of clamping force adjustment; Indicates the target's support force; F c Indicates clamping force;

[0042] When the clamping force adjustment exceeds the safety tolerance of the mechanical pair, the elastic limiting pair generates a flexible compensation displacement:

[0043]

[0044] In the formula, k comp Indicates the minute flexible modulus of the mechanical pair;

[0045] The end effector of the flexible support posture arm is used for rigid support and flexible degree of freedom adjustment; the end effector dynamic angle compensation range of the flexible support posture arm includes:

[0046] Δθ adj =θ ref ·(1+λ flex ·r align ),

[0047] In the formula, θ ref λ is the reference angle for the support arm. flex r is the flexible adaptation coefficient. align For the transient matching degree of the workpiece;

[0048] In the logistics buffer channel roller, transient accumulation pressure affects the roller speed, and the method for dynamically adjusting the roller speed includes:

[0049]

[0050] In the formula, Indicates the roller speed; v ref Indicates the reference roller speed; λ buf Represents the roller flexibility matching coefficient; ρ buf (t) represents the transient accumulation pressure.

[0051] More preferably, in S6, after the operation is completed, the auxiliary fixture first records the residual error of the end clamping force, and evaluates the accuracy of the end-mechanical matching of the auxiliary fixture based on the maximum deviation of the mechanical feedback curve of the residual clamping force error.

[0052] The dynamic end angle residual of the flexible support posture arm is measured using a displacement sensor at the end of the flexible sub-arm.

[0053] The logistics buffer channel roller forms a physical feedback closed loop at the mechanical buffer layer at the end of the buffer sub through the transient accumulation pressure residual;

[0054] More preferably, the method for adaptive evolution and updating of the auxiliary device includes:

[0055] After each cycle, the correction coefficients between the flexible pair buffer zone and the mechanical pair contact surface are dynamically updated based on the fatigue wear coefficient of the mechanical pair.

[0056] The fatigue wear coefficient of the mechanical pair includes:

[0057]

[0058] In the formula, Nwear Indicates the number of cycles in which fretting or wear of the contact pair occurs; N total Indicates the total number of loops;

[0059] The dynamic evolution effect of the cyclic task is quantified using the overall performance gain rate:

[0060]

[0061] In the formula, and Let represent the comprehensive performance evaluation function of the mechanization in the i-th cycle of operation.

[0062] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0063] 1. This invention employs a highly integrated combination of multi-dimensional modular fixtures, multi-degree-of-freedom flexible support arms, and multi-channel buffer rollers to construct a reconfigurable physical assembly system for dynamic matching across multiple processes. Compared to existing rigid auxiliary devices, this system not only supports real-time workpiece adaptation and differential cycle time adjustment, but also achieves rapid and flexible matching during high-cycle time process switching and complex assembly cycle time fluctuations. This flexible matching capability enables the system to efficiently adapt to complex working conditions such as multi-task mixed lines, dynamic changes in cycle time, and differences in workpiece shape, significantly improving the safety of assembly coordination between workstations and the level of process-level flexibility.

[0064] 2. This invention, based on multidimensional sensor data and multimodal physical feedback, integrates adaptive nonlinear mapping and multidimensional convolutional feature extraction to form a multimodal adaptive compensation strategy supporting multi-process scenarios. Through dynamic sensing of workpiece insertion posture error, buffer queue stacking status, and micro-deviations in fixture clamping force, the system can output multidimensional compensation actions in milliseconds, including fixture fine-tuning force, dynamic adjustment of support arm posture, and flexible response speed of the buffer roller. Compared to traditional devices that can only perform single-dimensional fine-tuning, this invention can achieve comprehensive real-time compensation for multi-process assembly conditions under the combined dynamic influence of process disturbances, cycle time impacts, and workpiece deviations, enhancing the stability and matching accuracy of multi-process collaboration.

[0065] 3. In its modular interface design, this invention employs a magnetically assisted quick-release mechanism and a high-strength flexible limiting mechanism, combined with a visual multi-dimensional human-computer interaction panel and an adaptive learning mechanism for the resume database. The system not only supports second-level modular replacement and rapid process switching, but also allows for manual intervention in retrieving resume data. hist Intelligent comparison and analysis with physical state datasets enables self-learning updates of auxiliary actions. This closed-loop optimized human-machine collaboration system effectively supports high-frequency mixed-line production and variable cycle time interference in intelligent manufacturing scenarios, significantly improving the workshop's safety matching capability, flexible response speed, and full-process intelligent upgrade capability under actual dynamic working conditions. Attached Figure Description

[0066] To more clearly illustrate the technical solution of the present invention, the drawings used in the embodiments are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0067] Figure 1 This is a schematic diagram of a control method for a multi-process mechanized auxiliary device in a workshop production line, according to an embodiment of the present invention. Detailed Implementation

[0068] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0069] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0070] Example 1:

[0071] like Figure 1 As shown, this embodiment provides a control method for a multi-process mechanized auxiliary device suitable for workshop production lines, wherein the auxiliary device includes: an auxiliary fixture, a flexible support posture arm, and a logistics buffer channel roller; the method includes the following steps:

[0072] S1. Collect the state parameters of the auxiliary fixture, the flexible support posture arm, the logistics buffer channel roller, and the workpiece. Preprocess the state parameters to obtain a global physical state dataset. The state parameters include: clamping force, end effector position drift information, three-dimensional posture vector, roller speed, roller cycle offset coefficient, and workstation disturbance vector.

[0073] In multi-process dynamic assembly workshops, the assembly sequence of workpieces is complex, the cycle time changes frequently, and the geometric and positional tolerances of the workpieces are highly variable. To achieve flexible matching between processes and dynamic compensation of workpieces, it is necessary to first construct a multimodal and multidimensional sensing network at the physical level to form a high-resolution physical state monitoring system for each auxiliary device.

[0074] In the auxiliary clamping part, integrated dynamic force sensors and micro-displacement sensors are used to collect the clamping force F. c (Used to monitor the real-time clamping force of the workpiece) and the end gripper position drift information δ gripThis enables the system to detect minute fluctuations in assembly force between the auxiliary fixture and the workpiece. The flexible support attitude arm employs multi-axis attitude calculation and spatial inertia measurement to form a three-dimensional attitude vector θ. r (Including parameters such as pitch angle, yaw angle, and roll angle, used to dynamically sense the attitude changes of the support arm in multiple processes), monitoring the end-effector angle and moment of inertia changes of the flexible support attitude arm with high temporal resolution, enhancing the dynamic response capability of the flexible support attitude arm's flexible support characteristics. The logistics buffer channel roller operates at a traditional roller speed v. buf Based on monitoring, a drum cycle offset coefficient χ is introduced. buf It depicts the transient logistics buffer queuing pressure and cycle time impact response.

[0075] To adapt to complex operating condition fluctuations in multiple dimensions, dynamic filtering and normalization algorithms are employed to eliminate high-frequency noise interference and address the asynchronous sampling issues between workstations. The original multimodal feature set (i.e., state parameters) before physical state vector fusion is as follows:

[0076]

[0077] Supplemented by workstation disturbance vector T var (Covering external operating conditions such as temperature, shock, humidity, and workshop vibration), forming an extended multimodal sensing vector:

[0078]

[0079] All vectors are subjected to tensor mapping and global renormalization through the nonlinear feature fusion operator Φ(·) to obtain the multidimensional physical state vector X:

[0080]

[0081] Where X represents a multidimensional physical state vector; Φ(·) has a built-in adaptively updatable nonlinear activation network (such as Swish, Mish, etc.), which has high robustness and strong representation ability under multi-process mixed line and multi-task dynamic working conditions.

[0082] The target pose ptarget of the workpiece and the actual assembly pose pctual are jointly calculated by the station-level vision and force sensing coupling module to generate the residual error of workpiece mating in real time.

[0083] ε align =|ptarget-pactual|. (4)

[0084] residual error ε of workpiece fit align Together with the multidimensional physical state vector X, it constitutes the system's global physical state dataset, providing real-time and efficient physical data support for subsequent dynamic flexible compensation and multi-task process matching.

[0085] Thus, in stage S1, the construction of the multi-dimensional physical state perception network and the fusion of high-dimensional features were completed, forming the physical state perception foundation that supports flexible adaptive matching, dynamic beat compensation, and dynamic reconstruction under multiple process conditions.

[0086] S2. Perform dynamic abnormal state monitoring on the global physical state dataset, calculate compensation data for abnormal states, and perform abnormal state compensation based on the compensation data.

[0087] In complex workshop environments involving multi-process dynamic matching and mixed-line assembly, the dynamic state monitoring and multi-dimensional anomaly detection capabilities of the mechanized auxiliary control network directly determine the system's flexible adaptation efficiency and assembly stability. Addressing the high dynamic fluctuation characteristics of mechanized devices such as auxiliary fixtures, flexible support arms, and logistics buffer channel rollers, this embodiment proposes a full-process dynamic monitoring and anomaly detection mechanism centered on mechanized physical characteristics, based on the physical state fusion in stage S1, ensuring physical safety and dynamic response in multi-process collaborative assembly.

[0088] Firstly, at the monitoring level of the auxiliary clamp, not only is the clamping force F acquired in real time... c (t), and also captures the minute deformation δ of the fixture during the assembly process. grip (t), high-precision capture is achieved by displacement sensors arranged at multiple points. During the clamping action of the auxiliary fixture, transient cycle disturbances or workpiece tolerance differences may cause brief fluctuations in the clamping force, which are difficult to capture in time by traditional static monitoring. However, this invention achieves high-precision capture by using F c (t) and δ grip (t) This system forms a coupled dynamic monitoring system, which can accurately determine the force change trend and gripper flexibility deformation during the clamping process, dynamically distinguishing between normal flexible fit and potential mismatch. If the clamping force fluctuation of the auxiliary fixture is detected to exceed the upper and lower tolerance range... The auxiliary fixture is adaptively compensated with a millisecond-level response to prevent workpiece slippage or local deformation of the fixture and protect assembly quality.

[0089] Methods for adaptive compensation include:

[0090] Introducing a multimodal convolutional fusion neural network for e align Δq and θ assist Feature extraction and multidimensional coupling are performed, expressed as follows:

[0091] F c =f CNN (e align ,Δq,θ assist (5)

[0092] In the formula, f CNN() represents a multi-layer convolutional neural network with perceptual convolutional kernels of different scales, capable of rapidly converging under the impact of multiple process cycles, and assisting the clamping force F of the fixture. c ;e align The contact force distribution and friction changes during workpiece assembly are represented; Δq represents the six-degree-of-freedom deviation vector of the workpiece attitude monitored in real time; θ assist This indicates the attitude assistance response of the support arm to assembly conditions.

[0093] Regarding the flexible support posture arm, a multi-dimensional posture solver is used to generate a real-time posture vector θ. r (t), and continuously track the minute attitude drift trend at the end of the flexible support attitude arm. Through a multi-modal sensor combination of a micro gyroscope and an optical rotary encoder, not only is the absolute value of the angle change monitored, but the dynamic rate of change of the transient drift rate is also introduced as a safety criterion, expressed as:

[0094]

[0095] When the transient drift rate exceeds the safe drift threshold This means that transient support instability may occur due to workpiece weight deviation, cycle time impact, or insufficient flexibility of the support arm's mechanical structure. In this case, the attitude deviation is dynamically corrected by the combined action of the end-effector buffer rotary joint and the linear fine-tuning module, maintaining assembly safety within the flexibility range of the flexible support arm.

[0096] The flexible support posture arm employs a multi-degree-of-freedom, multi-point rigid-flexible coupled hinge structure for flexible posture adjustment, possessing adaptive posture fine-tuning capabilities based on multi-dimensional posture and cycle time feedback. Its real-time flexible angle fine-tuning range is determined by the process dynamic cycle time perturbation S. dyn Assembly space constraints C space and the stiffness characteristics K of the support arm mechanism arm The joint decision, the expression for dynamically correcting attitude deviations, is as follows:

[0097]

[0098] Where θ0 is the assembly reference angle, α is the flexibility matching coefficient, ω is the cycle perturbation frequency, and t is the current sampling time. This multi-dimensional matching strategy enables the flexible support posture arm to maintain high flexibility and high response accuracy for attitude fine-tuning under high cycle fluctuations and multi-process differences.

[0099] The logistics buffer roller module adopts an adaptive adjustment strategy based on the transient impedance characteristics of the roller, with the roller speed v... mod The adjustment not only considers the drum load bulk density ρ dyn Furthermore, a beat synchronization coefficient ζ is introduced. sync and roller flexible inertia compensation factor σ buf The calculation formula is as follows:

[0100]

[0101] Among them, v ref For the reference speed of the roller, φ load Based on the current phase difference of the buffer queue, the roller can automatically suppress accumulation fluctuations under dynamic fluctuations in the clock cycle, achieving bidirectional optimization of clock cycle coordination and flexible buffer adjustment.

[0102] To enhance the matching accuracy of multiple processes, the residual error ε of workpiece fit is continuously monitored. align (t) Dynamic monitoring of residual errors in workpiece fit can quickly identify insufficient workpiece alignment accuracy under different assembly cycle conditions, especially during the switching phase of multi-task mixed-line assembly, where transient alignment misalignment is more likely to occur. If the error exceeds the process tolerance δ align The system instantly activates a multi-dimensional physical flexibility compensation mode, generating a command vector that includes multi-dimensional compensation parameters such as the clamping force of the auxiliary fixture, the flexible posture of the flexible support posture arm, and the logistics buffering rate of the logistics buffer channel roller. This command vector is then sent to the actuators of each mechanized auxiliary device in real time through the edge intelligent control node, forming an efficient dynamic flexible matching network to eliminate the risk of transient assembly mismatch.

[0103] Based on the monitoring results of multi-dimensional dynamic states, a workshop-level central visualization interface is also integrated. Operators can intuitively grasp the changing trends and transient risk points of each physical state through multi-dimensional trend curves, dynamic fluctuation graphs, and real-time alarm markers. It also supports multi-level comparison of multi-dimensional state curves, allowing operators to quickly switch perspectives and observe the real-time dynamic evolution of devices such as auxiliary fixtures, flexible support arms, and logistics buffer channel rollers. If the operator finds that the residual micro-deviation after automatic compensation by the system is still within the critical range, they can manually adjust the target clamping force of the auxiliary fixture. Flexible support posture arm with flexible micro-adjustment angle and logistics buffer channel roller rate To achieve personalized matching through human-machine collaboration.

[0104] All dynamic monitoring data, alarm records, and operator intervention actions will be uniformly written into the history database. hist This serves as an important reference for subsequent self-learning of the dynamic flexible compensation model and optimization of multi-process dynamic matching strategies. Through step S2, comprehensive coverage from microscopic dynamic fluctuation monitoring and transient anomaly sensitivity detection to full-process safety compensation is achieved in the mechanized assisted control network, ensuring highly flexible physical adaptation and safety assurance in multi-process dynamic matching scenarios.

[0105] S3. Generate multi-module dynamic compensation instructions for the auxiliary device, and perform flexible compensation on the auxiliary device based on the multi-module dynamic compensation instructions.

[0106] Multi-module dynamic adaptive control and process matching action generation: In multi-process dynamic matching and mixed-line production, the mechanized auxiliary device network needs to possess real-time dynamic adaptive control and multi-module linkage compensation capabilities when facing complex working conditions such as sudden changes in assembly cycle time, differences in workpiece shape and tolerance, and multi-task mixed-line switching. Building upon the aforementioned multi-dimensional dynamic monitoring and multi-level anomaly detection, this step focuses on elaborating on the generation of multi-module dynamic compensation commands and the continuous adaptive execution of flexible actions in the mechanized network, constructing a high-precision, high-resilience matching system for multi-process flexible assembly.

[0107] Specifically, for auxiliary clamps, combined with dynamic clamping force F c (t) and the small deformation δ grip (t) not only considers the workpiece's stress safety threshold during assembly but also evaluates the multi-point minute responses to local deformation of the gripper. By arranging multimodal sensors at the end of the auxiliary fixture, the non-uniformity of the stress distribution at the interface between the gripper and the workpiece is dynamically tracked, forming a multi-dimensional dynamic stress map. This data is used to generate minute and continuous fine-tuning commands ΔF for flexible fixture adjustment. c Multiple fine-tunings within a short cycle ensure that the auxiliary fixture maintains the safety of workpiece clamping and the accuracy of local fit under the impact of process cycle and fluctuations in workpiece micro-tolerance.

[0108] In the flexible support posture arm section, the multi-degree-of-freedom posture calculation and the workpiece mating residual error ε are combined. align (t) combined to establish a multi-level dynamic matching compensation logic. The flexible support posture arm not only performs end-angle fine-tuning, but also realizes a linear flexible buffer in a local area through a modular and scalable structure, dynamically matching the transient impact absorption of workpiece insertion. Especially in the transient misalignment of assembly caused by cycle fluctuations, multi-degree-of-freedom composite compensation actions can be realized within the flexible support posture arm, including small-angle rotation adjustment, micro-linear scaling, and end-angle flexible energy absorption, forming a distributed, flexible multimodal support network to ensure the dynamic collaborative stability of complex assembly nodes.

[0109] Regarding the logistics buffer channel rollers, not only is the stacking load factor ρ adjusted in real time... buf (t) Cache generation rate v buf Furthermore, through multi-segment distributed control within the roller module, the transient rate differences between roller segments can be flexibly adjusted to prevent fluctuations in accumulated pressure during rapid cycle switching. A transient cycle buffer is formed in the local buffer segment to ensure precise matching of logistics cycles between downstream and upstream processes, avoiding backflow of accumulated material or mismatch of assembly cycles caused by transient impacts.

[0110] To achieve integrated coordination of flexible actions across multiple modules, a multi-channel data synchronization control and fusion judgment mechanism is established in the edge intelligent nodes. The dynamic physical states, compensation commands, and execution feedback from different modules converge in real time to the central judgment module. Based on task cycle commands and physical state adaptability, the central node generates a workstation-level integrated control command package.

[0111] Instructio={Station_ID, Adjust_Type, Target_ValueSafety_Flag, Priority_Level}, (9)

[0112] In the formula, Station_ID represents the ID during operation; Adjust_Type represents the adjustment type; Target_Value represents the target value; Safety_Flag represents the safety value; and Priority_Level represents the priority level.

[0113] The Priority_Level in the instruction package can be dynamically assigned a value based on the urgency of matching the current process, prioritizing the flexible matching execution of key processes while taking into account the rhythm continuity of the overall workshop.

[0114] Furthermore, to address the highly variable demands of multi-task mixed-line production, personalized flexible parameter presets are supported during the instruction generation stage. Operators can use a visual human-machine interface to fine-tune the sensitivity of the auxiliary fixture's clamping force, the range of flexible support arm posture correction, and the buffer width of the roller buffer cycle for different processes and workpiece types, achieving differentiated matching for diverse processes. The operator's fine-tuning inputs are incorporated into the instruction generation system in real time, forming a dual-layer guarantee strategy of "automatic dynamic compensation + manual differentiated adaptation."

[0115] During instruction execution, the physical execution effect of the compensation action is dynamically reviewed and compensated continuously in millisecond-level cycles. For minor residual deviations in the clamping force at the end of the auxiliary fixture, slight drifts in the angle at the end of the flexible support posture arm, and transient drifts in the cycle time of the roller buffer section, micro-amplitude secondary and tertiary compensations can be triggered based on feedback data, forming a chain-like closed loop of flexible actions to ensure the accuracy, personalization, and safety of all physical compensation actions under dynamic working conditions.

[0116] On the visual interface, operators can monitor the dynamic response trajectory curve of each round of fine-tuning actions in real time. The system supports hierarchical visualization of multi-dimensional dynamic data, including the micro-motion trend of the auxiliary fixture clamping force, the micro-tuning curve of the flexible support posture arm end, and the dynamic adaptation of the roller cycle buffer layer. If the operator finds that there is still a slight mismatch in the physical state of a local process, they can immediately input adjustment commands manually. All manual adjustments and automatic system compensations are written to the history database R in real time. histThis supports the continuous iterative optimization of the subsequent multi-process flexible evolution model.

[0117] Through this step, the mechanized auxiliary control network not only achieved multi-level flexible compensation for the three major modules—auxiliary fixture, flexible support posture arm, and logistics buffer channel roller—but also constructed a continuous fine-tuning chain-like closed loop for the flexible movements of multiple modules, enhancing the adaptive robustness of workshop-level multi-process cycle time matching. The next step will be to further improve the execution efficiency and safety assurance capabilities of workshop-level multi-task flexible response through rapid replacement of modular structures and adaptive reconfiguration of multi-process tasks.

[0118] S4. Dynamically reconstruct the process switching, workpiece cutting, and mixed-line production process of the auxiliary device to complete mechanized flexible assembly.

[0119] In high-paced, multi-process mixed-line production environments, mechanized auxiliary control networks must not only achieve flexible physical matching and dynamic fine-tuning during process transitions, but also possess flexible and efficient modular rapid assembly capabilities and dynamic reconfiguration adaptability during process switching, workpiece switching, and multi-variety mixed-line production. This step focuses on the multi-level dynamic reconstruction of multi-dimensional flexible mechanized structures at the modular physical layer, signal link layer, and process configuration layer, forming a rapidly adaptable mechanized flexible assembly support system for complex working conditions.

[0120] Firstly, for the auxiliary fixtures, an integrated frame based on high-strength, lightweight alloy materials is adopted, with pre-installed multi-station quick-assembly interfaces and multi-dimensional flexible connection slots. Each auxiliary fixture is equipped with a multi-point force sensor array, which can calibrate the distribution characteristics of the clamping force in real time after modular quick-release installation, ensuring that the fixture still has efficient and flexible support and clamping capabilities under sudden fluctuations in assembly cycle and complex changes in workpiece shape. The gripper module achieves mechanical coupling through quick-release positioning cones and inclined limit pairs, allowing a single person to complete module installation or replacement within 2-3 minutes, greatly reducing downtime. The built-in fine-tuning pairs of the modular grippers can slightly correct installation errors after replacement, ensuring consistency and cycle continuity of repetitive assembly processes.

[0121] At the flexible support arm level, a multi-degree-of-freedom telescopic arm structure is introduced. Modular segments are quickly spliced ​​and assembled using multi-dimensional registration pins and linear positioning slots. Each support segment has a built-in electric servo adjustment pair. When the operator replaces or adds support segments, the system can automatically calculate the end effector fine-tuning range based on the process cycle and workpiece assembly space, generating a multi-dimensional adaptation range for the end effector. The support arm end effector uses a quick-change flexible rotary joint, which can quickly switch between adsorption-type, elastic buffer-type, or rigid pressing-type end tools, supporting multi-mode flexible support in multi-process and multi-variety workpiece assembly scenarios.

[0122] The logistics buffer channel rollers adopt a distributed roller segment structure. Each roller buffer segment is an independent module, integrating servo drives and a multi-modal stacking pressure detection unit. The module interface uses high-strength mating pairs, combined with multi-core foolproof electrical quick connectors, enabling single-person installation and quick disassembly of roller segments. Operators can flexibly adjust the buffer zone length and roller segment combination according to production plans and logistics cycle requirements, adapting to the buffering rhythm and stacking safety buffering of different task processes. After installation, the roller segment status parameters are instantly transmitted back to the central control node, realizing real-time mapping between the virtual twin model and the physical buffer zone status, ensuring high precision in dynamic cycle adaptation.

[0123] At the mechanical interface level, emphasis is placed on the safety and repeatability of modular rapid assembly. Quick-release assemblies and quick-release pins utilize high-toughness alloy steel for mechanical strength, possessing high cycle life and fatigue resistance, enabling them to adapt to frequent switching during continuous workshop operations. Flexible limit blocks and mechanical thrust surfaces absorb transient impacts during assembly, preventing module damage or decreased positioning accuracy due to improper operation.

[0124] At the electrical and signal levels, all module interfaces adopt multi-core quick connectors with high sealing protection level (IP67 level and above), which support multi-channel parallel transmission of data bus and power signals, avoiding the problems of complex plugging and unplugging and easy loosening of traditional multi-core plugs, ensuring that the signal link is intact and undamaged after the module is quickly replaced, and that the sensor data and execution commands are transmitted in real time without delay.

[0125] Immediately after the module quick-change is completed, a multi-dimensional adaptive safety check is performed. The check includes self-check of the mechanical pair assembly position consistency (assisted by displacement sensor array), verification of electrical connection integrity (resistance or current loop detection), and functional test of the module's flexible motion range (end-effector trial operation). If any module is found to have slight looseness, signal disconnection, or substandard execution after quick-change, the system will highlight an alarm on the central visualization interface. The operator can quickly correct the issue according to the instructions, preventing process cycle fluctuations caused by the spread of minor errors.

[0126] At the process configuration and task reconfiguration level, the central control node, based on a modular configuration management database, updates the physical characteristics, end effector configuration, and flexibility range of new modules in real time. The system not only supports rapid reloading of static configurations but also automatically matches the historical record database R based on multi-process switching conditions. hist The optimal flexible matching model is used to achieve dynamic matching compensation of workstations under "hot switching". After the change, the system will synchronously update the multi-dimensional state characteristics of the new module (such as clamping force range, support arm flexible range, roller buffer inertia, etc.) to the workshop digital twin, and the virtual model will automatically complete the dynamic verification of workpiece spatial matching.

[0127] During rapid module replacement and multi-task switching, operators can view the real-time status self-inspection results, dynamic flexibility range, and process cycle time matching status of each module through the central interactive panel. The visual interface supports modular assembly 3D views, mechanical state mapping, and dynamic compensation trend overlay. Operators can manually input cycle time deviation correction coefficients to form a human-machine collaborative dynamic matching adjustment under multi-task process switching.

[0128] Through this step, the mechanized auxiliary device network not only achieves high-strength quick replacement, flexible assembly, and multi-mode end-point adaptation at the physical structure level, but also constructs a digital twin-physical execution bidirectional synchronization of multi-process flexible dynamic reconfiguration at the system level, realizing safe, efficient, visualized, and intelligent flexible matching in multi-task and multi-process mixed-line assembly scenarios.

[0129] The next step will be to leverage these modular rapid reconfiguration results, combined with human-computer interaction and safety monitoring feedback, to further achieve efficient and flexible control and safety assurance during the assembly process.

[0130] S5. Adjust the auxiliary device by performing rigid-flexible cooperation, physical-mechanical matching, and dynamic impact absorption capacity to complete multi-dimensional dynamic matching at the mechanical level.

[0131] In complex assembly scenarios involving dynamic matching of multiple processes and mixed-task production lines, the network of mechanized auxiliary control devices not only relies on signal feedback but also heavily depends on the physical coupling and dynamic coordination capabilities between multiple mechanized modules. This step focuses on the rigid-flexible collaboration of mechanized modules, equipment-level physical-mechanical matching, and dynamic impact absorption capabilities, forming a multi-dimensional dynamic matching and safety assurance system at the mechanical level.

[0132] In the auxiliary clamping part, the physical matching degree of the clamping action is affected by the clamping force F of the clamp. c (t) and end clamping displacement δ grip (t) Joint influence. The fine adjustment of the clamping force of the fixture is described by the following formula:

[0133]

[0134] In the formula, It indicates the support or encouragement for the target.

[0135] When ΔF c Exceeding the mechanical pair safety tolerance δ F Multi-layered elastic limiting pairs can generate flexible compensation displacement:

[0136]

[0137] Where, k compThe mechanical pair features a micro-flexible modulus to ensure physical safety and transient dynamic absorption during clamping. The surfaces of the auxiliary fixture's mechanical pairs undergo hardening treatment, exhibiting excellent wear resistance and fatigue resistance, with a cycle life exceeding 10. 6 Secondly, it meets the equipment safety requirements for high-frequency switching.

[0138] The flexible support arm adopts a segmented, multi-pair combined structure. The end effector not only provides high rigidity support but also enables flexible self-adaptation through mechanized micro-degree-of-freedom adjustment during complex process matching. The dynamic angle compensation range at the end of the support arm is:

[0139] Δθ adj =θ ref ·(1+λ flex ·r align (12)

[0140] Where, θ ref λ is the reference angle for the support arm. flex r is the flexible adaptation coefficient. align For transient workpiece matching, the mechanical pair rotary bearing and buffer ring form a composite rotary pair. Under transient insertion fluctuations, the support arm can mechanically absorb minute deviations within a range of ±8°, forming a multi-dimensional matching action of the equipment.

[0141] The logistics buffer channel rollers rely on modular splicing of multi-segment roller units, with mechanical pairs forming a rigid mechanical link through inclined guide grooves and multi-axis plug-in pairs. Each buffer segment has an independent mechanical pair inertia buffer structure, and the transient accumulation pressure ρ... buf (t) directly affects the roller speed Its physical dynamic adjustment formula is:

[0142]

[0143] Among them, v ref λ is the reference roller speed. buf This refers to the roller flexibility matching coefficient. The mechanical buffer pair at the end of the roller can form a mechanized transient inertia matching, suppressing the impact of material accumulation and ensuring the physical synchronization of the upstream and downstream process cycles.

[0144] Mechanical pairs in modular assembly not only focus on dynamic compensation capabilities but also possess high mechanical safety margins. The multi-stage alignment pins and high-precision positioning slots built into the mechanized quick-assembly pairs control the repeatability deviation of the mechanical pairs within ±0.03mm, ensuring repeatability accuracy under high-cycle switching. The rigid-flexible hybrid fit of the mechanical pair interfaces between modules: the inclined pair absorbs most of the impact, while the flexible pair provides end-effector buffering; this combination of rigidity and flexibility forms a multi-dimensional physical safety redundancy at the equipment level.

[0145] The operator can observe the force distribution trend of the clamp pair, the end posture correction of the support arm pair, and the transient rate adjustment curve of the roller pair in real time on the mechanized status indicator panel. The dynamic indicator lights and analog dials on the interface synchronously reflect the motion trajectory of the mechanical pairs. The operator can manually adjust the working range of the flexible pair (such as the compression stroke of the buffer pair or the flexible angle of the rotary pair) on the mechanized operation panel, forming an equipment-level human-machine integrated physical matching fine-tuning operation.

[0146] The interface provides an interactive visualization of trend curves, when η match Below the adaptive safety threshold δ safe In such cases, the system automatically generates graphical and voice alerts to prompt the operator to intervene gently in a timely manner. The interface further supports the operator in setting target values ​​for the clamping force. Support arm posture fine adjustment range and logistics cache rate Custom input and real-time adjustments are enabled, and all human interaction records are generated in real-time into a resume database (R). hist By combining the resume database with real-time multidimensional physical feedback, the parameters of the multidimensional flexible matching model are continuously and adaptively updated to enhance the dynamic assembly safety assurance under human-machine collaboration. It is particularly suitable for flexible matching and cycle stability in multi-process mixed-line assembly and high-cycle-fluctuation production scenarios.

[0147] Through this step, the mechanized auxiliary device network not only achieves dynamic adaptation at the sensing and signal levels, but also establishes an equipment-level adaptive physical motion network between rigid mechanical pairs and flexible end-effector modules. The rigid-flexible collaborative mechanical pair buffer, the modular high-strength mechanical interfaces, and the multi-degree-of-freedom micro-compensation capabilities constitute the key physical support system for safe mechanized execution and dynamic rhythm matching in multi-task and multi-process scenarios.

[0148] S6. Perform performance feedback and adaptive evolution updates on the auxiliary device to complete the control of the auxiliary device.

[0149] In complex workshop scenarios involving multi-process mixed-line production and multi-task switching, the network of mechanized auxiliary devices must not only achieve dynamic matching of multiple modular mechanical pairs during assembly execution, but also generate multi-dimensional feedback and adaptive evolution updates of the mechanized execution effect after the operation is completed, ensuring long-term operational reliability and continuous efficiency. This step, from a mechanization perspective, elaborates on the equipment-level operational effect feedback collection, equipment-level physical adaptive evolution mechanism, and equipment fatigue safety assurance.

[0150] After the operation is completed, the auxiliary fixture first records the residual error of the end clamping force. The maximum deviation of its mechanical feedback curve It is an important indicator for evaluating the accuracy of mechanized matching at the end of the fixture pair. The dynamic end angle residual of the support arm module... Precise measurements are taken using displacement sensors at the ends of the flexible joints to achieve angle matching playback of multi-cycle mechanical joints. The drum buffer module, on the other hand, is based on transient accumulation pressure residuals. A physical feedback loop is formed at the mechanical buffer layer at the end of the buffer.

[0151] To quantify the dynamic evolution effect of mechanized equipment in multiple cyclic tasks, the system introduces the comprehensive performance gain rate of mechanized assembly:

[0152]

[0153] in, and These are the comprehensive mechanical performance evaluation functions for the i-th cycle of operation, encompassing multiple physical characteristics such as the fit accuracy of rigid pairs, the dynamic response of flexible pairs, and the cycle synchronization capability. If η mech The continuous increase in performance across multiple missions demonstrates that the equipment-level mechanized matching system possesses continuous evolution and high adaptability.

[0154] Fatigue safety of mechanical pairs is particularly critical in high-cycle, multi-tasking operations. Under cyclic stress, microscopic fatigue damage accumulates on the contact surfaces of the fixture pair and the support arm pair, leading to a dynamic wear trend. The fatigue wear coefficient of the mechanical pair is used. Conduct long-term monitoring:

[0155]

[0156] In the formula, N wear N is the number of cycles at which fretting or wear of the contact pair occurs. total This represents the total number of cycles. This indicator allows equipment maintenance personnel to monitor the fatigue progress of mechanical components in real time, enabling them to replace or adjust these components in advance and prevent assembly mismatches or safety hazards caused by fretting fatigue.

[0157] Regarding equipment adaptive evolution, after each cycle, the correction coefficients for the buffer zone of the flexible pair and the contact surface of the mechanical pair are dynamically updated based on the fatigue detection data of the mechanical pair. Taking the flexible pair of the support arm as an example, if fatigue detection is detected... When the cumulative value exceeds 10%, the system will adjust the flexibility adaptation coefficient λ of the support arm pair. flex Dynamically corrected to:

[0158]

[0159] Among them, κ updateThis is the mechanical pair evolution adjustment coefficient. Dynamic evolution enables the support arm pair to maintain optimal flexibility compensation capability during multi-cycle tasks, avoiding mechanical failure due to accumulated contact fatigue.

[0160] Operators can view the fatigue state curves of mechanical pairs, the residual clamping curves of fixture pairs, and the inertia response fluctuations of buffer roller pairs in real time on the machine equipment's visualization panel. The panel uses bar charts, overlaid trend curves, and dynamic numerical indicators to help operators achieve collaborative human-machine safety assurance at the mechanization level. Operators can manually input the preload value for the mechanical pair buffers or the cycle buffer sensitivity of the roller pairs for the next task based on dynamic feedback, forming a human-machine joint safety control system at the machine equipment level.

[0161] At a higher level, the central mechanical maintenance warehouse in the workshop stores the dynamic feedback history, contact surface wear characteristics, and fatigue state curves of each mechanical sub-module into the equipment history database R. hist The system utilizes this historical database to generate dynamic life curves and maintenance plans for mechanical pairs, ensuring that the equipment maintains a high safety margin and a dynamic matching capability of rigidity and flexibility even in multi-process mixed-line modes.

[0162] Through this step, the mechanized auxiliary device network not only achieves high adaptability and matching of multiple rigid and flexible pairs in a single execution, but also forms adaptive evolution of the physical state of mechanical pairs and continuous updates of equipment-level safety in multi-task dynamic cycles. This constructs the workshop-level mechanized assembly network with continuous high reliability, flexible adaptability and intelligent flexible self-optimization characteristics under future complex working conditions.

[0163] The embodiments described above are merely preferred embodiments of the present invention and are not intended to limit the scope of the present invention. Various modifications and improvements made to the technical solutions of the present invention by those skilled in the art without departing from the spirit of the present invention should fall within the protection scope defined by the claims of the present invention.

Claims

1. A control method for a multi-process mechanized auxiliary device suitable for workshop production lines, the auxiliary device comprising: The auxiliary clamp, flexible support posture arm, and logistics buffer channel roller are characterized in that the control method includes the following steps: S1. Collect the state parameters of the auxiliary fixture, the flexible support posture arm, the logistics buffer channel roller and the workpiece, and preprocess the state parameters to obtain a global physical state dataset. S2. Perform dynamic abnormal state monitoring on the global physical state dataset, calculate compensation data for the abnormal state, and perform abnormal state compensation based on the compensation data. S3. Generate multi-module dynamic compensation instructions for the auxiliary device, and perform flexible compensation on the auxiliary device based on the multi-module dynamic compensation instructions; S4. Dynamically reconstruct the process switching, workpiece cutting, and mixed-line production process of the auxiliary device to complete mechanized flexible assembly. S5. Adjust the auxiliary device by performing rigid-flexible cooperation, physical-mechanical matching and dynamic impact absorption capacity to complete multi-dimensional dynamic matching at the mechanical level. S6. Perform execution effect feedback and adaptive evolution update on the auxiliary device to complete the control of the auxiliary device; The clamping force and end-gripper position drift information are coupled and dynamically monitored. When the clamping force fluctuation exceeds the upper and lower tolerance range, the auxiliary fixture performs adaptive compensation. ， In the formula, This represents a multi-layer convolutional neural network; This indicates the distribution of contact force and changes in friction during the workpiece assembly process; q represents the six-degree-of-freedom deviation vector of the workpiece attitude monitored in real time; This indicates the attitude assistance response of the support arm to assembly conditions; The flexible support posture arm determines whether posture deviation needs to be corrected based on a dynamic rate of change, which includes: ， In the formula, t represents the change over time; Methods for angle correction include: ， In the formula, The assembly reference angle is α, the flexible matching coefficient is ω, the clock perturbation frequency is ω, and the current sampling time is t. This indicates the dynamic cycle time disturbance of the process; Indicates assembly space constraints; This indicates the stiffness characteristics of the support arm mechanism; The logistics buffer roller module adaptively adjusts based on the transient impedance characteristics of the roller: ， In the formula, This is the reference speed for the rollers; The current phase difference of the cache queue; Indicates the beat synchronization coefficient; This indicates the roller's flexible inertia compensation factor. This indicates the drum load packing density.

2. The control method for a multi-process mechanized auxiliary device in a workshop production line according to claim 1, characterized in that, The state parameters include: clamping force, end gripper position drift information, three-dimensional attitude vector, roller speed, roller cycle offset coefficient, and workstation disturbance vector; The methods for representing the state parameters include: ， In the formula, Indicates state parameters; Indicates clamping force; This indicates the position drift information of the end gripper; Represents a three-dimensional attitude vector; Indicates the roller speed; Indicates the drum cycle offset coefficient; Using the aforementioned workstation disturbance vector, we obtain: ， In the formula, Represents the extended multimodal sensing vector; Represents the workstation disturbance vector; Employing nonlinear fusion operators Tensor mapping and global renormalization are performed on the extended multimodal sensing vector to obtain a multidimensional physical state vector: ； The global physical state dataset includes a multidimensional physical state vector and workpiece mating residual error; The residual error in the workpiece fit includes: ， In the formula, This represents the residual error in workpiece fit; ptarget represents the target pose of the workpiece; pactual represents the actual assembly pose.

3. The control method for a multi-process mechanized auxiliary device in a workshop production line according to claim 1, characterized in that, S5 include: In the auxiliary clamp, the physical matching degree of the clamping action is jointly affected by the clamping force and the end effector position drift information. The calculation method for the clamping force adjustment includes: ， In the formula, Indicates the amount of clamping force adjustment; This indicates the support or encouragement for the target; Indicates clamping force; When the clamping force adjustment exceeds the safety tolerance of the mechanical pair, the elastic limiting pair generates a flexible compensation displacement: ， In the formula, Indicates the minute flexible modulus of the mechanical pair; The end effector of the flexible support posture arm is used for rigid support and flexible degree of freedom adjustment; the end effector dynamic angle compensation range of the flexible support posture arm includes: ， In the formula, This is the reference angle for the support arm; For flexible adaptation coefficient; For the transient matching degree of the workpiece; In the logistics buffer channel roller, transient accumulation pressure affects the roller speed, and the method for dynamically adjusting the roller speed includes: ， In the formula, Indicates the roller speed; Indicates the reference roller speed; Indicates the roller flexibility matching coefficient; This represents transient accumulation pressure.

4. The control method for a multi-process mechanized auxiliary device in a workshop production line according to claim 1, characterized in that, In S6, after the operation is completed, the auxiliary fixture first records the residual error of the end clamping force, and evaluates the accuracy of the end-mechanical matching of the auxiliary fixture based on the maximum deviation of the mechanical feedback curve of the residual clamping force error. The dynamic end angle residual of the flexible support posture arm is measured by a displacement sensor at the end of the flexible pair, forming an angle matching playback of the multi-cycle mechanical pair; The logistics buffer channel roller forms a physical feedback closed loop at the mechanical buffer layer at the end of the buffer sub through the transient accumulation pressure residual.

5. The control method for a multi-process mechanized auxiliary device in a workshop production line according to claim 1, characterized in that, The method for adaptive evolution and updating of the auxiliary device includes: After each cycle, the correction coefficients between the flexible pair buffer zone and the mechanical pair contact surface are dynamically updated based on the fatigue wear coefficient of the mechanical pair. The fatigue wear coefficient of the mechanical pair includes: ， In the formula, N wear Indicates the number of cycles in which fretting or wear of the contact pair occurs; N total Indicates the total number of loops; The dynamic evolution effect of the cyclic task is quantified using the overall performance gain rate: ， In the formula, and Let represent the comprehensive performance evaluation function of the mechanization in the i-th cycle of operation.

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