Control method suitable for workshop production line multi-process mechanical auxiliary device

Abstract

The invention discloses a control method suitable for a workshop production line multi-process mechanical auxiliary device, and belongs to the technical field of intelligent manufacturing workshop multi-dimensional physical matching and dynamic control. Comprising the steps of collecting state parameters of an auxiliary device and a workpiece 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 an abnormal state, and performing abnormal state compensation based on compensation data; a multi-module dynamic compensation instruction is generated for the auxiliary device, and flexible compensation is carried out; the process switching, workpiece fitting and mixed-line production process of the auxiliary device are dynamically reconstructed, and mechanical flexible assembly is completed; rigid-flexible cooperation, physical and mechanical matching and dynamic impact absorption capacity adjustment are carried out on the auxiliary device, and multi-dimensional dynamic matching of the mechanical level is completed; and performing execution effect feedback and adaptive evolution updating on the auxiliary device to complete control of the auxiliary device. According to the method, the physical adaptability of the production line-level assembly process is enhanced.

Description

Technical Field

[0001] The present invention belongs to the technical field of multi-dimensional physical matching and dynamic control of intelligent manufacturing workshops, and specifically relates to a control method suitable for a multi-process mechanized auxiliary device of a workshop production line. Background Art

[0002] With the rapid development of intelligent manufacturing and high-variety and variable-batch production, workshop production lines face multiple challenges such as mixed-line operations, complex rhythm fluctuations, and differences in workpiece assembly shape tolerances. Existing mechanized auxiliary devices are mostly based on fixed fixtures, single-degree-of-freedom support tables, and linear logistics buffer rollers. These rigid or semi-rigid mechanical structures are difficult to adapt to the needs of multi-task switching and workpiece matching under complex working conditions, and are prone to problems such as assembly clamping force mismatch, support instability, and logistics buffer stacking conflicts. Especially in high-beat mixed-line production and multi-task parallel assembly processes, traditional rigid fixtures and single-point support configurations lack dynamic adjustment capabilities and are difficult to adapt to changes in workpiece shape or assembly sequence in a timely manner, resulting in an increase in process matching mismatch rate, and assembly efficiency and product quality are significantly affected.

[0003] Currently, some workshops have deployed sensor arrays and local monitoring systems, but most are limited to single-point clamping force or posture angle monitoring and lack a holistic adaptive flexible matching strategy based on multi-dimensional state perception. Existing mechanized auxiliary devices often lack modular quick-change structures and multi-dimensional flexible buffering capabilities, making it impossible to form a mechanized flexible adaptive network for dynamic matching of multiple processes. Furthermore, without real-time multi-dimensional state feedback and physical compensation capabilities, instantaneous beat impacts and workpiece position drift during the assembly process can easily lead to beat instability, logistics congestion, and even workpiece assembly defects, affecting the efficient and safe operation of the production line.

[0004] Therefore, a mechanized physical control system integrating multi-dimensional modular fixtures, retractable flexible support arms, and multi-channel logistics buffer drums is urgently needed. This system, with real-time multi-source physical state perception, adaptive flexible adjustment, and human-machine collaboration capabilities, can form a highly flexible physical assembly support network for dynamic matching of multiple tasks and processes. This new system can significantly improve the flexible physical adaptability and dynamic safety assurance levels of multi-process workstations under complex dynamic matching and high-speed 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 rigid adaptation, delayed process switching response, and logistics buffer conflicts in traditional auxiliary devices. It proposes a control method for mechanized auxiliary devices for multiple processes on workshop production lines. The method integrates multi-dimensional physical components such as a multi-dimensional modular adjustable clamp unit, a retractable flexible support arm, and a multi-channel logistics buffer drum. By collecting multi-source physical state data such as clamping force, support arm posture angle, logistics buffer speed, and workpiece alignment error in real time, it forms a mechanized flexible control network for dynamic matching of multiple processes. This method is suitable for efficient and rapid adaptation and multi-degree-of-freedom dynamic safety assurance in complex working conditions such as parallel multi-task assembly processes, dynamic rhythm fluctuation matching, and flexible production of multiple products on mixed lines. It significantly enhances the physical adaptability, safety, and 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 applicable to a workshop production line, wherein the auxiliary device includes an auxiliary fixture, a flexible support arm, and a logistics buffer channel roller. The control method includes the following steps:

[0007] S1, collecting state parameters of the auxiliary fixture, the flexible support posture arm, the logistics cache channel roller, and the workpiece, and preprocessing the state parameters to obtain a global physical state data set;

[0008] S2. Dynamically monitor the global physical state data set for abnormal conditions, calculate compensation data for the abnormal conditions, and compensate for the abnormal conditions based on the compensation data;

[0009] S3. generating a multi-module dynamic compensation instruction for the auxiliary device, and performing flexible compensation on the auxiliary device based on the multi-module dynamic compensation instruction;

[0010] S4, dynamically reconfiguring the process switching, workpiece cutting and mixed-line production process of the auxiliary device to complete mechanized flexible assembly;

[0011] S5. Performing rigid-flexible coordination, physical-mechanical matching, and dynamic impact absorption capacity adjustment on the auxiliary device to achieve multi-dimensional dynamic matching at the mechanical level;

[0012] S6. Perform execution effect feedback and adaptive evolution update on the auxiliary device to complete the control of the auxiliary device.

[0013] Further preferably, the state parameters include: clamping force, end jaw position drift information, three-dimensional posture vector, roller speed, roller beat offset coefficient and workstation disturbance vector;

[0014] The method of expressing the state parameter includes:

[0015]

[0016] Where, Indicates state parameters; F c Indicates the clamping force; δ grip Indicates the position drift information of the end gripper; θ r represents the three-dimensional posture vector; v buf Indicates the roller speed; buf Indicates the drum beat offset coefficient;

[0017] Assisted by the workstation disturbance vector, we get:

[0018]

[0019] Where, represents the extended multimodal perception vector; T var represents the station disturbance vector;

[0020] The nonlinear fusion operator Φ(·) is used to perform tensor mapping and global reorganization on the extended multimodal perception vector to obtain a multidimensional physical state vector:

[0021]

[0022] The global physical state data set includes a multi-dimensional physical state vector and a workpiece matching residual error;

[0023] The workpiece matching residual error includes:

[0024] ε align =|ptarget-pactual|,

[0025] Where, ε align Represents the residual error of workpiece matching; ptarget represents the target pose of the workpiece; pactual represents the actual assembly pose.

[0026] Further preferably, the clamping force and the end jaw position drift information are coupled and dynamically monitored, and when the clamping force fluctuation exceeds the upper and lower tolerance ranges, the auxiliary clamp is adaptively compensated:

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

[0028] Where, f CNN () represents a multi-layer convolutional neural network; e align represents the contact force distribution and friction change during the workpiece assembly process; Δq represents the six-degree-of-freedom deviation vector for real-time monitoring of the workpiece posture; θ assistIndicates the attitude assistance response of the support arm to the assembly working condition;

[0029] The flexible support posture arm determines whether the posture deviation needs to be corrected through the dynamic change rate, and the dynamic change rate includes:

[0030]

[0031] Where Δt represents the time variation;

[0032] Methods for angle correction include:

[0033]

[0034] Where θ0 is the assembly reference angle, α is the flexible matching coefficient, ω is the beat disturbance frequency, and t is the current sampling time; S dyn represents the dynamic rhythm disturbance of the process; C space Represents assembly space constraints; K arm Represents the stiffness characteristics of the support arm mechanism;

[0035] The logistics buffer drum module performs adaptive adjustment based on the transient impedance characteristics of the drum:

[0036]

[0037] Where, v ref is the reference speed of the roller; load is the current cache queue phase difference; sync represents the beat synchronization coefficient; σ buf represents the roller flexible inertia compensation factor; ρ dyn Indicates drum load bulk density.

[0038] Further preferably, S5 includes:

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

[0040]

[0041] Where, ΔF c Indicates the clamping force adjustment amount; Indicates the target's blessing force; F c Indicates the clamping force;

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

[0043]

[0044] Where k comp represents the mechanical pair microflexibility modulus;

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

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

[0047] Where θ ref is the base angle of the support arm; flex is the flexible adaptation coefficient; r align is the transient matching degree of the workpiece;

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

[0049]

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

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

[0052] The displacement sensor of the flexible secondary end is used to measure the dynamic end angle residual of the flexible support posture arm;

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

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

[0055] After each cycle, the correction coefficients of 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] Where Nwear Indicates the number of cycles at which signs of contact pair fretting or wear occur; N total Indicates the total number of cycles;

[0059] The comprehensive performance gain rate is used to quantify the dynamic evolution effect of the cyclic task:

[0060]

[0061] Where, and They represent the comprehensive mechanization performance evaluation functions of the i-th cycle working condition.

[0062] Compared with the prior art, the present invention has the following beneficial effects:

[0063] 1. This invention utilizes 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 of multiple processes. Compared to existing rigid auxiliary devices, this system not only supports real-time workpiece adaptation and differentiated beat adjustment, but also enables fast and flexible matching during high-beat process switching and complex assembly beat fluctuations. This flexible matching capability enables the system to efficiently adapt to complex working conditions such as multi-task mixed lines, dynamic beat changes, and workpiece shape differences, significantly improving the safety of assembly coordination between workstations and the level of process-level flexibility.

[0064] 2. The present invention is based on multi-dimensional sensing data and multi-modal physical feedback, integrating adaptive nonlinear mapping and multi-dimensional convolution feature extraction to form a multi-modal adaptive compensation strategy that supports multi-process scenarios. Through dynamic perception of workpiece insertion posture errors, cache queue stacking status, and fixture clamping force micro-deviations, the system can output multi-dimensional compensation actions at the millisecond level, including fixture fine-tuning force, support arm posture dynamic adjustment, and cache roller flexible response speed. Compared to traditional devices that can only perform single-dimensional fine-tuning, the present invention can achieve comprehensive real-time compensation of multi-process assembly conditions under the combined dynamic influence of process disturbances, beat impacts, and workpiece deviations, thereby enhancing the stability and matching accuracy of multi-process collaboration.

[0065] 3. The present invention adopts a magnetic-assisted quick-release mechanism and a high-strength flexible limit mechanism in the modular interface design, combined with a visual multi-dimensional human-computer interaction panel and an adaptive learning mechanism of the resume database. The system not only supports modular replacement and fast process switching in seconds, but also can convert the resume R hist Intelligent comparison and analysis with physical state data sets enables self-learning and updating of auxiliary actions. This closed-loop optimized human-machine collaboration system effectively supports high-frequency mixed-line production and variable beat interference in intelligent manufacturing scenarios, significantly improving the workshop's safety matching capabilities, flexible response speed, and full-process intelligent upgrade capabilities under actual dynamic working conditions. BRIEF DESCRIPTION OF THE DRAWINGS

[0066] In order to more clearly illustrate the technical solution of the present invention, the following briefly introduces the drawings required for use in the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0067] Figure 1 The present invention is a flowchart of a control method for a multi-process mechanized auxiliary device for a workshop production line according to an embodiment of the present invention. DETAILED DESCRIPTION

[0068] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0069] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the present invention is 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 applicable to a workshop production line, 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 state parameters of the auxiliary fixture, the flexible support arm, the logistics buffer channel roller, and the workpiece, and preprocess these state parameters to obtain a global physical state dataset. The state parameters include: clamping force, end jaw position drift information, three-dimensional posture vector, roller speed, roller beat offset coefficient, and workstation disturbance vector.

[0073] In a multi-process dynamic assembly workshop, workpiece assembly sequences are complex, cycle times change frequently, and workpiece geometry and form / position tolerances are highly dispersed. To achieve flexible matching between processes and dynamic workpiece compensation, a multimodal, multidimensional perception network must be built at the physical level to provide high-resolution physical status monitoring of each auxiliary device.

[0074] In the auxiliary fixture part, an integrated dynamic mechanical sensor and a micro-displacement sensor are used to collect the clamping force F c (used to monitor the real-time force of workpiece clamping) and end clamp position drift information δ grip, so that the system can sense the tiny assembly force fluctuations between the auxiliary fixture and the workpiece. The flexible support posture arm uses multi-axis posture solution and spatial inertia measurement to form a three-dimensional posture vector θ r (including parameters such as pitch angle, yaw angle and roll angle, used to dynamically sense the posture changes of the support arm in multiple processes), monitor the changes in the angle and moment of inertia of the end of the flexible support posture arm with high time resolution, and enhance the dynamic response capability of the flexible support characteristics of the flexible support posture arm. buf Based on the monitoring, the drum beat offset coefficient χ is introduced buf , characterizing the transient logistics cache queue pressure and beat impact response.

[0075] In order to adapt to the complex working condition fluctuations of multi-dimensional states, dynamic filtering and normalization algorithms are used to eliminate high-frequency noise interference and the problem of asynchronous sensor sampling between workstations. The original multimodal feature set (i.e., state parameters) before physical state vector fusion is:

[0076]

[0077] Assisted by the workstation disturbance vector T var (covering external working conditions such as temperature, shock, humidity, and workshop vibration), forming an extended multimodal perception vector:

[0078]

[0079] All vectors are tensor-mapped and globally reshaped through the nonlinear feature fusion operator Φ(·) to obtain the multidimensional physical state vector X:

[0080]

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

[0082] The workpiece target pose ptarget and the actual assembly pose pactual are jointly solved by the workstation-level vision and force sensing coupling module to generate the workpiece matching residual error in real time:

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

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

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

[0086] S2. Dynamically monitor the global physical state data set for abnormal conditions, calculate compensation data for the abnormal conditions, and compensate for the abnormal conditions based on the compensation data.

[0087] In complex workshop environments characterized by dynamic multi-process 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. To address the high dynamic fluctuations of mechanized devices such as auxiliary fixtures, flexible support arms, and logistics buffer channel rollers, this embodiment, based on the fusion of physical states in the S1 phase, proposes a full-process dynamic monitoring and anomaly detection mechanism centered on mechanized physical characteristics, ensuring physical safety and dynamic response during multi-process collaborative assembly.

[0088] First, at the monitoring level of the auxiliary fixture, not only the clamping force F is obtained in real time c (t), and also captures the small deformation of the fixture during the assembly process δ grip (t), high-precision capture is achieved by multi-point displacement sensors. During the clamping action of the auxiliary fixture, transient beat disturbances or workpiece tolerance differences may cause short-term fluctuations in the clamping force (clamping force), which are difficult to be captured in time by traditional static monitoring. c (t) and δ grip (t) The coupling dynamic monitoring is formed, which can accurately judge the force change trend and the flexible deformation of the clamping jaws during the clamping process, and dynamically distinguish between normal flexible adaptation and potential mismatch hazards. If the clamping force fluctuation of the auxiliary clamp is detected to exceed the upper and lower tolerance range Adaptive compensation is performed on the auxiliary fixture with millisecond response to prevent workpiece slippage or local deformation of the fixture, thus protecting assembly quality.

[0089] Methods for performing adaptive compensation include:

[0090] Introducing multimodal convolutional fusion neural network to e align , Δq and θ assist Perform feature extraction and multi-dimensional coupling, the expression is:

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

[0092] Where, f CNN() represents a multi-layer convolutional neural network with perception convolution kernels of different scales, which can quickly converge the auxiliary fixture clamping force F under the impact of multiple process beats. c ;e align represents the contact force distribution and friction change during the workpiece assembly process; Δq represents the six-degree-of-freedom deviation vector for real-time monitoring of the workpiece posture; θ assist Indicates the posture assistance response of the support arm to the assembly working condition.

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

[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, rhythmic impact, or insufficient flexibility of the support arm mechanical structure. In this case, the end-cushion rotary pair and linear fine-tuning module work together to dynamically correct posture deviations and maintain assembly safety within the flexible support arm's range.

[0096] The flexible support arm adopts a multi-degree-of-freedom multi-point rigid-flexible coupling hinge structure for flexible posture adjustment, and has the ability to fine-tune the posture based on multi-dimensional posture and beat state feedback. The real-time fine-tuning range of its flexible angle is determined by the dynamic beat disturbance S of the process. dyn , assembly space constraint C space And the stiffness characteristic K of the support arm mechanism arm The expression for jointly determining and dynamically correcting the posture deviation is:

[0097]

[0098] Where θ0 is the assembly reference angle, α is the flexibility matching coefficient, ω is the beat disturbance 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 posture fine-tuning under high beat fluctuations and multi-process differences.

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

[0100]

[0101] wherein, v ref is the reference speed of the drum, φ load is the current buffer queue phase difference, the drum can automatically suppress the accumulation fluctuation under the dynamic fluctuation of the beat, realize the two-way optimization of beat cooperation and flexible buffer adjustment.

[0102] To strengthen the matching accuracy of multiple processes, the workpiece matching residual error ε align (t) is continuously monitored. Dynamic monitoring of workpiece matching residual error can quickly identify insufficient workpiece alignment accuracy under different assembly beat conditions, especially during multi-task mixed line assembly switching stage, transient alignment mismatch is more likely to occur. If the error exceeds the process tolerance δ align , immediately start the multi-dimensional physical flexible compensation mode, generate an instruction vector containing 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 buffer rate of the logistics buffer channel drum; The instruction vector is issued in real time to the actuators of each mechanized auxiliary device through the edge intelligent control node, forming an efficient dynamic flexible matching network, eliminating transient assembly mismatch hazards.

[0103] Based on the monitoring results of multi-dimensional dynamic state, a workshop-level central visual interface is also integrated. Operators can intuitively master the change trend and transient risk points of each physical state through multi-dimensional trend curves, dynamic fluctuation graphs and real-time alarm markers. And support multi-level comparison of multi-dimensional state curves, operators can quickly switch perspectives to observe the real-time dynamic evolution of auxiliary fixtures, flexible support posture arms and logistics buffer channel drums and other devices. If the operator finds that the residual micro-deviation after the system automatic compensation is still in the critical range, the operator can manually adjust the target clamping force of the auxiliary fixture Flexible fine-tuning angle of flexible support posture arm And the rate of logistics buffer channel drum Realize personalized matching under man-machine cooperation.

[0104] All dynamic monitoring data, alarm records and operator intervention actions will be written into the history database R hist , as an important reference for subsequent dynamic flexible compensation model self-learning and multi-process dynamic matching strategy optimization. Through S2 step, the comprehensive coverage from micro dynamic fluctuation monitoring, transient anomaly sensitive detection to whole-process safety compensation is realized in the mechanized auxiliary control network, ensuring high flexible physical adaptation and safety guarantee in the multi-process dynamic matching scene.

[0105] S3, generating a multi-module dynamic compensation instruction for the auxiliary device, and flexibly compensating the auxiliary device based on the multi-module dynamic compensation instruction.

[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 faced with complex working conditions such as sudden changes in assembly rhythm, differentiated workpiece shapes and tolerances, and multi-task mixed-line switching. Building on the aforementioned multi-dimensional dynamic monitoring and multi-level anomaly detection, this step focuses on the generation of multi-module dynamic compensation instructions and the continuous adaptive execution of flexible actions in the mechanized network, building a high-precision, high-resilience matching system for multi-process flexible assembly.

[0107] Specifically, for the auxiliary clamp, combined with the dynamic clamping force F c (t) and small deformation δ grip (t) not only considers the safety threshold of the workpiece force during assembly, but also evaluates the multi-point micro-response of the local deformation of the clamp. By arranging a multimodal sensor at the end of the auxiliary clamp, the force distribution non-uniformity of the contact interface between the clamp and the workpiece is dynamically tracked to form a multi-dimensional dynamic force map. This data is used to generate a small and continuous clamp flexibility fine-tuning instruction ΔF c , multiple fine-tuning is performed in a short cycle to ensure that the auxiliary fixture always maintains the security of workpiece clamping and local matching accuracy under the impact of process rhythm and micro-tolerance fluctuations of workpiece.

[0108] In the flexible support posture arm part, the multi-degree-of-freedom posture solution is combined with the workpiece matching residual error ε align (t) is combined to establish a multi-level dynamic matching compensation logic. The flexible support posture arm not only performs terminal angle fine-tuning, but also, through a modular and retractable structure, implements a local linear flexible buffer zone to dynamically match the transient impact absorption of workpiece insertion. In particular, in the case of transient assembly misalignment caused by beat fluctuations, multi-degree-of-freedom compound compensation actions can be implemented within the flexible support posture arm, including small-angle rotation adjustment, micro-linear scaling, and flexible energy absorption at the terminal end, forming a distributed, flexible multimodal support network to ensure the dynamic collaborative stability of complex assembly nodes.

[0109] In terms of the logistics buffer channel roller, not only the stacking load coefficient ρ buf (t) Generate cache rate v buf The multi-segment distributed control within the roller module flexibly adjusts transient rate differences between roller segments to prevent fluctuations in accumulation pressure during rapid cycle switching. This creates a transient cycle buffer within the local buffer segment, ensuring precise matching of logistics cycles between downstream and upstream processes, avoiding accumulation backflow or assembly cycle mismatches caused by transient shocks.

[0110] To achieve integrated coordination of multi-module flexible actions, a multi-channel data synchronization control and fusion judgment mechanism is established in the edge intelligent node. The dynamic physical state, compensation instructions, and execution feedback of different modules are aggregated to the central judgment module in real time. The central node generates a comprehensive control instruction package at the workstation level based on the task beat instructions and physical state adaptability:

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

[0112] Where, Station_ID represents the working ID; 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 according to the matching urgency of the current process, giving priority to ensuring the flexible matching execution of key processes while taking into account the rhythmic continuity of the overall workshop beat.

[0114] Furthermore, to address the high variability of multi-task, mixed-line production, the system supports customized flexible parameter presetting during the instruction generation phase. Through a visual human-machine interface, operators can set the fine-tuning sensitivity of the auxiliary fixture's clamping force, the correction range of the flexible support arm's posture, and the buffer width of the roller's buffering beat for different processes and workpiece types, achieving differentiated matching for diverse processes. The operator's fine-tuning input is incorporated into the instruction generation system in real time, forming a dual-layered guarantee strategy of "automatic dynamic compensation + manual differentiated adaptation."

[0115] During command execution, the system dynamically backtracks the physical execution of compensation actions in a continuous millisecond-scale cycle. For minute residual deviations in the gripping force at the auxiliary fixture end, subtle drifts in the angle of the flexible support arm end, and transient drifts in the drum buffer segment rhythm, feedback data triggers micro-amplitude secondary and tertiary compensation, forming a chained closed loop of flexible actions, ensuring the precision, personalization, and safety of all physical compensation actions under dynamic working conditions.

[0116] The operator can monitor the dynamic response trajectory curve of each round of fine-tuning action in real time on the visual interface. The system supports layered visualization of multi-dimensional dynamic data, including the micro-movement trend of the auxiliary clamping force, the fine-tuning curve of the flexible support arm end, and the dynamic adaptation of the drum beat buffer layer. If the operator finds that the physical state of a local process still has a slight mismatch, he can manually input the adjustment command immediately. All manual adjustments and system automatic compensations are written into the history database in real time. hist, supporting the continuous iterative optimization of subsequent multi-process flexible evolution models.

[0117] Through this step, the mechanized auxiliary control network not only achieves multi-level flexible compensation for the three modules—the auxiliary fixture, the flexible support arm, and the logistics buffer channel roller—but also establishes a continuous fine-tuning chain closed loop for the flexible movements of these multiple modules, enhancing the adaptive robustness of the workshop-level multi-process rhythm matching. Next, through the rapid disassembly and replacement of modular structures and the adaptive reconstruction of multiple process tasks, the efficiency and safety assurance capabilities of the workshop-level multi-task flexible response will be further improved.

[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 a high-speed, multi-process, mixed-line production environment, the mechanized auxiliary control network must not only achieve flexible physical matching and dynamic fine-tuning during the process, but also possess flexible and efficient modular rapid reassembly 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 the multi-dimensional flexible mechanized structure at the modular physical layer, signal link layer, and process configuration layer, forming a mechanized flexible assembly support system that can quickly adapt to complex working conditions.

[0120] First, for the auxiliary fixture, an integrated frame based on high-strength and lightweight alloy material is used, with pre-installed multi-station quick-install 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 fixture's 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 rhythm and complex changes in workpiece shape. The clamping jaw module is mechanically coupled through a quick-release positioning cone and a bevel limit pair. A single person can complete the installation or replacement of the module within 2-3 minutes, greatly reducing downtime. The built-in fine-tuning pair of the modular jaws can slightly correct the installation error after replacement, ensuring the consistency and rhythm continuity of repeated assembly processes.

[0121] At the flexible support arm level, a multi-degree-of-freedom retractable arm segment structure is introduced. Multi-dimensional registration pins and linear positioning slots are used to enable rapid splicing and assembly between modular segments. Each support segment has a built-in electric servo adjustment pair. When the operator replaces or adds a support segment, the system automatically calculates 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's end effector utilizes a quick-change flexible rotary joint that allows for rapid switching between adsorption-type, elastic buffering-type, or rigid crimping-type end tools, supporting multi-modal flexible support for 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, integrated with a servo drive and a multi-modal stacking pressure detection unit. The module interface adopts a high-strength docking pair, combined with a multi-core fool-proof electrical quick connector, to achieve single-person replacement and segmented quick disassembly of the roller segments. The operator can flexibly adjust the buffer area length and roller segment combination according to the production plan and logistics rhythm requirements to adapt to the cache rhythm and stacking safety buffer of different task process rhythms. After the change, the roller segment status parameters will be immediately transmitted back to the central control node, realizing real-time mapping of the virtual twin model and the physical buffer area status, ensuring high-precision dynamic adaptation of the rhythm.

[0123] At the mechanical interface level, emphasis is placed on safety and repeatable positioning accuracy for modular rapid assembly. The quick-release latches and quick-release pins are constructed from high-toughness alloy steel for mechanical strength, ensuring a long cycle life and fatigue resistance, enabling them to withstand the high-frequency switching of continuous factory operations. Flexible stoppers and mechanical thrust surfaces absorb transient shocks during assembly, preventing module damage or loss of positioning accuracy due to improper operation.

[0124] At the electrical and signal level, all module interfaces use multi-core quick connectors with a 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 after the module is quickly replaced, and the sensor data and execution instructions are transmitted in real time without delay.

[0125] After the quick module change is complete, a multi-dimensional adaptive safety check is immediately performed. This check includes a self-check of the mechanical sub-assembly position consistency (assisted by a displacement sensor array), verification of the electrical connection integrity (resistance or current loop detection), and a functional test of the module's flexible motion range (end effector test). If any module is detected to be slightly loose, signal disconnected, or substandard after the quick change, the system will highlight an alarm on the central visual interface, allowing the operator to quickly correct the problem based on the instructions, preventing process cycle fluctuations caused by the propagation of minor errors.

[0126] At the process configuration and task reconstruction level, the central control node updates the physical characteristics, end effector configuration, and flexibility range of the new module in real time based on the modular configuration management database. The system not only supports fast reloading of static configurations, but also automatically matches the historical database R according to the switching conditions of multiple processes. hist The optimal flexible matching model in the system enables dynamic matching compensation of workstations during "hot switching." After the replacement, the system synchronizes the multi-dimensional state characteristics of the new module (such as clamping force range, support arm flexibility range, roller buffer inertia, etc.) to the workshop digital twin, automatically completing dynamic verification of workpiece spatial matching in the virtual model.

[0127] The operator can view the self-checking results, dynamic flexible interval and process beat matching state of each module in real time through the central interactive panel during the module quick replacement and multi-task switching. The visual interface supports the 3D view of modular assembly, mechanical state mapping and dynamic compensation trend superposition. The operator can manually input the beat deviation correction coefficient to form a man-machine cooperative dynamic matching adjustment under multi-task process switching.

[0128] Through this step, the mechanical auxiliary device network not only realizes high-strength quick replacement, flexible assembly and multi-state end adaptation at the module level in the physical structure layer, but also builds a digital twin-physical execution bidirectional synchronization of multi-process flexible dynamic reconfiguration at the system level, realizing safe, efficient, visual and intelligent flexible matching in the multi-task multi-process mixed-line assembly scene.

[0129] Next, relying on these modular quick reconstruction results, combined with human-computer interaction and safety monitoring feedback, further efficient flexible control and safety protection in the assembly process will be realized.

[0130] S5, rigid-flexible cooperation, physical and mechanical matching, and dynamic impact absorption capacity adjustment of the auxiliary device are performed to complete multi-dimensional dynamic matching at the mechanical level.

[0131] In the complex assembly scene of multi-process dynamic matching and multi-task mixed-line production, the mechanical auxiliary control device network not only relies on signal feedback, but also highly depends on the physical coupling and dynamic cooperation ability between mechanical multi-modules. This step focuses on the rigid-flexible cooperation, equipment-level physical and mechanical matching, and dynamic impact absorption capacity of mechanical modules, forming a multi-dimensional dynamic matching and safety protection system at the mechanical level.

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

[0133]

[0134] In the formula, represents the target clamping force.

[0135] When ΔF c exceeds the mechanical pair safety tolerance δ F , the multi-layer elastic limit pair will produce a flexible compensation displacement:

[0136]

[0137] Where, k compThe mechanical pair has a micro-flexible modulus to ensure physical safety and transient dynamic absorption during the clamping process. The mechanical pair surface of the auxiliary fixture has been hardened and has excellent wear resistance and fatigue resistance. The mechanical pair cycle life exceeds 10 6 Second, it meets the equipment safety requirements of high-beat switching.

[0138] The flexible support arm adopts a segmented multi-pair combination structure. The end mechanical pair can not only achieve high rigidity support, but also achieve flexible self-adaptation through mechanized end micro-degree of freedom adjustment when matching complex processes. The dynamic angle compensation range of the support arm end is:

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

[0140] Among them, θ ref is the base angle of the support arm, λ flex is the flexible adaptation coefficient, r align The mechanical pair's rotating bearing and buffer ring form a composite rotating pair. The support arm can mechanically absorb small deviations within the range of ±8° under transient insertion fluctuations, forming a multi-dimensional matching action.

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

[0142]

[0143] Among them, v ref is the reference roller speed, λ buf The mechanical buffer at the end of the drum can form a mechanized transient inertia matching, suppressing the impact of logistics accumulation and ensuring the physical synchronization of the upstream and downstream process beats.

[0144] The mechanical joints used in module assembly not only focus on dynamic compensation capabilities but also possess a high degree of mechanical safety margin. The multi-level registration pins and high-precision positioning slots built into the mechanized quick-release joints control the repeatability of the joints to within ±0.03mm, ensuring repeatability even at high-speed switching. The inter-module mechanical joint interfaces utilize a hybrid rigid-flexible design: the bevel joint absorbs the majority of impact, while the flexible joint provides end-stage cushioning. This combination of rigidity and flexibility creates multi-dimensional physical safety redundancy at the equipment level.

[0145] The operator can observe the force distribution trend of the fixture pair, the end-of-arm 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 simultaneously reflect the movement trajectory of the mechanical pair. 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, achieving equipment-level human-machine fusion and physical matching fine-tuning operation.

[0146] The interface provides interactive visual trend curves. match Below the adaptive safety threshold δ safe When the clamping force reaches the target value, the operator can automatically generate graphic and voice warnings to prompt the operator to make flexible intervention in time. Support arm posture fine-tuning range and logistics cache rate Custom input and real-time adjustment, all manual interaction operation records are generated in real time into a resume database R hist , combining the resume database with real-time multi-dimensional physical feedback, continuously and adaptively updating the multi-dimensional flexible matching model parameters, strengthening the dynamic assembly safety guarantee under human-machine collaboration, and is particularly suitable for flexible matching and beat stability in multi-process mixed-line assembly and high-beat fluctuation production scenarios.

[0147] This step not only enables dynamic adaptation of the mechanized auxiliary device network at the perception and signal levels, but also establishes an equipment-level adaptive physical action network between the rigid mechanical subassembly and the flexible end module. The coordinated rigid-flexible mechanical subassembly buffer, modular high-strength mechanical interface, and multi-degree-of-freedom micro-compensation capabilities form the critical physical support system for safe mechanized execution and dynamic rhythm matching in multi-task and multi-process scenarios.

[0148] S6. Perform execution effect feedback and adaptive evolution update 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 dynamically match multi-module mechanical pairs during assembly execution but also provide multi-dimensional feedback and adaptive evolutionary updates of mechanized execution results after the job is completed, ensuring long-term operational reliability and sustained efficiency. This step, from a mechanized perspective, explains the collection of operational feedback at the equipment level, the 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 mechanical matching accuracy of the fixture end. Dynamic end angle residual of the support arm module The displacement sensor at the end of the flexible pair accurately measures the angle of the multi-cycle mechanical pair and the drum buffer module is based on the transient accumulation pressure residual. A physical feedback loop is formed at the mechanical secondary buffer layer at the secondary end of the cache.

[0151] In order 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 are the comprehensive mechanization performance evaluation functions for the i-th cycle working condition, covering multiple physical characteristics such as the rigid pair matching accuracy, the flexible pair dynamic response and the beat synchronization capability. mech The continuous increase in multiple rounds of tasks indicates that the equipment-level mechanized matching system has the ability of continuous evolution and high adaptability.

[0154] The fatigue safety of mechanical pairs is particularly critical in high-beat multi-task cycles. Under the action of cyclic stress, the contact surfaces of the fixture pair and the support arm pair accumulate micro fatigue damage, forming a dynamic wear trend of the contact pair. The fatigue wear coefficient of the mechanical pair is used. For long-term monitoring:

[0155]

[0156] Where N wear N is the number of cycles when fretting or wear of the contact pair occurs. total This indicator allows equipment maintenance personnel to understand the fatigue progress of mechanical pairs in real time and replace or adjust them in advance to prevent assembly mismatches or safety hazards caused by fretting fatigue.

[0157] In terms of equipment adaptive evolution, after each cycle, the flexible pair buffer zone and the mechanical pair contact surface correction coefficient are dynamically updated based on the mechanical pair fatigue detection data. Taking the support arm flexible pair as an example, if it is detected that If the cumulative value is higher than 10%, the system will adjust the flexible adaptation coefficient λ of the support arm pair. flex Dynamic correction:

[0158]

[0159] Among them, κ updateis the evolution adjustment coefficient of the mechanical pair. Dynamic evolution enables the supporting arm pair to maintain optimal flexibility compensation ability in multi-cycle tasks, avoiding mechanical coordination failure caused by contact fatigue accumulation.

[0160] The operator can view the mechanical pair fatigue state curve of each module, the fixture pair clamping residual curve, and the inertia response fluctuation of the buffer roller pair in real time on the mechanical equipment visualization panel. The panel uses column charts, trend curve superimposition, and dynamic numerical indication to help the operator form a human-machine collaborative safety operation at the mechanical level. The operator can manually input the mechanical pair buffer preload value or the roller pair beat buffer sensitivity of the next round of tasks based on dynamic feedback, forming a human-machine joint safety control at the mechanical equipment level.

[0161] At a higher level, the central mechanical maintenance library of the workshop stores the dynamic feedback history, contact surface wear characteristics, and fatigue state curve of each mechanical pair module into the equipment history database R hist . Calling the history database forms the mechanical pair dynamic life curve and maintenance plan, ensuring that the equipment always has high safety margin and dynamic matching ability of rigid-flexible balance in multi-process mixed line mode.

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

[0163] The above-described embodiments are only descriptions of the preferred modes of the present application and do not limit the scope of the present application. Without departing from the design spirit of the present application, various modifications and improvements to the technical solutions of the present application made by those of ordinary skill in the art shall fall within the protection scope determined by the claims of the present application.

Claims

1. A control method for a multi-process mechanized auxiliary device for a workshop production line, the auxiliary device comprising: The auxiliary clamp, the flexible support posture arm and the logistics buffer channel roller are characterized in that the control method includes the following steps: S1, collecting state parameters of the auxiliary fixture, the flexible support posture arm, the logistics cache channel roller, and the workpiece, and preprocessing the state parameters to obtain a global physical state data set; S2. Dynamically monitor the global physical state data set for abnormal conditions, calculate compensation data for the abnormal conditions, and compensate for the abnormal conditions based on the compensation data; S3. generating a multi-module dynamic compensation instruction for the auxiliary device, and performing flexible compensation on the auxiliary device based on the multi-module dynamic compensation instruction; S4, dynamically reconfiguring the process switching, workpiece cutting and mixed-line production process of the auxiliary device to complete mechanized flexible assembly; S5. Performing rigid-flexible coordination, physical-mechanical matching, and dynamic impact absorption capacity adjustment on the auxiliary device to achieve 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.

2. A control method for a multi-process mechanized auxiliary device for a workshop production line according to claim 1, characterized in that: The state parameters include: clamping force, end jaw position drift information, three-dimensional posture vector, roller speed, roller beat offset coefficient and workstation disturbance vector; The method of expressing the state parameter includes: x raw =F c ,d grip ,i r ,v buf ,x buf , Where, χraw represents the state parameter; F c Indicates the clamping force; δ grip Indicates the position drift information of the end gripper; θ r represents the three-dimensional posture vector; v buf Indicates the roller speed; buf Indicates the drum beat offset coefficient; Assisted by the workstation disturbance vector, we get: χext=xraw,T var , Where xext represents the extended multimodal perception vector; T var represents the station disturbance vector; The nonlinear fusion operator Φ(·) is used to perform tensor mapping and global reorganization on the extended multimodal perception vector to obtain a multidimensional physical state vector: X = Φ(xext); The global physical state data set includes a multi-dimensional physical state vector and a workpiece matching residual error; The workpiece matching residual error includes: ε align =|ptarget-pactual|, Where, ε align Represents the residual error of workpiece matching; 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 for a workshop production line according to claim 2 is characterized in that: The clamping force and the end jaw position drift information are coupled and dynamically monitored. When the clamping force fluctuation exceeds the upper and lower tolerance ranges, the auxiliary clamp is adaptively compensated: F c =f CNN (e align ,Δq,θ assist ), Where, f CNN () represents a multi-layer convolutional neural network; e align Indicates the contact force distribution and friction changes during workpiece assembly; Δq represents the six-degree-of-freedom deviation vector of the workpiece posture in real time monitoring; θ assist Indicates the attitude assistance response of the support arm to the assembly working condition; The flexible support posture arm determines whether the posture deviation needs to be corrected through the dynamic change rate, and the dynamic change rate includes: Where Δt represents the time variation; Methods for angle correction include: Where θ0 is the assembly reference angle, α is the flexible matching coefficient, ω is the beat disturbance frequency, and t is the current sampling time; S dyn represents the dynamic rhythm disturbance of the process; C space Represents assembly space constraints; K arm Represents the stiffness characteristics of the support arm mechanism; The logistics buffer drum module performs adaptive adjustment based on the transient impedance characteristics of the drum: Where, v ref is the reference speed of the roller; load is the current cache queue phase difference; sync represents the beat synchronization coefficient; σ buf represents the roller flexible inertia compensation factor; ρ dyn Indicates drum load bulk density.

4. The control method for a multi-process mechanized auxiliary device for 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 affected by the clamping force and the end jaw position drift information. The calculation method of the clamping force adjustment amount includes: Where, ΔF c Indicates the clamping force adjustment amount; Indicates the target's blessing force; F c Indicates the clamping force; When the clamping force adjustment exceeds the safety tolerance of the mechanical pair, the elastic limit pair generates a flexible compensation displacement: Where k comp represents the mechanical pair microflexibility modulus; The mechanical pair at the end of the flexible support posture arm is used for rigid support and flexible degree of freedom adjustment; the dynamic angle compensation range of the end of the flexible support posture arm includes: Dth adj =θ ref ·(1+λ flex ·r align ), Where θ ref is the base angle of the support arm; flex is the flexible adaptation coefficient; r align is the transient matching degree of the workpiece; In the logistics buffer channel drum, the transient accumulation pressure affects the drum speed, and the method for dynamically adjusting the drum speed includes: Where, Indicates the roller speed; v ref Indicates the reference roller speed; buf represents the roller flexibility matching coefficient; ρ buf (t) represents the transient accumulation pressure.

5. The control method for a multi-process mechanized auxiliary device for a workshop production line according to claim 1 is 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 mechanized matching accuracy of the auxiliary fixture end based on the maximum deviation of the mechanical feedback curve of the residual error of the clamping force; The displacement sensor at the end of the flexible pair is used to measure the dynamic end angle residual of the flexible support posture arm to form a multi-cycle mechanical pair angle matching playback; The logistics cache channel roller forms a physical feedback closed loop in the mechanical secondary buffer layer at the cache secondary end through the transient accumulation pressure residual.

6. The control method for a multi-process mechanized auxiliary device for a workshop production line according to claim 1 is characterized in that: The method for adaptive evolution updating of the auxiliary device includes: After each cycle, the correction coefficients of 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: Where N wear Indicates the number of cycles at which signs of contact pair fretting or wear occur; N total Indicates the total number of cycles; The comprehensive performance gain rate is used to quantify the dynamic evolution effect of the cyclic task: Where, and They represent the comprehensive mechanization performance evaluation functions of the i-th cycle working condition.

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