Automatic cooperative control system for precision component production line

Abstract

This invention relates to the field of power supply control technology in precision manufacturing, and discloses an automated collaborative control system for precision component production lines, comprising: a distributed load response monitoring module, a global dynamic phase reference generation module, and a global power supply frequency collaborative adjustment module. The system collects dynamic data of load energy-consuming nodes in real time to calculate response deviations, generates a dimensionless driving frequency modulation factor based on the maximum deviation, and then performs inverse modulation on the phase accumulation rate of the global dynamic phase reference signal. This invention drives all nodes to proportionally and synchronously reduce their physical operating speed by reducing the time growth rate of the global signal. While maintaining coordinated power supply timing and stable energy flow across the entire line, it achieves dynamic elimination of local dynamic hysteresis without the need for a physical buffer.

Description

Technical Field

[0001] This invention relates to an automated collaborative control system for precision component production lines, belonging to the field of precision manufacturing power supply control technology. Background Technology

[0002] In the automated manufacturing process of modern precision components, with the ever-increasing requirements for production line throughput and assembly accuracy, the distributed collaborative control architecture based on industrial Ethernet has become the industry mainstream. Virtual spindle technology is usually used to establish the timing reference of the entire line. The controller generates a monotonic linear logic phase signal, and each physical execution unit tracks the phase signal in real time through electronic cam curves to achieve logical synchronization of multiple task positions. This control method is stable when handling low-frequency or overall-scale rigid transmission tasks, effectively replacing the rigid connection of traditional mechanical long shafts and realizing flexible parameterized configuration.

[0003] However, when this technology is applied to micro-assemblies with micron-level precision or high-speed conjugate motion scenarios, there is an inherent lag between the ideal linear programming at the logic level and the nonlinear execution response at the physical level, based on electromagnetic physics characteristics. Specifically, after receiving the logic phase command, the servo drive unit needs an integral time to establish an electromagnetic torque sufficient to overcome static friction and load inertia within its internal current loop. This results in the initial phase of the physical action inevitably lagging behind the logic command phase. In traditional production line design, the response lag is often attributed to the physical structure of the transmission components or the limitations of the roller shape at the hardware level, and is overcome by simply optimizing the mechanical structure. In reality, in addition to hardware limitations, existing systems also have shortcomings in software control methods. For example, Chinese invention patent CN212245333U discloses a sheet metal mechanical transmission device that uses a cylinder electromagnet gripper and cylindrical rollers to construct a transmission system. Although it achieves automated material handling, the control logic is completely dependent on... Limited by preset mechanical stroke and rigid triggering of photoelectric switches, the control is essentially a global-scale sequential motion control. Based on fixed-beat open-loop and simple point-to-point control methods, it lacks the ability to perceive the transient physical impedance and dynamic response characteristics of the actuator in real time. When facing high-speed, high-frequency, and multi-node collaborative working conditions, the control system cannot dynamically modulate the overall collaborative beat according to the real-time response deviation of each physical node. As a result, the surface mechanical lag of local workstations cannot be absorbed by the system and evolves into a global phase tracking error. To alleviate this physical lag, existing technologies widely use S-shaped speed planning algorithms to smooth the acceleration and deceleration segments of the command curve. By reducing the jump of the command, mechanical shock is reduced and the following performance is indirectly improved. However, this strategy based on kinematic trajectory smoothing does not address the fundamental mechanism of dynamic response lag. It cannot pre-compensate for the torque build-up delay caused by the inductive effect of the motor windings and the mechanical static friction at the moment the command is issued. Moreover, the over-reliance on high-gain PID parameter tuning is prone to inducing mechanical resonance when the system is running at high frequencies.

[0004] Therefore, the technical problem to be solved by this invention is how to establish a mechanism that can perceive the electromagnetic and mechanical response characteristics at the physical execution level in real time, and achieve precise phase locking between logical instructions and physical actions in the surface time domain through dynamic feedforward compensation and time base modulation mechanisms. Summary of the Invention

[0005] To address the problems mentioned in the background art, the technical solution of the present invention is as follows: An automated collaborative control system for a precision component production line, comprising:

[0006] The distributed load response monitoring module includes multiple drive status acquisition units that are coupled to the input terminals of each load energy consumption node in the production line. These units are used to collect the actual dynamic response data of the corresponding load energy consumption node in real time and calculate the current load response deviation value based on the difference between the actual dynamic response data and the preset ideal dynamic trajectory benchmark.

[0007] The global power phase reference generation module is used to construct and output a global power phase reference signal that governs the power supply timing of all load energy consumption nodes in the entire production line. The global power phase reference signal serves as the sole timing basis for each node in the entire system to acquire driving energy and execute actions.

[0008] The global power supply frequency coordination adjustment module is built in a closed-loop feedback loop between the distributed load response monitoring module and the global dynamic phase reference generation module. The global power supply frequency coordination adjustment module is configured to execute the following control logic: In each control cycle, it collects all load response deviation values ​​output by the distributed load response monitoring module and selects the key load deviation data with the largest modulus value. This key load deviation data represents the state of the node with the tightest dynamic constraints in the current production line. It compares the key load deviation data with the preset system allowable deviation reference and calculates a dimensionless drive frequency modulation factor in real time. It uses the drive frequency modulation factor to inversely modulate the phase accumulation rate of the global dynamic phase reference generation module. When the key load deviation data exceeds the system allowable deviation reference, it reduces the time growth rate of the global dynamic phase reference signal, thereby driving all load energy-consuming nodes to reduce their physical operating speed proportionally and synchronously, so as to eliminate local dynamic hysteresis while maintaining the coordination of the power supply timing and the smooth flow of energy across the entire line.

[0009] Preferably, the global power supply frequency coordinated adjustment module includes: a deviation extreme value locking unit, used to sort all load response deviation values ​​uploaded by the distributed load response monitoring module within a communication cycle by absolute value and lock the maximum deviation source node within the cycle; and a frequency modulation coefficient calculation unit, which has a preset nonlinear mapping rule. The nonlinear mapping rule defines the inverse monotonic relationship between the key load deviation data and the driving frequency modulation factor, so that as the key load deviation data increases, the output value of the driving frequency modulation factor decays nonlinearly within the preset nominal value to zero value range.

[0010] Preferably, the global dynamic phase reference generation module includes: a phase accumulation and synthesis unit, used to receive the drive frequency modulation factor output by the frequency modulation coefficient calculation unit, and multiply the drive frequency modulation factor with a preset basic drive frequency, and then perform time integration on the calculation result to generate a global dynamic phase reference signal; and a multi-node drive distribution interface, which broadcasts the global dynamic phase reference signal to the servo drive actuators of multiple load energy consumption nodes through an industrial fieldbus, and the servo drive actuators use the global dynamic phase reference signal as an independent electronic cam spindle input to control energy output.

[0011] Preferably, the system further includes: a nonlinear load mapping module, which is located between the global dynamic phase reference generation module and the specific load energy consumption node; the nonlinear load mapping module stores multiple preset electronic cam curve tables and is configured to look up the table according to the current value of the global dynamic phase reference signal to obtain the target position command of the corresponding load energy consumption node; the nonlinear load mapping module also includes a micro power compensation unit, which is used to superimpose an S-shaped velocity curve correction component on the target position command for the remaining steady-state position residual based on the steady-state basis of the global power supply frequency collaborative adjustment module to achieve micron-level positioning accuracy correction.

[0012] Preferably, the calculation logic of the driving frequency modulation factor specifically follows the following mathematical relationship: ,in, To drive the frequency modulation factor, The modulus of the key load deviation data. Let α be the system's allowable deviation benchmark, and let α be the preset response sensitivity coefficient. The minimum lower limit is clamped at a preset safety threshold.

[0013] Preferably, the distributed load response monitoring module further includes: a load spectrum feature analysis unit, used to perform real-time frequency domain analysis on load response deviation data and separate characteristic signals of specific frequency bands from the data noise floor; and a drive chain status evaluation unit, used to monitor the amplitude evolution trend of the characteristic signals, and when the amplitude of the characteristic signals at a specific frequency point exceeds a preset electrical wear threshold, generate a preventive maintenance command indicating loosening of the drive chain clearance or increased dry friction, and send the command to the upper management system.

[0014] Preferably, the system further includes: a direct-coupled power supply architecture, wherein two adjacent load power consumption nodes are directly adjacent in physical space and there is no intermediate buffer device; the two adjacent load power consumption nodes are logically elastically connected through a global dynamic phase reference signal. When the load response deviation value of the downstream node increases due to disturbance, the upstream node automatically reduces the feed speed by receiving the slowed-down global dynamic phase reference signal, thereby absorbing the timing deviation between the upstream and downstream without stopping the physical movement.

[0015] Preferably, the global power supply frequency coordinated adjustment module further includes: a load recovery hysteresis control unit, used to control the drive frequency modulation factor to gradually rise back to the nominal value according to a preset acceleration limit after the key load deviation data recovers to below the system allowable deviation reference; and a drive surge suppression filter, connected in series on the output path of the drive frequency modulation factor, used to filter out high-frequency fluctuations of the modulation factor caused by transient jumps in the deviation data, and ensure the continuity of the second derivative of the global power phase reference signal.

[0016] Preferably, the load energy consumption node includes a micro-manipulator drive motor, a dispensing valve actuator, or an optical inspection platform displacement stage for assembling precision components; the actual dynamic response data collected by the distributed load response monitoring module is specifically the encoder feedback value of the servo drive circuit or the position reading of the linear grating ruler; the system allowable deviation benchmark is set to a range of 10μm to 50μm.

[0017] Preferably, the system also includes: an overload fuse protection module for real-time monitoring of the continuous low value of the drive frequency modulation factor; when the duration of the drive frequency modulation factor being lower than the shutdown threshold exceeds a preset safe time window, the overload fuse protection module determines that there is an unhealable physical jamming fault in the production line and sends an emergency stop command to the entire line to cut off the power supply to all load energy-consuming nodes.

[0018] Compared with the prior art, the beneficial effects of the present invention are:

[0019] 1. In the automated collaborative control of precision component production lines, this invention eliminates the dynamic time delay between logic commands and physical responses, ensuring phase locking accuracy under high-frequency collaboration. Unlike traditional technologies that only perform smoothing at the trajectory planning level, this invention introduces a feedforward compensation mechanism based on the current feedback slope in the drive command generation stage. This solves the response lag problem caused by the sudden change in static friction force at the moment of startup of precision actuators. The system can capture the transient rate of change of the drive current in real time and inversely infer the current physical impedance characteristics. Then, it automatically superimposes a pre-excitation current component that can offset the startup inertia into the speed planning command, so that the physical displacement of the processing unit can overcome the interference of mechanical nonlinear factors and achieve zero-order synchronous tracking of the virtual spindle phase signal. This avoids phase overshoot or second-order oscillation caused by physical execution lag in conventional control, ensuring the positional stability of precision components during high-speed handover.

[0020] 2. Establishing an elastic time base mechanism based on global load impedance enhances the continuous operation capability of the production line under extreme conditions. This invention changes the traditional control method where the production line must unconditionally obey the rigid production cycle. It constructs a virtual spindle dynamic modulation logic with physical execution capability as the boundary. By monitoring the position following error of each processing unit in real time, it uses this error as a feedback variable to characterize the physical layer load impedance. This variable is then used to reversely adjust the phase growth rate of the virtual spindle. When it is detected that the following error of any station increases due to lubrication deterioration or load fluctuation, the system will automatically reduce the virtual time base elapse rate of the entire line. This allows the logic cycle to actively adapt to the current capability boundary of the physical entity. Without interrupting production, the local dynamic bottleneck is instantly transformed into a synchronous deceleration adjustment of the entire line. This effectively prevents servo overload alarms or increased mechanical wear caused by forced acceleration, thereby extending the mean time between failures (MTBF) of the equipment.

[0021] 3. Achieving endogenous health perception based on semantic control residuals reduces hardware maintenance costs in clean environments. This invention fully leverages the phase deviation residual data generated during collaborative control. Without adding extra vibration sensors or external monitoring hardware, based on the system's self-diagnostic capability for the sub-health state of mechanical components, the system can extract and statistically analyze the phase correction residuals in the frequency domain. This allows the system to separate characteristic signals representing loose transmission chain gaps or increased dry friction from the data noise. Based on the evolution trend of these signals, the system can automatically adjust production strategies or trigger preventative maintenance prompts. This technical approach of using control loop byproducts for state inversion not only avoids introducing new sources of contamination into precision manufacturing cleanrooms but also achieves transparent management of the chronic physical wear and tear process of equipment, ensuring the controllability of long-term production line operating accuracy. Attached Figure Description

[0022] Figure 1This is a closed-loop feedback logic architecture diagram of the automated collaborative control system of the present invention;

[0023] Figure 2 This is a timing evolution diagram of the signal for the coordinated adjustment of the key load deviation trigger frequency in this invention. Detailed Implementation

[0024] The technical solutions of the embodiments of this application will be clearly described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of this application are within the scope of protection of this application.

[0025] An automated collaborative control system for a precision component production line includes:

[0026] The distributed load response monitoring module includes multiple drive status acquisition units that are coupled to the input terminals of each load energy consumption node in the production line. These units are used to collect the actual dynamic response data of the corresponding load energy consumption node in real time and calculate the current load response deviation value based on the difference between the actual dynamic response data and the preset ideal dynamic trajectory benchmark.

[0027] The global power phase reference generation module is used to construct and output a global power phase reference signal that governs the power supply timing of all load energy consumption nodes in the entire production line. The global power phase reference signal serves as the sole timing basis for each node in the entire system to acquire driving energy and execute actions.

[0028] The global power supply frequency coordination adjustment module is built in a closed-loop feedback loop between the distributed load response monitoring module and the global dynamic phase reference generation module. The global power supply frequency coordination adjustment module is configured to execute the following control logic: In each control cycle, it collects all load response deviation values ​​output by the distributed load response monitoring module and selects the key load deviation data with the largest modulus value. This key load deviation data represents the state of the node with the tightest dynamic constraints in the current production line. It compares the key load deviation data with the preset system allowable deviation reference and calculates a dimensionless drive frequency modulation factor in real time. It uses the drive frequency modulation factor to inversely modulate the phase accumulation rate of the global dynamic phase reference generation module. When the key load deviation data exceeds the system allowable deviation reference, it forcibly reduces the time growth rate of the global dynamic phase reference signal, thereby driving all load energy-consuming nodes to reduce their physical operating speed proportionally and synchronously, so as to eliminate local dynamic hysteresis while maintaining the coordination of the power supply timing and the smooth flow of energy across the entire line.

[0029] Preferably, the global power supply frequency coordinated adjustment module includes: a deviation extreme value locking unit, used to sort all load response deviation values ​​uploaded by the distributed load response monitoring module within a communication cycle by absolute value and lock the maximum deviation source node within the cycle; and a frequency modulation coefficient calculation unit, which has a preset nonlinear mapping rule. The nonlinear mapping rule defines the inverse monotonic relationship between the key load deviation data and the driving frequency modulation factor, so that as the key load deviation data increases, the output value of the driving frequency modulation factor decays nonlinearly within the preset nominal value to zero value range.

[0030] Preferably, the global dynamic phase reference generation module includes: a phase accumulation and synthesis unit, used to receive the drive frequency modulation factor output by the frequency modulation coefficient calculation unit, and multiply the drive frequency modulation factor with a preset basic drive frequency, and then perform time integration on the calculation result to generate a global dynamic phase reference signal; and a multi-node drive distribution interface, which broadcasts the global dynamic phase reference signal to the servo drive actuators of multiple load energy consumption nodes through an industrial fieldbus, and the servo drive actuators use the global dynamic phase reference signal as an independent electronic cam spindle input to control energy output.

[0031] Preferably, the system further includes: a nonlinear load mapping module, which is located between the global dynamic phase reference generation module and the specific load energy consumption node; the nonlinear load mapping module stores multiple preset electronic cam curve tables and is configured to look up the table according to the current value of the global dynamic phase reference signal to obtain the target position command of the corresponding load energy consumption node; the nonlinear load mapping module also includes a micro power compensation unit, which is used to superimpose an S-shaped velocity curve correction component on the target position command for the remaining steady-state position residual based on the steady-state basis of the global power supply frequency collaborative adjustment module to achieve micron-level positioning accuracy correction.

[0032] Preferably, the calculation logic of the driving frequency modulation factor specifically follows the following mathematical relationship: ,in, To drive the frequency modulation factor, The modulus of the key load deviation data. Let α be the system's allowable deviation benchmark, and let α be the preset response sensitivity coefficient. The minimum lower limit is clamped at a preset safety threshold.

[0033] Preferably, the distributed load response monitoring module further includes: a load spectrum feature analysis unit, used to perform real-time frequency domain analysis on load response deviation data and separate characteristic signals of specific frequency bands from the data noise floor; and a drive chain status evaluation unit, used to monitor the amplitude evolution trend of the characteristic signals, and when the amplitude of the characteristic signals at a specific frequency point exceeds a preset electrical wear threshold, generate a preventive maintenance command indicating loosening of the drive chain clearance or increased dry friction, and send the command to the upper management system.

[0034] Preferably, the system further includes: a direct-coupled power supply architecture, wherein two adjacent load power consumption nodes are directly adjacent in physical space and there is no intermediate buffer device; the two adjacent load power consumption nodes are logically elastically connected through a global dynamic phase reference signal. When the load response deviation value of the downstream node increases due to disturbance, the upstream node automatically reduces the feed speed by receiving the slowed-down global dynamic phase reference signal, thereby absorbing the timing deviation between the upstream and downstream without stopping the physical movement.

[0035] Preferably, the global power supply frequency coordinated adjustment module further includes: a load recovery hysteresis control unit, used to control the drive frequency modulation factor to gradually rise back to the nominal value according to a preset acceleration limit after the key load deviation data recovers to below the system allowable deviation reference; and a drive surge suppression filter, connected in series on the output path of the drive frequency modulation factor, used to filter out high-frequency fluctuations of the modulation factor caused by transient jumps in the deviation data, and ensure the continuity of the second derivative of the global power phase reference signal.

[0036] Preferably, the load energy consumption node includes a micro-manipulator drive motor, a dispensing valve actuator, or an optical inspection platform displacement stage for assembling precision components; the actual dynamic response data collected by the distributed load response monitoring module is specifically the encoder feedback value of the servo drive circuit or the position reading of the linear grating ruler; the system allowable deviation benchmark is set to a range of 10μm to 50μm.

[0037] Preferably, the system also includes: an overload fuse protection module for real-time monitoring of the continuous low value of the drive frequency modulation factor; when the duration of the drive frequency modulation factor being lower than the shutdown threshold exceeds a preset safe time window, the overload fuse protection module determines that there is an unhealable physical jamming fault in the production line and sends an emergency stop command to the entire line to cut off the power supply to all load energy-consuming nodes.

[0038] Example 1: In an automated production line scenario integrating multiple precision processes, the system operates at a production cycle of 120 times per minute. The production line includes multiple load-consuming nodes such as the micro-manipulator drive motor for precision component assembly, the dispensing valve actuator for nanoscale fluid coating, and the optical inspection platform displacement stage for finished product scanning. Under continuous operation, the dispensing valve actuator node experiences thermal drift due to the viscosity of the guide rail grease, causing its servo drive circuit to experience physical hysteresis when establishing electromagnetic torque sufficient to overcome static friction. This physical response delay causes the actual dynamic response data of the node to lag behind the preset ideal dynamic trajectory reference when executing standard electronic cam commands. The calculated load response deviation value exceeds the system allowable deviation reference set at 20μm.

[0039] To address the aforementioned operating conditions, the distributed load response monitoring module, through drive status acquisition units coupled to each node, synchronously acquires encoder feedback values ​​from each node at a servo communication cycle of 250μs, and calculates the current load response deviation value in real time. The global power supply frequency coordinated adjustment module aggregates the deviation data from all nodes in the control closed loop and filters out the critical load deviation data with the largest modulus. That is, the deviation modulus of the above-mentioned dispensing valve node, will With respect to the system's allowable deviation benchmark Perform real-time comparisons, when detected Greater than At that time, the system calculates the dimensionless driving frequency modulation factor in real time according to the preset nonlinear mapping rules. This factor As the deviation modulus increases, it decays nonlinearly within the range from the nominal value of 1.0 to the preset safety lower limit. The global dynamic phase reference generation module receives this. Furthermore, the phase accumulation rate is inversely modulated to forcibly reduce the time growth rate of the global dynamic phase reference signal. Since all load-consuming nodes in the production line, including the upstream robot and the downstream optical inspection platform, use the unique global dynamic phase reference signal as the timing basis for obtaining driving energy and executing actions, the reduction in the time growth rate of the reference signal drives all nodes to synchronously reduce their physical running speed in the same proportion. This elastic scaling mechanism based on the global time base provides additional physical time for the dispensing valve node that experiences physical hysteresis to overcome physical resistance while maintaining the coordination of the power supply timing and the smooth flow of energy across the entire line. This allows the node to eliminate the deviation from the ideal trajectory within the stretched time window. As a result, the system eliminates local dynamic hysteresis without triggering the servo follow error alarm or interrupting the physical motion, and achieves adaptive beat coordination for physical boundaries.

[0040] Example 2: In the automated production line verification platform for high-density microelectromechanical systems (MEMS) wafer-level packaging, the system conducted a full-process engineering verification of nonlinear dynamic disturbances caused by the dynamic evolution of surface friction. The test platform simulates the physical architecture of a real industrial site. Its core includes four high-precision linear motor drive units that are clock-synchronized via a gigabit industrial Ethernet bus, corresponding to wafer transfer, dispensing, mounting, and optical inspection processes in the production line. The test data is acquired based on FPGA hardware probes built into the servo driver, which are configured to synchronously record encoder position feedback, current commands, and bus phase data of each axis at a sampling frequency of 50kHz. The position measurement resolution is set to 1nm to ensure that the data source has sufficient physical accuracy to capture microsecond-level dynamic transients. To reproduce the real industrial electromagnetic environment, Gaussian white noise with a signal-to-noise ratio of 20dB is actively superimposed on the current loop feedback signal of each axis during the test, and power frequency interference harmonics with a frequency of 50Hz and an amplitude of 0.5A are introduced to construct a background noise environment that conforms to engineering reality.

[0041] The experiment established the effectiveness of the global power supply frequency coordinated adjustment mechanism and the response sensitivity coefficient of the core control parameters. To verify the optimal range, the experiment designed three groups of control systems with gradients: the rigid control group adopted the traditional constant virtual principal axis control strategy, i.e., the time growth rate of the global dynamic phase reference signal was kept constant at 1.0; the out-of-range parameter group set the response sensitivity coefficient α of the present invention to 2.5, which is outside the theoretically calculated stability boundary; the cooperative control group adopted the complete cooperative control scheme of the present invention, setting α to 0.8. In all groups, the system allowable deviation reference used to trigger the adjustment was... All values ​​were set to 15μm, while the hard safety threshold for triggering a full-line emergency stop was set to 25μm. 2.5 seconds after the test started, a reverse resistance torque was applied to the third axis (mounting unit) via the electromagnetic brake to simulate a sudden increase in friction due to guide rail lubrication failure. The strength of this resistance torque was set to 15% of the rated output torque. The recording and analysis of the test data revealed the differences in system dynamics under different control strategies. In the rigid control group, when the resistance torque intervened, the load response deviation value of the third axis... It exhibits an irreversible linear cumulative trend. Data recorded by the FPGA probe shows that within 120ms after the application of the resistance torque, the deviation of the axis rapidly exceeded 20μm and reached 28.5μm at 150ms, triggering the hard position over-tolerance alarm of the servo system and causing an emergency shutdown of the entire line. This data objectively confirms that under a rigid timing framework, the physical obstruction of a single node will lead to the failure of global coordination.

[0042] In contrast, the data from the coordinated control group demonstrates the system's adaptive adjustment process when faced with the same physical disturbance, when the load response deviation value of the third axis... It climbed to 15.2 μm at 2.52 seconds, exceeding the allowable standard. At that time, the global power supply frequency coordination adjustment module is activated, and the system adjusts according to the formula. Real-time calculation of the driving frequency modulation factor, where The measured deviation modulus is given, with α set to 0.8. Data shows that as... Try to increase it further. The dimensionless factor was rapidly reduced from a nominal value of 1.0 to 0.88, directly impacting the global dynamic phase reference generation module. This caused the virtual spindle's phase accumulation rate to decrease by 12% within two control cycles. Consequently, the actual physical feed rates of all nodes, including the unaffected first, second, and fourth axes, decreased synchronously. This global slowdown provided an additional physical time window for the obstructed third axis to overcome the resistance torque. The final measured data showed that the peak deviation of the third axis in the collaborative control group was effectively clamped at 18.2 μm, without triggering the 25 μm shutdown alarm. Within 400 ms, with the accumulation of the servo integral term and the dynamic adaptation of the virtual spindle speed, the deviation gradually converged to a steady-state range of 5 μm. The production line maintained continuous production despite the 12% speed reduction. Data from the out-of-range parameter group revealed the engineering rationality of the parameter boundary selection. When α was set to 2.5, the system's response to deviation exhibited excessively aggressive characteristics. Data showed that once a small deviation fluctuation was detected... This resulted in a sharp, step-like drop, causing the virtual spindle speed to oscillate at high frequency between 1.0 and 0.4. This oscillation not only failed to eliminate the deviation of the third axis, but also induced mechanical resonance of the first and fourth axes, causing the root mean square value of the current command for each axis to increase by 45% compared to the cooperative control group. Ultimately, the system stopped due to loss of stability, indicating that excessive sensitivity destroyed the damping characteristics of the system.

[0043] Example 3: This example provides an in-depth engineering explanation of the calibration logic of the core control parameters in the global power supply frequency coordinated adjustment module and the internal generation mechanism of the micro-power compensation unit. In the actual engineering deployment of the automated coordinated control system for precision component production lines, the setting of the response sensitivity coefficient α is not based on random selection of empirical values, but follows a dynamic boundary calibration procedure based on the system's electromechanical time constant. It defines the load node with the largest moment of inertia in the production line as the critical inertia node and measures the critical braking acceleration of this node in the open-loop state. This physical quantity characterizes the maximum deceleration capability of a mechanical structure without rigid impact or loss of synchronization. The system is based on the formula... Determine the theoretical upper limit of the sensitivity coefficient, where, This is the preset safety lower limit value for the driving frequency modulation factor. To control the duration of the cycle, it is ensured that when the deviation... Reaching the permissible benchmark At that time, the deceleration command generated by the system will not exceed the physical tolerance limit of the mechanical system. During the calibration phase, engineers recorded the number of step response oscillations of the system under different load conditions by gradually increasing the test load, and locked the α value that makes the number of oscillations converge to zero as the final operating parameter, thus establishing a deterministic mapping from the physical boundary to the control parameter; regarding the drive frequency modulation factor Safety lower limit The clamping logic of the system implements a thermal balance protection strategy based on the low-speed characteristics of the servo driver. Because linear motors or servo motors accumulate Joule heat when operating at extremely low speeds and high torque, prolonged exposure to this state can lead to winding overheating. Therefore... The value is anchored to the rated heat dissipation power curve of the motor. Specifically, the system reads the continuous stall current limit in the motor specification sheet and, combined with the average load rate of the production line, calculates the minimum equivalent speed ratio that allows continuous operation. For example, under natural cooling conditions, this ratio is usually set between 0.2 and 0.3. When the calculated modulation factor is lower than this threshold, the global power supply frequency coordination adjustment module will force the output of this lower limit value and simultaneously trigger the overload pre-cooling mode of the cooling system, ensuring that the system will not cause thermal failure due to long-term low-speed crawling when executing the time-for-space strategy.

[0044] For the S-shaped velocity curve correction component executed by the micro-power compensation unit in the nonlinear load mapping module, its construction process follows the seven-segment jerk (Jerk) continuity constraint algorithm. After the global power supply frequency coordinated adjustment module completes the overall velocity dimensionality reduction, for the remaining micron-level steady-state position residual, the micro-power compensation unit does not directly superimpose the position step command, but generates a continuously differentiable fine-tuning trajectory for jerk. The generation of this trajectory is based on the system's maximum allowable jerk. As the core constraint, the system first calculates the required peak acceleration and peak velocity in reverse based on the current position residual ΔP and the remaining adjustment time window. If the calculated peak acceleration exceeds the maximum output capacity of the actuator, the system will automatically extend the adjustment time window and recalculate the trajectory parameters. A velocity profile comprising seven stages—acceleration, uniform acceleration, deceleration, uniform speed, acceleration / deceleration, uniform deceleration, and deceleration—is constructed. The servo-driven actuator uses this velocity profile as a feedforward control variable, superimposed onto the current loop input. This trajectory planning based on jerk constraints eliminates potential high-frequency mechanical jitter during position correction, ensuring the smoothness of the micrometer-level positioning accuracy correction process. This allows the final component mounting or inspection actions to meet tolerance requirements. Through the above transparent description of the key parameter calibration procedure and trajectory generation mechanism, the technical solution logically achieves full-band controllability from overall coordinated adjustment to surface precision compensation. In the physical implementation of the frequency modulation coefficient calculation unit, the nonlinear mapping rule is visualized as a piecewise continuous mapping procedure with underlying saturation limiting characteristics. When key load deviation data... Not greater than the system's allowable deviation benchmark Output a constant nominal value when Greater than The linear attenuation clamp is executed according to the preset response sensitivity coefficient α, and the value is kept at the preset safety lower limit. For the switching of the nonlinear load mapping module's operating state, the system has a preset steady-state judgment control loop that extracts key load deviation data in real time over M consecutive cycles according to the servo communication cycle. The first-order difference absolute value is calculated, where M is the preset sliding window length. When the continuously calculated difference absolute value is less than the preset steady-state judgment threshold ϵ, and the state duration crosses the preset time constant window, the judgment logic outputs a high-level state flag. After receiving the state flag, the micro-power compensation unit confirms that the global velocity dimensionality reduction has reached the steady-state basis, and activates the issuance of a jerk continuously differentiable fine-tuning trajectory command based on the flag bit.

[0045] Example 4: During the initial configuration phase of a production line for a specific type of precision component, the system first executes an ideal dynamic trajectory teaching procedure based on a gold standard sample to construct a comparison benchmark for the distributed load response monitoring module. This procedure controls each load-consuming node of the entire production line to complete a full standard operating cycle in a low-speed constant mode under rated load conditions. During this period, each drive status acquisition unit synchronously records the absolute position data stream of the servo encoder of each node at an oversampling frequency of 100kHz. These discrete time-domain position data are mapped to the phase domain of the global dynamic phase reference signal through a cubic spline interpolation algorithm, thereby generating a continuous and differentiable ideal dynamic trajectory reference curve and storing it in the controller's non-volatile memory, ensuring the accuracy of the data used to calculate the load response deviation value. The reference benchmark is anchored to the specific mechanical assembly tolerances and kinematic characteristics of the production line, eliminating systematic calculation errors caused by the mismatch between the theoretical model and the physical structure.

[0046] Before the system officially enters closed-loop collaborative operation, the controller automatically triggers a dynamic boundary identification and parameter self-tuning sequence for the current physical environment. The global dynamic phase reference generation module injects a series of pseudo-random binary sequence excitation signals with controlled amplitude into each servo drive actuator. The initial calibration reference for the amplitude of this excitation signal is 5% of the rated output current of the servo motor, and the single sequence injection period is set to 2 seconds. During the injection period, the system continuously calculates the signal-to-noise ratio of the encoder feedback signal. If the signal-to-noise ratio is detected to be lower than the judgment threshold of 15dB, the current amplitude is automatically increased step by step in increments of 1% until the safety threshold is exceeded. After entering the parameter identification process, the system will input the discrete current and speed feedback from the driver. The bidirectional data array is input to the autoregressive exogenous discrete difference equation computation block. During the zero-load initialization phase on the production line when no workpieces are mounted, the main controller calls the recursive least squares module to iteratively update the weight coefficients of the difference equation every 250μs communication cycle. When the overall variance of the weight coefficient fluctuation is less than 0.001 for 100 consecutive cycles, the system directly extracts the solidified discrete weight coefficient array and uses the load spectrum feature analysis unit to perform frequency domain analysis on the feedback signal to extract key physical parameters such as the moment of inertia, viscous friction coefficient, and mechanical resonant frequency of each node. Based on these measured parameters, the system updates the critical braking acceleration involved in the aforementioned embodiment in real time. And the value of the response sensitivity coefficient α, and verify the driving frequency modulation factor. Whether the calculation boundary is always within the safe operating area of ​​the motor thermodynamic model, this pre-calibration process ensures that the system's control strategy always converges within the current actual physical capability boundary of the equipment, preventing the risk of control model mismatch caused by equipment aging or ambient temperature drift.

[0047] Example 5: To ensure the absolute engineering stability of the distributed load response monitoring module's decision-making logic under complex electromagnetic environments and mechanical micro-vibration conditions, the system calculates key load deviation data. Previously, a signal integrity verification procedure based on joint time-frequency domain constraints was implemented. Discrete first-order inertial filtering was applied to the original position error signal sequence e(n) uploaded by the drive state acquisition unit to remove high-frequency random interference caused by encoder quantization noise or bus transmission jitter. The filtering algorithm followed a recursive formula. Where β is the filtering smoothing coefficient, its value is set between 0.15 and 0.25 based on the Nyquist sampling theorem and the system's mechanical bandwidth, ensuring that the phase characteristics of the true physical hysteresis are preserved while suppressing noise. Based on this, the procedure introduces a time-domain persistent logic gate as the final criterion for determining the validity of the deviation, i.e., when the filtered deviation value... The system exceeds the allowable deviation benchmark for N consecutive control cycles. Only when the system confirms that the deviation is a substantial physical delay and triggers the subsequent frequency adjustment logic, the setting of the counting threshold N is positively correlated with the mechanical response time constant of the production line, and is usually set to 3 to 5 cycles, thereby blocking the system misjudgment caused by transient mechanical shock or signal glitches from the source and ensuring the certainty of control intervention.

[0048] To address the implementation path of the load spectrum feature analysis unit in extracting the underlying feature signals, the system incorporates a sliding fast Fourier transform algorithm module based on the Hanning window function at the digital signal processing level. This module uses a discretized load response deviation data sequence as the basic input source. The system's underlying hardware timer is forcibly locked at a sampling frequency of 50kHz to ensure complete coverage of the critical mechanical resonant frequency band of the production line drivetrain, from 10Hz to 2kHz. In the data buffering stage, the sliding time window is defined as 2048 consecutive sampling points, equivalent to a physical data truncation span of 40.96ms. Furthermore, the overlap rate between adjacent sliding windows is fixed at 50%, meaning only 1024 new windows are allowed per calculation cycle. The collected deviation data is pushed into the first-in-first-out queue. Based on the above three clearly defined physical calibration values, the control program extracts the data array within a set time window, applies Hanning window multiplication, performs discrete Fourier transform to generate a frequency domain energy spectral density matrix, calls a pre-configured digital bandpass filter to filter out full-band noise, extracts a specific frequency band amplitude array, extracts the envelope extrema within the array as a feature signal, and outputs it to the drive chain status assessment unit. The upper and lower limits of the specific frequency band are pre-anchored to the inherent mechanical meshing frequency and higher harmonic range of the production line's physical drive chain. The drive chain status assessment unit receives the feature signal and directly compares the amplitude with the preset electrical wear threshold. Based on the sign of the difference, it outputs a Boolean-type preventive maintenance command to the system bus.

[0049] The global power supply frequency coordination adjustment module outputs the drive frequency modulation factor. In this stage, the system incorporates a dynamic limiting procedure for the output gradient to prevent jerk shocks to the virtual spindle caused by sudden changes in adjustment commands, and monitors the rate of change of the modulation factor in real time. And constrain the rate of change to a preset slope limit threshold. Within that threshold The physical meaning corresponds to the bearing limit of the node with the lowest mechanical stiffness among all load-dissipating nodes along the entire line. Its value is obtained by inverse calculation through the dynamic simulation model of the system. If the original rate of change calculated by the algorithm exceeds this threshold, the system will proceed according to... The output value is linearly truncated so that... The smoothing process of this output stage ensures that the time growth rate of the global dynamic phase reference signal always remains within the linear response range of the mechanical system, transitioning to the target value along a smooth curve with controlled slope. This avoids longitudinal oscillations of the production line or inertial displacement of precision components caused by sudden frequency adjustments, achieving a balance between the flexibility of control commands and engineering safety.

[0050] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention.

[0051] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.

Claims

1. An automated collaborative control system for a precision component production line, characterized in that, include: The distributed load response monitoring module includes multiple drive status acquisition units that are coupled to the input terminals of each load energy consumption node in the production line. These units are used to collect the actual dynamic response data of the corresponding load energy consumption node in real time and calculate the current load response deviation value based on the difference between the actual dynamic response data and the preset ideal dynamic trajectory benchmark. The global power phase reference generation module is used to construct and output a global power phase reference signal that governs the power supply timing of all load energy consumption nodes in the entire production line. The global power phase reference signal serves as the sole timing basis for each node in the entire system to acquire driving energy and execute actions. The global power supply frequency coordination adjustment module is built in the closed-loop feedback loop between the distributed load response monitoring module and the global dynamic phase reference generation module. The global power supply frequency coordination adjustment module is configured to execute the following control logic: In each control cycle, it collects all load response deviation values ​​output by the distributed load response monitoring module and selects the key load deviation data with the largest modulus value. This key load deviation data represents the node state with the tightest dynamic constraints in the current production line. The key load deviation data is compared with the preset system allowable deviation benchmark, and a dimensionless driving frequency modulation factor is calculated in real time accordingly. The phase accumulation rate of the global dynamic phase benchmark generation module is inversely modulated using the driving frequency modulation factor. When the key load deviation data exceeds the system allowable deviation benchmark, the time growth rate of the global dynamic phase benchmark signal is forcibly reduced, thereby driving all load energy consumption nodes to reduce their physical operating speed proportionally and synchronously, so as to eliminate local dynamic hysteresis while maintaining the overall power supply timing coordination and energy flow stability.

2. The automated collaborative control system for a precision component production line according to claim 1, characterized in that, The global power supply frequency coordinated adjustment module includes: a deviation extreme value locking unit, which sorts all load response deviation values ​​uploaded by the distributed load response monitoring module within a communication cycle by absolute value and locks the source node of the largest deviation within that cycle; and a frequency modulation coefficient calculation unit, which has a preset nonlinear mapping rule. The nonlinear mapping rule defines the inverse monotonic relationship between the key load deviation data and the driving frequency modulation factor, so that as the key load deviation data increases, the output value of the driving frequency modulation factor decays nonlinearly within the preset nominal value to zero value range.

3. The automated collaborative control system for a precision component production line according to claim 2, characterized in that, The global dynamic phase reference generation module includes: a phase accumulation and synthesis unit, which receives the drive frequency modulation factor output by the frequency modulation coefficient calculation unit, multiplies the drive frequency modulation factor with a preset basic drive frequency, and then integrates the calculation result over time to generate a global dynamic phase reference signal; and a multi-node drive distribution interface, which broadcasts the global dynamic phase reference signal to the servo drive actuators of multiple load energy consumption nodes via an industrial fieldbus. The servo drive actuators use the global dynamic phase reference signal as an independent electronic cam spindle input to control energy output.

4. The automated collaborative control system for a precision component production line according to claim 1, characterized in that, The system also includes: a nonlinear load mapping module, which is set between the global dynamic phase reference generation module and the specific load energy consumption node; the nonlinear load mapping module stores multiple preset electronic cam curve tables and is configured to look up the table according to the current value of the global dynamic phase reference signal to obtain the target position command of the corresponding load energy consumption node; the nonlinear load mapping module also includes a micro power compensation unit, which is used to superimpose an S-shaped velocity curve correction component on the target position command based on the steady state of the global velocity dimension reduction completed by the global power supply frequency collaborative adjustment module, for the remaining steady state position residual.

5. An automated collaborative control system for a precision component production line according to claim 1, characterized in that, The calculation logic for the driving frequency modulation factor specifically follows the following mathematical relationship: ,in, To drive the frequency modulation factor, The modulus of the key load deviation data. Let α be the system's allowable deviation benchmark, and let α be the preset response sensitivity coefficient. The minimum lower limit is clamped at a preset safety threshold.

6. The automated collaborative control system for a precision component production line according to claim 1, characterized in that, The distributed load response monitoring module also includes: a load spectrum feature analysis unit, used to perform real-time frequency domain analysis on load response deviation data and separate characteristic signals of specific frequency bands from the data noise floor; and a drive chain status assessment unit, used to monitor the amplitude evolution trend of characteristic signals. When the amplitude of the characteristic signal at a specific frequency point exceeds the preset electrical wear threshold, a preventive maintenance command indicating loosening of the drive chain clearance or increased dry friction is generated and sent to the upper management system.

7. An automated collaborative control system for a precision component production line according to claim 1, characterized in that, The system also includes: a direct-coupled power supply architecture, in which two adjacent load power consumption nodes are directly adjacent in physical space and there is no intermediate buffer device; two adjacent load power consumption nodes are logically elastically connected through a global power phase reference signal. When the load response deviation of the downstream node increases due to disturbance, the upstream node automatically reduces the feed speed by receiving the reduced global power phase reference signal.

8. An automated collaborative control system for a precision component production line according to claim 1, characterized in that, The global power supply frequency coordinated adjustment module also includes: a load recovery hysteresis control unit, which controls the drive frequency modulation factor to gradually rise back to the nominal value according to a preset acceleration limit after the key load deviation data recovers to below the system allowable deviation benchmark; and a drive surge suppression filter, which is connected in series in the output path of the drive frequency modulation factor to filter out high-frequency fluctuations in the modulation factor caused by transient jumps in the deviation data.

9. An automated collaborative control system for a precision component production line according to claim 1, characterized in that, The load energy consumption nodes include the drive motor of the micro-manipulator used for precision component assembly, the dispensing valve actuator, or the displacement stage of the optical inspection platform; the actual dynamic response data collected by the distributed load response monitoring module are specifically the encoder feedback value of the servo drive circuit or the position reading of the linear grating ruler; the system allowable deviation benchmark is set to a range of 10μm to 50μm.

10. An automated collaborative control system for a precision component production line according to claim 1, characterized in that, The system also includes: an overload fuse protection module for real-time monitoring of the continuous low value of the drive frequency modulation factor; when the duration of the drive frequency modulation factor being lower than the shutdown threshold exceeds the preset safe time window, the overload fuse protection module determines that there is an unhealable physical jamming fault in the production line and sends an emergency stop command to the entire line to cut off the power supply to all load energy-consuming nodes.

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