Multi-axis linkage direct driving power tool turret machine precision motion control method and system

Abstract

The application relates to the field of precise motion control, in particular to a multi-axis linkage direct drive power tool turret machine precise motion control method and system. The method comprises the following steps: acquiring a machining track, discretizing the machining track into multiple space motion units, and determining target displacement amounts for each motion axis; receiving a completion signal; after determining that the motion axes participating in the current space motion unit complete the corresponding target displacement amounts according to the completion signal, acquiring the completion times of the motion axes, taking the completion time of the motion axis with the longest completion time as a time reference, issuing the target displacement amounts corresponding to the next space motion unit to each motion axis, and starting the motion of each motion axis to the next space motion unit. The technical problems of machining precision reduction and product quality unqualification caused by clock frequency drift and motion axis synchronization deviation accumulation due to the gradual change of the microphysical characteristics of the system inside the multi-axis linkage direct drive power tool turret machine are solved.

Description

Technical Field

[0001] This application relates to the field of precision motion control, and more specifically, to a precision motion control method and system for a multi-axis linkage direct drive turret crane. Background Technology

[0002] Multi-axis linkage direct-drive turret lathes are widely used in high-precision fields such as aerospace, precision molds, and medical devices, achieving high-speed, high-precision cutting of complex curved surfaces through multi-axis collaboration. However, during prolonged high-load operation, the control system's crystal oscillator experiences slight frequency drift due to material fatigue, stress release, and temperature fluctuations. This causes the time step perceived by the control system to deviate from the actual physical time, resulting in continuously accumulating synchronization errors when each motion axis executes interpolation commands. To maintain trajectory accuracy, the servo driver must output a high-frequency, large-amplitude correction current, leading to overheating of the direct-drive motor. Key parameters such as its torque constant and winding resistance deviate from their nominal values, thereby compromising the accuracy of the PID, current loop, and speed feedforward models tuned based on room-temperature parameters. The mismatch between the controller and the actual motor model makes the servo system prone to overshoot, oscillation, and hysteresis, ultimately forming visible micro-wave marks on the workpiece surface and causing critical dimensional deviations, affecting part yield and processing stability.

[0003] To address the aforementioned issues, existing technologies urgently need improvement. Summary of the Invention

[0004] This application discloses a precision motion control method and system for a multi-axis linkage direct drive turret machine, aiming to solve the technical problems of reduced servo system robustness, reduced machining accuracy, and unqualified product quality caused by clock frequency drift and accumulated motion axis synchronization deviation due to gradual changes in the internal micro-physical characteristics of the multi-axis linkage direct drive turret machine during long-term, high-load continuous production.

[0005] The technical solution of this application is as follows:

[0006] In a first aspect, this application discloses a precision motion control method for a multi-axis linkage direct-drive turret crane, comprising:

[0007] The machining trajectory to be executed is obtained, and the machining trajectory is discretized into multiple spatial motion units arranged sequentially along the machining trajectory. The target displacement of each motion axis in the corresponding spatial motion unit is determined.

[0008] Receive the completion signal of the corresponding motion axis after the target displacement is completed;

[0009] After determining the target displacement of the motion axis participating in the current spatial motion unit based on the completion signal, motion coordination is performed. The completion time of each motion axis from the start of participating in the current spatial motion unit to the issuance of the completion signal is obtained. The completion time of the motion axis with the longest completion time is used as the time reference. The target displacement of the next spatial motion unit is issued to each motion axis to start the motion of each motion axis to the next spatial motion unit.

[0010] Furthermore, after determining the target displacement of the motion axes participating in the current spatial motion unit based on the completion signal, motion coordination is performed. The completion time of each motion axis from the start of participation in the current spatial motion unit to the issuance of the completion signal is obtained. Using the completion time of the motion axis with the longest completion time as the time reference, the target displacement corresponding to the next spatial motion unit is sent to each motion axis to initiate the motion of each motion axis towards the next spatial motion unit, including:

[0011] Acquire the target displacement, material property data of the material to be processed, and operation data of each motion axis corresponding to the current spatial motion unit and subsequent spatial motion units;

[0012] When it is determined that the completion time of at least one motion axis is delayed relative to other motion axes based on the completion time from the start of each motion axis participating in the current spatial motion unit to the issuance of the completion signal, the delay is determined based on the target displacement, material property data and operation data corresponding to the current spatial motion unit, whether the delay is caused by the increase of instantaneous local cutting load encountered by the motion axis in the current spatial motion unit and is within the preset tolerance period.

[0013] When the delay is caused by an increase in instantaneous local cutting load and is within the preset tolerance period, the completion time of the motion axis with the longest completion time is used as the time reference. The motion axis that has completed the target displacement in the current spatial motion unit receives the target displacement corresponding to the next spatial motion unit and starts the motion to the next spatial motion unit after the preset tolerance period expires.

[0014] The spatial deviation caused by the delay is determined for the motion axis with the delay time. In the subsequent spatial motion units, the spatial deviation is gradually made up by adjusting the motion speed of the motion axis with the delay, under the premise of not exceeding the preset current, acceleration and / or speed limits, so that the actual motion progress of the motion axis with the delay is consistent with the motion progress of other motion axes.

[0015] Furthermore, using the completion time of the longest-running motion axis as the time reference, after the motion axis that has completed the target displacement within the current spatial motion unit receives the target displacement corresponding to the next spatial motion unit and initiates motion on the next spatial motion unit after waiting for the preset tolerance period to expire, the process also includes:

[0016] Trend analysis is performed on the operating data of each motion axis. Based on the results of the trend analysis, when the operating data of a certain motion axis shows continuous changes in multiple spatial motion units and exceeds the corresponding preset normal fluctuation threshold, the motion axis is identified as a motion axis with progressively degraded performance. The operating data includes completion time, motor current and / or position error.

[0017] The priority of motion axes with progressive performance degradation is reduced in motion coordination, and the sending time of the start command of the next spatial motion unit is adaptively adjusted according to the adjusted priority. Other motion axes without progressive performance degradation are given priority as the motion axes with the longest completion time under the preset non-transient delay waiting threshold constraint, which is used to determine the time reference.

[0018] Based on the type of gradual performance degradation, generate corresponding performance compensation or maintenance operation suggestions.

[0019] Furthermore, based on the type of gradual performance degradation, corresponding performance compensation or maintenance operation suggestions are generated, including:

[0020] The operation data of the progressively degrading motion axis when completing each spatial motion unit is preprocessed to obtain the operation data feature set reflecting the current operation state of the corresponding motion axis;

[0021] Predefine and store operational data feature patterns associated with different physical causes, and construct a physical cause feature pattern library from these operational data feature patterns;

[0022] The current motion state's operational data feature set is matched with the physical cause feature pattern library. By calculating the similarity and / or deviation between the current operational data feature set and each operational data feature pattern, the physical cause that best matches the operational data feature set is determined.

[0023] When multiple motion axes exhibit a progressive performance degradation trend simultaneously, the motion correlation and load transfer relationship between each motion axis are analyzed. If it is determined that the progressive performance degradation of the first motion axis leads to an increase in the completion time of the second motion axis, and the similarity between the running data feature set of the second motion axis and any running data feature pattern is less than a preset similarity threshold and / or the deviation is greater than a preset deviation threshold, the determination that the second motion axis itself has a progressive performance degradation is excluded, and the increase in the completion time of the second motion axis is attributed to the progressive performance degradation of the first motion axis, thus achieving an independent attribution result for the physical cause of the progressive performance degradation of each motion axis.

[0024] Based on the physical causes obtained from the independent attribution results, the type of progressive performance degradation is determined, and performance compensation or maintenance operation suggestions corresponding to the physical causes are generated for the motion axes with progressive performance degradation.

[0025] Furthermore, the machining trajectory is discretized into multiple spatial motion units arranged sequentially along the machining trajectory, including:

[0026] Based on the curvature change of the machining trajectory at each position, the corresponding feed speed command, and the preset upper limit of contour error, the initial spatial length of each spatial motion unit on the machining trajectory is adaptively determined so that the contour error generated by linear approximation within any spatial motion unit does not exceed the upper limit of contour error.

[0027] Under the speed limit constraints of each motion axis, the initial spatial length is corrected to obtain the target spatial length of each spatial motion unit.

[0028] Furthermore, after generating performance compensation or maintenance recommendations for motion axes with progressively degraded performance based on physical causes, the following are also included:

[0029] Obtain the current production plan information for the machine tool. The production plan information should include at least the priority and deadline of the tasks to be processed.

[0030] Based on the physical causes obtained from the independent attribution results and the corresponding degree of performance degradation, determine the type of maintenance operation required for performance compensation or maintenance operation recommendations and the estimated time required to perform the maintenance operation;

[0031] Obtain inventory information for spare parts required to perform maintenance operations;

[0032] Obtain availability information for the specialized tools required to perform maintenance operations;

[0033] Obtain the scheduling information of maintenance personnel with the skills required to perform maintenance operations;

[0034] The maintenance operation type and estimated time are compared with the production plan information, and a conflict analysis between the maintenance operation and the production plan is performed to obtain the conflict analysis results.

[0035] When the conflict analysis results indicate that there is a time conflict between maintenance operations and high-priority tasks to be processed in the production plan, and spare parts, special tools are unavailable or maintenance personnel are insufficient, an alternative maintenance strategy is generated. The alternative maintenance strategy includes at least adjusting the execution time of some tasks to be processed in the production plan, adjusting the execution time of maintenance operations, and / or, under the premise of not being lower than the preset processing accuracy requirements, temporarily adjusting the motion parameters of the relevant motion axes based on performance compensation or performance compensation measures in the maintenance operation recommendations.

[0036] Generate comprehensive maintenance recommendations that include maintenance operation type, estimated time, spare parts and their inventory information, special tools and their availability, maintenance personnel scheduling information, suggested execution time, and alternative maintenance strategies.

[0037] Furthermore, before generating comprehensive maintenance recommendation information that includes maintenance operation type, estimated time, spare parts and their inventory information, special tools and their availability, maintenance personnel scheduling information, suggested execution time, and alternative maintenance strategies, it also includes:

[0038] For each alternative maintenance scheme identified in the alternative maintenance strategy, obtain the time impact data of each alternative maintenance scheme on the completion time of the tasks to be processed in the production plan, the material consumption data of the maintenance operation, the manpower consumption data of the maintenance operation, and the life impact data of the machine tool components related to the maintenance operation type corresponding to the alternative maintenance scheme after the execution of the alternative maintenance scheme.

[0039] Based on the time-related impact data, calculate the productivity loss value for each alternative maintenance option;

[0040] Based on material consumption data and manpower consumption data, calculate the total maintenance cost of each alternative maintenance plan;

[0041] Based on the lifespan impact data, calculate the equipment health impact value for each alternative maintenance option;

[0042] The production efficiency loss value, total maintenance cost value, and equipment health impact value corresponding to each alternative maintenance plan are weighted to obtain the comprehensive evaluation value of each alternative maintenance plan;

[0043] The optimal alternative maintenance solution based on the comprehensive evaluation value is identified as the recommended alternative maintenance solution, and the maintenance operation type and suggested execution time corresponding to the recommended alternative maintenance solution are integrated into the comprehensive maintenance recommendation information.

[0044] Furthermore, the production efficiency loss value, total maintenance cost value, and equipment health impact value corresponding to each alternative maintenance plan are weighted to obtain a comprehensive evaluation value for each alternative maintenance plan, including:

[0045] Obtain the priority of the current machining task, the real-time load status of each motion axis of the machine tool, and the historical performance impact data of historical maintenance operations on equipment performance;

[0046] Adjust the weight of production efficiency loss in the overall evaluation based on the priority of the current processing tasks;

[0047] Adjust the weight of the equipment health impact value in the comprehensive evaluation based on the real-time load status of each motion axis of the machine tool;

[0048] Adjust the weight of total maintenance cost in the comprehensive evaluation based on historical performance impact data;

[0049] Based on the adjusted weights of production efficiency loss, total maintenance cost, and equipment health impact, the production efficiency loss, total maintenance cost, and equipment health impact corresponding to each alternative maintenance plan are weighted to obtain a comprehensive evaluation value for each alternative maintenance plan.

[0050] Furthermore, after adjusting the weight of the equipment health impact value in the comprehensive evaluation based on the real-time load status of each motion axis of the machine tool, it also includes:

[0051] Real-time comparison of data from multiple load-related sensors on the same motion axis; when the data deviation of a certain load-related sensor data from other load-related sensor data on the same axis and / or from the historical normal operation data corresponding to that load-related sensor data exceeds a preset deviation threshold, the corresponding load-related sensor data is marked as abnormal data.

[0052] The received load-related sensor data is sequenced based on timestamps. When a data arrival delay or data packet loss is detected, the corresponding load-related sensor data is marked as delayed data or incomplete data.

[0053] When all load-related sensor data for a certain motion axis are marked as abnormal, the historical load status data of that motion axis is called to make a short-term prediction and generate predicted load status data for load status assessment.

[0054] When load-related sensor data is continuously marked as lagging data for multiple consecutive sampling periods and its time delay exceeds a preset delay threshold, time compensation is performed on the load status assessment result obtained based on the corresponding load-related sensor data.

[0055] When adjusting the weight of the equipment health impact value based on the load status assessment results after time compensation, the abnormal data, lag data and / or incomplete data are weighted and attenuated according to the abnormal data marking and / or lag data marking of load-related sensor data. The upper limit of the weight adjustment range of the equipment health impact value is set in combination with the duration of data abnormality or lag.

[0056] Secondly, this application also discloses a precision motion control system for a multi-axis linkage direct-drive turret machine, comprising:

[0057] The trajectory decomposition module is used to obtain the machining trajectory to be executed, discretize the machining trajectory into multiple spatial motion units arranged sequentially along the machining trajectory, and determine the target displacement of each motion axis in the corresponding spatial motion unit.

[0058] The motion execution module is used to receive the completion signal of the corresponding motion axis after the target displacement is completed;

[0059] The motion initiation module is used to coordinate motion after determining the target displacement of the motion axis participating in the current spatial motion unit based on the completion signal. It obtains the completion time of each motion axis from the start of participating in the current spatial motion unit to the issuance of the completion signal, and uses the completion time of the motion axis with the longest completion time as the time reference to send the target displacement of the next spatial motion unit to each motion axis, so as to start the motion of each motion axis to the next spatial motion unit.

[0060] Beneficial Effects: This application ensures high-precision synchronous movement of each motion axis on complex machining trajectories, avoiding the output of instantaneous high-frequency current pulses by the servo driver for forced synchronization. This reduces motor heating and stabilizes key physical parameters such as the motor's torque constant and winding resistance. This allows the servo controller's pre-set PID gain, current loop regulator, and speed feedforward model to match the actual dynamic response of the motor, significantly improving the robustness of the servo system. Ultimately, this method effectively eliminates micro-amplitude vibration marks formed on the workpiece surface by the cutting tool, ensuring that the critical dimensions of the parts meet strict tolerance requirements, thereby greatly improving machining accuracy and product quality, and overcoming the machining defects caused by the accumulation of synchronization deviations in existing technologies. Attached Figure Description

[0061] Figure 1 This is a flowchart illustrating a precision motion control method for a multi-axis linkage direct-drive turret machine provided in this application.

[0062] Figure 2 The structural block diagram of a precision motion control system for a multi-axis linkage direct drive turret machine provided in this application.

[0063] In the diagram: 1. Trajectory decomposition module; 2. Motion execution module; 3. Motion initiation module. Detailed Implementation

[0064] The technical solutions of this application will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are merely some embodiments of this application, and not all embodiments. The components of this application described and shown in the accompanying drawings can generally be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of this application provided in the accompanying drawings is not intended to limit the scope of the claimed application, but merely to illustrate selected embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without inventive effort are within the scope of protection of this application.

[0065] In traditional multi-axis direct-drive turret rigs, when performing high-speed, high-precision machining of complex curved surfaces, the crystal oscillator inside the control system may experience extremely slight frequency drift due to factors such as material fatigue, internal stress release, and ambient temperature fluctuations. This gradual, imperceptible clock frequency drift causes a deviation between the system's perceived "time step" and the actual physical time step. Consequently, when each motion axis executes interpolation commands, a small but continuously increasing time difference appears between the theoretical synchronization point and the actual execution time. This accumulated time difference causes the servo controller's PID gain, current loop regulator, and speed feedforward model, originally set based on ambient temperature parameters, to no longer match the actual dynamic response of the motor, ultimately resulting in defective machined parts.

[0066] Reference Figure 1 In response, this application proposes a precision motion control method for a multi-axis linkage direct-drive turret crane, comprising:

[0067] S1000: Obtain the machining trajectory to be executed, discretize the machining trajectory into multiple spatial motion units arranged sequentially along the machining trajectory, and determine the target displacement of each motion axis within the corresponding spatial motion unit.

[0068] S2000: Receives the completion signal of the corresponding motion axis after the target displacement is completed;

[0069] S3000: After determining the target displacement amount of the motion axis participating in the current spatial motion unit based on the completion signal, motion coordination is performed. The completion time of each motion axis from the start of participating in the current spatial motion unit to the issuance of the completion signal is obtained. The completion time of the motion axis with the longest completion time is used as the time reference. The target displacement amount corresponding to the next spatial motion unit is issued to each motion axis to start the motion of each motion axis to the next spatial motion unit.

[0070] Specifically, the "multi-axis linkage direct-drive turret machine" mentioned in this application refers to a machine tool with multiple motion axes (e.g., X, Y, Z, A, B axes, etc.), whose motion axes are directly driven by direct-drive motors, enabling multi-axis coordinated motion and precision machining of complex curved surfaces. Here, "direct-drive turret" refers to the tool being mounted on a rotary or linear axis directly driven by a motor to achieve high dynamic response and high-precision positioning. "Machining trajectory" is the path followed by the tool when cutting on the workpiece, usually generated by CAD / CAM software. "Spatial motion unit" is a small line segment or arc segment obtained by discretizing a continuous curve or surface path; each unit represents a segment of tool movement within a short time. "Target displacement" is the precise distance that each motion axis needs to complete within each spatial motion unit. "Completion signal" is the confirmation signal sent by the motion axis to the control system after completing its target displacement. "Completion time" is the time from when the motion axis begins participating in a spatial motion unit to when it sends out the completion signal. The "time reference" is a reference point used during motion coordination to synchronize the motion axes and initiate the next spatial motion unit.

[0071] In practice, the first step is to obtain the machining trajectory to be executed. This trajectory can be generated by computer-aided design (CAD) and computer-aided manufacturing (CAM) software, and is typically represented in G-code or a similar CNC program format. For example, a preset machining program file containing the geometric path and speed information of the tool on the workpiece can be read from the machine tool's CNC system.

[0072] Subsequently, the machining trajectory is discretized into multiple spatial motion units arranged sequentially along the trajectory. During discretization, the continuous curve or surface path is decomposed into a series of tiny straight line segments or arc segments. For example, a fixed step size discretization can be used, or the length of the spatial motion unit can be adaptively adjusted according to the machining accuracy requirements and curvature changes. For each spatial motion unit, the target displacement is determined for each motion axis using an interpolation algorithm. For example, for a three-axis linkage machining task, when the length of a spatial motion unit is ΔL and the motion direction vectors of each axis are (vx, vy, vz), the target displacements of each axis are ΔL*vx, ΔL*vy, and ΔL*vz, respectively.

[0073] After each motion axis begins to execute the target displacement within the current spatial motion unit, the system continuously receives completion signals from each motion axis. These completion signals are typically issued by the servo driver after detecting that the motion axis has reached the target position. For example, when the error between the position fed back by the servo motor position encoder and the target position is less than a preset threshold, the servo driver generates a digital signal indicating that the motion axis has completed its current task.

[0074] After determining the target displacement of the motion axes participating in the current spatial motion unit based on the completion signal, the system performs motion coordination: acquiring the completion time of each motion axis from the start of participation in the current spatial motion unit to the issuance of the completion signal. The motion axis participating in the current spatial motion unit refers to the motion axis whose target displacement within that spatial motion unit is not zero (or greater than a preset minimum displacement threshold). The completion time from the start of participation in the current spatial motion unit to the issuance of the completion signal refers to the time interval from when the motion axis receives the start command of the current spatial motion unit and begins executing the target displacement of that unit until the issuance of the completion signal. For example, a high-precision timer can be used to record the time interval from when each motion axis receives the start command of the current spatial motion unit to the issuance of the completion signal.

[0075] Subsequently, the completion time of the motion axis with the longest completion time is used as the time reference. This means that even if some motion axes complete the movement of the current spatial motion unit ahead of schedule, they must wait for this time reference before starting the next spatial motion unit. For example, when the completion time of the X-axis is 10ms, the Y-axis is 12ms, and the Z-axis is 11ms, the time reference is set to 12ms.

[0076] After the time reference is determined, the target displacement corresponding to the next spatial motion unit is sent to each motion axis to start the motion of each motion axis to the next spatial motion unit. For example, when all motion axes have completed the motion of the current spatial motion unit and the waiting time has reached the time reference, the control system will simultaneously send the next set of target displacement commands to the servo drivers of each motion axis, thereby realizing the synchronous start of each axis.

[0077] The multi-axis linkage direct drive turret machine precision motion control method proposed in this application effectively suppresses the accumulation of small time deviations of each motion axis by discretizing the machining trajectory into spatial motion units and introducing a time reference based on the motion axis with the longest completion time for motion coordination.

[0078] In another embodiment of this application, S3000 is further proposed to include:

[0079] S3100: Acquire the target displacement, material property data of the material to be processed, and running data of each motion axis corresponding to the current spatial motion unit and subsequent spatial motion units respectively;

[0080] S3200: When it is determined that the completion time of at least one motion axis is delayed relative to other motion axes based on the completion time of each motion axis from the start of participating in the current spatial motion unit to the issuance of the completion signal, the delay is determined based on the target displacement, material property data and operation data corresponding to the current spatial motion unit, whether the delay is caused by the increase of instantaneous local cutting load encountered by the motion axis in the current spatial motion unit and is within the preset tolerance period.

[0081] S3300: When the delay is caused by an increase in instantaneous local cutting load and is within the preset tolerance period, the completion time of the motion axis with the longest completion time is used as the time reference. The motion axis that has completed the target displacement in the current spatial motion unit receives the target displacement corresponding to the next spatial motion unit and starts the motion of the next spatial motion unit after the preset tolerance period expires.

[0082] S3400: For the motion axis with delay, determine the resulting spatial deviation based on its delay time. In subsequent spatial motion units, under the premise of not exceeding the preset current, acceleration and / or speed limits, gradually make up for the spatial deviation by adjusting the motion speed of the motion axis with delay, so that the actual motion progress of the motion axis with delay is consistent with the motion progress of other motion axes again.

[0083] Specifically, before motion coordination, the system acquires the target displacements corresponding to the current and subsequent spatial motion units. These target displacements are determined by the motion distance planned for each motion axis after the machining trajectory is discretized. Simultaneously, it acquires material property data of the material to be processed, such as hardness, toughness, and thermal conductivity, to assess changes in cutting load. It also collects real-time operating data for each motion axis, such as motor current, position error, and speed feedback, to monitor the actual operating status of the motion axes. When, based on the completion time of each motion axis from the start of its participation in the current spatial motion unit to the issuance of a completion signal, it is determined that the completion time of at least one motion axis is delayed relative to other motion axes, the system activates a delay analysis mechanism. This delay indicates that the time required for that motion axis to complete the current spatial motion unit is significantly longer than expected and / or that of other motion axes.

[0084] Furthermore, based on the target displacement, material property data, and operational data corresponding to the current spatial motion unit, the system determines whether the delay is caused by an increase in instantaneous local cutting load encountered by the motion axis within the current spatial motion unit and is within a preset tolerance period. Specifically, it can identify whether it is an increase in instantaneous local cutting load by analyzing the instantaneous peak value of the motor current, the instantaneous fluctuation of the position error, and the matching degree between material properties and cutting parameters. The preset tolerance period limits the acceptable range of instantaneous delay time for the system; delays exceeding the preset tolerance period are considered delays not caused by an increase in instantaneous local cutting load.

[0085] When a delay is determined to be caused by an instantaneous increase in local cutting load and is within a preset tolerance period, the system uses the completion time of the longest-completing motion axis as the time reference. The motion axis that has completed the target displacement within the current spatial motion unit waits for the preset tolerance period to expire before uniformly receiving the target displacement corresponding to the next spatial motion unit and initiating motion for that unit. That is, for instantaneous and tolerable delays, the system avoids overcompensation by waiting a short time rather than immediately performing aggressive compensation, thus preventing the introduction of new vibrations or instabilities. Simultaneously, the system calculates the resulting spatial deviation based on the delay time of the motion axis, which is the difference between the actual and ideal positions of the motion axis. In subsequent spatial motion units, without exceeding preset current, acceleration, and / or speed limits, the system gradually compensates for the spatial deviation by adjusting the motion speed of the motion axis. For example, by fine-tuning the feed rate or acceleration of the motion axis, it allows it to "catch up" with the progress of other motion axes in subsequent spatial motion units, ensuring that its actual motion progress is consistent with the progress of other motion axes, thereby guaranteeing the accuracy of the overall machining trajectory.

[0086] In some preferred embodiments, for example, a three-axis linkage direct-drive turret machine is machining a complex curved surface. In a certain spatial motion unit, the X-axis suddenly encounters a region with high material hardness during cutting, causing its motor current to increase instantaneously. The time to complete the current spatial motion unit is 50 milliseconds longer than that of the Y-axis and Z-axis. The system first acquires the target displacement of the current spatial motion unit, the material properties data of the material to be processed (e.g., stainless steel), and the real-time operating data of the X, Y, and Z axes (including motor current, position feedback, etc.). Based on this, it determines that the 50-millisecond delay is caused by an instantaneous increase in local cutting load encountered by the X-axis in the current spatial motion unit, and that this delay (50 milliseconds) is within a preset tolerance period (e.g., 100 milliseconds). At this time, although the Y-axis and Z-axis have completed the movement of the current spatial motion unit, they will wait for the X-axis to complete. After the preset tolerance period expires, they will synchronously receive the target displacement corresponding to the next spatial motion unit and start the movement. The system simultaneously calculates the minute spatial deviation generated by the 50-millisecond delay of the X-axis, and in several subsequent spatial motion units, without exceeding the preset current, acceleration and speed limits of the X-axis, it fine-tunes the X-axis motion speed, for example, by slightly increasing its feed rate, so that the X-axis gradually catches up with the progress of the Y-axis and Z-axis in subsequent motions, ultimately eliminating the spatial deviation and ensuring the continuity and accuracy of the machining trajectory.

[0087] In another embodiment of this application, it is further proposed that, after S3300, the following is also included:

[0088] S3310: Perform trend analysis on the operating data of each motion axis. Based on the results of the trend analysis, when the operating data of a certain motion axis shows continuous changes in multiple spatial motion units and exceeds the corresponding preset normal fluctuation threshold, the motion axis is identified as a motion axis with progressively degraded performance. The operating data includes completion time, motor current and / or position error.

[0089] S3320: Reduces the priority of motion axes with progressive performance degradation in motion coordination, and adaptively adjusts the sending time of the start command of the next spatial motion unit according to the adjusted priority, so that other motion axes without progressive performance degradation are given priority as the motion axes with the longest completion time under the preset non-transient delay waiting threshold constraint, and are used to determine the time reference.

[0090] S3330: Generates appropriate performance compensation or maintenance operation suggestions based on the type of gradual performance degradation.

[0091] Specifically, trend analysis of the operational data of each motion axis refers to the system continuously collecting operational data of each motion axis as it completes each spatial motion unit, such as completion time, motor current, and / or position error, and performing time series analysis to identify slow, cumulative changes over time, rather than instantaneous fluctuations. The completion time is the time required for the motion axis to complete one spatial motion unit; the motor current is the current of the motor driving the motion axis during operation; and the position error is the deviation between the actual position and the target position of the motion axis. These operational data can be used individually or in combination to comprehensively assess the health status of the motion axes.

[0092] When the operating data of a certain motion axis exhibits continuous changes across multiple spatial motion units and exceeds the corresponding preset normal fluctuation threshold, that motion axis is identified as a motion axis with progressively deteriorating performance. Continuous change means that the data no longer fluctuates randomly, but shows a stable upward or downward trend, such as a continuous increase in motor current, a continuous increase in completion time, or a continuous increase in position error. The preset normal fluctuation threshold is set based on the machine tool's historical operating data and design specifications, and is used to distinguish between slight fluctuations caused by normal wear or environmental changes and substantial performance degradation.

[0093] After identifying motion axes with progressively degraded performance, the system lowers their priority in motion coordination, prioritizing motion axes with normal performance when determining the time reference. Specifically, by adjusting the priority, the system adaptively adjusts the sending time of the next spatial motion unit start command, so that other motion axes without progressively degraded performance, under a preset non-transient delay waiting threshold constraint, are prioritized as the motion axes with the longest completion time for determining the time reference. This avoids a single motion axis "dragging down" the overall efficiency for a long time, while ensuring the smoothness of motion coordination.

[0094] Based on the type of progressive performance degradation, the system generates corresponding performance compensation or maintenance operation suggestions. For example, when trend analysis indicates a continuous increase in motor current, it can be determined that there may be bearing wear or insufficient lubrication, and lubrication maintenance or bearing replacement is recommended; when the position error continues to increase, it may indicate encoder failure or servo parameter drift, and parameter calibration or inspection of relevant components is recommended. Through the above-mentioned preventive or predictive maintenance, potential faults can be intervened at an early stage, extending equipment life and maintaining machining accuracy. This application is thus able to identify progressive performance degradation problems that are difficult to capture by traditional mechanisms that only deal with instantaneous delays.

[0095] In another embodiment of this application, S3330 further includes the following steps:

[0096] S3331: Preprocess the running data of the motion axis with progressively degrading performance when completing each spatial motion unit to obtain a set of running data features that reflect the current running state of the corresponding motion axis;

[0097] S3332: Predefine and store operational data feature patterns associated with different physical causes, and construct a physical cause feature pattern library from the operational data feature patterns;

[0098] S3333: Match the current motion state's running data feature set with the physical cause feature pattern library, and determine the physical cause that best matches the running data feature set by calculating the similarity and / or deviation between the current running data feature set and each running data feature pattern;

[0099] S3334: When multiple motion axes exhibit a progressive performance degradation trend simultaneously, analyze the motion correlation and load transfer relationship between each motion axis. If it is determined that the progressive performance degradation of the first motion axis leads to an increase in the completion time of the second motion axis, and the similarity between the running data feature set of the second motion axis and any running data feature pattern is less than a preset similarity threshold and / or the deviation is greater than a preset deviation threshold, exclude the determination that the second motion axis itself has a progressive performance degradation, attribute the increase in the completion time of the second motion axis to the progressive performance degradation of the first motion axis, and achieve an independent attribution result for the physical cause of the progressive performance degradation of each motion axis.

[0100] S3335: Determine the type of progressive performance degradation based on the physical causes obtained from the independent attribution results, and generate performance compensation or maintenance operation recommendations corresponding to the physical causes for the motion axes with progressive performance degradation.

[0101] Specifically, preprocessing the operational data of motion axes with progressively degrading performance refers to extracting key information characterizing the current operational state of the motion axis from the raw operational data, forming an operational data feature set. This feature set can include, but is not limited to, statistical features (such as mean, variance, kurtosis, and skewness), frequency domain features (such as the spectral energy distribution after Fourier transform), time domain features (such as autocorrelation function and waveform factor), and features extracted based on models (such as wavelet analysis and empirical mode decomposition). Preprocessing can employ techniques such as data cleaning, normalization, and dimensionality reduction (such as principal component analysis (PCA) and linear discriminant analysis (LDA)) to eliminate noise, reduce redundancy, and highlight key information.

[0102] This involves pre-defining and storing operational data feature patterns associated with different physical causes, and constructing a physical cause feature pattern library. This refers to establishing a mapping relationship between different physical faults (such as bearing wear, increased lead screw backlash, motor winding aging, driver parameter drift, and insufficient lubrication) and specific operational data feature sets based on historical data analysis, expert experience, and fault diagnosis model training. Each feature pattern represents a typical fault type, describing its typical manifestation on the operational data feature set. The physical cause feature pattern library can be viewed as a multi-dimensional vector space, where each vector corresponds to a feature pattern of a physical cause.

[0103] In practical applications, the current motion data feature set is matched against a physical cause feature pattern library. By calculating the similarity and / or deviation between the current motion data feature set and each motion data feature pattern, the physical cause that best matches the motion data feature set is determined. A match is determined when the similarity is greater than or equal to a preset similarity threshold; a match is determined when the deviation is less than or equal to a preset deviation threshold; otherwise, a mismatch is determined. The threshold can be set based on historical data statistics / experience. Matching can employ distance-based algorithms (such as Euclidean distance, Mahalanobis distance), similarity-based algorithms (such as cosine similarity), machine learning classifiers (such as support vector machines (SVM), neural networks (NN), decision trees (DT), or clustering algorithms. By quantifying the distance or similarity between the current feature set and each pattern, the physical cause most likely to cause current performance degradation is identified.

[0104] Furthermore, when multiple motion axes exhibit a progressive performance degradation trend simultaneously, independent attribution of faults in a multi-axis linkage system can be achieved by analyzing the motion correlation and load transfer relationships between each motion axis. Motion correlation can be determined by combining machine tool mechanical structure, kinematic model, control logic, and historical operating data. For example, whether two motion axes frequently coordinate during machining, or whether a load change on one axis is transmitted to the other axis through the workpiece or tool. Load transfer relationships can be evaluated using force sensor, torque sensor, or motor current data. When it is determined that the progressive performance degradation of the first motion axis leads to an increase in the completion time of the second motion axis, and the similarity between the operating data feature set of the second motion axis and any operating data feature pattern is less than a preset similarity threshold and / or the deviation is greater than a preset deviation threshold, the determination that the second motion axis itself has a progressive performance degradation can be ruled out. The increase in the completion time of the second motion axis can be attributed to the progressive performance degradation of the first motion axis, thereby achieving independent attribution of the physical causes of the progressive performance degradation of each motion axis and avoiding misdiagnosis.

[0105] Based on this, the type of progressive performance degradation is determined according to the physical causes obtained from the independent attribution results, and performance compensation or maintenance operation suggestions are generated for the motion axis with progressive performance degradation, corresponding to the physical causes. Performance compensation may include adjusting the control parameters of the motion axis (such as PID gain, feedforward compensation), software-level error compensation (such as backlash compensation, nonlinear error compensation), etc.; maintenance operation suggestions may include replacing worn parts, relubricating, tightening loose connections, and providing maintenance cycle suggestions and a list of required spare parts, etc.

[0106] In some preferred embodiments, for example, after a three-axis linkage direct drive turret machine has been running for a long time, both the X-axis and Y-axis exhibit a progressive performance decline trend with increasing completion time. By preprocessing the X-axis operating data (such as motor current, position error, vibration signal), an operating data feature set is obtained and matched with a physical cause feature pattern library. It is found that the X-axis feature set highly matches the feature pattern of "X-axis ball screw wear". The same processing is then performed on the Y-axis operating data, and its feature set does not match the results when the similarity between it and any known physical cause feature pattern is less than a preset similarity threshold and / or the deviation is greater than a preset deviation threshold. At this point, the system further analyzes the motion correlation and load transmission relationship between the X-axis and Y-axis. Based on the machine tool structure model and historical machining data, it is found that the increased motion resistance of the X-axis (caused by ball screw wear) will increase the load on the Y-axis through the workpiece or tool in a specific motion segment, thereby leading to an increase in the Y-axis completion time. This eliminates the possibility of gradual performance degradation of the Y-axis itself, attributing the increase in Y-axis completion time to wear of the X-axis ball screw, and generating maintenance operation suggestions such as "recommend replacing the X-axis ball screw and recalibrating the X-axis," thereby avoiding unnecessary inspections or repairs of the Y-axis and improving maintenance efficiency and accuracy.

[0107] In another embodiment of this application, a method for discretizing a machining trajectory into multiple spatial motion units arranged sequentially along the machining trajectory is further proposed, specifically including:

[0108] S1100: Based on the curvature change of the machining trajectory at each position, the corresponding feed speed command, and the preset upper limit of contour error, the initial spatial length of each spatial motion unit on the machining trajectory is adaptively determined so that the contour error generated by linear approximation within any spatial motion unit does not exceed the preset upper limit of contour error.

[0109] S1200: Under the speed limit constraints of each motion axis, the initial space length is corrected to obtain the target space length of each spatial motion unit.

[0110] Specifically, the curvature changes of the machining trajectory at various locations reflect the geometric complexity of the trajectory: the greater the curvature, the more curved the trajectory. To ensure machining accuracy, the length of the spatial motion unit should be smaller to more precisely approximate the curve. The feed rate command reflects the dynamic requirements of machining. Under the constraint of a preset upper limit for contour error, a higher feed rate places higher demands on discretization accuracy, while within the allowable accuracy range, it is desirable to lengthen the spatial motion unit as much as possible to maintain machining efficiency. The preset upper limit for contour error limits the maximum allowable geometric deviation when a straight line approximates a curve. The system integrates curvature changes, feed rate commands, and the upper limit for contour error, adaptively calculating the initial spatial length of each spatial motion unit to ensure that the maximum contour error generated by straight-line approximation within any spatial motion unit does not exceed the upper limit for contour error. The determination of the initial spatial length is a dynamic adjustment process. Under the premise of meeting accuracy constraints, the unit length is increased as much as possible to avoid excessive discretization. This can be achieved through iterative calculation or by looking up a table based on a predefined model.

[0111] Furthermore, after obtaining the initial spatial length, the system corrects the initial spatial length under the speed limit constraints of each motion axis. Even if the upper limit of contour error is met geometrically, if the initial spatial length of a certain spatial motion unit is too large, one or more motion axes may need to exceed their maximum allowable speed to complete the unit within a given machining cycle, which is detrimental to motion coordination and smoothness. Therefore, the system reduces the initial spatial length as necessary based on the maximum allowable speed of each motion axis, so that all motion axes can complete the corresponding displacement within their respective speed limits, ultimately obtaining the target spatial length that simultaneously satisfies geometric accuracy and kinematic constraints.

[0112] In some preferred embodiments, for example, it is necessary to process a complex part contour that includes straight segments, large-radius arcs, and small-radius arcs. First, the system acquires the processing trajectory and analyzes it according to a preset upper limit for contour error (e.g., 0.01mm) and the current feed rate command: When processing straight segments, since the curvature change is close to zero, the system adaptively determines a relatively long initial spatial length, such as 5mm, at which point the contour error of the straight approximation is much less than 0.01mm; when entering the large-radius arc segment, the curvature increases, and the system adjusts the initial spatial length to a medium length, such as 2mm, based on the curvature change and the upper limit for contour error, still ensuring that the contour error does not exceed 0.01mm; when reaching the small-radius arc segment (e.g., R=1mm), the curvature increases sharply, and the system further reduces the initial spatial length, such as 0.5mm, to accurately approximate the high-curvature region, ensuring that the contour error is strictly controlled within 0.01mm. After determining the initial spatial length, the system checks whether each motion axis (e.g., X-axis, Y-axis, Z-axis) will exceed the maximum allowable speed when completing the corresponding spatial motion unit at the current feed rate. If it is found that a certain 0.5mm spatial motion unit requires a certain axis speed to exceed its maximum allowable speed within a given machining cycle, the initial 0.5mm spatial length is corrected, for example, shortened to 0.4mm, so that all motion axes can smoothly complete the unit displacement within their respective speed limits, and finally obtain the target spatial length that meets the accuracy and speed constraints.

[0113] In another embodiment of this application, after generating performance compensation or maintenance operation suggestions corresponding to physical causes for motion axes with progressively degraded performance, the method further includes:

[0114] S3336-1: Obtain the current machine tool's production plan information, which includes at least the priority and deadline of the tasks to be processed;

[0115] S3336-2: Based on the physical causes obtained from the independent attribution results and the corresponding degree of performance degradation, determine the type of maintenance operation required for performance compensation or maintenance operation recommendations and the estimated time required to perform the maintenance operation;

[0116] S3336-3: Obtain inventory information for spare parts required to perform maintenance operations;

[0117] S3336-4: Obtain availability information for the specialized tools required to perform maintenance operations;

[0118] S3336-5: Obtain the scheduling information of maintenance personnel with the skills required to perform maintenance operations;

[0119] S3336-6: Compare the maintenance operation type and estimated time with the production plan information, perform a conflict analysis between the maintenance operation and the production plan, and obtain the conflict analysis results;

[0120] S3336-7: When the conflict analysis results indicate that there is a time conflict between maintenance operations and high-priority tasks to be processed in the production plan, and spare parts, special tools are unavailable or maintenance personnel are insufficient, an alternative maintenance strategy is generated. The alternative maintenance strategy includes at least adjusting the execution time of some tasks to be processed in the production plan, adjusting the execution time of maintenance operations, and / or, under the premise of not being lower than the preset processing accuracy requirements, temporarily adjusting the motion parameters of the relevant motion axes based on performance compensation or performance compensation measures in the maintenance operation recommendations.

[0121] S3336-8: Generate comprehensive maintenance recommendation information that includes maintenance operation type, estimated time, spare parts and their inventory information, special tools and their availability, maintenance personnel scheduling information, recommended execution time, and alternative maintenance strategies.

[0122] Specifically, obtaining the current machine tool production plan information means that the system automatically extracts detailed information about the currently executing or about to be executed processing tasks from the production management system or MES (Manufacturing Execution System). This includes the unique identifier of each task, product model, quantity, expected start and end times, priority in the entire production process (e.g., urgent orders, regular orders, etc.), and final delivery deadline, providing basic data for conflict analysis between subsequent maintenance plans and production plans.

[0123] Based on the physical causes obtained from independent attribution results and the corresponding degree of performance degradation, the maintenance operation type and estimated time are determined. This means that after identifying the specific physical causes of the progressive performance degradation of the motion axis (such as bearing wear, insufficient lubrication, motor aging, etc.), the system automatically matches a suitable maintenance operation plan based on a preset knowledge base or expert experience system, such as "bearing wear → replace bearing" or "insufficient lubrication → supplement or replace lubricant". The estimated time of the maintenance operation is estimated based on historical data or standard working hours, including preparation time, execution time and verification time.

[0124] Obtaining inventory information of spare parts required for maintenance operations, availability information of special tools, and scheduling information of maintenance personnel refers to the system querying the inventory management system in real time to confirm the current inventory quantity of required spare parts (such as specific models of bearings, seals, etc.); checking whether special tools (such as special disassembly tools, calibration equipment, etc.) are available (not occupied and not under maintenance); and retrieving the scheduling and available time of maintenance personnel with corresponding skills (such as mechanics, electrical engineers, etc.) from the maintenance personnel management system to assess the feasibility of maintenance operations at the resource level.

[0125] The system compares maintenance operation types and estimated time durations with production plan information to perform conflict analysis between maintenance operations and the production plan. This involves overlaying planned maintenance operations (including their types and estimated time durations) with current and future production tasks on a timeline and comparing whether the maintenance period overlaps with the machine usage time of high-priority tasks. For example, if a high-priority task needs to be completed within the next 24 hours, but the planned maintenance operation requires 8 hours of use on the same machine, a time conflict is identified, thus quantifying the potential impact of maintenance on production progress.

[0126] When conflict analysis results indicate a time conflict between maintenance operations and high-priority tasks in the production plan, and spare parts, special tools, or maintenance personnel are unavailable, an alternative maintenance strategy is generated. This means that when directly executing maintenance according to the original plan is not feasible, the system intelligently generates multiple alternative solutions. Alternative maintenance strategies include at least: adjusting the execution time of some tasks in the production plan (e.g., postponing non-urgent tasks to free up machine tool time for maintenance); adjusting the execution time of maintenance operations (e.g., scheduling them during production breaks or non-production hours at night); and, under the premise of not falling below the preset machining accuracy requirements, temporarily adjusting the motion parameters of relevant motion axes based on performance compensation or maintenance operation suggestions. These performance compensation or maintenance operation suggestions include performance compensation measures and / or maintenance operation measures. Performance compensation measures are used to achieve performance compensation during the machining process by temporarily adjusting the motion parameters of relevant motion axes, such as temporary parameter adjustments, progressive compensation within speed / acceleration constraints, and feedforward / error compensation, under the premise of not falling below the preset machining accuracy requirements. Maintenance operation measures are used to restore performance through maintenance actions such as inspection, replacement, and calibration. Slight performance degradation can be offset by software compensation, allowing production to be maintained temporarily without shutdown.

[0127] Generating comprehensive maintenance recommendation information, which includes maintenance operation type, estimated time, spare parts and their inventory information, special tools and their availability, maintenance personnel scheduling information, suggested execution time, and alternative maintenance strategies, refers to the system summarizing the above analysis results and resource information and outputting them in the form of reports or visualization interfaces. The comprehensive maintenance recommendation information includes not only the original maintenance operation suggestions, but also a list of required resources and their status, estimated time, conflict points with the current production plan, and corresponding alternative maintenance strategies. It also provides a suggested execution time window based on conflict analysis and resource availability, serving as a direct basis for maintenance decisions.

[0128] The solution proposed in this application deeply integrates maintenance operation recommendations for progressively degrading motion axes with actual production constraints such as production planning information, spare parts inventory, availability of special tools, and maintenance personnel scheduling. This solves the problem of simply providing "how to maintain it technically" without connecting it to production operations.

[0129] In another embodiment of this application, prior to S3336-8, the following is further included:

[0130] S3336-801: For each alternative maintenance scheme determined in the alternative maintenance strategy, obtain the time impact data of each alternative maintenance scheme on the completion time of the tasks to be processed in the production plan, the material consumption data of the maintenance operation, the manpower consumption data of the maintenance operation, and the life impact data of the machine tool components related to the maintenance operation type corresponding to the alternative maintenance scheme after the execution of the alternative maintenance scheme.

[0131] S3336-802: Calculate the productivity loss value for each alternative maintenance option based on time impact data;

[0132] S3336-803: Calculate the total maintenance cost for each alternative maintenance plan based on material consumption data and manpower consumption data;

[0133] S3336-804: Calculate the equipment health impact value for each alternative maintenance option based on lifespan impact data;

[0134] S3336-805: The production efficiency loss value, total maintenance cost value and equipment health impact value corresponding to each alternative maintenance plan are weighted to obtain the comprehensive evaluation value of each alternative maintenance plan;

[0135] S3336-806: The alternative maintenance solution with the best comprehensive evaluation value shall be determined as the recommended alternative maintenance solution, and the maintenance operation type and recommended execution time corresponding to the recommended alternative maintenance solution shall be integrated into the comprehensive maintenance recommendation information.

[0136] Specifically, before generating comprehensive maintenance recommendations, a quantitative assessment of each alternative maintenance scheme within the alternative maintenance strategy is required. First, the system acquires data on the expected time impact of each alternative maintenance scheme on the completion time of tasks in the production plan, such as task delay duration, production interruption duration, or percentage reduction in production capacity, to assess the degree of disruption to production schedule. Simultaneously, it acquires data on the expected material consumption (spare parts types, quantities, and costs) and manpower consumption (maintenance personnel working hours, skill requirements, and labor costs) required for the maintenance operation, as well as the lifespan impact data on the expected lifespan of machine tool components (including but not limited to ball screws, linear guides, bearings, servo motors, and turret transmission mechanisms) related to the maintenance operation type corresponding to the alternative maintenance scheme, such as changes in remaining lifespan or wear acceleration / deceleration, to measure the long-term health impact of the scheme on the equipment.

[0137] The process includes calculating the productivity loss for each alternative maintenance plan based on time impact data. For example, if time impact data indicates that a plan will cause a high-priority task to be delayed by X hours, the corresponding productivity loss can be calculated based on the task's output per unit time. The total maintenance cost, including spare parts procurement costs, labor costs, and other direct or indirect costs, is calculated based on material and labor consumption data. Finally, the equipment health impact value is calculated based on lifespan impact data to reflect the positive or negative impact of the plan on the long-term operational stability and reliability of the equipment. For example, a positive impact is demonstrated by extending the lifespan of critical components and reducing the risk of failure, while a negative impact is demonstrated by shortening the lifespan through only temporary repairs.

[0138] Furthermore, the production efficiency loss value, total maintenance cost value, and equipment health impact value corresponding to each alternative maintenance plan are weighted to obtain a comprehensive evaluation value for each alternative maintenance plan. The weighting process involves calculating the three evaluation values ​​comprehensively based on preset or dynamically adjusted weight coefficients. For example, when production tasks are urgent, the weight of the production efficiency loss value can be increased; when equipment health is poor, the weight of the equipment health impact value can be increased; and when cost pressures are high, the weight of the total maintenance cost value can be appropriately increased. The alternative maintenance plan with the optimal comprehensive evaluation value is determined as the recommended alternative maintenance plan, and its corresponding maintenance operation type and suggested execution time are integrated into the final comprehensive maintenance recommendation information, providing users with a clear decision-making basis.

[0139] As a specific implementation method, suppose one motion axis of a multi-axis linkage direct-drive turret machine is identified as having progressively degraded performance. Based on its physical causes, the system generates two alternative maintenance strategies: Option 1: Perform temporary lubrication and parameter fine-tuning, estimated to take 2 hours. This will not affect the deadline of the current high-priority task, but may shorten the lifespan of critical components by 5%. Material consumption includes lubricant and a small amount of consumables, and manpower consumption is 1 person for 2 hours. Option 2: Schedule a small-scale shutdown for maintenance, replacing worn parts. This is estimated to take 8 hours, which will affect the completion time of the current high-priority task, but will restore the lifespan of critical components to normal levels. Material consumption includes spare parts and consumables, and manpower consumption is 2 people for 8 hours.

[0140] According to the scheme of this application, the system evaluates the two alternative maintenance schemes mentioned above: First, it obtains time impact data, with Scheme 1 having a delay of 0 hours and Scheme 2 having a delay of 6 hours for high-priority tasks; Second, it obtains material consumption data and manpower consumption data, with Scheme 1 having lower material and manpower costs and Scheme 2 having higher material and manpower costs; Third, it obtains lifespan impact data, with Scheme 1 having a 5% reduction in the lifespan of critical components and Scheme 2 having the lifespan of critical components return to normal.

[0141] Based on this, the system calculates various evaluation values: Option 1 has a low production efficiency loss value (close to 0), a low total maintenance cost value, and a negative equipment health impact value (shortened lifespan); Option 2 has a high production efficiency loss value (due to task delays), a high total maintenance cost value, and a positive equipment health impact value (lifespan recovery). Subsequently, the system weights these evaluation values, for example, increasing the weight of the production efficiency loss value when the current production task has a very high priority, and increasing the weight of the equipment health impact value when the equipment is nearing the end of its lifespan. For example, the comprehensive evaluation value for Option 1 can be set as: 0.1 * production efficiency loss value + 0.3 * total maintenance cost value + 0.6 * equipment health impact value; the comprehensive evaluation value for Option 2 can be set as: 0.5 * production efficiency loss value + 0.2 * total maintenance cost value + 0.3 * equipment health impact value, and the respective comprehensive evaluation results are calculated based on the actual weights and values.

[0142] By comparing comprehensive evaluation values, if the comprehensive evaluation value of Option 1 is better than Option 2 when the current production task is urgent and the equipment lifespan can be slightly shortened, the system will definitely recommend Option 1 as the alternative maintenance plan and integrate its maintenance operation type (temporary lubrication and parameter fine-tuning) and suggested execution time into the comprehensive maintenance recommendation information. Conversely, in scenarios where production pressure is relatively controllable and long-term equipment health is of greater importance, if the comprehensive evaluation value of Option 2 is better, then Option 2 will be recommended. Through the above evaluation and optimization process, this application transforms maintenance decision-making from experience-based to data-driven and quantitative, significantly improving the scientific nature and interpretability of maintenance decisions.

[0143] In another embodiment of this application, S3336-805 specifically includes:

[0144] A1: Obtain the priority of the current machining task, the real-time load status of each motion axis of the machine tool, and the historical performance impact data of historical maintenance operations on equipment performance;

[0145] A2: Adjust the weight of production efficiency loss in the overall evaluation based on the priority of the current processing task;

[0146] A3: Adjust the weight of the equipment health impact value in the comprehensive evaluation based on the real-time load status of each motion axis of the machine tool;

[0147] A4: Adjust the weight of total maintenance cost in the comprehensive evaluation based on historical performance impact data;

[0148] A5: Based on the adjusted weights of production efficiency loss, total maintenance cost, and equipment health impact, the production efficiency loss, total maintenance cost, and equipment health impact corresponding to each alternative maintenance plan are weighted to obtain a comprehensive evaluation value for each alternative maintenance plan.

[0149] The priority of current processing tasks can be understood as the importance of the currently executing or about-to-be-executed processing task within the overall production plan. For example, it can be categorized as high, medium, and low, reflecting the urgency and criticality of the production tasks. The real-time load status of each motion axis of the machine tool refers to the actual working load on each motion bearing of the machine tool at the current moment, obtained by monitoring parameters such as motor current, torque, and vibration. This reflects the current workload and potential wear risks of the machine tool. Historical performance impact data of maintenance operations refers to records of the actual impact of past maintenance operations on the machine tool's accuracy, efficiency, lifespan, and other performance characteristics. This data provides a basis for cost-benefit assessments of future maintenance operations.

[0150] Specifically, when the current processing task has a high priority, the weight of the production efficiency loss value in the comprehensive evaluation is increased to prioritize production continuity and efficiency in maintenance decisions, avoiding delays in high-priority tasks caused by maintenance operations. When the real-time load status of each motion axis of the machine tool is high and the equipment is operating under high pressure, the weight of the equipment health impact value is increased, making the system more inclined to select maintenance schemes that are more beneficial to equipment health, thereby extending equipment life and reducing the risk of future failures. When historical maintenance data shows that some maintenance operations are costly but effective, or that some low-cost maintenance operations are ineffective, the weight of the total maintenance cost value in the comprehensive evaluation can be adjusted accordingly, so that the maintenance cost weight more accurately reflects whether the expenditure is worthwhile. Through the above dynamic adjustment mechanism, the comprehensive evaluation value can more accurately reflect the optimal maintenance strategy under the current production environment and equipment status.

[0151] In some preferred embodiments, assuming that during the operation of a multi-axis linkage direct-drive turret machine, its X-axis is identified as exhibiting a progressive performance degradation trend, requiring maintenance, the system generates two alternative maintenance schemes:

[0152] Option A: Perform localized lubrication and parameter fine-tuning during the interval between the next low-priority tasks. This is expected to result in lower production efficiency loss and lower total maintenance cost, but with a moderate impact on equipment health.

[0153] Option B: Arrange a major shutdown for overhaul to replace key worn parts. The expected production efficiency loss and total maintenance cost are high, but the impact on equipment health is low.

[0154] Under traditional static weighted evaluation, the weights of production efficiency loss, total maintenance cost, and equipment health impact are assumed to be 0.4, 0.3, and 0.3, respectively. If the machine tool is currently executing a high-priority urgent order, and the real-time load status of the X-axis indicates that it is close to overload, then according to the scheme of this application, the system first identifies the current machining task as high priority and adjusts the weight of the production efficiency loss value from 0.4 to 0.6; due to the high real-time load status of the X-axis, the weight of the equipment health impact value is adjusted from 0.3 to 0.4; assuming that historical maintenance data indicates similar poor local lubrication effects, the weight of the total maintenance cost value is adjusted from 0.3 to 0.2 (the weights can be normalized in the specific implementation). At this time, the comprehensive evaluation value of the two schemes is recalculated:

[0155] The overall assessment value of Option A = Production efficiency loss * 0.6 + Total maintenance cost * 0.2 + Equipment health impact * 0.4

[0156] The overall evaluation value of Option B = Production efficiency loss * 0.6 + Total maintenance cost * 0.2 + Equipment health impact * 0.4

[0157] Under high-priority and high-load conditions, the system, with the aforementioned weight configuration, may yield a better overall evaluation value for Option B than Option A. This means that although Option B has higher downtime costs, it provides better long-term equipment health protection. Furthermore, in this scenario, continuing to use ineffective local lubrication is more likely to trigger failures at critical moments and cause greater production losses. Therefore, the system will tend to choose Option B. This contrasts with the result where static weights might favor Option A, demonstrating the ability of the proposed solution to optimize maintenance decisions through adaptive weight adjustment in complex dynamic environments.

[0158] In another embodiment of this application, it is further proposed that, after A3, it also includes:

[0159] A31: Real-time comparison of multiple load-related sensor data on the same motion axis. When the data deviation of a certain load-related sensor data relative to other load-related sensor data on the same axis and / or relative to the historical normal operation data corresponding to that load-related sensor data exceeds a preset deviation threshold, the corresponding load-related sensor data is marked as abnormal data.

[0160] A32: Perform sequence integrity verification on the received load-related sensor data based on timestamps. When a data arrival delay or data packet loss is detected, the corresponding load-related sensor data is marked as delayed data or incomplete data.

[0161] A33: When all load-related sensor data for a certain motion axis are marked as abnormal data, the historical load status data of that motion axis is called to make a short-term prediction and generate predicted load status data for load status assessment.

[0162] A34: When load-related sensor data is continuously marked as lagging data in multiple consecutive sampling periods and its time delay exceeds a preset delay threshold, time compensation is performed on the load status assessment results obtained based on the corresponding load-related sensor data.

[0163] A35: When adjusting the weight of the equipment health impact value based on the load status assessment results after time compensation, the abnormal data, lag data and / or incomplete data are weighted and attenuated according to the abnormal data marking and / or lag data marking of the load-related sensor data, and the upper limit of the weight adjustment range of the equipment health impact value is set in combination with the duration of data abnormality or lag.

[0164] Specifically, real-time comparison of data from multiple load-related sensors on the same motion axis is performed. Cross-validation using redundant information allows for the timely detection of potential faults or abnormal readings in individual sensors. For example, a motion axis can be configured with multiple force sensors, torque sensors, or current sensors. Under normal operating conditions, these sensors should exhibit interconnected data patterns that conform to physical laws. When the data from a particular sensor deviates significantly from the data of other sensors on the same axis and / or from its historical normal operating data, exceeding a preset deviation threshold, the data is considered unreliable and marked as abnormal data. The preset deviation threshold can be set based on the machine tool model, sensor accuracy, machining process requirements, and historical data statistical analysis results.

[0165] Specifically, the received load-related sensor data undergoes sequence integrity verification based on timestamps to ensure the timing and integrity of the data. During data transmission, sensor data packets may arrive late or be lost due to network congestion, communication failures, or system processing delays. By checking the timestamps of the data packets, it can be determined whether the data arrived in the expected order and whether any data is missing. When a data arrival delay or data packet loss is detected, the corresponding load-related sensor data is marked as delayed or incomplete data for subsequent differentiation and processing.

[0166] In practical applications, when all load-related sensor data for a certain motion axis are marked as abnormal, it indicates that the current real-time data cannot reliably reflect the load status of that motion axis. In this case, to avoid evaluation interruption or erroneous results, historical load status data of that motion axis is retrieved and combined with machine learning algorithms or statistical models for short-term prediction, generating predicted load status data as a temporary, alternative basis for load status assessment to maintain the continuity of system operation.

[0167] Furthermore, when load-related sensor data is continuously marked as lagging data for multiple consecutive sampling periods and its time delay exceeds a preset delay threshold, it indicates a significant time difference between real-time data and the actual physical state. To make the load state assessment results closer to the current real state, time compensation is needed for the assessment results obtained based on these lagging data. This can be achieved through interpolation, extrapolation, or by combining kinematic models to correct the assessment results based on the delay time, making them reflect the load state as accurately as possible. In addition, when adjusting the weights of the equipment health impact values ​​based on the time-compensated load state assessment results, to avoid excessive negative impacts from abnormal or lagging data on weight adjustments, these data can be weighted and attenuated. That is, data marked as abnormal, lagging, or incomplete data is assigned lower weights when calculating the load state assessment results and corresponding weight adjustments. Furthermore, an upper limit is set on the weight adjustment range of the equipment health impact values ​​based on the duration of data abnormality or lag, preventing excessive fluctuations in weights when data quality is poor, thus ensuring the stability and rationality of the system.

[0168] Reference Figure 2 The specific embodiments of this application also disclose a precision motion control system for a multi-axis linkage direct drive turret crane, including:

[0169] The trajectory decomposition module 1 is used to obtain the machining trajectory to be executed, discretize the machining trajectory into multiple spatial motion units arranged sequentially along the machining trajectory, and determine the target displacement of each motion axis in the corresponding spatial motion unit.

[0170] Motion execution module 2 is used to receive the completion signal of the corresponding motion axis after the target displacement is completed;

[0171] The motion initiation module 3 is used to coordinate motion after determining the target displacement of the motion axis participating in the current spatial motion unit based on the completion signal. It obtains the completion time of each motion axis from the start of participating in the current spatial motion unit to the issuance of the completion signal, and uses the completion time of the motion axis with the longest completion time as the time reference to send the target displacement of the next spatial motion unit to each motion axis, so as to start the motion of each motion axis to the next spatial motion unit.

[0172] This embodiment of the system effectively integrates functions such as discretization of the machining trajectory, determination of the target displacement of the motion axis, reception of motion completion signals, motion coordination based on the longest completion time, and initiation of the next motion unit through modular design.

[0173] The above description is merely an embodiment of this application and is not intended to limit the scope of protection of this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of protection of this application.

Claims

1. A precision motion control method for a multi-axis linkage direct-drive turret crane, characterized in that, include: The machining trajectory to be executed is obtained, the machining trajectory is discretized into multiple spatial motion units arranged sequentially along the machining trajectory, and the target displacement of each motion axis in the corresponding spatial motion unit is determined. Receive the completion signal of the corresponding motion axis after the target displacement is completed; After determining the target displacement amount of the motion axis participating in the current spatial motion unit based on the completion signal, motion coordination is performed to obtain the completion time of each motion axis from the start of participating in the current spatial motion unit to the issuance of the completion signal. The completion time of the motion axis with the longest completion time is used as the time reference to send the target displacement amount corresponding to the next spatial motion unit to each motion axis, so as to start the motion of each motion axis to the next spatial motion unit. After determining the target displacement amount corresponding to the motion axis participating in the current spatial motion unit based on the completion signal, motion coordination is performed. The completion time of each motion axis from the start of participation in the current spatial motion unit to the issuance of the completion signal is obtained. Using the completion time of the motion axis with the longest completion time as the time reference, the target displacement amount corresponding to the next spatial motion unit is sent to each of the motion axes to initiate the motion of each motion axis towards the next spatial motion unit, including: Acquire the target displacement, material property data of the material to be processed, and operation data of each motion axis corresponding to the current spatial motion unit and subsequent spatial motion units; When it is determined that the completion time of at least one motion axis is delayed relative to other motion axes based on the completion time from the start of participation in the current spatial motion unit to the issuance of the completion signal, the delay is determined based on the target displacement corresponding to the current spatial motion unit, the material property data, and the operation data, whether the delay is caused by an increase in the instantaneous local cutting load encountered by the motion axis in the current spatial motion unit and is within a preset tolerance period. When the delay is caused by an increase in instantaneous local cutting load and is within a preset tolerance period, the completion time of the motion axis with the longest completion time is used as the time reference. The motion axis that has completed the target displacement in the current spatial motion unit receives the target displacement corresponding to the next spatial motion unit and starts the motion of the next spatial motion unit after the preset tolerance period expires. The spatial deviation is determined for the motion axis with the delay based on its delay time. In subsequent spatial motion units, the spatial deviation is gradually compensated by adjusting the motion speed of the motion axis with the delay, provided that the preset current, acceleration and / or speed limits are not exceeded, so that the actual motion progress of the motion axis with the delay is consistent with the motion progress of other motion axes again.

2. The precision motion control method for a multi-axis linkage direct-drive turret machine according to claim 1, characterized in that, Using the completion time of the longest-completion motion axis as the time reference, after the motion axis that has completed the target displacement within the current spatial motion unit receives the target displacement corresponding to the next spatial motion unit and starts motion on the next spatial motion unit after waiting for the preset tolerance period to expire, the method further includes: Trend analysis is performed on the operating data of each motion axis. Based on the results of the trend analysis, when the operating data of a certain motion axis shows continuous changes in multiple spatial motion units and exceeds the corresponding preset normal fluctuation threshold, the motion axis is identified as a motion axis with progressively deteriorating performance. The operating data includes completion time, motor current and / or position error. The priority of the motion axis with progressively degraded performance is reduced in motion coordination, and the sending time of the start command of the next spatial motion unit is adaptively adjusted according to the adjusted priority, so that other motion axes without progressively degraded performance are given priority as the motion axis with the longest completion time under the preset non-transient delay waiting threshold constraint, and used to determine the time reference. Based on the type of gradual performance degradation, corresponding performance compensation or maintenance operation suggestions are generated.

3. The precision motion control method for a multi-axis linkage direct-drive turret machine according to claim 2, characterized in that, Based on the type of progressive performance degradation, corresponding performance compensation or maintenance operation suggestions are generated, including: The operation data of the progressively degrading motion axis when completing each spatial motion unit is preprocessed to obtain an operation data feature set reflecting the current operation state of the corresponding motion axis; Predefine and store operational data feature patterns associated with different physical causes, and construct a physical cause feature pattern library from the operational data feature patterns; The current motion state's operational data feature set is matched with the physical cause feature pattern library. By calculating the similarity and / or deviation between the current operational data feature set and each operational data feature pattern, the physical cause that best matches the operational data feature set is determined. When multiple motion axes exhibit a progressive performance degradation trend simultaneously, the motion correlation and load transfer relationship between each motion axis are analyzed. If it is determined that the progressive performance degradation of the first motion axis leads to an increase in the completion time of the second motion axis, and the similarity between the running data feature set of the second motion axis and any of the running data feature patterns is less than a preset similarity threshold and / or the deviation is greater than a preset deviation threshold, the determination that the second motion axis itself has a progressive performance degradation is excluded, and the increase in the completion time of the second motion axis is attributed to the progressive performance degradation of the first motion axis, thereby achieving an independent attribution result for the physical cause of the progressive performance degradation of each motion axis. Based on the physical causes obtained from the independent attribution results, the type of progressive performance degradation is determined, and performance compensation or maintenance operation suggestions corresponding to the physical causes are generated for the motion axes with progressive performance degradation.

4. The precision motion control method for a multi-axis linkage direct-drive turret machine according to claim 1, characterized in that, The machining trajectory is discretized into multiple spatial motion units arranged sequentially along the machining trajectory, including: Based on the curvature change of the machining trajectory at each position, the corresponding feed speed command, and the preset upper limit of contour error, the initial spatial length of each spatial motion unit on the machining trajectory is adaptively determined, so that the contour error generated by linear approximation within any spatial motion unit does not exceed the upper limit of contour error. And under the speed limit constraints of each motion axis, the initial space length is corrected to obtain the target space length of each space motion unit.

5. The precision motion control method for a multi-axis linkage direct-drive turret machine according to claim 3, characterized in that, After generating performance compensation or maintenance operation suggestions corresponding to the physical causes for the progressively degraded motion axis, the method further includes: Obtain the current production plan information of the machine tool, wherein the production plan information includes at least the priority and deadline of the tasks to be processed; Based on the physical causes obtained from the independent attribution results and the corresponding degree of performance degradation, determine the type of maintenance operation required for the performance compensation or maintenance operation recommendation and the estimated time required to perform the maintenance operation; Obtain the inventory information of the spare parts required to perform the maintenance operation; Obtain availability information for the specialized tools required to perform the maintenance operations; Obtain the scheduling information of maintenance personnel with the skills required to perform the maintenance operations; The maintenance operation type and the estimated time are compared with the production plan information, and a conflict analysis between the maintenance operation and the production plan is performed to obtain the conflict analysis results. When the conflict analysis results indicate that the maintenance operation conflicts with the high-priority tasks to be processed in the production plan in terms of time, and spare parts, special tools are unavailable or maintenance personnel are insufficient, an alternative maintenance strategy is generated. The alternative maintenance strategy includes at least adjusting the execution time of some tasks to be processed in the production plan, adjusting the execution time of the maintenance operation, and / or, under the premise of not being lower than the preset processing accuracy requirements, temporarily adjusting the motion parameters of the relevant motion axis based on the performance compensation or performance compensation measures in the maintenance operation suggestion. Generate comprehensive maintenance recommendation information that includes the maintenance operation type, the estimated time, spare parts and their inventory information, special tools and their availability, the maintenance personnel's scheduling information, the suggested execution time, and alternative maintenance strategies.

6. The precision motion control method for a multi-axis linkage direct-drive turret machine according to claim 5, characterized in that, Before generating comprehensive maintenance recommendation information that includes the maintenance operation type, the estimated time, spare parts and their inventory information, special tools and their availability, the maintenance personnel's scheduling information, the suggested execution time, and alternative maintenance strategies, the following is also included: For each alternative maintenance scheme determined in the alternative maintenance strategy, obtain the time impact data of the expected completion time of the tasks to be processed in the production plan, the material consumption data of the expected maintenance operation, the manpower consumption data of the expected maintenance operation, and the life impact data of the expected life of the machine tool components related to the maintenance operation type corresponding to the alternative maintenance scheme after the execution of the alternative maintenance scheme. Based on the time impact data, calculate the production efficiency loss value for each of the alternative maintenance schemes; Based on the material consumption data and the manpower consumption data, calculate the total maintenance cost for each of the alternative maintenance solutions; Based on the lifespan impact data, calculate the equipment health impact value for each of the alternative maintenance schemes; The production efficiency loss value, total maintenance cost value, and equipment health impact value corresponding to each alternative maintenance scheme are weighted to obtain a comprehensive evaluation value for each alternative maintenance scheme. The optimal alternative maintenance solution based on the comprehensive evaluation value is determined as the recommended alternative maintenance solution, and the maintenance operation type and suggested execution time corresponding to the recommended alternative maintenance solution are integrated into the comprehensive maintenance recommendation information.

7. The precision motion control method for a multi-axis linkage direct-drive turret machine according to claim 6, characterized in that, The production efficiency loss value, total maintenance cost value, and equipment health impact value corresponding to each alternative maintenance scheme are weighted to obtain a comprehensive evaluation value for each alternative maintenance scheme, including: Obtain the priority of the current machining task, the real-time load status of each motion axis of the machine tool, and the historical performance impact data of historical maintenance operations on equipment performance; Adjust the weight of the production efficiency loss value in the comprehensive evaluation based on the priority of the current processing task; The weight of the equipment health impact value in the comprehensive evaluation is adjusted according to the real-time load status of each motion axis of the machine tool. Based on the historical performance impact data, adjust the weight of the total maintenance cost in the comprehensive evaluation; Based on the adjusted weights of production efficiency loss, total maintenance cost, and equipment health impact, the production efficiency loss, total maintenance cost, and equipment health impact corresponding to each alternative maintenance scheme are weighted to obtain a comprehensive evaluation value for each alternative maintenance scheme.

8. The precision motion control method for a multi-axis linkage direct-drive turret machine according to claim 7, characterized in that, Based on the real-time load status of each motion axis of the machine tool, after adjusting the weight of the equipment health impact value in the comprehensive evaluation, the evaluation also includes: Real-time comparison of data from multiple load-related sensors on the same motion axis; when the data deviation of a certain load-related sensor data from other load-related sensor data on the same axis and / or from the historical normal operation data corresponding to that load-related sensor data exceeds a preset deviation threshold, the corresponding load-related sensor data is marked as abnormal data. The received load-related sensor data is sequenced based on timestamps. When a data arrival delay or data packet loss is detected, the corresponding load-related sensor data is marked as delayed data or incomplete data. When all load-related sensor data for a certain motion axis are marked as abnormal, the historical load status data of that motion axis is called to make a short-term prediction and generate predicted load status data for load status assessment. When load-related sensor data is continuously marked as lagging data for multiple consecutive sampling periods and its time delay exceeds a preset delay threshold, time compensation is performed on the load status assessment result obtained based on the corresponding load-related sensor data. When adjusting the weight of the equipment health impact value based on the load status assessment results after time compensation, the abnormal data, lag data and / or incomplete data are weighted and attenuated according to the abnormal data marking and / or lag data marking of the load-related sensor data. The upper limit of the weight adjustment range of the equipment health impact value is set in combination with the duration of data abnormality or lag.

9. A precision motion control system for a multi-axis linkage direct-drive turret crane, characterized in that, include: The trajectory decomposition module is used to obtain the processing trajectory to be executed, discretize the processing trajectory into multiple spatial motion units arranged sequentially along the processing trajectory, and determine the target displacement of each motion axis in the corresponding spatial motion unit. The motion execution module is used to receive the completion signal of the corresponding motion axis after the target displacement is completed; The motion initiation module is used to coordinate motion after determining that the motion axis participating in the current spatial motion unit has completed the corresponding target displacement based on the completion signal. It acquires the completion time of each motion axis from the start of participating in the current spatial motion unit to the issuance of the completion signal, and uses the completion time of the motion axis with the longest completion time as the time reference to send the target displacement corresponding to the next spatial motion unit to each motion axis, so as to start the motion of each motion axis to the next spatial motion unit. After determining the target displacement amount corresponding to the motion axis participating in the current spatial motion unit based on the completion signal, motion coordination is performed. The completion time of each motion axis from the start of participation in the current spatial motion unit to the issuance of the completion signal is obtained. Using the completion time of the motion axis with the longest completion time as the time reference, the target displacement amount corresponding to the next spatial motion unit is sent to each of the motion axes to initiate the motion of each motion axis to the next spatial motion unit, including: Acquire the target displacement, material property data of the material to be processed, and operation data of each motion axis corresponding to the current spatial motion unit and subsequent spatial motion units; When it is determined that the completion time of at least one motion axis is delayed relative to other motion axes based on the completion time from the start of participation in the current spatial motion unit to the issuance of the completion signal, the delay is determined based on the target displacement corresponding to the current spatial motion unit, the material property data, and the operation data, whether the delay is caused by an increase in the instantaneous local cutting load encountered by the motion axis in the current spatial motion unit and is within a preset tolerance period. When the delay is caused by an increase in instantaneous local cutting load and is within a preset tolerance period, the completion time of the motion axis with the longest completion time is used as the time reference. The motion axis that has completed the target displacement in the current spatial motion unit receives the target displacement corresponding to the next spatial motion unit and starts the motion of the next spatial motion unit after the preset tolerance period expires. The spatial deviation is determined for the motion axis with the delay based on its delay time. In subsequent spatial motion units, the spatial deviation is gradually compensated by adjusting the motion speed of the motion axis with the delay, provided that the preset current, acceleration and / or speed limits are not exceeded, so that the actual motion progress of the motion axis with the delay is consistent with the motion progress of other motion axes again.

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