Error coupling compensation and positioning precision control method for lock manufacturing machine tool

Abstract

The invention relates to the technical field of lock manufacturing machine tools, in particular to an error coupling compensation and positioning precision control method for a lock manufacturing machine tool. The method comprises the following steps: acquiring the structure and operation data of a lock making machine tool through a sensor, detecting the operation condition of the lock making machine tool and detecting the spatial transformation of each motion unit of the lock making machine tool, and generating the spatial transformation data of each motion unit; according to the spatial transformation data of each motion unit, error coupling positioning of a workpiece and a locking piece of the locking machine tool and operation coupling error analysis of each component of the locking machine tool are carried out, and operation coupling error data of each component are generated; setting precision compensation control parameters of the locking machine tool according to the operation coupling error data of each component, and generating precision compensation control parameter data; and real-time precision compensation and machining track correction of the locking machine tool are carried out on the operation error coupling data of all the components based on the precision compensation control parameter data. Error coupling positioning and precision compensation control of the lock manufacturing machine tool are achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of lock-making machine tools, and in particular to a method for error coupling compensation and positioning accuracy control of a lock-making machine tool. Background Art

[0002] As precision machining equipment, lock making machine tools are widely used in the manufacturing process of lock bodies and lock core structures of various high-security locks, industrial protective devices and intelligent security systems. This type of machine tool usually includes a multi-axis linkage structure, a workpiece clamping unit, a lock forming module and a high-precision control system, and relies on complex spatial motion and the coordinated execution of multiple components to complete precision locking tasks. In the existing technology, it is difficult to identify the motion coupling relationship between multiple components of the lock making machine tool by using error compensation or geometric deduction methods of a single axis system for trajectory correction. At the same time, there is a lack of efficient perception and adaptive control of the tiny posture changes and thermal deformations that occur in real time during the locking process. In particular, in complex processing processes, the tiny posture drift between components, the deformation caused by thermal expansion, and the slight deviation in the clamping of the lock lead to insufficient matching accuracy between the lock and the workpiece, and the processing trajectory deviation is difficult to correct in time. Summary of the Invention

[0003] Based on this, the present invention provides a method for error coupling compensation and positioning accuracy control of a lock making machine tool to solve at least one of the above technical problems.

[0004] To achieve the above-mentioned purpose, a method for error coupling compensation and positioning accuracy control of a lock making machine tool comprises the following steps: Step S1: collecting the structure and operation data of the lock making machine tool through sensors, performing an operation status detection of the lock making machine tool based on the structure and operation data of the lock making machine tool, and generating the operation status data of the lock making machine tool; Step S2: performing spatial transformation detection of each motion unit of the locking machine tool based on the structure and operation data of the locking machine tool and the operation status data of the locking machine tool, and generating spatial transformation data of each motion unit; Step S3: performing a workpiece and lock component error coupling positioning analysis of the locking machine tool based on the spatial transformation data of each motion unit to generate workpiece-lock component error coupling positioning data of the locking machine tool; performing an operation coupling error analysis of each component of the locking machine tool based on the workpiece-lock component error coupling positioning data of the locking machine tool to generate operation coupling error data of each component; Step S4: setting the precision compensation control parameters of the lock making machine tool according to the coupling error data of each component operation, and generating precision compensation control parameter data; Step S5: Based on the precision compensation control parameter data, the operation error coupling data of each component is subjected to real-time precision compensation and machining trajectory correction of the locking machine tool to generate real-time precision compensation and machining trajectory data.

[0005] Furthermore, step S1 includes the following steps: Step S11: collecting the structure and operation data of the lock-making machine tool through sensors, and analyzing the structural characteristics and operation characteristics of the lock-making machine tool based on the structure and operation data of the lock-making machine tool to generate the structure characteristic-operation characteristic data of the lock-making machine tool; Step S12: Analyzing the operating parameters of the lock-making machine tool based on the structural characteristics-operation characteristic data of the lock-making machine tool to generate the operating parameter data of the lock-making machine tool; Step S13: performing operation calibration processing of the locking machine tool on the structural feature-operation characteristic data of the locking machine tool based on the operation parameter data of the locking machine tool to generate operation calibration data of the locking machine tool; Step S14: performing an operation status detection of the locking machine tool according to the operation calibration data of the locking machine tool, and generating operation status data of the locking machine tool.

[0006] Furthermore, step S2 includes the following steps: Step S21: Analyzing the structural connection relationship of the lock-making machine tool according to the structure and operation data of the lock-making machine tool to generate structural connection relationship data of the lock-making machine tool; Step S22: performing posture change detection on each motion unit of the locking machine tool according to the motion status data of the locking machine tool, and generating posture change data of each motion unit; Step S23: performing structural connection and drive analysis on the locking machine based on the posture change data of each motion unit and the structural connection relationship data of the locking machine to generate structural connection-drive data of the locking machine; Step S24: performing structural linkage drive change detection of the locking machine tool according to the structural connection-drive data of the locking machine tool, and generating structural linkage drive change data of the locking machine tool; Step S25: performing spatial transformation detection on each motion unit of the locking machine tool according to the structural linkage drive change data of the locking machine tool, and generating spatial transformation data of each motion unit.

[0007] Furthermore, step S3 includes the following steps: Step S31: analyzing the relative posture of the workpiece and the locking component of the locking machine tool according to the spatial transformation data of each motion unit to generate workpiece-locking component relative posture data; Step S32: Analyzing the position and motion linkage of each component of the lockmaking machine tool based on the relative position and motion data of the workpiece and the locking component to generate position and motion linkage data of each component; Step S33: performing workpiece and lock component error coupling positioning analysis of the locking machine tool based on the posture-motion linkage data of each component, and generating workpiece-lock component error coupling positioning data of the locking machine tool; Step S34: analyzing the operation coupling errors of the components of the locking machine based on the posture-motion linkage data of the components and the workpiece-locking piece error coupling positioning data of the locking machine, and generating the operation coupling error data of the components.

[0008] Furthermore, step S32 includes the following steps: Step S321: performing a main structure analysis of the workpiece and the lock component matching of the lock making machine tool based on the workpiece-lock component relative posture data, and generating main component data of the workpiece-lock component matching; Step S322: performing workpiece and lock component coordination component analysis of the lockmaking machine tool based on the workpiece-lock component matching main component data to generate workpiece-lock component coordination component data; Step S323: analyzing the spatial rotation and translation characteristics of the workpiece and the lock component of the lock making machine based on the workpiece-lock component matching main component data and the workpiece-lock component coordination component data to generate spatial rotation-translation motion characteristic data of the workpiece and the lock component; Step S324: performing position and motion linkage analysis of components of the locking machine tool based on the spatial rotation-translation motion characteristic data of the workpiece and the locking component, and generating position and motion linkage data of each component.

[0009] Furthermore, step S33 includes the following steps: Step S331: Detecting the machining clearance between the workpiece and the locking component of the lockmaking machine tool based on the posture-motion linkage data of each component, and generating workpiece-locking component machining clearance data; Step S332: identifying the contact status of the workpiece and the lock component of the lock making machine tool according to the workpiece-lock component machining gap data, and generating workpiece-lock component contact status data; Step S333: performing workpiece positioning and lock component deformation deviation analysis of the lock making machine tool based on the workpiece-lock component contact status data to generate workpiece positioning-lock component deformation deviation data; Step S334: performing workpiece and locking component error coupling positioning analysis of the locking machine based on the workpiece positioning-locking component deformation deviation data and the workpiece-locking component contact status data to generate workpiece-locking component error coupling positioning data of the locking machine.

[0010] Furthermore, step S34 includes the following steps: Step S341: performing a coordination test on the workpiece and lock component machining paths of the lock making machine tool based on the posture-motion linkage data of each component, and generating workpiece-lock component machining path coordination data; Step S342: performing workpiece and lock component machining geometric error detection on the lock making machine tool based on the workpiece-lock component error coupling positioning data of the lock making machine tool, and generating workpiece-lock component machining geometric error data; Step S343: performing a lock component geometry and thermal deformation error analysis of the lock component of the lock making machine tool based on the workpiece-lock component processing path coordination data and the workpiece-lock component processing geometric error data to generate lock component geometry-thermal deformation error data; Step S344: performing operation coupling error analysis of each component of the locking machine tool based on the locking piece geometry-thermal deformation error data and the posture-motion linkage data of each component, and generating operation coupling error data of each component.

[0011] Furthermore, step S343 includes the following steps: Perform workpiece and lock component cutting linkage trajectory offset detection based on workpiece-lock component machining path coordination data, and generate workpiece-lock component cutting linkage trajectory offset data; Perform lock part contour partition detection based on workpiece-lock part machining geometric error data to generate lock part contour partition data; Based on the workpiece-locking part cutting linkage trajectory offset data and the lock part contour partition data, the workpiece and lock part thermal deformation analysis of the lock making machine tool is performed to generate the workpiece-lock part thermal deformation data; Based on the workpiece-locking part thermal deformation data and the lock part and workpiece-locking part cutting linkage trajectory offset data, the lock part geometry and thermal deformation error of the lock making machine tool are analyzed to generate the lock part geometry-thermal deformation error data.

[0012] Furthermore, step S4 includes the following steps: Step S41: identifying the error characteristics of the workpiece and the locking component of the locking machine tool according to the coupling error data of the operation of each component, and generating the workpiece-locking component error characteristic data; Step S42: Analyzing the roughness of the workpiece and the lock component machining surfaces of the lock making machine tool based on the workpiece-lock component error characteristic data to generate workpiece-lock component machining surface roughness data; Step S43: setting the precision compensation control parameters of the lock-making machine tool according to the roughness data of the workpiece-locking component processing surface, and generating precision compensation control parameter data.

[0013] Furthermore, step S5 includes the following steps: Step S51: Perform a coordinated analysis of the power and execution structure of the lock making machine tool based on the precision compensation control parameter data to generate power-execution structure coordinated data. Step S52: performing correction of each motion unit of the lockmaking machine tool and collaborative detection of the machining path according to the power-execution structure collaborative data, and generating each motion unit correction-machining path collaborative data; Step S53: Based on the correction-machining path collaborative data of each motion unit, the operation coupling error data of each component is subjected to real-time precision compensation and machining trajectory correction of the locking machine tool to generate real-time precision compensation and machining trajectory data.

[0014] Beneficial effects of the present invention: The error coupling compensation and positioning accuracy control method of a locking machine tool proposed in the present invention collects the structural and operating data of the locking machine tool through sensors, collects the structural data and operating data of the locking machine tool in real time, and can comprehensively reflect the current physical state and working performance of the machine tool. The operating status of the locking machine tool is detected based on the structural and operating data of the locking machine tool, and it can be found whether there is any abnormality in the machine tool, thereby achieving early warning of faults, avoiding production interruptions due to sudden faults, and improving the continuity and stability of production. The spatial transformation detection of each motion unit of the locking machine tool is performed based on the structural and operating data of the locking machine tool and the operating status data of the locking machine tool, which can accurately capture the changes in the spatial position and motion trajectory of each motion unit under different working conditions, and can effectively identify whether there are problems such as positioning deviation, unstable motion or insufficient coordination of the motion unit. The coupled positioning analysis of the workpiece and lock error of the locking machine tool based on the spatial transformation data of each motion unit can accurately identify the coupling relationship between the workpiece positioning deviation and the lock processing error. The operation coupling error analysis of each component of the locking machine tool is performed based on the workpiece-lock error coupled positioning data of the locking machine tool, which clearly shows how the errors caused by factors such as vibration, wear, and temperature changes in different components during operation are superimposed, transmitted, and amplified. The precision compensation control parameters of the locking machine tool are set according to the operation coupling error data of each component, which can ensure that the compensation parameters are highly matched with the actual error situation, making the compensation control more targeted and effective. Based on the precision compensation control parameter data, the real-time precision compensation and processing trajectory correction of the locking machine tool are performed on the operation error coupling data of each component. During the processing process, the operating status of the machine tool can be adjusted in real time according to the dynamically changing error situation, avoiding lock processing defects caused by processing trajectory offset.

[0015] The error coupling compensation and positioning accuracy control method of a locking machine tool of the present invention systematically identifies the motion coupling relationship between multiple components of the locking machine tool, and analyzes the slight posture drift between the components during the operation of the locking machine tool, the deformation caused by thermal expansion, and the subtle deviation of the clamping of the locking parts. It can realize efficient perception and adaptive regulation of the slight posture changes and thermal deformations that occur in real time during the locking process, improve the matching accuracy between the locking parts and the workpiece, and at the same time, can timely correct the processing trajectory deviation of the locking machine tool, thereby realizing error coupling positioning and accuracy compensation control of the locking machine tool. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 A schematic flow chart of the steps of a method for error coupling compensation and positioning accuracy control of a lock-making machine tool according to the present invention; Figure 2 for Figure 1 Detailed implementation steps of step S1 in FIG. Figure 3 for Figure 1 Detailed implementation steps of step S3 in FIG. The purpose, features and advantages of the present invention will be further described with reference to the accompanying drawings and in conjunction with the embodiments. DETAILED DESCRIPTION

[0017] The following is a clear and complete description of the technical method of the present invention in conjunction with the accompanying drawings. Obviously, the embodiments described are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without making any creative work are within the scope of protection of the present invention.

[0018] In addition, the accompanying drawings are merely schematic illustrations of the present invention and are not necessarily drawn to scale. Identical reference numerals in the figures denote identical or similar parts, and thus repetitive descriptions thereof will be omitted. Some of the block diagrams shown in the accompanying drawings are functional entities that do not necessarily correspond to physically or logically separate entities. These functional entities may be implemented in software, in one or more hardware modules or integrated circuits, or in different network and / or processor and / or microcontroller approaches.

[0019] It should be understood that although the terms "first," "second," and the like may be used herein to describe various elements, these elements should not be limited by these terms. These terms are used solely to distinguish one element from another. For example, a first element may be referred to as a second element, and similarly, a second element may be referred to as a first element, without departing from the scope of the exemplary embodiments. The term "and / or" as used herein includes any and all combinations of one or more of the listed associated items.

[0020] To achieve this, please refer to Figures 1 to 3 The present invention provides a method for error coupling compensation and positioning accuracy control of a lock making machine tool, comprising the following steps: Step S1: collecting the structure and operation data of the lock making machine tool through sensors, performing an operation status detection of the lock making machine tool based on the structure and operation data of the lock making machine tool, and generating the operation status data of the lock making machine tool; Step S2: performing spatial transformation detection of each motion unit of the locking machine tool based on the structure and operation data of the locking machine tool and the operation status data of the locking machine tool, and generating spatial transformation data of each motion unit; Step S3: performing a workpiece and lock component error coupling positioning analysis of the locking machine tool based on the spatial transformation data of each motion unit to generate workpiece-lock component error coupling positioning data of the locking machine tool; performing an operation coupling error analysis of each component of the locking machine tool based on the workpiece-lock component error coupling positioning data of the locking machine tool to generate operation coupling error data of each component; Step S4: setting the precision compensation control parameters of the lock making machine tool according to the coupling error data of each component operation, and generating precision compensation control parameter data; Step S5: Based on the precision compensation control parameter data, the operation error coupling data of each component is subjected to real-time precision compensation and machining trajectory correction of the locking machine tool to generate real-time precision compensation and machining trajectory data.

[0021] In the embodiment of the present invention, please refer to Figure 1 FIG. 1 is a flow chart showing the steps of a method for error coupling compensation and positioning accuracy control of a lock-making machine tool according to the present invention. In this example, the method for error coupling compensation and positioning accuracy control of a lock-making machine tool includes the following steps: Step S1: collecting the structure and operation data of the lock making machine tool through sensors, performing an operation status detection of the lock making machine tool based on the structure and operation data of the lock making machine tool, and generating the operation status data of the lock making machine tool; In an embodiment of the present invention, various sensors, including acceleration sensors, temperature sensors, displacement sensors, and current sensors, are installed in key locations of a lockmaking machine tool, such as the spindle, guide rails, lead screw, and motor. Acceleration sensors collect vibration acceleration data during machine operation to monitor the machine's vibration status and determine whether abnormal vibration exists. Temperature sensors measure the temperature of various components in real time to prevent damage or loss of accuracy due to excessive temperatures. Displacement sensors accurately capture the displacement of moving parts, providing data support for analyzing motion accuracy. Current sensors monitor motor current changes to reflect motor load conditions. These sensors collect machine tool structural and operational data at high speed and high precision, for example, multiple times per second. The collected data is transmitted in real time to a data acquisition system via a data transmission line using a high-speed transmission protocol, such as USB 3.0 or Ethernet. The data acquisition system performs preliminary preprocessing on the collected raw data to remove noise and outliers. A sliding average filter algorithm is then used to average five data points to produce smoothed machine tool structural and operational data. Based on this data, a pre-built machine tool health assessment model, trained using a support vector machine algorithm and trained on a large amount of normal and abnormal operating data, is used. The pre-processed data is fed into the model, which then compares and analyzes the data characteristics against a pre-defined range of normal operating characteristics. This generates health data for the lockmaking machine, clarifying whether the machine is currently operating normally, at risk of potential failure, or has already experienced a failure.

[0022] Step S2: performing spatial transformation detection of each motion unit of the locking machine tool based on the structure and operation data of the locking machine tool and the operation status data of the locking machine tool, and generating spatial transformation data of each motion unit; In an embodiment of the present invention, based on the structure, operation, and status data of a locking machine tool, multi-body system theory and homogeneous coordinate transformation methods are used to detect the spatial transformation of each motion unit. First, each motion unit of the locking machine tool, such as the spindle unit, worktable unit, and tool feed unit, is abstracted as a rigid body in the multi-body system, and a right-handed rectangular coordinate system is established for each rigid body. By analyzing the connection relationships and motion transmission methods between the motion units, the motion transformation matrix between adjacent rigid bodies is determined. The actual motion trajectory of each motion unit is measured using measuring equipment such as laser interferometers and ballbars. Laser interferometers can accurately measure displacement errors and straightness errors in linear motion, while ballbars can detect errors in circular motion. The measured actual motion trajectory data is compared with the theoretical motion trajectory data, and the actual trajectory data is converted to a unified coordinate system through homogeneous coordinate transformation for analysis. For example, for the rotational motion of the spindle unit, an angular displacement sensor is used to measure its actual rotation angle, and the spatial position change in the machine tool coordinate system is calculated through homogeneous coordinate transformation. Based on the analysis results, the spatial transformation data of each motion unit under different working conditions is generated, including the changes in parameters such as displacement, velocity, acceleration, and rotation angle, so as to accurately grasp the motion state and accuracy of each motion unit.

[0023] Step S3: performing a workpiece and lock component error coupling positioning analysis of the locking machine tool based on the spatial transformation data of each motion unit to generate workpiece-lock component error coupling positioning data of the locking machine tool; performing an operation coupling error analysis of each component of the locking machine tool based on the workpiece-lock component error coupling positioning data of the locking machine tool to generate operation coupling error data of each component; In an embodiment of the present invention, a workpiece and lock component error coupling positioning analysis is performed based on the spatial transformation data of each motion unit. By establishing a mathematical model of the workpiece and lock component, their theoretical position in the machine tool coordinate system is compared with the actual processing position. A high-precision three-dimensional coordinate measuring instrument is used to measure the processed workpiece and lock component to obtain their actual size, shape and position information. The deviation calculation is performed between the measured data and the theoretical data in the design drawings to analyze how the errors of each motion unit are coupled with each other during the processing of the workpiece and lock component, resulting in the final processing error. For example, when there is a positioning error in the linear motion of the worktable unit and the feed rate of the tool feed unit is inaccurate, the errors of the two will be coupled during the processing of the lock core hole, causing deviations in the diameter and position of the lock core hole. By in-depth analysis of this error coupling relationship, the workpiece-lock component error coupling positioning data of the lockmaking machine tool is generated. On this basis, the operation coupling errors of each component are further analyzed. For each machine tool component, such as guide rails, lead screws, and bearings, strain gauges, force sensors, and other devices are used to measure the forces acting on them during operation. Combined with the spatial transformation data of each motion unit, the force transmission and interaction relationships between components are analyzed. For example, lead screw pitch error can cause displacement error during table movement, while guide rail wear can cause uneven table movement. The interaction between the two creates coupling error. This analysis generates operational coupling error data for each component, clarifying the extent and manner in which each component error affects the overall accuracy of the machine tool.

[0024] Step S4: setting the precision compensation control parameters of the lock making machine tool according to the coupling error data of each component operation, and generating precision compensation control parameter data; In an embodiment of the present invention, an error compensation algorithm is employed to set the precision compensation control parameters for a lockmaking machine tool based on the coupled error data from the operation of each component. Using an optimization algorithm such as the least squares method, compensation parameters are calculated to maximize the offset of these errors based on the coupled error data from each component. For example, for the pitch error of a lead screw, the required compensation displacement increase or decrease at different positions is determined by calculation; for the straightness error of a guide rail, the corresponding angle compensation value is calculated. Furthermore, the compensation parameters are dynamically adjusted by considering the dynamic characteristics of the machine tool, such as inertia and damping. Using real-time monitored machine operation data, such as motor speed and load current, and based on a pre-established machine tool dynamics model, the compensation parameters are updated online to adapt to variations in machine tool errors under different operating conditions. The calculated precision compensation control parameters, such as displacement compensation, angle compensation, and speed correction coefficient, are organized into precision compensation control parameter data, providing accurate control instructions for subsequent real-time precision compensation.

[0025] Step S5: Based on the precision compensation control parameter data, the operation error coupling data of each component is subjected to real-time precision compensation and machining trajectory correction of the locking machine tool to generate real-time precision compensation and machining trajectory data.

[0026] In an embodiment of the present invention, real-time precision compensation and machining trajectory correction are performed on a locking machine tool based on the coupled operational errors of various components. The precision compensation control parameter data is loaded into the corresponding control module via the machine tool's numerical control system. During machining, the numerical control system uses real-time collected operational data from various components, such as the actual position of the worktable as fed back by the displacement sensor and the motor speed as fed back by the encoder, in conjunction with the precision compensation control parameters, to adjust the machine tool's motion instructions in real time. For example, when a deviation between the actual and theoretical worktable positions is detected, the numerical control system automatically increases or decreases the corresponding feed rate based on pre-set compensation parameters, correcting the machining trajectory so that the tool can machine along the corrected trajectory, thereby compensating for machining errors caused by the coupled operational errors of various components. Simultaneously, the machining process is monitored in real time using equipment such as a laser tracker. The actual machining trajectory data obtained is compared and analyzed with the theoretical machining trajectory data to further verify the effectiveness of the precision compensation. Based on the comparison results, the precision compensation control parameters are fine-tuned to achieve higher machining accuracy.

[0027] Furthermore, step S1 includes the following steps: Step S11: collecting the structure and operation data of the lock-making machine tool through sensors, and analyzing the structural characteristics and operation characteristics of the lock-making machine tool based on the structure and operation data of the lock-making machine tool to generate the structure characteristic-operation characteristic data of the lock-making machine tool; Step S12: Analyzing the operating parameters of the lock-making machine tool based on the structural characteristics-operation characteristic data of the lock-making machine tool to generate the operating parameter data of the lock-making machine tool; Step S13: performing operation calibration processing of the locking machine tool on the structural feature-operation characteristic data of the locking machine tool based on the operation parameter data of the locking machine tool to generate operation calibration data of the locking machine tool; Step S14: performing an operation status detection of the locking machine tool according to the operation calibration data of the locking machine tool, and generating operation status data of the locking machine tool.

[0028] As an embodiment of the present invention, refer to Figure 2 As shown, Figure 1 Detailed step flow diagram of step S1 in FIG. 1 , in this embodiment, step S1 includes the following steps: Step S11: collecting the structure and operation data of the lock-making machine tool through sensors, and analyzing the structural characteristics and operation characteristics of the lock-making machine tool based on the structure and operation data of the lock-making machine tool to generate the structure characteristic-operation characteristic data of the lock-making machine tool; In an embodiment of the present invention, laser displacement sensors, piezoelectric accelerometers, infrared temperature sensors, and torque sensors are installed in key structural locations of a lockmaking machine tool (such as the spindle box, guide rail sliders, and transmission gear train). The laser displacement sensor is fixed 50 mm from the guide rail surface and collects structural data such as the guide rail's straightness and parallelism with a resolution of 0.001 mm. The piezoelectric accelerometer is attached to the spindle housing and records the spindle's vibration acceleration during operation at a sampling frequency of 10 kHz. The infrared temperature sensor is aligned with the motor windings and collects temperature values ​​every 100 ms. The torque sensor is connected in series to the drive screw to measure the torque transmitted by the screw in real time. Simultaneously, a data interface is connected to the machine tool's CNC system to collect operating parameters such as spindle speed (range: 500-3000 rpm), feed rate (0.1-5 mm / s), and cutting depth (0.01-1 mm). After compiling the collected structural data and operating parameters, 3D modeling software is used to construct a structural characteristic model of the machine tool. This model includes parameters such as the geometric dimensions, material properties, and connection methods of each component. Vibration signals are converted into frequency domain data using Fourier transforms to analyze vibration characteristics at different speeds. Thermal distribution maps and torque variation curves are then created by combining temperature and torque data. Through comprehensive analysis of this data, the correlation between structural parameters (such as guideway span) and operating characteristics (such as vibration amplitude) is clarified. Ultimately, structural characteristic-operational characteristic data is generated, including structural dimensional tolerances, vibration frequency peaks, temperature field distribution, and torque fluctuation range.

[0029] Step S12: Analyzing the operating parameters of the lock-making machine tool based on the structural characteristics-operation characteristic data of the lock-making machine tool to generate the operating parameter data of the lock-making machine tool; In this embodiment of the present invention, a hierarchical analytical method is used to analyze operational parameters based on the structural and operational characteristics of a lockmaking machine tool. The data is first divided into a structural static parameter layer (such as bed stiffness and guideway spacing) and an operational dynamic parameter layer (such as spindle vibration frequency and feed acceleration). For the static parameter layer, finite element analysis software is used to calculate the bed deformation under rated load. The rationality of the structural parameters is determined by comparing them to design standard values ​​(e.g., deformation ≤ 0.02 mm / m). For the dynamic parameter layer, a spectrum analyzer is used to decompose the spindle vibration signal, extracting characteristic frequencies within the 1-1000 Hz frequency band. These frequencies are then compared with the machine tool's resonance frequency threshold (e.g., ≥500 Hz is considered a dangerous range). Simultaneously, the heat dissipation efficiency coefficient is calculated using motor temperature rise data collected by a temperature sensor (temperature rise ≤ 10°C per hour). Based on the torque sensor's measurements, a load-torque curve is plotted to determine the optimal cutting torque range (e.g., 50-80 N·m). Through quantitative analysis of these parameters, the impact of structural characteristics on operating performance is converted into specific numerical indicators. For example, for every 0.01mm increase in guide rail parallelism error, the feed speed fluctuation increases by 2%. Ultimately, operating parameter data is generated, including structural parameter adaptation values, dynamic operating thresholds, and performance impact coefficients.

[0030] Step S13: performing operation calibration processing of the locking machine tool on the structural feature-operation characteristic data of the locking machine tool based on the operation parameter data of the locking machine tool to generate operation calibration data of the locking machine tool; In an embodiment of the present invention, the structural feature-operation characteristic data of the locking machine tool is subjected to operation calibration based on the operating parameter data of the locking machine tool. First, a calibration reference database is established, in which the structural feature parameters (such as spindle radial runout ≤ 0.005mm) and operation characteristic indicators (such as noise value ≤ 75dB) of the machine tool under standard working conditions are stored. A data comparison algorithm is used to compare the real-time collected structural feature-operation characteristic data with the standard values ​​in the reference database point by point. For example, the difference between the current spindle vibration acceleration (such as 1.2g) and the standard value (such as ≤ 1g) is calculated to obtain the deviation (0.2g). For data that exceeds the allowable deviation range (such as deviation ≥ 0.5g), a secondary calibration process is initiated, and a laser interferometer is used to re-measure the actual displacement accuracy of the guide rail to verify the accuracy of the data. At the same time, the structural characteristic data is dynamically calibrated by combining the dynamic adjustment coefficients in the operating parameter data (for example, for every 5°C increase in temperature, the spindle speed correction coefficient is 0.98). For example, when the motor temperature reaches 60°C, the rated spindle speed is corrected from 3000 r / min to 3000 × 0.98 = 2940 r / min. This dynamic comparison and calibration eliminates systematic and random errors in the data acquisition process, generating operational calibration data that includes deviation correction values, calibrated characteristic parameters, and dynamic adaptation coefficients.

[0031] Step S14: performing an operation status detection of the locking machine tool according to the operation calibration data of the locking machine tool, and generating operation status data of the locking machine tool.

[0032] In an embodiment of the present invention, a multi-dimensional evaluation method is used to detect the operating status of the lock-making machine tool based on the operation proofreading data. First, a detection system containing five evaluation dimensions is constructed: structural stability (such as the vibration amplitude of the bed ≤ 0.01mm), operation accuracy (such as positioning error ≤ 0.003mm), power performance (such as motor output power fluctuation ≤ 5%), thermal stability (such as temperature field uniformity ≥ 90%), and safety redundancy (such as emergency stop response time ≤ 0.1s). A quantitative scoring standard is set for each dimension (full score 100 points). For example, in the structural stability dimension, a vibration amplitude of 0.005mm corresponds to 100 points, and 20 points are deducted for every increase of 0.001mm. The various indicators in the operation proofreading data are substituted into the scoring system to calculate the actual score of each dimension. When the score of a dimension is lower than 80 points, it is marked as an item to be optimized. A weighted summation method is also used to calculate a comprehensive score (weighting each dimension: structural stability 30%, operational accuracy 30%, power performance 20%, thermal stability 10%, and safety redundancy 10%). A comprehensive score of 90 or higher indicates excellent operating status, 80-89 indicates good operating status, 70-79 indicates a state requiring adjustment, and less than 70 indicates a fault warning. This multi-dimensional quantitative assessment generates operational status data that includes scores for each dimension, the overall status level, details of items to be optimized, and warning indicator values, fully reflecting the current operating status of the machine tool.

[0033] Furthermore, step S2 includes the following steps: Step S21: Analyzing the structural connection relationship of the lock-making machine tool according to the structure and operation data of the lock-making machine tool to generate structural connection relationship data of the lock-making machine tool; In an embodiment of the present invention, a structural connection relationship analysis is performed based on the structure and operating data of a lockmaking machine tool to generate structural connection relationship data. First, the machine tool's structural design drawings are obtained to clearly identify the model, size, and assembly position of each component. For example, the spindle and gearbox are connected via a JS100 coupling, and the guide rails and bed are secured with M12 bolts with a bolt spacing of 150 mm. An industrial CT scanner is used to scan the entire machine tool structure, generating a three-dimensional structural image of each component with a resolution of 0.01 mm. This image is then used to confirm the consistency of the actual connection positions with the design drawings. Force sensors are used to measure the tightening force at each connection point. For example, the bolt preload must reach 300 N, and the coupling's transmission torque must be 500 N·m. Simultaneously, the vibration transmission characteristics of the connection points are analyzed based on the vibration frequencies in the operating data. For example, when the spindle vibration frequency is 50 Hz, the vibration frequency transmitted to the gearbox through the coupling is attenuated by 20%. This information is integrated to determine the connection method (rigid or flexible), connection point coordinates, tightening parameters, and force transmission coefficient of each component. Structural connection relationship data is then generated, containing the specific parameters of each connection point.

[0034] Step S22: performing posture change detection on each motion unit of the locking machine tool according to the motion status data of the locking machine tool, and generating posture change data of each motion unit; In an embodiment of the present invention, the position change detection of each motion unit is performed based on the motion status data of the lock making machine tool, and the position change data of each motion unit is generated. The motion status data includes the motion speed, acceleration and time node of each motion unit, such as the spindle speed is 1000r / min and the workbench feed speed is 5mm / s. Three orthogonal laser displacement sensors are installed on each motion unit. The sensor sampling frequency is 10kHz, the measurement range is 0-500mm, and the accuracy is 0.001mm. The displacement changes of the motion unit in the X, Y and Z axis directions are detected respectively. At the same time, a circular grating encoder with a resolution of 10,000 lines / turn is installed on the rotating axis of the motion unit to measure the rotation angle change. Taking the worktable motion unit as an example, when the worktable moves from its initial position (X=0, Y=0, Z=0) to its target position (X=100mm, Y=50mm, Z=0), a laser displacement sensor records the displacement of each axis in real time, and a circular grating encoder records the rotation angle. The deviation between the actual and theoretical displacements is calculated. For example, if the actual X-axis displacement is 100.002mm, the deviation is 0.002mm, and the rotation angle deviation is 0.01°. The displacement and angle data of all motion units at different times are collated to generate the position change data for each motion unit, including the displacement of each axis, the rotation angle, and the corresponding time point.

[0035] Step S23: performing structural connection and drive analysis on the locking machine based on the posture change data of each motion unit and the structural connection relationship data of the locking machine to generate structural connection-drive data of the locking machine; In an embodiment of the present invention, a structural connection and drive analysis is performed based on the posture change data and structural connection relationship data of each motion unit to generate structural connection-drive data. First, the connection type and connection parameters of each motion unit are extracted from the structural connection relationship data. For example, the spindle unit and the feed unit are connected by gear meshing, the gear module is 2, and the transmission ratio is 1:3. Combined with the posture change data of each motion unit, the motion transmission relationship between the active motion unit and the driven motion unit is analyzed. For example, when the spindle rotation angle changes by 30°, the distance the feed unit should move is 5mm according to the transmission ratio. Then, compared with the moving distance of the feed unit of 4.998mm in the actual posture change data, a transmission error of 0.002mm is obtained. A dynamic strain gauge is used to measure the strain value of the connection part. For example, the maximum strain value at the gear meshing part is 200με, and it is judged whether the load-bearing capacity of the connection is within the allowable range (the maximum allowable value is 250με). At the same time, the current changes in the drive motor were recorded. When the spindle speed increased from 500 rpm to 1000 rpm, the motor current increased from 5A to 8A. The relationship between drive power and the position change of the motion unit was analyzed. These analysis results were integrated to clarify the corresponding relationship between transmission error, load strain, and drive parameters at each connection point and position change, thus generating structural connection-drive data.

[0036] Step S24: performing structural linkage drive change detection of the locking machine tool according to the structural connection-drive data of the locking machine tool, and generating structural linkage drive change data of the locking machine tool; In an embodiment of the present invention, a structural linkage drive change detection is performed based on the structural connection-drive data to generate structural linkage drive change data. The linkage relationship of each motion unit is obtained from the structural connection-drive data, such as the linkage ratio of the main shaft rotation and the feed unit movement is 10r:1mm, that is, the main shaft rotates 10 circles and the feed unit moves 1mm. During the operation of the machine tool, a high-speed camera is used to shoot the linkage process of each motion unit with a frame rate of 1000 frames / second, and the position of each unit at the linkage moment is recorded. At the same time, the output torque and speed of the motor are measured in real time by the torque sensor and speed sensor installed on the drive motor. The sampling frequency is 1kHz, the torque measurement range is 0-1000N·m, the accuracy is 0.1N·m, and the speed measurement range is 0-3000r / min, with an accuracy of 1r / min. During the lock core drilling process, the spindle rotation is linked to the feed unit's feed. By comparing the theoretical linkage relationship with the actual measured motor parameters and positional relationships recorded by high-speed video, the linkage error is calculated. For example, theoretically, the feed unit should move 10mm after 100 spindle rotations, but it actually moves 9.995mm, with an error of 0.005mm. The motor torque change during this period is also recorded as 500±2N·m and the speed change is 1000±5r / min. The parameter change data during this linkage process is collated to generate structural linkage drive change data.

[0037] Step S25: performing spatial transformation detection on each motion unit of the locking machine tool according to the structural linkage drive change data of the locking machine tool, and generating spatial transformation data of each motion unit.

[0038] In an embodiment of the present invention, a spatial transformation detection of each motion unit is performed based on the structural linkage drive change data, and the spatial transformation data of each motion unit is generated. The structural linkage drive change data of the lock making machine tool is used to determine the speed, acceleration and position change rules of each motion unit in the linkage process. The spatial coordinate transformation method is adopted, and the local coordinate system of each motion unit is established with the reference coordinate system of the machine tool (with the lower left corner of the bed as the origin, the X axis along the length direction of the bed, the Y axis along the width direction, and the Z axis vertically upward) as a reference. The laser tracker installed on each motion unit has a measurement range of 0-50m and an accuracy of 0.01mm. The spatial position of the feature point on the motion unit is tracked in real time, and the sampling frequency is 5kHz. For example, the tool tip is selected as the feature point on the tool motion unit. When the tool is cutting the lock hole, the laser tracker records the spatial coordinates of the tool tip at different times. 、 ..., combined with the velocity and acceleration information in the structural linkage drive change data, calculate the displacement, velocity, acceleration vector, and attitude angle (pitch angle, yaw angle, roll angle) of the feature point in space. For example, if the tool tip moves from (100, 50, 20) to (150, 50, 20), the displacement vector is (50, 0, 0), the velocity is 5mm / s, the acceleration is 0.1mm / s², and the pitch angle changes by 0.02°. Typical body in a multi-body system 、 The relative transformation between the typical body and the attached body coordinate system can be realized by the relative transformation between the typical body and the attached body coordinate system. 、 The translation transformation between them can be represented by a homogeneous matrix. The spatial coordinates, motion vectors and attitude angle change data of all motion units are summarized to generate the spatial transformation data of each motion unit.

[0039] Furthermore, step S3 includes the following steps: Step S31: analyzing the relative posture of the workpiece and the locking component of the locking machine tool according to the spatial transformation data of each motion unit to generate workpiece-locking component relative posture data; Step S32: Analyzing the position and motion linkage of each component of the lockmaking machine tool based on the relative position and motion data of the workpiece and the locking component to generate position and motion linkage data of each component; Step S33: performing workpiece and lock component error coupling positioning analysis of the locking machine tool based on the posture-motion linkage data of each component, and generating workpiece-lock component error coupling positioning data of the locking machine tool; Step S34: analyzing the operation coupling errors of the components of the locking machine based on the posture-motion linkage data of the components and the workpiece-locking piece error coupling positioning data of the locking machine, and generating the operation coupling error data of the components.

[0040] As an embodiment of the present invention, refer to Figure 3 As shown, Figure 1 Detailed step flow diagram of step S3 in the embodiment, step S3 includes the following steps: Step S31: analyzing the relative posture of the workpiece and the locking component of the locking machine tool according to the spatial transformation data of each motion unit to generate workpiece-locking component relative posture data; In an embodiment of the present invention, the relative position and posture of the workpiece and the locking component are analyzed based on the spatial transformation data of each motion unit to generate the workpiece-locking component relative position and posture data. The spatial transformation data of each motion unit includes the spatial coordinates, motion vectors, and attitude angle changes of motion units such as the tool and the worktable. For example, the coordinates of the tool tip at a certain moment are (150, 50, 20), and the coordinates of the worktable are (100, 30, 0). Three reflective marking points are attached to the workpiece and the locking component respectively. A three-dimensional coordinate measuring machine (measuring range 0-1000mm, accuracy 0.001mm) is used to perform static measurement of the marking points to obtain the initial coordinates of the workpiece on the worktable (such as the coordinates of the workpiece marking point A (105, 35, 5)) and the initial coordinates of the locking component in the fixture (such as the coordinates of the locking component marking point B (110, 40, 5)). Combining the worktable's displacement changes (e.g., a 10mm X-axis movement) in the motion unit's spatial transformation data, the workpiece's real-time coordinates (115, 35, 5) after the worktable's movement are calculated. Based on the tool's spatial transformation data, the real-time coordinates of the locking element during machining (110, 40, 5) are calculated. Coordinate difference calculations reveal a relative displacement of 5mm between the workpiece and the locking element in the X-axis, 5mm in the Y-axis, and 0° in the Z-axis, with an attitude angle deviation of 0.01°. This data is organized into a time series to generate workpiece-locking element relative position data, including relative displacement, relative angle, and corresponding machining steps.

[0041] Step S32: Analyzing the position and motion linkage of each component of the lockmaking machine tool based on the relative position and motion data of the workpiece and the locking component to generate position and motion linkage data of each component; In an embodiment of the present invention, the position and motion linkage of each component are analyzed based on the workpiece-locking component relative position data to generate component position-motion linkage data. The workpiece-locking component relative position data records the relative position relationship between the two at different times. For example, in the keyhole drilling process, the relative displacement X-axis deviation is 0.003mm at the 10th second. Component connection parameters are extracted from the structural connection relationship data, such as the coaxiality error between the spindle and the tool is ≤0.002mm, and the parallelism error between the guide rail and the worktable is ≤0.001mm / m. High-precision inclination sensors (measuring range ±5°, accuracy 0.001°) and displacement sensors (sampling frequency 5kHz, accuracy 0.0005mm) are installed on each component (spindle, guide rail, fixture, etc.) to collect component position data in real time. When the relative posture of the workpiece and the locking component deviates, the motion state of the related components is analyzed. For example, when the relative displacement deviation of the X-axis is 0.003mm, the guide rail displacement deviation in the X direction is detected to be 0.002mm, and the spindle runout in the X direction is 0.001mm. The interaction between the two leads to a total deviation. By establishing a mapping relationship between component posture changes and relative posture deviations, such as for every 0.001mm increase in guide rail displacement, the relative posture deviation increases by 0.0015mm, the posture-motion linkage data of each component is generated, including the posture parameters of each component, the motion linkage coefficient, and the deviation contribution ratio.

[0042] Step S33: performing workpiece and lock component error coupling positioning analysis of the locking machine tool based on the posture-motion linkage data of each component, and generating workpiece-lock component error coupling positioning data of the locking machine tool; In an embodiment of the present invention, a workpiece and lock error coupling positioning analysis is performed based on the posture-motion linkage data of each component to generate workpiece-lock error coupling positioning data. The posture-motion linkage data of each component clearly defines the influence of the component posture on the relative posture, such as the linkage coefficient of the fixture positioning error and the tool feed error is 0.8. A laser interferometer (measuring accuracy 0.001mm) is used to measure the actual position of the workpiece during the processing, and the positioning error is obtained by comparing it with the theoretical position. For example, the actual X-axis position of the workpiece is 100.002mm, the theoretical position is 100mm, and the error is 0.002mm. At the same time, a three-coordinate measuring machine (detection accuracy 0.001mm) is used to measure the key dimensions of the lock after processing, such as the theoretical diameter of the lock hole is 5mm, the actual diameter is 5.001mm, and the error is 0.001mm. Combining the position and motion linkage data of each component, we analyzed the error coupling relationship: When a fixture positioning error of 0.002mm and a tool radial runout of 0.001mm coexist, the coupling between the two results in a 0.0025mm deviation in the locking component hole position (rather than a simple addition of 0.003mm). By quantifying the coupling effect of different component errors, such as an error coupling coefficient of 0.83, we generated workpiece-locking component error coupling positioning data, including the error source, coupling coefficient, total error after coupling, and positioning deviation coordinates.

[0043] Step S34: analyzing the operation coupling errors of the components of the locking machine based on the posture-motion linkage data of the components and the workpiece-locking piece error coupling positioning data of the locking machine, and generating the operation coupling error data of the components.

[0044] In this embodiment of the present invention, an analysis of the operational coupling errors of each component is performed based on the position-motion linkage data of each component and the workpiece-locking element error coupling positioning data, generating operational coupling error data for each component. Component motion parameters, such as a leadscrew pitch error of 0.001mm / 100mm and a guide rail straightness error of 0.0005mm / m, are extracted from the position-motion linkage data. The total coupling error, such as a lock cylinder groove symmetry error of 0.003mm, is then obtained from the workpiece-locking element error coupling positioning data. While the machine tool is operating, a dynamic signal analyzer (frequency range 0-10kHz, sampling rate 20kHz) is used to collect vibration signals from each component. These signals include: a leadscrew vibration frequency of 200Hz and an amplitude of 0.001mm; and a guide rail vibration frequency of 150Hz and an amplitude of 0.0008mm. Analysis of the correlation of the vibration signals reveals that when the lead screw and guide rail vibration frequencies differ by 50Hz, the resonance error generated by the coupling increases the total error by 0.0005mm. Combined with data from the temperature sensor (measurement range -50°C to 150°C, accuracy 0.1°C), we found that when the motor temperature rises from 30°C to 50°C, thermal deformation of the leadscrew causes the pitch error to increase by 0.0003mm. This, coupled with the 0.0002mm thermal deformation error of the guide rail, increases the total error to 0.0006mm. By quantifying these coupling relationships and clarifying the coupling values ​​of each component error under different operating conditions, for example, for every 10°C increase in temperature, the coupling error increases by 0.0002mm, we generated operational coupling error data for each component, including component error values, coupling conditions, coupling error amounts, and error transmission paths.

[0045] Furthermore, step S32 includes the following steps: Step S321: performing a main structure analysis of the workpiece and the lock component matching of the lock making machine tool based on the workpiece-lock component relative posture data, and generating main component data of the workpiece-lock component matching; In an embodiment of the present invention, a main structural analysis of the workpiece and lock component matching is performed based on the workpiece-lock component relative posture data to generate the workpiece-lock component matching main component data. The workpiece-lock component relative posture data includes the relative displacement, angle, and corresponding process of the two during the processing. For example, in the assembly process of the lock body and lock core, the relative displacement is 0.02mm on the X axis and 0.01mm on the Y axis. Using a structural decomposition method, the structures of the workpiece and lock component are split into core functional modules. The workpiece side focuses on key structures such as the lock body positioning hole and the lock tongue mounting groove, while the lock component side focuses on mating parts such as the lock core cylindrical surface and the keyhole. Industrial CT scanning (resolution 0.01mm) is used to obtain a three-dimensional model of the two, and three-dimensional comparison software is used to extract the matching main structural features, such as the lock body positioning hole diameter of 10mm, the lock core cylindrical surface diameter of 9.995mm, and the mating clearance between the two is 0.005mm. Combined with the deviation values ​​in the relative pose data, the components that play a dominant role in fit accuracy are identified, such as the fixture base where the lock body locating hole is located and the spindle chuck that holds the lock core. The positional accuracy of these components directly affects the relative pose deviation (for example, a 0.002mm flatness error in the fixture base will result in a 0.0015mm relative displacement error on the X-axis). By integrating these key structural parameters (locating hole center coordinates X=100mm, Y=50mm), material rigidity (elastic modulus of 200GPa for the cast iron base), and fit tolerances (H7 / g6), data for the primary component matching between the workpiece and the lock component is generated.

[0046] Step S322: performing workpiece and lock component coordination component analysis of the lockmaking machine tool based on the workpiece-lock component matching main component data to generate workpiece-lock component coordination component data; In an embodiment of the present invention, workpiece and lock component coordination component analysis is performed based on the workpiece-locking component matching main component data to generate workpiece-locking component coordination component data. The matching main component data specifies core components such as the fixture base and spindle chuck, with parameters such as the 300N preload of the bolts connecting the fixture base and the worktable. Coordinating components, such as guide shafts, locating pins, and elastic supports, assist in achieving precise coordination of the main components. Force sensors (range 0-500N, accuracy 0.1N) are used to measure the stress state of the coordinating components, such as the 80N lateral force on the locating pins. A laser micrometer (measuring range 0-50mm, accuracy 0.0001mm) is used to measure the radial runout of the guide shaft to 0.001mm. The impact of the coordinating components on the main component coordination is analyzed. For example, a 0.002mm / m guide shaft straightness error will cause a 0.001mm offset in the lock body feed trajectory, and a 200N / mm elastic support stiffness coefficient can offset 50% of vibration transmission. Combined with the position parameters of the main components, the installation position of the coordination component (for example, the center of the locating pin is 10 mm from the edge of the locating hole in the lock body), structural parameters (guide shaft diameter 15 mm, tolerance f7) and performance indicators (maximum deformation of the elastic support 0.05 mm) are determined. These data are organized into workpiece-locking part coordination component data, which includes the specific parameters of each coordination component and the correction coefficient for the main component fit.

[0047] Step S323: analyzing the spatial rotation and translation characteristics of the workpiece and the lock component of the lock making machine based on the workpiece-lock component matching main component data and the workpiece-lock component coordination component data to generate spatial rotation-translation motion characteristic data of the workpiece and the lock component; In this embodiment of the present invention, spatial rotational and translational motion characteristics are analyzed based on the workpiece-locking component matching main component data and coordination component data to generate spatial rotational-translational motion characteristic data. The matching parameters of the lock body locating hole and the lock core cylindrical surface (e.g., a clearance of 0.005 mm) in the main component data are matched, and the guide shaft straightness (0.002 mm / m) in the coordination component data is used as the basis for the analysis. A rotary encoder (resolution of 10,000 lines / turn) and a linear scale (accuracy of 0.001 mm) are installed on the main components (fixture base and spindle chuck) to record rotation angle (range 0-360°) and translation distance (range 0-500 mm) in real time. When machining the keyway, the lock body translates with the worktable (50 mm in the X-axis at a speed of 10 mm / s), while the lock core rotates with the spindle (30° / s for a total of 90°). Simultaneously, a locating pin in the coordination component limits the lock body's rotation about the Z-axis (with an allowable error of ≤ 0.01°). The collected data was used to calculate motion characteristics: the lock body's translational acceleration was 0.5 mm / s², the lock cylinder's angular acceleration was 0.5° / s², and the synchronization error between the two movements was ≤ 0.002 seconds. The coupled relationship between rotation and translation was analyzed. For example, a 30° rotation of the lock cylinder requires a 16.67 mm translation of the lock body (a transmission ratio of 1:0.555). These parameters were categorized by motion phase (acceleration, constant speed, and deceleration), generating spatial rotation-translation motion characteristic data including rotational angular velocity, translational velocity, and motion synchronization coefficient.

[0048] Step S324: performing position and motion linkage analysis of components of the locking machine tool based on the spatial rotation-translation motion characteristic data of the workpiece and the locking component, and generating position and motion linkage data of each component.

[0049] In this embodiment of the present invention, the position and motion linkage of each component are analyzed based on the spatial rotation-translation motion characteristic data of the workpiece and lock element, generating position-motion linkage data for each component. This motion characteristic data records the parameters of the lock body translation and lock core rotation, such as an X-axis translation speed of 10 mm / s during the uniform phase, a lock core rotation speed of 30° / s, and a synchronization error of 0.001s. A three-dimensional accelerometer (with a range of ±10g and an accuracy of 0.001g) and an inclinometer (with an accuracy of 0.001°) are installed on the relevant components (the worktable guide rails, spindle bearings, and guide shaft supports) with a sampling frequency of 10kHz. These sensors collect the vibration acceleration (e.g., 0.05g X-axis acceleration of the guide rails) and the tilt angle (e.g., 0.002° tilt of the spindle end) of the components during motion. When motion characteristics deviate (for example, synchronization error increases to 0.003s), component pose changes are tracked: a 0.0015mm guideway straightness error causes a 0.002s lag in worktable translation, and a 0.001mm spindle bearing clearance causes a 0.001s lead in rotation. These two factors interact to form a total error. A quantitative relationship is established: for every 0.001mm guideway deviation, translational lag is 0.0013s; for every 0.0005mm increase in spindle bearing clearance, rotational advance is 0.0005s. These linkage parameters (error transfer coefficient, component contribution ratio) are integrated with pose data to generate pose-motion linkage data for each component, including the component's real-time pose, motion deviation correlation value, and correction threshold.

[0050] Furthermore, step S33 includes the following steps: Step S331: Detecting the machining clearance between the workpiece and the locking component of the lockmaking machine tool based on the posture-motion linkage data of each component, and generating workpiece-locking component machining clearance data; In this embodiment of the present invention, the machining clearance between the workpiece and the locking element is detected based on the position-motion linkage data of each component, generating workpiece-locking element machining clearance data. This position-motion linkage data includes parameters such as the table guideway straightness error of 0.0015mm and the spindle bearing clearance of 0.001mm, which directly affect the machining clearance. Three sets of laser clearance sensors (measuring range 0-5mm, accuracy 0.0001mm, sampling frequency 10kHz) are installed around the contact area between the tool and the locking element. Two sets are arranged orthogonally in the horizontal direction, and one set is arranged vertically to measure the machining clearance in the X, Y, and Z axes, respectively. Taking the lock core drilling process as an example, when the spindle rotates at 30° / s and the table translates at 10mm / s, the sensors collect the clearance between the tool and the locking element hole wall in real time. The original detection data is corrected based on the trajectory offset caused by guideway deviation in the linkage data (for example, a 0.001mm offset in the X axis reduces the clearance by 0.0008mm). By continuously collecting 500 sets of data, the average clearance of the X-axis is calculated to be 0.012mm, the Y-axis is 0.011mm, and the Z-axis is 0.010mm, with a maximum clearance fluctuation of 0.002mm. These data are classified according to the processing stage (feed, cutting, and retract) to generate workpiece-locking part processing clearance data including the clearance value of each axis, the clearance fluctuation amplitude, and the corresponding component deviation influence coefficient.

[0051] Step S332: identifying the contact status of the workpiece and the lock component of the lock making machine tool according to the workpiece-lock component machining gap data, and generating workpiece-lock component contact status data; In an embodiment of the present invention, the contact status of the workpiece and the lock component is identified based on the workpiece-lock component machining gap data, and the workpiece-lock component contact status data is generated. The machining gap data shows an average X-axis gap of 0.012 mm. When the gap value is less than 0.005 mm, it is determined to be in a potential contact state, and when it is equal to 0, it is in an actual contact state. Resistance strain gauges (sensitivity coefficient 2.0, measurement range ±2000 με) are attached to key mating surfaces of the workpiece and the lock component (such as the lock body positioning hole and the outer diameter of the lock core). The strain gauges are connected to a dynamic strain gauge (sampling frequency 10 kHz) via a Wheatstone bridge to detect changes in contact stress in real time. When the machining gap data shows that the X-axis gap suddenly decreases from 0.01 mm to 0, the strain gauge detects that the contact stress suddenly increases from 0 to 50 MPa, which continues for 0.5 seconds and then drops to 30 MPa due to changes in cutting force. Combining the gap change rate (e.g., 0.002mm / ms) and peak stress, we distinguish between three states: elastic contact (stress ≤ 20MPa), plastic contact (20MPa < stress ≤ 80MPa), and rigid collision (stress > 80MPa). For example, when a lock cylinder is inserted into the lock body's positioning hole, it initially forms elastic contact (stress 15MPa) and transitions to plastic contact (stress 40MPa) as it moves deeper. The start time, stress value, duration, and corresponding gap change characteristics of these contact states are integrated to generate workpiece-locking component contact data.

[0052] Step S333: performing workpiece positioning and lock component deformation deviation analysis of the lock making machine tool based on the workpiece-lock component contact status data to generate workpiece positioning-lock component deformation deviation data; In this embodiment of the present invention, workpiece positioning and lock component deformation deviation analysis are performed based on workpiece-lock component contact data to generate workpiece positioning and lock component deformation deviation data. The contact data indicates plastic contact between the lock core and the lock body's locating hole in the X-axis direction (stress 40 MPa, duration 2 seconds). During this time, a laser tracker (0.001 mm accuracy) was used to track the positional changes of the workpiece positioning reference (two locating pins on the bottom surface of the lock body). The locating pin displacements of 0.003 mm in the X-axis and 0.002 mm in the Y-axis were measured, and the positioning deviation was calculated. Simultaneously, three displacement sensors (0.0005 mm accuracy) were placed on the lock component surface to detect deformation under contact stress. For example, under 40 MPa stress, the lock core exhibited a radial deformation of 0.0015 mm and an axial elongation of 0.0008 mm. The theoretical deformation values ​​were calculated using material mechanics formulas (for a mild steel lock core with an elastic modulus of 210 GPa, a diameter of 10 mm, and a length of 50 mm, the theoretical radial deformation was 0.0014 mm). Comparison with the actual measured values ​​revealed a deviation of 0.0001 mm. The relationship between contact stress and deformation is analyzed (for example, for every 10 MPa increase in stress, the radial deformation increases by 0.0003 mm). The positioning deviation coordinates (X=100.003 mm, Y=50.002 mm), the locking component deformation and the stress-deformation coefficient are integrated to generate the workpiece positioning-locking component deformation deviation data.

[0053] Step S334: performing workpiece and locking component error coupling positioning analysis of the locking machine based on the workpiece positioning-locking component deformation deviation data and the workpiece-locking component contact status data to generate workpiece-locking component error coupling positioning data of the locking machine.

[0054] In the embodiment of the present invention, error coupling positioning analysis is performed based on the workpiece positioning-locking component deformation deviation data and the workpiece-locking component contact condition data to generate workpiece-locking component error coupling positioning data. Axis positioning deviation , radial deformation of the lock ; Plastic contact causes stress peaks in contact condition data , corresponding to the contact stress influence coefficient (When σ≥30MPa, At that time ). Using the vector superposition error coupling model, the total error calculation formula is: (in is the total coupling error, is the positioning deviation component, is the deformation deviation component, is the contact stress influence coefficient. ), calculate The total axis deviation is 0.003mm + 0.0015mm × 0.8 (contact stress influence coefficient) = 0.0042mm. Combined with the clearance fluctuation of 0.002mm in the machining clearance data, , calculate the coupling error dynamic range as (0.8 is the transmission coefficient of gap fluctuation to coupling error.) The dynamic range of coupling error is calculated (0.0042 ± 0.0016 mm). By analyzing coupling errors under 10 different machining parameters, the main causes of error coupling were determined: positioning deviation accounts for 60% (caused by guideway straightness error), and deformation deviation accounts for 40% (caused by contact stress). These coupling error values, coupling coefficients, main cause ratios, and corresponding machining conditions are integrated to generate workpiece-locking component error coupling positioning data.

[0055] Furthermore, step S34 includes the following steps:

[0056] Step S341: performing a coordination test on the workpiece and lock component machining paths of the lock making machine tool based on the posture-motion linkage data of each component, and generating workpiece-lock component machining path coordination data; In this embodiment of the present invention, the coordination of the workpiece and locking component machining paths is checked based on the pose-motion linkage data of each component, generating workpiece-locking component machining path coordination data. This pose-motion linkage data includes parameters affecting the path, such as a guide rail straightness error of 0.0015mm and a spindle bearing clearance of 0.001mm. Two high-speed industrial cameras (1920×1080 resolution, 1000fps) are installed in the machine tool work area to capture the machining process from the XZ and YZ planes, while simultaneously marking high-contrast reference points on the tool and workpiece. Image recognition technology is used to extract the coordinates of the reference points and calculate the deviation between the actual machining path and the theoretical path. For example, if the theoretical path is a straight line from 100mm to 150mm on the X-axis, the actual path exhibits a wavy deviation of 0.002mm due to guide rail deviation. The deviation data is corrected based on the motion delay of each component in the linkage data (a 0.001s spindle response lag results in a 0.001mm path deviation). Path coordination indicators are calculated, including trajectory overlap (99.8%), speed synchronization rate (99.5%), and acceleration matching (99.2%). These indicators are classified according to the processing steps (milling, drilling, and tapping) to generate workpiece-locking part processing path coordination data including path deviation values, coordination indicators, and corresponding component influence weights.

[0057] Step S342: performing workpiece and lock component machining geometric error detection on the lock making machine tool based on the workpiece-lock component error coupling positioning data of the lock making machine tool, and generating workpiece-lock component machining geometric error data; In this embodiment of the present invention, workpiece and lock component machining geometric errors are detected based on workpiece-lock component error coupling positioning data to generate workpiece-lock component machining geometric error data. The total X-axis error in the workpiece-lock component error coupling positioning data is 0.0042mm, which serves as the basis for determining the inspection focus. A three-coordinate measuring machine (with a detection accuracy of 0.001mm) is used to inspect the key geometric features of the machined lock components. The theoretical outer diameter of the lock cylinder is 10mm, but the actual measurement is 10.002mm, with a cylindricity error of 0.001mm. The theoretical position coordinates of the keyhole are (10, 5)mm, but the actual measurement is (10.003, 5.002)mm, with a position error of 0.0036mm. Simultaneously, a laser interferometer (with a measurement accuracy of 0.001mm) is used to inspect the flatness of the workpiece positioning surface, with a theoretical value of 0.002mm and an actual measurement of 0.003mm. Combined with the error distribution in the coupled positioning data (60% due to positioning deviation), the geometric error is decomposed into dimensional error (diameter deviation 0.002mm), form error (cylindricity 0.001mm), and position error (position accuracy 0.0036mm). The deviation ratio of each error term is calculated (dimensional error deviation 20%), generating workpiece-locking component machining geometric error data that includes the geometric error type, value, deviation ratio, and corresponding coupling error contribution.

[0058] Step S343: performing a lock component geometry and thermal deformation error analysis of the lock component of the lock making machine tool based on the workpiece-lock component processing path coordination data and the workpiece-lock component processing geometric error data to generate lock component geometry-thermal deformation error data; In this embodiment of the present invention, a lock component geometry and thermal deformation error analysis is performed based on workpiece-lock component machining path compatibility data and workpiece-lock component machining geometric error data, generating lock component geometry-thermal deformation error data. The path compatibility data shows a trajectory overlap of 99.8% with a 0.002mm wavy offset; the geometric error data also shows a cylindricity error of 0.001mm. An infrared thermal imager (resolution 640×512, temperature range -20°C to 150°C, accuracy ±0.5°C) is placed in the lock component machining area to record the temperature field distribution in real time. For example, when the cutting area temperature rises from room temperature (25°C) to 60°C, the surrounding area has a temperature gradient of 5°C / mm. Combined with the path compatibility data showing path offset due to frictional heating (0.0005mm increase in offset for every 10°C temperature increase), the impact of thermal deformation on geometric error is analyzed. Using the thermal deformation formula, the lock core's longitudinal thermal expansion at 60°C is 0.003mm (material linear expansion coefficient 11×10^-6 / °C). Comparing this with the actual measured length deviation of 0.0028mm, we determined that thermal deformation accounts for 40% of the geometric error. By integrating the geometric error (cylindricity 0.001mm) with the thermal deformation error (length elongation 0.003mm), we generated lock component geometric-thermal deformation error data, including the error value, thermal deformation percentage, and a temperature-error curve.

[0059] Step S344: performing operation coupling error analysis of each component of the locking machine tool based on the locking piece geometry-thermal deformation error data and the posture-motion linkage data of each component, and generating operation coupling error data of each component.

[0060] In this embodiment of the present invention, the operational coupling errors of each component are analyzed based on the geometric and thermal deformation error data of the lock and the position-motion linkage data of each component, generating operational coupling error data for each component. Thermal deformation accounts for 40% of the geometric and thermal deformation error data, and the linkage data includes the position deviations of components such as the guide rail and spindle. Temperature sensors (measuring range -50°C to 150°C, accuracy 0.1°C) and vibration sensors (measuring range 0–50g, accuracy 0.001g) are installed at key locations on each component to measure temperature changes (guide rail temperature increases from 25°C to 35°C) and vibration amplitudes (spindle vibration 0.001mm). Analysis of the coupling relationship between component errors shows that a 10°C increase in guide rail temperature increases the straightness error by 0.0005mm. This, coupled with the 0.001mm spindle vibration, increases the total error to 0.002mm (rather than a simple addition of 0.0015mm). The coupling coefficients are calculated, and the error coupling coefficients between the guide rail and spindle are 1.3, and between the guide rail and worktable are 1.2. By analyzing 10 groups of different working conditions, the main forms of error coupling of each component (temperature-vibration coupling accounts for 60%) and the degree of influence (spindle error accounts for 45%, guide rail accounts for 35%) are determined, and the operating coupling error data of each component is generated, including coupling error value, coupling coefficient, component contribution ratio and working condition parameters.

[0061] Furthermore, step S343 includes the following steps: Perform workpiece and lock component cutting linkage trajectory offset detection based on workpiece-lock component machining path coordination data, and generate workpiece-lock component cutting linkage trajectory offset data; In an embodiment of the present invention, the workpiece and lock component cutting linkage trajectory offset detection is performed based on the workpiece-lock component processing path coordination data to generate the workpiece-lock component cutting linkage trajectory offset data. The workpiece-lock component processing path coordination data includes information such as a trajectory overlap of 99.8% and a 0.002mm wavy offset. Laser interferometers (with a measurement accuracy of 0.001mm and a sampling frequency of 5kHz) are installed in the X, Y, and Z axes of the machine tool to track the motion trajectory of the contact point between the tool cutting edge and the lock component in real time. Taking the lock core milling process as an example, the theoretical linkage trajectory is a straight line of 50-100mm on the X axis and 20mm on the Y axis, with a synchronous feed rate of 10mm / s. The actual trajectory collected by the laser interferometer is offset by 0.0012mm at 55mm on the X axis and 0.0018mm at 65mm. The maximum offset occurs at 75mm, reaching 0.002mm, and the offset direction is consistent with the wavy offset in the path coordination data. Combined with the 99.5% speed synchronization rate in the coordination data, the trajectory offset component caused by speed asynchrony (accounting for 30% of the total offset) was calculated. The offset data was categorized by cutting phase (entry, steady cutting, and exit), and the average offset for each phase (0.0015mm for entry, 0.001mm for steady cutting, and 0.0012mm for exit) and the corresponding time points were recorded. This generated workpiece-locking part cutting linkage trajectory offset data, including the offset value, offset phase, and speed synchronization influence coefficient for each axis.

[0062] Preferably, the lock piece contour partition detection is performed based on the workpiece-lock piece machining geometric error data to generate the lock piece contour partition data; In this embodiment of the present invention, lock component contour zoning detection is performed based on workpiece-lock component machining geometric error data to generate lock component contour zoning data. This workpiece-lock component machining geometric error data includes parameters such as the lock core outer diameter deviation of 0.002mm, cylindricity of 0.001mm, and keyhole position accuracy of 0.0036mm. A high-precision optical profilometer (measuring range 0-50mm, vertical resolution 0.001μm) is used to scan the entire lock component contour with a scanning step size of 0.01mm. A three-dimensional coordinate point cloud of the lock core outer diameter, keyhole edge, and end face contours is obtained. The contour is divided into functional areas: Area A (lock core outer diameter mating surface, 30mm length), Area B (keyhole periphery, 10mm diameter range), and Area C (end face positioning surface, 15mm diameter). Geometric error values ​​were calculated for each zone: cylindricity of Zone A was 0.001mm, and diameter deviation was 0.002mm; keyhole position accuracy of Zone B was 0.0036mm, and profile accuracy was 0.0015mm; and flatness of Zone C was 0.002mm. By comparing the error distribution within the machining geometric error data, the error contribution of each zone was determined (40% for Zone A, 50% for Zone B, and 10% for Zone C). The error-exceeding zones were marked (80% for keyhole position error in Zone B). This generated lock contour partition data, which included the zone boundary coordinates, each zone's error value, error contribution, and an error mark.

[0063] Preferably, based on the workpiece-locking component cutting linkage trajectory offset data and the lock component contour partition data, the workpiece and lock component thermal deformation analysis of the lock making machine tool is performed to generate workpiece-lock component thermal deformation data; In this embodiment of the present invention, thermal deformation analysis of the workpiece and locking component is performed based on workpiece-locking component cutting trajectory offset data and locking component contour partitioning data, generating workpiece-locking component thermal deformation data. The cutting trajectory offset data shows a maximum offset of 0.002mm at 75mm. The error in Zone A (external cylindrical mating surface) in the locking component contour partitioning data accounts for 40%. Micro-thermocouples (measuring range 0-300°C, accuracy 0.1°C) are embedded in the locking component's zones A, B, and C. The thermocouple leads are connected to a data acquisition system (sampling frequency 1kHz) to monitor temperature changes during cutting in real time. When the trajectory offset reaches 0.002mm, the thermocouple in Zone A shows a temperature increase from room temperature (25°C) to 65°C, in Zone B to 60°C, and in Zone C to 50°C. The temperature gradient is positively correlated with the offset (with each 10°C increase in temperature resulting in a 0.0005mm increase in offset). Considering the linear expansion coefficient of the lock component material (mild steel) of 11×10^-6 / °C, the thermal expansion of Zone A due to a 40°C temperature increase was calculated to be 0.0044mm in the diameter direction. Comparing this with the 0.002mm diameter deviation in Zone A from the contour partition data, it was determined that thermally induced deformation accounted for 45% of the diameter deviation. Finite element analysis was used to calculate the thermal stress distribution in each zone (with a thermal stress of 20MPa in Zone A). This generated workpiece-lock component thermal deformation data, including the temperature values, thermal expansion, thermal stress, and deformation percentage for each zone.

[0064] Preferably, the lock geometry and thermal deformation error analysis of the lock machine tool is performed based on the workpiece-lock thermal deformation data and the lock and workpiece-lock cutting linkage trajectory offset data to generate the lock geometry-thermal deformation error data.

[0065] In the embodiment of the present invention, the geometric and thermal deformation errors of the lock are analyzed based on the workpiece-locking component thermal deformation data and the workpiece-locking component cutting linkage trajectory offset data to generate the lock component geometric-thermal deformation error data. The thermal expansion of area A in the thermal deformation data is 0.0044mm, and the maximum offset in the cutting linkage trajectory offset data is 0.002mm. The geometric error is decomposed into non-thermal geometric error and thermal deformation error, and the formula is used. Calculate the athermal geometric error, where is the non-thermal geometric error, is the actual deviation, is the thermal expansion, is the thermal expansion contribution coefficient (A area ), from which the non-thermal deviation of the diameter of zone A = 0.002mm-0.0044mm×0.45=0.0011mm; using the formula Calculate the effect of thermally induced deformation on trajectory deviation, where is the thermally induced trajectory offset, is the total offset, is the temperature effect ratio ( ),have to The error of each partition of the lock is analyzed by superposition, and the formula is used Calculate the total error, the total error of area A = 0.0011mm + 0.0044mm × 0.45 = 0.002mm; the total error of the keyhole in area B = 0.0014mm + 0.0022mm = 0.0036mm, which is consistent with the processing geometric error data. The error coupling model is established using the formula Quantify the interaction between thermal deformation and geometric errors, where is the geometric error increment, is the thermal deformation increment, is the error amplification coefficient (β=1.2), that is, for every 0.001mm increase in thermal deformation, the geometric error is amplified by 1.2 times, and the locking part geometric-thermal deformation error data including the non-thermal / thermal error value of each partition, error coupling coefficient, total error and temperature correlation curve are generated.

[0066] Furthermore, step S4 includes the following steps: Step S41: identifying the error characteristics of the workpiece and the locking component of the locking machine tool according to the coupling error data of the operation of each component, and generating the workpiece-locking component error characteristic data; In an embodiment of the present invention, workpiece and lock component error characteristics of a lockmaking machine tool are identified based on the coupling error data of each component, generating workpiece-lock component error characteristic data. The coupling error data for each component includes the coupling error value, coupling coefficient, and component contribution. For example, the coupling error between the spindle and the guide rail is 0.002mm, the coupling coefficient is 1.3, and the spindle error contributes 45%. Using an error feature extraction algorithm, this data is analyzed multi-dimensionally to identify characteristics based on error value, distribution pattern, and variation trend. Using a data visualization tool, the error data is plotted against a processing time series. It is observed that after 30 minutes of continuous processing, the error shows an increasing trend of 0.0005mm, and the error fluctuation amplitude in the X-axis direction (0.0015mm) is greater than that in the Y-axis (0.001mm). Based on the lock component processing process, typical error characteristics were identified: drilling errors are primarily due to positional deviation (accounting for 60%), while milling errors are primarily due to shape errors (accounting for 55%). The error value is positively correlated with component temperature (with an increase of 5°C in temperature resulting in an increase of 0.0003mm in error). By calculating the standard deviation (0.0008mm), peak value (0.002mm), and mean value (0.0012mm) of the error, the statistical characteristics of the error are clarified, and workpiece-locking part error characteristic data is generated, including error type (position, shape, size), characteristic parameters (standard deviation, peak value), related factors (temperature, processing time), and corresponding process.

[0067] Step S42: Analyzing the roughness of the workpiece and the lock component machining surfaces of the lock making machine tool based on the workpiece-lock component error characteristic data to generate workpiece-lock component machining surface roughness data; In an embodiment of the present invention, the roughness of the workpiece and lock processing surface of the lock making machine tool is analyzed based on the workpiece-lock error characteristic data, and the workpiece-lock processing surface roughness data is generated. In the workpiece-lock error characteristic data, the milling process is mainly characterized by shape error, accounting for 55%, which is closely related to the roughness of the processing surface. A white light interferometer (measuring range 0-10mm, vertical resolution 0.1nm) is used to scan the processing surface with a scanning area of ​​5mm×5mm and a sampling point spacing of 0.001mm to obtain three-dimensional data of the surface micro-contour. The data is filtered to remove the long-wave component (wavelength>0.8mm), retain the short-wave component reflecting the roughness, and calculate the arithmetic mean deviation of the contour. and maximum profile height , milling surface The value is 1.2μm, The value is 6.5μm; the Ra value of the drilling surface is 1.5μm, The value is 8.0μm. Combined with the shape error in the error feature data (such as the groove width deviation of 0.002mm), the correlation between the roughness and the error is analyzed and it is found that For every 0.3μm increase in the value, the shape error increases by 0.0005mm. Classify the roughness data by the type of machined surface (plane, curved surface, hole wall), and record the roughness of different types of surfaces. , Rz value and correlation coefficient with error characteristics to generate workpiece-locking part machining surface roughness data including roughness parameters, surface type, correlation coefficient and corresponding error characteristics.

[0068] Step S43: setting the precision compensation control parameters of the lock-making machine tool according to the roughness data of the workpiece-locking component processing surface, and generating precision compensation control parameter data.

[0069] In an embodiment of the present invention, the precision compensation control parameters of a lockmaking machine tool are set based on the workpiece-locking component machining surface roughness data to generate precision compensation control parameter data. The machining surface roughness data shows the milling groove surface Ra value of 1.2μm, and the correlation coefficient between Ra and form error is 0.0005mm / 0.3μm. Based on this, the core parameters for precision compensation are determined: feed rate, spindle speed, and depth of cut. These parameters directly affect the roughness of the machined surface and the magnitude of the error. Through orthogonal experimental methods, different parameter combinations were set for trial machining. When the feed rate was 5mm / s, the spindle speed was 3000r / min, and the cutting depth was 0.2mm, the Ra value dropped to 0.8μm, and the form error was reduced by 0.0007mm. In combination with the correlation between temperature and error in the error characteristic data, a temperature compensation coefficient was set (for every 5°C increase, the feed rate decreases by 0.2mm / s). Dedicated compensation parameters are set for different machining processes: The drilling process focuses on adjusting the positioning compensation value (X-axis +0.001mm, Y-axis +0.0008mm), and the slot milling process adjusts the trajectory correction factor (profile correction amount 0.0012mm). These parameters are linked to the target value of the machined surface roughness (Ra ≤ 1.0μm) to ensure that the parameter settings can control the roughness within the allowable range. Precision compensation control parameter data is generated, including feed rate, spindle speed, cutting depth, temperature compensation coefficient, positioning compensation value, and trajectory correction coefficient.

[0070] Furthermore, step S5 includes the following steps: Step S51: Perform a coordinated analysis of the power and execution structure of the lock making machine tool based on the precision compensation control parameter data to generate power-execution structure coordinated data. In this embodiment of the present invention, a coordinated analysis of the power and actuator structure of a lockmaking machine tool is performed based on precision compensation control parameter data to generate power-actuator coordination data. This precision compensation control parameter data includes parameters such as a feed rate of 5 mm / s, a spindle speed of 3000 rpm, and a temperature compensation coefficient (feed rate decreases by 0.2 mm / s for every 5°C increase in temperature). A torque sensor (range 0-100 N·m, accuracy 0.01 N·m) and a speed sensor (range 0-5000 rpm, accuracy 1 rpm) are installed on the power structure (spindle motor and feed motor). A displacement sensor (accuracy 0.0005 mm) and a vibration sensor (range 0-10 g, accuracy 0.001 g) are installed on the actuator structure (guide rails, lead screw, and tool) to simultaneously collect dynamic data on power output and actuator movements. When the spindle speed was increased to 3000 rpm according to the compensation parameters, the motor torque increased from 20 N·m to 35 N·m. Simultaneously, the screw displacement response lagged by 0.001 seconds, resulting in the actual feed rate being 0.05 mm / s lower than the set value. By analyzing the response time difference (the actuator displacement reached stability 0.002 seconds after the motor torque reached its stable value) and the parameter matching (the torque-to-feed rate ratio remained stable at 7 N·m·s / mm), the synergy coefficient (98.5%) was determined. The resulting power-actuator synergy data included dynamic parameters (torque, speed), actuator parameters (displacement, speed), response time difference, synergy coefficient, and a correction for temperature effects.

[0071] Step S52: performing correction of each motion unit of the lockmaking machine tool and collaborative detection of the machining path according to the power-execution structure collaborative data, and generating each motion unit correction-machining path collaborative data; In an embodiment of the present invention, corrections are made to each motion unit of a lockmaking machine tool and collaborative detection of the machining path is performed based on the power-actuator coordination data, generating correction and machining path coordination data for each motion unit. The power-actuator coordination data shows a lead screw displacement response lag of 0.001s and a coordination coefficient of 98.5%. Based on this, the control parameters of each motion unit (spindle, worktable, and tool holder) are corrected: the spindle rotation angle is corrected by +0.005° (to compensate for response lag), the worktable X-axis feed rate is corrected by +0.001mm (to offset displacement deviation), and the tool holder Z-axis positioning is corrected by -0.0005mm. A laser tracker (measuring range 0-50m, accuracy 0.001mm) is used to track the corrected motion trajectory in real time. Comparing the corrected trajectory with the theoretical machining path (e.g., the straight line from the lock core hole coordinates (100, 50, 0) to (100, 50, 20)) reveals that the deviation between the actual and theoretical trajectory after correction has decreased from 0.002mm to 0.0008mm. At the same time, a high-speed camera (1000fps) was used to capture the coordinated movements of multiple motion units and analyze the synchronization between spindle rotation and table feed. After correction, the synchronization error was reduced from 0.0015s to 0.0005s. Correction parameters (angle and displacement corrections) and path deviation data were categorized by machining process. This generated correction-path coordination data for each motion unit, including motion unit correction values, trajectory deviations, synchronization errors, and a 99.2% coordination pass rate.

[0072] Step S53: Based on the correction-machining path collaborative data of each motion unit, the operation coupling error data of each component is subjected to real-time precision compensation and machining trajectory correction of the locking machine tool to generate real-time precision compensation and machining trajectory data.

[0073] In an embodiment of the present invention, the real-time precision compensation and machining trajectory correction of the locking machine tool are performed on the running coupling error data of each component based on the correction-machining path collaborative data of each motion unit, and real-time precision compensation and machining trajectory data are generated. In the correction-machining path collaborative data of each motion unit, the trajectory deviation is 0.0008mm, the synchronization error is 0.0005s, and the running coupling error data of each component includes a spindle and guide rail coupling error of 0.002mm. The real-time compensation algorithm is loaded into the CNC system, and the output instructions are dynamically adjusted according to the correction value in the collaborative data: when it is detected that the guide rail temperature rises to 30°C (5°C higher than the room temperature), the feed speed is immediately reduced from 5mm / s to 4.8mm / s according to the compensation coefficient; when the coupling error data shows that the X-axis deviation reaches 0.001mm, the worktable X-axis reverse compensation amount is automatically increased by 0.0008mm. Using a grating ruler (resolution 0.0001mm), the actual position after correction is fed back in real time. Compared with the theoretical trajectory, the hole position deviation in the drilling process is reduced from 0.0036mm to 0.001mm, and the slot width deviation in the slot milling process is reduced from 0.002mm to 0.0005mm. The time point, compensation amount, and trajectory coordinates before and after each compensation are recorded (for example, before correction (100.002, 50.001), after correction (100.000, 50.000)). Real-time precision compensation and machining trajectory data are generated, including real-time compensation parameters (speed, displacement correction amount), trajectory coordinate sequence, error attenuation curve, and process qualification rate (99.9%).

[0074] The present invention is therefore intended to be illustrative and non-restrictive in all respects, with the scope of the invention being defined by the appended claims rather than the foregoing description, and all changes that come within the meaning and range of equivalents of the application documents are intended to be embraced therein.

[0075] The foregoing description is intended only to provide specific embodiments of the present invention, which will enable those skilled in the art to understand and implement the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention is not intended to be limited to the embodiments shown herein, but is to be construed in the widest possible manner consistent with the principles and novel features disclosed herein.

Claims

1. A method for error coupling compensation and positioning accuracy control of a lock making machine tool, characterized in that: The following steps are involved: Step S1: collecting the structure and operation data of the lock making machine tool through sensors, performing an operation status detection of the lock making machine tool based on the structure and operation data of the lock making machine tool, and generating the operation status data of the lock making machine tool; Step S2: performing spatial transformation detection of each motion unit of the locking machine tool based on the structure and operation data of the locking machine tool and the operation status data of the locking machine tool, and generating spatial transformation data of each motion unit; Step S3: performing a workpiece and lock component error coupling positioning analysis of the locking machine tool based on the spatial transformation data of each motion unit to generate workpiece-lock component error coupling positioning data of the locking machine tool; performing an operation coupling error analysis of each component of the locking machine tool based on the workpiece-lock component error coupling positioning data of the locking machine tool to generate operation coupling error data of each component; Step S4: setting the precision compensation control parameters of the lock making machine tool according to the coupling error data of each component operation, and generating precision compensation control parameter data; Step S5: Based on the precision compensation control parameter data, the operation error coupling data of each component is subjected to real-time precision compensation and machining trajectory correction of the locking machine tool to generate real-time precision compensation and machining trajectory data.

2. The error coupling compensation and positioning accuracy control method for a lock making machine tool according to claim 1, characterized in that: Step S1 includes the following steps: Step S11: collecting the structure and operation data of the lock-making machine tool through sensors, and analyzing the structural characteristics and operation characteristics of the lock-making machine tool based on the structure and operation data of the lock-making machine tool to generate the structure characteristic-operation characteristic data of the lock-making machine tool; Step S12: Analyzing the operating parameters of the lock-making machine tool based on the structural characteristics-operation characteristic data of the lock-making machine tool to generate the operating parameter data of the lock-making machine tool; Step S13: performing operation calibration processing of the locking machine tool on the structural feature-operation characteristic data of the locking machine tool based on the operation parameter data of the locking machine tool to generate operation calibration data of the locking machine tool; Step S14: performing an operation status detection of the locking machine tool according to the operation calibration data of the locking machine tool, and generating operation status data of the locking machine tool.

3. The error coupling compensation and positioning accuracy control method for a lock making machine tool according to claim 1, characterized in that: Step S2 includes the following steps: Step S21: Analyzing the structural connection relationship of the lock-making machine tool according to the structure and operation data of the lock-making machine tool to generate structural connection relationship data of the lock-making machine tool; Step S22: performing posture change detection on each motion unit of the locking machine tool according to the motion status data of the locking machine tool, and generating posture change data of each motion unit; Step S23: performing structural connection and drive analysis on the locking machine based on the posture change data of each motion unit and the structural connection relationship data of the locking machine to generate structural connection-drive data of the locking machine; Step S24: performing structural linkage drive change detection of the locking machine tool according to the structural connection-drive data of the locking machine tool, and generating structural linkage drive change data of the locking machine tool; Step S25: performing spatial transformation detection on each motion unit of the locking machine tool according to the structural linkage drive change data of the locking machine tool, and generating spatial transformation data of each motion unit.

4. The error coupling compensation and positioning accuracy control method for a lock making machine tool according to claim 1, characterized in that: Step S3 includes the following steps: Step S31: analyzing the relative posture of the workpiece and the locking component of the locking machine tool according to the spatial transformation data of each motion unit to generate workpiece-locking component relative posture data; Step S32: Analyzing the position and motion linkage of each component of the lockmaking machine tool based on the relative position and motion data of the workpiece and the locking component to generate position and motion linkage data of each component; Step S33: performing workpiece and lock component error coupling positioning analysis of the locking machine tool based on the posture-motion linkage data of each component, and generating workpiece-lock component error coupling positioning data of the locking machine tool; Step S34: analyzing the operation coupling errors of the components of the locking machine based on the posture-motion linkage data of the components and the workpiece-locking piece error coupling positioning data of the locking machine, and generating the operation coupling error data of the components.

5. The error coupling compensation and positioning accuracy control method for a lock making machine tool according to claim 4, characterized in that: Step S32 includes the following steps: Step S321: performing a main structure analysis of the workpiece and the lock component matching of the lock making machine tool based on the workpiece-lock component relative posture data, and generating main component data of the workpiece-lock component matching; Step S322: performing workpiece and lock component coordination component analysis of the lockmaking machine tool based on the workpiece-lock component matching main component data to generate workpiece-lock component coordination component data; Step S323: analyzing the spatial rotation and translation characteristics of the workpiece and the lock component of the lock making machine based on the workpiece-lock component matching main component data and the workpiece-lock component coordination component data to generate spatial rotation-translation motion characteristic data of the workpiece and the lock component; Step S324: performing position and motion linkage analysis of components of the locking machine tool based on the spatial rotation-translation motion characteristic data of the workpiece and the locking component, and generating position and motion linkage data of each component.

6. The error coupling compensation and positioning accuracy control method for a lock making machine tool according to claim 4, characterized in that: Step S33 includes the following steps: Step S331: Detecting the machining clearance between the workpiece and the locking component of the lockmaking machine tool based on the posture-motion linkage data of each component, and generating workpiece-locking component machining clearance data; Step S332: identifying the contact status of the workpiece and the lock component of the lock making machine tool according to the workpiece-lock component machining gap data, and generating workpiece-lock component contact status data; Step S333: performing workpiece positioning and lock component deformation deviation analysis of the lock making machine tool based on the workpiece-lock component contact status data to generate workpiece positioning-lock component deformation deviation data; Step S334: performing workpiece and locking component error coupling positioning analysis of the locking machine based on the workpiece positioning-locking component deformation deviation data and the workpiece-locking component contact status data to generate workpiece-locking component error coupling positioning data of the locking machine.

7. The error coupling compensation and positioning accuracy control method for a lock making machine tool according to claim 4, characterized in that: Step S34 includes the following steps: Step S341: performing a coordination test on the workpiece and lock component machining paths of the lock making machine tool based on the posture-motion linkage data of each component, and generating workpiece-lock component machining path coordination data; Step S342: performing workpiece and lock component machining geometric error detection on the lock making machine tool based on the workpiece-lock component error coupling positioning data of the lock making machine tool, and generating workpiece-lock component machining geometric error data; Step S343: performing a lock component geometry and thermal deformation error analysis of the lock component of the lock making machine tool based on the workpiece-lock component processing path coordination data and the workpiece-lock component processing geometric error data to generate lock component geometry-thermal deformation error data; Step S344: performing operation coupling error analysis of each component of the locking machine tool based on the locking piece geometry-thermal deformation error data and the posture-motion linkage data of each component, and generating operation coupling error data of each component.

8. The error coupling compensation and positioning accuracy control method for a lock making machine tool according to claim 7, characterized in that: Step S343 includes the following steps: Perform workpiece and lock component cutting linkage trajectory offset detection based on workpiece-lock component machining path coordination data, and generate workpiece-lock component cutting linkage trajectory offset data; Perform lock part contour partition detection based on workpiece-lock part machining geometric error data to generate lock part contour partition data; Based on the workpiece-locking part cutting linkage trajectory offset data and the lock part contour partition data, the workpiece and lock part thermal deformation analysis of the lock making machine tool is performed to generate the workpiece-lock part thermal deformation data; Based on the workpiece-locking part thermal deformation data and the lock part and workpiece-locking part cutting linkage trajectory offset data, the lock part geometry and thermal deformation error of the lock making machine tool are analyzed to generate the lock part geometry-thermal deformation error data.

9. The error coupling compensation and positioning accuracy control method for a lock making machine tool according to claim 1, characterized in that: Step S4 includes the following steps: Step S41: identifying the error characteristics of the workpiece and the locking component of the locking machine tool according to the coupling error data of the operation of each component, and generating the workpiece-locking component error characteristic data; Step S42: Analyzing the roughness of the workpiece and the lock component machining surfaces of the lock making machine tool based on the workpiece-lock component error characteristic data to generate workpiece-lock component machining surface roughness data; Step S43: setting the precision compensation control parameters of the lock-making machine tool according to the roughness data of the workpiece-locking component processing surface, and generating precision compensation control parameter data.

10. The error coupling compensation and positioning accuracy control method for a lock making machine tool according to claim 1, characterized in that: Step S5 includes the following steps: Step S51: Perform a coordinated analysis of the power and execution structure of the lock making machine tool based on the precision compensation control parameter data to generate power-execution structure coordinated data. Step S52: performing correction of each motion unit of the lockmaking machine tool and collaborative detection of the machining path according to the power-execution structure collaborative data, and generating each motion unit correction-machining path collaborative data; Step S53: Based on the correction-machining path collaborative data of each motion unit, the operation coupling error data of each component is subjected to real-time precision compensation and machining trajectory correction of the locking machine tool to generate real-time precision compensation and machining trajectory data.

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