A numerical control compensation method and a numerical control system based on multi-physical field coupling digital twinning

Abstract

The application relates to a numerical control compensation method and a numerical control system based on multi-physical field coupling digital twinning, and belongs to the technical field of precision numerical control machining. In view of the dynamic machining error problem caused by mechanical vibration, thermal deformation and electromagnetic interference multi-field coupling, the following solutions are proposed: multi-source data is collected in real time through a three-axis vibration sensor, a temperature array and current harmonic analysis; a three-field coupling model is constructed to quantize the nonlinear relationship of the thermal integration effect, the cutting force change rate and the weighted sum of electromagnetic energy; a hierarchical compensation mechanism of a linear motor and a piezoelectric ceramic is adopted to realize full-scale error correction from millimeter-level coarse adjustment to nanometer-level fine adjustment; model parameters are dynamically optimized in combination with a sliding window least square method to ensure adaptive accuracy under working condition changes. The system improves machining profile accuracy through an edge computing unit and a double closed-loop control strategy, can realize real-time early warning of abnormal phenomena such as main shaft dynamic balance failure, and significantly improves system reliability and machining consistency.

Description

Technical Field

[0001] This invention relates to the field of precision CNC machining technology, specifically to a CNC compensation method and CNC system based on multi-physics field coupled digital twins. Background Technology

[0002] The machining accuracy of CNC machine tools directly determines the performance of core components. However, under complex working conditions such as high speed and heavy load, the strong coupling effect of multiple physical fields such as mechanical vibration, thermal deformation, and electromagnetic interference can cause dynamic error superposition.

[0003] Mechanical vibration: Sudden changes in cutting force cause high-frequency chatter (>5kHz) in the tool-workpiece system, leading to micron-level displacement deviations;

[0004] Thermal deformation: When the spindle temperature rise rate reaches 0.5℃ / s, the cumulative thermal expansion error exceeds 15μm within 3 hours;

[0005] Electromagnetic interference: High-frequency harmonics (above 10kHz) from the motor induce position drift in the servo system through conductive coupling.

[0006] Traditional error compensation techniques often employ single-physics modeling or static parameter compensation, which have significant drawbacks:

[0007] Single field model: It models only temperature or vibration independently, ignores the interaction of multiple fields (such as temperature rise aggravating bearing clearance vibration), and has a compensation residual rate of up to 30%.

[0008] Limitations of fixed parameters: The compensation coefficient based on offline calibration cannot adapt to dynamic changes in processing load, and the error drift exceeds 8μm after 4 hours of continuous processing;

[0009] Actuator bottleneck: linear motors have insufficient large stroke compensation resolution (≥5μm), while piezoelectric ceramics have limited nanoscale fine-tuning stroke (<50μm), making it difficult to meet coarse-fine compensation requirements.

[0010] The aforementioned technical bottlenecks have resulted in existing CNC systems generally maintaining a contour accuracy of ±5μm in five-axis linkage machining, which has hindered the further development of ultra-precision manufacturing technology. Summary of the Invention

[0011] In order to solve the problems of the prior art, the present invention provides a numerical control compensation method and numerical control system based on multi-physics field coupled digital twin.

[0012] To solve the above-mentioned technical problems, the present invention is achieved through the following technical solution: Firstly, a numerical control compensation method and numerical control system based on multi-physics field coupled digital twins, comprising the following steps:

[0013] S1: Real-time acquisition of multi-source data:

[0014] Mechanical vibration signals are acquired by a three-axis vibration sensor deployed on the machine tool body at a sampling frequency of not less than 50kHz.

[0015] A temperature sensor array is used to monitor the spindle temperature rise, with a temperature measurement resolution of 0.1 degrees Celsius.

[0016] The motor drive current signal is acquired by a current sensor, and harmonic energy analysis is performed on the signal in the 0 to 10 kHz frequency band.

[0017] S2: Multiphysics coupling modeling:

[0018] A three-field coupled model incorporating mechanical vibration, thermal deformation, and electromagnetic interference is established, wherein:

[0019] The thermal deformation component is positively correlated with the temperature integral value and the temperature rise rate.

[0020] The mechanical dynamic response component is proportional to the rate of change of cutting force;

[0021] The correlation between the electromagnetic interference component and the energy weighted sum of each frequency band of current harmonics;

[0022] The coefficient of thermal expansion, the coefficient of mechanical response, and the electromagnetic susceptibility coefficient are set as the core parameters of the model.

[0023] S3: Real-time error compensation:

[0024] Coarse compensation stage: The linear motor completes the position correction of ±2 mm stroke within 2 milliseconds, and the positioning accuracy reaches ±1 micrometer;

[0025] Fine compensation stage: Piezoelectric ceramic actuators are used to achieve micro-displacement adjustment with a resolution of 5 nanometers within 0.1 milliseconds;

[0026] Graded compensation is performed based on the magnitude of the overall error: coarse compensation is initiated when the absolute error is ≥1 micrometer, and fine compensation is initiated only when the error is between 0.1 micrometer and 1 micrometer.

[0027] S4: Dynamic parameter update:

[0028] The coefficients of the coupled model are updated every 5 minutes based on the least squares optimization algorithm.

[0029] The optimization objective is to minimize the sum of squared residuals between the actual measurement error and the model prediction.

[0030] A sliding window mechanism is used to retain the most recent 300 data points for parameter iteration.

[0031] In one specific embodiment of the first aspect, current harmonic energy analysis includes:

[0032] The 0-10kHz frequency band is divided into 10 sub-bands with a bandwidth of 1kHz;

[0033] An exponentially decreasing weighting is applied to the harmonic energy of each sub-band, with the weight of the high-frequency band being lower than that of the low-frequency band.

[0034] The total electromagnetic interference energy is calculated by multiplying the square of the current amplitude in each frequency band by its corresponding weight.

[0035] In this aspect, high-precision compensation is achieved through multi-source data fusion and dynamic modeling. The specific process is as follows:

[0036] 1. Real-time acquisition of multi-source data: A high-precision sensor network is deployed at key locations on the machine tool, including a triaxial vibration sensor (sampling rate ≥50kHz), a fiber optic temperature sensor array (resolution 0.1℃), and a current harmonic analysis module (0-10kHz frequency band). Multi-physics data are aligned using timestamp synchronization technology to eliminate timing deviations, and an adaptive filtering algorithm is used to suppress environmental noise interference.

[0037] 2. Multiphysics Coupling Modeling: A joint influence model of mechanical vibration, thermal deformation, and electromagnetic interference is constructed. The thermal deformation component is calculated by integrating the spindle temperature field; the mechanical response component is correlated with the cutting force change rate and the vibration phase difference; and the electromagnetic interference component is based on the weighted and quantized current harmonic energy. The core parameters of the model (thermal expansion coefficient, mechanical response coefficient, and electromagnetic susceptibility coefficient) are calibrated to initial values ​​through no-load experiments and dynamically optimized during machining.

[0038] 3. Real-time Error Compensation: A coarse-fine dual-stage compensation architecture is adopted. A linear motor (±2mm stroke, 2ms response) is responsible for large error correction, while piezoelectric ceramics (5nm resolution, 0.1ms response) realize micro-displacement adjustment. The compensation strategy is triggered in stages according to the error magnitude: when the error is ≥1μm, the two stages work together; when the error is 0.1-1μm, only fine compensation is activated; and when the error is <0.1μm, compensation is performed after the cumulative error exceeds the threshold.

[0039] 4. Dynamic Parameter Update: Every 5 minutes, based on 300 sets of data within a sliding window, the model parameters are iteratively optimized using a least squares algorithm, with the goal of minimizing the sum of squared residuals. Physical constraints (such as limits on the range of thermal expansion coefficients) are introduced during the parameter update process to prevent overfitting and ensure model stability.

[0040] In one specific implementation of the first aspect, multi-source data acquisition employs time synchronization technology, including:

[0041] Configure each sensor with a clock synchronization module with microsecond-level precision;

[0042] Time-domain interpolation is performed on the vibration signal to match the temperature sampling time reference;

[0043] Create a circular data buffer to store the raw waveform data of the most recent 2 seconds.

[0044] In one specific embodiment of the first aspect, the composite compensation mechanism satisfies the following control requirements:

[0045] The linear motor and piezoelectric ceramic are mounted in a coaxial series structure;

[0046] The coaxiality error of the dual-axis motion direction is ensured to be ≤0.5 micrometers / 100 millimeters through laser calibration;

[0047] Set up anti-motion interference logic: when the piezoelectric ceramic reaches the travel limit, trigger the linear motor position reset.

[0048] In one specific embodiment of the first aspect, it further includes:

[0049] The fault self-diagnosis module is implemented as follows:

[0050] A system alarm is triggered when the sum of squared residuals after three consecutive parameter optimizations exceeds 10 square micrometers.

[0051] Compare the deviation rate between the predicted compensation amount and the actual compensation amount. If the deviation rate is greater than 15% for 10 consecutive minutes, the sensor is considered abnormal.

[0052] Spindle faults are identified through spectrum analysis: a warning signal is output when the fundamental frequency vibration energy accounts for more than 40%.

[0053] Secondly, a numerical control system based on multi-physics coupled digital twins includes:

[0054] Multiphysics sensing unit: includes at least 6-channel temperature sensing, 3-axis vibration sensing, and 3-phase current sensing modules;

[0055] Edge computing unit: Equipped with a programmable system-on-a-chip (SoC) and running a real-time operating system;

[0056] Composite compensation actuator: a two-stage motion system consisting of a linear motor and a piezoelectric ceramic actuator;

[0057] Human-computer interaction interface: Real-time display of the trend of coupling coefficient change and historical compensation statistics charts.

[0058] In the second aspect, the method is implemented through hardware collaboration and intelligent control, and its core components are as follows:

[0059] 1. Multiphysics Sensing Unit: Includes a high-dynamic vibration sensing module (bandwidth DC-30kHz), a distributed temperature monitoring network (6-channel fiber Bragg grating), and a three-phase current harmonic detection circuit (200kHz sampling rate). Sensor data is preprocessed (time-domain interpolation, normalization) before being input into the edge computing unit.

[0060] 2. Edge Computing Unit: Equipped with a programmable system-on-a-chip (Xilinx Zynq UltraScale+) and running a real-time operating system (VxWorks 7). Multi-threaded architecture enables parallel processing: a high-frequency vibration signal thread (0.1ms cycle) extracts time-domain features, a temperature modeling thread (1ms cycle) reconstructs the three-dimensional temperature field, and an electromagnetic analysis thread (5ms cycle) calculates harmonic energy weights.

[0061] 3. Composite Compensation Actuator: A linear motor and piezoelectric ceramic are connected in series, and coaxiality (≤0.5μm / 100mm) is ensured by laser calibration. In the dual closed-loop control strategy, the outer loop position PID (bandwidth ≥500Hz) adjusts the macroscopic position, while the inner loop impedance control (stiffness 1-100N / μm) suppresses high-frequency disturbances. An acceleration feedforward mechanism compensates for inertial errors in advance during rapid motion.

[0062] 4. Human-Computer Interaction and Diagnostic Module: Real-time display of coupling coefficient change curves and compensation quantity statistics charts. The fault diagnosis module achieves early fault detection and improves system reliability through residual analysis (three consecutive threshold alarms) and spectrum characteristics (fundamental frequency ratio > 40% warning).

[0063] In one specific implementation of the second aspect, the edge computing unit is configured with a multi-task processing architecture, including:

[0064] High-frequency vibration signal processing thread (execution cycle 0.1 milliseconds);

[0065] Temperature field modeling thread (execution cycle 1 millisecond);

[0066] Electromagnetic interference analysis thread (execution cycle 5 milliseconds);

[0067] Each thread exchanges data through shared memory, with a memory access latency of ≤50 nanoseconds.

[0068] In one specific implementation of the second aspect, the composite compensation actuator employs a dual closed-loop control strategy:

[0069] The outer loop position control uses a proportional-integral-derivative algorithm with a control bandwidth of ≥500Hz;

[0070] The inner loop force control is based on a variable stiffness-resistance model, with stiffness adjustment range of 1-100 N / μm;

[0071] An acceleration feedforward mechanism is set up to be automatically enabled when the command position change rate is greater than 1 mm / s.

[0072] The beneficial effects of this invention are as follows:

[0073] 1. By integrating a three-field coupling model of mechanical vibration, thermal deformation, and electromagnetic interference, accurate prediction of comprehensive errors under complex working conditions was achieved. Experimental data shows that this scheme reduces the profile error of aerospace titanium alloy blades from ±5.2μm to ±1.3μm, improving accuracy by 75%. The piezoelectric ceramic fine compensation layer further enables fine-tuning at a resolution of 5nm, resolving the technical contradiction between large stroke and high precision inherent in traditional single compensation mechanisms.

[0074] 2. The multi-threaded architecture based on edge computing units (vibration processing cycle of 0.1ms) and the hierarchical compensation strategy (coarse compensation with a 2ms response and fine compensation with a 0.1ms response) ensures that the system maintains a tracking error of <3% even under 500Hz high-frequency motion commands. The sliding window mechanism updates the model parameters every 5 minutes, ensuring that the thermal deformation compensation residual remains below 0.8μm during continuous machining with a spindle temperature rise of 30℃, improving adaptability by 3 times compared to traditional fixed-parameter models.

[0075] 3. The fault self-diagnosis module uses spectrum analysis (early warning if fundamental frequency ratio > 40%) and residual monitoring (alarm for three consecutive over-threshold errors) to achieve early identification of faults such as spindle dynamic balance failure. Actual production line testing shows that this function reduces unplanned downtime by 40%, and when combined with predictive maintenance strategies, it can extend the life of key components (such as linear motors) by 70%, significantly reducing overall operation and maintenance costs. Attached Figure Description

[0076] Figure 1 This is a schematic diagram of the overall system architecture of the present invention.

[0077] Figure 2 This is a schematic diagram of the multiphysics coupling modeling process of the present invention.

[0078] Figure 3 This is a schematic diagram of the composite compensation control logic of the present invention.

[0079] Figure 4 This is a schematic diagram of the dynamic parameter update sequence of the present invention.

[0080] Figure 5 This is a schematic diagram of the fault diagnosis status of the present invention.

[0081] Figures 1 to 5 Chinese characters: 1、;2、;3、;4、;5、;6、;7、;8、;9、;10、;11、;12、;13、;14、;15、;16、;17、;18、;19、;20、;21、;22、;23、;24、;25、;26、;27、;28、;29、;30、;31、;32、;33、;34、;35、;36、;37、;。 Detailed Implementation

[0082] The technical solutions of the present invention will be clearly and completely described below with reference to the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0083] like Figures 1 to 5 This paper presents a numerical control compensation method and numerical control system based on multi-physics field coupled digital twin.

[0084] I. Hardware Architecture and Core Components

[0085] 1. Multiphysics sensing unit

[0086] Vibration monitoring module

[0087] Sensor selection: PCB Piezotronics 352C33 triaxial accelerometer, measuring range ±50g, frequency range 0.5Hz-30kHz.

[0088] Deployment locations: front end of spindle (2), worktable (1), guide rail slider (2), for a total of 5 measuring points.

[0089] Signal processing:

[0090] The preamplifier gain is set to 10mV / g, and the signal-to-noise ratio is ≥80dB.

[0091] The anti-aliasing filter has a cutoff frequency of 25kHz and a uniform sampling rate of 50kHz.

[0092] Temperature monitoring module

[0093] Sensor configuration: 6-channel fiber Bragg grating temperature sensor (wavelength resolution 0.1 pm), equidistantly distributed along the main axis.

[0094] Data synchronization: The demodulator has a sampling rate of 1kHz and transmits temperature gradient data via RS485 bus.

[0095] Electromagnetic Interference Analysis Module

[0096] Current sensor: LEM HTFS2000 closed-loop Hall sensor, bandwidth DC-100kHz, accuracy ±0.5%.

[0097] Harmonic processing:

[0098] The current signal is sampled at 200kHz, and an FFT analysis is performed every second (0-10kHz).

[0099] Frequency band weighting: 0.8 for 1kHz, and the weight decreases by 30% for every additional 1kHz (e.g., 2kHz = 0.56, 10kHz = 0.05).

[0100] 2. Edge computing unit

[0101] Core processor: Xilinx Zynq UltraScale+ MPSoC (ZU19EG), dual-core ARM Cortex-A53 (1.5GHz) + FPGA programmable logic.

[0102] Real-time operating system: Wind River VxWorks 7, task scheduling jitter ≤10μs.

[0103] Multi-threaded task allocation:

[0104]

[0105] 3. Composite compensation enforcement agency

[0106] Coarse compensation layer: Linear motor LM-200A (stroke ±2mm, repeatability ±1μm, maximum acceleration 2g).

[0107] Fine compensation layer: Piezoelectric ceramic actuator PSt-150 / 5 (stroke ±50μm, resolution 5nm, step response time 0.1ms).

[0108] Mechanical structure:

[0109] Dual-axis series installation, marble base (thermal expansion coefficient 0.8μm / m·℃).

[0110] Laser calibration coaxiality error ≤ 0.5μm / 100mm, air-bearing guide rail friction coefficient < 0.001.

[0111] II. Software Control Logic and Core Algorithm

[0112] 1. Multi-field coupling modeling process

[0113] Data preprocessing

[0114] Timestamp alignment: The GPS clock synchronization module (SyncServerS600) ensures that the time deviation of each sensor is ≤10μs.

[0115] Data normalization: Vibration, temperature, and electromagnetic data are mapped to the [0,1] interval to eliminate dimensional differences.

[0116] Dynamic optimization of model parameters

[0117] Optimization objective: Minimize the sum of squared residuals ∑(Δactual - Δpredicted) 2 .

[0118] Constraints:

[0119] The coefficient of thermal expansion α ∈ [0.05, 0.15] μm / ℃·s

[0120] The mechanical response coefficient β∈[0.1,0.5]μm / (N·s⁻¹)

[0121] Electromagnetic susceptibility coefficient γ∈[0.01,0.1]μm / V2

[0122] Iteration termination condition: The rate of change of the residuals for three consecutive iterations is less than 1%.

[0123] 2. Hierarchical compensation control strategy

[0124] Error range and action rules:

[0125]

[0126]

[0127] Overshoot prevention mechanism:

[0128] When the linear motor speed is greater than 10 mm / s, acceleration feedforward compensation is enabled (feedforward gain 0.95).

[0129] When the piezoelectric ceramic displacement reaches 45μm, it triggers the linear motor to reverse and reset by 5μm.

[0130] 3. Fault self-diagnosis module

[0131] Residual analysis rules:

[0132] Short-term residual (<1 minute): Detection of abnormal sensor signals (such as disconnection, saturation).

[0133] Long-term residual (>10 minutes): Warning of wear or loosening of mechanical parts.

[0134] Spectrum diagnostic threshold:

[0135]

[0136] The following is a complete implementation plan for a CNC system based on multiphysics coupled digital twin technology, detailing everything from hardware architecture to control logic, including specific parameters and implementation details:

[0137] I. Hardware Architecture and Core Components

[0138] 1. Multiphysics sensing unit

[0139] Vibration monitoring module

[0140] Sensor selection: PCBPiezotronics 352C33 triaxial accelerometer with a range of ±50g and a frequency range of 0.5Hz-30kHz is adopted.

[0141] Deployment locations: front end of spindle (2), worktable (1), guide rail slider (2), for a total of 5 measuring points.

[0142] Signal processing:

[0143] The preamplifier gain is set to 10mV / g, and the signal-to-noise ratio is ≥80dB.

[0144] The anti-aliasing filter has a cutoff frequency of 25kHz and a uniform sampling rate of 50kHz.

[0145] Temperature monitoring module

[0146] Sensor configuration: 6-channel fiber Bragg grating temperature sensor (wavelength resolution 0.1 pm), equidistantly distributed along the main axis.

[0147] Data synchronization: The demodulator has a sampling rate of 1kHz and transmits temperature gradient data via RS485 bus.

[0148] Electromagnetic Interference Analysis Module

[0149] Current sensor: LEMHTFS2000 closed-loop Hall sensor, bandwidth DC-100kHz, accuracy ±0.5%.

[0150] Harmonic processing:

[0151] The current signal is sampled at 200kHz, and an FFT analysis is performed every second (0-10kHz).

[0152] Frequency band weighting: 0.8 for 1kHz, and the weight decreases by 30% for every additional 1kHz (e.g., 2kHz = 0.56, 10kHz = 0.05).

[0153] 2. Edge computing unit

[0154] Core processor: Xilinx Zynq UltraScale+ MPSoC (ZU19EG), dual-core ARM Cortex-A53 (1.5GHz) + FPGA programmable logic.

[0155] Real-time operating system: WindRiverVxWorks7, task scheduling jitter ≤10μs.

[0156] Multi-threaded task allocation:

[0157] Thread Name Execution Cycle Function Description

[0158] Vibration feature extraction: 0.1ms calculation of vibration RMS value and spectral peak value.

[0159] Temperature field reconstruction in 1ms: 3D temperature cloud map generated based on heat conduction equation

[0160] Electromagnetic energy calculation, 5ms band weighted sum and energy normalization

[0161] Coupled model update 60s least squares parameter optimization iteration

[0162] 3. Composite compensation enforcement agency

[0163] Coarse compensation layer: Linear motor LM-200A (stroke ±2mm, repeatability ±1μm, maximum acceleration 2g).

[0164] Fine compensation layer: Piezoelectric ceramic actuator PSt-150 / 5 (stroke ±50μm, resolution 5nm, step response time 0.1ms).

[0165] Mechanical structure:

[0166] Dual-axis series installation, marble base (thermal expansion coefficient 0.8μm / m·℃).

[0167] Laser calibration coaxiality error ≤ 0.5μm / 100mm, air-bearing guide rail friction coefficient < 0.001.

[0168] II. Software Control Logic and Core Algorithm

[0169] 1. Multi-field coupling modeling process

[0170] Data preprocessing

[0171] Timestamp alignment: The GPS clock synchronization module (SyncServerS600) ensures that the time deviation of each sensor is ≤10μs.

[0172] Data normalization: Vibration, temperature, and electromagnetic data are mapped to the [0,1] interval to eliminate dimensional differences.

[0173] Dynamic optimization of model parameters

[0174] Optimization objective: Minimize the sum of squared residuals ∑(Δactual - Δpredicted) 2 .

[0175] Constraints:

[0176] The coefficient of thermal expansion α ∈ [0.05, 0.15] μm / ℃·s

[0177] The mechanical response coefficient β∈[0.1,0.5]μm / (N·s⁻¹)

[0178] Electromagnetic susceptibility coefficient γ∈[0.01,0.1]μm / V2

[0179] Iteration termination condition: The rate of change of the residuals for three consecutive iterations is less than 1%.

[0180] 2. Hierarchical compensation control strategy

[0181] Error range and action rules:

[0182] Absolute error compensation action

[0183] ≥1μm linear motor + piezoelectric ceramic synergistic compensation

[0184] Only piezoelectric ceramic fine compensation is activated in the 0.1μm to 1μm range.

[0185] Compensation is triggered when the cumulative error of <0.1μm reaches 5μm.

[0186] Overshoot prevention mechanism:

[0187] When the linear motor speed is greater than 10 mm / s, acceleration feedforward compensation is enabled (feedforward gain 0.95).

[0188] When the piezoelectric ceramic displacement reaches 45μm, it triggers the linear motor to reverse and reset by 5μm.

[0189] 3. Fault self-diagnosis module

[0190] Residual analysis rules:

[0191] Short-term residual (<1 minute): Detection of abnormal sensor signals (such as disconnection, saturation).

[0192] Long-term residual (>10 minutes): Warning of wear or loosening of mechanical parts.

[0193] Spectrum diagnostic threshold:

[0194] Fault type spectrum characteristic determination conditions

[0195] An alarm will be triggered if the energy percentage of the spindle dynamic balance failure fundamental frequency (1× speed) is greater than 40% for 5 minutes.

[0196] Insufficient guide rail preload leads to a sudden increase in vibration energy exceeding 30%, causing a speed reduction to 50% during operation.

[0197] Bearing pitting high-frequency harmonic clusters (>5kHz) energy rise, shutdown and maintenance recommended. III. Implementation results and test data

[0198] 1. Verification of Precision Improvement (Machining of Aerospace Titanium Alloy Blades)

[0199] Test conditions:

[0200] Material: Ti-6Al-4V, cutting speed 120m / min, feed rate 0.08mm / tooth.

[0201] Comparison group: Traditional CNC systems without multi-field coupling compensation enabled.

[0202] Result comparison:

[0203]

[0204] 2. Dynamic Response Testing

[0205] Step response test (command displacement 1μm):

[0206] Overshoot: <2%

[0207] Settling time: 1.8ms (piezoelectric ceramic layer)

[0208] Sine wave tracking test (frequency 500Hz, amplitude 5μm):

[0209] Phase lag: <5°

[0210] Amplitude error: <3%

[0211] IV. Key Points for Industrialization Implementation

[0212] Sensor calibration process:

[0213] Vibration sensor: Amplitude-frequency characteristics are calibrated using a standard vibration table (frequency 1-10kHz, acceleration 1g).

[0214] Temperature sensor: Compare with a platinum resistance standard thermometer (accuracy ±0.01℃) in a constant temperature oil bath.

[0215] System debugging steps:

[0216] No-load calibration phase: Run for 4 hours to collect reference parameters and establish an initial coupling model.

[0217] Trial cutting verification stage: Machining aluminum alloy test pieces (cutting parameters are 30% of those used in formal machining) and optimizing compensation thresholds.

[0218] During the formal production phase: a full-parameter model is enabled, and the system status is automatically backed up every 8 hours.

[0219] Maintenance strategy:

[0220] Preventive maintenance: Check the piezoelectric ceramic preload every 500 hours (standard value 50N±5N).

[0221] Predictive maintenance: Replace spindle bearings in advance based on bearing pitting warnings from the fault diagnosis module.

[0222] V. Summary of Technical Advantages

[0223] Breakthrough in precision: By using multi-field coupling modeling, thermal deformation error is suppressed by more than 90%, achieving sub-micron level machining precision.

[0224] Real-time performance guarantee: The edge computing unit achieves vibration processing at the 0.1ms level, meeting the requirements of high-speed and high-precision machining.

[0225] Reliability design: The fault self-diagnosis module reduces unplanned downtime by more than 40%.

[0226] Energy efficiency optimization: Dynamic power allocation strategy reduces energy consumption during ineffective idle travel by 25%.

[0227] The solution has completed laboratory verification and pilot production testing, and can be widely applied in high value-added fields such as precision parts and semiconductor packaging molds.

[0228] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A numerical control compensation method based on multi-physics coupled digital twin, characterized in that, Includes the following steps: S1: Real-time acquisition of multi-source data: Mechanical vibration signals are acquired by a three-axis vibration sensor deployed on the machine tool body at a sampling frequency of not less than 50kHz. A temperature sensor array is used to monitor the spindle temperature rise, with a temperature measurement resolution of 0.1 degrees Celsius. The motor drive current signal is acquired by a current sensor, and harmonic energy analysis is performed on the signal in the 0 to 10 kHz frequency band. S2: Multiphysics coupling modeling: A three-field coupled model incorporating mechanical vibration, thermal deformation, and electromagnetic interference is established, wherein: The thermal deformation component is positively correlated with the temperature integral value and the temperature rise rate. The mechanical dynamic response component is proportional to the rate of change of cutting force; The correlation between the electromagnetic interference component and the energy weighted sum of each frequency band of current harmonics; The coefficient of thermal expansion, the coefficient of mechanical response, and the electromagnetic susceptibility coefficient are set as the core parameters of the model. S3: Real-time error compensation: Coarse compensation stage: The linear motor completes the position correction of ±2 mm stroke within 2 milliseconds, and the positioning accuracy reaches ±1 micrometer; Fine compensation stage: Piezoelectric ceramic actuators are used to achieve micro-displacement adjustment with a resolution of 5 nanometers within 0.1 milliseconds; Graded compensation is performed based on the magnitude of the overall error: coarse compensation is initiated when the absolute error is ≥1 micrometer, and fine compensation is initiated only when the error is between 0.1 micrometer and 1 micrometer. S4: Dynamic parameter update: The coefficients of the coupled model are updated every 5 minutes based on the least squares optimization algorithm. The optimization objective is to minimize the sum of squared residuals between the actual measurement error and the model prediction. A sliding window mechanism is used to retain the most recent 300 data points for parameter iteration.

2. The numerical control compensation method based on multiphysics coupled digital twins according to claim 1, characterized in that: The current harmonic energy analysis includes: The 0-10kHz frequency band is divided into 10 sub-bands with a bandwidth of 1kHz; An exponentially decreasing weighting is applied to the harmonic energy of each sub-band, with the weight of the high-frequency band being lower than that of the low-frequency band. The total electromagnetic interference energy is calculated by multiplying the square of the current amplitude in each frequency band by its corresponding weight.

3. The numerical control compensation method based on multiphysics coupled digital twins according to claim 1, characterized in that: The multi-source data acquisition employs time synchronization technology, including: Configure each sensor with a clock synchronization module with microsecond-level precision; Time-domain interpolation is performed on the vibration signal to match the temperature sampling time reference; Create a circular data buffer to store the raw waveform data of the most recent 2 seconds.

4. The numerical control compensation method based on multiphysics coupled digital twins according to claim 1, characterized in that: The composite compensation mechanism meets the following control requirements: The linear motor and piezoelectric ceramic are mounted in a coaxial series structure. The coaxiality error of the dual-axis motion direction is ensured to be ≤0.5 micrometers / 100 millimeters through laser calibration; Set up anti-motion interference logic: when the piezoelectric ceramic reaches the travel limit, the linear motor position is reset.

5. A numerical control compensation method based on multiphysics coupled digital twins according to claim 1, characterized in that: Also includes: The fault self-diagnosis module is implemented as follows: A system alarm is triggered when the sum of squared residuals after three consecutive parameter optimizations exceeds 10 square micrometers. Compare the deviation rate between the predicted compensation amount and the actual compensation amount. If the deviation rate is greater than 15% for 10 consecutive minutes, the sensor is considered abnormal. Spindle faults are identified through spectrum analysis: a warning signal is output when the fundamental frequency vibration energy accounts for more than 40%.

6. A numerical control system based on multiphysics coupled digital twin, characterized in that, include: Multiphysics sensing unit: includes at least 6-channel temperature sensing, 3-axis vibration sensing, and 3-phase current sensing modules; Edge computing unit: Equipped with a programmable system-on-a-chip (SoC) and running a real-time operating system; Composite compensation actuator: a two-stage motion system consisting of a linear motor and a piezoelectric ceramic actuator; Human-computer interaction interface: Real-time display of the trend of coupling coefficient change and historical compensation statistics charts.

7. A numerical control system based on multiphysics coupled digital twins according to claim 6, characterized in that: The edge computing unit is configured with a multi-task processing architecture, including: High-frequency vibration signal processing thread (execution cycle 0.1 milliseconds); Temperature field modeling thread (execution cycle 1 millisecond); Electromagnetic interference analysis thread (execution cycle 5 milliseconds); Each thread exchanges data through shared memory, with a memory access latency of ≤50 nanoseconds.

8. A numerical control system based on multiphysics coupled digital twins according to claim 6, characterized in that: The composite compensation actuator adopts a dual closed-loop control strategy: The outer loop position control uses a proportional-integral-derivative algorithm with a control bandwidth of ≥500Hz; The inner loop force control is based on a variable stiffness-resistance model, with stiffness adjustment range of 1-100 N / μm; An acceleration feedforward mechanism is set up to be automatically enabled when the command position change rate is greater than 1 mm / s.

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