Cutting precision optimization method and system for four-axis linkage lathe

Abstract

The invention relates to the technical field of numerical control machining, and particularly discloses a cutting precision optimization method and system for a four-axis linkage lathe, and the method comprises the steps: constructing a viscosity-temperature distribution field matrix, extracting a gradient vector, judging the stability of a cutting fluid, judging a heat flow coupling effect if the viscosity-temperature distribution field matrix is not stable, and determining a coupling monitoring period; establishing a transfer function of viscosity and cutting force, and constructing a cutting force instability point set; mapping the instability point set to a two-dimensional manifold, calculating a boundary point manifold curvature, and determining that manifold wrinkles exist; and constructing a mapping model of cutting parameters, and outputting parameter offset to realize precision closed-loop control. The system comprises a coupling analysis module, a period extraction module, an instability extraction module, a closed loop verification module and a precision adjustment module, the problem of cutting force instability caused by viscosity-temperature coupling is relieved through physical field data coupling analysis and dynamic compensation, and the method is suitable for complex curved surface machining.

Description

Technical Field

[0001] The present invention relates to the technical field of numerical control machining, and in particular to a cutting precision optimization method and system for a four-axis linkage lathe. Background Art

[0002] In the field of CNC machining, four-axis linkage lathes have become the core equipment for processing complex curved parts due to their multi-axis collaborative capabilities, but their cutting accuracy is significantly affected by the viscosity-temperature coupling effect of the cutting fluid.

[0003] Existing technologies use a fixed cycle to monitor the cutting fluid state, which makes it difficult to cope with real-time fluctuations in the viscosity-temperature coupling strength. In the strong coupling interval, instability points may be missed due to the long cycle, while in the steady-state interval, computing resources may be wasted due to excessive monitoring.

[0004] Since the cutting force instability caused by viscosity-temperature coupling is easily mixed with interference signals such as machine tool vibration and tool wear, existing technologies are difficult to separate the real instability characteristics, cannot eliminate pseudo-instability points, and construct an instability point set with physical meaning, resulting in a high misjudgment rate of instability positions. Summary of the Invention

[0005] The purpose of the present invention is to provide a cutting accuracy optimization method and system for a four-axis linkage lathe to solve the above background problems.

[0006] The purpose of the present invention can be achieved through the following technical solutions: A method for optimizing the cutting accuracy of a four-axis linkage lathe comprises the following steps: Extract the time series data stream of cutting fluid viscosity and temperature, perform coupled analysis of viscosity and temperature based on the time series data stream, and extract the viscosity-temperature gradient vector of the micro-domain grid; Based on the viscosity-temperature gradient vector, gradient fluctuation analysis and spatial consistency analysis are performed to determine the stability of the cutting fluid. If it is unstable, the viscosity-temperature trajectory is drawn. By determining whether the trajectory forms a closed loop, if so, the coupling strength value is obtained by performing back-expansion and symmetry analysis, and the coupling monitoring period is determined. The torque component and instantaneous phase angle are intercepted during the coupled monitoring period, and the transfer function of viscosity and cutting force is established. The critical candidate instability points of the cutting force during the coupled monitoring period are identified. The critical candidate instability points are verified by the second-order force signal criterion and the viscosity-temperature gradient, and the cutting force instability point set is constructed. The cutting force mutation points in the boundary area of ​​the coupling monitoring cycle are collected, and the effectiveness of the coupling monitoring cycle is verified to determine whether the coupling monitoring cycle cuts the topological closed loop of viscosity-temperature coupling. If so, the coupling monitoring cycle is adjusted.

[0007] As a further technical solution of the present invention: the method of extracting the viscosity-temperature gradient vector of the micro-domain grid is: During the monitoring period, the time series data stream of micro-domain viscosity and temperature in the cutting micro-domain is collected; The cutting micro-domain is divided into different micro-domain grids, and the time-series data streams within the micro-domain grids are aligned using a spatiotemporal registration algorithm to obtain the aligned micro-domain viscosity, temperature, and sampling time. Based on the microdomain viscosity, temperature, and sampling time, a viscosity-temperature distribution field matrix including different microdomain grids is constructed; The viscosity-temperature gradient vector of each micro-domain grid containing viscosity and temperature is extracted based on the viscosity-temperature distribution field matrix.

[0008] As a further technical solution of the present invention: the coupling monitoring period is determined as follows: If there is a thermal flow coupling effect, obtain the maximum longitudinal temperature span and the minimum longitudinal temperature span of the closed loop; Calculate the ratio of the deviation between the maximum longitudinal temperature span and the minimum longitudinal temperature span as the loop expansion coefficient; Obtain the slope of the right branch and the slope of the left branch of the closed loop, perform ratio processing on the slope of the right branch and the slope of the left branch to obtain the asymmetry; The asymmetry and the loop expansion coefficient are summed to obtain the coupling strength value; Divide different level intervals based on the coupling strength value and extract the strong coupling interval; The monitoring period of the strong coupling interval is obtained as the coupling monitoring period.

[0009] As a further technical solution of the present invention: the determination method of the presence of the thermal flow coupling effect is: Based on the viscosity-temperature gradient vector of each micro-domain grid, gradient fluctuation analysis and spatial consistency analysis are performed to obtain the spatial consistency coefficient and gradient fluctuation coefficient; Based on the spatial consistency coefficient and gradient fluctuation coefficient as independent criteria for judging the stability of the cutting fluid, the stability of the cutting fluid is judged; If the cutting fluid is unstable, the viscosity-temperature trajectory is drawn with the micro-domain viscosity as the horizontal axis and the temperature as the vertical axis; Based on the viscosity-temperature trajectory, it is determined whether the trajectory forms a clockwise closed loop. If so, it is determined that there is a thermal-flux coupling effect.

[0010] As a further technical solution of the present invention: the method for judging whether the cutting fluid is unstable is: Based on the viscosity-temperature gradient vector of each micro-domain grid, gradient fluctuation analysis and spatial consistency analysis are performed to obtain the spatial consistency coefficient and gradient fluctuation coefficient; Based on the spatial consistency coefficient and gradient fluctuation coefficient as independent criteria for judging the stability of cutting fluid; A comparative analysis was conducted based on the independent criteria of cutting fluid stability to obtain the result of cutting fluid instability.

[0011] As a further technical solution of the present invention: the method of constructing the cutting force instability point set is: Obtain the critical candidate instability point of the cutting force and the viscosity-temperature gradient vector, extract the temperature gradient and viscosity drop rate, and re-screen the critical candidate instability point based on the temperature and viscosity drop rate; The complete coupling monitoring cycle is traversed to obtain the critical candidate instability points screened again within the complete coupling monitoring cycle, and a cutting force instability point set containing the instantaneous phase angle and amplitude of each critical candidate instability point is constructed.

[0012] As a further technical solution of the present invention, the method for obtaining the critical candidate instability point of the cutting force is: The torque component of the main shaft is collected during the coupling monitoring period; The fundamental frequency component of the cutting force is calculated based on the torque component, and the instantaneous phase angle of the vibration signal is extracted by performing Hilbert-Huang transform on the fundamental frequency component. The transfer function of viscosity and cutting force is established based on the instantaneous phase angle, and the critical candidate instability points of the cutting force in the coupled monitoring cycle are identified.

[0013] As a further technical solution of the present invention, the method for identifying the critical candidate instability point of the cutting force in the coupled monitoring cycle is: Establish the sweep range of angular frequency and calculate the amplitude of the transfer function of viscosity and cutting force; Based on the amplitude within the frequency sweep range, the minimum amplitude point is solved by the Newton iteration method and is used as the critical candidate instability point.

[0014] As a further technical solution of the present invention, the method for judging whether the coupling monitoring period cuts the topological closed loop of the viscosity-temperature coupling is: If there are manifold wrinkles, obtain the number of phase ring handles of the boundary instability points within the coupling monitoring period and the average number of phase ring handles of all effective instability points within the coupling monitoring period in the two-dimensional manifold; The absolute deviation between the number of phase ring handles at the boundary instability point and the average number of phase ring handles of all effective instability points within the coupling monitoring period is calculated to obtain the stretching judgment value; Based on the pull-up judgment value, it is determined whether the coupling monitoring cycle cuts the topological closed loop of the viscosity-temperature coupling.

[0015] As a further technical solution of the present invention: the determination method of the presence of the manifold fold is: A two-dimensional manifold is constructed to map the cutting force instability point set of the coupled monitoring period to the two-dimensional manifold; Obtain the boundary point neighborhood of the two-dimensional manifold and the manifold of the effective instability point, and calculate the manifold curvature of the boundary instability point; The average curvature of all valid instability points in the two-dimensional manifold is obtained. If the manifold curvature of the boundary instability point is higher than or equal to the preset boundary curvature threshold, it is determined that the boundary has manifold wrinkles.

[0016] As a further technical solution of the present invention: extracting the cutting parameters of the effective instability point within the coupling monitoring period, establishing a mapping relationship between the viscosity-temperature coupling strength and the cutting parameters, and optimizing the cutting accuracy based on the mapping relationship.

[0017] As a further technical solution of the present invention: the mapping relationship is used to optimize the cutting accuracy in the following manner: Establish a mapping relationship model between viscosity-temperature coupling strength and cutting parameters, and output the cutting parameter offset; The cutting accuracy of a quadrilateral lathe is controlled based on the offset of the cutting parameters.

[0018] A cutting precision optimization system for a four-axis linkage lathe includes the following modules: Coupling analysis module: used to extract the time series data stream of cutting fluid viscosity and temperature, perform coupling analysis on viscosity and temperature based on the time series data stream, and extract the viscosity-temperature gradient vector of the micro-domain grid; Cycle Extraction Module: This module performs gradient fluctuation analysis and spatial consistency analysis based on the viscosity-temperature gradient vector to determine the stability of the cutting fluid. If the viscosity-temperature trajectory is unstable, it plots the viscosity-temperature trajectory and determines whether the trajectory forms a closed loop. If so, it performs back-expansion and symmetry analysis to obtain the coupling strength value and determine the coupling monitoring cycle. Instability extraction module: This module intercepts the torque component and instantaneous phase angle during the coupled monitoring period, establishes a transfer function between viscosity and cutting force, identifies critical candidate instability points of the cutting force during the coupled monitoring period, verifies these critical candidate instability points using the second-order force signal criterion and viscosity-temperature gradient, and constructs a set of cutting force instability points. Closed-loop verification module: This module is used to collect the cutting force mutation points in the boundary area of ​​the coupling monitoring cycle and verify the validity of the coupling monitoring cycle to determine whether the coupling monitoring cycle cuts through the topological closed loop of the viscosity-temperature coupling. If so, the coupling monitoring cycle is adjusted. Precision adjustment module: used to extract the cutting parameters of the effective instability point within the coupling monitoring period, establish the mapping relationship between the viscosity-temperature coupling strength and the cutting parameters, and optimize the cutting accuracy based on the mapping relationship.

[0019] Beneficial effects of the present invention: The viscosity-temperature time series data of the cutting micro-domain grid are collected synchronously, and the multi-sensor coordinate system is aligned with the machine tool coordinate system using the spatiotemporal registration algorithm. The constructed viscosity-temperature distribution field matrix reflects the viscosity-temperature gradient distribution in three-dimensional space, which is conducive to capturing the viscosity-temperature coupling characteristics at the micro-domain scale and provides a high-density, high-spatiotemporal resolution data basis for subsequent cutting fluid stability judgment and thermal flow coupling analysis.

[0020] A dual-criteria model based on the gradient fluctuation coefficient and the spatial consistency coefficient identifies the steady-state properties of the cutting fluid and reduces cutting force anomalies caused by viscosity-temperature fluctuations. The closed loop of the viscosity-temperature trajectory determines the thermal coupling effect, and the coupling strength is quantified using the loop expansion coefficient and asymmetry, enabling dynamic calibration of the coupling monitoring cycle. By adaptively matching the real-time strength of the viscosity-temperature coupling, compared to traditional fixed-cycle monitoring, this reduces computational redundancy caused by over-monitoring and minimizes the omission of critical instability points due to long cycles, thereby improving monitoring efficiency and accuracy.

[0021] By decoupling the spindle current signal to extract the torque component and combining it with the Hilbert-Huang transform to obtain the instantaneous phase angle, a viscosity-temperature-cutting force transfer function was established to represent the dynamic modulation of the viscosity-temperature coupling on the cutting force. The Newton iteration method was used to solve for the amplitude minimum point. Combined with the back force second-order derivative criterion and viscosity-temperature gradient verification, pseudo-instability points such as machine tool vibration were effectively eliminated. The resulting cutting force instability point set was constructed, effectively separating the true instability characteristics caused by viscosity-temperature coupling from multi-source signals, providing a clear control target for subsequent precision compensation.

[0022] The set of unstable points is mapped onto a two-dimensional manifold, and the topological integrity of the coupled monitoring cycle is determined by the deviation between the manifold curvature and the number of phase ring handles at the boundary points. When wrinkles are detected on the manifold, the cycle length is dynamically adjusted based on the wrinkle strength, achieving a topologically closed monitoring loop covering the viscosity-temperature coupling. This approach reduces the hysteresis of traditional fixed-cycle monitoring. By quantifying the cycle validity through manifold geometric features, self-calibration of the monitoring cycle is achieved, reducing missed detection of unstable points due to cycle mismatch and improving the spatiotemporal consistency of multi-physics coupled analysis.

[0023] By extracting the spindle speed and cutting depth parameters at the effective instability point, a mapping model between viscosity-temperature coupling strength and cutting parameters is constructed. The output parameter offset can directly drive the CNC system for real-time compensation. The closed-loop control mechanism transforms the implicit impact of viscosity-temperature coupling into explicit parameter adjustment instructions, achieving full automation of the monitoring, analysis, and compensation process. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] The present invention will be further described below with reference to the accompanying drawings.

[0025] Figure 1 This is a flow chart of a method for optimizing cutting accuracy of a four-axis linkage lathe according to the present invention; Figure 2 It is a flow chart for determining whether there are manifold wrinkles in the present invention; Figure 3 It is a module diagram of a cutting precision optimization system for a four-axis linkage lathe of the present invention. DETAILED DESCRIPTION

[0026] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making any creative efforts shall fall within the scope of protection of the present invention. Example 1

[0027] See also Figure 1 As shown, the present invention is a method for optimizing the cutting accuracy of a four-axis linkage lathe, comprising the following steps: S1. Collect cutting data of the cutting micro-domain grid of the four-axis linkage lathe, extract the time series data stream of the cutting fluid viscosity and temperature, perform coupled analysis of viscosity and temperature based on the time series data stream, and extract the viscosity-temperature gradient vector of the micro-domain grid; Among them, the method of extracting cutting fluid viscosity and temperature data stream is: Preferably, during the monitoring period, a piezoresistive microviscosity sensor array and a fiber Bragg grating temperature sensor are embedded in the spindle to synchronously collect the time series data stream of the micro-domain viscosity and temperature of the cutting micro-domain belonging to the tool cutting interface; The cutting micro-domain is divided into different micro-domain grids. According to the time series data flow in the micro-domain grid, the coordinate system of the piezoresistive micro-viscosity sensor array and the fiber Bragg grating temperature sensor are aligned with the coordinate system of the four-axis linkage machine tool through the time-space registration algorithm to obtain the aligned micro-domain viscosity. and temperature and sampling time t; in, are the coordinate values ​​of the x-axis, y-axis, and z-axis respectively; It will be understood by those skilled in the art that, within the monitoring period, the cutting micro-domain is first divided into different micro-domain grids according to a regular three-dimensional structure to achieve high-density sampling of the local physical field; then, the time series data stream within each micro-domain grid is subjected to spatiotemporal registration and alignment processing, and the installation positions of the piezoresistive micro-viscosity sensor array and the fiber Bragg grating temperature sensor on the tool handle are calibrated to construct a rotation and translation matrix, and the micro-domain viscosity and temperature data in the sensor coordinate system are converted into coordinates in the machine tool coordinate system. At the same time, the sensor sampling timestamps are collected, and the clock deviations of different sensors are corrected using linear interpolation or clock synchronization algorithms, thereby achieving spatial and temporal alignment of the time series data stream within the micro-domain grid with the machine tool coordinate system, and obtaining the aligned micro-domain viscosity, temperature and sampling time; Based on micro-domain viscosity and temperature , and the sampling time to construct the viscosity-temperature distribution field matrix including different micro-domain grids ; in, , is the partial differential symbol; Extract the viscosity-temperature gradient vector of each micro-domain grid containing viscosity and temperature based on the viscosity-temperature distribution field matrix; It can be understood that the purpose of constructing the viscosity-temperature gradient vector is: Function 1: Based on the viscosity-temperature gradient vector of each micro-domain grid, the gradient fluctuation analysis and spatial consistency analysis of the viscosity-temperature gradient vector can be performed, which can be used as an independent criterion to judge the stability of the cutting fluid; Function 2: When the cutting fluid is unstable, the viscosity-temperature trajectory is drawn with the micro-domain viscosity as the horizontal axis and the temperature as the vertical axis. The presence of a thermal-fluid coupling effect is determined by judging whether the trajectory forms a clockwise closed loop. If so, the loop is expanded and symmetric analyzed, and the coupling strength value is summed up. The strong coupling interval is divided to determine the coupling monitoring period, providing a time benchmark for the subsequent cutting force instability point analysis.

[0028] S2. Based on the viscosity-temperature gradient vector of each micro-domain grid, gradient fluctuation analysis and spatial consistency analysis are performed to determine the stability of the cutting fluid. If it is unstable, the viscosity-temperature trajectory is plotted. By determining whether the trajectory forms a closed loop, if so, the coupling strength value is obtained by performing back-expansion and symmetry analysis, and the coupling monitoring period is determined; Among them, the method of performing gradient fluctuation analysis and spatial consistency analysis is: Preferably, based on the viscosity-temperature gradient vector of each micro-domain grid, gradient fluctuation analysis and spatial consistency analysis are performed to determine the stability of the cutting fluid; Judging whether the cutting fluid of a four-axis linkage lathe is stable based on the viscosity-temperature steady-state coefficient; Among them, the method of performing gradient fluctuation analysis and spatial consistency analysis is: Preferably, by the formula: Get the gradient fluctuation coefficient Cv; in, 、 are the standard deviation and mean of the viscosity-temperature gradient vector norm of all micro-domain grids; By formula: I=1- Get the spatial consistency coefficient I; in, is the viscosity-temperature gradient vector norm of micro-domain grid i; i is the number of each micro-domain grid; Based on the spatial consistency coefficient and gradient fluctuation coefficient as independent criteria for judging the stability of the cutting fluid, the stability of the cutting fluid is judged; It should be explained that the gradient fluctuation coefficient is compared with the preset fluctuation threshold, and the spatial consistency coefficient is compared with the preset consistency threshold. If the gradient fluctuation coefficient does not exceed the fluctuation threshold and the spatial consistency coefficient is not lower than the consistency threshold, the cutting fluid stability is determined to meet the standard, otherwise it is determined to be unstable; If it is unstable, the micro-domain viscosity Draw the viscosity-temperature trajectory (μ, T) with θ as the horizontal axis and temperature T as the vertical axis; Based on the viscosity-temperature trajectory, determine whether the trajectory forms a clockwise closed loop. If so, it is determined that there is a thermal-flux coupling effect. It is understood by those skilled in the art that during the cutting process, there is a positive feedback loop between temperature and micro-domain viscosity, where temperature rises and micro-domain viscosity decreases, and the decrease in micro-domain viscosity leads to increased cutting heat generation and further increase in temperature, driving both to change periodically and dynamically. When a phase plane of the viscosity-temperature trajectory is constructed with micro-domain viscosity as the horizontal axis and temperature as the vertical axis, the cycle forms a closed trajectory. Based on dynamic characteristics, the temperature change rate is negatively correlated with viscosity. The viscosity change rate causes the trajectory slope to be negative. Combined with the phase difference between the heat conduction delay and the viscosity response lag, the trajectory rotates clockwise. The self-excited oscillation caused by thermal flow coupling is accompanied by a stable clockwise closed loop. The trajectory of uncoupled disturbances is irregular or decays rapidly, making it difficult to form a closed loop. Therefore, the thermal flow coupling effect is determined by geometric characteristics. If there is a thermal flow coupling effect, obtain the maximum longitudinal temperature span and the minimum longitudinal temperature span of the closed loop; Calculate the ratio of the deviation between the maximum longitudinal temperature span and the minimum longitudinal temperature span as the loop expansion coefficient; Obtain the slope of the right branch and the slope of the left branch of the closed loop, perform ratio processing on the slope of the right branch and the slope of the left branch to obtain the asymmetry; The asymmetry and the loop expansion coefficient are summed to obtain the coupling strength value; It can be understood that the coupling strength value comprehensively characterizes the dynamic characteristics of viscosity-temperature coupling through the loop expansion coefficient and asymmetry of the closed loop. The loop expansion coefficient is calculated by the deviation between the maximum and minimum longitudinal temperature spans of the closed loop, reflecting the fluctuation amplitude and spatial distribution unevenness of the temperature field during the viscosity-temperature coupling process. The asymmetry is obtained by the ratio of the slopes of the left and right branches of the loop, reflecting the difference in the dynamic response of the viscosity-temperature trajectory during the heating and cooling stages. The higher the coupling strength value obtained by summing the two, the more intense the viscosity-temperature coupling effect, the more unstable the cutting fluid state, and the stronger the modulation effect on the cutting force. Therefore, it is necessary to divide the strong coupling interval into strong coupling intervals to dynamically adjust the monitoring cycle and capture the instability point of the cutting force caused by viscosity-temperature coupling. Divide different level intervals based on the coupling strength value and extract the strong coupling interval; For example, calculations show that the maximum longitudinal temperature span of a closed loop under a certain cutting state is 50°C and the minimum longitudinal temperature span is 30°C, so the loop expansion coefficient is approximately 0.67. If the slope of the right branch of the closed loop is 2 and the slope of the left branch is 1, then the asymmetry is 2 / 1=2, and the sum of the two gives a coupling strength value of 2.67. The coupling strength value is divided into a level interval: [0,1] is a weak coupling interval, (1,2] is a medium coupling interval, (2,3) is a strong coupling interval, and 3 and above is an extremely strong coupling interval. Since 2.67 is within the strong coupling interval, the monitoring period corresponding to the strong coupling interval (e.g., 10-15 seconds) is extracted as the coupling monitoring period to specifically capture the cutting force instability point under the strong coupling state; The monitoring period of the strong coupling interval is obtained as the coupling monitoring period. Example 2

[0029] like Figure 1 As shown, a method for optimizing the cutting accuracy of a four-axis linkage lathe further includes the following steps: S3. Intercept the torque component and instantaneous phase angle during the coupling monitoring period, establish the transfer function of viscosity and cutting force based on the instantaneous phase angle, identify the critical candidate instability points of the cutting force during the coupling monitoring period, verify the critical candidate instability points with the second-order force signal criterion and viscosity-temperature gradient, and construct the cutting force instability point set; The method for identifying the candidate instability points within the coupling monitoring period is as follows: Preferably, the three-phase current signal of the main shaft is collected during the coupling monitoring period, and the three-phase current signal is subjected to Clarke transform decoupling to extract the torque component; The fundamental frequency component of the cutting force is calculated based on the torque component, and the instantaneous phase angle of the vibration signal is extracted by performing Hilbert-Huang transform on the fundamental frequency component. Those skilled in the art will understand that after collecting the three-phase current signal of the spindle, it is decoupled into the α-β two-phase components through Clarke transformation, the zero-sequence component is eliminated, and the pure torque component is decoupled in real time by combining the spindle speed and the motor torque formula; the torque component is subjected to empirical mode decomposition to screen out the intrinsic mode function containing the fundamental frequency, and the analytical signal of the Hilbert transform is performed on it. Its phase angle is the instantaneous phase of the vibration, and the phase fluctuation of the cutting force modulation is separated by the phase difference. The phase mutation under the viscosity-temperature coupling is identified to obtain the instantaneous phase angle; The transfer function of viscosity and cutting force is established based on the instantaneous phase angle to identify the critical candidate instability point of the cutting force in the coupled monitoring cycle; Among them, the transfer function of viscosity and cutting force is established as follows: Preferably, by the equation: Construct the transfer function H(s) of viscosity and cutting force; Where s=j*ω, j is the imaginary unit, ω is the angular frequency; is the fundamental frequency component of the cutting force, Δμ is the viscosity change rate, μ0 is the viscosity reference value, and s is the complex frequency component, which is used to map the dynamic relationship between viscosity and temperature in the time domain and the cutting force to the frequency domain. The cutting force is the vibration signal at the frequency The phase angle at Used to reflect the cutting force energy and system dynamic phase, Used to reflect the dynamic characteristics of viscosity changes; Establishing the sweep range of angular frequency , through the formula: Calculate the amplitude of the frequency sweep coverage ; Where Re and Im represent the real and imaginary parts of the transfer function, respectively. are the maximum and minimum values ​​of the angular frequency in the sweep range; Based on the amplitude within the frequency sweep range, the minimum amplitude point is solved by the Newton iteration method and used as the critical candidate instability point; It can be understood that the Newton iteration method is expressed by the formula: And the termination condition: , solve the minimum point of the amplitude within the sweep frequency range, k is an integer mark of the number of iteration steps; in, is the preset iteration termination threshold; When the angular frequency deviation of adjacent iterations meets the termination condition, it is determined is the minimum point of amplitude; Based on the critical candidate instability point of the cutting force, the force signal second-order criterion and viscosity-temperature gradient verification are performed to extract the effective instability point. Preferably, the force signal second-order criterion and viscosity-temperature gradient verification are performed as follows: If the cutting force has a critical candidate instability point, the back force at the moment corresponding to the mutation point is immediately extracted and the second-order derivative is calculated. If the second-order derivative of the back force is greater than 500N / ms² and the sign changes from negative to positive, the critical candidate instability point is retained, which is conducive to eliminating pseudo mutations such as machine tool vibration. At the same time, the viscosity-temperature gradient vector is obtained, the temperature gradient and viscosity drop rate are extracted, and the critical candidate instability points are screened again based on the temperature and viscosity drop rate; Traverse the complete coupling monitoring cycle, obtain the critical candidate instability points screened again within the complete coupling monitoring cycle, and construct a cutting force instability point set containing the instantaneous phase angle and amplitude of each critical candidate instability point; It can be understood that the purpose of constructing the cutting force instability point set is: Function 1: Provides real-time monitoring of critical features for the machining process. By comparing the cutting force and vibration signals collected by the sensor, it can promptly detect situations where the frequency or amplitude is close to the instability point, thereby providing early warning and adjusting parameters, and warning of problems such as chatter and tool damage. Function 2: Based on the distribution and characteristic differences of instability points, reverse diagnosis of the instability root cause is performed. If the instability points are concentrated in the strong viscosity-temperature coupling range, it can be determined that the problem is the cutting fluid; if the instability points drift over time, it may be related to tool wear or improper parameter settings, thus locating the fault. Function 3: Provide a basis for cutting parameter optimization and cutting fluid formulation improvement, which is conducive to reducing the possibility of cutting parameters falling into the unstable parameter range, quantitatively evaluating the formulation effect, and at the same time correcting the theoretical model through actual data to form a closed loop of process optimization and mechanism analysis, thereby improving processing accuracy.

[0030] S4. Collect the cutting force mutation points in the boundary area of ​​the coupling monitoring period, verify the validity of the coupling monitoring period, and determine whether the coupling monitoring period cuts the topological closed loop of the viscosity-temperature coupling. If so, adjust the coupling monitoring period. Among them, the method of verifying the effectiveness of the coupling monitoring cycle is: A two-dimensional manifold is constructed to map the cutting force instability point set of the coupled monitoring period to the two-dimensional manifold; Obtain the boundary point neighborhood of the two-dimensional manifold and the manifold of the effective instability point, and calculate the manifold curvature of the boundary instability point; Those skilled in the art will understand that, during the coupling monitoring cycle, the set of cutting force instability points is first mapped to a two-dimensional manifold space using a dimensionality reduction algorithm (such as principal component analysis (PCA)) to maintain the topological structure of the high-dimensional instability features in the two-dimensional plane unchanged. Next, the boundary points of the two-dimensional manifold (such as convex hull vertices or density mutation points) are determined, and a neighborhood (such as a circular area with a radius of ε) is delineated with each boundary point as the center. Effective instability points within the neighborhood are extracted to form a local manifold surface. Differential geometry methods are then used to fit a quadratic paraboloid to the manifold within the neighborhood of the boundary point, and the average curvature of the quadratic paraboloid is calculated as the manifold curvature of the boundary instability point, which is used to quantify the degree of geometric distortion at the boundary. Obtain the average curvature of all valid instability points in the two-dimensional manifold and set the boundary curvature threshold based on the average curvature; It can be understood that the average curvature of all effective instability points in the two-dimensional manifold is calculated as the benchmark for the overall geometric smoothness of the manifold; the standard deviation of the curvature of these instability points is used to reflect the degree of discreteness. Combined with the engineering requirements for instability sensitivity, a smaller empirical coefficient is used for high-precision scenarios and a larger coefficient is used for robust scenarios. A threshold model of the average curvature and several times the standard deviation is constructed. The manifold curvature of the boundary point is compared with the threshold to define the degree of geometric distortion and identify critical instability boundary points. like Figure 2As shown in Figure 2, if the manifold curvature of the boundary instability point is higher than or equal to the preset boundary curvature threshold, it is determined that there is a manifold wrinkle on the boundary, that is, the cutting force instability point is not fully captured within the coupling monitoring period; If the manifold curvature of the boundary instability point is lower than the preset boundary curvature threshold, the manifold curvature of the boundary instability point is continuously monitored; If manifold wrinkles exist, a periodic stretching analysis is performed on the coupled monitoring period to determine whether the coupled monitoring period cuts through the topological closed loop of the viscosity-temperature coupling. Preferably, if manifold wrinkles exist, the number of phase ring handles of the boundary instability points within the coupling monitoring period and the average number of phase ring handles of all effective instability points within the coupling monitoring period are obtained in the two-dimensional manifold; The absolute deviation between the number of phase ring handles at the boundary instability point and the average number of phase ring handles of all effective instability points within the coupling monitoring period is calculated to obtain the stretching judgment value; Based on the pull-up judgment value, it is judged whether the coupling monitoring cycle cuts the topological closed loop of the viscosity-temperature coupling; For example, if , then the topological closed loop of the coupling monitoring cycle cutting viscosity-temperature coupling is determined. are the number of phase loop handles at the boundary instability point and the average number of phase loop handles of all effective instability points within the coupling monitoring period; when This indicates that the boundary topology is disconnected from the main body, for example, a closed loop in the topology is cut into an open loop, and the cycle needs to be stretched to include the complete closed loop; It should be explained that the difference in the number of phase ring handles exceeding 1 indicates a topological structure break; If the topological closed loop of viscosity-temperature coupling is cut, the ratio of the manifold curvature at the boundary point to the boundary curvature threshold is calculated as the wrinkle strength; Obtain the period length of the coupling monitoring period, multiply the fold intensity by the period length to obtain the alternating period length; The coupling cycle length and the alternation cycle length are summed to obtain the cycle verification length; The cycle verification length is used as the cycle length of the next coupling monitoring cycle, the stretching judgment value is calculated again, and it is judged again whether the coupling monitoring cycle cuts the topological closed loop of the viscosity-temperature coupling; If there is no cutting, the adjustment of the coupling monitoring period is completed; if there is still cutting, the coupling monitoring period is continuously adjusted; It can be understood that by dynamically adjusting the coupling monitoring cycle, a topological closed loop that fully covers the viscosity-temperature coupling can be achieved, reducing the missed detection of instability points caused by improper cycle settings; When the coupling monitoring cycle does not cut the topological closed loop, it means that the current cycle length can fully capture the dynamic changes of viscosity-temperature coupling, and adjustment can be stopped to ensure monitoring efficiency. If cutting still occurs, it means that the cycle fails to cover the full range of viscosity-temperature coupling. The cycle length is continuously adjusted until it completely includes the topological closed loop of viscosity-temperature coupling, thereby capturing the cutting force instability point within the strong coupling range, improving the spatiotemporal consistency of multi-physics field coupling analysis, and providing a reliable time benchmark for subsequent cutting precision optimization.

[0031] S5. Extract cutting parameters of effective instability points within the coupling monitoring period, establish a mapping relationship between viscosity-temperature coupling strength and cutting parameters, and optimize cutting accuracy based on the mapping relationship; Among them, the method of extracting the cutting parameters of the effective instability point within the coupling monitoring period is: The spindle speed, cutting depth, feed rate, coupling strength value, number of phase ring shanks and manifold curvature of the effective instability point during the coupling monitoring period are obtained, the cutting parameter vector is constructed, and the cutting parameter vector is standardized. Establish a mapping relationship model between viscosity-temperature coupling strength and cutting parameters, and output the cutting parameter offset; It will be understood by those skilled in the art that the cutting parameters and viscosity-temperature coupling strength values ​​corresponding to the effective instability points are extracted, and the characteristics such as the number of phase ring shanks and manifold curvature of each point are collected at the same time to construct a vector set containing multidimensional parameters, such as [coupling strength value, spindle speed, cutting depth, feed rate, number of phase ring shanks, manifold curvature], and the dimensional effect is eliminated through standardization. A mapping model was constructed using random forest regression in machine learning. 60% of the historical data samples were used as the training set. The standardized coupling strength and cutting parameter vectors were input. The nonlinear relationship between coupling strength and parameter changes was learned using the splitting rules of a decision tree. For example, when the coupling strength is greater than 2.5, the cutting depth needs to be reduced by 0.05 mm for every 100 r / min increase in spindle speed to maintain stability; 20% of the samples are used as a validation set, and hyperparameters such as tree depth and node splitting threshold are adjusted through mean square error; the remaining 20% ​​of the samples are used to test the generalization ability of the model and whether the parameter offset prediction error is less than 5%). The real-time monitored coupling strength value is input into the trained model to output the offset of each cutting parameter; for example, the spindle speed offset Δn = -5%, the cutting depth offset Δd = -0.1mm); Control the cutting accuracy of the quadrilateral lathe based on the offset of the cutting parameters; It can be understood that by embedding the offset instruction into the code through the cutting control interface of the CNC system, real-time dynamic compensation of the cutting parameters can be achieved, forming a closed-loop optimization of viscosity-temperature coupling analysis, parameter calculation, and precision control.

[0032] Example 3 like Figure 3 As shown, a cutting accuracy optimization system for a four-axis linkage lathe also includes the following modules: Coupling Analysis Module: This module is used to collect cutting data from the micro-domain mesh of a four-axis lathe, extract the time series data stream of cutting fluid viscosity and temperature, perform coupling analysis on viscosity and temperature based on the time series data stream, and extract the viscosity-temperature gradient vector of the micro-domain mesh. Cycle Extraction Module: Based on the viscosity-temperature gradient vector of each micro-domain grid, it is used to perform gradient fluctuation analysis and spatial consistency analysis to determine the stability of the cutting fluid. If it is unstable, the viscosity-temperature trajectory is drawn. By determining whether the trajectory forms a closed loop, if so, the coupling strength value is obtained by performing back-expansion and symmetry analysis, and the coupling monitoring period is determined; Instability extraction module: This module intercepts the torque component and instantaneous phase angle during the coupled monitoring period, establishes a transfer function between viscosity and cutting force based on the instantaneous phase angle, identifies critical candidate instability points of the cutting force during the coupled monitoring period, verifies these critical candidate instability points using the second-order force signal criterion and viscosity-temperature gradient, and constructs a set of cutting force instability points. Closed-loop verification module: This module is used to collect the cutting force mutation points in the boundary area of ​​the coupling monitoring cycle and verify the validity of the coupling monitoring cycle to determine whether the coupling monitoring cycle cuts through the topological closed loop of the viscosity-temperature coupling. If so, the coupling monitoring cycle is adjusted. Precision adjustment module: used to extract the cutting parameters of the effective instability point within the coupling monitoring period, establish the mapping relationship between the viscosity-temperature coupling strength and the cutting parameters, and optimize the cutting accuracy based on the mapping relationship.

[0033] The above is a detailed description of an embodiment of the present invention. However, the content is only a preferred embodiment of the present invention and should not be considered to limit the scope of the present invention. All equivalent changes and improvements made within the scope of the present invention should still fall within the scope of the present invention.

Claims

1. A method for optimizing the cutting accuracy of a four-axis linkage lathe, characterized by: The steps include: Extract the time series data stream of cutting fluid viscosity and temperature, perform coupled analysis of viscosity and temperature based on the time series data stream, and extract the viscosity-temperature gradient vector of the micro-domain grid; Based on the viscosity-temperature gradient vector, gradient fluctuation analysis and spatial consistency analysis are performed to determine the stability of the cutting fluid. If it is unstable, the viscosity-temperature trajectory is drawn. By determining whether the trajectory forms a closed loop, if so, the coupling strength value is obtained by performing back-expansion and symmetry analysis, and the coupling monitoring period is determined. The torque component and instantaneous phase angle are intercepted during the coupled monitoring period, and the transfer function of viscosity and cutting force is established. The critical candidate instability points of the cutting force during the coupled monitoring period are identified. The critical candidate instability points are verified by the second-order force signal criterion and the viscosity-temperature gradient, and the cutting force instability point set is constructed. The cutting force mutation points in the boundary area of ​​the coupling monitoring cycle are collected, and the effectiveness of the coupling monitoring cycle is verified to determine whether the coupling monitoring cycle cuts the topological closed loop of viscosity-temperature coupling. If so, the coupling monitoring cycle is adjusted.

2. The cutting accuracy optimization method of a four-axis linkage lathe according to claim 1, characterized in that: The method of extracting the viscosity-temperature gradient vector of the micro-domain grid is: During the monitoring period, the time series data stream of micro-domain viscosity and temperature in the cutting micro-domain is collected; The cutting micro-domain is divided into different micro-domain grids, and the time-series data streams within the micro-domain grids are aligned using a spatiotemporal registration algorithm to obtain the aligned micro-domain viscosity, temperature, and sampling time. Based on the microdomain viscosity, temperature, and sampling time, a viscosity-temperature distribution field matrix including different microdomain grids is constructed; The viscosity-temperature gradient vector of each micro-domain grid containing viscosity and temperature is extracted based on the viscosity-temperature distribution field matrix.

3. The cutting accuracy optimization method of a four-axis linkage lathe according to claim 1, characterized in that: The coupling monitoring period is determined as follows: If there is a thermal flow coupling effect, obtain the maximum longitudinal temperature span and the minimum longitudinal temperature span of the closed loop; Calculate the ratio of the deviation between the maximum longitudinal temperature span and the minimum longitudinal temperature span as the loop expansion coefficient; Obtain the slope of the right branch and the slope of the left branch of the closed loop, perform ratio processing on the slope of the right branch and the slope of the left branch to obtain the asymmetry; The asymmetry and the loop expansion coefficient are summed to obtain the coupling strength value; Divide different level intervals based on the coupling strength value and extract the strong coupling interval; The monitoring period of the strong coupling interval is obtained as the coupling monitoring period.

4. The cutting accuracy optimization method of a four-axis linkage lathe according to claim 3, characterized in that: The determination method of the presence of the thermal-fluid coupling effect is as follows: Based on the viscosity-temperature gradient vector of each micro-domain grid, gradient fluctuation analysis and spatial consistency analysis are performed to obtain the spatial consistency coefficient and gradient fluctuation coefficient; Based on the spatial consistency coefficient and gradient fluctuation coefficient as independent criteria for judging the stability of the cutting fluid, the stability of the cutting fluid is judged; If the cutting fluid is unstable, the viscosity-temperature trajectory is drawn with the micro-domain viscosity as the horizontal axis and the temperature as the vertical axis; Based on the viscosity-temperature trajectory, it is determined whether the trajectory forms a clockwise closed loop. If so, it is determined that there is a thermal-flux coupling effect.

5. The cutting accuracy optimization method of a four-axis linkage lathe according to claim 4, characterized in that: The judgment method of cutting fluid instability is: Based on the viscosity-temperature gradient vector of each micro-domain grid, gradient fluctuation analysis and spatial consistency analysis are performed to obtain the spatial consistency coefficient and gradient fluctuation coefficient; Based on the spatial consistency coefficient and gradient fluctuation coefficient as independent criteria for judging the stability of cutting fluid; A comparative analysis was conducted based on the independent criteria of cutting fluid stability to obtain the result of cutting fluid instability.

6. The cutting accuracy optimization method of a four-axis linkage lathe according to claim 1, characterized in that: The method of constructing the cutting force instability point set is: Obtain the critical candidate instability point of the cutting force and the viscosity-temperature gradient vector, extract the temperature gradient and viscosity drop rate, and re-screen the critical candidate instability point based on the temperature and viscosity drop rate; The complete coupling monitoring cycle is traversed to obtain the critical candidate instability points screened again within the complete coupling monitoring cycle, and a cutting force instability point set containing the instantaneous phase angle and amplitude of each critical candidate instability point is constructed.

7. The cutting accuracy optimization method of a four-axis linkage lathe according to claim 6, characterized in that: The method of obtaining the critical candidate instability point of the cutting force is: The torque component of the main shaft is collected during the coupling monitoring period; The fundamental frequency component of the cutting force is calculated based on the torque component, and the instantaneous phase angle of the vibration signal is extracted by performing Hilbert-Huang transform on the fundamental frequency component. The transfer function of viscosity and cutting force is established based on the instantaneous phase angle, and the critical candidate instability points of the cutting force in the coupled monitoring cycle are identified.

8. The cutting accuracy optimization method of a four-axis linkage lathe according to claim 7, characterized in that: The method for identifying the critical candidate instability points of the cutting force in the coupled monitoring cycle is as follows: Establish the sweep range of angular frequency and calculate the amplitude of the transfer function of viscosity and cutting force; Based on the amplitude within the frequency sweep range, the minimum amplitude point is solved by the Newton iteration method and is used as the critical candidate instability point.

9. The cutting accuracy optimization method of a four-axis linkage lathe according to claim 1, characterized in that: The method for judging whether the coupling monitoring cycle cuts the topological closed loop of viscosity-temperature coupling is: If there are manifold wrinkles, obtain the number of phase ring handles of the boundary instability points within the coupling monitoring period and the average number of phase ring handles of all effective instability points within the coupling monitoring period in the two-dimensional manifold; The absolute deviation between the number of phase ring handles at the boundary instability point and the average number of phase ring handles of all effective instability points within the coupling monitoring period is calculated to obtain the stretching judgment value; Based on the pull-up judgment value, it is determined whether the coupling monitoring cycle cuts the topological closed loop of the viscosity-temperature coupling.

10. The cutting accuracy optimization method of a four-axis linkage lathe according to claim 9, characterized in that: The determination method of the presence of the manifold fold is: A two-dimensional manifold is constructed to map the cutting force instability point set of the coupled monitoring period to the two-dimensional manifold; Obtain the boundary point neighborhood of the two-dimensional manifold and the manifold of the effective instability point, and calculate the manifold curvature of the boundary instability point; The average curvature of all valid instability points in the two-dimensional manifold is obtained. If the manifold curvature of the boundary instability point is higher than or equal to the preset boundary curvature threshold, it is determined that the boundary has manifold wrinkles.

11. The cutting accuracy optimization method of a four-axis linkage lathe according to claim 1, characterized in that: The following steps are also included: The cutting parameters of the effective instability points within the coupling monitoring period are extracted, and the mapping relationship between the viscosity-temperature coupling strength and the cutting parameters is established. The cutting accuracy is optimized based on the mapping relationship.

12. The cutting accuracy optimization method of a four-axis linkage lathe according to claim 1, characterized in that: The mapping relationship optimizes the cutting accuracy in the following manner: Establish a mapping relationship model between viscosity-temperature coupling strength and cutting parameters, and output the cutting parameter offset; The cutting accuracy of a quadrilateral lathe is controlled based on the offset of the cutting parameters.

13. A cutting accuracy optimization system for a four-axis linkage lathe, used to implement any one of the cutting accuracy optimization methods for a four-axis linkage lathe according to claims 1-12, characterized in that: Includes the following modules: Coupling analysis module: used to extract the time series data stream of cutting fluid viscosity and temperature, perform coupling analysis on viscosity and temperature based on the time series data stream, and extract the viscosity-temperature gradient vector of the micro-domain grid; Cycle Extraction Module: This module performs gradient fluctuation analysis and spatial consistency analysis based on the viscosity-temperature gradient vector to determine the stability of the cutting fluid. If the viscosity-temperature trajectory is unstable, it plots the viscosity-temperature trajectory and determines whether the trajectory forms a closed loop. If so, it performs back-expansion and symmetry analysis to obtain the coupling strength value and determine the coupling monitoring cycle. Instability extraction module: This module intercepts the torque component and instantaneous phase angle during the coupled monitoring period, establishes a transfer function between viscosity and cutting force, identifies critical candidate instability points of the cutting force during the coupled monitoring period, verifies these critical candidate instability points using the second-order force signal criterion and viscosity-temperature gradient, and constructs a set of cutting force instability points. Closed-loop verification module: This module is used to collect the cutting force mutation points in the boundary area of ​​the coupling monitoring cycle and verify the validity of the coupling monitoring cycle to determine whether the coupling monitoring cycle cuts through the topological closed loop of the viscosity-temperature coupling. If so, the coupling monitoring cycle is adjusted. Precision adjustment module: used to extract the cutting parameters of the effective instability point within the coupling monitoring period, establish the mapping relationship between the viscosity-temperature coupling strength and the cutting parameters, and optimize the cutting accuracy based on the mapping relationship.

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