CN-122018429-A - Intelligent multi-axis error compensation control system and method for aluminum material processing

Abstract

The invention discloses an intelligent multi-axis error compensation control system and method for aluminum processing, which relate to the technical field of numerical control processing precision control, the current signal sequence of the multi-axis servo system is synchronously collected, and the current signal sequence is deconstructed into low-frequency, medium-frequency and high-frequency components reflecting the characteristics of heat, force and materials by utilizing a variational modal decomposition algorithm. And adjusting the thermal displacement weight by using the material confidence coefficient, and adjusting the nonlinear deformation compensation quantity by combining with the thermal softening gain coefficient based on the Sigmoid function. The compensation vector of the output space position is weighted and synthesized to solve the nonlinear mismatch problem caused by the heat flow evolution triggered by cutting energy consumption and load fluctuation, so that the compensation instruction and the evolution process of the actual physical field maintain the consistent mapping relation.

Inventors

• LIN JUNFENG
• ZHANG TONGYING

Assignees

• 南阳恒亚铝业有限公司

Dates

Publication Date

20260512

Application Date

20260209

Claims (7)

1. 1. The intelligent multi-axis error compensation control method for aluminum processing is characterized by comprising the following steps of: S1, acquiring a current signal sequence, namely synchronously acquiring the current signal sequence of a multi-axis servo system and processing track information of a multi-axis numerical control system, and analyzing the processing track information to obtain a processing path normal unit vector; S2, generating physical characteristic components, namely generating a material stiffness characteristic matrix according to the power spectrum energy distribution of the high-frequency components, calculating a dynamic cutter relieving deformation scalar by utilizing the material stiffness characteristic matrix and the medium-frequency components, and performing time domain integration on the low-frequency components to generate a transient thermal deformation vector; S3, calculating a weight coefficient, namely generating a material confidence coefficient according to the dispersion of the material stiffness characteristic matrix, and generating a heat softening gain coefficient according to the modulus value of the transient heat deformation vector; And S4, synthesizing an output vector, namely carrying out weighted synthesis on the transient thermal deformation vector and the dynamic cutter yielding deformation scalar according to the material confidence coefficient and the thermal softening gain coefficient, and outputting a space position compensation vector for correcting the track deviation.
2. 2. The method of claim 1, wherein generating the material stiffness feature matrix in step S2 comprises: Acquiring the power spectral density of the high-frequency component; and identifying the characteristic energy peak frequency in the power spectrum density, and matching the characteristic energy peak frequency with a preset fingerprint library to correct parameters in the material stiffness characteristic matrix.
3. 3. The method according to claim 1, wherein the spatial position compensation vector is synthesized in step S4 The following formula is followed: Wherein, the For the confidence coefficient of the material, For the transient thermal deformation vector, For the heat softening gain factor, For the preset gain factor to be a predetermined gain factor, For the dynamic let-down tool to deform a scalar, Is a normal unit vector of the processing path.
4. 4. The method according to claim 1, wherein the texture confidence coefficient is generated in step S3 The following formula is followed: Wherein, the For the variance of the high frequency component, In order to adjust the coefficient of the power supply, Is a smooth constant.
5. 5. The method according to claim 1, wherein the heat softening gain factor is generated in step S3 The following formula is followed: Wherein, the As a modulus of the transient thermal deformation vector, As a reference to the reference level, In order to set the threshold value in advance, As a gain factor, the gain factor is used, Is the maximum gain boundary.
6. 6. An intelligent multi-axis error compensation control system for aluminum processing, characterized in that the system comprises a processor and a memory, the memory storing computer program instructions that when executed by the processor implement the steps of the method of any one of claims 1 to 5.
7. 7. A computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the steps of the method according to any one of claims 1 to 5.

Description

Intelligent multi-axis error compensation control system and method for aluminum material processing Technical Field The invention relates to the technical field of numerical control machining precision control, in particular to an intelligent multi-axis error compensation control system and method for aluminum material machining. Background In the multi-axis linkage processing process of the aluminum alloy, an electromagnetic current sequence of a feed axis servo system contains dynamic evolution information of cutting energy consumption, mechanical load and material characteristics. The existing error compensation technology utilizes a preset analytical model to correlate current, temperature and displacement. However, in the face of high dynamic cutting and multi-field coupling conditions, the machining system has the following failure mechanisms: The non-linear mismatch mechanism of critical softening point is that the aluminum alloy material has heat sensitivity. When the transient heat flow accumulated in the processing area triggers the material to enter a heat softening stage, the mechanical constitutive relation of the aluminum alloy is subjected to nonlinear mutation. Because the existing compensation algorithm is mostly based on linear mapping logic, continuous and matched gain adjustment cannot be provided near a thermal softening critical point, so that a compensation vector generates overshoot in a physical sense or dynamic oscillation of a servo control loop is induced due to step-type switching. The mapping mismatch mechanism caused by material heterogeneity is that microscopic constitutive differences (such as uneven hardness or tissue segregation) inside aluminum alloy parts can cause high-frequency disturbance of cutting moment and synchronously reflect the high-frequency disturbance in fluctuation of electromagnetic current sequences. Conventional compensation models generally consider material stiffness as a constant parameter, lacking in the perceived and feedback dimensions of heterogeneous disturbances of the material. Under the working condition of large material variance, the mapping relation between the output of a thermal prediction model preset in a processing system and the deformation state of an actual structure is difficult to keep stable and consistent, so that the compensation precision is in integral failure. Peeling failure mechanism of non-stationary signal characteristics, namely signals generated by multi-axis linkage processing have non-stationary and time-varying characteristics. The low-frequency thermal evolution characteristic triggered by energy consumption and the high-frequency fingerprint characteristic caused by material difference are overlapped in a time-frequency space. The existing frequency domain analysis means are limited by global stationarity assumption, lack of dynamic constraint on local time domain features of signals, so that decoupled physical components have spectrum interference and feature mismatch, and pure physical input cannot be provided for subsequent spatial position compensation vector synthesis. In summary, the physical characteristic analysis shows nonlinear mismatch characteristics in the space-time dimension due to transient heat flow evolution triggered by cutting energy consumption, dynamic load fluctuation and material surface layer rigidity degradation, so that a preset compensation vector in a processing system is difficult to maintain a stable and consistent mapping relation with the evolution process of an actual physical field, and the overall failure of the steady-state characteristic of the processing system is caused. Disclosure of Invention The invention provides an intelligent multi-axis error compensation control system and method for aluminum processing, which are used for solving the problem that in the multi-axis linkage processing process of aluminum alloy, transient heat flow evolution, dynamic load fluctuation and material surface layer rigidity degradation triggered by cutting energy consumption show nonlinear mismatch characteristics in space-time dimension, so that a preset compensation vector in a processing system is difficult to maintain a stable and consistent mapping relation with the evolution process of an actual physical field, thereby causing the overall failure of steady-state characteristics of the processing system. In view of the above problems, the present invention provides an intelligent multi-axis error compensation control method for aluminum processing, the method comprising the steps of: S1, acquiring a current signal sequence, namely synchronously acquiring the current signal sequence of a multi-axis servo system and processing track information of a multi-axis numerical control system, and analyzing the processing track information to obtain a processing path normal unit vector; S2, generating physical characteristic components, namely generating a material stiffness characteristic matr