CN-122021371-A - Thermodynamic performance analysis method under coordinate grinder multi-process conversion driven by hidden mechanism

CN122021371ACN 122021371 ACN122021371 ACN 122021371ACN-122021371-A

Abstract

The application discloses a thermodynamic performance analysis method under the multi-process conversion of a coordinate grinder driven by a visible and hidden mechanism, and relates to the technical field of equipment thermodynamic performance analysis; the method comprises the steps of performing multi-process actual measurement and simulation data iterative optimization, obtaining an explicit thermodynamic differential control equation with unified multi-process through symbolization, symmetry and dimensionless treatment, analyzing to obtain an implicit mathematical expression by taking deviation of theoretical prediction and actual measurement data as a target, and finally fusing the implicit expression as a compensation term and the explicit equation, and performing iterative correction through an alternate optimization mechanism until the thermodynamic field prediction precision reaches the standard. The method has the advantages of taking physical consistency and prediction precision into consideration, accurately predicting the complete thermodynamic field distribution of the machine tool based on sparse thermodynamic sensing data, and providing reliable theoretical support for machine tool machining precision guarantee.

Inventors

QIU CHAN
SUN JIACHENG
LIU ZHENYU
HOU MINGJIE
ZHANG YUSONG
TAN JIANRONG

Assignees

浙江大学

Dates

Publication Date: 20260512
Application Date: 20260416

Claims (10)

1. The thermodynamic performance analysis method under the transformation of the coordinate grinder multi-process driven by the implicit mechanism is characterized by comprising the following steps: based on thermodynamic physical rules of heat conduction process, heat convection process and process intermittent thermal shock, and combining elastic mechanics and contact mechanics theory, establishing an explicit thermodynamic mechanism equation corresponding to key components of the compound coordinate grinding machine under various processes; Based on the actual measurement data and the thermodynamic numerical simulation data of the thermodynamic tests under various processes, carrying out iterative optimization on the explicit thermodynamic mechanism equation, and carrying out symbolization, symmetry and dimensionless treatment on the optimized explicit thermodynamic mechanism equation to obtain a unified explicit thermodynamic differential control equation under various processes; Taking the deviation between the thermodynamic theory predicted data output by the explicit thermodynamic differential control equation and the thermodynamic test measured data under the corresponding working condition as an implicit mechanism analysis target, constructing an implicit mechanism module for representing the dynamic characteristics of the deviation, and analyzing to obtain an implicit mathematical expression corresponding to the deviation; The implicit mathematical expression is used as a compensation term and is fused with the explicit thermodynamic differential control equation to obtain a complete implicit thermodynamic mechanism equation, the implicit thermodynamic mechanism equation is subjected to iterative correction based on an alternate optimization mechanism of model prediction accuracy verification and implicit mathematical expression coefficient updating until model prediction accuracy reaches a preset threshold value, the implicit thermodynamic mechanism equation is used for predicting and obtaining complete thermodynamic field distribution of the compound coordinate grinding machine according to sparse thermodynamic sensing data collected on the compound coordinate grinding machine, and the model prediction accuracy is the prediction accuracy of the implicit thermodynamic mechanism equation on the thermodynamic field distribution.
2. The method for analyzing the thermodynamic performance under the multi-process conversion of the coordinate grinder driven by the obvious mechanism according to claim 1 is characterized in that the explicit thermodynamic equation comprises an explicit heat transfer mechanism equation and an explicit stress distribution mechanism equation, and the method specifically comprises the steps of establishing the explicit thermodynamic equation corresponding to the key components of the coordinate grinder under various processes based on thermodynamic physical rules of heat conduction process, heat convection process and process intermittent thermal shock by combining elastic mechanics and contact mechanics theory: Based on thermodynamic physical rules of heat conduction process, heat convection process and intermittent thermal shock of process, an explicit heat transfer mechanism equation of key parts of the compound coordinate grinding machine is established; Based on elastic mechanics and contact mechanics theory, combining the assembly pretightening force, the component gravity and the multiaxial motion coupling factor, and establishing an explicit stress distribution mechanism equation of the key component of the compound coordinate grinding machine; and integrating according to the explicit heat transfer mechanism equation and the explicit stress distribution mechanism equation to obtain an explicit thermodynamic mechanism equation.
3. The method for analyzing the thermal performance under the multi-process conversion of the coordinate grinder driven by the hidden mechanism according to claim 2 is characterized in that the key components of the compound coordinate grinder comprise a main shaft box, a stand column, a guide rail and a workbench of the compound coordinate grinder, the thermal conduction process covers the thermal diffusion process in the components, the thermal convection process covers the heat exchange process of cutting fluid, ambient air and the surfaces of the components, the intermittent thermal shock of the process is generated by periodic feeding, idle stroke and tool changing actions in the processing process, the assembly pretightening force is exerted by foundation bolts, guide rail bands and a main shaft bearing pretightening mechanism, the gravity of the components is a constant load generated by the main shaft box, the stand column, a workpiece and a clamp under the action of a gravity field, and the multi-axis motion coupling factor is a dynamic inertia force and a moment generated by the interaction of acceleration and speed of multiple motion axes of the compound coordinate grinder in the linkage processing on the structural components.
4. The method for analyzing thermal performance under the transformation of multiple processes of a coordinate grinder driven by a hidden mechanism according to claim 1, wherein the method is characterized by performing iterative optimization on the explicit thermodynamic mechanism equation based on the actual measurement data and the thermodynamic numerical simulation data of the thermodynamic tests under multiple processes, and performing symbolization, symmetry and dimensionless treatment on the optimized explicit thermodynamic mechanism equation to obtain a unified explicit thermodynamic differential control equation under multiple processes, and specifically comprises the following steps: Substituting the actual measurement data of the thermal test and the thermal numerical simulation data under various processes into the explicit thermal mechanism equation, and reversely solving and correcting the undetermined coefficient and the functional relation in the explicit thermal mechanism equation through a parameter identification algorithm to ensure that the output value of the explicit thermal mechanism equation, the actual measurement data of the thermal test and the thermal numerical simulation data reach the best fit in the global process range; Through symbolization, symmetry and dimensionless treatment, the modified explicit thermodynamic mechanism equations corresponding to different processes are unified and normalized into an explicit thermodynamic differential control equation with the same differential form, and the differences of the different processes are distinguished through the process coefficient matrix, the input excitation vector and the values of boundary conditions in the explicit thermodynamic differential control equation.
5. The method for analyzing thermal performance under the multi-process conversion of the coordinate grinding machine driven by the implicit mechanism according to claim 1 is characterized by constructing an implicit mechanism module for representing the dynamic characteristics of the deviation, analyzing to obtain an implicit mathematical expression corresponding to the deviation, specifically, extracting a potential change mode in the deviation by a nonlinear fitting model driven by data, calculating the gradient of the deviation relative to each influencing variable by utilizing an automatic differentiation technology, and analyzing to obtain the implicit mathematical expression of the deviation by a gradient reverse tracing and sparse regression algorithm.
6. The method for analyzing thermal performance under multi-process conversion of a coordinate grinder driven by a hidden mechanism according to claim 5, wherein the nonlinear fitting model is a deep neural network, an input layer of the deep neural network receives process parameters, motion states and time sequence monitoring data, nonlinear transformation is performed through at least one hidden layer, an output layer fits a current value of thermal deviation, the influencing variables comprise process parameters and various process variables, the process parameters comprise cutting depth, feed rate and spindle rotation speed, and the process variables comprise spindle power, servo current of each axis and component key point temperature.
7. The method for analyzing thermal performance under multi-process conversion of a coordinate grinder driven by a implicit mechanism according to claim 5, wherein the gradient backtracking is specifically characterized in that based on the gradient relation between an offset value output by a nonlinear fitting model and each influence variable, the influence variables are ordered according to gradient significance, a candidate function expression library is constructed through basic mathematical operators based on the ordered influence variables, the basic mathematical operators comprise addition and subtraction, multiplication and division and exponentiation, and the candidate function expression library comprises polynomial terms, trigonometric function terms, exponential function terms and logarithmic function terms.
8. The method for analyzing thermal performance under the transformation of multiple processes of a coordinate grinding machine driven by a hidden mechanism according to claim 7, wherein the sparse regression algorithm adopts a LASSO regression, stepwise regression or symbolic regression method, and the hidden mathematical expression of the deviation is obtained by introducing regularization terms or setting a significance threshold value, screening sparse non-zero key terms from the candidate function expression library, and combining the key terms.
9. The method for analyzing thermal performance under the transformation of multiple processes of a coordinate grinding machine driven by a hidden mechanism according to claim 1, wherein the alternate optimization mechanism for model prediction accuracy verification and implicit mathematical expression coefficient update specifically comprises: Inputting actual measurement sparse thermal sensing data into a current implicit thermal mechanism equation, predicting to obtain thermal theory prediction data, and obtaining global prediction deviation of the current implicit thermal mechanism equation based on thermal test actual measurement data and the thermal theory prediction data under corresponding working conditions; Determining model prediction accuracy based on the global prediction deviation, and judging whether the model prediction accuracy reaches a preset threshold value or not; if the model prediction precision does not reach the preset threshold value, analyzing the gradient of the global prediction deviation on each coefficient in the implicit mathematical expression through a back propagation algorithm, and determining the coefficient optimization direction; updating each coefficient in the implicit mathematical expression by adopting an optimization algorithm based on the gradient direction so as to minimize the global prediction deviation and obtain the updated implicit mathematical expression; and merging the updated implicit mathematical expression with the explicit thermodynamic differential control equation again to obtain an updated implicit thermodynamic mechanism equation, taking the updated implicit thermodynamic mechanism equation as a current implicit thermodynamic mechanism equation, jumping to the step of inputting actual measurement sparse thermodynamic sensing data into the current implicit thermodynamic mechanism equation, predicting to obtain thermodynamic theory prediction data, and obtaining global prediction deviation of the current implicit thermodynamic mechanism equation based on thermodynamic test actual measurement data and the thermodynamic theory prediction data under corresponding working conditions until model prediction accuracy reaches a preset threshold.
10. The method for analyzing the thermodynamic performance under the transformation of the coordinate grinding machine multi-process driven by the implicit mechanism according to claim 1 is characterized in that the implicit mathematical expression is used as a compensation term and fused with the explicit thermodynamic differential control equation to obtain a complete implicit thermodynamic mechanism equation, specifically, the implicit mathematical expression is used as a source term and is overlapped into the explicit thermodynamic differential control equation to form the complete implicit thermodynamic mechanism equation.

Description

Thermodynamic performance analysis method under coordinate grinder multi-process conversion driven by hidden mechanism Technical Field The application relates to the technical field of equipment thermal performance analysis, in particular to a thermal performance analysis method under the transformation of a coordinate grinder process driven by a hidden mechanism. Background The precision machining of complex parts is the core capability of the modern high-end manufacturing technology, and in a high-end machining machine tool, a composite coordinate grinding machine has ultrahigh coordinate positioning precision and multiple processing capabilities of turning, milling, drilling and grinding, and is key equipment for realizing the precision machining of core basic parts of high-end equipment. The dynamic time-varying thermal characteristic under the multi-process conversion is a main bottleneck for restricting the machining precision of the compound coordinate grinding machine, and the accurate calculation of the thermal performance of the machine tool is realized, so that the method is a necessary premise for guaranteeing the machining precision. In recent years, a mechanism data fusion method represented by a physical information neural network has shown the advantage of both efficiency and precision in the field of physical field calculation. However, the thermodynamic mechanism under the multi-process conversion of the compound coordinate grinding machine is complex, the dynamic thermodynamic characteristics are difficult to accurately describe by the traditional simplified mechanism equation, and the dynamic thermodynamic characteristics are directly used as physical constraints to be embedded into a calculation model, so that the calculation precision of the thermodynamic performance is insufficient, and the requirements of high-efficiency and high-precision thermodynamic performance calculation under the multi-working condition of the compound coordinate grinding machine cannot be met. Disclosure of Invention The application aims to provide a thermodynamic performance analysis method under the multi-process conversion of a coordinate grinder driven by a hidden mechanism, which can realize the high-precision analysis of thermodynamic performance under the multi-process conversion of a compound coordinate grinder and provide reliable theoretical support for the thermodynamic performance analysis of a machine tool. In order to achieve the above object, the present application provides the following solutions: A thermodynamic performance analysis method under the transformation of a coordinate grinder multi-process driven by a hidden mechanism comprises the following steps: Based on thermodynamic physical rules of heat conduction process, heat convection process and intermittent thermal shock of process, and combining elastic mechanics and contact mechanics theory, an explicit thermodynamic mechanism equation corresponding to key parts of the compound coordinate grinding machine under various processes is established. Based on the actual measurement data and the thermodynamic numerical simulation data of the thermodynamic tests under various processes, carrying out iterative optimization on the explicit thermodynamic mechanism equation, and carrying out symbolization, symmetry and dimensionless treatment on the optimized explicit thermodynamic mechanism equation to obtain a unified explicit thermodynamic differential control equation under various processes. And constructing an implicit mechanism module for representing the dynamic characteristics of the deviation by taking the deviation between the thermodynamic theory predicted data output by the explicit thermodynamic differential control equation and the thermodynamic test measured data under the corresponding working condition as an implicit mechanism analysis target, and analyzing to obtain an implicit mathematical expression corresponding to the deviation. The implicit mathematical expression is used as a compensation term and fused with an explicit thermodynamic differential control equation to obtain a complete implicit thermodynamic mechanism equation, the implicit thermodynamic mechanism equation is subjected to iterative correction based on an alternate optimization mechanism of model prediction accuracy check and implicit mathematical expression coefficient update until model prediction accuracy reaches a preset threshold, the implicit thermodynamic mechanism equation is used for predicting and obtaining complete thermodynamic field distribution of the compound coordinate grinding machine according to sparse thermodynamic sensing data acquired on the compound coordinate grinding machine, and the model prediction accuracy is the prediction accuracy of the implicit thermodynamic mechanism equation on the thermodynamic field distribution. Optionally, the explicit thermodynamic mechanism equation comprises an explicit heat transfer mechanism equa