An Analytical Modeling Method for Ambient Temperature of Heavy Machine Tool

Abstract

The present invention provides an analytical modeling method for environmental temperature in a heavy-duty machine tool workshop, which combines time series analysis and Fourier series decomposition method to express the measured environmental temperature in the form of Fourier triangular series to obtain the time series, fluctuation frequency, Fluctuation amplitude, phase and other information, real-time measurement of updated temperature data and current time signal are used as input to realize real-time prediction of temperature, and replace the measured temperature for thermal error response prediction modeling. The present invention takes into account the periodicity and aperiodicity of ambient temperature fluctuations, as well as the characteristics of fluctuations that vary with seasons and years, and at the same time considers the objective fact that the current thermal state of the current machine tool is affected by both the current ambient temperature and the historical temperature state. It is beneficial to more accurately describe the time-delay response characteristics of the thermal deformation error of the machine tool, and then improve the accuracy and robustness of the thermal error prediction of the machine tool.

Description

technical field [0001] The invention relates to the field of thermal error modeling and compensation of numerical control machine tools, and more specifically relates to an analytical modeling method for ambient temperature of heavy numerical control machine tools placed in non-constant temperature processing workshops. Background technique [0002] The ambient temperature of the heavy-duty CNC machine tool has a great influence on the thermal deformation of the machine tool. In the workshop without temperature control conditions, the ambient temperature fluctuation has the characteristics of slow change and approximate cycle, and the time of daily minimum and maximum temperature varies with seasonal fluctuations. At the same time, the thermal deformation response of heavy CNC machine tools to environmental temperature fluctuations has a time lag, and the lag time also changes with the seasonal temperature. The mathematical description of the long-term fluctuation characteri...

AI Technical Summary

Problems solved by technology

However, the current linear and nonlinear thermal error prediction models cannot reflect the hysteresis characteristics with temperature, resulting in limited versatility of the current thermal error prediction model in different environments, and even failure of compensation accuracy

On the other hand, current research and analysis on ambient temperature is limited to experimental measurements, phenomenon descriptions, and qualitative discussions

The current literature search did not find any discussion on the quantitative use of nonlinear and time-delay characteristics of ambient temperature for thermal error modeling or compensation, nor did it find research on analytical modeling of ambient temperature for heavy-duty machine tools

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