A Physical Modeling Method for Axial Thermal Error of CNC Machine Tool Spindle

Abstract

The invention discloses a physical modeling method for axial thermal error of a CNC machine tool spindle, which includes the following steps: (A) Installing a temperature sensor on the machine tool, the temperature sensor includes a first temperature sensor, a second temperature sensor, a third temperature sensor sensor and the fourth temperature sensor; (B) Establish a thermal error linear submodel of the spindle only caused by ambient temperature changes; (C) Establish a thermal error linear submodel of the spindle only caused by spindle temperature changes; (D) Establish a spindle only affected by Non-linear sub-model of thermal error caused by column temperature change; (E) Establish a superposition model including the above-mentioned error components; the spindle axial thermal error model provided by the present invention takes into account the structural parameters of the machine tool, only needs 4 temperature sensors, and the model is general It has strong transformation ability and physical significance, and is easy to program and realize, providing technical support for the application of thermal error compensation in the later stage.

Description

technical field [0001] The invention belongs to the field of thermal error modeling and compensation of a main shaft in the thermal precision control of a numerical control machine tool, and in particular relates to a physical modeling method for the axial thermal error of the main shaft of a numerical control machine tool. Background technique [0002] The processing accuracy of parts is mainly determined by the accuracy of processing equipment; CNC machine tools are widely used in the processing of complex curved surface parts in the automotive, aerospace, shipbuilding and other industries. In order to achieve better product quality, these parts have higher and higher requirements for machining accuracy; therefore, there are higher requirements for the accuracy of CNC machine tools. Among the many factors affecting the accuracy of the machine tool, the deformation of the machine tool caused by thermal load and the resulting thermal error are the most critical factors affec...

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Problems solved by technology

[0004] At present, there are a large number of literatures on the axial thermal error of the spindle, but there are the following problems: (1) only consider the axial thermal error of the spindle caused by the spindle temperature, and ignore the ambient temperature and column temperature on the axial thermal error of the spindle; (2) ) requires more sensors, which increases the compensation cost and may affect the actual processing; (3) the BP neural network method is mainly used to calculate the axial thermal error of the spindle. These methods require many hyperparameters, and it is difficult to find the optimal parameters in practical applications. , it is easy to lead to over-fitting of the model, which eventually leads to insufficient generalization ability and affects the accuracy of later compensation; and these methods are only statistically significant, without machine tool structural parameters, and have no physical meaning

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