Turning surface roughness prediction method based on tool parameters and material parameters

Abstract

The invention discloses a turning surface roughness prediction method based on tool parameters and material parameters. The turning surface roughness prediction method comprises the following steps that firstly, the tool parameters such as waviness of a turning tool, arc radius of a tool nose and blunt radius of a cutting edge are measured, and a surface roughness component corresponding to the contour of the cutting edge of the tool is calculated; then, the material parameters such as hardness and an elastic model are obtained, and surface roughness components corresponding to plastic lateral flow and the like are calculated through the material parameters; and finally, the surface roughness component and the non-deterministic surface roughness component corresponding to the contour, the elastic recovery, the plastic side flow and the like of the cutting edge of the cutter are integrated, and the turning surface roughness is accurately predicted. The predicted absolute error of a fine-grain metal material can be controlled within 3nm.

Description

technical field [0001] The invention relates to a roughness prediction method, in particular to a turning surface roughness prediction method. Background technique [0002] Roughness is a key parameter to characterize the quality of turning surface processing, and it is closely related to the service performance of the workpiece. The current prediction method of turning surface roughness does not consider the micro-defects of the cutting edge of the tool, and the prediction method has certain accuracy when the processing parameters are large. However, with the widespread application of micro-machining methods represented by precision / ultra-precision turning technology, the defects of the above prediction methods are becoming more and more obvious, which are manifested in the following aspects: [0003] 1. Under the condition of small cutting parameters, the effect of tool profile copying on surface roughness is gradually enhanced. Specifically, due to the limitation of the...

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Problems solved by technology

[0004] 2. In addition to the copying effect of the tool profile, there are also elastic recovery and plastic side flow of the workpiece material during the cutting process, in which the value of the elastic recovery of the material does not change much with the decrease of the feed per revolution, while the plastic side flow The phenomenon increases significantly with the decrease of the feed per revolution. The existing prediction method does not consider the influence of the elastic recovery and plastic side flow of the material, resulting in a significant increase in the prediction error with the reduction of the cutting parameters.

[0005] 3. When processing polycrystalline metal materials, material defects such as grain boundaries inside the material will also affect the surface roughness, and the current surface roughness prediction method lacks consideration of material defects

[0006] Due to the existence of the above problems, the prediction error of the existing prediction methods increases significantly when predicting the surface roughness of precision / ultra-precision turning, and the change trend of the surface roughness cannot be accurately obtained.

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