A hobbing dry cutting processing method based on analysis and optimization of small sample multivariate process parameters

Abstract

The invention discloses a hobbing dry cutting processing method based on the analysis and optimization of small sample multivariate process parameters, which is characterized in that the analysis and optimization of the hobbing dry cutting process parameters in the case of small samples is carried out according to the following steps, and the specific steps are: (1) Realize the standardization of the hobbing dry cutting process parameter sample set; (2) Realize the generation of the optimization kernel of the hobbing dry cutting input parameter attributes; (3) Realize the hobbing dry cutting process parameter support vector regression estimation. The invention has the advantages that: aiming at the characteristics of small samples of gear hobbing dry cutting process parameters, the regression estimation of process parameters is carried out by using a support vector machine, and the method has simple operation and fast convergence speed.

Description

Technical field [0001] The invention relates to a gear dry cutting processing technology, in particular to a processing method for optimizing multiple process parameters in the case of a small sample. Background technique [0002] In the actual dry cutting of gear hobbing, since the cutting speed can reach more than twice that of general hobbing, the hob will have a special coating, and the tool life will be greatly improved. These all propose new parameters for the dry cutting of gear hobbing. Currently, domestic companies lack a library of optimized process parameters, and some even do not. They only rely on the experience of workers or process personnel to make decisions. This poses huge challenges to the processing quality, processing time, and processing costs of dry cutting. [0003] The domestic is still in the new stage of gear hobbing dry cutting machine tool manufacturing, and there are few researches on the optimization of process parameters in the process of gear hobbin...

AI Technical Summary

Problems solved by technology

[0002] In the actual hobbing dry cutting process, because its cutting speed can reach more than twice that of general hobbing, the hob will have a special coating, and the tool life will be greatly improved. However, at present, domestic enterprises lack optimized process parameter databases, some even do not, and only rely on the experience of workers or craftsmen to make decisions, which poses a huge challenge to the processing quality, processing time, and processing cost of hobbing dry cutting.

[0003] The country is still in the stage of seeking innovation in the manufacture of gear hobbing dry cutting machine tools, and there are few researches on the optimization of process parameters in the process of gear hobbing dry cutting. The existing processing methods for the optimization of process parameters in gear hobbing dry cutting are mainly experimental research and numerical simulation. , did not reach the stage of quantitative analysis

In addition, currently there are few samples that can be used as optimized process parameters, and the optimization method combining neural network and genetic algorithm, graph theory and case-based reasoning method, and differential evolution algorithm that can be used for general hobbing process parameter optimization are difficult to use, and the application effect Therefore, it is novel to apply the method of support vector machine to the optimization of hobbing dry cutting process parameters and guide the processing, and the current research in this area is lacking

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