Machine tool processing energy efficiency modeling system and method based on support vector regression and t test

Abstract

The invention discloses a machine tool machining energy efficiency modeling system and method based on support vector regression and t inspection, and the system comprises a machine tool machining energy efficiency data collection and preprocessing module which achieves the obtaining of machine tool machining energy efficiency data, the construction of machine tool machining energy efficiency modeling feature vectors, and the normalization processing of energy efficiency impact factor data; the machine tool machining energy efficiency model building module is used for completing machine tool machining energy efficiency index definition and realizing machine tool machining energy efficiency model training and pre-detection; and the machine tool processing energy efficiency model accuracy evaluation module realizes machine tool processing energy efficiency model accuracy judgment and model retraining so as to achieve the purpose of updating the model. According to the method, the universality of the machine tool energy efficiency modeling method for different types and models of machine tools can be improved, and the prediction accuracy of the model for the machining energy efficiency of the machine tool is improved.

Description

technical field [0001] The invention belongs to the fields of electronic engineering and computer science, and in particular relates to a machine tool processing energy efficiency modeling system and method based on support vector regression and t test. Background technique [0002] Today, when global environmental problems are prominent and energy costs are increasing, energy efficiency modeling of machine tool processing has become one of the key technologies in the field of machine tool processing, and has been widely studied by scholars, enterprises and institutions at home and abroad. With the deepening of research, the energy efficiency model of machine tool processing has been gradually improved. The current energy efficiency model of machine tool machining takes depth of cut, width of cut, cutting speed and feed rate as the influencing factors of machine tool machining energy efficiency, and uses physical experimental data combined with mathematical empirical formula...

AI Technical Summary

Problems solved by technology

However, since mathematical empirical formulas cannot accurately describe the differences in energy efficiency of machine tools of different types, models, and states, how to improve the generality of the energy efficiency modeling method for machine tool machining to different types and models of machine tools, and how to solve the problems caused by tool wear and machine tool aging The reduction in the prediction accuracy of the model for the energy efficiency of machine tool machining caused by such factors is a problem that needs to be solved at present

In view of the lack of versatility of the modeling method, at present, it is mainly based on the energy efficiency characteristics of different types and models of machine tools to adjust empirical formulas and modify relevant parameters, but this method requires high professional knowledge

Aiming at the problem that the energy efficiency model of machine tool processing cannot change dynamically according to the state of the machine tool, tool wear parameters are mainly introduced as new factors affecting energy efficiency of machine tool processing to improve the accuracy of the energy efficiency model of machine tool processing, but the acquisition of tool wear parameters has become a difficulty in implementing this method

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