Numerical control machine tool multi-working-condition cutting parameter optimization method based on multilayer perceptron

Abstract

The invention relates to a numerical control machine tool multi-working-condition cutting parameter optimization method based on a multilayer perceptron, and belongs to the field of numerical control machine tool intelligent manufacturing equipment. The invention provides a multi-working-condition cutting parameter optimization method of a numerical control machine tool based on a multi-layer perceptron, aiming at solving the problem of uncertainty of machine tool coordinates and cutter parameters of the numerical control machine tool, which can cause strong flutter of the numerical control machine tool in a cutting process. The method comprises the steps that firstly, a tool nose frequency response function curve based on different main shaft coordinates, tool diameters and overhanging lengths needs to be obtained under a hammering modal experiment, and a milling stability lobe graph is drawn by combining a modal theoretical formula and milling chatter stability mathematical model analysis; according to a cutting chatter stability prediction method, constructing a limit cutting depth MLP prediction model taking the displacement of a moving part in each direction, the diameter of a cutter, the overhanging length, the rotating speed of a main shaft, the cutting width and the feeding amount of each tooth as input; the regression prediction model is adopted as a cutting stability constraint to establish a multi-objective optimization model of the material removal rate and the cutter life, and optimal machining parameter configuration is solved through a non-dominated sorting NSGAII algorithm with an elitist strategy. And example research and analysis are carried out by one machining center, so that the obtained optimal configuration can meet stable cutting of the machine tool, and the reliability and the effectiveness of the method are verified.

Description

technical field [0001] The invention belongs to the field of intelligent manufacturing of numerical control machine tools, and relates to a multi-layer perceptron-based cutting parameter optimization method for multi-working conditions of numerical control machine tools. Background technique [0002] The chatter problem in the high-speed milling process is an important factor affecting the machining efficiency and machining accuracy of CNC machine tools. According to its cause, it is usually divided into free vibration, forced vibration and self-excited vibration (ie chatter). Among them, the self-excited vibration is the vibration maintained by the vibration system by the excitation generated by itself. During the milling process, the strong self-excited vibration between the tool and the workpiece will drastically deteriorate the surface quality and dimensional accuracy of the workpiece, and reduce the service life of the tool and CNC machine tools. It is a key factor that...

AI Technical Summary

Problems solved by technology

This phenomenon often results in misalignment between the machined part and the machine tool, whi

Images