融合机床精度与工艺参数的铣削误差预测模型

doi:10.7527/S1000-6893.2018.21713

Abstract

Abstract: To overcome the deficiency of machining accuracy evaluation system of five-axis NC milling machine in processing aircraft structural parts, an evaluation system is constructed using machine tool precision detection data, characteristics structural parts and their machining parameters. Based on the BP neural network, a prediction model for machining errors of five-axis NC milling machine is built up. The influence of each input index on the evaluation result is calculated through weight distribution of the trained network, and effectiveness of the model is verified by an example. It is shown that the results obtained by the BP neural network model are in good agreements with those by the coordinate measuring machine, demonstrating the effectiveness of those selected evaluation indexes. The prediction model can effectively evaluate the processing accuracy of the five-axis NC milling machine by combining the machine tool precision detection data, characteristics of the parts and process parameters.

Key words: CNC milling machine, aircraft structural part, prediction of machining error, BP neural network, process parameter

CLC Number:

V261.2

XIONG Qingchun, WANG Jiaxu, ZHOU Qinghua. Prediction model of machining errors based on precision and process parameters of machine tools[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2018, 39(8): 421713-421713.

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Prediction model of machining errors based on precision and process parameters of machine tools

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