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Date of Publication:2022-10-10

Journal:大连理工大学学报

Affiliation of Author(s):机械工程学院

Issue:6

Page Number:814-818

ISSN No.:1000-8608

Abstract:To predict and control cutting force effectively is very important for machining process to achieve high quality and low cost. Based on the feed-forward multi-layer neural networks, trained by the error back-propagation (BP) algorithm, the predicting cutting force program by using oriented-object language Visual C++ has been built up. In order to make calculating fast and accurate, two methods of optimization, the conjugated gradient and Quasi-Newton, have been applied to the training process of the network to avoid the main problems of supersaturation and local minimum. The experimental data of milling and grinding of two kinds of materials which are difficult to machine have been applied to the program. The results indicate that the maximum relative errors obtained by the traditional empirical formula method and the artificial neural network method are 24.9% and 2.01% respectively. The approach to the prediction of cutting force with the help of artificial neural network is valuable for application.

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