双电极同步伺服放电加工工艺效果建模研究
首发时间:2008-01-02
摘要:针对非导电工程陶瓷双电极同步伺服放电加工工艺参数与加工效果间的高度非线性,传统神经网络方法收敛速度慢,易陷入局部最优解等缺陷,提出了一种既能充分利用神经网络的自学习能力,又能利用小波良好的时频局部化特性的非导电工程陶瓷双电极同步伺服放电加工的小波神经网络方法,建立了其加工效果的预测模型,同时与传统的神经网络方法建立的模型进行了比较。经过与实验数据的对比,认为这两种模型均能较准确的预测出给定加工条件下的材料去除率和表明粗糙度,均能反映机床的加工工艺规律,但利用小波网络方法建立的模型较神经网络模型具有更快的收敛速度和更高的预测精度。
关键词: 非导电工程陶瓷 双电极同步伺服 放电加工 小波网络
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Study on Modeling of Electrical Discharge Machining Process with synchronous servo double electrodes
Abstract:A model of wavelet neutral network which can make full use of part characteristic of wavelet time-frequent and the ability of self-study of neutral network is presented to predict the process of electrical discharge machining with synchronous servo double electrodes for non-conductive engineering ceramics as a neutral network has the limitations of slow convergence and local optimums due to the high nonlinear features and complexity of electrical discharge machining for non-conductive engineering ceramics. Experiments were carried out to verify the validity of the wavelet neutral network model and neutral network model. Results show that both models provide accurate results, and the wavelet neural network model fits the experiments result better.
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No.1766018188811992****
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