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Study of synthesis identification in the cutting process with a fuzzy neural network

机译:基于模糊神经网络的切削过程综合识别研究

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摘要

With the development of intelligent manufacturing systems, the requirements of the stability and reliability are increasingly more important, especially in the NC cutting process. The method of traditional and single working condition monitoring cannot be fully satisfied. In this paper, an artificial neural network with fuzzy logic, signal processing and other techniques is composed, and a method of synthesis identification and diagnosis of the working condition with a model of a compound fuzzy inference neural network has been tested and has yielded good result, so that the stability and reliability of on-line monitoring and diagnosis is rationally expected to be realized.
机译:随着智能制造系统的发展,对稳定性和可靠性的要求越来越重要,尤其是在数控切割过程中。传统和单一工作状态监视的方法不能完全满足。本文构建了一种具有模糊逻辑,信号处理等技术的人工神经网络,并通过复合模糊推理神经网络模型对工作状态进行综合识别与诊断,取得了良好的效果。因此,可以合理地期望实现在线监测和诊断的稳定性和可靠性。

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