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ENN-based recognition method for tool cutting state

机译:基于ENN的刀具切削状态识别方法

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摘要

In order to accurately and quickly identify the tool cutting state, a new recognition method based on extension neural network (ENN) is proposed in this paper. The related theories, the structure design of ENN and the recognition algorithm are discussed in detail. To demonstrate the effectiveness of the proposed method, a real-world engineering application is tested. Some comparative experiments with traditional ANN-based methods are conducted. The experimental results show that the proposed ENN-based recognition method can identify the state of cutting tool accurately with shorter learning time and simpler structure. The experimental results also confirm that the proposed method has a better performance in recognition accuracy, generalization ability and fault-tolerant ability.
机译:为了准确,快速地识别出刀具的切削状态,提出了一种基于扩展神经网络的新识别方法。详细讨论了相关理论,ENN的结构设计和识别算法。为了证明所提出方法的有效性,测试了一个实际的工程应用程序。使用传统的基于ANN的方法进行了一些比较实验。实验结果表明,基于ENN的识别方法能够准确识别刀具状态,学习时间短,结构简单。实验结果也证明了该方法在识别精度,泛化能力和容错能力方面具有较好的性能。

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