Neural Network Based Tool Wear Monitoring in Face Milling

机译：铣削中基于神经网络的刀具磨损监控

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Neural networks are widely used for pattern classification tasks, as they do not require any knowledge of the underlying distribution or any other assumptions in order to estimate how outputs functionally depend on inputs. Their ability to learn through training algorithms and their generalization capability make them very effective for tool wear monitoring applications. This paper discusses the use of Radial basis function (RBF) neural networks for tool wear monitoring in face milling operations.

机译：神经网络被广泛用于模式分类任务，因为它们不需要任何有关基础分布的知识或任何其他假设即可估计输出在功能上如何取决于输入。它们具有通过训练算法学习的能力和综合能力，从而使其在刀具磨损监测应用中非常有效。本文讨论了径向基函数（RBF）神经网络在面铣操作中刀具磨损监控中的应用。

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来源
《International Conference on e-Manufacturing: An Emerging Need for 21st Century World Class Enterprises; 20021117-20021119; Bhopal; IN》|2002年|P.177-183|共7页
会议地点 Bhopal(IN)
作者
SRINIVASA PAL P.; T.N. NAGABHUSHANA; P.K. RAMAKRISHNA RAO;
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Dept. of Industrial Production Engg., NMAM Institute of Technology, Nitte-574 110;

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原文格式 PDF
正文语种 eng
中图分类生产行业管理;
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1. The monitoring of the turning tool wear process using an artificial neural network. Part 2: the data processing and the use of artificial neural network on monitoring of the tool wear [J] . G C Balan A Epureanu Proceedings of the Institution of Mechanical Engineers . 2008,第B10期

机译：使用人工神经网络监控车刀的磨损过程。第2部分：数据处理和人工神经网络在工具磨损监测中的使用
2. The monitoring of the turning tool wear process using an artificial neural network. Part 2: the data processing and the use of artificial neural network on monitoring of the tool wear [J] . G. C. Balan, A. Epureanu Proceedings of the Institution of Mechanical Engineers, Part B. Journal of engineering manufacture . 2008,第b10期

机译：使用人工神经网络监控车刀的磨损过程。第2部分：数据处理和人工神经网络在工具磨损监测中的使用
3. Tool Wear Monitoring with Vibration Signals Based on Short-Time Fourier Transform and Deep Convolutional Neural Network in Milling [J] . Zhiwen Huang, Jianmin Zhu, Jingtao Lei, Mathematical Problems in Engineering: Theory, Methods and Applications . 2021,第a期

机译：基于短时傅里叶变换和铣削深卷积神经网络的振动信号进行刀具磨损监测
4. Neural Network Based Tool Wear Monitoring in Face Milling [C] . SRINIVASA PAL P., T.N. NAGABHUSHANA, P.K. RAMAKRISHNA RAO International conference on e-Manufacturing: An emerging need for 21st century world class enterprises . 2002

机译：基于神经网络的刀具磨损监测
5. Intelligent tool condition monitoring in milling operations through neural networks. [D] . Sanchez Castillo, Manuel. 1997

机译：通过神经网络对铣削操作中的智能刀具状态进行监控。
6. Automatic Identification of Tool Wear Based on Convolutional Neural Network in Face Milling Process [O] . Xuefeng Wu, Yahui Liu, Xianliang Zhou, 2019

机译：基于卷积神经网络的端面铣削刀具磨损自动识别
7. Tool Wear Prediction Based on Artificial Neural Network during Aluminum Matrix Composite Milling [O] . Martyna Wiciak-Pikuła, Agata Felusiak-Czyryca, Paweł Twardowski 2020

机译：基于人工神经网络铝基复合材料研磨工具磨损预测
8. Tool Wear Estimation Using Neural Networks [R] . Stevenson, F., Greenwood, D. 1990

机译：基于神经网络的刀具磨损估计

Neural Network Based Tool Wear Monitoring in Face Milling

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