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Tool Wear Predicting Based on Multisensory Raw Signals Fusion by Reshaped Time Series Convolutional Neural Network in Manufacturing

机译：基于多师原始信号融合的刀具磨损预测由Reshaped Time Seriete系列卷积神经网络制造业

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Zhiwen Huang; Jianmin Zhu; Jingtao Lei; Xiaoru Li; Fengqing Tian;
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1. Tool wear predicting based on multi-domain feature fusion by deep convolutional neural network in milling operations [J] . Huang Zhiwen, Zhu Jianmin, Lei Jingtao, Journal of Intelligent Manufacturing . 2020,第4期

机译：基于多域特征融合的刀具磨损预测铣削操作中深卷积神经网络
2. 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
3. A multi-sensor fusion model based on artificial neural network to predict tool wear during hard turning [J] . P. Sam Paul, A. S. Varadarajan Proceedings of the Institution of Mechanical Engineers, Part B. Journal of engineering manufacture . 2012,第5期

机译：基于人工神经网络的多传感器融合模型预测硬车削刀具磨损
4. Neural network based fusion of global and local information in predicting time series [C] . Shun-Feng Su, Sou-Horng Li . 2003

机译：基于神经网络的全局和局部信息融合预测时间序列
5. On-line tool wear estimation in turning through sensor data fusion and neural networks. [D] . Kamarthi, Sagar Vidya. 1994

机译：通过传感器数据融合和神经网络进行在线工具磨损估计。
6. Time Series Multiple Channel Convolutional Neural Network with Attention-Based Long Short-Term Memory for Predicting Bearing Remaining Useful Life [O] . Jehn-Ruey Jiang, Juei-En Lee, Yi-Ming Zeng 2020

机译：时间序列多通道卷积神经网络具有基于注意力的长短期记忆可预测轴承剩余使用寿命
7. Time Series Multiple Channel Convolutional Neural Network with Attention-Based Long Short-Term Memory for Predicting Bearing Remaining Useful Life [O] . Jehn-Ruey Jiang, Juei-En Lee, Yi-Ming Zeng 2019

机译：时间序列多通道卷积神经网络，具有基于关注的长短期记忆，用于预测轴承剩余的使用寿命

Tool Wear Predicting Based on Multisensory Raw Signals Fusion by Reshaped Time Series Convolutional Neural Network in Manufacturing

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