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Enhancing Spindle Power Data Application with Neural Network for Real-time Tool Wear/Breakage Prediction During Inconel Drilling

机译：通过神经网络增强主轴功率数据应用，以进行因科镍合金钻探期间的刀具磨损/破损实时预测

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Corne Raphael; Nath Chandra; Mansori Mohamed El; Kurfess Thomas;
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1. Enhancing Spindle Power Data Application with Neural Network for Real-time Tool Wear/Breakage Prediction During Inconel Drilling [J] . Raphael Corne, Chandra Nath, Mohamed El Mansori, Procedia Manufacturing . 2016,第3期

机译：通过神经网络增强主轴功率数据应用，以进行因科镍合金钻探期间的刀具磨损/破损实时预测
2. Improvement of process reliability by prediction of tool breakage due to wear with the help of neural networks [J] . G. Wamecke, R. Kluge Werkstattstechnik . 1998,第1a2期

机译：通过神经网络预测磨损造成的刀具破损，从而提高过程可靠性
3. Artificial Neural Networks for Tool Wear Prediction Based on Sensor Fusion Monitoring of CFRP/CFRP Stack Drilling [J] . Alessandra Caggiano, Luigi Nele International journal of automation technology . 2018,第3期

机译：基于传感器融合监测CFRP / CFRP钻孔的刀具磨损预测的人工神经网络
4. Enhancing Spindle Power Data Application with Neural Network for Real-Time Tool Wear/Breakage Prediction during Inconel Drilling [C] . Raphael Corne, Chandra Nath, Mohamed El Mansori, North American Manufacturing Research Conferece . 2016

机译：用神经网络增强主轴电力数据应用，以期间钻孔期间的实时工具磨损/断开预测
5. An enhanced cutting force model and its application in tool breakage detection for end milling process using NURBS based neural-fuzzy system. [D] . Ahn, Ilyoung. 1999

机译：基于NURBS的神经模糊系统的增强切削力模型及其在立铣刀破损检测中的应用。
6. Prediction of Tool Wear Using Artificial Neural Networks during Turning of Hardened Steel [O] . Paweł Twardowski, Martyna Wiciak-Pikuła 2019

机译：硬化钢车削过程中使用人工神经网络预测刀具磨损
7. Prediction of tool wear in CFRP drilling based on neural network with multicharacteristics and multisignal sources [O] . Guoqiang Zhu, Shanshan Hu, Hongqun Tang 2021

机译：基于神经网络的CFRP钻探工具磨损预测兼体式兼容性源
8. Applications of neural networks to real-time data processing at the Environmental and Molecular Sciences Laboratory (EMSL). [R] . Keller, P. E., Kouzes, R. T., Kangas, L. J. 1993

机译：神经网络在环境与分子科学实验室（EmsL）的实时数据处理中的应用。

Enhancing Spindle Power Data Application with Neural Network for Real-time Tool Wear/Breakage Prediction During Inconel Drilling

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