Real-Time Prediction of Workpiece Errors for a CNC Turning Centre, Part 3. Cutting Force Estimation Using Current Sensors

2001 ◽  
Vol 17 (9) ◽  
pp. 659-664 ◽  
Author(s):  
X. Li
2012 ◽  
Vol 6 (5) ◽  
pp. 669-674 ◽  
Author(s):  
Kazuto Enomoto ◽  
◽  
Masaya Takei ◽  
Yasuhiro Kakinuma

The automation of machining processes requires highly accurate process monitoring. However, the use of additional sensors leads to a significant increase in the cost and reduces the stiffness and reliability of mechanical systems. Hence, we propose a system called the cutting force observer, which uses a sensor-less and real-time cutting force estimation methodology based on the disturbance observer theory. Monitoring methods using the cutting force observer may enhance the productivity during turning. One of the parameters that significantly affect the cutting process is the shear angle. The determination of the shear angle is very important as it can be used for identifying the machining conditions. In this study, an external sensor-less monitoring system of the shear angle during turning is developed, and its performance is evaluated.


2019 ◽  
Author(s):  
D Dall Alba ◽  
◽  
E Tagliabue ◽  
E Magnabosco ◽  
C Tenga ◽  
...  

2012 ◽  
Author(s):  
J. D. Doyle ◽  
R. M. Hodur ◽  
S. Chen ◽  
H. Jin ◽  
Y. Jin ◽  
...  

2021 ◽  
Author(s):  
Yanfei Guan ◽  
S. V. Shree Sowndarya ◽  
Liliana C. Gallegos ◽  
Peter C. St. John ◽  
Robert S. Paton

From quantum chemical and experimental NMR data, a 3D graph neural network, CASCADE, has been developed to predict carbon and proton chemical shifts. Stereoisomers and conformers of organic molecules can be correctly distinguished.


ACS Omega ◽  
2020 ◽  
Author(s):  
Ahmed Alsaihati ◽  
Salaheldin Elkatatny ◽  
Abdulazeez Abdulraheem

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