Tool condition monitoring for high-performance machining systems—A review

A Mohamed, M Hassan, R M'Saoubi, H Attia - Sensors, 2022 - mdpi.com
In the era of the “Industry 4.0” revolution, self-adjusting and unmanned machining systems
have gained considerable interest in high-value manufacturing industries to cope with the …

Chatter in machining processes: A review

G Quintana, J Ciurana - International Journal of Machine Tools and …, 2011 - Elsevier
Chatter is a self-excited vibration that can occur during machining operations and become a
common limitation to productivity and part quality. For this reason, it has been a topic of …

Modelling and monitoring of abrasive finishing processes using artificial intelligence techniques: A review

V Pandiyan, S Shevchik, K Wasmer, S Castagne… - Journal of Manufacturing …, 2020 - Elsevier
Abrasive finishing processes such as grinding, lapping or disc polishing are one of the most
practical means for processing materials to manufacture products with fine surface finish …

Recent developments in grinding machines

K Wegener, F Bleicher, P Krajnik, HW Hoffmeister… - CIRP Annals, 2017 - Elsevier
Grinding is often the final step in the process/manufacturing chain, meaning that no
subsequent post-grinding correction of the surface and geometry is performed. This imposes …

An intelligent system for grinding wheel condition monitoring based on machining sound and deep learning

CH Lee, JS Jwo, HY Hsieh, CS Lin - IEEE Access, 2020 - ieeexplore.ieee.org
Immediate monitoring of the conditions of the grinding wheel during the grinding process is
important because it directly affects the surface accuracy of the workpiece. Because the …

A robust condition monitoring methodology for grinding wheel wear identification using Hilbert Huang transform

S Mahata, P Shakya, NR Babu - Precision Engineering, 2021 - Elsevier
Grinding is a finishing operation performed to obtain the desired finish on the component.
Wheel wear is one of the primary constraints in achieving the desired productivity in …

Sparse multiple kernel learning for signal processing applications

N Subrahmanya, YC Shin - IEEE Transactions on Pattern …, 2009 - ieeexplore.ieee.org
In many signal processing applications, grouping of features during model development and
the selection of a small number of relevant groups can be useful to improve the …

Application of Hilbert–Huang transform to acoustic emission signal for burn feature extraction in surface grinding process

Z Yang, Z Yu, C Xie, Y Huang - Measurement, 2014 - Elsevier
This paper presents a sensor system using motor current sensors, voltage sensors,
accelerator and acoustic emission sensor for grinding burn feature extraction. The new …

Monitoring tool wear using classifier fusion

E Kannatey-Asibu, J Yum, TH Kim - Mechanical Systems and Signal …, 2017 - Elsevier
Real time monitoring of manufacturing processes using a single sensor often poses
significant challenge. Sensor fusion has thus been extensively investigated in recent years …

Grinding wheel wear monitoring based on wavelet analysis and support vector machine

Z Yang, Z Yu - The International Journal of Advanced Manufacturing …, 2012 - Springer
A novel grinding wheel wear monitoring system based on discrete wavelet decomposition
and support vector machine is proposed. The grinding signals are collected by an acoustic …