Tool condition monitoring (TCM) in machining operations is crucial to maximise the useful
tool life while reducing the risks associated with tool breakage. Unlike progressive tool wear …

Entropy is a powerful tool for the analysis of time series, as it allows describing the
probability distributions of the possible state of a system, and therefore the information …

This paper presents a novel hybrid model for fault detection and classification of motor
bearing. In the proposed model, permutation entropy (PE) of the vibration signal is …

CIRP has had a long history of research and publication on the development and
implementation of sensor monitoring of machining operations including tool condition …

In machining processes several phenomena occur during material cutting. These
phenomena can affect the production through the reduction of quality or accuracy, or by …

This paper investigates the usage of permutation entropy for working status characterization
of rotary machines. As a statistical measure, the permutation entropy describes complexity of …

Tool wear and breakage is one of the biggest obstacles for develo** the unattended CNC
machining. Especially when cutting the difficult-to-machining materials, the tool wear will be …

Tool breakage monitoring (TBM) during milling operations is crucial for ensuring workpiece
quality and minimizing economic losses. Under the premise of sufficient training data with a …

Bearing fault diagnosis has attracted significant attention over the past few decades. It
consists of two major parts: vibration signal feature extraction and condition classification for …

Rapid tool wear is a major concern of the machining operation, affecting the tooling cost and
dimensional tolerance of the components. In line with Industry 4.0, rapid tool failure can be …