Nonstationary signal analysis is one of the main topics in the field of machinery fault
diagnosis. Time–frequency analysis can identify the signal frequency components, reveals …

This paper reviews the state-of-the-art of wavelet analysis for tool condition monitoring
(TCM). Wavelet analysis has been the most important non-stationary signal processing tool …

The protection, consistency and effectiveness of rotating machinery are of a key
apprehension in industries. Condition monitoring of a machines helps to retain the …

This study presents a new intelligent diagnosis system for classification of different machine
conditions using data obtained from infrared thermography. In the first stage of this proposed …

This paper addresses the detection of periodic transients in vibration signals so as to detect
faults in rotating machines. For this purpose, we present a method to estimate periodic …

Fault diagnosis of rotating machinery is receiving more and more attentions. Vibration
signals of rotating machinery are commonly analyzed to extract features of faults, and the …

In this study, a novel fault diagnosis system for rotating machinery using thermal imaging is
proposed. This system consists of bi-dimensional empirical mode decomposition (BEMD) for …

Improvement of recognition rate is ultimate aim for fault diagnosis researchers using pattern
recognition techniques. However, the unique recognition method can only recognise a …

Fuzzy measure and fuzzy integral theory are an outgrowth of classical measure theory.
Fuzzy measure and fuzzy integral theory take into account the importance of criteria and …

Local mean decomposition (LMD) is a new self-adaptive time–frequency analysis method,
which is particularly suitable for the processing of multi-component amplitude-modulated …