Rotating machinery faults can induce characteristic modulation effects in a vibration signal,
and their diagnosis can thus be conducted by extracting fault-induced modulation features …

Rotating machinery often works under time-varying speeds, and nonstationary conditions
and harsh environments make its key parts, such as rolling bearings and gears, prone to …

With the popularization of the intelligent manufacturing, much attention has been paid in
such intelligent computing methods as deep learning ones for machinery fault diagnosis …

In the recent years, deep learning-based intelligent fault diagnosis methods of rolling
bearings have been widely and successfully developed. However, the data-driven method …

Time-frequency (TF) analysis (TFA) method is an important tool in industrial engineering
fields. However, restricted to Heisenberg uncertainty principle or unexpected cross terms …

Fault diagnosis is an effective tool to guarantee safe operations in gearboxes. Acoustic and
vibratory measurements in such mechanical devices are all sensitive to the existence of …

Gearbox fault detection commonly relies on comparing sideband frequencies beside the
meshing frequency of gear, and its harmonics of higher orders in frequency domain between …

Health condition monitoring for rotating machinery has been developed for many years due
to its potential to reduce the cost of the maintenance operations and increase availability …

Synchrosqueezing transform (SST) is an effective post-processing time-frequency analysis
(TFA) method in mechanical signal processing. It improves the concentration of the time …

This second edition of The Illustrated Wavelet Transform Handbook: Introductory Theory and
Applications in Science, Engineering, Medicine and Finance has been fully updated and …