Prognostics and health management design for rotary machinery systems—Reviews, methodology and applications
Much research has been conducted in prognostics and health management (PHM), an
emerging field in mechanical engineering that is gaining interest from both academia and …
emerging field in mechanical engineering that is gaining interest from both academia and …
A review on empirical mode decomposition in fault diagnosis of rotating machinery
Rotating machinery covers a broad range of mechanical equipment and plays a significant
role in industrial applications. It generally operates under tough working environment and is …
role in industrial applications. It generally operates under tough working environment and is …
Fault diagnosis of rotary machinery components using a stacked denoising autoencoder-based health state identification
C Lu, ZY Wang, WL Qin, J Ma - Signal Processing, 2017 - Elsevier
Effective fault diagnosis has long been a research topic in the prognosis and health
management of rotary machinery engineered systems due to the benefits such as safety …
management of rotary machinery engineered systems due to the benefits such as safety …
Intelligent fault diagnosis of rolling bearing using hierarchical convolutional network based health state classification
C Lu, Z Wang, B Zhou - Advanced Engineering Informatics, 2017 - Elsevier
Rolling bearing tips are often the most susceptible to electro-mechanical system failure due
to high-speed and complex working conditions, and recent studies on diagnosing bearing …
to high-speed and complex working conditions, and recent studies on diagnosing bearing …
Recent advances in time–frequency analysis methods for machinery fault diagnosis: A review with application examples
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 …
diagnosis. Time–frequency analysis can identify the signal frequency components, reveals …
Early fault diagnosis of rotating machinery based on wavelet packets—Empirical mode decomposition feature extraction and neural network
GF Bin, JJ Gao, XJ Li, BS Dhillon - Mechanical Systems and Signal …, 2012 - Elsevier
After analyzing the shortcomings of current feature extraction and fault diagnosis
technologies, a new approach based on wavelet packet decomposition (WPD) and …
technologies, a new approach based on wavelet packet decomposition (WPD) and …
The numerical modeling of rotor–stator rubbing in rotating machinery: a comprehensive review
The rotor–stator rubbing in rotating machinery generated as a consequence of rotor
imbalance, shaft misalignment, and casing deformation is a potential threat to the machinery …
imbalance, shaft misalignment, and casing deformation is a potential threat to the machinery …
Diagnostics of gear faults based on EMD and automatic selection of intrinsic mode functions
R Ricci, P Pennacchi - Mechanical Systems and Signal Processing, 2011 - Elsevier
Signal processing is an important tool for diagnostics of mechanical systems. Many different
techniques are available to process experimental signals, among others: FFT, wavelet …
techniques are available to process experimental signals, among others: FFT, wavelet …
Fault diagnosis for rotating machinery: A method based on image processing
Rotating machinery is one of the most typical types of mechanical equipment and plays a
significant role in industrial applications. Condition monitoring and fault diagnosis of rotating …
significant role in industrial applications. Condition monitoring and fault diagnosis of rotating …
Fault diagnosis for rotary machinery with selective ensemble neural networks
ZY Wang, C Lu, B Zhou - Mechanical Systems and Signal Processing, 2018 - Elsevier
The diagnosis of rotary machinery systems is gaining interest both in academic and industry
fields, which assures machinery operational safety and reliability in terms of typical rotary …
fields, which assures machinery operational safety and reliability in terms of typical rotary …