Construction of health indicators for condition monitoring of rotating machinery: A review of the research
The condition monitoring (CM) of rotating machinery (RM) is an essential operation for
improving the reliability of mechanical systems. For this purpose, an efficient CM method that …
improving the reliability of mechanical systems. For this purpose, an efficient CM method that …
Deep learning models for predictive maintenance: a survey, comparison, challenges and prospects
Given the growing amount of industrial data in the 4th industrial revolution, deep learning
solutions have become popular for predictive maintenance (PdM) tasks, which involve …
solutions have become popular for predictive maintenance (PdM) tasks, which involve …
Incremental learning for remaining useful life prediction via temporal cascade broad learning system with newly acquired data
Deep neural networks have promoted the technology development of fault classification and
remaining useful life (RUL) prediction for mechanical equipment due to their powerful …
remaining useful life (RUL) prediction for mechanical equipment due to their powerful …
Intelligent framework for degradation monitoring, defect identification and estimation of remaining useful life (RUL) of bearing
The proposed intelligent framework seamlessly integrates degradation monitoring, defect
identification, and remaining useful life (RUL) estimation for a comprehensive and holistic …
identification, and remaining useful life (RUL) estimation for a comprehensive and holistic …
Condition monitoring and fault detection in roller bearing used in rolling mill by acoustic emission and vibration analysis
NW Nirwan, HB Ramani - Materials Today: Proceedings, 2022 - Elsevier
Bearings for rolling elements are essential components of rotating devices and bearing
failure can lead to machine failure. As a result, early identification of such defects, as well as …
failure can lead to machine failure. As a result, early identification of such defects, as well as …
MPNet: A lightweight fault diagnosis network for rotating machinery
Y Liu, Y Chen, X Li, X Zhou, D Wu - Measurement, 2025 - Elsevier
Rotating machinery is prone to faults, especially bearing faults. Existing machinery fault
diagnosis methods suffer from low accuracy and poor robustness under actual complex …
diagnosis methods suffer from low accuracy and poor robustness under actual complex …
Ensemble empirical mode decomposition energy moment entropy and enhanced long short-term memory for early fault prediction of bearing
Z Gao, Y Liu, Q Wang, J Wang, Y Luo - Measurement, 2022 - Elsevier
Bearings are the core components of rotating machinery and are vulnerable to failure. Early
fault prediction is a significant and challenging task for bearing due to the weakness of fault …
fault prediction is a significant and challenging task for bearing due to the weakness of fault …
An adaptive group sparse feature decomposition method in frequency domain for rolling bearing fault diagnosis
Group-sparse mode decomposition (GSMD) is a decomposition method designed based on
the group sparse property of signals in frequency domain. It is proved to be highly efficient …
the group sparse property of signals in frequency domain. It is proved to be highly efficient …
[HTML][HTML] A review of the intelligent condition monitoring of rolling element bearings
V Kannan, T Zhang, H Li - Machines, 2024 - mdpi.com
Bearing component damage contributes significantly to rotating machinery failures. It is vital
for the rotor-bearing system to be in good condition to ensure the proper functioning of the …
for the rotor-bearing system to be in good condition to ensure the proper functioning of the …
Hybrid system response model for condition monitoring of bearings under time-varying operating conditions
Condition monitoring (CM) plays a vital role in machine maintenance for ensuring the
system's operating reliability and safety as fault detection and health degradation …
system's operating reliability and safety as fault detection and health degradation …