[HTML][HTML] Industry 4.0 smart reconfigurable manufacturing machines

J Morgan, M Halton, Y Qiao, JG Breslin - Journal of Manufacturing Systems, 2021 - Elsevier
This paper provides a fundamental research review of Reconfigurable Manufacturing
Systems (RMS), which uniquely explores the state-of-the-art in distributed and decentralized …

An overview on fault diagnosis, prognosis and resilient control for wind turbine systems

Z Gao, X Liu - Processes, 2021 - mdpi.com
Wind energy is contributing to more and more portions in the world energy market. However,
one deterrent to even greater investment in wind energy is the considerable failure rate of …

Prognostics and Health Management (PHM): Where are we and where do we (need to) go in theory and practice

E Zio - Reliability Engineering & System Safety, 2022 - Elsevier
We are performing the digital transition of industry, living the 4th industrial revolution,
building a new World in which the digital, physical and human dimensions are interrelated in …

Vibration based condition monitoring and fault diagnosis of wind turbine planetary gearbox: A review

T Wang, Q Han, F Chu, Z Feng - Mechanical Systems and Signal …, 2019 - Elsevier
As one of the most immensely growing renewable energies, the wind power industry also
experiences a high failure rate and operation & maintenance cost. Therefore, the condition …

A comprehensive review on signal-based and model-based condition monitoring of wind turbines: Fault diagnosis and lifetime prognosis

H Badihi, Y Zhang, B Jiang, P Pillay… - Proceedings of the …, 2022 - ieeexplore.ieee.org
Wind turbines play an increasingly important role in renewable power generation. To ensure
the efficient production and financial viability of wind power, it is crucial to maintain wind …

Anomaly detection and critical SCADA parameters identification for wind turbines based on LSTM-AE neural network

H Chen, H Liu, X Chu, Q Liu, D Xue - Renewable Energy, 2021 - Elsevier
Continuous monitoring of wind turbine health conditions using anomaly detection methods
can improve the reliability and reduce maintenance costs during operation of wind turbine …

Towards machine-learning driven prognostics and health management of Li-ion batteries. A comprehensive review

S Khaleghi, MS Hosen, J Van Mierlo… - … and Sustainable Energy …, 2024 - Elsevier
Prognostics and health management (PHM) has emerged as a vital research discipline for
optimizing the maintenance of operating systems by detecting health degradation and …

Challenges and opportunities of deep learning models for machinery fault detection and diagnosis: A review

SR Saufi, ZAB Ahmad, MS Leong, MH Lim - Ieee Access, 2019 - ieeexplore.ieee.org
In the age of industry 4.0, deep learning has attracted increasing interest for various
research applications. In recent years, deep learning models have been extensively …

Vibration-based intelligent fault diagnosis for roller bearings in low-speed rotating machinery

L Song, H Wang, P Chen - IEEE Transactions on …, 2018 - ieeexplore.ieee.org
This paper proposes a new signal feature extraction and fault diagnosis method for fault
diagnosis of low-speed machinery. Statistic filter (SF) and wavelet package transform (WPT) …

Input-based event-triggering consensus of multiagent systems under denial-of-service attacks

Y Xu, M Fang, ZG Wu, YJ Pan… - IEEE Transactions on …, 2018 - ieeexplore.ieee.org
This paper applies an input-based triggering approach to investigate the secure consensus
problem in multiagent systems under denial-of-service (DoS) attacks. The DoS attacks are …