Challenges and opportunities of AI-enabled monitoring, diagnosis & prognosis: A review

Z Zhao, J Wu, T Li, C Sun, R Yan, X Chen - Chinese Journal of Mechanical …, 2021 - Springer
Abstract Prognostics and Health Management (PHM), including monitoring, diagnosis,
prognosis, and health management, occupies an increasingly important position in reducing …

Internet of ships: A survey on architectures, emerging applications, and challenges

S Aslam, MP Michaelides… - IEEE Internet of Things …, 2020 - ieeexplore.ieee.org
The recent emergence of Internet-of-Things (IoT) technologies in mission-critical
applications in the maritime industry has led to the introduction of the Internet-of-Ships (IoS) …

Fusing physics-based and deep learning models for prognostics

MA Chao, C Kulkarni, K Goebel, O Fink - Reliability Engineering & System …, 2022 - Elsevier
Physics-based and data-driven models for remaining useful lifetime (RUL) prediction
typically suffer from two major challenges that limit their applicability to complex real-world …

A review on deep learning applications in prognostics and health management

L Zhang, J Lin, B Liu, Z Zhang, X Yan, M Wei - Ieee Access, 2019 - ieeexplore.ieee.org
Deep learning has attracted intense interest in Prognostics and Health Management (PHM),
because of its enormous representing power, automated feature learning capability and best …

Abnormality detection and failure prediction using explainable Bayesian deep learning: Methodology and case study with industrial data

AKM Nor, SR Pedapati, M Muhammad, V Leiva - Mathematics, 2022 - mdpi.com
Mistrust, amplified by numerous artificial intelligence (AI) related incidents, is an issue that
has caused the energy and industrial sectors to be amongst the slowest adopter of AI …

A review of deep learning based anomaly detection strategies in Industry 4.0 focused on application fields, sensing equipment and algorithms

A Liso, A Cardellicchio, C Patruno, M Nitti… - IEEE …, 2024 - ieeexplore.ieee.org
Anomaly detection is a topic of interest in several areas, ranging from Industry 4.0 to Energy
Management, Smart Agriculture, Cybersecurity, and Bioinformatics. In a wide sense …

Lightweight bidirectional long short-term memory based on automated model pruning with application to bearing remaining useful life prediction

J Sun, X Zhang, J Wang - Engineering Applications of Artificial Intelligence, 2023 - Elsevier
Rolling bearings are key components in industrial machinery, and their remaining useful life
(RUL) prediction plays a prominent part in machine safety and maintenance. Bidirectional …

Fault prognostics using LSTM networks: application to marine diesel engine

P Han, AL Ellefsen, G Li, V Æsøy… - IEEE Sensors …, 2021 - ieeexplore.ieee.org
Maintenance is the key to ensuring the safe and efficient operation of marine vessels.
Currently, reactive maintenance and preventive maintenance are two main approaches …

Remaining Useful Life Estimation of Turbofan Engines with Deep Learning Using Change-Point Detection Based Labeling and Feature Engineering

K Ensarioğlu, T İnkaya, E Emel - Applied Sciences, 2023 - mdpi.com
Accurate remaining useful life (RUL) prediction is one of the most challenging problems in
the prognostics of turbofan engines. Recently, RUL prediction methods for turbofan engines …

Data-Driven Models Applied to Predictive and Prescriptive Maintenance of Wind Turbine: A Systematic Review of Approaches Based on Failure Detection, Diagnosis …

RAF Santiago, NB Barbosa, HG Mergulhão… - Energies, 2024 - mdpi.com
Wind energy has achieved a leading position among renewable energies. The global
installed capacity in 2022 was 906 GW of power, with a growth of 8.4% compared to the …