[HTML][HTML] Remaining Useful Life prediction and challenges: A literature review on the use of Machine Learning Methods

C Ferreira, G Gonçalves - Journal of Manufacturing Systems, 2022 - Elsevier
Abstract Approaches such as Cyber-Physical Systems (CPS), Internet of Things (IoT),
Internet of Services (IoS), and Data Analytics have built a new paradigm called Industry 4.0 …

Deep learning techniques in intelligent fault diagnosis and prognosis for industrial systems: a review

S Qiu, X Cui, Z **, N Shan, Z Li, X Bao, X Xu - Sensors, 2023 - mdpi.com
Fault diagnosis and prognosis (FDP) tries to recognize and locate the faults from the
captured sensory data, and also predict their failures in advance, which can greatly help to …

Health status assessment and remaining useful life prediction of aero-engine based on BiGRU and MMoE

Y Zhang, Y **n, Z Liu, M Chi, G Ma - Reliability Engineering & System …, 2022 - Elsevier
Prognostics and health management (PHM) is a critical work to ensure the reliable operation
of industrial equipment, in which health status (HS) assessment and remaining useful life …

Multi-hop graph pooling adversarial network for cross-domain remaining useful life prediction: A distributed federated learning perspective

J Zhang, J Tian, P Yan, S Wu, H Luo, S Yin - Reliability Engineering & …, 2024 - Elsevier
Accurate remaining useful life (RUL) prediction has gained increasing attention in modern
maintenance management. Considering the data privacy requirements of distributed multi …

Remaining useful life prediction of roller bearings based on improved 1D-CNN and simple recurrent unit

D Yao, B Li, H Liu, J Yang, L Jia - Measurement, 2021 - Elsevier
To overcome the shortcomings of traditional roller bearing remaining useful life prediction
methods, which mainly focus on prediction accuracy improvement and ignore labor cost and …

A parallel GRU with dual-stage attention mechanism model integrating uncertainty quantification for probabilistic RUL prediction of wind turbine bearings

L Cao, H Zhang, Z Meng, X Wang - Reliability Engineering & System Safety, 2023 - Elsevier
The accurate probabilistic prediction of remaining useful life (RUL) of bearings plays an
important role in ensuring the safe operation of wind turbine maintenance decision making …

State of AI-based monitoring in smart manufacturing and introduction to focused section

H Ding, RX Gao, AJ Isaksson… - IEEE/ASME …, 2020 - ieeexplore.ieee.org
Over the past few decades, intelligentization, supported by artificial intelligence (AI)
technologies, has become an important trend for industrial manufacturing, accelerating the …

Data-driven bearing health management using a novel multi-scale fused feature and gated recurrent unit

Q Ni, JC Ji, K Feng, Y Zhang, D Lin, J Zheng - Reliability Engineering & …, 2024 - Elsevier
Remaining useful life (RUL) prediction plays a crucial role in bearing health management
which can guarantee the rotating machinery systems' safety and reliability. This paper …

A reliability evaluation model of rolling bearings based on WKN-BiGRU and Wiener process

L Dai, J Guo, JL Wan, J Wang, X Zan - Reliability Engineering & System …, 2022 - Elsevier
Reliability evaluation is highly significant for the safe and reliable service of rolling bearings.
It is to accurately reflect degradation states of rolling bearings. However, traditional methods …

Rolling bearing remaining useful life prediction based on dilated causal convolutional DenseNet and an exponential model

W Ding, J Li, W Mao, Z Meng, Z Shen - Reliability Engineering & System …, 2023 - Elsevier
Accurate prediction of the remaining useful life (RUL) of rolling bearings is important to
ensure the safe operation of mechanical system and to formulate maintenance strategies …