Fault diagnosis of laminar cooling roller motor based on morphological recognition and combination patterns mining of multicurrent signatures
Laminar cooling roller motor (LCRM) is the main driving equipment of laminar cooling
Section (LCS) in a steelmaking plant. To promote an intelligent upgrade of the safe …
Section (LCS) in a steelmaking plant. To promote an intelligent upgrade of the safe …
A process knowledge-based hybrid method for univariate time series prediction with uncertain inputs in process industry
L Sun, Y Ji, Q Li, T Yang - Advanced Engineering Informatics, 2024 - Elsevier
In process industry, accurate and efficient univariate time series prediction (TSP) of key
process parameters is crucial for optimizing production processes. However, noisy data and …
process parameters is crucial for optimizing production processes. However, noisy data and …
An interpretable RUL prediction method of aircraft engines under complex operating conditions using spatio-temporal features
J Gao, Y Wang, Z Sun - Measurement Science and Technology, 2024 - iopscience.iop.org
Long short-term memory (LSTM) based prediction methods have achieved remarkable
achievements in remaining useful life (RUL) prediction for aircraft engines. However, their …
achievements in remaining useful life (RUL) prediction for aircraft engines. However, their …
A lightweight transformer and depthwise separable convolution model for remaining useful life prediction of turbofan engines
R Li, H Zhan, J Yu, R Wang, K Han - Measurement Science and …, 2023 - iopscience.iop.org
The degradation of turbofan engines under complex operating conditions makes it difficult to
predict their remaining useful life (RUL), which affects aircraft maintenance efficiency and …
predict their remaining useful life (RUL), which affects aircraft maintenance efficiency and …
A multiple conditions dual inputs attention network remaining useful life prediction method
The degradation process of mechanical equipment shows considerable disparities under
varying operating conditions. However, most existing remaining useful life (RUL) prediction …
varying operating conditions. However, most existing remaining useful life (RUL) prediction …
A dual-scale transformer-based remaining useful life prediction model in industrial Internet of Things
With recent advents of industrial Internet of Things (IIoT), the connectivity and data collection
capabilities of industrial equipment have be significantly enhanced, yet bringing new …
capabilities of industrial equipment have be significantly enhanced, yet bringing new …
Self-Attention Transformer-Based Architecture for Remaining Useful Life Estimation of Complex Machines
Meaningful feature extraction from multivariate time-series data is still challenging since it
takes into account the correlation between pairs of sensors as well as the temporal …
takes into account the correlation between pairs of sensors as well as the temporal …
[HTML][HTML] A novel transformer-based DL model enhanced by position-sensitive attention and gated hierarchical LSTM for aero-engine RUL prediction
X Chen - Scientific Reports, 2024 - nature.com
Accurate prediction of remaining useful life (RUL) for aircraft engines is essential for
proactive maintenance and safety assurance. However, existing methods such as physics …
proactive maintenance and safety assurance. However, existing methods such as physics …
A Remaining Useful Life Prediction Method of Rolling Bearings Based on Deep Reinforcement Learning
G Zheng, Y Li, Z Zhou, R Yan - IEEE Internet of Things Journal, 2024 - ieeexplore.ieee.org
Remaining useful life (RUL) prediction technology is a crucial task in prognostics and health
management (PHM) systems, as it contributes to the enhancement of the reliability of …
management (PHM) systems, as it contributes to the enhancement of the reliability of …
A time series anomaly detection method based on series-parallel transformers with spatial and temporal association discrepancies
S Fu, X Gao, F Zhai, B Li, B Xue, J Yu, Z Meng… - Information …, 2024 - Elsevier
Multivariate time series anomaly detection methods can discover malfunctions in a complex
system by detecting anomalies in the monitoring data. Multivariate time series have complex …
system by detecting anomalies in the monitoring data. Multivariate time series have complex …