Transfer learning algorithms for bearing remaining useful life prediction: A comprehensive review from an industrial application perspective
Accurate remaining useful life (RUL) prediction for rolling bearings encounters many
challenges such as complex degradation processes, varying working conditions, and …
challenges such as complex degradation processes, varying working conditions, and …
A systematic review of data-driven approaches to fault diagnosis and early warning
As an important stage of life cycle management, machinery PHM (prognostics and health
management), an emerging subject in mechanical engineering, has seen a huge amount of …
management), an emerging subject in mechanical engineering, has seen a huge amount of …
Deep imbalanced domain adaptation for transfer learning fault diagnosis of bearings under multiple working conditions
The tremendous success of deep learning and transfer learning broadened the scope of
fault diagnosis, especially the latter further improved the diagnosis accuracy under multiple …
fault diagnosis, especially the latter further improved the diagnosis accuracy under multiple …
Multi-hop graph pooling adversarial network for cross-domain remaining useful life prediction: A distributed federated learning perspective
Accurate remaining useful life (RUL) prediction has gained increasing attention in modern
maintenance management. Considering the data privacy requirements of distributed multi …
maintenance management. Considering the data privacy requirements of distributed multi …
A multi-head attention network with adaptive meta-transfer learning for RUL prediction of rocket engines
Accurate prediction of remaining useful life (RUL) is necessary to ensure stable and safe
operations for rocket engines. The paper proposed a multi-head attention network coupled …
operations for rocket engines. The paper proposed a multi-head attention network coupled …
Machinery cross domain degradation prognostics considering compound domain shifts
Nowadays, data-driven based decision-making mode significantly promotes machinery
prognostics and health management (PHM), but are also profoundly affected by domain shift …
prognostics and health management (PHM), but are also profoundly affected by domain shift …
An adversarial transfer network with supervised metric for remaining useful life prediction of rolling bearing under multiple working conditions
J Zhuang, M Jia, X Zhao - Reliability Engineering & System Safety, 2022 - Elsevier
Many existing domain adaptation-based methods try to derive domain invariant features to
address domain shifts and obtain satisfactory remaining useful life (RUL) of bearings under …
address domain shifts and obtain satisfactory remaining useful life (RUL) of bearings under …
Digital twin-assisted multiscale residual-self-attention feature fusion network for hypersonic flight vehicle fault diagnosis
Y Dong, H Jiang, Z Wu, Q Yang, Y Liu - Reliability Engineering & System …, 2023 - Elsevier
Hypersonic flight vehicle (HFV) with long term exposure to poor operating environments will
inevitably experience performance degradation and potential failures. Currently, data-driven …
inevitably experience performance degradation and potential failures. Currently, data-driven …
A review on deep sequential models for forecasting time series data
Deep sequential (DS) models are extensively employed for forecasting time series data
since the dawn of the deep learning era, and they provide forecasts for the values required …
since the dawn of the deep learning era, and they provide forecasts for the values required …
MCA-DTCN: A novel dual-task temporal convolutional network with multi-channel attention for first prediction time detection and remaining useful life prediction
First prediction time (FPT) detection is a significant task when conducting remaining useful
life (RUL) prediction for mechanical equipment. Nevertheless, many existing works conducts …
life (RUL) prediction for mechanical equipment. Nevertheless, many existing works conducts …