An integrated multi-head dual sparse self-attention network for remaining useful life prediction
Committed to accident prevention, prediction of remaining useful life (RUL) plays a crucial
role in prognostics health management technology. Conventional convolutional neural …
role in prognostics health management technology. Conventional convolutional neural …
An integrated multitasking intelligent bearing fault diagnosis scheme based on representation learning under imbalanced sample condition
Accurate bearing fault diagnosis is of great significance of the safety and reliability of rotary
mechanical system. In practice, the sample proportion between faulty data and healthy data …
mechanical system. In practice, the sample proportion between faulty data and healthy data …
A data-model interactive remaining useful life prediction approach of lithium-ion batteries based on PF-BiGRU-TSAM
Accurate remaining useful life (RUL) prediction of lithium-ion batteries is critical for energy
supply systems. In conventional data-driven RUL prediction approaches, the battery's …
supply systems. In conventional data-driven RUL prediction approaches, the battery's …
A parallel hybrid neural network with integration of spatial and temporal features for remaining useful life prediction in prognostics
Prediction of remaining useful life (RUL) is an indispensable part of prognostics health
management (PHM) in complex systems. Considering the parallel integration of the spatial …
management (PHM) in complex systems. Considering the parallel integration of the spatial …
Lifetime extension approach based on the Levenberg–Marquardt neural network and power routing of DC–DC converters
The power conversion system based on the modular connection has widespread
applications in various power electronic systems. To accurately estimate the state of health …
applications in various power electronic systems. To accurately estimate the state of health …
Scalability, explainability and performance of data-driven algorithms in predicting the remaining useful life: A comprehensive review
Early detection of faulty patterns and timely scheduling of maintenance events can minimize
risk to the underlying processes and increase a system's lifespan, reliability, and availability …
risk to the underlying processes and increase a system's lifespan, reliability, and availability …
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 …
Prognostics for the sustainability of industrial cyber-physical systems: From an artificial intelligence perspective
As industrial cyber-physical systems (ICPS) play an increasingly pivotal role in the new
industrial paradigm, their sustainability has become the current research focus. Remaining …
industrial paradigm, their sustainability has become the current research focus. Remaining …
Overview of fault prognosis for traction systems in high-speed trains: A deep learning perspective
K Zhong, J Wang, S Xu, C Cheng, H Chen - Engineering Applications of …, 2023 - Elsevier
As the “heart” of high-speed train, traction systems play an important role in the safe
operation of trains, of which the operation and maintenance level is still unable to meet the …
operation of trains, of which the operation and maintenance level is still unable to meet the …
Adaptive deep learning-based remaining useful life prediction framework for systems with multiple failure patterns
Recent advances in multivariate data fusion technology have promoted the applications of
neural network-based models for remaining useful life (RUL) prediction. However, the …
neural network-based models for remaining useful life (RUL) prediction. However, the …