A sensor fusion based approach for bearing fault diagnosis of rotating machine
Fault diagnosis in rotating machines plays a vital role in various industries. Bearing is the
essential element of rotating machines, and early fault detection can reduce the …
essential element of rotating machines, and early fault detection can reduce the …
Transfer-learning-based state-of-health estimation for lithium-ion battery with cycle synchronization
Accurately estimating a battery's state of health (SOH) helps prevent battery-powered
applications from failing unexpectedly. With the superiority of reducing the data requirement …
applications from failing unexpectedly. With the superiority of reducing the data requirement …
Health state identification method of nuclear power main circulating pump based on EEMD and OQGA-SVM
Z Liu, M Li, Z Zhu, L Xiao, C Nie, Z Tang - Electronics, 2023 - mdpi.com
Main circulation pump is the only high-speed rotating equipment in primary loop of nuclear
power plant. Its function is to ensure the normal operation of primary loop system by …
power plant. Its function is to ensure the normal operation of primary loop system by …
Spatiotemporal capsule neural network for vehicle trajectory prediction
Through advancement of the Vehicle-to-Everything (V2X) network, road safety, energy
consumption, and traffic efficiency can be significantly improved. An accurate vehicle …
consumption, and traffic efficiency can be significantly improved. An accurate vehicle …
Lithium-ion battery state of health estimation by matrix profile empowered online knee onset identification
Lithium-ion batteries (LiBs) degrade slightly until the knee onset, after which the
deterioration accelerates to end of life (EOL). The knee onset, which marks the initiation of …
deterioration accelerates to end of life (EOL). The knee onset, which marks the initiation of …
A robust supervised subspace learning approach for output-relevant prediction and detection against outliers
W Li, Y Wang - Journal of Process Control, 2021 - Elsevier
This paper proposes a novel robust supervised subspace learning (RSSL) method for output-
relevant prediction and detection against outliers. RSSL learns the robust subspaces by …
relevant prediction and detection against outliers. RSSL learns the robust subspaces by …
A Subspace Projective Clustering Approach for Backdoor Attack Detection and Mitigation in Deep Neural Networks
Backdoor attacks in Deep Neural Networks (DNNs) involve an attacker inserting a backdoor
into the network by manipulating the training dataset, which causes misclassification of …
into the network by manipulating the training dataset, which causes misclassification of …
Data screening based on correlation energy fluctuation coefficient and deep learning for fault diagnosis of rolling bearings
B Qin, Q Luo, Z Li, C Zhang, H Wang, W Liu - Energies, 2022 - mdpi.com
The accuracy of the intelligent diagnosis of rolling bearings depends on the quality of its
vibration data and the accuracy of the state identification model constructed accordingly …
vibration data and the accuracy of the state identification model constructed accordingly …
Graph neural network-based lithium-ion battery state of health estimation using partial discharging curve
Data-driven methods have gained extensive attention in estimating the state of health (SOH)
of lithium-ion batteries. Accurate SOH estimation requires degradation-relevant features and …
of lithium-ion batteries. Accurate SOH estimation requires degradation-relevant features and …
A hybrid deep learning model-based remaining useful life estimation for reed relay with degradation pattern clustering
Reed relay serves as the fundamental component of functional testing, which closely relates
to the successful quality inspection of electronics. To provide accurate remaining useful life …
to the successful quality inspection of electronics. To provide accurate remaining useful life …