High-rate structural health monitoring and prognostics: An overview
Structural health monitoring (SHM) includes both static and highly dynamic engineering
systems. With the advent of real-time sensing, edge-computing, and high-bandwidth …
systems. With the advent of real-time sensing, edge-computing, and high-bandwidth …
A physics-constrained Bayesian neural network for battery remaining useful life prediction
In order to predict the remaining useful life (RUL) of lithium-ion batteries, a capacity
degradation model may be developed using either simplified physical laws or machine …
degradation model may be developed using either simplified physical laws or machine …
[HTML][HTML] Evaluating the use of rate-based monitoring for improved fatigue remnant life predictions
The ability to perform accurate remnant life predictions is crucial to ensure the integrity of
engineering components that experience fatigue loading during operation. This is …
engineering components that experience fatigue loading during operation. This is …
A probabilistic estimation approach for the failure forecast method using Bayesian inference
Positive-feedback mechanisms such as fatigue induce a self-accelerating behavior,
captured by models displaying infinite limit-state asymptotics, collectively known as the …
captured by models displaying infinite limit-state asymptotics, collectively known as the …
[PDF][PDF] FATIGUE PROGNOSIS USING THE UNCERTAINTY-QUANTIFIED FAILURE FORECAST METHOD
Several material failure modes such as fatigue have been noted to occur, after initiation
phases, as a consequence of a positive-feedback mechanism. Positive feedback systems …
phases, as a consequence of a positive-feedback mechanism. Positive feedback systems …