Dynamic fault detection and diagnosis of industrial alkaline water electrolyzer process with variational Bayesian dictionary learning

arXiv:2404.09524v1 Announce Type: new
Abstract: Alkaline Water Electrolysis (AWE) is one of the simplest green hydrogen production method using renewable energy.
AWE system typically yields process variables that are serially correlated and contaminated by measurement uncertainty.
A novel robust dynamic variational Bayesian dictionary learning (RDVDL) monitoring approach is proposed to improve the reliability and safety of AWE operation.
RDVDL employs a sparse Bayesian dictionary learning to preserve the dynamic mechanism information of AWE process which allows the easy interpretation of …

abstract arxiv bayesian cs.lg detection diagnosis dictionary dynamic energy green hydrogen industrial measurement novel process production renewable robust type uncertainty variables water