12 citations · 20 across the 11 of their papers we have counts for
3 papers · 1 filter
Probabilistic Machine Learning for Uncertainty-Aware Diagnosis of Industrial Systems
Arman Mohammadi, Mattias Krysander, Daniel Jung +1
Deep neural networks has been increasingly applied in fault diagnostics, where it uses historical data to capture systems behavior, bypassing the need for high-fidelity physical mo…
Usage-Specific Survival Modeling Based on Operational Data and Neural Networks
Olov Holmer, Mattias Krysander, Erik Frisk
Accurate predictions of when a component will fail are crucial when planning maintenance, and by modeling the distribution of these failure times, survival models have shown to be…
Analysis of Numerical Integration in RNN-Based Residuals for Fault Diagnosis of Dynamic Systems
Arman Mohammadi, Theodor Westny, Daniel Jung +1
Data-driven modeling and machine learning are widely used to model the behavior of dynamic systems. One application is the residual evaluation of technical systems where model pred…