86 citations · 89 across the 4 of their papers we have counts for
4 papers
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…
Data-Driven Fault Diagnosis Analysis and Open-Set Classification of Time-Series Data
Andreas Lundgren, Daniel Jung
Fault diagnosis of dynamic systems is done by detecting changes in time-series data, for example residuals, caused by system degradation and faulty components. The use of general-p…
Residual Generation Using Physically-Based Grey-Box Recurrent Neural Networks For Engine Fault Diagnosis
Daniel Jung
Data-driven fault diagnosis is complicated by unknown fault classes and limited training data from different fault realizations. In these situations, conventional multi-class class…
Isolation and Localization of Unknown Faults Using Neural Network-Based Residuals
Daniel Jung
Localization of unknown faults in industrial systems is a difficult task for data-driven diagnosis methods. The classification performance of many machine learning methods relies o…