Daniel E. Jung

发表

A Combined Data-Driven and Model-Based Residual Selection Algorithm for Fault Detection and Isolation

Daniel Jung, Christofer Sundström, Daniel E. Jung, 2019, IEEE Transactions on Control Systems Technology.

A generalized fault isolability matrix for improved fault diagnosability analysis

Daniel E. Jung, 2016, 2016 3rd Conference on Control and Fault-Tolerant Systems (SysTol).

Data-driven fault diagnosis analysis and open-set classification of time-series data

Daniel E. Jung, Andreas Lundgren, 2022, Control Engineering Practice.

Development and Evaluation of Model-Based Misfire Detection Algorithm

P. Ericson, E. Frisk, Daniel E. Jung, 2014 .

Data-driven fault diagnosis analysis and open-set classification of time-series data

Daniel E. Jung, Andreas Lundgren, 2020, Control Engineering Practice.

A Data-Driven Clustering Algorithm for Residual Data Using Fault Signatures and Expectation Maximization

Daniel E. Jung, Kevin Lindström, Max Johansson, 2022, IFAC-PapersOnLine.

Analysis of grey-box neural network-based residuals for consistency-based fault diagnosis

Arman Mohammadi, Daniel E. Jung, M. Krysander, 2022, IFAC-PapersOnLine.

Automated Design of Grey-Box Recurrent Neural Networks For Fault Diagnosis using Structural Models and Causal Information

Daniel E. Jung, 2022, L4DC.

Engine Fault Diagnosis Combining Model-based Residuals and Data-Driven Classifiers

Daniel Jung, Daniel E. Jung, 2019, IFAC-PapersOnLine.

Model-based diagnosis through Structural Analysis and Causal Computation for automotive Polymer Electrolyte Membrane Fuel Cell systems

Erik Frisk, Mattias Krysander, Cesare Pianese, 2017 .

Residual Generation Using Physically-Based Grey-Box Recurrent Neural Networks For Engine Fault Diagnosis

Daniel Jung, Daniel E. Jung, 2020, 2008.04644.

A Toolbox for Analysis and Design of Model Based Diagnosis Systems for Large Scale Models

Erik Frisk, Mattias Krysander, Daniel Jung, 2017 .

Sensor selection for fault diagnosis in uncertain systems

Yi Dong, Gautam Biswas, Erik Frisk, 2018, Int. J. Control.

Data-Driven Open-Set Fault Classification of Residual Data Using Bayesian Filtering

Daniel Jung, Daniel E. Jung, 2020, IEEE Transactions on Control Systems Technology.

Isolation and Localization of Unknown Faults Using Neural Network-Based Residuals pdf

Daniel Jung, Daniel E. Jung, 2019, Annual Conference of the PHM Society.

Distributed Feature Selection for Multi-Class Classification Using ADMM

Daniel Jung, Daniel E. Jung, 2021, IEEE Control Systems Letters.

Data-Driven Open Set Fault Classification and Fault Size Estimation Using Quantitative Fault Diagnosis Analysis pdf

Daniel Jung, Andreas Lundgren, Daniel E. Jung, 2020, ArXiv.

Combining model-based diagnosis and data-driven anomaly classifiers for fault isolation

Erik Frisk, Mattias Krysander, Daniel Jung, 2018, Control Engineering Practice.

Residual change detection using low-complexity sequential quantile estimation

Erik Frisk, Mattias Krysander, Daniel Jung, 2017 .

Fault Diagnosis Using Data, Models, or Both – An Electrical Motor Use-Case

E. Frisk, Daniel E. Jung, Mattias Krysander, 2022, IFAC-PapersOnLine.