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Fotografi av Daniel Jung

Daniel Jung

Universitetslektor, Docent


Publikationslista

Nya preprints

Daniel Jung, Erik Frisk, Mattias Krysander, The LiU-ICE Benchmark – An Industrial Fault Diagnosis Case Study (2024)  https://arxiv.org/abs/2408.13269

Tidskriftsartiklar

Max Johansson, Arnaud Contet, Olof Erlandsson, Robin Holmbom, Erik Hockerdal, Oskar Lind Jonsson, Daniel Jung, Lars Eriksson,  The Electrochemical Commercial Vehicle (ECCV) Platform, Energies 17:1742 (2024)  https://doi.org/10.3390/en17071742

Vishnu Renganathan, Qadeer Ahmed, Daniel Jung,  Enhancing the Security of Automotive Systems Using Attackability Index, IEEE Transactions on Intelligent Vehicles 9:315-327 (2024)  https://doi.org/10.1109/TIV.2023.3332006

Daniel Jung, Christofer Sundström,  Analysis of Tariffs and the Impact on Voltage Variations in Low-Voltage Grids with Smart Charging and Renewable Energy, Energies 16:7648 (2023)  https://doi.org/10.3390/en16227648

Andreas Lundgren, Daniel Jung,  Data-driven fault diagnosis analysis and open-set classification of time-series data, Control Engineering Practice 121:105006 (2022)  https://doi.org/10.1016/j.conengprac.2021.105006  https://arxiv.org/abs/2009.04756

Daniel Jung,  Distributed Feature Selection for Multi-Class Classification Using ADMM, IEEE Control Systems Letters 5:821-826 (2021)  https://doi.org/10.1109/LCSYS.2020.3006428

Eeshan Deosthale, Daniel Jung, Qadeer Ahmed,  Discrete Fault Diagnosis of Structurally Reconfigurable Systems, Journal of Dynamic Systems Measurement, and Control 143:101009 (2021)  https://doi.org/10.1115/1.4051252

Sergii Voronov, Daniel Jung, Erik Frisk,  A forest-based algorithm for selecting informative variables using Variable Depth Distribution, Engineering applications of artificial intelligence 97:104073 (2021)  https://doi.org/10.1016/j.engappai.2020.104073

Shreshta Rajakumar Deshpande, Daniel Jung, Leo Bauer, Marcello Canova,  Integrated Approximate Dynamic Programming and Equivalent Consumption Minimization Strategy for Eco-Driving in a Connected and Automated Vehicle, IEEE Transactions on Vehicular Technology 70:11204-11215 (2021)  https://doi.org/10.1109/TVT.2021.3102505

Daniel Jung,  Data-Driven Open-Set Fault Classification of Residual Data Using Bayesian Filtering, IEEE Transactions on Control Systems Technology 28:2045-2052 (2020)  https://doi.org/10.1109/TCST.2020.2997648

Daniel Jung, Yi Dong, Erik Frisk, Mattias Krysander, Gautam Biswas,  Sensor selection for fault diagnosis in uncertain systems, International Journal of Control 93:629-639 (2020)  https://doi.org/10.1080/00207179.2018.1484171

Daniel Jung, Christofer Sundström,  A Combined Data-Driven and Model-Based Residual Selection Algorithm for Fault Detection and Isolation, IEEE Transactions on Control Systems Technology 27:616-630 (2019)  https://doi.org/10.1109/TCST.2017.2773514

Hamed Khorasgani, Gautam Biswas, Daniel Jung,  Structural Methodologies for Distributed Fault Detection and Isolation, Applied Sciences 9:1286 (2019)  https://doi.org/10.3390/app9071286

Jan Åslund, Erik Frisk, Daniel Jung,  Asymptotic behavior of a fault diagnosis performance measure for linear systems, Automatica 106:143-149 (2019)  https://doi.org/10.1016/j.automatica.2019.04.041

Daniel Jung, Erik Frisk,  Residual selection for fault detection and isolation using convex optimization, Automatica 97:143-149 (2018)  https://doi.org/10.1016/j.automatica.2018.08.006

Daniel Jung, Kok Yew Ng, Erik Frisk, Mattias Krysander,  Combining model-based diagnosis and data-driven anomaly classifiers for fault isolation, Control Engineering Practice 80:146-156 (2018)  https://doi.org/10.1016/j.conengprac.2018.08.013

Pierpaolo Polverino, Erik Frisk, Daniel Jung, Mattias Krysander, Cesare Pianese,  Model-based diagnosis through Structural Analysis and Causal Computation for automotive Polymer Electrolyte Membrane Fuel Cell systems, Journal of Power Sources 357:26-40 (2017)  https://doi.org/10.1016/j.jpowsour.2017.04.089

Daniel Jung, Erik Frisk, Mattias Krysander,  A flywheel error compensation algorithm for engine misfire detection, Control Engineering Practice 47:37-47 (2016)  https://doi.org/10.1016/j.conengprac.2015.12.009

Daniel Jung, Lars Eriksson, Erik Frisk, Mattias Krysander,  Development of misfire detection algorithm using quantitative FDI performance analysis, Control Engineering Practice 34:49-60 (2015)  https://doi.org/10.1016/j.conengprac.2014.10.001

Daniel Eriksson, Erik Frisk, Mattias Krysander,  A method for quantitative fault diagnosability analysis of stochastic linear descriptor models, Automatica 49:1591-1600 (2013)  https://doi.org/10.1016/j.automatica.2013.02.045

Konferensartiklar

2024

Niklas Allansson, Arman Mohammadi, Daniel Jung, Mattias Krysander,  Fuel injection fault diagnosis using structural analysis and data-driven residuals, IFAC PAPERSONLINE, pp. 360-365, ELSEVIER (2024)  https://doi.org/10.1016/j.ifacol.2024.07.244

Theodor Westny, Arman Mohammadi, Daniel Jung, Erik Frisk,  Stability-Informed Initialization of Neural Ordinary Differential Equations, Proceedings of the 41 st International Conference on Machine Learning, Vienna, Austria. PMLR 235, 2024, Neil Lawrence (ed.), Proceedings of Machine Learning Research, pp. 52903-52914, PMLR (2024)

2023

Daniel Jung, Mattias Krysander, Arman Mohammadi,  Fault diagnosis using data-driven residuals for anomaly classification with incomplete training data, IFAC PAPERSONLINE, pp. 2903-2908, ELSEVIER (2023)  https://doi.org/10.1016/j.ifacol.2023.10.1410

Arman Mohammadi, Theodor Westny, Daniel Jung, Mattias Krysander,  Analysis of Numerical Integration in RNN-Based Residuals for Fault Diagnosis of Dynamic Systems, IFAC PAPERSONLINE, pp. 2909-2914, ELSEVIER (2023)  https://doi.org/10.1016/j.ifacol.2023.10.1411

2022

Daniel Jung,  Automated Design of Grey-Box Recurrent Neural Networks for Fault Diagnosis using Structural Models and Causal Information, LEARNING FOR DYNAMICS AND CONTROL CONFERENCE, VOL 168, Proceedings of Machine Learning Research, JMLR-JOURNAL MACHINE LEARNING RESEARCH (2022)

Daniel Jung, Bjorn Kleman, Henrik Lindgren, Hakan Warnquist,  Fault Diagnosis of Exhaust Gas Treatment System Combining Physical Insights and Neural Networks, IFAC PAPERSONLINE, pp. 97-102, ELSEVIER (2022)  https://doi.org/10.1016/j.ifacol.2022.10.268

Daniel Jung, Joakim Säfdal,  A flexi-pipe model for residual-based engine fault diagnosis to handle incomplete data and class overlapping, IFAC PAPERSONLINE, pp. 84-89, ELSEVIER (2022)  https://doi.org/10.1016/j.ifacol.2022.10.266

Arman Mohammadi, Mattias Krysander, Daniel Jung,  Analysis of grey-box neural network-based residuals for consistency-based fault diagnosis, , IFAC papers online, pp. 1-6, Elsevier (2022)  https://doi.org/10.1016/j.ifacol.2022.07.097

Erik Frisk, Fabian Jarmolowitz, Daniel Jung, Mattias Krysander,  Fault Diagnosis Using Data, Models, or Both – An Electrical Motor Use-Case, , IFAC papers online, pp. 533-538, Elsevier (2022)  https://doi.org/10.1016/j.ifacol.2022.07.183

Kevin Lindstrom, Max Johansson, Daniel Jung,  A Data-Driven Clustering Algorithm for Residual Data Using Fault Signatures and Expectation Maximization, IFAC PAPERSONLINE, pp. 121-126, ELSEVIER (2022)  https://doi.org/10.1016/j.ifacol.2022.07.116

2020

Daniel Jung,  Structural Methods for Distributed Fault Diagnosis of Large-Scale Systems, 2020 59TH IEEE CONFERENCE ON DECISION AND CONTROL (CDC), IEEE Conference on Decision and Control, pp. 2690-2695, IEEE (2020)  https://doi.org/10.1109/CDC42340.2020.9303744

Frans Skarman, Oscar Gustafsson, Daniel Jung, Mattias Krysander,  A Tool to Enable FPGA-Accelerated Dynamic Programming for Energy Management of Hybrid Electric Vehicles, IFAC PAPERSONLINE, pp. 15104-15109, ELSEVIER (2020)  https://doi.org/10.1016/j.ifacol.2020.12.2033

Frans Skarman, Oscar Gustafsson, Daniel Jung, Mattias Krysander,  Acceleration of Simulation Models Through Automatic Conversion to FPGA Hardware, 2020 30th International Conference on Field-Programmable Logic and Applications (FPL), pp. 359-360, IEEE (2020)  https://doi.org/10.1109/FPL50879.2020.00068

2019

Daniel Jung,  Engine Fault Diagnosis Combining Model-based Residuals and Data-Driven Classifiers, IFAC PAPERSONLINE, IFAC papers online, pp. 285-290, ELSEVIER (2019)  https://doi.org/10.1016/j.ifacol.2019.09.046

2018

Daniel Jung, Qadeer Ahmed, Giorgio Rizzoni,  Design Space Exploration for Powertrain Electrification using Gaussian Processes, 2018 Annual American Control Conference (ACC), pp. 846-851 (2018)  https://doi.org/10.23919/ACC.2018.8430899

Daniel Jung, Qadeer Ahmed, Xieyuan Zhang, Giorgio Rizzoni,  Mission-based Design Space Exploration for Powertrain Electrification of Series Plugin Hybrid Electric Delivery Truck, WCX World Congress Experience, SAE International (2018)  https://doi.org/10.4271/2018-01-1027

Eeshan Deosthale, Daniel Jung, Qadeer Ahmed,  Sensor Selection for Fault Detection and Isolation in Structurally Reconfigurable Systems, 2018 Annual American Control Conference (ACC), pp. 5807-5812 (2018)  https://doi.org/10.23919/ACC.2018.8430950

Pradeep Sharma Oruganti, Qadeer Ahmed, Daniel Jung,  Effects of Thermal and Auxiliary Dynamics on a Fuel Cell Based Range Extender, SAE Technical Paper, SAE International (2018)  https://doi.org/10.4271/2018-01-1311

Santhosh Tamilarasan, Daniel Jung, Levent Guvenc,  Drive Scenario Generation Based on Metrics for Evaluating an Autonomous Vehicle Controller, SAE Technical Paper, SAE International (2018)  https://doi.org/10.4271/2018-01-0034

2017

Daniel Jung, Erik Frisk, Mattias Krysander,  Residual change detection using low-complexity sequential quantile estimation, 20th IFAC World Congress, Denis Dochain, Didier Henrion, Dimitri Peaucelle (eds.), IFAC-PapersOnLine, pp. 14064-14069 (2017)  https://doi.org/10.1016/j.ifacol.2017.08.1842

Erik Frisk, Mattias Krysander, Daniel Jung,  A Toolbox for Analysis and Design of Model Based Diagnosis Systems for Large Scale Models, IFAC PAPERSONLINE, IFAC Papers Online, pp. 3287-3293, ELSEVIER SCIENCE BV (2017)  https://doi.org/10.1016/j.ifacol.2017.08.504

2016

Daniel Jung,  A generalized fault isolability matrix for improved fault diagnosability analysis, 2016 3RD CONFERENCE ON CONTROL AND FAULT-TOLERANT SYSTEMS (SYSTOL), Conference on Control and Fault-Tolerant Systems, pp. 519-524, IEEE (2016)  https://doi.org/10.1109/SYSTOL.2016.7739801

Daniel Jung, Kok Yew Ng, Erik Frisk, Mattias Krysander,  A combined diagnosis system design using model-based and data-driven methods, 2016 3RD CONFERENCE ON CONTROL AND FAULT-TOLERANT SYSTEMS (SYSTOL), Conference on Control and Fault-Tolerant Systems, pp. 177-182, IEEE (2016)  https://doi.org/10.1109/SYSTOL.2016.7739747

Christofer Sundström, Daniel Jung, Anders Blom,  Analysis of optimal energy management in smart homes using MPC, 2016 EUROPEAN CONTROL CONFERENCE (ECC) , pp. 2066-2071, Institute of Electrical and Electronics Engineers (IEEE) (2016)  https://doi.org/10.1109/ECC.2016.7810596

Sergii Voronov, Daniel Jung, Erik Frisk,  Heavy-duty truck battery failure prognostics using random survival forests, IFAC PAPERSONLINE, IFAC PapersOnline, pp. 562-569, ELSEVIER SCIENCE BV (2016)  https://doi.org/10.1016/j.ifacol.2016.08.082

Sergii Voronov, Daniel Jung, Erik Frisk,  Variable selection for heavy-duty vehicle battery failure prognostics using random survival forests, PHME 2016 Proceedings of the Third European Conference of the Prognostics and Health Management Society 2016, Bilbao, Spain July 5–8, 2016, Ioana Eballard and Anibal Bregon (ed.), pp. 649-659 (2016)

2015

Daniel Jung, Erik Frisk, Mattias Krysander,  Quantitative isolability analysis of different fault modes, 9th IFAC Symposium on Fault Detection, Supervision and Safety for Technical Processes SAFEPROCESS 2015 – Paris, 2–4 September 2015, Didier Maquin (ed.), IFAC-PapersOnLine, pp. 1275-1282, Elsevier (2015)  https://doi.org/10.1016/j.ifacol.2015.09.701

Daniel Jung, Hamed Khorasgani, Erik Frisk, Mattias Krysander, Gautam Biswas,  Analysis of fault isolation assumptions when comparing model-based design approaches of diagnosis systems, Proceedings of the 9th IFAC Symposium on Fault Detection, Supervision and Safety of Technical Processes Safeprocess’15, IFAC-PapersOnLine, pp. 1289-1296, Elsevier (2015)  https://doi.org/10.1016/j.ifacol.2015.09.703

Hamed Khorasgani, Daniel Jung, Gautam Biswas,  Structural approach for distributed fault detection and isolation, , IFAC papers online, Elsevier (2015)  https://doi.org/10.1016/j.ifacol.2015.09.507

2014

Daniel Eriksson, Christofer Sundström,  Sequential Residual Generator Selection for Fault Detection, 2014 European Control Conference (ECC), pp. 932-937, IEEE (2014)  https://doi.org/10.1109/ECC.2014.6862195

Hamed Khorasgani, Daniel Jung, Gautam Biswas, Erik Frisk, Mattias Krysander,  Off-line robust residual selection using sensitivity analysis, (2014)

Hamed Khorasgani, Daniel Jung, Gautam Biswas, Erik Frisk, Mattias Krysander,  Robust Residual Selection for Fault Detection, 2014 IEEE 53RD ANNUAL CONFERENCE ON DECISION AND CONTROL (CDC), pp. 5764-5769, IEEE (2014)

2013

Daniel Eriksson, Lars Eriksson, Erik Frisk, Mattias Krysander,  Flywheel angular velocity model for misfire and driveline disturbance simulation, Proceedings of the 7th IFAC Symposium on Advances in Automotive Control, The International Federation of Automatic Control, IFAC Publications / IFAC Proceedings series, pp. 570-575, Elsevier (2013)  https://doi.org/10.3182/20130904-4-JP-2042.00020

2012

Daniel Eriksson, Erik Frisk, Mattias Krysander,  A sequential test selection algorithm for fault isolation, Proceedings of the 10th European Workshop on Advanced Control and Diagnosis, ACD 2012, Copenhagen, Denmark (2012)

Daniel Eriksson, Mattias Krysander, Erik Frisk,  Using quantitative diagnosability analysis for optimal sensor placement, Proceedings of the 8th IFAC Safe Process, Mexico City, Mexico, Carlos Manuel Astorga-Zaragoza, Arturo Molina Gutierrez and Adriana Aguilera-Gonzalez (eds.), pp. 940-945, Curran Associates, Inc. (2012)  https://doi.org/10.3182/20120829-3-MX-2028.00196

2011

Daniel Eriksson, Mattias Krysander, Erik Frisk,  Quantitative Fault Diagnosability Performance of Linear Dynamic Descriptor Models, (2011)

Daniel Eriksson, Mattias Krysander, Erik Frisk,  Quantitative Stochastic Fault Diagnosability Analysis, 2011 50th IEEE Conference on Decision and Control andEuropean Control Conference (CDC-ECC)Orlando, FL, USA, December 12-15, 2011, Decision and Control (CDC), pp. 1563-1569, Institute of Electrical and Electronics Engineers (IEEE) (2011)  https://doi.org/10.1109/CDC.2011.6160362

2010

Erik Almqvist, Daniel Eriksson, Andreas Lundberg, Emil Nilsson, Niklas Wahlström, Erik Frisk, Mattias Krysander,  Solving the ADAPT Benchmark Problem - A Student Project Study, (2010)

Rapporter

Daniel Eriksson, Lars Eriksson, Erik Frisk, Mattias Krysander,  Analysis and optimization with the Kullback-Leibler divergence for misfire detection using estimated torque, LiTH-ISY-R-3057, Linköping University Electronic Press, Linköping (2013)

Preprints

Daniel Jung, Residual Generation Using Physically-Based Grey-Box Recurrent Neural Networks For Engine Fault Diagnosis (2020)  https://arxiv.org/abs/2008.04644

Shreshta Rajakumar Deshpande, Daniel Jung, Marcello Canova, Integrated Approximate Dynamic Programming and Equivalent Consumption Minimization Strategy for Eco-Driving in a Connected and Automated Vehicle (2020)  https://arxiv.org/abs/2010.03620

Daniel Jung, Isolation and Localization of Unknown Faults Using Neural Network-Based Residuals (2019)  https://arxiv.org/abs/1910.05626

Doktorsavhandlingar

Daniel Jung,  Diagnosability performance analysis of models and fault detectors, Linköping Studies in Science and Technology. Dissertations 1660, Linköping University Electronic Press, Linköping (2015)  https://doi.org/10.3384/diss.diva-117058

Licentiatavhandlingar

Daniel Eriksson,  Diagnosability analysis and FDI system design for uncertain systems, Linköping Studies in Science and Technology. Thesis 1584, Linköping University Electronic Press, Linköping (2013)