AVA:
Abstraction of behavior models for distributed automation plants using observations

Project Duration: 1.9.2011 to 31.8.2014 (Finished)
Area of Research:
Project Manager: Prof. Dr. Oliver Niggemann


  

Motivation

In automation engineering, methods exist (i) to capture the overall state of production and process plants, and (ii) for the early detection of degradation and anomalies. In this project, these approaches are extended: First, distributed automation systems are used for data collection. Second, new approaches to anomaly detection in computer science such as learning or the automatic parameterization of plant and process models for model-based diagnosis are used.

Project goals and research activities

To achieve high degree of utilization, and short maintenance periods, signs of degradation should be recognized as early as possible. Today, threshold-based methods often cannot do this. Operators can recognize these behavior changes often too late and this may lead to high maintenance costs and extended downtimes. Here, to overcome this problem, the project uses more complex and more dynamic models of the normal behavior.

The models of the normal behavior are automatically learned based on observations in the operation phase of the system. In this project, algorithms are developed which learn the models in form of hybrid temporal finite automata. The learned models are then used for anomaly detection. During runtime, the forecast of the learned model is compared with the current system observations. For each deviation, an error is signaled.


Weidmüller
Jowat AG
ISI Automation
Universität Paderborn
Fraunhofer IOSB

Image: Abstraction of behavior models for distributed automation plants using observations


Publications:

Niggemann, Oliver; Vodenčarević, Asmir; Maier, Alexander; Windmann, Stefan; Kleine Büning, Hans: A Learning Anomaly Detection Algorithm for Hybrid Manufacturing Systems. In: The 24th International Workshop on Principles of Diagnosis (DX-2013) Jerusalem, Israel, Oct 2013 (More)

Tack, Tim; Maier, Alexander; Niggemann, Oliver: Visuelle Anomalie-Erkennung in Produktionsanlagen. In: VDI Kongress AUTOMATION 2013 Baden Baden Jun 2013 (More)

Maier, Alexander; Köster, Markus; Paiz Gatica, Carlos; Niggemann, Oliver: Automated Generation of Timing Models in Distributed Production Plants. In: IEEE International Conference on Industrial Technology (ICIT 2013), Cape Town, South Africa, Feb 2013 Feb 2013 (More)

Vodenčarević, Asmir; Maier, Alexander; Niggemann, Oliver: Evaluating Learning Algorithms for Stochastic Finite Automata. In: 2nd International Conference on Pattern Recognition Applications and Methods (ICPRAM 2013); Barcelona, Spain, Feb 2013 Feb 2013 (More)

Maier, Alexander; Paiz Gatica, Carlos; Köster, Markus; Niggemann, Oliver; Michels, Jan Stefan: Lernen des Zeitverhaltens in verteilten Produktionsanlagen. In: Kommunikation in der Automation (KommA 2012), Lemgo, Germany, Nov 2012 Nov 2012 (More)

Maier, Alexander; Tack, Tim; Niggemann, Oliver: Visual Anomaly Detection in Production Plants.. In: 9th International Conference on Informatics in Control, Automation and Robotics (ICINCO) Rome, Italy, Jul 2012, Jul 2012 (More)

Maier, Alexander; Pethig, Florian; Vodenčarević, Asmir; Schetinin, Nikolai; Niggemann, Oliver; Kleine Büning, Hans: Analyse und Visualisierung des Energieverbrauchs in Produktionsanlagen. VDI Kongress AUTOMATION 2012, Baden Baden, Jun 2012 (More)

Niggemann, Oliver; Stein, Benno; Maier, Alexander: Solving Modeling Problems with Machine Learning - A Classification Scheme of Model Learning Approaches for Technical Systems. MBEES, 2012 MBEES - Model-Based Development of Embedded Systems, Dagstuhl, Germany, Feb 2012 (More)

Vodenčarević, Asmir; Niggemann, Oliver; Maier, Alexander: Using Behavior Models for Anomaly Detection in Hybrid Systems. In: 23rd International Symposium on Information, Communication and Automation Technologies-ICAT 2011, Sarajevo, Bosnia and Herzegovina. Oct 2011 (More)

Vodenčarević, Asmir; Kleine Büning, Hans; Niggemann, Oliver; Maier, Alexander: Identifying Behavior Models for Process Plants. In: 16th IEEE International Conference on Emerging Technologies and Factory Automation ETFA'2011, Toulouse, France, 2011 In: 16th IEEE International Conference on Emerging Technologies & Factory Automation (ETFA) Sep 2011 (More)

Niggemann, Oliver; Maier, Alexander; Vodenčarević, Asmir; Jantscher, Bernhard: Fighting the Modeling Bottleneck – Learning Models for Production Plants. In: MBEES - Model-Based Development of Embedded Systems Dagstuhl, Germany, 2011 , Feb 2011 (More)


Funded by: BMBF
Project Management: Projektträger Jülich
Grant ID: 17N1211
Funding: IngenieurNachwuchs
Contact Person: M.Sc. Alexander Maier , M.Sc. Johann Badinger
Research Assistant: M.Sc. Alexander Maier , M.Sc. Johann Badinger