---
_id: '4276'
abstract:
- lang: eng
  text: In the presented work, the detection of anomalous energy consumption in hybrid
    industrial production systems is investigated. A model-based approach with a timed
    hybrid automaton as overall system model is employed for anomaly detection. The
    approach is based on the assumption of several system modes, i.e. phases with
    continuous system behavior. Transitions between the modes are attributed to discrete
    control events such as on/off signals. The underlying discrete event system which
    comprises both system modes and transitions is modeled as finite state machine.
    The focus of this paper is set on the modeling of the energy consumption in the
    particular system modes. Sequences of stochastic state space models are employed
    for this purpose. Model learning and anomaly detection for this approach are considered.
    The proposed approach is further evaluated in a small model factory. The experimental
    results show significant improvements compared to existing approaches to anomaly
    detection in hybrid industrial systems.
author:
- first_name: Stefan
  full_name: Windmann, Stefan
  id: '58525'
  last_name: Windmann
- first_name: Shuo
  full_name: Jiao, Shuo
  last_name: Jiao
- first_name: Oliver
  full_name: Niggemann, Oliver
  id: '10876'
  last_name: Niggemann
- first_name: Holger
  full_name: Borcherding, Holger
  id: '1693'
  last_name: Borcherding
citation:
  ama: 'Windmann S, Jiao S, Niggemann O, Borcherding H. A Stochastic Method for the
    Detection of Anomalous Energy Consumption in Hybrid Industrial Systems. In: <i>11th
    International IEEE Conference on Industrial Informatics</i>. Bochum: IEEE; 2013:194-199.'
  apa: 'Windmann, S., Jiao, S., Niggemann, O., &#38; Borcherding, H. (2013). A Stochastic
    Method for the Detection of Anomalous Energy Consumption in Hybrid Industrial
    Systems. In <i>11th International IEEE Conference on Industrial Informatics</i>
    (pp. 194–199). Bochum: IEEE.'
  bjps: '<b>Windmann S <i>et al.</i></b> (2013) A Stochastic Method for the Detection
    of Anomalous Energy Consumption in Hybrid Industrial Systems. <i>11th International
    IEEE Conference on Industrial Informatics</i>. Bochum: IEEE, pp. 194–199.'
  chicago: 'Windmann, Stefan, Shuo Jiao, Oliver Niggemann, and Holger Borcherding.
    “A Stochastic Method for the Detection of Anomalous Energy Consumption in Hybrid
    Industrial Systems.” In <i>11th International IEEE Conference on Industrial Informatics</i>,
    194–99. Bochum: IEEE, 2013.'
  chicago-de: 'Windmann, Stefan, Shuo Jiao, Oliver Niggemann und Holger Borcherding.
    2013. A Stochastic Method for the Detection of Anomalous Energy Consumption in
    Hybrid Industrial Systems. In: <i>11th International IEEE Conference on Industrial
    Informatics</i>, 194–199. Bochum: IEEE.'
  din1505-2-1: '<span style="font-variant:small-caps;">Windmann, Stefan</span> ; <span
    style="font-variant:small-caps;">Jiao, Shuo</span> ; <span style="font-variant:small-caps;">Niggemann,
    Oliver</span> ; <span style="font-variant:small-caps;">Borcherding, Holger</span>:
    A Stochastic Method for the Detection of Anomalous Energy Consumption in Hybrid
    Industrial Systems. In: <i>11th International IEEE Conference on Industrial Informatics</i>.
    Bochum : IEEE, 2013, S. 194–199'
  havard: 'S. Windmann, S. Jiao, O. Niggemann, H. Borcherding, A Stochastic Method
    for the Detection of Anomalous Energy Consumption in Hybrid Industrial Systems,
    in: 11th International IEEE Conference on Industrial Informatics, IEEE, Bochum,
    2013: pp. 194–199.'
  ieee: S. Windmann, S. Jiao, O. Niggemann, and H. Borcherding, “A Stochastic Method
    for the Detection of Anomalous Energy Consumption in Hybrid Industrial Systems,”
    in <i>11th International IEEE Conference on Industrial Informatics</i>, Bochum,
    2013, pp. 194–199.
  mla: Windmann, Stefan, et al. “A Stochastic Method for the Detection of Anomalous
    Energy Consumption in Hybrid Industrial Systems.” <i>11th International IEEE Conference
    on Industrial Informatics</i>, IEEE, 2013, pp. 194–99.
  short: 'S. Windmann, S. Jiao, O. Niggemann, H. Borcherding, in: 11th International
    IEEE Conference on Industrial Informatics, IEEE, Bochum, 2013, pp. 194–199.'
  ufg: '<b>Windmann, Stefan et. al. (2013)</b>: A Stochastic Method for the Detection
    of Anomalous Energy Consumption in Hybrid Industrial Systems, in: <i>11th International
    IEEE Conference on Industrial Informatics</i>, Bochum, S. 194–199.'
  van: 'Windmann S, Jiao S, Niggemann O, Borcherding H. A Stochastic Method for the
    Detection of Anomalous Energy Consumption in Hybrid Industrial Systems. In: 11th
    International IEEE Conference on Industrial Informatics. Bochum: IEEE; 2013. p.
    194–9.'
conference:
  end_date: 2013-07-31
  location: Bochum
  name: 11th International IEEE Conference on Industrial Informatics
  start_date: 20013-07-29
date_created: 2020-12-14T10:38:54Z
date_updated: 2023-03-15T13:49:51Z
department:
- _id: DEP6020
- _id: DEP5018
language:
- iso: eng
page: 194 - 199
place: Bochum
publication: 11th International IEEE Conference on Industrial Informatics
publication_identifier:
  eisbn:
  - 978-1-4799-0752-6
publication_status: published
publisher: IEEE
status: public
title: A Stochastic Method for the Detection of Anomalous Energy Consumption in Hybrid
  Industrial Systems
type: conference
user_id: '74004'
year: 2013
...