Abstract
| Originalsprache | englisch |
|---|---|
| Titel | Diagnosability, Security and Safety of Hybrid Dynamic and Cyber-Physical Systems |
| Redakteure/-innen | Moamar Sayed-Mouchaweh |
| Erscheinungsort | Cham |
| Herausgeber (Verlag) | Springer International Publishing AG |
| Seiten | 17-43 |
| Seitenumfang | 27 |
| ISBN (Print) | 978-3-319-74962-4 |
| DOIs | |
| Publikationsstatus | Veröffentlicht - 2018 |
Dies zitieren
Wind Turbine Fault Localization: A Practical Application of Model-Based Diagnosis. / Koitz, Roxane; Wotawa, Franz; Lüftenegger, Johannes; Gray, Christopher S.; Langmayr, Franz.
Diagnosability, Security and Safety of Hybrid Dynamic and Cyber-Physical Systems. Hrsg. / Moamar Sayed-Mouchaweh. Cham : Springer International Publishing AG , 2018. S. 17-43.Publikation: Beitrag in Buch/Bericht/Konferenzband › Beitrag in Buch/Bericht › Forschung › Begutachtung
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TY - CHAP
T1 - Wind Turbine Fault Localization: A Practical Application of Model-Based Diagnosis
AU - Koitz, Roxane
AU - Wotawa, Franz
AU - Lüftenegger, Johannes
AU - Gray, Christopher S.
AU - Langmayr, Franz
PY - 2018
Y1 - 2018
N2 - Diagnosis of complex engineered systems such as wind turbines poses a challenging task involving fault detection, localization, and repair activities. Wind turbines are equipped with a large number of sensors tracking their operation and condition. Data is continuously transmitted to a central monitoring system, where it can be used to automatically detect deviations between the observed and expected behavior. Based on the revealed anomalies, appropriate actions may be taken to restore an operational state. Whereas fault detection has been automated to some extent, localization is still performed mostly manually based on the experience of the service staff. This is inefficient due to limitations in available human resources, lack of long-term learning, and a high potential for false positives. In this chapter, we introduce an application that supports the process of efficient fault identification. Besides exploring the foundations, we present the overall diagnosis process as well as the software's user interface, which has been developed in consideration of the typical work processes and environments of the maintenance staff. Further, we discuss the current stage of the application's integration into the wind turbine diagnosis process.
AB - Diagnosis of complex engineered systems such as wind turbines poses a challenging task involving fault detection, localization, and repair activities. Wind turbines are equipped with a large number of sensors tracking their operation and condition. Data is continuously transmitted to a central monitoring system, where it can be used to automatically detect deviations between the observed and expected behavior. Based on the revealed anomalies, appropriate actions may be taken to restore an operational state. Whereas fault detection has been automated to some extent, localization is still performed mostly manually based on the experience of the service staff. This is inefficient due to limitations in available human resources, lack of long-term learning, and a high potential for false positives. In this chapter, we introduce an application that supports the process of efficient fault identification. Besides exploring the foundations, we present the overall diagnosis process as well as the software's user interface, which has been developed in consideration of the typical work processes and environments of the maintenance staff. Further, we discuss the current stage of the application's integration into the wind turbine diagnosis process.
U2 - 10.1007/978-3-319-74962-4_2
DO - 10.1007/978-3-319-74962-4_2
M3 - Chapter
SN - 978-3-319-74962-4
SP - 17
EP - 43
BT - Diagnosability, Security and Safety of Hybrid Dynamic and Cyber-Physical Systems
A2 - Sayed-Mouchaweh, Moamar
PB - Springer International Publishing AG
CY - Cham
ER -