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Algorithms for Fault Detection and Diagnosis

Objektkategorie:
Elektronische Ressource
Person/Institution:
Ferracuti, Francesco
Freddi, Alessandro
Monteriù, Andrea
Verlag:
MDPI - Multidisciplinary Digital Publishing Institute
Veröffentlichungsort:
Basel, Switzerland
Entstehungszeit:
2021
Umfang, Illustration, Format:
1 Online-Ressource (130 p.)
Sprache:
Englisch
Bereitstellende Institution:
Forschungsbibliothek Gotha
GND Explorer
Abstract:
Due to the increasing demand for security and reliability in manufacturing and mechatronic systems, early detection and diagnosis of faults are key points to reduce economic losses caused by unscheduled maintenance and downtimes, to increase safety, to prevent the endangerment of human beings involved in the process operations and to improve reliability and availability of autonomous systems. The development of algorithms for health monitoring and fault and anomaly detection, capable of the early detection, isolation, or even prediction of technical component malfunctioning, is becoming more and more crucial in this context. This Special Issue is devoted to new research efforts and results concerning recent advances and challenges in the application of “Algorithms for Fault Detection and Diagnosis”, articulated over a wide range of sectors. The aim is to provide a collection of some of the current state-of-the-art algorithms within this context, together with new advanced theoretical solutions
Objekttext:
English

Zugriff und Nutzungsmöglichkeiten

Universität Erfurt
Forschungsbibliothek Gotha
Schloss Friedenstein
Schlossplatz 1
99867 Gotha
+49 361 737-5540
bibliothek.gotha(at)uni-erfurt.de
Datensatz angelegt am:
2023-04-13
Zuletzt geändert am:
2021-11-25
In Portal übernommen am:
2023-04-13