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Repozytorium publikacji
Politechniki Gdańskiej

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Faults and Fault Detection Methods in Electric Drives

The chapter presents a review of faults and fault detection methods in electric drives. Typical faults are presented that arises for the induction motor, which is valued in the industry for its robust construction and cost-effective production. Moreover, a summary is presented of detectable faults in conjunction with the required physical information that allow a detection of specific faults. In order to address faults of a complete drive system, characteristic failures of the mechanical part of the drive system are as well presented. Furthermore, the physical forces, which arise during specific faults (i.e. centrifugal, kinematic) are presented along with dominant harmonics in the frequency spectrum. These dominant harmonics are especially important for the determination of a malfunction of the drive. The detection of the particular could be performed with signal processing methods which are tabular summarized for introduction purposes. In order to cover a further industry interest, a cost-effectiveness relation is presented, which describes whether a diagnostic system is appreciative or not. Moreover, most important international standards regarding the safety, health for human and machinery are summarized that are required to be fulfilled in every industrial application. The next subsection is dedicated to the presentation of fault detection methods that include a review of conventional methods for monitoring the conditions of the electric machine. That includes the monitoring of variables that are based on electrical, chemical, mechanical and thermal changes in the induction motor. The last subsection considers the fault detection methods, which are based on utilization of mathematical models. In this kind of fault detection, the model description is utilized to identify changes in the drive system, which then can be used for a potential fault identification procedure. Such mathematical constructs are mainly based on observer, Kalman filters or neural networks. The chapter is concluded with a short summary of the presented sections.

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Kategoria
Publikacja monograficzna
Typ
rozdział, artykuł w książce - dziele zbiorowym /podręczniku w języku o zasięgu międzynarodowym
Język
angielski
Rok wydania
2020

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