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Semi-Supervised Learning for Diagnosing Faults in Electromechanical Systems
Başlık:
Semi-Supervised Learning for Diagnosing Faults in Electromechanical Systems
Yazar:
Hallaji, Ehsan, author.
ISBN:
9780438000995
Yazar Ek Girişi:
Fiziksel Tanımlama:
1 electronic resource (109 pages)
Genel Not:
Source: Masters Abstracts International, Volume: 57-06M(E).
Advisors: Mehrdad Saif.
Özet:
Safe and reliable operation of the systems relies on the use of online condition monitoring and diagnostic systems that aim to take immediate actions upon the occurrence of a fault. Machine learning techniques are widely used for designing data-driven diagnostic models. The training procedure of a data-driven model usually requires a large amount of labeled data, which may not be always practical. This problem can be untangled by resorting to semi-supervised learning approaches, which enables the decision making procedure using only a few numbers of labeled samples coupled with a large number of unlabeled samples. Thus, it is crucial to conduct a critical study on the use of semi-supervised learning for the purpose of fault diagnosis.
Another issue of concern is fault diagnosis in non-stationary environments, where data streams evolve over time, and as a result, model-based and most of the data-driven models are impractical. In this work, this has been addressed by means of an adaptive data-driven diagnostic model.
Notlar:
School code: 0115
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Yer Numarası | Demirbaş Numarası | Shelf Location | Lokasyon / Statüsü / İade Tarihi |
---|---|---|---|
XX(694020.1) | 694020-1001 | Proquest E-Tez Koleksiyonu | Arıyor... |
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