Szczegóły publikacji
Opis bibliograficzny
Non-clustering method for autmatic selection of machine operational states / Adam JABŁOŃSKI, Tomasz BARSZCZ, Piotr WICIAK // W: Advances in Condition Monitoring of Machinery in Non-stationary Operations : proceedings of the third international conference on Condition Monitoring of Machinery in Non-stationary Operations CMMNO 2013 / eds. Giorgio Dalpiaz, [et al.]. — Berlin ; Heidelberg : Springer-Verlag, cop. 2014. — (Lecture Notes in Mechanical Engineering ; ISSN 2195-4356). — ISBN: 978-3-642-39347-1; e-ISBN: 978-3-642-39348-8. — S. 419–427. — Bibliogr., Abstr.
Autorzy (3)
Słowa kluczowe
Dane bibliometryczne
| ID BaDAP | 104138 |
|---|---|
| Data dodania do BaDAP | 2017-02-20 |
| DOI | 10.1007/978-3-642-39348-8_36 |
| Rok publikacji | 2014 |
| Typ publikacji | materiały konferencyjne (aut.) |
| Otwarty dostęp |  |
| Konferencja | Third international conference on Condition Monitoring of Machinery in Non-Stationary Operations |
| Czasopismo/seria | Lecture Notes in Mechanical Engineering |
Abstract
A reliable evaluation of technical condition of machinery working under non-stationary conditions requires a rigorous tracking of operational parameters. Therefore, modern condition monitoring systems (CMS) enable reading and registering of process parameters (e. g. speed, load, pressure, etc.) in parallel with acquisition of vibroacoustic signals. Although few tries have been undertaken to develop state-free analysis of vibration signals, currently installed systems still do rely on state-preclassified data. The paper shows how the process, referential data might be automatically transformed into proposition of optimal machine operational states in terms of their number and their range. As indicated by the title, the paper shows common pitfalls coming from implementation of popular clustering approach. The proposed algorithm illustrates is verified on real data from a pitch-controlled wind turbine.
