Szczegóły publikacji

Opis bibliograficzny

Fault diagnostics of acoustic signals of loaded synchronous motor using SMOFS-25-EXPANDED and selected classifiers — Dijagnostika greške akustičkih signala opterećenog sinkronog motora primjenom SMOFS-25-EXPANDED i odabranih klasifikatora / Adam GŁOWACZ // Tehnički Vjesnik = Technical Gazette ; ISSN 1330-3651. — 2016 — vol. 23 no. 5, s. 1365–1372. — Bibliogr. s. 1370–1372


Autor


Słowa kluczowe

loaded synchronous motorrecognitionfault detectionacoustic signal

Dane bibliometryczne

ID BaDAP101915
Data dodania do BaDAP2016-12-20
Tekst źródłowyURL
DOI10.17559/TV-20150328135652
Rok publikacji2016
Typ publikacjiartykuł w czasopiśmie
Otwarty dostęptak
Creative Commons
Czasopismo/seriaTehnički Vjesnik=Technical Gazette

Abstract

A system of fault diagnostics of loaded synchronous motor was proposed. Proposed system was based on acoustic signals of loaded synchronous motor. A new method of feature extraction SMOFS-25-EXPANDED (shorted method of frequencies selection-25-Expanded) was proposed. Presented method was analysed for 3 classifiers: LDA (Linear Discriminant Analysis), NN (Nearest Neighbour), SOM (Self-organizing Map). Analysis was carried out for real incipient states of loaded synchronous motor. Acoustic signals generated by motor were used in analysis. The following states of motor were analysed: healthy motor, motor with shorted stator coil, motor with shorted stator coil and broken coil, motor with shorted stator coil and two broken coils. These states are caused by natural degradation of rotating synchronous motor. The results of recognition were good. Proposed method of acoustic signal recognition can be used to protect loaded synchronous motors.

Publikacje, które mogą Cię zainteresować

artykuł
Recognition of acoustic signals of loaded synchronous motor using FFT, MSAF-5 and LSVM / Adam GŁOWACZ // Archives of Acoustics ; ISSN 0137-5075. — 2015 — vol. 40 no. 2, s. 197–203. — Bibliogr. s. 202–203
artykuł
Fault diagnostics of synchronous motor based on analysis of acoustic signals with the use of Haar Wavelet Transform and Nearest Mean classifier / Adam GŁOWACZ, Zygfryd GŁOWACZ [et al.] // Journal of Modern Engineering ; ISSN 2544-7327. — 2017 — vol. 1 no. 1, s. 4–8. — Bibliogr. s. 7–8, Abstr.