Skip to the main content

Original scientific paper

https://doi.org/10.17559/TV-20150328135652

Fault diagnostics of acoustic signals of loaded synchronous motor using SMOFS-25-EXPANDED and selected classifiers

Adam Glowacz orcid id orcid.org/0000-0003-0546-7083 ; AGH University of Science and Technology, Faculty of Electrical Engineering, Automatics, Computer Science and Biomedical Engineering, Department of Automatics and Biomedical Engineering, al. A. Mickiewicza 30, 30-059 Krakow, Poland


Full text: croatian pdf 1.133 Kb

page 1365-1372

downloads: 532

cite

Full text: english pdf 1.133 Kb

page 1365-1372

downloads: 479

cite


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.

Keywords

acoustic signal; fault detection; loaded synchronous motor; recognition

Hrčak ID:

167495

URI

https://hrcak.srce.hr/167495

Publication date:

13.10.2016.

Article data in other languages: croatian

Visits: 2.814 *