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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 icon 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

Fulltext: english, pdf (1 MB) pages 1365-1372 downloads: 250* cite
APA 6th Edition
Glowacz, A. (2016). Fault diagnostics of acoustic signals of loaded synchronous motor using SMOFS-25-EXPANDED and selected classifiers. Tehnički vjesnik, 23 (5), 1365-1372. https://doi.org/10.17559/TV-20150328135652
MLA 8th Edition
Glowacz, Adam. "Fault diagnostics of acoustic signals of loaded synchronous motor using SMOFS-25-EXPANDED and selected classifiers." Tehnički vjesnik, vol. 23, no. 5, 2016, pp. 1365-1372. https://doi.org/10.17559/TV-20150328135652. Accessed 23 Apr. 2021.
Chicago 17th Edition
Glowacz, Adam. "Fault diagnostics of acoustic signals of loaded synchronous motor using SMOFS-25-EXPANDED and selected classifiers." Tehnički vjesnik 23, no. 5 (2016): 1365-1372. https://doi.org/10.17559/TV-20150328135652
Harvard
Glowacz, A. (2016). 'Fault diagnostics of acoustic signals of loaded synchronous motor using SMOFS-25-EXPANDED and selected classifiers', Tehnički vjesnik, 23(5), pp. 1365-1372. https://doi.org/10.17559/TV-20150328135652
Vancouver
Glowacz A. Fault diagnostics of acoustic signals of loaded synchronous motor using SMOFS-25-EXPANDED and selected classifiers. Tehnički vjesnik [Internet]. 2016 [cited 2021 April 23];23(5):1365-1372. https://doi.org/10.17559/TV-20150328135652
IEEE
A. Glowacz, "Fault diagnostics of acoustic signals of loaded synchronous motor using SMOFS-25-EXPANDED and selected classifiers", Tehnički vjesnik, vol.23, no. 5, pp. 1365-1372, 2016. [Online]. https://doi.org/10.17559/TV-20150328135652
Fulltext: croatian, pdf (1 MB) pages 1365-1372 downloads: 189* cite
APA 6th Edition
Glowacz, A. (2016). Dijagnostika greške akustičkih signala opterećenog sinkronog motora primjenom SMOFS-25-EXPANDED i odabranih klasifikatora. Tehnički vjesnik, 23 (5), 1365-1372. https://doi.org/10.17559/TV-20150328135652
MLA 8th Edition
Glowacz, Adam. "Dijagnostika greške akustičkih signala opterećenog sinkronog motora primjenom SMOFS-25-EXPANDED i odabranih klasifikatora." Tehnički vjesnik, vol. 23, no. 5, 2016, pp. 1365-1372. https://doi.org/10.17559/TV-20150328135652. Accessed 23 Apr. 2021.
Chicago 17th Edition
Glowacz, Adam. "Dijagnostika greške akustičkih signala opterećenog sinkronog motora primjenom SMOFS-25-EXPANDED i odabranih klasifikatora." Tehnički vjesnik 23, no. 5 (2016): 1365-1372. https://doi.org/10.17559/TV-20150328135652
Harvard
Glowacz, A. (2016). 'Dijagnostika greške akustičkih signala opterećenog sinkronog motora primjenom SMOFS-25-EXPANDED i odabranih klasifikatora', Tehnički vjesnik, 23(5), pp. 1365-1372. https://doi.org/10.17559/TV-20150328135652
Vancouver
Glowacz A. Dijagnostika greške akustičkih signala opterećenog sinkronog motora primjenom SMOFS-25-EXPANDED i odabranih klasifikatora. Tehnički vjesnik [Internet]. 2016 [cited 2021 April 23];23(5):1365-1372. https://doi.org/10.17559/TV-20150328135652
IEEE
A. Glowacz, "Dijagnostika greške akustičkih signala opterećenog sinkronog motora primjenom SMOFS-25-EXPANDED i odabranih klasifikatora", Tehnički vjesnik, vol.23, no. 5, pp. 1365-1372, 2016. [Online]. https://doi.org/10.17559/TV-20150328135652

Abstracts
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

[croatian]

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