Fault diagnostics of acoustic signals of loaded synchronous motor using SMOFS-25-EXPANDED and selected classifiers
Adam Glowacz
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
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, br. 5, 2016, str. 1365-1372. https://doi.org/10.17559/TV-20150328135652. Citirano 03.03.2021.
Chicago 17th Edition Glowacz, Adam. "Fault diagnostics of acoustic signals of loaded synchronous motor using SMOFS-25-EXPANDED and selected classifiers." Tehnički vjesnik 23, br. 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), str. 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 [pristupljeno 03.03.2021.];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, br. 5, str. 1365-1372, 2016. [Online]. https://doi.org/10.17559/TV-20150328135652
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, br. 5, 2016, str. 1365-1372. https://doi.org/10.17559/TV-20150328135652. Citirano 03.03.2021.
Chicago 17th Edition Glowacz, Adam. "Dijagnostika greške akustičkih signala opterećenog sinkronog motora primjenom SMOFS-25-EXPANDED i odabranih klasifikatora." Tehnički vjesnik 23, br. 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), str. 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 [pristupljeno 03.03.2021.];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, br. 5, str. 1365-1372, 2016. [Online]. https://doi.org/10.17559/TV-20150328135652
Sažetak 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.