@ARTICLE{Glowacz_Adam_Diagnostics_2014,
 author={Glowacz, Adam},
 volume={vol. 39},
 number={No 2},
 journal={Archives of Acoustics},
 pages={189-194},
 howpublished={online},
 year={2014},
 publisher={Polish Academy of Sciences, Institute of Fundamental Technological Research, Committee on Acoustics},
 abstract={In industrial processes electrical motors are serviced after a specific number of hours, even if there is a need for service. This led to the development of early fault diagnostic methods. Paper presents early fault diagnostic method of synchronous motor. This method uses acoustic signals generated by synchronous motor. Plan of study of acoustic signal of synchronous motor was proposed. Two conditions of synchronous motor were analyzed. Studies were carried out for methods of data processing: Line Spectral Frequencies and K-Nearest Neighbor classifier with Minkowski distance. Condition monitoring is useful to protect electric motors and mining equipment. In the future, these studies can be used in other electrical devices.},
 type={Artykuły / Articles},
 title={Diagnostics of Synchronous Motor Based on Analysis of Acoustic Signals with the use of Line Spectral Frequencies and K-nearest Neighbor Classifier},
 URL={http://ochroma.man.poznan.pl/Content/101445/PDF/04_paper.pdf},
 doi={10.2478/aoa-2014-0022},
 keywords={acoustic signal, pattern analysis, synchronous motor, diagnostics},
}