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Optimization of the Spectrum of Digital Diagnostic Signals to Improve the Analysis of Harmonic Parameters Using Resampling Algorithms

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Analysis of harmonic parameters and detection of foreign frequencies in diagnostic signals, which are most often interpreted as fault results, may be problematic because of the spectral leakage effect. When the signal contains only the fundamental frequency and harmonics, it is possible to adjust its spectral resolution to eliminate any distortions for regular frequencies. The paper discusses the influence of resampling distortions on the quality of spectral resolution optimization in diagnostic signals, recorded digitally for objects in a steady state. The method effectiveness is measured with the use of a synthetic signal generated from an analog prototype whose parameters are known. In order to achieve low values of harmonic amplitude errors in the diagnostic signal, a high quality resampling algorithm should be used, therefore the analysis of distortions generated by four popular reasampling methods is performed. Errors are measured for test signals containing different spectral structures. Finally, the results of the test of the analyzed method in practical applications are presented.
Rocznik
Strony
335--341
Opis fizyczny
Bibliogr. 11 poz., il., tab., wykr.
Twórcy
  • West Pomeranian University of Technology, Szczecin, Poland
  • West Pomeranian University of Technology, Szczecin, Poland
Bibliografia
  • [1] R. G. Lyons, Understanding digital signal processing, New Jersey, USA: Prentice Hall 2010.
  • [2] S. J. Orfanidis, Introduction to signal processing, Upper Saddle River, USA: Prentice Hall 2010.
  • [3] D. Borkowski, R. Dlugosz, M. Szulc and, P. Skruch, Multi-Rate Signal Processing Issues in Active Safety Algorithms, SAE Technical Paper, 2016.
  • [4] A. Muhammad, On the implementation of integer and non-integer sampling rate conversion, Link¨oping, Sweden: Link¨oping University Electronic Press, 2012.
  • [5] M. Jarmołowicz and E. Kornatowski, Method of vibroacoustic signal spectrum optimization in diagnostics of devices, 2017 International Conference on Systems, Signals and Image Processing (IWSSIP), IEEE Xplore, 2017
  • [6] V. Parsa and D. G. Jamieson, Acoustic Discrimination of Pathological Voice, Journal of Speech, Language, and Hearing Research, 2001.
  • [7] J. Laaksonen, I. J. Loewen, J. Wolfaardt, J. Rieger, H. Seikaly and J. Harr, Speech After Tongue Reconstruction and Use of a Palatal Augmentation Prosthesis: An acoustic case study, Ottawa, Canada: Canadian Journal of Speech-Language Pathology and Audiology, 2009.
  • [8] S. Sanei and J. Chambers, EEG signal processing, Cardiff University, England: John Wiley & Sons, Inc., 2007.
  • [9] E. Kornatowski, Mechanical-condition assessment of power transformer using vibroacoustic analysis, Key Engineering Materials 2012.
  • [10] W. Li, F. Gu, D. A. Ball, A. Y. T. Leung and C. E. Phipps, A study of the noise from diesel engines using the independent component analysis, Mechanical Systems and Signal Processing 2001.
  • [11] L. Barelli, G. Bidini, C. Buratti, R. Mariani, Diagnosis of internal combustion engine through vibration and acoustic pressure non-intrusive measurements, Applied Thermal Engineering 2009.
Uwagi
Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2018).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-518cd07a-eb54-43f3-9568-1160cc47a427
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