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Wyświetlanie 1-3 z 3
Tytuł:
The identification of piston-cylinder clearance using time-frequency methods
Autorzy:
Flekiewicz, M.
Fabiś, P.
Madej, H.
Powiązania:
https://bibliotekanauki.pl/articles/245755.pdf
Data publikacji:
2009
Wydawca:
Instytut Techniczny Wojsk Lotniczych
Tematy:
fault diagnosis
engine vibration
Gabor Spectrogram
Adaptive Spectrogram
Opis:
A fault recognition technique for the internal combustion engines using time-frequency representations of vibration signal has been presented in this paper. Engine block vibration results as a sum of many excitations mainly connected with engine speed and their intensity increases with the appearance of a fault or in case ofhigher engine elements wearing. In this paper an application of acceleration signals for the estimation of the influence of piston skirt clearance on diesel engine block vibrations has been described. Engine body accelerations registered for three simulated cases representing piston skirt clearance variations were an object of preliminary analysis. The presented procedures were applied to vibration and pressure signals acquired for a 0.5 dm3 Ruggerini, air cooled diesel engine. reciprocating machines are difficult to diagnose using traditional frequency domain techniques due to the fact they generale transient vibrations. In the experiments that were conducted Gabor Analysis and Adaptive Spectrogram has been chosen The Gabor spectrogram is a powerful tool for on-line monitoring and diagnosis of combustion process. There are important features of the vibration signal that are sensitive to the change of IC engine condition. For that reason the DWT transform was applied. Based on the results, authors propose detection and piston skirt clearance monitoring algorithm.
Źródło:
Journal of KONES; 2009, 16, 4; 93-103
1231-4005
2354-0133
Pojawia się w:
Journal of KONES
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Adaptacyjna analiza czasowo-częstotliwościowa niestacjonarnego sygnału pomiarowego
Adaptive time - frequency analysis of a non-stationary measuring signal
Autorzy:
Pałczyńska, B.
Powiązania:
https://bibliotekanauki.pl/articles/151732.pdf
Data publikacji:
2012
Wydawca:
Stowarzyszenie Inżynierów i Techników Mechaników Polskich
Tematy:
sygnały niestacjonarne
spektrogram adaptacyjny
algorytm pogoni za dopasowaniem
non-stationary signals
adaptive spectrogram
matching pursuit algorithm
Opis:
W artykule zaprezentowano wirtualny analizator czas-częstotliwość zaprojektowany w środowisku programowania LabVIEW, w którym zaimplementowano metodę adaptacyjną analizy czasowo-częstotliwościowej opartą na algorytmie pogoni za dopasowaniem (ang. matching pursuit MP). Przedstawiono wyniki analiz sygnału pomiarowego, reprezentującego poziom natężenia wolnozmiennego pola magnetycznego, zarejestrowanego w otoczeniu okrętowych odbiorników dużej mocy.
In the paper there is presented a virtual time-frequency analyzer designed with use of LabVIEW programming environment, in which there is implemented an adaptive method of time-frequency analysis based on the matching pursuit algorithm (Fig. 1). Matching pursuit (MP) is an iterative algorithm using a redundant dictionary of functions in order to select the functions, which best match the signal components. Thanks to the varying window size and modulation frequency, MP enables an adaptive (i.e. fitting local structures) signal representation. Linear Gaussian chirplets were used as the elementary functions. Measuring signals are the sum of time-limited waveforms occurring at different time instants and having different bandwidths (Fig. 2). The application of the time-frequency adaptive method certainly provides a significantly better joint time-frequency resolution in comparison with other quadratic joint time-frequency distributions. The analysis of the measuring signal of low-varying magnetic field recorded in the surroundings of high power ship receivers is presented (Figs. 3, 4, 5). Estimation of the usefulness of the implemented method for measurements of the non-stationary magnetic field intensity of ship electromagnetic environment is performed. It is shown that the adaptive time-frequency-domain representation of the magnetic field intensity was successfully applied to determine, with some time resolution, the moments when the analyzed signal components of different frequencies occurred.
Źródło:
Pomiary Automatyka Kontrola; 2012, R. 58, nr 11, 11; 934-936
0032-4140
Pojawia się w:
Pomiary Automatyka Kontrola
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Specific emitter identification using geometric features of frequency drift curve
Autorzy:
Zhao, Y.
Wui, L.
Zhang, J.
Li, Y.
Powiązania:
https://bibliotekanauki.pl/articles/200575.pdf
Data publikacji:
2018
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
specific emitter identification
geometric features
frequency drift
adaptive fractional spectrogram
support vector machine
emiter
cechy geometryczne
dryf częstotliwości
spektrogram
Opis:
Specific emitter identification (SEI) is a technique for recognizing different emitters of the same type which have the same modulation parameters. Using only the classic modulation parameters for recognition, one cannot distinguish different emitters of a same type. To solve the problem, new features urgently need to be developed for recognition. This paper focuses on the common phenomenon of frequency drift, defines geometric features of frequency drift curve and, finally, proposes a practical algorithm of specific emitter identification using the geometric features. The proposed algorithm consists of three processes: instantaneous frequency estimation based on the adaptive fractional spectrogram, feature extraction of frequency drift curve based on geometric methods for describing a curve and recognition process based on support vector machine. Simulation results show that the identification rate is generally more than 98% above –5 dB of signal to noise ratio (SNR), and real data experiment verifies the practical performance of the proposed algorithm.
Źródło:
Bulletin of the Polish Academy of Sciences. Technical Sciences; 2018, 66, 1; 99-108
0239-7528
Pojawia się w:
Bulletin of the Polish Academy of Sciences. Technical Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-3 z 3

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