Proposal for the Diagnosis of Railway Engines

• Autorzy: Dziurdź J.
• Języki publikacji: EN

Abstrakty

EN

This article contains a proposal of another kind of analysis than the traditional time-frequency analysis (see Lee and White, 1999; Mallat, 1989; Uchikawa et all, 2002; Wang and McFadden, 1993). The proposed method increases the resolution of the spectral analysis on the frequency scale down to values lower than can be obtained while using the Fourier transform in a situation when it is not possible to obtain samples with sufficient duration, e. g. in not fully stationary motion (when slowly changing disturbance of rotational speed occurs). During many years of research on railway engines, the authors often came across the problem of maintaining over a longer period (for the time required for the registration of signals) of constant speeds. Failure to fulfit this requirement either hinders or makes the use of simple methods of digital analysis of stationary signals in a diagnostic task impossible. In such a situation we can choose from among two ways to proceed: - for a long time of averaging we have insufficient mapping of main spectral vibrations (spectral line broadening), - for a very short time sample (limited to the part of run registered for a constant rotational speed) we get insufficient analytical resolution. A good example of such problems is the research related to the power units of vehicles. Since the length of the registered signal does not always allow the obtaining the relevant analytical resolution, the authors decided to use some of the properties of the ordinary coherence function to increase the digital precision of the signal analysis. As an example of applying the proposed method we present the results of vibration measurements of the casing of a bearing in a power unit of an electrical locomotive (EZT) of EN-57 type. The power unit consists of an electrical, direct current motor and of a one-stage helical reduction gear, whose slow speed shaft serves at the same time as the axle of the driving wheels. For the digital registration of acceleration of vibration at various points of the EZT locomotive we used the ROADRUNNER analyser from LMS. The numerical analysis was performed no MATLAB software.

• Wydawca: Oficyna Wydawnicza Politechniki Warszawskiej
• Czasopismo: Machine Dynamics Problems
• Rocznik: 2002
• Tom: Vol. 26, No. 2/3
• Strony: 43--55
• Opis fizyczny: Bibliogr. 9 poz.

Twórcy

autor

Dziurdź J.

• Warsaw University of Technology

Bibliografia

• Bendat, J.S., Piersol, A.G., 1980, Engineering Applications of Correlation and Spectral Analysis, John Wiley & Sons Inc.
• Dąbrowski, Z., Dziurdź, J., Deuszkiewicz, P., 1999, On the Applicability of Methods of Separating Signais Using Coherence, Proceedings of the 6th International Congress on Sound and Vibration, Copenhagen-Denmark, 2845-2850.
• Dąbrowski, Z., Dziurdź, J., Tomaszek, S., 2000, New Concepts of Using Coherence Function in Noise Propagation Modeling, Proceedings of the International Conference on Applied Mechanics „SALAM 2000", Durban-South Africa, 306-311.
• Dąbrowski, Z., Dziurdź, J., 2000, Improving the Accuracy of the Results of spectrum Analysis in a Diagnostic Task, Proceeding of the II International Congress of Technical Diagnostics, Warsaw, Poland, 93.
• Lee, S.K., White, P.R., 1999, Detection of impulsive sound and vibration signal using the sliced Wigner fourth order moment spectra (SWFOMS), INTER-NOISE 99, Florida, USA.
• Mallat, S., 1989, A Theory for Multiresolution Signal Decomposition: The Wavelet representation, IEEE Transaction on Pattern Analysis and Machine Intelligence, 11, No 7, 674-693.
• Randall, R.B., 1987, Frequency Analysis, Brüel&Kjaer.
• Uchikawa, H., Shi, O., Ando, S., Saegusa, H., 2002, Salvaging transient measurement signals with serious flaws using wavelet analysis, Proceedings of Sixth International Conference on Rotor Dynamics, Sydney, Australia.
• Wang, W.J., McFadden P.D., 1993, Early detection of gear failure by vibration analysis Calculation of the time-frequency distribution, Mechanical Systems and Signal Processing, 7(3), 193-204.