Sideband extraction on the vibration power spectra for the traction gearboxes of electric trains (original) (raw)
2018, Collected scientific works of Ukrainian State University of Railway Transport
The paper deals with the time-synchronous averaging technique of vibration signals for extraction of the features of the technical state of electric train traction gearboxes. Simulation of the vibration of the faultless gear mesh, and gearwheel with a cracked tooth and strong deterministic component was carried out. The rotation frequencies of gearwheel and pinion, and the mesh frequency are clear visible on the vibration power spectrum. Taking into account the poor visibility of the sidebands around mesh frequency on the power spectra, the time-synchronous averaging technique enhances the sidebands, the width of which corresponds to the gearwheel rotation frequency and influences weakening of the sidebands of the faultless pinion. During the experimental research the traction gearbox vibration of electric train was acquired on the test bench in a depot, and the calculated power spectrum has not identified sidebands and mesh frequency. After the time-synchronous average within 18 revolutions for the pinion and gearwheel frequency, the vibration power spectra were acquired. The time-synchronous average technique eliminates random and non-synchronous components while keeping the frequency components that are synchronous to the rotating frequency of the pinion and gearwheel of the traction gearbox. On the vibration power spectra in the vicinity of the mesh frequency the strong sidebands are visible, and they do not coincide with the previously calculated rotation frequencies, which means the absence of gearwheel faults. At the vibration power spectrum for the pinion there are six sidebands in the vicinity of the meshing frequency that coincide with the previously calculated pinion rotation frequencies, which means the presence of localized or distributed faults for the pinion. Disassembling of the traction gearbox shows a crack of the rolling bearing inner race and faultless state of the gear mesh. It was established that the sensitivity of the time-synchronous average technique makes it possible to identify not only localized faults extraction but also distributed faults such as eccentricity and misalignment of the pinion shaft through the modulation of the sidebands on vibration power spectra of the gearwheel.
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Collection of scientific works of the Ukrainian State University of Railway Transport, 2019
The paper deals with the property of discrete wavelet transform based on the multiresolution analysis feature to identify different types of the gear and bearing vibration. The direct analysis of the vibration time series by the use of conventional statistical measures, such as mean, root mean square, standard deviation, is not always useful due to the complexity of the signal. It was proposed to choose the best mother wavelet which is able to identify the transients in vibration signal according to the calculated minimum value of Shannon entropy, which quantifies the level of uncertainty of a given vibration time series. The main idea is that when a bearing is healthy, it will produce low amplitude random vibration with a uniform-like probability mass function and as the fault occurs and progresses some probability mass function component will be prevalent with a higher probability of occurrence. The chosen Daubechies wavelet of the 4-th order has decomposed the acquired vibration signal of the traction gearbox of electric train into approximated and detailed coefficients on four decomposition scales with further reconstruction of the signals on the appropriate scales according to the above-mentioned coefficients. The autocorrelation was applied for the detection of deterministic and random components in the reconstructed signals through evaluation of the impulse periodicities of the reconstructed signals according to the detailed coefficients at all scales and has taken the sinusoidal shape for the reconstructed signals according to the approximated coefficients. It was established that a deterministic vibration component dominates and there are no bearing damage features in the reconstructed signals according to the approximated coefficients due two strong gearmesh harmonics. The presence of impulse periodicity on the reconstructed signals according to the detailed coefficients at the second decomposition scale is possible to monitor due to the correlogram, which can be explained by the periodic contact of the damaged element with other elements during their rotation in bearing. The kurtosis is applied as a reliable tool for the frequency band selection where the bearing vibration has the strongest excitation. Кeywords: bearing, impulse, spectrum, traction gearbox, vibration, wavelet.
Application of the spectral kurtosis for the traction gearbox vibrodiagnostics of an electric train
Technical Sciences and Technologies, 2019
Urgency of the research. It is established that introduction of effective vibrodiagnostics techniques, which are capable of the early identification of the traction gearbox faults of electric trains, is a relevant task. Target setting. The vibrodiagnostics of mechanical units of electric trains is known to be a trustworthy technique that is able to extract impulsive components with a periodic repetition in accordance with the revolution of the faulty parts of gears or bearings. The main problem is development of effective methods for the noise elimination and identification of the technical condition features of gears and bearings. Actual scientific researches and issues analysis. Recently the calculation of the kurtosis index has taken a leading role in the extraction of weak periodic impulses. However, unclear recommendations on increasing the accuracy of these results needed improvement, which led to emergence of the spectral kurtosis method based on the filters for the reconstruction of random signals with a high level of additive stationary noise. Uninvestigated parts of general matters defining. The identification of a bearing vibration component and the influence of a gear component in high frequency band on it were not clearly understood. The research objective. The objective of the paper is identification of the informative frequency band of excited bearing vibration by means of the spectral kurtosis method. The statement of basic materials. The paper selects the best window length of the Short-Time Fourier Transform by means of the spectral kurtosis method, which allows to identify the highest level of the spectral kurtosis and to find the proper frequency band. Conclusions. By means of Wiener filter, the broadband structures of the traction gearboxes vibration of electric trains were identified, and the frequency band with excited resonance component of the bearing vibration was registered. Keywords: bearing, frequency, gear, electric train, spectral kurtosis, vibration.
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