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Analiza dynamiki wirnika pionowego wirówki acww1000 w aspekcie diagnozowania

100%

Zachwieja J.

Diagnostyka

2005

tom Vol. 33

301--306

Przedmiotem niniejszej pracy jest analiza dynamiki wirówki ACWW1000 prowadzona pod kątem interpretacji uzyskanego w trakcie badań diagnostycznych urządzenia widma amplitudowo-częstotliwościowego, ujawniającego wyraźny wzrost drgań maszyny przy częstotliwości obrotowej 29Hz. Istnieje przypuszczenie, że eksploatacyjna prędkość obrotowa wirówki jest bliska prędkości krytycznej przy której może pojawić się precesja przeciwbieżna i towarzysząca jej niestabilność ruchu.

An object of the present work is the analysis of the ACWW1000 centrifuge dynamics, led with the aim of the interpreting an amplitude-frequency spectrum, obtained during system diagnostic's examinations, revealing a meaningful increase of system's vibrations in the rotational frequency 29Hz. There is an supposition, that an operating rotational speed of the centrifuge is near to the critical speed at which there appears a backward precession and a motion instability.

Wavelet Based Signal Demodulation Technique for Bearing Fault Detection

84%

Klepka A.

2011

tom Vol. 15, nr 4

61--69

Diagnostics of rolling elements under varying operational conditions, where disturbances and other rotating elements have strong influence on correctness of analysis, requires engagement of advanced signal processing techniques. Extraction of signal components generated by bearing faults has been proven to be an exceptionally promising method for rolling element bearing fault detection. In this paper, wavelet signal demodulation diagnostic techniques is presented. The method is based on the wavelet transform as a method of signal demodulation. Properties of time–frequency representation of the signal enables extraction of typical damage signatures from the signal. First step of this method is a wavelet filtration, which uses Continuous Wavelet Transform (CWT). For this transformation, the Morlet wavelet function has been used. Next, the envelope function of a decoupled frequency component is estimated from wavelet coefficients. Finally, the Discrete Wavelet Transform (DWT) has been used as a post–processing method.

On the detection of distributed roughness on ball bearings via stator current energy: experimental results

84%

Curcuru G. , Cocconcelli M. , Immovilli F. , Rubini R.

Diagnostyka

2009

tom nr 3(51)

17-21

This paper deals with the detection of distributed roughness on ball-bearings mounted on electric motors. Most of the literature techniques focus on the early detection of localized faults on bearing (e.g. on the outer ring) in order to determine the bearing life and to plan the bearing replacing. Localized faults can be detected because they have characteristic signatures which is revealed in the frequency spectrum of the vibration signal acquired by an external sensor, e.g. accelerometer. Unfortunately other faults exist which do not have a characteristic signatures and then they could not be foreseen accurately: e.g. the distributed roughness. In this paper the motor stator current energy is proposed as a fault indicator to identify the presence of the distributed roughness on the bearing. Moreover an orthogonal experiment is set to analyse, through a General Linear Model (GLM), the dependencies of the current energy to the roughness level, and two environmental conditions: the motor velocity and the loads applied externally. ANOVA investigates the statistical significance of the considered factors.