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Analysis of Solid Contamination in Ball Bearing Through Acoustic Emission Signals

Sheriff K. A. I., Hariharan V., Kannan T.

Archives of Metallurgy and Materials

2017

Vol. 62, iss. 3

1871--1874

Acoustic emission is one of the effective techniques used for the condition monitoring of rolling element bearings. Contamination is one of the major reasons for bearing early failure due to presence of solid particle in lubricant grease. In most cases, outer race is stationary and the inner race is attached to the rotating assembly. The lubrication is very essential for the bearing to perform under various demanding conditions. The main aim of this project is to analyze the effect of contamination of lubricant by solid particles on the dynamic behavior of rolling bearing. Green sand at three concentration levels 5%, 15%, 25% and different particle sizes 75 μm, 106 μm and 150μm is used to contaminate the lubricant. Experimental tests have been performed for different load and speed condition in good and contaminated ball bearings lubricated with grease. The trends in the amount of AE waves affected by the contamination of the grease were determined. Acoustic emission signals were analyzed in terms of RMS, kurtosis, and peak-peak.

Estymacja wartości parametrów sygnału na podstawie dostępnej wiedzy

Smołalski G.

Pomiary Automatyka Kontrola

2014

R. 60, nr 12

1140--1143

Jako menzurand przyjęto jeden z możliwych parametrów segmentu sygnału. Przedstawiono metodę jednolitego uwzględniania wszelkich dostępnych informacji o sygnale. Wykorzystano reprezentację sygnału w skończenie-wymiarowej przestrzeni liczbowej. Rozważono przypadek ogólny, gdy parametr mierzony nie jest równy parametrowi estymowanemu. Przeanalizowano użyteczność danej informacji o sygnale w estymacji określonego jego parametru. Przedstawiono przykład ilustrujący stosowanie zaproponowanej metody.

In this paper a measurand is assumed to be some particular parameter of the signal segment - the estimated parameter E (Section 2). A model of measurement is formulated in which all the information items available about the investigated signal (both those available a priori and those provided by measurement) are uniformly taken into account during the evaluation of the uncertainty of E. All information items are assumed to be certain. It is shown (Section 3) that the investigated signal segment can be interpreted as a point in a finite-dimensional numerical space. With each available information item corresponds in that space a specific constraint (1) of possible signals. Finding out the global extremes of the estimated parameter over the resulting set of possible signals, gives the prior uncertainty interval (3) according to E (Section 4). Measurement of some additional parameter M continues restricting the prior set of possible signals. The uncertainty (4), remaining after the measurement of M, results from a structural discrepancy between parameters E and M. One of measurability necessary conditions is presented in Section 6. It enables an easy rejection of such measured parameters M that cannot be useful for the estimation of E. Finally, an illustrative example for the method has been provided in Section 7.