Paper Title:
Acoustic Emission Monitoring of Mechanical Seals Using MUSIC Algorithm Based on Higher Order Statistics

This paper presents the use of the MUSIC algorithm improved by higher order statistics (HOS) to extract key features from the noisy acoustic emission (AE) signals. The low signal-to-noise ratio of AE signals has been identified as a main barrier to the successful condition monitoring of pump mechanical seals. Since HOS methods can effectively eliminate Gaussian noise, it is possible in theory to identify a change in seal conditions from AE measurements even with low signal-to-noise ratios. Tests conducted on a test rig show that the developed algorithm can successfully detect the AE signal generated from the friction of seal faces under noisy conditions.

Key Engineering Materials (Volumes 413-414)
Edited by
F. Chu, H. Ouyang, V. Silberschmidt, L. Garibaldi, C.Surace, W.M. Ostachowicz and D. Jiang
Y. B. Fan, F. S. Gu, A. Ball, "Acoustic Emission Monitoring of Mechanical Seals Using MUSIC Algorithm Based on Higher Order Statistics", Key Engineering Materials, Vols. 413-414, pp. 811-816, 2009
Online since
June 2009
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