Abstract
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.
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