Abstract
The instrumented tracking and telemetry ship with a ship-borne satellite antenna (SSA) is the critical device to ensure high quality of space exploration work. To effectively detect mechanical anomalies that can lead to unexpected downtime of the SSA, an ensemble multiwavelet (EM) is presented for identifying the anomaly related incipient-signatures within the measured dynamic signals. Rather than using a predetermined basis as in a conventional multiwavelet, an EM optimizes the matching basis which satisfactorily adapts to the anomaly related incipient-signatures. The construction technique of an EM is based on the conjunction of a two-scale similarity transform (TST) and lifting scheme (LS). For the technique above, the TST improves the regularity by increasing the approximation order of multiscaling functions, while subsequently the LS enhances the smoothness and localizability via utilizing the vanishing moment of multiwavelet functions. Moreover, combining the Hilbert transform with EM decomposition, we identify the incipient-signatures induced by the mechanical anomalies from the measured dynamic signals. A numerical simulation and two successful applications of diagnosis cases (a planetary gearbox and a roller bearing) demonstrate that the proposed technique is capable of dealing with the challenging incipient-signature identification task even though spectral complexity, as well as the strong amplitude/frequency modulation effect, is present in the dynamic signals.
Published Version
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