Weak signal detection based on two dimensional stochastic resonance


Barbini, L., Cole, M. O. T., Hillis, A. J. and Du Bois, J. L., 2015. Weak signal detection based on two dimensional stochastic resonance. In: Signal Processing Conference (EUSIPCO), 2015, 2015-08-31 - 2015-09-04. IEEE.

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    The analysis of vibrations from rotating machines gives information about their faults. From the signal processing perspective a significant problem is the detection of weak signals embedded in strong noise. Stochastic resonance (SR) is a mechanism where noise is not suppressed but exploited to trigger the synchronization of a non-linear system and in its one-dimensional form has been recently applied to vibration analysis. This paper focuses on the use of SR in a two-dimensional system of gradient type for detection of weak signals submerged in Gaussian noise. Comparing the traditional one-dimensional system and the two-dimensional used here, this paper shows that the latter can offer a more sensitive means of detection. An alternative metric is proposed to assess the output signal quality, requiring no a priori knowledge of the signal to be detected, and it is shown to offer similar results to the more conventional signal-to-noise ratio.


    Item Type Conference or Workshop Items (UNSPECIFIED)
    CreatorsBarbini, L., Cole, M. O. T., Hillis, A. J. and Du Bois, J. L.
    DepartmentsFaculty of Engineering & Design > Mechanical Engineering
    Research CentresCentre for Power Transmission & Motion Control
    ?? WIRC ??
    ID Code47744


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