Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/22737
Title: On weak unsteady signal detection using statistical tests
Authors: Chan, CM
Tang, SK 
Wong, H 
Lee, WL 
Keywords: Machine monitoring
Signal detection
Statistics
Issue Date: 2012
Publisher: Pergamon Press
Source: Applied acoustics, 2012, v. 73, no. 2, p. 164-172 How to cite?
Journal: Applied acoustics 
Abstract: Two statistical tests, namely the Jarque-Bera and the D'Agostino tests, originally adopted for checking data normality are used to recover the initialization of an exponentially growing wave embedded inside a stationary background noise in the present investigation both numerically and experimentally. Such type of signal is very important especially in building services engineering where the early detection of very small alien signals in the systems is crucial to the smooth operation of a heavily serviced building. The effects of the background noise magnitude on the accuracy of the recovery process are examined. The numerical simulation results show that these statistical tests are very sensitive to the change incurred by the wave to the background noise statistics and they are very helpful in locating the instant of the wave initialization even when the signal-to-noise ratio drops to -30 dB. A new parameter derived from the parameters of these two statistical tests, which is easy to compute, is proposed and its performance is found to be better than those of the two tests. It is also demonstrated that the performance of the new parameter does not depend much on the background noise. The experimental results are in line with the numerical simulations.
URI: http://hdl.handle.net/10397/22737
ISSN: 0003-682X
EISSN: 1872-910X
DOI: 10.1016/j.apacoust.2011.06.018
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