Detection and simulation of roof-corner pressure transients

Abstract Many practical time series, including pressure signals measured on roof-corners of low-rise buildings in quartering winds, consist of relatively quiescent periods interrupted by intermittent transients. The dyadic wavelet transform is used to detect these transients in pressure time series and a relatively simple pattern classification scheme is used to detect underlying structure in these transients. Statistical analysis of the resulting pattern classes yields a library of signal building blocks, which are useful for detailed characterization of transients inherent to the signals being analyzed. Probability density functions describing the arrival intervals and characteristics of the detected transients are used to synthesize time series that mimic the intermittency of the original signal. In addition, the signal that remains when the detected transients are removed from the original signal is examined to suggest appropriate models for the background noise in the intermittent signal.