A Statistical Measure for Wavelet Based Singularity Detection

Abstract

This paper presents a statistical measure for the identification of the presence, the location, and the calibration of the strength of singularity in a signal or in any of its derivatives in the presence of measurement noise without the requirement of a baseline using a wavelet based detection technique. For this proposed wavelet based detection of singularities present in a signal, the problem of false alarm and its significant reduction by use of multiple measurements is presented. The importance of the proposed measure on baseline and nonbaseline damage calibration has been discussed from the aspect of structural health monitoring. The findings in this paper can also be used for cross-checking of background noise level in an observed signal. The detection of the existence, location, and extent of an open crack from the first fundamental modeshape of a simply supported beam is presented as an example problem.