A Feature of Mechanics-Driven Statistical Moments of Wavelet Transform-Processed Dynamic Responses for Damage Detection in Beam-Type Structures

Abstract

Multiple damage detection using structural responses only is a problem unresolved that is in the field of structural health monitoring. To address this problem, a novel feature of mechanics-driven statistical moments of wavelet transform-processed dynamic responses is proposed for multi-damage identification in beam-type structures. This feature is referred to as a continuous wavelet transform (CWT)-second-order strain statistical moment (SSSM), with CWT-SSSM in the abbreviation. The mechanical connotation of CWT-SSSM lies in that the SSSM of each order principal vibration contains strain mode shapes, inducing greater sensitivity to local damage. With this method, the CWT is used to extract and amplify the singularities caused by damage in each order SSSM curve, following which the data fusion technology and three-sigma rule in statistics are adopted to construct the damage index. The presence of damage is characterized by the abrupt change in the damage index. The soundness and characteristics of the CWT-SSSM feature are verified by identifying multiple damages in a cantilever beam bearing two breathing cracks. The results show that the proposed feature can accurately designate multiple cracks free of baseline information on the intact counterpart; moreover, it has robustness against noise and applicability under excitations of approximately uniform spectra.