Conjunctive and compromised data fusion schemes for identification of multiple notches in an aluminium plate using lamb wave signals

Conjunctive and compromised data fusion schemes were applied to aggregate perceptions from individual actuator-sensor paths, for the purpose of evaluating positions of multiple notches in an aluminum plate, with the signatures extracted from the scattered Lamb wave signals captured by sensors. An active sensor network consisting of piezoelectric (lead zirconium tantalate, PZT) wafers was employed to activate and capture Lamb wave signals, where two-level configurations hierarchically provided global and local evaluations of the location of damage. A signal processing algorithm featuring signal correlation was proposed to facilitate accurate extraction of the arrival time of damage-scattered waves in the time domain. The diagnostic results demonstrate that the proposed approach is capable of identifying the locations of multiple notches with good accuracy.