Development and validation of a probabilistic multistage algorithm for damage localization in piezo-monitored structures

All structures during operating life can be affected by faults induced by accidental events and operational conditions. Structural health monitoring systems can provide quasi-real-time diagnosis of the structure, thus enabling the condition-based maintenance approach. By means of piezoelectric transducers (PZTs) and ultrasonic guided waves (UGW), the structural integrity can be easily interrogated, even though laborious post-processing techniques are required to correctly interpret sensed data. This work aims to devise a new automatic diagnosis framework based on the propagation of UGW for thin-walled structures fault detection and localisation. Specifically, a fully automated damage identification algorithm was developed through a numerical dataset obtained by finite element simulations, and then validated experimentally. The case of study consisted of a square-shaped aluminium plate equipped with a five PZTs network. Five different damage positions and three different damage sizes were considered. The originality of the proposed algorithm lies in the data processing methodology as well as in its capability to detect damages located inside and outside the sensors network, even close to the panel edges. Algorithm provides, in less than 15 s, indications on the possible damage location and related probability position with a reduced dispersion with respect to other algorithms proposed in literature. A clear image is created displaying the damage position map. The visualisation of the damage position map on the surface of the monitored part allows successful damage imaging and would enable operators to address more efficiently the inspection procedures only in the highlighted areas, reducing maintenance and repair expenses.