A phased array-based method for damage detection and localization in thin plates

Malinowski, P. and Wandowski, T. and Trendafilova, I. and Ostachowicz, W.M. (2009) A phased array-based method for damage detection and localization in thin plates. Structural Health Monitoring, 8 (1). pp. 5-15. ISSN 1475-9217 (https://doi.org/10.1177/1475921708090569)

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Abstract

A method for damage localization based on the phased array idea has been developed. Four arrays oftransducers are used to perform a beam-forming procedure. Each array consists of nine transducersplaced along a line, which are able to excite and register elastic waves. The A0 Lamb wave mode hasbeen chosen for the localization method. The arrays are placed in such a way that the angulardifference between them is 458 and the rotation point is the middle transducer, which is common for allthe arrays. The idea has been tested on a square aluminium plate modeled by the Spectral Element Method. Two types of damage were considered, namely distributed damage, which was modeled asstiffness reduction, and cracks, modeled as separation of nodes between selected spectral elements.The plate is excited by a wave packet. The whole array system is placed in the middle of the plate.Each linear phased array in the system acts independently and produces maps of a scanned fieldbased on the beam-forming procedure. These maps are made of time signals (transferred to spacedomain) that represent the difference between the damaged plate signals and those from the intactplate. An algorithm was developed to join all four maps. The final map is modified by proposed signal processing algorithm to indicate the damaged area of the plate more precisely. The problem fordamage localization was investigated and exemplary maps confirming the effectiveness of theproposed system were obtained. It was also shown that the response of the introduced configurationremoves the ambiguity of damage localization normally present when a linear phased array is utilized.The investigation is based exclusively on numerical data.