PSI - Issue 64

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Hendrik Holzmann / Structural Integrity Procedia 00 (2019) 000 – 000

1304 © 2024 The Authors. Published by ELSEVIER B.V. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0) Peer-review under responsibility of SMAR 2024 Organizers Keywords: sandwich panel; detection; localization; feature engineering; neural network Hendrik Holzmann et al. / Procedia Structural Integrity 64 (2024) 1303–1310

1. Introduction Sandwich panels in civil engineering have the advantages of a high flexural strength and thermal insulation while providing a very low density. They are made of two steel sheets and a core of polyurethane (PUR) or polyisocyanurate (PIR) foam (Lange and Berner 2020; Pozorski 2016), cf. Fig. 1 (a). Due to the manufacturing process, the panels occasionally have defects, that are not visible from the outside during or immediately after production. The defects can cause visible damages after installation in building facades, cf. Fig. 1 (b). Reliable methods for detection and localization of defects are not implemented in the current production lines of manufacturers although these can lead to significant reduction of customer complaints and savings in replacement costs. Since the sandwich panels become increasingly popular with a production of about 20 million m² in Germany and 200 million m² in the European Union, the potential for emission reduction is immense.

(a) (b) Fig. 1. (a) Detail view of a sandwich element with foam and two steel sheets; (b) facade with blister faults.

Structural health monitoring (SHM) is a research and engineering field for the detection and investigation of faults in structures from various sectors. It can for example be used to evaluate the fault location and its severity. Since classical destructive evaluation is not reasonable for many use cases, non-destructive evaluation (NDE) is in general used in connection with SHM. NDE for SHM can be performed with different excitation and measurement principles. Common in engineering is vibration analysis where different frequency bands can be used. In recent years, the topic of guided waves has become more and more popular, for example, to perform integral measurements in structures like metal sheets or pipes and also sandwich structures (Feng et al. 2023; Yaacoubi et al. 2019). Recent works use air coupled lamb waves for fault detection and visualization in the addressed sandwich structures (Haugwitz et al. 2023) at 40 kHz. In the lower frequency range up to a few kHz, that contains information about the first system eigenfrequencies, other excitation principles can be of interest. Especially useful is the excitation with an impact hammer since there does not have to be a permanent connection between structure and excitation device in contrast to an electrodynamic shaker. The impact hammer provides sufficient impact energy to measure a system s’ response with good signal-to-noise ratio. Furthermore, modal parameters can be obtained by modal hammer measurement, and modal parameter-based damage identification algorithms can be useful for SHM according to Fan and Qiao (2011). Vibration measurement data can be obtained in several ways, e. g. using accelerometers or laser vibrometers. To discern between structures without and with faults, measurement data must be acquired for the different system states according to the statistical pattern recognition paradigm (Farrar and Worden 2013).