Damage Assessment of a 3D-Printed Plate Using Capacitance of Surface-Bonded and Embedded Piezoelectric Sensors

Abstract

This research focuses on damage assessment based on the electromechanical impedance (EMI) method. The method uses piezoelectric transducers that excite the investigated structure and sense the response. The damage assessment is based on comparing the electrical spectra gathered for structural parts at different structural conditions. In particular, the unknown case (possibly damaged) is compared with data for known healthy (undamaged) case. In the reported research the EMI method was applied to additively manufactured samples. For several years, additive manufacturing (AM), or 3D printing, has become a popular manufacturing technique that is environmentally friendly by allowing for waste reduction. The structural parts manufactured with AM methods were introduced into the mechanical and aerospace industries. Similar to structures made from traditional metals or polymers, there is a need for structural health monitoring of 3D printed structures. This requires the development of accurate and reliable methods for evaluating and monitoring the structural integrity of such components. Additionally, the AM method gives more freedom in design and also allows for easier sensor integration for structural health monitoring. In this work, the piezoelectric sensors were embedded in a polymer 3D- printed plate and their response was compared with the surface-bonded sensor. In this study, the effective excitability of the sensors was tested with the scanning laser vibrometer. Due to high attenuation, the EMI investigation was limited to 100 kHz. In total four sensors were used for the sample assessment, and the capacitance as a function of frequency was analyzed. Firstly, the structural change was simulated by an additional mass. Secondly, a through-thickness hole was drilled to simulate damage, and the EMI responses were compared for four diameters of this hole. Traditionally, in the EMI approach resistance, conductance, or impedance is studied. However, in this study, promising results were obtained for capacitance that allowed for damage detection and later for severity assessment. The introduced data processing approach based on principal component analysis (PCA) allowed for the differentiation of all the investigated cases and showed good sensitivity to the simulated damage severity.