Self-powered triboelectric vibration sensor for non-destructive density evaluation of metal 3D-printed parts

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Authors: Young Won Kim, Jiyong Park
Cited by: 0
References: 47

Abstract

Abstract In this study, a self-powered triboelectric vibration sensor (TVS) was designed and fabricated to enable non-destructive evaluation of the density of metal 3D-printed specimens. The developed TVS employed a rigid glass substrate combined with an aluminum friction electrode and an electrospun PVDF-TrFE nanofiber layer, which together established a contact-separation-based triboelectric conversion mechanism. The nanofiber layer, characterized by its high porosity and flexibility, was engineered to increase the effective contact area and enhance the sensing sensitivity, while also functioning as a structural cushion to improve mechanical durability.Using this sensor, the vibration attenuation characteristics of metal 3D-printed specimens with different densities (10%, 60%, and 100%) were measured. Under test conditions of 200 Hz frequency and 50 µm amplitude, the results demonstrated a clear linear correlation between the specimen density and the degree of vibration attenuation. The relationship between the TVS output voltage and specimen density was quantified with a coefficient of determination (R²) of 0.984, confirming the feasibility of accurate density estimation.These findings indicate that the triboelectric sensor can be extended beyond conventional energy harvesting applications into a practical sensing platform capable of industrial use in structural health monitoring and quality assessment of 3D-printed components. Furthermore, this study provides a concrete example of how TENG technology can contribute to broader commercialization and adoption by demonstrating low-cost, battery-free, and lightweight advantages that enable deployment across diverse industrial settings.

Fields of Study & Subjects

Advanced Sensor and Energy Harvesting Materials Adhesion Friction and Surface Interactions Conducting polymers and applications

Publication details

Journal / source
Journal of Intelligent Material Systems and Structures
Publisher
SAGE Publications
Publication date
7 September 2026
Language
EN