The aging of materials is one of the main causes of failure of instruments and devices. Availability of early detection tools can improve the Predictive Maintenance process to extend the lifetime of devices, saving on costs and time. We here introduce the new paradigm of wireless monitoring of surface integrity based on Space Filling Curves (SFC). It acts as an artificial electric skin suitable to envelope a surface to detect from remote the presence of small aging signs. In particular, the occurrence of an even small surface crack is detected in a binary form and transmitted remotely, following a standard RFID interrogation. The feasibility of the idea is supported by numerical analysis and experimental outcomes on 2D and curved thin, flexible and stretchable surfaces and metallic objects, such as an orthopedic prosthesis.
Nappi, S., Marrocco, G. (2020). RFID-Based Stress Predictive Engineering. ??????? it.cilea.surplus.oa.citation.tipologie.CitationProceedings.prensentedAt ??????? 23esima Riunione Nazionale di Elettromagnetismo (RiNEm 2020).
RFID-Based Stress Predictive Engineering
Gaetano Marrocco
2020-11-01
Abstract
The aging of materials is one of the main causes of failure of instruments and devices. Availability of early detection tools can improve the Predictive Maintenance process to extend the lifetime of devices, saving on costs and time. We here introduce the new paradigm of wireless monitoring of surface integrity based on Space Filling Curves (SFC). It acts as an artificial electric skin suitable to envelope a surface to detect from remote the presence of small aging signs. In particular, the occurrence of an even small surface crack is detected in a binary form and transmitted remotely, following a standard RFID interrogation. The feasibility of the idea is supported by numerical analysis and experimental outcomes on 2D and curved thin, flexible and stretchable surfaces and metallic objects, such as an orthopedic prosthesis.File | Dimensione | Formato | |
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