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Impact damage detection and localization of adhesively bonded fiber reinforced structures using silver nanoparticle based printed circuits
Publikationstyp
Conference Paper
Date Issued
2017
Sprache
English
Author(s)
TORE-URI
Volume
1
Start Page
1461
End Page
1468
Citation
Structural Health Monitoring 2017: Real-Time Material State Awareness and Data-Driven Safety Assurance - Proceedings of the 11th International Workshop on Structural Health Monitoring, IWSHM 2017 (1): 1461-1468 (2017)
Contribution to Conference
Publisher
DEStech Publications, Inc.
Electrical conductivity of carbon fibers and carbon nanotubes provides the possibility of in situ strain monitoring and damage detection of composite structures by electrical resistance measurement. To exploit this property and use the material itself as a sensor in a structural health monitoring system a reliable contacting of the material is needed to enable electrical resistance measurement during operation. Due to its high potential for industrial automation and its excellent reproducibility, ink-jet printing serves as promising technology to print circuits and realize contacting on the monitored material. The study deals with a new structural health monitoring approach using inkjet printing of silver nanoparticle based ink directly onto the composites structure. Impact damages are introduced into adhesively bonded glass fiber reinforced polymer test specimens. A modification of the epoxy based adhesive films with carbon nanoparticles allows for electrical resistance measurements through the bonding. The introduced impacts are investigated using non-destructive testing methods, i.e. ultrasonic inspection, and light microscopy. Electrical resistance measurement shows the possibility of accurate damage detection and damage localization in one or two dimensions, depending on the conducting path designs.
DDC Class
620: Ingenieurwissenschaften
More Funding Information
The financial support from Landesforschungsförderung Hamburg (project “Health-Monitoring von Faserverbundstrukturen mit Hilfe von Sensorarrays”, grant number LFF-FV 05).