2016
DOI: 10.1007/s40684-016-0040-4
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Structural health monitoring of carbon-material-reinforced polymers using electrical resistance measurement

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Cited by 39 publications
(16 citation statements)
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“…In this context, assembled graphene‐based films can be easily deposited and patterned onto low‐cost substrates and integrated into flexible composite materials for monitoring localized strain. They can also act as embedded sensors in structural components such as fiber‐reinforced polymer composites and used as passive RFID tags . The desirable properties of these sensors are wireless, highly flexible, and nonintrusive, while requiring very low power and cost–effectiveness.…”
Section: Graphene Assemblies For Electromechanical Piezoresistive Strmentioning
confidence: 99%
“…In this context, assembled graphene‐based films can be easily deposited and patterned onto low‐cost substrates and integrated into flexible composite materials for monitoring localized strain. They can also act as embedded sensors in structural components such as fiber‐reinforced polymer composites and used as passive RFID tags . The desirable properties of these sensors are wireless, highly flexible, and nonintrusive, while requiring very low power and cost–effectiveness.…”
Section: Graphene Assemblies For Electromechanical Piezoresistive Strmentioning
confidence: 99%
“…For safety‐critical structures, it is important that there is a high probability of timely detection of any cracks throughout the operational life of the structures . For example, composites are vulnerable under impact damages . Life of structures needs to be maximized by ensuring their health and safety before reaching a critical state.…”
Section: Introductionmentioning
confidence: 99%
“…This paper attempted to develop a fault detection method that uses only the data types being acquired in industrial fields, without the need for any additional sensors. To use (12), the values of internal resistances are required; however, in real-world settings, no sensor can be available to measure these resistances [28]. In this case, it is necessary to perform curve fitting using the proposed linear regression model of (12).…”
Section: Resultsmentioning
confidence: 99%