| Author: | Li, Yehai |
| Title: | Graphene nanoparticle-functionalized polymer composites for self-sensing ultrasonic waves : an initiative towards "sensor-free" structural health monitoring |
| Advisors: | Su, Zhongqing (ME) |
| Degree: | Ph.D. |
| Year: | 2019 |
| Subject: | Hong Kong Polytechnic University -- Dissertations Nanostructured materials Polymeric composites Ultrasonic testing Structural health monitoring |
| Department: | Department of Mechanical Engineering |
| Pages: | xviii, 137 pages : color illustrations |
| Language: | English |
| Abstract: | The bourgeoning nano-engineered composite materials have ignited researchers' vast interest to explore new capabilities and attempt innovative applications with tailor-made functionalities. This new breed of composites, in lieu of conventional materials, has been the core of intensive research in the past two decades, and demonstrated their immense potential for new generation of structural health monitoring (SHM). In this study, nano-engineered fibre-reinforced polymer composites with a dispersed "graphene Nanoparticle-Networked Self-sensing System" (gNano-NSS) are developed for guided ultrasonic wave (GUW)-based SHM. The self-sensing capability of this type of functional composites is achieved by making use of the quantum tunneling effect rendered by the gNano-NSS which is triggered when GUWs traverse the composites. To this end, a diversity of nanoparticles and dispersion methods are comparatively attempted for designing and optimizing the gNano-NSS. Electrical conductivity of composites that are made of various nanoparticles at different degrees of weight content in the polymer matrices is measured, in order to determine the most appropriate type of nanoparticles and percolation threshold, whereby a gNano-NSS can be formed inside the polymer matrix that is responsive and sensitive to GUWs. Based on a series of comparative studies, the two-dimensional (2D) graphene nanoparticles are selected as the nanofillers, owing to their excellent electrical performance and mechanical property enhancement. Morphology characterization is conducted, indicating that the direct mixing method involving mechanical stirring and bath sonication can disperse graphene nanoparticles evenly in polymer and therefore applicable for massive production to fulfill the high-volume demand of nanoparticle-enriched epoxy resin in producing large composite structures. With approximately 1 wt.% graphene-enriched epoxy resin, conductivity of the developed composites has been dramatically enhanced with the dispersed piezoresistive gNano-NSS. With the functionalized piezoresistivity in the gNano-NSS, the polymer composites are endowed with a capability to self-sense GUWs. Any part of the structure made of the developed nano-engineered composites possesses the competence of serving as an individual sensor to monitor the dynamic strain induced by the propagated GUWs. Theoretically, such a gNano-NSS can respond to GUWs with ultralow magnitude and ultra-broadband frequency. This self-sensing functionality is testified and calibrated using a series of quasi-static tensile tests and low-frequency vibration tests first. Through measurement of changes in the resistance of gNano-NSS, the nano-engineered composites show an accurate response to static and dynamic loads up to several kilohertz. Meanwhile experimental results from tensile tests also exhibit that besides endowing the composites with functional properties, gNano-NSS also strengthens the original mechanical properties of the structure. Both the Young's elastic modulus and tensile strength have a certain level of enhancement. This makes gNano-NSS quite different from conventional attached/embedded sensor networks, in which the local strength degradation, stress concentration, debonding and corrosion are serious issues required careful concern. In recognition of the existing studies related to self-sensing capability of composites being restricted to the measurement of static strains or low-frequency yet large-magnitude structural vibration, in this study, the sensing capability of gNano-NSS is tested under a series of broadband loads up to ultrasonic regime. GUWs in an ultrasonic frequency regime up to several hundreds of kilohertz, are introduced to evaluate the self-sensing performance of the nano-engineered composites. Experimental validation is conducted, in which GUWs are self-sensed by gNano-NSS at sites arbitrarily selected in nano-engineered composites, to observe no discrepancy against counterpart signals obtained with piezoelectric sensors surface-mounted therein. Precise and fast self-response of the composites to broadband ultrasonic signals (up to 500 kHz) reveals that the composite structure itself can serve as ultrasound sensors, comparable to piezoceramic sensors in performance, whereas avoiding the use of external sensors. Combining circuits printing technology could further reduce weight penalty from unwieldy associated cables and wires. With the capability of self-sensing ultrasonic waves, gNano-NSS in manufactured nano-engineered composites is ready to implement in-situ SHM without a need to use any additional sensor externally attached to or internally embedded in the composites. To take a step further, GUW-based active SHM is performed to locate the barely visible impact damage (BVID) committed on the composite via a drop test. The time-of-flight (ToF) triangulation location algorithm is seamlessly combined with sensing paths formed by a piezoelectric actuator and the gNano-NSS. This study has spotlighted a new breed of functional composites with a capability of self-health monitoring. Not only does it facilitate a reduced weight and volume penalty to original composites, but minimizes possible mechanical degradation of the composites due to the intrusion of sensors, blazing a trail in developing "sensor-free" SHM for composites. |
| Rights: | All rights reserved |
| Access: | open access |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| 991022197537403411.pdf | For All Users | 6.74 MB | Adobe PDF | View/Open |
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