Abstract
This study proposes a multi-channel electrical impedance-based crack localization technique of fiber-reinforced cementitious composites (FRCCs) under bending conditions. FRCCs have a self-sensing capability by adding conductive steel fibers into nonconductive cementitious composites, making it possible to measure electrical impedance without sensor installation. Moreover, FRCCs materials can be used as a structural member thanks to its own enhanced structural ductility as well as stiffness. In a structural health monitoring point of view, these characteristics make FRCCs suitable for monitoring structural hot spots, particularly where the crack is most likely to be initiated. Since the electrical impedance obtained from FRCCs is typically sensitive to environmental and operational conditions, false alarms are often triggered. The proposed technique can minimize the false alarms by using currently measured multi-path data as well as localize a crack within the sensing range. To examine the feasibility of crack localization in FRCCs, an instantaneous multi-channel electrical impedance acquisition system and a crack localization algorithm are developed. Subsequently, three-point bending tests are carried out under various temperature conditions. The validation test results reveal that cracks are successfully identified and localized even under varying temperature conditions.
Highlights
Concrete is one of the most commonly and widely used construction materials over the world thanks to its high compressive strength and economic superiority [1]
The physical reason is speculated that the temperature changes cause the change of the ion mobility along the internal electrical bridge of fiber-reinforced cementitious composites (FRCCs), the absolute values might be different in each region because of FRCCs’ inhomogeneity
The proposed technique was experimentally validatedusing using specially manufactured four FRCCs specimens under temperature change and three-point bending loading conditions
Summary
Concrete is one of the most commonly and widely used construction materials over the world thanks to its high compressive strength and economic superiority [1]. Jang et al proposed the fully noncontact hybrid sensing system combining a continuous-wave line laser, IR and digital cameras for enhancing deep learning-based crack detectability of a concrete structure [28]. The noncontact crack detection techniques can address the technical limitations of the contact-type sensing mechanism, they are more suitable for periodic inspection rather than real-time monitoring of a target structure. The self-sensing concrete is made by adding conductive fibrous materials into nonconductive normal cement to increase its electrical sensing capability as well as structural ductility [30,31] It can be used as a sensor for crack monitoring in structural hot spots. An instantaneous multi-channel electrical impedance-based crack localization technique of using FRCCs is proposed.
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