Abstract
Structural health monitoring (SHM) is a novel area of research and it is the process of implementing a damage detection strategy. The initial step of implementation a SHM system involves, incorporating structural self-sensing capability of material to achieve the reliability and possesses long term stability. Smart sensing technologies involves the applications of fiber optic sensors and self-diagnosing fiber reinforced composites which possess important capabilities of monitoring various physical or chemical parameters to achieve the durable service life of structures. The addition Carbon fiber to concrete composites possess the electric properties, therefore it can be used as Smart sensing composite that provide the capability of non-destructive flaw detection in structures. In this paper, carbon fiber (CF’s) is added to cement composite to attain piezoresistive properties of composite. This carbon fiber is added in the composite by forming tube which act as conductive element. Later on, electromechanical test is conducted to this sensor by embedded into structural elements that is in beam and column to evaluate self-sensing properties. Scanning electron microscope is carried to understand the morphology of sample. A Finite elemental modeling is done to validate this experimental result. A FEA modelling is carried out using ANSYS software, subjected to steady steady static loading and electric analysis were done. Form the experimental is observed that addition carbon fiber induces conductivity property and the resistance decrease for failure load. The resistivity from experimental study observed is 9.2 kilo ohms and 11.2 kilo ohms for embedded carbon fibre sensor into beam and column respectively. The percentage error in electrical analysis of experimental tests compared with analytical modelling, found to be 15 %. Based on these results it can be concluded that carbon fiber cement composites have great potential and they can be used for structural health monitoring applications.
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More From: IOP Conference Series: Materials Science and Engineering
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