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Development of Smart Cementitious Composite Sensors for Ambient Vibration-Based Continuous Health Monitoring of Structures

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Part of the Lecture Notes in Mechanical Engineering book series (LNME)

Abstract

In the present study, smart cementitious composite (SCC)-based sensors are developed that can be utilized as embedded senor for vibration-based health monitoring of large civil structures. The strain sensing ability is obtained through the incorporation of nanometer size carbon particles into cement paste which induces the piezoresistive properties. A systematic approach has been described for the fabrication of SCC sensors exploiting the unique capabilities of multi-walled carbon nanotubes (MWCNTs). The SCC sensor was mounted on a large reinforced concrete (RC) beam and the dynamic signals were captured by measuring the variance in electrical resistance/voltage from SCC sensor, and further benchmarked against conventional accelerometer measurement. The developed sensors show very good piezoresistive behavior with high strain sensitivity for the vibration sensing of large structures. The SCC-sensors are capable of capturing the first three fundamental frequencies with less than 2% deviation in comparison with the conventional accelerometer. The maximum acceleration sensitivity of SCC sensors was obtained to be 34.24 mV/g.

Keywords

  • Carbon nanotubes (CNTs)
  • Smart cementitious composites
  • Conductivity
  • Natural frequency
  • Vibration-based monitoring

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Acknowledgements

Authors would like to acknowledge the support received from the Special and Multifunctional Structures Laboratory (SMSL) of CSIR-SERC.

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© 2022 Indian Society for Non-destructive Testing

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Rao, R.K., Sasmal, S. (2022). Development of Smart Cementitious Composite Sensors for Ambient Vibration-Based Continuous Health Monitoring of Structures. In: Mandayam, S., Sagar, S.P. (eds) Advances in Non Destructive Evaluation. NDE 2020. Lecture Notes in Mechanical Engineering. Springer, Singapore. https://doi.org/10.1007/978-981-16-9093-8_17

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  • DOI: https://doi.org/10.1007/978-981-16-9093-8_17

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