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Internet of Things Based Data Acquisition System of Acoustic Emission Sensor for Structural Health Monitoring Applications

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Intelligent Data Communication Technologies and Internet of Things (ICICI 2019)

Part of the book series: Lecture Notes on Data Engineering and Communications Technologies ((LNDECT,volume 38))

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Abstract

In this paper a IoT based data acquisition (DAQ) system has been developed for acquisition of the data from acoustic emission sensor for structural health monitoring (SHM) of the steel bridge using acoustic emission technique. The DAQ device is developed by using Raspberry Pi 3 Model B+ interfaced with a high-speed 1 MSPS and 16 bit ADC ADAQ7980 to capture the high frequency acoustic emission signal generated by crack related activities on the surface of the steel structure for real-time monitoring, identification and localisation of any crack happening on the structure through cloud computing.

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Author information

Authors and Affiliations

  1. CSIR-Central Mechanical Engineering Research Institute, Durgapur, 713209, West Bengal, India

    Arpita Mukherjee, Abhishek Maurya, Pratap Karmakar & Partha Bhattacharjee

Authors
  1. Arpita Mukherjee
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  2. Abhishek Maurya
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  3. Pratap Karmakar
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  4. Partha Bhattacharjee
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Corresponding author

Correspondence to Arpita Mukherjee .

Editor information

Editors and Affiliations

  1. Department of ECE, Karunya University, Coimbatore, India

    D. Jude Hemanth

  2. Department of Electronics and Computer Engineering, Tribhuvan University, Kirtipur, Nepal

    Subarna Shakya

  3. School of Science, Edith Cowan University, Joondalup Campus, Joondalup, WA, Australia

    Zubair Baig

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Mukherjee, A., Maurya, A., Karmakar, P., Bhattacharjee, P. (2020). Internet of Things Based Data Acquisition System of Acoustic Emission Sensor for Structural Health Monitoring Applications. In: Hemanth, D., Shakya, S., Baig, Z. (eds) Intelligent Data Communication Technologies and Internet of Things. ICICI 2019. Lecture Notes on Data Engineering and Communications Technologies, vol 38. Springer, Cham. https://doi.org/10.1007/978-3-030-34080-3_16

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