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SENSOR FAULT DIAGNOSIS USING DEEP LEARNING FOR OFFSHORE STRUCTURAL HEALTH MONITORING

Jianqianga Mou, Liuyangb Feng, Xiudongb Qian , Shan Cui
  • Abstract:
    A measurement system using strain gauges for structural health monitoring (SHM) was built up. The measurement uncertainty and sensor fault models were studied under a cyclic loading condition emulating the ocean waves. A methodology for sensor fault diagnosis and classification using the Convolutional Neural Network (CNN) deep learning with the images converted from time domain measurement data as the input was investigated.
  • Keywords:
    Measurement uncertainty, sensor fault diagnosis, CNN deep learning, structural health monitoring, finite element analysis, offshore structure
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  • DOI:
    tc6-2022.001

Event details:

  • IMEKO TC:
  • Event name:
    M4Dconf2022
  • Title:

    First International IMEKO TC6 Conference on Metrology and Digital Transformation

  • Place:
    Berlin, GERMANY
  • Time:
    19 September 2022 - 21 September 2022