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IMEKO TC6 M4Dconf

Hybrid with physical attendance in Berlin, Germany

19 — 21 September 2022

Sensor fault diagnosis using deep learning for offshore structurual health monitoring

 SNM - Sensor Network Metrology 

 

21st September, 13:00 CEST
Lecture Hall, Helmholtz Building

Authors

  • Speaker: Jianqiang MOU (National Metrology Centre, A*STAR, SINGAPORE)
  • Liuyang FENG (National University of Singapore, Singapore)
  • Xiudong QIAN (National University of Singapore, Singapore)
  • Shan CUI (National Metrology Centre, A*STAR, Singapore)

Paper

  • SENSOR FAULT DIAGNOSIS USING DEEP LEARNING FOR OFFSHORE STRUCTURAL HEALTH MONITORING570 KB

    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.