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.