SENSOR FAULT DIAGNOSIS USING DEEP LEARNING FOR OFFSHORE STRUCTURAL HEALTH MONITORING |
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| 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
- Download:
- IMEKO-TC6-2022-001.pdf
- DOI:
- 10.21014/tc6-2022.001
- Event details
- Event name:
- M4Dconf2022
- Title:
First International IMEKO TC6 Conference on Metrology and Digital Transformation
- Place:
- Berlin, GERMANY
- Time:
- 19 September 2022 - 21 September 2022
- Event details
- Event name:
- Special session at M4Dconf2022
- Title:
First International IMEKO TC6 Conference on Metrology and Digital Transformation
- Place:
- Berlin, GERMANY
- Time:
- 19 September 2022 - 21 September 2022
- Event details
- Event name:
- M4Dconf2022 (2)
- Title:
First International IMEKO TC6 Conference on Metrology and Digital Transformation
- Place:
- Berlin, GERMANY
- Time:
- 19 September 2022 - 21 September 2022