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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IMEKO-TC6-2022-001.pdf

DOI

10.21014/tc6-2022.001

IMEKO TC

TC6 - Digitalization

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