CNN and Convolutional Autoencoder (CAE) based real-time sensor fault detection, localization, and correction

Increasing advances in sensing technologies and analytics have led to the proliferation of sensors to monitor structural and infrastructural systems. Accurate sensor data can provide information about structural health, aid in prognosis, and help calculate forces for vibration control. However, sens...

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Bibliographic Details
Published in:	Mechanical systems and signal processing Vol. 169; p. 108723
Main Authors:	Jana, Debasish, Patil, Jayant, Herkal, Sudheendra, Nagarajaiah, Satish, Duenas-Osorio, Leonardo
Format:	Journal Article
Language:	English
Published:	Berlin Elsevier Ltd 15.04.2022 Elsevier BV
Subjects:	Accuracy Arch bridges Artificial neural networks Convolutional autoencoder Convolutional neural network Data reconstruction Deep learning Downtime Drift Fault classification Fault detection Faults Faulty sensor Linear systems Localization Machine learning Parameter identification Random noise Reconstruction Sensors Signal processing Structural health monitoring Vibration control Deep learning Fault classification Fault detection Convolutional neural network Data reconstruction Convolutional autoencoder Faulty sensor
ISSN:	0888-3270, 1096-1216
Online Access:	Get full text
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