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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Vydáno v:	Mechanical systems and signal processing Ročník 169; s. 108723
Hlavní autoři:	Jana, Debasish, Patil, Jayant, Herkal, Sudheendra, Nagarajaiah, Satish, Duenas-Osorio, Leonardo
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Berlin Elsevier Ltd 15.04.2022 Elsevier BV
Témata:	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
On-line přístup:	Získat plný text
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