Multiclass anomaly detection in imbalanced structural health monitoring data using convolutional neural network

Multiclass anomaly detection in imbalanced structural health monitoring data using convolutional neural network

Abstract Structural health monitoring (SHM) system aims to monitor the in-service condition of civil infrastructures, incorporate proactive maintenance, and avoid potential safety risks. An SHM system involves the collection of large amounts of data and data transmission. However, due to the normal...

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Bibliographic Details
Main Authors: Mengchen Zhao, Ayan Sadhu, Miriam Capretz
Format: Article
Language:English
Published: SpringerOpen 2022-08-01
Series:Journal of Infrastructure Preservation and Resilience
Subjects:
Structural health monitoring
Anomaly detection
Convolutional neural network
Imbalanced dataset
Hyperparameter tuning
Online Access:https://doi.org/10.1186/s43065-022-00055-4

Internet

https://doi.org/10.1186/s43065-022-00055-4

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