Abnormal data detection for structural health monitoring: State-of-the-art review
Structural health monitoring (SHM) is widely used to monitor and assess the condition and performance of engineering structures such as, buildings, bridges, dams, and tunnels. Owing to sensor defects, data acquisition errors, and environmental interference, abnormal data are often collected and stor...
Main Authors: | Yang Deng, Yingjie Zhao, Hanwen Ju, Ting-Hua Yi, Aiqun Li |
---|---|
Format: | Article |
Language: | English |
Published: |
Elsevier
2024-03-01
|
Series: | Developments in the Built Environment |
Subjects: | |
Online Access: | http://www.sciencedirect.com/science/article/pii/S2666165924000188 |
Similar Items
-
A Comprehensive Survey for Deep-Learning-Based Abnormality Detection in Smart Grids with Multimodal Image Data
by: Fangrong Zhou, et al.
Published: (2022-05-01) -
Research and application of recognition technology for abnormal data from coal gas monitoring system
by: WANG Yong, et al.
Published: (2013-04-01) -
Analysis and verification methods of abnormal data of coal mine safety monitoring system
by: XING Chengcheng
Published: (2017-06-01) -
Abnormal event detection of city slope monitoring data based on multi-sensor information fusion
by: Gang Liu, et al.
Published: (2022-03-01) -
Underground abnormal sensor condition detection based on gas monitoring data and deep learning image feature engineering
by: Guoquan Chang, et al.
Published: (2023-11-01)