Convolutional neural network-based data anomaly detection method using multiple information for structural health monitoring-Reference-Cited by-同舟云学术

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Convolutional neural network-based data anomaly detection method using multiple information for structural health monitoring

Published:2018-11-29 Issue:1 Volume:26 Page:e2296
ISSN:1545-2255
Container-title:Structural Control and Health Monitoring
language:en
Short-container-title:Struct Control Health Monit

Author:

Tang Zhiyi¹²³^ORCID,Chen Zhicheng¹²³,Bao Yuequan¹²³^ORCID,Li Hui¹²³^ORCID

Affiliation:

1. Key Lab of Structures Dynamic Behavior and Control of the Ministry of Education; Harbin Institute of Technology; Harbin China

2. Key Lab of Intelligent Disaster Mitigation of the Ministry of Industry and Information Technology; Harbin Institute of Technology; Harbin China

3. School of Civil Engineering; Harbin Institute of Technology; Harbin China

Funder

National Key R&D Program of China

National Natural Science Foundation of China

Publisher

Wiley

Subject

Mechanics of Materials,Building and Construction,Civil and Structural Engineering

Link

http://onlinelibrary.wiley.com/wol1/doi/10.1002/stc.2296/fullpdf

Reference57 articles.

1. The state of the art in structural health monitoring of cable-stayed bridges;Li;Struct Health Monit,2016

2. Structural health monitoring: technological advances to practical implementations [scanning the issue];Lynch;Proc IEEE,2016

3. Three-tier modular structural health monitoring framework using environmental and operational condition clustering for data normalization: validation on an operational wind turbine system;Häckell;Proc IEEE,2016

4. Continuous dynamic monitoring of a prestressed concrete bridge based on strain, inclination and crack measurements over a 14-year span;Hu;Struct Health Monit,2017

5. Sensor validation using principal component analysis;Kerschen;Smart Mater Struct,2004

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