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Data quality evaluation for bridge structural health monitoring based on deep learning and frequency-domain information

Author(s): ORCID (School of Civil and Transportation Engineering, Beijing University of Civil Engineering and Architecture, Beijing, China)
(School of Civil and Transportation Engineering, Beijing University of Civil Engineering and Architecture, Beijing, China)
(Shandong Provincial Communications Planning and Design Institute Group Co., Ltd, Jinan, China)
(School of Civil and Transportation Engineering, Beijing University of Civil Engineering and Architecture, Beijing, China)
Medium: journal article
Language(s): English
Published in: Structural Health Monitoring, , n. 5, v. 22
Page(s): 147592172211387
DOI: 10.1177/14759217221138724
Structurae cannot make the full text of this publication available at this time. The full text can be accessed through the publisher via the DOI: 10.1177/14759217221138724.
  • About this
    data sheet
  • Reference-ID
    10702196
  • Published on:
    16/12/2022
  • Last updated on:
    01/09/2023
 
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