Acoustic Signal-Based Deep Learning Approach and Device for Detecting Interfacial Voids in Steel–Con...
Acoustic Signal-Based Deep Learning Approach and Device for Detecting Interfacial Voids in Steel–Concrete Composite Structures
About this item
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Author / Creator
Tian, Wei , Yuan, Hang , You, Xinpeng , Zheng, Hehui , Li, Bazhou and Peng, Chengming
Publisher
New York: John Wiley & Sons, Inc
Journal title
Language
English
Formats
Publication information
Publisher
New York: John Wiley & Sons, Inc
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Scope and Contents
Contents
The reliable synergy between steel and concrete is an important evaluation criterion for the safety and long-term use of steel–concrete composite structures (SCCSs). However, it is still a great challenge to realize fast and automated interface void detection for composite structures such as towers. Therefore, the experiments of void detection of t...
Alternative Titles
Full title
Acoustic Signal-Based Deep Learning Approach and Device for Detecting Interfacial Voids in Steel–Concrete Composite Structures
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Author / Creator
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Primary Identifiers
Record Identifier
TN_cdi_doaj_primary_oai_doaj_org_article_17333baa662f463e868bad9018dca084
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_17333baa662f463e868bad9018dca084
Other Identifiers
ISSN
1687-8086
E-ISSN
1687-8094
DOI
10.1155/adce/2347213
