Pattern recognition framework using asynchronous discrete binary data for condition and damage assessment in plate-like structures

Hadi Salehi; Rigoberto Burgueño

doi:10.1177/1045389X19835948

Pattern recognition framework using asynchronous discrete binary data for condition and damage assessment in plate-like structures

Hadi Salehi
, Rigoberto Burgueño

Michigan State University

Research output: Contribution to journal › Article › peer-review

Original language	English
Pages (from-to)	1200-1215
Number of pages	16
Journal	Journal of Intelligent Material Systems and Structures
Volume	30
Issue number	8
DOIs	https://doi.org/10.1177/1045389X19835948
State	Published - May 1 2019
Externally published	Yes

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

ASJC Scopus Subject Areas

General Materials Science
Mechanical Engineering

Keywords

Pattern recognition
binary data
sensor networks
structural health monitoring

Access to Document

10.1177/1045389X19835948

Cite this

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title = "Pattern recognition framework using asynchronous discrete binary data for condition and damage assessment in plate-like structures",

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language = "English",

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AU - Salehi, Hadi

AU - Burgueño, Rigoberto

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Y1 - 2019/5/1

KW - Pattern recognition

KW - binary data

KW - sensor networks

KW - structural health monitoring

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M3 - Article

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JO - Journal of Intelligent Material Systems and Structures

JF - Journal of Intelligent Material Systems and Structures

IS - 8

ER -

Pattern recognition framework using asynchronous discrete binary data for condition and damage assessment in plate-like structures

UN SDGs

ASJC Scopus Subject Areas

Keywords

Access to Document

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