CNN-LSTM Hybrid Model to Promote Signal Processing of Ultrasonic Guided Lamb Waves for Damage Detection in Metallic Pipelines.

Shang, Li; Zhang, Zi; Tang, Fujian; Cao, Qi; Pan, Hong; Lin, Zhibin

Shang, Li; Zhang, Zi; Tang, Fujian; Cao, Qi; Pan, Hong; Lin, Zhibin.

Afiliação

Shang L; Department of Civil and Environmental Engineering, North Dakota State University, Fargo, ND 58018, USA.
Zhang Z; Department of Civil and Environmental Engineering, North Dakota State University, Fargo, ND 58018, USA.
Tang F; School of Civil Engineering, Dalian University of Technology, Dalian 116024, China.
Cao Q; School of Civil Engineering, Dalian University of Technology, Dalian 116024, China.
Pan H; Department of Civil and Environmental Engineering, North Dakota State University, Fargo, ND 58018, USA.
Lin Z; Department of Civil and Environmental Engineering, North Dakota State University, Fargo, ND 58018, USA.

Sensors (Basel) ; 23(16)2023 Aug 09.

Article em En | MEDLINE | ID: mdl-37631596

Palavras-chave

CNN-LSTM hybrid model; Lamb wave; damage identification; data-driven approach; machine learning; structural health monitoring

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Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Diagnostic_studies / Prognostic_studies Idioma: En Ano de publicação: 2023 Tipo de documento: Article

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Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Diagnostic_studies / Prognostic_studies Idioma: En Ano de publicação: 2023 Tipo de documento: Article