A Novel Pipeline Corrosion Monitoring Method Based on Piezoelectric Active Sensing and CNN.

Yang, Dan; Zhang, Xinyi; Zhou, Ti; Wang, Tao; Li, Jiahui

Yang, Dan; Zhang, Xinyi; Zhou, Ti; Wang, Tao; Li, Jiahui.

Afiliação

Yang D; Key Laboratory for Metallurgical Equipment and Control of Ministry of Education, Wuhan University of Science and Technology, Wuhan 430081, China.
Zhang X; Hubei Key Laboratory of Mechanical Transmission and Manufacturing Engineering, Wuhan University of Science and Technology, Wuhan 430081, China.
Zhou T; Key Laboratory for Metallurgical Equipment and Control of Ministry of Education, Wuhan University of Science and Technology, Wuhan 430081, China.
Wang T; Precision Manufacturing Institute, Wuhan University of Science and Technology, Wuhan 430081, China.
Li J; Wuhan Digital Engineering Institute, Wuhan 430074, China.

Sensors (Basel) ; 23(2)2023 Jan 11.

Article em En | MEDLINE | ID: mdl-36679652

Assuntos

Redes Neurais de Computação; Análise de Ondaletas; Corrosão; Ultrassom

Palavras-chave

convolutional neural network; pipeline corrosion; time reversal; wavelet packet

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Redes Neurais de Computação / Análise de Ondaletas Idioma: En Revista: Sensors (Basel) Ano de publicação: 2023 Tipo de documento: Article País de afiliação: China

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