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

• Published in: Sensors (Basel, Switzerland) Vol. 23; no. 16; p. 7059
• Main Authors: Shang, Li, Zhang, Zi, Tang, Fujian, Cao, Qi, Pan, Hong, Lin, Zhibin
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.08.2023; MDPI
• Subjects: Accuracy; Classification; CNN-LSTM hybrid model; Corrosion; Corrosion and anti-corrosives; damage identification; Data processing; data-driven approach; Datasets; Deep learning; Lamb wave; Machine learning; Neural networks; Pattern recognition systems; Pipe lines; Signal processing; structural health monitoring; Time series; Taiwan

The ultrasonic guided lamb wave approach is an effective non-destructive testing (NDT) method used for detecting localized mechanical damage, corrosion, and welding defects in metallic pipelines. The signal processing of guided waves is often challenging due to the complexity of the operational cond...