Measurement of weld penetration depths in thin structures using transmission coefficients of laser-generated Lamb waves and neural network.
The Laser/EMAT ultrasonic (LEU) technique has shown the capability to measure weld penetration depths in thick structures based on ray-tracing of laser-generated bulk and surface waves. The ray-tracing method is not applicable to laser-generated Lamb waves when the LEU technique is used to measure weld penetration depths in thin structures. In this work, transmission coefficients of Lamb waves present in the LEU signals are investigated against varying weld penetration depths. An artificial neural network is developed to use transmission coefficients of sensitive Lamb waves and LEU signal energy to predict weld penetration depths accurately. The developed method is very attractive because it allows a quick inspection of weld penetration depths in thin structures.
G.W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, 813 Ferst Drive NW, Atlanta, GA 30332-0405, United States.
Lei
L
Yang
G.W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, 813 Ferst Drive NW, Atlanta, GA 30332-0405, United States. Electronic address: charles.ume@me.gatech.edu.
I Charles
IC
Ume
Lamb waves; Laser/EMAT; Neural network; Ultrasonic; Weld penetration depth