Numerical and analytical study for ultrasonic testing of internal delamination defects considering surface roughness

Area of Science:

• Materials Science
• Non-Destructive Testing
• Acoustics

Background:

• Surface roughness hinders accurate detection of micro-defects in ultrasonic testing.
• Flat-bottom holes (FBHs) are crucial reference targets for assessing ultrasonic testing sensitivity.
• Existing models often fail to account for surface roughness effects on defect detection.

Purpose of the Study:

• To develop a roughness-modified analytical model for ultrasonic testing of FBHs.
• To investigate the influence of surface roughness on the amplitude of echo signals and noise.
• To propose a method for predicting internal defect detection accuracy under varying surface roughness conditions.

Main Methods:

• Established a roughness-modified analytical model using multi-Gaussian beam and phase-screen approximation.
• Utilized a 2D ultrasonic simulation model to obtain reference reflector signals.
• Analyzed amplitude changes of echo signals and noise for FBHs with varying dimensions and roughness.

Main Results:

• Root-mean-square (rms) height of roughness was identified as the dominant factor affecting signal amplitude.
• Reflected wave amplitude from FBHs decreased nonlinearly with increasing roughness.
• Noise amplitude showed a slight increase with enhanced surface roughness.

Conclusions:

• The developed analytical model accurately predicts the impact of surface roughness on ultrasonic testing signals.
• A novel method combining simulated noise and modeled echo signals effectively estimates internal defect detection accuracy.
• Experimental validation confirmed the reliability of the proposed evaluation method for rough surfaces.