High Precision Detection Method for Delamination Defects in Carbon Fiber Composite Laminates Based on Ultrasonic...

Area of Science:

• Materials Science
• Non-Destructive Testing
• Signal Processing

Background:

• Carbon fiber reinforced plastic (CFRP) is widely used in various industries.
• Detecting delamination defects in CFRP is crucial for structural integrity.
• Current ultrasonic testing methods can be complex and require significant expertise.

Purpose of the Study:

• To develop a high-precision, convenient method for detecting delamination defects in CFRP.
• To distinguish between defect and non-defect signals using signal correlation.
• To accurately determine the depth and size of defects through imaging.

Main Methods:

• A reference signal is generated from non-defect areas using autocorrelation theory.
• Euclidean distance is employed to differentiate defect and non-defect signals based on correlation results.
• Cubic spline interpolation is utilized for enhanced time-of-flight accuracy.
• The proposed algorithm is validated against ultrasonic phased array C-scan data.

Main Results:

• The signal correlation method successfully distinguishes defect signals from non-defect signals.
• Defect depth and size are accurately presented through image processing.
• Experimental results show less than 4% error in defect size and less than 3% error in depth.
• The method demonstrates effective defect shape presentation and location calculation.

Conclusions:

• Signal correlation offers a novel and effective approach for automatic ultrasonic testing of CFRP.
• This method simplifies defect detection by avoiding complex signal peak tracking and gate setting.
• The proposed technique requires less prior knowledge from inspectors, enhancing usability in automatic ultrasonic testing.