Debonding damage detection in CFRP-reinforced steel structures using scanning probabilistic imaging method improved...

Area of Science:

• Structural Health Monitoring
• Materials Science
• Non-Destructive Testing

Background:

• Carbon Fiber Reinforced Polymer (CFRP) is used to strengthen steel structures.
• Research on detecting debonding damage in these composite structures is limited.
• Accurate localization and imaging of debonding are crucial for structural integrity.

Purpose of the Study:

• To develop an improved probabilistic imaging method for localizing debonding damage in CFRP-reinforced steel structures.
• To enhance the detection capability for small-scale debonding damages.
• To provide a precise and effective method for early debonding detection.

Main Methods:

• A novel waveform feature index with high robustness against damage and environmental disturbances was proposed.
• A dynamic scanning approach using orthogonal directions replaced conventional fixed sensor arrays, reducing sensor count and increasing flexibility.
• The method's independence from signal amplitude ensures accurate localization irrespective of coupling conditions.

Main Results:

• The proposed waveform feature index demonstrated superior detection of small-scale debonding compared to linear indices.
• The dynamic scanning approach enabled efficient 2D imaging with fewer sensors and adjustable detection areas.
• Numerical simulations and experimental validation confirmed the method's accuracy in detecting and localizing debonding in CFRP-steel structures.

Conclusions:

• The developed probabilistic imaging method effectively localizes debonding damage in CFRP-reinforced steel structures.
• The technique offers enhanced applicability, robustness, and precision for early damage detection.
• This research contributes a valuable tool for ensuring the safety and longevity of reinforced steel structures.