Detecting small flaws in two-phase Ti-6Al-4V with rough surfaces.

Area of Science:

• Materials Science
• Non-Destructive Testing
• Ultrasonic Testing

Background:

• Surface roughness significantly impairs ultrasonic testing's ability to detect sub-wavelength flaws.
• Accurate detection of small defects is crucial for the integrity of materials like titanium alloys in industrial applications.

Purpose of the Study:

• To develop and validate a roughness-modified doubly-scattered response (DSR) model for enhanced ultrasonic flaw detection on rough surfaces.
• To improve the segmentation of sub-wavelength flaws in two-phase Ti-6Al-4V using C-scan imaging.

Main Methods:

• A roughness-modified doubly-scattered response (DSR) model was developed.
• Extreme value statistics were employed to determine confidence bounds for grain noise.
• These bounds were utilized as a time-dependent threshold for flaw segmentation in ultrasonic C-scan images.

Main Results:

• The developed method successfully distinguished sub-wavelength flaws (approximately 1/3 wavelength) in two-phase Ti-6Al-4V with varying surface roughness.
• Validation was performed on three manufactured Ti-6Al-4V samples with different surface roughness levels.

Conclusions:

• The roughness-modified DSR model effectively enhances ultrasonic flaw detection on rough surfaces.
• The method shows promise for practical industrial applications in non-destructive testing of titanium alloys.