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Picosecond laser ultrasonic imaging detection of near-surface micro defects using PCS and SAFT algorithm
Kangwen Huang1, Xiaokai Wang1, Shutong Dai1
1Hubei Key Laboratory of Advanced Technology for Automotive Components, Wuhan University of Technology, Wuhan 430070, China; Hubei Collaborative Innovation Center for Automotive Components Technology, Wuhan University of Technology, Wuhan 430070, China; School of Automotive Engineering, Wuhan University of Technology, Wuhan 430070, China.
This study introduces laser ultrasound for detecting tiny, near-surface defects, achieving high resolution. A novel imaging algorithm significantly improves signal quality compared to traditional methods, enhancing product quality assessment.
Area of Science:
- Materials Science
- Nondestructive Testing
- Photonics
Background:
- Effective detection of near-surface microdefects remains a challenge in ultrasonic inspection.
- Laser ultrasound offers high resolution and sensitivity for microdefect detection.
Purpose of the Study:
- To investigate the characteristics of picosecond laser ultrasound for microdefect detection.
- To analyze the interaction between microdefects and ultrasonic waves.
- To develop an advanced imaging algorithm for improved defect detection.
Main Methods:
- Utilized picosecond pulsed laser to excite ultrasonic waves in samples with microdefects.
- Employed an optical interferometer for ultrasonic wave detection.
- Developed and applied a defect imaging algorithm combining principal component subtraction (PCS) and synthetic aperture focusing technique (SAFT).
Main Results:
- Successfully detected near-surface microdefects with 0.13 mm diameters and depths ranging from 0.3 mm to 2 mm.
- The proposed PCS-SAFT algorithm effectively suppressed blind areas and artifacts from Rayleigh (R)-wave interference.
- Achieved a 25.57 dB average signal-to-noise ratio (SNR) increase compared to conventional total focusing method (TFM).
Conclusions:
- Picosecond laser ultrasound is a viable technology for detecting near-surface microdefects.
- The PCS-SAFT algorithm enhances defect imaging performance and signal quality.
- This research contributes to improved quality assessment in manufacturing and service processes.
