Research on the fusion imaging method of sign coherence and time reversal for Lamb wave sparse array

• Published in: Ultrasonics 2025-01, Vol.145, p.107489, Article 107489
• Main Authors: Sun, Liu-Jia, Han, Qing-Bang, Yin, Cheng, Jin, Qi-Lin, Ge, Kao
• Format: Article
• Language: English
• Subjects: Amplitude-phase estimation; Lamb waves; SCF-TR; Sparse array; Super-resolution imaging
• ISSN: 0041-624X; 1874-9968; 1874-9968
• DOI: 10.1016/j.ultras.2024.107489

•Realized super-resolution imaging of asymmetric multi blind hole defects in aluminum plates.•The design of a sparse optimization algorithm enhances imaging efficiency.•Improved the quality and efficiency of time reversal imaging. Time-reversal imaging struggles to detect plate-like structures due to interference from Lamb wave mode conversion and the processing demands, leading to less effective outcomes. This paper proposes a sign coherence factor and time reversal fusion (SCF-TR) imaging method based on amplitude and phase estimation. This method removes the coherence of array signals during signal reversal and refocusing. It reintroduces the sign coherence component to reduce interference from non-target scattered waves and partially overcome the constraints imposed by the Rayleigh criterion. The method allows imaging at a resolution smaller than the wavelength of Lamb and enhances the quality of the resulting images. In addition, a sparse array design utilizing the White Shark Optimisation Algorithm (WSO) is proposed to streamline the SCF-TR calculation process. This design utilizes sparse full matrix data to improve imaging efficiency. The experimental results show that for single blind hole defects, the SCF-TR method improves the array performance metrics and signal-to-noise ratio by 22.46% and 42.50%, respectively, compared to the TR method. For multiple asymmetric blind hole defects, when the defect size exceeds the resolution threshold, SCF-TR accurately reflects the position and morphology of defects smaller than the wavelength. When the defect size is below the resolution threshold, SCF-TR achieves super-resolution imaging. The sparse array designed using the White Shark Optimization algorithm demonstrates good sidelobe characteristics, effectively reducing sidelobe noise without reducing the array aperture. Moreover, the SCF-TR imaging time is reduced by approximately half while maintaining imaging accuracy.