Research on defect quantification technique of Sparse array Total focusing method imaging based on Coherence factor weighting

Additive manufacturing technology is widely used in key components in the aerospace field due to its high manufacturing freedom and high precision. However, in the process of internal quality inspection of products, the signal attenuation caused by printing methods and materials brings certain challenges to the identification and quantification of defects. Total focusing method (TFM) is adopted to exploit FMC data and form an image where all pixels are focused in transmission and reception. The FMC–TFM approach is as highly accepted as the gold standard in ultrasonic imaging improve detection sensitivity and image resolution. However, the computational cost of TFM is substantial because it mainly operates in the time domain. In view of the above problems, this paper combines simulation and experimental verification, uses sparse matrix (SMC) set to carry out SMC-TFM imaging, and uses coherence factor (CF) weighted processing algorithm to enhance the SMC-TFM image and gets the SMC-TFM-CF image. On this basis, the quantitative characterization of defects of different sizes and orientations is realized, which can meet the needs of practical engineering.