This study applies the phase coherence imaging (PCI) post-processing algorithm to the ultrasonic phased array total focusing method (TFM) to effectively improve the low signal-to-noise ratio (SNR) level of TFM imaging. Initially, a carbon steel block model was established in COMSOL software to obtain full matrix simulation data. Subsequently, by using MATLAB, circular coherence factor (CCF), sign coherence factor (SCF), sign coherence weighting (SCW), and instantaneous phase coherence factor (IPCF) were constructed to characterize the phase coherence of signals at each point in the full matrix. Following this, these factors were combined with the TFM imaging algorithm to compare their noise reduction and artifact removal effects, through which the optimal phase coherence factor was obtained. Furthermore, experimental validation was peformed, and the optimal phase coherence factor was further enhanced in dB amplitude to form the TFM-CCF-dB imaging algorithm. The results show that TFM-CCF-dB can eliminate image noise and artifacts while enhancing the amplitude of defect signals, thus improving the imaging SNR and detection accuracy.
