AN ULTRASONIC TIME-OF-FLIGHT EXTRACTION ALGORITHM BASED ON BLIND SOURCE SEPARATION IN THE PRESENCE OF NON-GAUSSIAN CO-FREQUENCY NOISE

Ultrasonic nondestructive stress testing supports the manufacture of precision equipment. Extracting the time-of-flight (TOF) of an ultrasonic echo signal is crucial for stress detection. However, the co-frequency noise, which is inevitably contained in the echo signal, extremely influences the accurate determination of TOF. This work proposes a novel TOF extraction method to address this problem. The proposed method firstly adds high-frequency signal, and a low-frequency signal into the ultrasonic echo signal. Then, the Co-T algorithm is applied to calculate the TOF by evaluating the minimums of the auto-correlation results of the signals, which are separated by independent component analysis algorithm (FastICA). The proposed method is demonstrably superior to the prevailing the Hilbert and the wavelet thresholding algorithms. Experiments verify the Co-T algorithm's efficacy and accuracy in retrieving TOF from signals in co-frequency noise environments.