A method based on the one-dimensional local binary pattern (1-D LBP) algorithm to extract features of ultrasonic defect signals and perform multi-class defect classification was proposed. The ultrasonic defect echo signals were first decomposed into wavelet coefficients by the wavelet packet decomposition. The 1-D LBP algorithm was employed to extract LBP features of components at low and high frequencies, respectively. Subsequently, these LBP statistical feature sets were regarded as feature vectors of defect classification. Weld defects were ...
