Detection and classification of welding defects in friction-welded joints using ultrasonic NDT methods

The weak bonding defect, which is a special defect occurring in solid-phase welded joints, cannot be detected effectively with normal ultrasonic testing methods used in industry. The signal reflected by such a defect is so small that it is submerged by the noise. This weak bonding defect is, however, a very dangerous defect and usually sampling destructive testing methods are adopted in the factories to detect it. In this paper, numerical signal analysis methods are used in the time-frequency domain to detect the weak bonding defect as well as other defects in friction welded joints. The dyadic wavelet transform method and singularity analysis method are used to separate the weak reflected signal from the defect from the noise. Weld quality, weak bonding defects and lack-of-bonding defects are detected and evaluated, based on characteristics analysis. The results show that the weak bonding defect can be detected effectively using a numerical signal analysis method, and the lack-of-bonding defect in the presence of various surface conditions, can also be recognised. Moreover, more than one defect in the same welding interface can be detected, based on the characteristics obtained by using a fuzzy logic analysis method.