Defect intelligent identification in resistance spot welding ultrasonic detection based on wavelet packet and neural network

In this paper, ultrasonic echo signals of four kinds of stainless steel resistance spot welds, namely failed weld, stick weld, good weld, and defective weld with gas pore, are analyzed in the time domain, frequency domain, and time-frequency domain based on wavelet packet transform. Fourteen ultrasonic characteristic signals which can reflect the different kinds of spot welds are extracted and can be automatically identified and classified by back-propagation (BP) neural network. The method of this paper can realize the intelligent identification of resistance spot welding defects, and the feasibility of this method has been verified in the experiment.