Application of Probabilistic Neural Network in Bonding Quality Ultrasonic Detection of Composite Material

Abstract The bonding quality of composite plate material is detected by ultrasonic waves. Taking ultrasonic detection signal as the research object, the theory of detection method pulse reflection echo method is comprehensively analyzed. Surveying the information carried by the echo signal of detection ultrasonic waves, the signal energy, signal duration and the product of singular wave peak value and quantity are regarded as characteristic values. According to the Probabilistic Neural Network sorting algorithm, the composite plate material bonding quality is divided by the qualitative judgment. Experimental results show that compared with Radial Basis Function Neural Network, the algorithm is very exact for recognition of bonding quality, and is more suitable for the classification of discrete data.