Ultrasonic Anti-counterfeiting Identification for Metal Material Based on Wavelet Packet Transform

Three kinds of metal materials with different composition and three kinds of metal materials with similar composition are taken for samples in this work, and the 10 MHz ultrasonic scattering signal in the samples of the materials was extracted. The anti-counterfeiting features in the scattering signal can be got by the wavelet packet transform. The genetic algorithm was used to optimize BP neural network as classifier. Results show that the metal materials with different composition and the metal materials with similar composition can be identified successfully. Compared with the similar composition of metal materials without heat treatment, the heat treated ones are easier to be identified. Also this method can be used in the anti-counterfeiting identification of unknown metal, and it has therefore a certain practicality.