Abstract:

A system based on acoustic resonance was developed for eggshell crack detection. It was achieved by analysis of the acoustic frequency response of eggshell excited with a light mechanical. Least mean square (LMS) adaptive filtering were attempted to remove the noise from the response signal. Some characteristics were extracted from excitation resonant frequency and served as input vectors of discrimination model. Back propagation artificial neural network (BP-ANN) model was employed to discriminate intact eggs and cracked eggs. This method allows a crack detection level of 97% in calibration and prediction set respectively. This work shows that acoustic resonance system combined with adaptive filters has a significant potential in cracked eggs detection.

Key words: egg, crack, acoustic resonance, normalized least mean square (NLMS), back propagation artificial neural network (BP-ANN)