Nowadays, breakthrough composite technologies are intensifying the complexity of structural components every day and assuring the structural integrity is becoming more essential, thus creating challenges for developing a cost effective and reliable non-destructive evaluation (NDE) technique. As conventional NDE techniques usually require expensive equipments, trained experts and out-of-service period, such techniques may be inadequate for autonomous online health monitoring of structures. In this study, a relatively new technique known as electromechanical impedance (EMI) technique is combined with a neural network technique to predict the damaged areas on a composite plate. Regardless of the advantages such as low cost, robustness, simplicity and online possibilities, this technique still has various problems to be solved. For one, locating a damaged area can be extremely difficult as this non-model based technique heavily relies on the variations in the impedance signatures. The results show that the non-homogenous property is an advantage for the study, successfully identifying the damage location for the prepared test specimen with an acceptable performance. (C) 2013 Elsevier Ltd. All rights reserved.