Robotic impact-acoustics system for tile-wall bonding integrity inspection

Impact acoustic is an effective non-destructive evaluation (NDE) method for many applications especially for inspecting the bonding quality of mosaic tile-walls. However, the audio noise can affect the power spectrum density (PSD) distribution of an acquired signal seriously. So, the traditional method of using PSD as the main identification tool is not sufficient. This paper proposes an evaluation method based on wavelet packet decomposition (WPD). Using WPD, the PSD of the signal is allocated into certain component fields. Investigation on the component PSD indicates it can reveal the bonding quality even in a noisy environment. An artificial neural network (ANN) is chosen as a classifier to simplify the evaluation system and makes it more effective and efficient. The performance of the proposed approach is evaluated experimentally. It is verified that this WPD approach can be applied to impact acoustic method to enhance its evaluation capability in a noisy environment. For practical implementation, an automatic gondola based climbing robot, called WICBOT, is being developed. To reduce the difficulty in handling large amount of cables, ZigBee and Bluetooth wireless network are used to transmit the inspection results and sample data from the climbing robot to the ground station.