An automated shearography system for cylindrical surface inspection

A shearography system has been developed to inspect the external heat proof coating bonded to a cylinder. The system consists of a shearography device integrated with thermal excitation, a mechanical translation and rotation device, and a central control unit. The translation and the rotation are driven with 2 servo motors. The combination of these two movements enables full inspection of the entire surface of the cylinder. The inspection sequence is automatically scheduled by inputting the geometry of the sample. Artificial intelligence (AI) has been first introduced to aid defect recognition from the resulted phase shifting fringe patterns. A recognition algorithm based on deep learning has been developed using Faster R-CNN model for recognition of bonding defects. By training the system using typical butterfly fringe patterns which are captured from bonding samples, the system can accurately identify the bonding defects on the cylindrical surface at a high success rate. (C) 2018 Elsevier Ltd. All rights reserved.