Towards automatic defect detection in carbon fiber composites using active thermography

Abstract

Major advances have occurred in the field of non-destructive testing based on active thermography. However, active thermography has yet to be integrated in the automation of a production line for defect detection. There is a general agreement about stimulation and post-processing methods that improve defect detectability, however, a general framework for automatic defect detection has not been defined. This work presents a general framework towards automatic defect detection using active thermography. The proposed framework has four steps: acquisition, enhancement, filtering and segmentation. The most appropriate methods are selected for each step. Finally, the performance of the proposed method is evaluated using a real carbon fiber composite.