Barker Code Thermography Inspection and Reliability Evaluation for CFRP Defects Detection

Abstract

In this paper, Barker code thermography is used to detect delamination defects incarbon fiber reinforced polymer (CFRP). Detection capability of this imaging technique is assessed through quantitative analysis of the signal-to-noise ratio (SNR) in the acquired feature images. An infrared thermography experimental system has been developed to implement the Barker code modulation for pulse compression excitation signals. A reference CFRP specimen with different diameter-to-depth ratio defects was tested. Three thermal wave imaging algorithms, namely principal component analysis (PCA), fitting correlation coefficient (FCC) and total harmonic distortion (THD), have been applied to process the acquired infrared images sequences, and determine SNR values characterizing the processing results. The experimental results show that Barker code thermography has the advantages of simple modulation and easy implementation. Also, the PCA algorithm outperforms the techniques of FCC and THD in terms of the SNR to enable effective identification defects in CFRP.