Guided waves based debonding classification in lap-joints using modified Fisher discriminant criterion

Abstract

In this paper, a modified fisher discriminant criterion is used to identify and rank damage sensitive features for debonding classification. For this purpose, the analysis of the correlation between features (ACF) based on Pearson correlation coefficient and the Fisher discriminant ratio (FDR) criterion were combined to select the most relevant features. The debondings classification was evaluated in a multiclass classification by considering three different classes of damage and one class of undamaged. The nondestructive inspection was performed in a composite-adhesive-composite lap-joint using guided Lamb wave testing with angle beam transducers mounted in a pitch-catch configuration. From the collected data, twelve features were extracted by using statistical functions and signal processing techniques. From the extracted features, the most damage sensitive features were selected based on the proposed method (ACF and FDR) and the results were compared using the conventional FDR method. For three different classifiers, the feature selection strategies were tested and their performance evaluated using the metrics: accuracy, precision, recall and F1 score. For the dataset collected in this study, the results support that the proposed method yields an improvement of the performance of the classifiers in comparison with the use of the conventional FDR-based feature selection.