Guided Waves Benchmark Dataset and Classifier Comparison

The guided-wave-based damage detection methodology is a well-established branch of Structural Health Monitoring. There are, however, many different approaches to processing and interpretation of signals acquired using guided waves. This paper presents the results of the SYPIN project in which a large database acquired in a diverse set of experiments was assembled. The experiments included static and variable environmental conditions, composite and metallic specimens of simple and complex geometries. The set includes, in particular, results of experiments on real-life aircraft specimens. This dataset was then used to benchmark several damage detection and quantification methodologies, including various classifiers and feature extraction methods. The performance of the methods is evaluated in a series of experiments, including knowledge transfer between different specimens. The paper presents the results of this research and provides a brief description of the dataset, which is made available for the scientific community’s use.