Overview and Analysis of Publicly Available Degradation Data Sets for Tasks within Prognostics and Health Management

The effectiveness of Prognostic and Health Management (PHM) methods relies on degradation data that reflect the health of engineering systems over time. In particular, publicly available degradation data sets are of high value. Despite their importance, these data sets are rarely discussed comprehensively in the literature, with existing overviews often limited in scope and detail. As a result, the search process for suitable data sets is often very time-consuming for users of PHM methods. Therefore, this work provides a comprehensive overview of 98 publicly available degradation data sets and conducts a novel, detailed, PHM-specific analysis. In order to carry out the analysis, a taxonomy is developed to categorize and classify the data sets based on defined PHM-specific aspects. The resulting taxonomy classifies the data sets across 38 applications in 11 domains. The analysis provides a comprehensive overview and entry point for selecting and using the available data sets. It shows that almost half of the data sets are from the domains of electrical and mechanical components, with battery and bearing applications being the most common. However, the analysis also reveals that the number of data sets is limited for many applications.

Keywords: PHM, Prognostics and health management, Degradation data set, Data set overview, Degradation signal, Fault detection, Diagnosis, Prognosis.