Print Email Facebook Twitter An Adaptive Framework For Remaining Useful Life Predictions Of Aircraft Systems Title An Adaptive Framework For Remaining Useful Life Predictions Of Aircraft Systems Author Bieber, M.T. (TU Delft Air Transport & Operations) Verhagen, W.J.C. (Royal Melbourne Institute of Technology University) Santos, Bruno F. (TU Delft Air Transport & Operations) Date 2021 Abstract Prognostics for condition-based maintenance does not only consist of prognostic algorithms but also involves steps such as data pre-processing, feature extraction, and feature selection, all of which contribute to the quality of the remaining useful life estimation. This process requires a lot of expertise and technical knowledge, which for many application systems is neither feasible nor affordable. In this paper, therefore, we present a generic framework with the capability to automatically choose the optimal settings for prognostics, given a specific data set. The framework consists of two phases. In the first one, a genetic algorithm optimizes the choice of methodologies together with hyperparameter settings for the feature extraction, feature selection, and prognostic algorithm selection. In the second phase, the identified settings define the prognostic setup, which in turn is used to train the model for remaining useful life estimation. This framework is then applied to a simulated aircraft engine data set. The first results show that remaining useful life estimates are comparable to the values obtained using established prognostic algorithms on the same data set. In addition, the framework is applied to estimate the remaining useful life of real aircraft systems. Results on underlying data sets suggest that the generic prognostic framework can easily and quickly be adapted to various systems. In further consequence, such a generic framework offers a way to assess the feasibility of prognostics for systems depending on the underlying existing data sets. To reference this document use: http://resolver.tudelft.nl/uuid:5fa21221-a5a2-4215-b288-9288d0f03a8c ISBN 978-1-936263-34-9 Source Proceedings of the 6th European Conference of the Prognostics and Health Management Society 2021 Event 6th European Conference of the prognostics and Health Management Society, 2021-06-28 → 2021-07-02, virtual event Part of collection Institutional Repository Document type conference paper Rights © 2021 M.T. Bieber, W.J.C. Verhagen, Bruno F. Santos Files PDF 2868_Document_Upload_9163 ... 210702.pdf 609.74 KB Close viewer /islandora/object/uuid:5fa21221-a5a2-4215-b288-9288d0f03a8c/datastream/OBJ/view