Degradation Modeling and Remaining Useful Life Prediction of Aircraft Engines Using Ensemble Learning
Degradation Modeling and Remaining Useful Life Prediction of Aircraft Engines Using Ensemble Learning is a scholarly work, published in 2018 in ''Journal of Engineering for Gas Turbines and Power''. The main subjects of the publication include materials science, random forest, particle swarm optimization, data mining, artificial intelligence, ensemble learning, biological robustness, artificial neural network, support vector machine, fault detection and isolation, prognostics, diagnosis, machine learning, computer science, and engineering. The objective of this study is to introduce an ensemble learning-based prognostic approach to modeling an exponential degradation process due to wear as well as predicting the RUL of aircraft engines.