Özçelik, Ahmet DevletÖktem, Ahmet Sinan2024-09-112024-09-112024978-303150919-31865-0929https://doi.org/10.1007/978-3-031-50920-9_19https://hdl.handle.net/11363/83972nd International Conference on Advanced Engineering, Technology and Applications, ICAETA 2023 -- 10 March 2023 through 11 March 2023 -- Istanbul -- 305999This study uses machine learning methods to find deterioration in turbomachine parts. In turbomachines, damage control procedures are carried out at specific times. Even though these checks take a while, if there is no damage, the components won’t be replaced, and it is not anticipated that they will be rechecked until the following control or an unforeseen incident. For this situation, a machine learning algorithm has been developed and 96% accuracy was obtained for overall components. © 2024, The Author(s), under exclusive license to Springer Nature Switzerland AG.eninfo:eu-repo/semantics/closedAccessMachine Learning; Predictive Maintenance; Turbo MachineryConference Object1983 CCIS24225310.1007/978-3-031-50920-9_192-s2.0-85180808150Q4