Fault Signal Emulation of Marine Turbo-Rotating Systems Based on Rotor-Gear Dynamic Interaction Modeling

Rotating machinery is essential in various industrial fields, and growing demands for high performance under harsh operating conditions have heightened interest in fault diagnosis and prognostic technologies. However, a major challenge in fault diagnosis research lies in the scarcity of data, primar...

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Bibliographic Details
Main Authors: Seong Hyeon Kim, Hyun Min Song, Se Hyeon Jeong, Won Joon Lee, Sun Je Kim
Format: Article
Language:English
Published: MDPI AG 2025-07-01
Series:Journal of Marine Science and Engineering
Subjects:
Online Access:https://www.mdpi.com/2077-1312/13/7/1321
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Summary:Rotating machinery is essential in various industrial fields, and growing demands for high performance under harsh operating conditions have heightened interest in fault diagnosis and prognostic technologies. However, a major challenge in fault diagnosis research lies in the scarcity of data, primarily due to the inability to deliberately introduce faults into machines during actual operation. In this study, a physical model is proposed to realistically simulate the system behavior of a ship’s turbo-rotating machinery by coupling the torsional and lateral vibrations of the rotor. While previous studies employed simplified single-shaft models, the proposed model adopted gear mesh interactions to reflect the coupling behavior between shafts. Furthermore, the time-domain response of the system is analyzed through state-space transformation. The proposed model was applied to simulate imbalance and gear teeth damage conditions that may occur in marine turbo-rotating systems and the results were compared with those under normal operating conditions. The analysis confirmed that the model effectively reproduces fault-induced dynamic characteristics. By enabling rapid implementation of various fault conditions and efficient data acquisition data, the proposed model is expected to contribute to enhancing the reliability of fault diagnosis and prognostic research.
ISSN:2077-1312