非線形モデルに基づくロバストフィルタを用いたジェットエンジンのヘルスモニタリング

• Published in: Shisutemu Seigyo Jouhou Gakkai rombunshi Vol. 29; no. 8; pp. 337 - 345
• Main Authors: 垣内, 大紀, 中村, 恵子, 木村, 麻衣, 足立, 修一, 小野, 雅裕, 若林, 優一, 木下, 萌, 佐藤, 諒
• Format: Journal Article
• Language: Japanese
• Published: Kyoto 一般社団法人 システム制御情報学会 2016; Japan Science and Technology Agency
• Subjects: Aerospace engines; Computer simulation; Extended Kalman filter; Fault detection; Gas turbine engines; Health; Jacobians; Jet engines; Kalman filters; Linearization; Space shuttle; State estimation
• ISSN: 1342-5668; 2185-811X
• DOI: 10.5687/iscie.29.337

We develop a novel jet engine health monitoring method using a high-fidelity, physics-based simulation model. In jet engine health monitoring, fault detection with a state estimation is frequently carried out. However, a challenge for a filtering-based health monitoring method with a high-fidelity model is the difficulty to analytically obtain the Jacobians, which is required for the extended Kalman filter. Our approach is to derive a linearized model a priori at a fixed operation point, and use a robust filter method to guarantee a reliable health monitoring over a wide range of operation points despite the linearization errors. We validate the proposed method by extensive simulations.