Health assessment of marine gas turbine propulsion system under cross-working conditions based on transfer learning

Congao Tan; Shijie Shi

doi:10.1117/12.3014466

9 January 2024 Health assessment of marine gas turbine propulsion system under cross-working conditions based on transfer learning

Congao Tan, Shijie Shi

Author Affiliations +

Proceedings Volume 12969, International Conference on Algorithm, Imaging Processing, and Machine Vision (AIPMV 2023); 1296923 (2024) https://doi.org/10.1117/12.3014466
Event: International Conference on Algorithm, Imaging Processing and Machine Vision (AIPMV 2023), 2023, Qingdao, China

Abstract

The marine gas turbine propulsion system generally works in a healthy state, and the samples collected by the monitoring system are characterized by more normal samples and fewer fault samples. Aiming at the problem of lack of fault samples faced by data-driven fault diagnosis methods, a cross-working condition fault diagnosis model is proposed by using transfer learning to reduce the dependence of data-driven methods on fault samples. The proposed method was experimentally validated by using a real-ship-validated dataset. Compared with traditional methods, the proposed method can achieve cross-working condition fault diagnosis with fewer fault samples.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Congao Tan and Shijie Shi "Health assessment of marine gas turbine propulsion system under cross-working conditions based on transfer learning", Proc. SPIE 12969, International Conference on Algorithm, Imaging Processing, and Machine Vision (AIPMV 2023), 1296923 (9 January 2024); https://doi.org/10.1117/12.3014466

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available