Anomaly Detection of Marine Diesel Engines: A Novel Approach using Transformer Neural Networks for Reconstruction and Residual Analysis

Anomaly Detection of Marine Diesel Engines: A Novel Approach using Transformer Neural Networks for Reconstruction and Residual Analysis

This paper proposes an unsupervised approach for anomaly detection in marine diesel engines using a transformer neural network based AutoEncoder (TAE) and residual analysis with Sequential Probability Ratio Test (SPRT) and Sum of Squares of Normalized Residuals (SSNR). This approach effectively capt...

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Bibliographic Details
Main Authors: Qin Liang, Erik Vanem, Knut Erik Knutsen, Vilmar Æsøy, Houxiang Zhang
Format: Article
Language:English
Published: The Prognostics and Health Management Society 2024-10-01
Series:International Journal of Prognostics and Health Management
Subjects:
marine diesel engine
phm
deep learning
machine learning
Online Access:https://papers.phmsociety.org/index.php/ijphm/article/view/3853
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