TTSNet: Transformer–Temporal Convolutional Network–Self-Attention with Feature Fusion for Prediction of Remaining Useful Life of Aircraft Engines

TTSNet: Transformer–Temporal Convolutional Network–Self-Attention with Feature Fusion for Prediction of Remaining Useful Life of Aircraft Engines

Accurately predicting the remaining useful life (RUL) is crucial for ensuring the safety and reliability of aircraft engine operation. However, aircraft engines operate in harsh conditions, with the characteristics of high speed, high temperature, and high load, resulting in high-dimensional and noi...

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Bibliographic Details
Main Authors: Zhaofei Li, Shilin Luo, Haiqing Liu, Chaobin Tang, Jianguo Miao
Format: Article
Language:English
Published: MDPI AG 2025-01-01
Series:Sensors
Subjects:
TCN
transformer
self-attention
aircraft engines
RUL prediction
Online Access:https://www.mdpi.com/1424-8220/25/2/432
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