A Method for Constructing Health Indicators of the Engine Bleed Air System Using Multi-Level Feature Extraction

• Published in: Aerospace Vol. 10; no. 7; p. 645
• Main Authors: Duan, Zhaobin, Cao, Xidan, Hu, Fangyu, Wang, Peng, Chen, Xi, Dong, Lei
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.07.2023
• Subjects: Aircraft industry; Airlines; Algorithms; Bleeding; Commercial aircraft; Compressed air; Deep learning; engine bleed air system; Fault diagnosis; Feature extraction; Health; health indicators; Indicators; Machine learning; Methods; multi-level feature extraction; Neural networks; Pneumatics; Principal components analysis; QAR; RDAE; System effectiveness; Unsupervised learning; United States; China

Traditional methods are unable to effectively assess the health status of engine bleed air systems. To address the limitation, this paper proposes a methodology for constructing health indicators using multi-level feature extraction. First, this approach involves data-level feature extraction from Q...