A Trend Forecasting Method for the Vibration Signals of Aircraft Engines Combining Enhanced Slice-Level Adaptive Normalization Using Long Short-Term Memory Under Multi-Operating Conditions

A Trend Forecasting Method for the Vibration Signals of Aircraft Engines Combining Enhanced Slice-Level Adaptive Normalization Using Long Short-Term Memory Under Multi-Operating Conditions

Trend forecasting and early anomaly warnings are important for avoiding aircraft engine failures or accidents. This study proposes a trend forecasting method based on enhanced Slice-level Adaptive Normalization (SAN) using a Long Short-Term Memory (LSTM) neural network under multi-operating conditio...

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Bibliographic Details
Main Authors: Jiantao Lu, Kuangzhi Yang, Peng Zhang, Wei Wu, Shunming Li
Format: Article
Language:English
Published: MDPI AG 2025-03-01
Series:Sensors
Subjects:
trend forecasting
<i>L</i><sub>1</sub> filtering
enhanced SAN
LSTM
multi-operating condition
Online Access:https://www.mdpi.com/1424-8220/25/7/2066
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